Search results for: deformable objects

Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

Procedia PDF Downloads 78

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Dmitry Lukyanov, Sergey Shevchenko, Alexander Kukaev

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Modern MEMS gyroscopes have strengthened their position in motion control systems and have led to the creation of tactical grade sensors (better than 15 deg/h). This was achieved by virtue of the success in micro- and nanotechnology development, cooperation among international experts and the experience gained in the mass production of MEMS gyros. This production is knowledge-intensive, often unique and, therefore, difficult to develop, especially due to the use of 3D-technology. The latter is usually associated with manufacturing of inertial masses and their elastic suspension, which determines the vibration and shock resistance of gyros. Today, consumers developing highly dynamic objects or objects working under extreme conditions require the gyro shock resistance of up to 65 000 g and the measurement range of more than 10 000 deg/s. Such characteristics can be achieved by solid-state gyroscopes (SSG) without inertial masses or elastic suspensions, which, for example, can be constructed with molecular kinetics of bulk or surface acoustic waves (SAW). Excellent effectiveness of this sensors production and a high level of structural integration provides basis for increased accuracy, size reduction and significant drop in total production costs. Existing principles of SAW-based sensors are based on the theory of SAW propagation in rotating coordinate systems. A short introduction to the theory of a gyroscopic (Coriolis) effect in SAW is provided in the report. Nowadays more and more applications require passive and wireless sensors. SAW-based gyros provide an opportunity to create one. Several design concepts incorporating reflective delay lines were proposed in recent years, but faced some criticism. Still, the concept is promising and is being of interest in St. Petersburg Electrotechnical University. Several experimental models were developed and tested to find the minimal configuration of a passive and wireless SAW-based gyro. Structural schemes, potential characteristics and known limitations are stated in the report. Special attention is dedicated to a novel method of a FEM modeling with piezoelectric and gyroscopic effects simultaneously taken into account.

Keywords: FEM simulation, gyroscope, OOFELIE, surface acoustic wave, wireless sensing

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Authors: Shib Shankar Banerjeea, Andreas Ferya, Gert Heinricha, Amit Das

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Recently, the growing need for the development of soft robots consisting of highly deformable and compliance materials emerge from the serious limitations of conventional service robots. However, one of the main challenges of soft robotics is to develop such compliance materials, which facilitates the design of soft robotic structures and, simultaneously, controls the soft-body systems, like soft artificial muscles. Generally, silicone or acrylic-based elastomer composites are used for soft robotics. However, mechanical performance and long-term reliabilities of the functional parts (sensors, actuators, main body) of the robot made from these composite materials are inferior. This work will present the development and characterization of robust super-soft programmable elastomeric materials from crosslinked natural rubber that can serve as touch and strain sensors for soft robotic arms with very high elastic properties and strain, while the modulus is altered in the kilopascal range. Our results suggest that such soft natural programmable elastomers can be promising materials and can replace conventional silicone-based elastomer for soft robotics applications.

Keywords: elastomers, soft materials, natural rubber, sensors

Procedia PDF Downloads 154

Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

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Authors: A. A. Vasin, N. V. Klassen, A. M. Likhter

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Water suspensions of in-organic (metals and oxides) and organic nano-objects (chitozan and collagen) were subjected to the treatment of direct and alternative electrical fields. In addition to quasi-periodical spatial patterning resonance-like performance of spatial distributions of these suspensions has been found at low frequencies of alternating electrical field. These resonances are explained as the result of creation of equilibrium states of groups of charged nano-objects with opposite signs of charges at the interparticle distances where the forces of Coulomb attraction are compensated by the repulsion forces induced by relatively negative polarization of hydrated regions surrounding the nanoparticles with respect to pure water. The low frequencies of these resonances are explained by comparatively big distances between the particles and their big masses with t\respect to masses of atoms constituting molecules with high resonance frequencies. These new resonances open a new approach to detailed modeling and understanding of mechanisms of the influence of electrical fields on the functioning of internal organs of living organisms at the level of cells and neurons.

Keywords: bio-polymers, chitosan, collagen, nanoparticles, coulomb attraction, polarization repulsion, periodical patterning, electrical low frequency resonances, transformations

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Authors: Douglas Rossi Ramos

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The current digital conjuncture, called by some authors as 'Internet of Things' (IoT), 'Web 2.0' or even 'Web 3.0', consists of a network that encompasses any communication of objects and entities, such as data, information, technologies, and people. At this juncture, especially characterized by an "object socialization," communication can no longer be represented as a simple informational flow of messages from a sender, crossing a channel or medium, reaching a receiver. The idea of communication must, therefore, be thought of more broadly in which it is possible to analyze the process communicative from interactions between humans and nonhumans. To think about this complexity, a communicative process that encompasses both humans and other beings or entities communicating (objects and things), it is necessary to constitute a new epistemology of communication to rethink concepts and notions commonly attributed to humans such as 'memory.' This research aims to contribute to this epistemological constitution from the discussion about the notion of memory according to the complex ontology of Henri Bergson. Among the results (the notion of memory in Bergson presents itself as a conceptual tool for the analysis of posthumanism and the anthropomorphic conjuncture of the new advent of digital), there was the need to think about an ontological memory, analyzed as a being itself (being itself of memory), as a strategy for understanding the forms of interaction and communication that constitute the new digital conjuncture, in which communicating beings or entities tend to interact with each other. Rethinking the idea of communication beyond the dimension of transmission in informative sequences paves the way for an ecological perspective of the digital dwelling condition.

Keywords: communication, digital, Henri Bergson, memory

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Authors: Chiung-Hui Chen

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With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity

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Authors: Tom Farrelly, Yvoonne Kavanagh, Tony Murphy

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In the last 20 years, Ireland has enjoyed an upsurge in the number of international students coming to avail of its well-regarded Higher Education system. While welcome, the influx of international students has posed a number of cultural, social and academic challenges for the Irish HE sector, both at institutional and individual lecturer level. Notwithstanding the challenge to the Irish HE sector, the difficulties that incoming students face needs to be acknowledged and addressed. For students who have never left their home country before the transition can be daunting even if they have not learned the customs and ways of the new country. In 2013, Ireland’s National Forum for the Advancement of Teaching and Learning in Higher Education invited submissions from interested parties to design and implement digital supports aimed at assisting students transitioning into or exiting higher education. Five colleges—the Institute of Technology, Tralee; University College Cork, Institute of Technology, Carlow; Cork Institute of Technology and Waterford Institute of Technology—collectively known as the Southern Cluster, were granted funding to research and develop digital objects to support international students' transition into the Irish higher education system. One of the key fundamentals of this project was its strong commitment to incorporating the student voice to help inform the design of the digital objects. The primary research method used to ascertain student views was the circulation of an online questionnaire using SurveyMonkey to existing international students in each of the five participant colleges. The questionnaire sought to examine the experiences and opinions of the students in relation to three main aspects of their living and studying in Ireland (hence the name of the project LiveAndLearnInIreland) (1) the academic environment (2) the social aspects of living in Ireland and (3) the practical aspects of living in Ireland. The response to the survey (n=573), revealed a number of sometimes surprising issues and themes for the digital objects to address. The research, therefore, offers insight into the types of concerns that any college, whether in Ireland or further afield, needs to take into consideration, if it is to genuinely assist what can be a difficult transition for the international student. That said, while there are a number of themes that emerged that have international implications there are other themes that have a particular resonance for the Irish HE sector.

Keywords: international, transition, support, inclusion

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Hosamuddin Hamza

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The major concept of 4D printing is self-folding under thermal and humidity changes. This concept relies on understanding how the microstructures of 3D-printed models can undergo spontaneous shape transformation under thermal and moisture changes. The transformation mechanism could be achieved by mixing, in a controllable pattern, a number of materials within the printed model, each with known strain/shrinkage properties. 4D printing has a strong potential to be applied in dentistry as the technology could produce dynamic and adaptable materials to be used as functional objects in the oral environment under the continuously changing thermal and humidity conditions. The motion criteria could override the undesired dimensional changes, thermal instability, polymerization shrinkage and microleakage. 4D printing could produce restorative materials being self-adjusted spontaneously without further intervention from the dentist or patient; that is, the materials could be capable of fixing its failed portions, compensating for some lost tooth structure, while avoiding microleakage or overhangs at the margins. In prosthetic dentistry, 4D printing could provide an option to manage the influence of bone and soft tissue imbalance during mastication (and at rest) with high predictability of the type/direction of forces. It can also produce materials with better fitting and retention characteristics than conventional or 3D-printed materials. Nevertheless, it is important to highlight that 4D-printed objects, having dynamic properties, could provide some cushion as they undergo self-folding compensating for any thermal changes or mechanical forces such as traumatic forces.

Keywords: functional material, self-folding material, 3D printing, 4D printing

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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Authors: Wilson Bastos, Sigal G. Barsade

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Much of what happens in the marketplace revolves around the provision and consumption of goods. Recent research has advanced a useful categorization of these goods—as experiential versus material—and shown that, from the consumers’ perspective, experiences (e.g., a theater performance) are superior to objects (e.g., an electronic gadget) in offering various social and psychological benefits. A common finding in this growing research stream is that consumers gain more happiness from the experiences they have than the objects they own. By focusing solely on those acquiring the experiential or material goods (the consumers), prior research has remained silent regarding another important group of individuals—those providing the goods (the employees). Do employees whose jobs are primarily focused on offering consumers an experience (vs. object) also gain more happiness from their occupation? We report evidence from four experiments supporting an experiential-employee advantage. Further, we use mediation and moderation tests to unearth the mechanism responsible for this effect. Results reveal that work meaningfulness is the primary driver of the experiential-employee advantage. Overall, our findings suggest that employees find it more meaningful to provide people with an experience as compared to a material object, which in turn shapes the happiness they derive from their jobs. We expect this finding to have implications on human development, and to be of relevance to researchers and practitioners interested in how to advance human condition in the workplace.

Keywords: employee happiness, experiential versus material jobs, work meaningfulness

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Authors: Jaime Carpio-García, Elena Blanco-Fernández, Jorge Rodríguez-Hernández, Daniel Castro-Fresno

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Geosynthetic mechanical behavior vs temperature or vs aging has been widely studied independently during the last years, both in laboratory and in outdoor conditions. This paper studies this behavior deeper, considering that geosynthetics have to perform adequately at different outdoor temperatures once they have been subjected to a certain degree of aging, and also considering the different geosynthetic structures made of the same material. This combining effect has been not considered so far, and it is important to ensure the performance of geosynthetics, especially where high temperatures are expected. In order to fill this gap, six commercial geosynthetics with different internal structures made of polypropylene (PP), high density polyethylene (HDPE), bitumen and polyvinyl chloride (PVC), or even a combination of some of them have been mechanically tested at mild temperature (20ºC or 23ºC) and at warm temperature (45ºC) before and after specific exposition to air at standardized high temperature in order to simulate 25 years of aging due to oxidation. Besides, for 45ºC tests, an innovative heating system during test for high deformable specimens is proposed. The influence of the combining effect of aging, structure and temperature in the product behavior have been analyzed and discussed, concluding that internal structure is more influential than aging in the mechanical behavior of a geosynthetic versus temperature.

Keywords: geosynthetics, mechanical behavior, temperature, aging, internal structure

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Hussain Jiffry, Kypros Pilakoutas, Reyes Garcia Lopez

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This study examines the effect of tsunami loads on reinforced concrete (RC) frame buildings analytically. The impact of tsunami wave loads and waterborne objects are analyzed using a typical substandard full-scale two-story RC frame building tested as part of the EU-funded Ecoleader project. The building was subjected to shake table tests in bare condition and subsequently strengthened using Carbon Fiber Reinforced Polymers (CFRP) composites and retested. Numerical models of the building in both bare and CFRP-strengthened conditions are calibrated in DRAIN-3DX software to match the test results. To investigate the response of wave loads and impact forces, the numerical models are subjected to nonlinear dynamic analyses using force-time history input records. The analytical results are compared in terms of displacements at the floors and the 'impact point' of a boat. The results show that the roof displacement of the CFRP-strengthened building reduced by 63% when compared to the bare building. The results also indicate that strengthening only the mid-height of the impact column using CFRP is more efficient at reducing damage when compared to strengthening other parts of the column. Alternative solutions to mitigate damage due to tsunami loads are suggested.

Keywords: tsunami loads, hydrodynamic load, impact load, waterborne objects, RC buildings

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Authors: X. Laurent, M. A. Estevez, P. Mari-Beffa

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A focus of recent research is to understand the role of our own response goals in the selection of information that will be encoded in episodic memory. For example, if we respond to a target in the presence of distractors, an important aspect under study is whether the distractor and the target share a common response (compatible) or not (incompatible). Some studies have found that compatible objects tend to be groups together and stored in episodic memory, whereas others found that targets in the presence of incompatible distractors are remembered better. Our current research seems to support both views. We used a Tulving-based definition of episodic memory to differentiate memory from episodic and non-episodic traces. In this task, participants first had to classify a blue object as human or animal (target) which appeared in the presence of a green one (distractor) that could belong to the same category of the target (compatible), to the opposite (incompatible) or to an irrelevant one (neutral). Later they had to report the identity (What), location (Where) and time (When) of both target objects (which had been previously responded to) and distractors (which had been ignored). Episodic memory was inferred when the three scene properties (identity, location and time) were correct. The measure of non-episodic memory consisted of those trials in which the identity was correctly remembered, but not the location or time. Our results showed that episodic memory for compatible stimuli is significantly superior to incompatible ones. In sharp contrast, non-episodic measures found superior memory for targets in the presence of incompatible distractors. Our results demonstrate that response compatibility affects the encoding of episodic and non-episodic memory traces in different ways.

Keywords: episodic memory, action systems, compatible response, what-where-when task

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Authors: Wann-Yun Shieh, Hsin-Yi Kathy Cheng, Yan-Ying Ju, Yu-Chun Yu, Ya-Cheng Shieh

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Adolescents who have intellectual disabilities often demonstrate maladaptive behaviors in their daily activities due to either physical abnormalities or neurological disorders. These adolescents commonly struggle with their cognition and movement coordination when it comes to executing tasks such as throwing or catching objects smoothly, quickly, and gracefully, in contrast to their typically developing peers. Simply measuring movement time and distance doesn't provide a comprehensive view of their performance challenges. In this study, a ball-playing approach was proposed to assess the cognition and movement coordination of adolescents with intellectual disabilities using a smart ball equipped with an embedded inertial sensor. Four distinct ball games were specifically designed for this smart ball: two focusing on lower limb activities (dribbling along a straight line and navigating a zigzag path) and two centered around upper limb tasks (picking up and throwing and catching the ball). The cognition and movement coordination of 25 adolescents with intellectual disabilities (average age 18.36 ± 2.46 years) with that of 25 typically developing adolescents (average age 18.36 ± 0.49 years) were compared in these four tests. The results clearly revealed significant differences in the cognition and movement coordination between the adolescents with intellectual disabilities and the typically developing adolescents. These differences encompassed aspects such as movement speed, hand-eye coordination, and control over objects across all the tests conducted.

Keywords: cognition, intellectual disabilities, movement coordination, smart ball

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: M. Warburton

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Background: Case study examining hydrotherapy for a person with DSI. A 46 year-old lady completely deaf and blind post congenital rubella syndrome. Touch becomes the primary information gathering sense to optimise function in life. Communication is achieved via tactile finger spelling and signals onto her hand and skin. Hydrotherapy may provide a suitable mobility environment and somato-sensory input to people, and especially DSI persons. Buoyancy, warmth, hydrostatic pressure, viscosity and turbulence are elements of hydrotherapy that may offer a DSI person somato-sensory input to stimulate the mechanoreceptors, thermoreceptors and proprioceptors and offer a unique hydro-therapeutic environment. Purpose: The purpose of this case study was to establish what measurable benefits could be achieved from hydrotherapy with a DSI person. Methods: Hydrotherapy was provided for 8-weeks, 2 x week, 35-minute session duration. Pool temperature 32.5 degrees centigrade. Pool length 25-metres. Each session consisted of mobility encouragement and supervision, and activities to stimulate the somato-sensory system utilising aquatic properties of buoyancy, turbulence, viscosity, warmth and hydrostatic pressure. Somato-sensory activities focused on stimulating touch and tactile exploration including objects of various shape, size, weight, contour, texture, elasticity, pliability, softness and hardness. Outcomes were measured by the Goal Attainment Scale (GAS) and included mobility distance, attendance, and timed tactile responsiveness to varying objects. Results: Mobility distance and attendance exceeded baseline expectations. Timed tactile responsiveness to varying objects also changed positively from baseline. Average scale scores were 1.00 with an overall GAS t-score of 63.69. Conclusions: Hydrotherapy can be a quantifiable physio-therapeutic option for persons with DSI. It provides a relatively safe environment for mobility and allows the somato-sensory system to be fully engaged - important for the DSI population. Implications: Hydrotherapy can be a measurable therapeutic option for a DSI person. Physiotherapists should consider hydrotherapy for DSI people. Hydrotherapy can offer unique physical properties for the DSI population not available on land.

Keywords: chronic, disability, disease, rehabilitation

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Authors: Radek Richtr, Petr Paus

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The connection to the primal environment, living and growing nature is disappearing for most of the residents in urban core areas nowadays. Most of the residents perceive scattered green mass like more technical objects than sentient living organisms. The Arboretum is a type of application from the 'serious games' genre -it is a research experiment masked as a gaming environment. In used virtual and augmented reality environments, every city district is represented by central objects; Pillars created as a result of resident’s consensus. Every player can furthermore plant and grow virtual organic seeds everywhere he wants. Seeds sprout, and their form is determined by both players’ choice and nearest pillar. Every house, private rooms, and even workspace get their new living virtual avatar-connected 'residents' growing from player-planted seeds. Every room or workspace is transformed into (calming) nature scene, reflecting in some way both players and community spirit and together create a vicinity environment. The conceptual design phase of the project is crucial and allows for the identification of the fundamental problems through abstraction. The project that centers on wide community usage needs a clear and accessible interface. Simultaneously the conceptual design allows early sharing of project ideas and creating public concern. The paper discusses the current conceptual model of an Arboretum project (which is part of a whole widespread project) and its validation.

Keywords: augmented reality, conceptual design, mixed reality, social engineering

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Authors: Damian Islas

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Debates on realism in science concern two different questions: (I) whether the unobservable entities posited by theories can be known; and (II) whether any knowledge we have of them is objective or not. Question (I) arises from the doubt that since observation is the basis of all our factual knowledge, unobservable entities cannot be known. Question (II) arises from the doubt that since scientific representations are inextricably laden with the subjective, idiosyncratic, and a priori features of human cognition and scientific practice, they cannot convey any reliable information on how their objects are in themselves. A way of understanding scientific realism (SR) is through three lines of inquiry: ontological, semantic, and epistemological. Ontologically, scientific realism asserts the existence of a world independent of human mind. Semantically, scientific realism assumes that theoretical claims about reality show truth values and, thus, should be construed literally. Epistemologically, scientific realism believes that theoretical claims offer us knowledge of the world. Nowadays, the literature on scientific realism has proceeded rather far beyond the realism versus antirealism debate. This stance represents a middle-ground position between the two according to which science can attain justified true beliefs concerning relational facts about the unobservable realm but cannot attain justified true beliefs concerning the intrinsic nature of any objects occupying that realm. That is, the structural content of scientific theories about the unobservable can be known, but facts about the intrinsic nature of the entities that figure as place-holders in those structures cannot be known. There are two possible versions of SR: Epistemological Structural Realism (ESR) and Ontic Structural Realism (OSR). On ESR, an agnostic stance is preserved with respect to the natures of unobservable entities, but the possibility of knowing the relations obtaining between those entities is affirmed. OSR includes the rather striking claim that when it comes to the unobservables theorized about within fundamental physics, relations exist, but objects do not. Focusing on ESR, questions arise concerning its ability to explain the empirical success of a theory. Empirical success certainly involves predictive success, and predictive success implies a theory’s power to make accurate predictions. But a theory’s power to make any predictions at all seems to derive precisely from its core axioms or laws concerning unobservable entities and mechanisms, and not simply the sort of structural relations often expressed in equations. The specific challenge to ESR concerns its ability to explain the explanatory and predictive power of successful theories without appealing to their substantive ontologies, which are often not preserved by their successors. The response to this challenge will depend on the various and subtle different versions of ESR and OSR stances, which show a sort of progression through eliminativist OSR to moderate OSR of gradual increase in the ontological status accorded to objects. Knowing the relations between unobserved entities is methodologically identical to assert that these relations between unobserved entities exist.

Keywords: eliminativist ontic structural realism, epistemological structuralism, moderate ontic structural realism, ontic structuralism

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.

Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh

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The slamming impact problem has a very important engineering background. For seaplane landing, recycling for the satellite re-entry capsule, and the impact load of the bow in the adverse sea conditions, the slamming problem always plays the important role. Due to its strong nonlinear effect, however, it seems to be not easy to obtain the accurate simulation results. Combined with the strong interaction between the fluid field and the elastic structure, the difficulty for the simulation leads to a new level for challenging. This paper presents a fully Lagrangian coupled solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with two different materials such as aluminum and steel on water entry. The present simulation results are compared with analytical solution derived using the hydrodynamic Wagner model and linear theory by Wan.

Keywords: fluid-structure interaction, moving particle semi-implicit (MPS) method, elastic structure, incompressible flow, wedge slamming impact

Procedia PDF Downloads 602