Search results for: Blind navigation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 295

Search results for: Blind navigation

55 A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT

Authors: Say Wei Foo, Qi Dong

Abstract:

Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied to each block. By concatenating the first singular values (SV) of adjacent blocks of the normalized image, a SV block is obtained. DCT is then carried out on the SV blocks to produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency band of a SVD-DCT block by imposing a particular relationship between two pseudo-randomly selected DCT coefficients. An adaptive frequency mask is used to adjust local watermark embedding strength. Watermark extraction involves mainly the inverse process. The watermark extracting method is blind and efficient. Experimental results show that the quality degradation of watermarked image caused by the embedded watermark is visually transparent. Results also show that the proposed scheme is robust against various image processing operations and geometric attacks.

Keywords: Image watermarking, Image normalization, Singularvalue decomposition, Discrete cosine transform, Robustness.

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54 Investigation of Maritime Accidents with Exploratory Data Analysis in the Strait of Çanakkale (Dardanelles)

Authors: Gizem Kodak

Abstract:

The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.

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53 Dynamic Reroute Modeling for Emergency Evacuation: Case Study of Brunswick City, Germany

Authors: Yun-Pang Flötteröd, Jakob Erdmann

Abstract:

The human behaviors during evacuations are quite complex. One of the critical behaviors which affect the efficiency of evacuation is route choice. Therefore, the respective simulation modeling work needs to function properly. In this paper, Simulation of Urban Mobility’s (SUMO) current dynamic route modeling during evacuation, i.e. the rerouting functions, is examined with a real case study. The result consistency of the simulation and the reality is checked as well. Four influence factors (1) time to get information, (2) probability to cancel a trip, (3) probability to use navigation equipment, and (4) rerouting and information updating period are considered to analyze possible traffic impacts during the evacuation and to examine the rerouting functions in SUMO. Furthermore, some behavioral characters of the case study are analyzed with use of the corresponding detector data and applied in the simulation. The experiment results show that the dynamic route modeling in SUMO can deal with the proposed scenarios properly. Some issues and function needs related to route choice are discussed and further improvements are suggested.

Keywords: Evacuation, microscopic traffic simulation, rerouting, SUMO.

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52 A Fragile Watermarking Scheme for Color Image Authentication

Authors: M. Hamad Hassan, S.A.M. Gilani

Abstract:

In this paper, a fragile watermarking scheme is proposed for color image specified object-s authentication. The color image is first transformed from RGB to YST color space, suitable for watermarking the color media. The T channel corresponds to the chrominance component of a color image andYS ÔèÑ T , therefore selected for embedding the watermark. The T channel is first divided into 2×2 non-overlapping blocks and the two LSBs are set to zero. The object that is to be authenticated is also divided into 2×2 nonoverlapping blocks and each block-s intensity mean is computed followed by eight bit encoding. The generated watermark is then embedded into T channel randomly selected 2×2 block-s LSBs using 2D-Torus Automorphism. Selection of block size is paramount for exact localization and recovery of work. The proposed scheme is blind, efficient and secure with ability to detect and locate even minor tampering applied to the image with full recovery of original work. The quality of watermarked media is quite high both subjectively and objectively. The technique is suitable for class of images with format such as gif, tif or bitmap.

Keywords: Image Authentication, LSBs, PSNR, 2D-Torus Automorphism, YST Color Space.

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51 Blind Channel Estimation for Frequency Hopping System Using Subspace Based Method

Authors: M. M. Qasaymeh, M. A. Khodeir

Abstract:

Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.

Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.

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50 Super-ellipsoidal Potential Function for Autonomous Collision Avoidance of a Teleoperated UAV

Authors: Mohammed Qasim, Kyoung-Dae Kim

Abstract:

In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: Artificial potential function, autonomy, collision avoidance, teleoperation, quadrotor, UAV.

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49 Tidal Current Behaviors and Remarkable Bathymetric Change in the South-Western Part of Khor Abdullah, Kuwait

Authors: Ahmed M. Al-Hasem

Abstract:

A study of the tidal current behavior and bathymetric changes was undertaken in order to establish an information base for future coastal management. The average velocity for tidal current was 0.46 m/s and the maximum velocity was 1.08 m/s during ebb tide. During spring tides, maximum velocities range from 0.90 m/s to 1.08 m/s, whereas maximum velocities vary from 0.40 m/s to 0.60 m/s during neap tides. Despite greater current velocities during flood tide, the bathymetric features enhance the dominance of the ebb tide. This can be related to the abundance of fine sediments from the ebb current approaching the study area, and the relatively coarser sediment from the approaching flood current. Significant bathymetric changes for the period from 1985 to 1998 were found with dominance of erosion process. Approximately 96.5% of depth changes occurred within the depth change classes of -5 m to 5 m. The high erosion processes within the study area will subsequently result in high accretion processes, particularly in the north, the location of the proposed Boubyan Port and its navigation channel.

Keywords: Bathymetric change, Boubyan Island, GIS, Khor Abdullah, tidal current behavior.

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48 Comparison of GSA, SA and PSO Based Intelligent Controllers for Path Planning of Mobile Robot in Unknown Environment

Authors: P. K. Panigrahi, Saradindu Ghosh, Dayal R. Parhi

Abstract:

Now-a-days autonomous mobile robots have found applications in diverse fields. An autonomous robot system must be able to behave in an intelligent manner to deal with complex and changing environment. This work proposes the performance of path planning and navigation of autonomous mobile robot using Gravitational Search Algorithm (GSA), Simulated Annealing (SA) and Particle Swarm optimization (PSO) based intelligent controllers in an unstructured environment. The approach not only finds a valid collision free path but also optimal one. The main aim of the work is to minimize the length of the path and duration of travel from a starting point to a target while moving in an unknown environment with obstacles without collision. Finally, a comparison is made between the three controllers, it is found that the path length and time duration made by the robot using GSA is better than SA and PSO based controllers for the same work.

Keywords: Autonomous Mobile Robot, Gravitational Search Algorithm, Particle Swarm Optimization, Simulated Annealing Algorithm.

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47 Appraisal of Relativistic Effects on GNSS Receiver Positioning

Authors: I. Yakubu, Y. Y. Ziggah, E. A. Gyamera

Abstract:

The Global Navigation Satellite System (GNSS) started with the launch of the United State Department of Defense Global Positioning System (GPS). GNSS systems has grown over the years to include: GLONASS (Russia); Galileo (European Union); BeiDou (China). Any GNSS architecture consists of three major segments: Space, Control and User Segments. Errors such as; multipath, ionospheric and tropospheric effects, satellite clocks, receiver noise and orbit errors (relativity effect) have significant effects on GNSS positioning. To obtain centimeter level accuracy, the impacts of the relative motion of the satellites and earth need to be taken into account. This paper discusses the relevance of the theory of relativity as a source of error for GNSS receivers for position fix based on available relevant literature. Review of relevant literature reveals that due to relativity; Time dilation, Gravitational frequency shift and Sagnac effect cause significant influence on the use of GNSS receivers for positioning by an error range of ± 2.5 m based on pseudo-range computation.

Keywords: GNSS, relativistic effects, pseudo-range, accuracy.

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46 Multi-Agent Simulation of Wayfinding for Rescue Operation during Building Fire

Authors: G. Sokhansefat, M. Delavar, M. Banedj-Schafii

Abstract:

Recently research on human wayfinding has focused mainly on mental representations rather than processes of wayfinding. The objective of this paper is to demonstrate the rationality behind applying multi-agent simulation paradigm to the modeling of rescuer team wayfinding in order to develop computational theory of perceptual wayfinding in crisis situations using image schemata and affordances, which explains how people find a specific destination in an unfamiliar building such as a hospital. The hypothesis of this paper is that successful navigation is possible if the agents are able to make the correct decision through well-defined cues in critical cases, so the design of the building signage is evaluated through the multi-agent-based simulation. In addition, a special case of wayfinding in a building, finding one-s way through three hospitals, is used to demonstrate the model. Thereby, total rescue time for rescue operation during building fire is computed. This paper discuses the computed rescue time for various signage localization and provides experimental result for optimization of building signage design. Therefore the most appropriate signage design resulted in the shortest total rescue time in various situations.

Keywords: Multi-Agent system (MAS), Spatial Cognition, Wayfinding, Indoor Environment, Geospatial Information System (GIS).

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45 Health Monitoring and Failure Detection of Electronic and Structural Components in Small Unmanned Aerial Vehicles

Authors: Gopi Kandaswamy, P. Balamuralidhar

Abstract:

Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: Fault detection, health monitoring, unmanned aerial vehicles, vibration analysis.

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44 Comparison of Different k-NN Models for Speed Prediction in an Urban Traffic Network

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: Big data, k-NN, machine learning, traffic speed prediction.

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43 Semantically Enriched Web Usage Mining for Personalization

Authors: Suresh Shirgave, Prakash Kulkarni, José Borges

Abstract:

The continuous growth in the size of the World Wide Web has resulted in intricate Web sites, demanding enhanced user skills and more sophisticated tools to help the Web user to find the desired information. In order to make Web more user friendly, it is necessary to provide personalized services and recommendations to the Web user. For discovering interesting and frequent navigation patterns from Web server logs many Web usage mining techniques have been applied. The recommendation accuracy of usage based techniques can be improved by integrating Web site content and site structure in the personalization process.

Herein, we propose semantically enriched Web Usage Mining method for Personalization (SWUMP), an extension to solely usage based technique. This approach is a combination of the fields of Web Usage Mining and Semantic Web. In the proposed method, we envisage enriching the undirected graph derived from usage data with rich semantic information extracted from the Web pages and the Web site structure. The experimental results show that the SWUMP generates accurate recommendations and is able to achieve 10-20% better accuracy than the solely usage based model. The SWUMP addresses the new item problem inherent to solely usage based techniques.

Keywords: Prediction, Recommendation, Semantic Web Usage Mining, Web Usage Mining.

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42 Issues in the User Interface Design of a Content Rich Vocational Training Application for Digitally Illiterate Users

Authors: Jamie Otelsberg, Nagarajan Akshay, Rao R. Bhavani

Abstract:

This paper discusses our preliminary experiences in the design of a user interface of a computerized content-rich vocational training courseware meant for users with little or no computer experience. In targeting a growing population with limited access to skills training of any sort, we faced numerous challenges, including language and cultural differences, resource limits, gender boundaries and, in many cases, the simple lack of trainee motivation. With the size of the unskilled population increasing much more rapidly than the numbers of sufficiently skilled teachers, there is little choice but to develop teaching techniques that will take advantage of emerging computer-based training technologies. However, in striving to serve populations with minimal computer literacy, one must carefully design the user interface to accommodate their cultural, social, educational, motivational and other differences. Our work, which uses computer based and haptic simulation technologies to deliver training to these populations, has provided some useful insights on potential user interface design approaches.

Keywords: User interface design, digitally illiterate, vocational training, navigation issues, computer human interaction, human factors.

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41 Effect of Tube Thickness on the Face Bending for Blind-Bolted Connection to Concrete Filled Tubular Structures

Authors: Mohammed Mahmood, Walid Tizani, Carlo Sansour

Abstract:

In this paper, experimental testing and numerical analysis were used to investigate the effect of tube thickness on the face bending for concrete filled hollow sections connected to other structural members using Extended Hollobolts. Six samples were tested experimentally by applying pull-out load on the bolts. These samples were designed to fail by column face bending. The main variable in all tests is the column face thickness. Finite element analyses were also performed using ABAQUS 6.11 to extend the experimental results and to quantify the effect of column face thickness. Results show that, the column face thickness has a clear impact on the connection strength and stiffness. However, the amount of improvement in the connection stiffness by changing the column face thickness from 5mm to 6.3mm seems to be higher than that when increasing it from 6.3mm to 8mm. The displacement at which the bolts start pulling-out from their holes increased with the use of thinner column face due to the high flexibility of the section. At the ultimate strength, the yielding of the column face propagated to the column corner and there was no yielding in its walls. After the ultimate resistance is reached, the propagation of the yielding was mainly in the column face with a miner yielding in the walls.

Keywords: Anchored bolted connection, Extended Hollobolt, Column faces bending and concrete filled hollow sections.

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40 NDENet: End-to-End Nighttime Dehazing and Enhancement

Authors: H. Baskar, A. S. Chakravarthy, P. Garg, D. Goel, A. S. Raj, K. Kumar, Lakshya, R. Parvatham, V. Sushant, B. Kumar Rout

Abstract:

In this paper, we present a computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve Structural Index Similarity (SSIM) of 0.8962 and Peak Signal to Noise Ratio (PSNR) of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task particularly for autonomous navigation applications, and hope that our work will open up new frontiers in research. The code for our network is made publicly available.

Keywords: Dehazing, image enhancement, nighttime, computer vision.

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39 Design and Implementation a Fully Autonomous Soccer Player Robot

Authors: S. H. Mohades Kasaei, S. M. Mohades Kasaei, S. A. Mohades Kasaei, M. Taheri, M. Rahimi, H. Vahiddastgerdi, M. Saeidinezhad

Abstract:

Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, Omni directional navigation system, Omni-vision system and solenoid kicking mechanism in such mobile robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, a comprehensive Omni directional mobile robot. Such a robot can respond more quickly and it would be capable for more sophisticated behaviors with multi-sensor data fusion algorithm for global localization base on the data fusion. This paper has tried to focus on the research improvements in the mechanical, electrical and software design of the robots of team ADRO Iran. The main improvements are the world model, the new strategy framework, mechanical structure, Omni-vision sensor for object detection, robot path planning, active ball handling mechanism and the new kicker design, , and other subjects related to mobile robot

Keywords: Mobile robot, Machine vision, Omni directional movement, Autonomous Systems, Robot path planning, Object Localization.

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38 Optical Fish Tracking in Fishways using Neural Networks

Authors: Alvaro Rodriguez, Maria Bermudez, Juan R. Rabuñal, Jeronimo Puertas

Abstract:

One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.

Keywords: Computer Vision, Neural Network, Fishway, Fish Trajectory, Tracking

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37 An Ontology for Spatial Relevant Objects in a Location-aware System: Case Study: A Tourist Guide System

Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

Abstract:

Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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36 SIFT Accordion: A Space-Time Descriptor Applied to Human Action Recognition

Authors: Olfa.Ben Ahmed, Mahmoud. Mejdoub, Chokri. Ben Amar

Abstract:

Recognizing human action from videos is an active field of research in computer vision and pattern recognition. Human activity recognition has many potential applications such as video surveillance, human machine interaction, sport videos retrieval and robot navigation. Actually, local descriptors and bag of visuals words models achieve state-of-the-art performance for human action recognition. The main challenge in features description is how to represent efficiently the local motion information. Most of the previous works focus on the extension of 2D local descriptors on 3D ones to describe local information around every interest point. In this paper, we propose a new spatio-temporal descriptor based on a spacetime description of moving points. Our description is focused on an Accordion representation of video which is well-suited to recognize human action from 2D local descriptors without the need to 3D extensions. We use the bag of words approach to represent videos. We quantify 2D local descriptor describing both temporal and spatial features with a good compromise between computational complexity and action recognition rates. We have reached impressive results on publicly available action data set

Keywords: Accordion, Bag of Features, Human action, Motion, Moving point, Space-Time Descriptor, SIFT, Video.

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35 Sustainability and Promotion of Inland Waterway Transportation Projects in Colombia: Case of the Magdalena River

Authors: David Julian Bernal Melgarejo

Abstract:

Inland Waterway Transportation (IWT) is playing an important role in national transport systems, water transportation is considered to be safe, energy efficient and environmentally friendly mode of transport, all benefits of IWT cause national awareness increase, for instance the Colombian government is planning to restore the navigability of the most important river of the country, the Magdalena’s River navigability, embrace waterway transportation in Colombia could strength competitiveness while reduce most of the transport externalities. However, the current situation of the Magdalena is deplorable, the most important river of Colombia has been abandoned for decades and the solution is beyond of a single administrative entity. This paper analyzes the outcomes of the Navigation And Inland Waterway Action and Development in Europe program (NAIADES) as a prospective to develop a similar program in Colombia with similar objectives and guidelines, considering sustainability, guarantying the long-term future results and adaptability of the program. Identifying stakeholders and policy experts, a set of individual interviews were carried out; findings support the idea of lack of integration within governmental institutions and lack of importance in marketing promotion as possible drawbacks on the implementation of IWT projects.

Keywords: Inland waterway transportation, Logistics, Sustainability, Multimodal transport systems, Water transportation.

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34 Optimization Based Tuning of Autopilot Gains for a Fixed Wing UAV

Authors: Mansoor Ahsan, Khalid Rafique, Farrukh Mazhar

Abstract:

Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.

Keywords: Unmanned aerial vehicle (UAV), autopilot, autonomous controls, PID controler gains tuning, optimization.

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33 Simple Agents Benefit Only from Simple Brains

Authors: Valeri A. Makarov, Nazareth P. Castellanos, Manuel G. Velarde

Abstract:

In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.

Keywords: Neural network, probabilistic control, robot navigation.

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32 Texture Feature Extraction of Infrared River Ice Images using Second-Order Spatial Statistics

Authors: Bharathi P. T, P. Subashini

Abstract:

Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.

Keywords: Gray Level Difference Method, Gray Level Run Length Method, Kurtosis, Probabilistic Neural Network, Skewness, Spatial Gray Level Dependence Method.

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31 Integrating Microcontroller-Based Projects in a Human-Computer Interaction Course

Authors: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo

Abstract:

This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.

Keywords: Maker movement, microcontrollers, learning, projects, course, technology acceptance.

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30 Robot Operating System-Based SLAM for a Gazebo-Simulated Turtlebot2 in 2d Indoor Environment with Cartographer Algorithm

Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

Abstract:

The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, Gazebo, Rviz, Turtlebot2, SLAM algorithms, 2d Indoor environment, Cartographer.

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29 Extraction of Data from Web Pages: A Vision Based Approach

Authors: P. S. Hiremath, Siddu P. Algur

Abstract:

With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.

Keywords: Web data records, web data regions, web mining.

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28 An Evaluation of Digital Elevation Models to Short-Term Monitoring of a High Energy Barrier Island, Northeast Brazil

Authors: Venerando E. Amaro, Francisco Gabriel F. de Lima, Marcelo S.T. Santos

Abstract:

The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.

Keywords: DEM, GNSS, short-term monitoring, Brazil.

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27 Road Traffic Accidents Analysis in Mexico City through Crowdsourcing Data and Data Mining Techniques

Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

Abstract:

Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: Data mining, K-means, road traffic accidents, Waze, Weka.

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26 Received Signal Strength Indicator Based Localization of Bluetooth Devices Using Trilateration: An Improved Method for the Visually Impaired People

Authors: Muhammad Irfan Aziz, Thomas Owens, Uzair Khaleeq uz Zaman

Abstract:

The instantaneous and spatial localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles, is the most demanding and challenging issue faced by the navigation systems today. Since Bluetooth cannot utilize techniques like Time Difference of Arrival (TDOA) and Time of Arrival (TOA), it uses received signal strength indicator (RSSI) to measure Receive Signal Strength (RSS). The measurements using RSSI can be improved significantly by improving the existing methodologies related to RSSI. Therefore, the current paper focuses on proposing an improved method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the method, class 2 Bluetooth devices were used along with the development of a software. Experiments were then conducted to obtain surface plots that showed the signal interferences and other environmental effects. Finally, the results obtained show the surface plots for all Bluetooth modules used along with the strong and weak points depicted as per the color codes in red, yellow and blue. It was concluded that the suggested improved method of measuring RSS using trilateration helped to not only measure signal strength affectively but also highlighted how the signal strength can be influenced by atmospheric conditions such as noise, reflections, etc.

Keywords: Bluetooth, indoor/outdoor localization, received signal strength indicator, visually impaired.

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