Search results for: tracking algorithm

Authors: Mohammad Befkin, Alireza Momtaz

Abstract:

Structural design is the challenging aspect of every project due to limitations in dimensions, functionality of the structure, and more importantly, the allocated budget for construction. This research study aims to investigate the optimized design for three steel moment frame buildings with different number of stories using genetic algorithm code. The number and length of spans, and height of each floor were constant in all three buildings. The design of structures are carried out according to AISC code within the provisions of plastic design with allowable stress values. Genetic code for optimization is produced using MATLAB program, while buildings modeled in Opensees program and connected to the MATLAB code to perform iterations in optimization steps. In the end designs resulted from genetic algorithm code were compared with the analysis of buildings in ETABS program. The results demonstrated that suggested structural elements by the code utilize their full capacity, indicating the desirable efficiency of produced code.

Keywords: genetic algorithm, structural analysis, steel moment frame, structural design

Procedia PDF Downloads 95

Authors: Qiuxiao Chen, Yan Hou, Ning Wu

Abstract:

As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

Procedia PDF Downloads 228

Authors: Rezky Rifaini, Raden Bagus Fajriya Hakim

Abstract:

This research was conducted at the Bolo primary health Care in Bima Regency. The purpose of the research is to find out the association pattern that is formed of medical record database from Bolo Primary health care’s patient. The data used is secondary data from medical records database PHC. Sequential pattern mining technique is the method that used to analysis. Transaction data generated from Patient_ID, Check_Date and diagnosis. Sequential Pattern Discovery Algorithms Using Equivalent Classes (SPADE) is one of the algorithm in sequential pattern mining, this algorithm find frequent sequences of data transaction, using vertical database and sequence join process. Results of the SPADE algorithm is frequent sequences that then used to form a rule. It technique is used to find the association pattern between items combination. Based on association rules sequential analysis with SPADE algorithm for minimum support 0,03 and minimum confidence 0,75 is gotten 3 association sequential pattern based on the sequence of patient_ID, check_Date and diagnosis data in the Bolo PHC.

Keywords: diagnosis, primary health care, medical record, data mining, sequential pattern mining, SPADE algorithm

Procedia PDF Downloads 383

Authors: Jayron Sanchez, Analyn Yumang, Felicito Caluyo

Abstract:

The visually impaired individual may use a cane, guide dog or ask for assistance from a person. This study implemented the RFID technology which consists of a low-cost RFID reader and passive RFID tag cards. The passive RFID tag cards served as checkpoints for the visually impaired. The visually impaired was guided through audio output from the system while traversing the path. The study implemented an ultrasonic sensor in detecting static obstacles. The system generated an alternate path based on A* algorithm to avoid the obstacles. Alternate paths were also generated in case the visually impaired traversed outside the intended path to the destination. A* algorithm generated the shortest path to the destination by calculating the total cost of movement. The algorithm then selected the smallest movement cost as a successor to the current tag card. Several trials were conducted to determine the effect of obstacles in the time traversal of the visually impaired. A dependent sample t-test was applied for the statistical analysis of the study. Based on the analysis, the obstacles along the path generated delays while requesting for the alternate path because of the delay in transmission from the laptop to the device via ZigBee modules.

Keywords: A* algorithm, RFID technology, ultrasonic sensor, ZigBee module

Procedia PDF Downloads 393

Authors: G. M. Komba

Abstract:

The Internet Gateway (IGW) has extra ability than a simple Mesh Router (MR) and the responsibility to route mostly the all traffic from Mesh Clients (MCs) to the Internet backbone however, IGWs are more expensive. Choosing strategic locations for the Internet Gateways (IGWs) best location in Backbone Wireless Mesh (BWM) precarious to the Wireless Mesh Network (WMN) and the location of IGW can improve a quantity of performance related problem. In this paper, we propose a novel algorithm, namely New Gateway Location Algorithm (NGLA), which aims to achieve four objectives, decreasing the network cost effective, minimizing delay, optimizing the throughput capacity, Different from existing algorithms, the NGLA increasingly recognizes IGWs, allocates mesh routers (MRs) to identify IGWs and promises to find a feasible IGW location and install minimum as possible number of IGWs while regularly conserving the all Quality of Service (QoS) requests. Simulation results showing that the NGLA outperforms other different algorithms by comparing the number of IGWs with a large margin and it placed 40% less IGWs and 80% gain of throughput. Furthermore the NGLA is easy to implement and could be employed for BWM.

Keywords: Wireless Mesh Network, Gateway Location Algorithm, Quality of Service, BWM

Procedia PDF Downloads 348

Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

Abstract:

Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

Procedia PDF Downloads 99

Authors: J. Liu, Z. P. Yu, L. Xiong, Y. Feng, J. He

Abstract:

According to the independence, accuracy and controllability of the driving/braking torque of the distributed drive electric vehicle, a control strategy of differential drive assisted steering was designed. Firstly, the assisted curve under different speed and steering wheel torque was developed and the differential torques were distributed to the right and left front wheels. Then the steering return ability assisted control algorithm was designed. At last, the joint simulation was conducted by CarSim/Simulink. The result indicated: the differential drive assisted steering algorithm could provide enough steering drive-assisted under low speed and improve the steering portability. Along with the increase of the speed, the provided steering drive-assisted decreased. With the control algorithm, the steering stiffness of the steering system increased along with the increase of the speed, which ensures the driver’s road feeling. The control algorithm of differential drive assisted steering could avoid the understeer under low speed effectively.

Keywords: differential assisted steering, control strategy, distributed drive electric vehicle, driving/braking torque

Procedia PDF Downloads 464

Authors: M. Nageswara Rao, V. S. N. K. Chaitanya, K. Amarendranath

Abstract:

This paper presents an optimal allocation and sizing of Distributed Generation (DG) in Radial Distribution Network (RDN) for total power loss minimization and enhances the voltage profile of the system. The two main important part of this study first is to find optimal allocation and second is optimum size of DG. The locations of DGs are identified by Analytical expressions and crow search algorithm has been employed to determine the optimum size of DG. In this study, the DG has been placed on single and multiple allocations.CSA is a meta-heuristic algorithm inspired by the intelligent behavior of the crows. Crows stores their excess food in different locations and memorizes those locations to retrieve it when it is needed. They follow each other to do thievery to obtain better food source. This analysis is tested on IEEE 33 bus and IEEE 69 bus under MATLAB environment and the results are compared with existing methods.

Keywords: analytical expression, distributed generation, crow search algorithm, power loss, voltage profile

Procedia PDF Downloads 216

Authors: N. Drir, L. Barazane, M. Loudini

Abstract:

It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

Procedia PDF Downloads 321

Authors: Volkan Uygun, H. Birkan Yilmaz, Tuna Tugcu

Abstract:

This study focuses on the development and use of algorithms that address the issue of resource management in response to emergency and disaster situations. The presented system, named Disaster Management Platform (DMP), takes the data from the data sources of service providers and distributes the incoming requests accordingly both to manage load balancing and minimize service time, which results in improved user satisfaction. Three different resource management algorithms, which give different levels of importance to load balancing and service time, are proposed for the study. The first one is the Minimum Distance algorithm, which assigns the request to the closest resource. The second one is the Minimum Load algorithm, which assigns the request to the resource with the minimum load. Finally, the last one is the Hybrid algorithm, which combines the previous two approaches. The performance of the proposed algorithms is evaluated with respect to waiting time, success ratio, and maximum load ratio. The metrics are monitored from simulations, to find the optimal scheme for different loads. Two different simulations are performed in the study, one is time-based and the other is lambda-based. The results indicate that, the Minimum Load algorithm is generally the best in all metrics whereas the Minimum Distance algorithm is the worst in all cases and in all metrics. The leading position in performance is switched between the Minimum Distance and the Hybrid algorithms, as lambda values change.

Keywords: emergency and disaster response, resource management algorithm, disaster situations, disaster management platform

Procedia PDF Downloads 323

Authors: Oral S. Saulters, Shanon D. Goldberg, Wendy A. Staples, Ellena I. Martinez, Lorie M. Sanchez, Diego E. Archuleta, Deborah L. Williams, Scot D. Johnson

Abstract:

To address an important set of unverified field conditions, the Los Alamos National Laboratory Waste Compliance and Tracking System (WCATS) Wall-to-Wall Team performed an unprecedented and advanced inventory. This reconciliation involved confirmation analysis for approximately 5850 hazardous, low-level, mixed low-level, and transuranic waste containers located in more than 200 staging and storage areas across 33 technical areas. The interdisciplinary team scoped, planned, and developed the multidimensional assessments. Through coordination with cross-functional site hosts, they were able to verify and validate data while resolving discrepancies identified in WCATS. The results were extraordinary with an updated inventory, tailored outreach, more cohesive communications, and timely closed-loop feedback.

Keywords: circular economy, environmental performance data, social-ecological-technological systems, waste management

Procedia PDF Downloads 110

Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

Abstract:

The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

Procedia PDF Downloads 273

Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh

Abstract:

Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: cell formation problem, group technology, imperialist competitive algorithm, sequence data

Procedia PDF Downloads 436

Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

Abstract:

Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

Procedia PDF Downloads 494

Authors: Davood Rajabi, Mojgan Yazdani

Abstract:

Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.

Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood

Procedia PDF Downloads 484

Authors: Suparman

Abstract:

This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

Procedia PDF Downloads 210

Authors: Muciz Özcan, Mustafa Sacid Endiz, Veysel Alver

Abstract:

In this paper we present a new approach to the boom welding related to the mobile cranes manufacturing, implementing a new method in order to get homogeneous welding quality and reduced energy usage during booms production. We aim to get the realization of the same welding quality carried out on the boom in every region during the manufacturing process and to detect the possible welding errors whether they could be eliminated using laser sensors. We determine the position of the welding region directly through our system and with the help of the welding oscillator we are able to perform a proper boom welding. Errors that may occur in the welding process can be observed by monitoring and eliminated by means of an operator. The major modification in the production of the crane booms will be their form of the booms. Although conventionally, more than one welding is required to perform this process, with the suggested concept, only one particular welding is sufficient, which will be more energy and environment-friendly. Consequently, as only one welding is needed for the manufacturing of the boom, the particular welding quality becomes more essential. As a way to satisfy the welding quality, a welding manipulator was made and fabricated. By using this welding manipulator, the risks of involving dangerous gases formed during the welding process for the operator and the surroundings are diminished as much as possible.

Keywords: boom welding, seam tracking, energy saving, global warming

Procedia PDF Downloads 322

Authors: Chih-Jer Lin, Jian-Hong Hou

Abstract:

Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

Procedia PDF Downloads 130

Authors: Luay Alsalmi

Abstract:

Background: Facial filler is the most common type of cosmetic surgery next to botox. Permanent filler is preferred nowadays due to the low cost brought about by non-recurring injection appointments. However, such fillers pose a higher risk for complications, with even greater adverse effects when the procedure is done using unknown dermal filler injections. AIM: This study aimed to establish an algorithm to categorize and manage patients that receive permanent fillers. Materials and Methods: Twelve participants were presented to the service through emergency or as outpatient from November 2015 to May 2021. Demographics such as age, sex, date of injection, time of onset, and types of complications were collected. After examination, all cases were managed based on an algorithm established. FACE-Q was used to measure overall satisfaction and psychological well-being. Results: The algorithm to diagnose and manage these patients effectively with a high satisfaction rate was established in this study. All participants were non-smoker females with no known medical comorbidities. The algorithm presented determined the treatment plan when faced with complications. Results revealed high appearance-related psychosocial distress was observed prior to surgery, while it significantly dropped after surgery. FACE-Q was able to establish evidence of satisfactory ratings among patients prior to and after surgery. Conclusion: This treatment algorithm can guide the surgeon in formulating a suitable plan with fewer complications and a high satisfaction rate.

Keywords: facial filler, FACE-Q, psycho-social stress, botox, treatment algorithm

Procedia PDF Downloads 66

Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

Abstract:

In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

Procedia PDF Downloads 73

Authors: Safiqul Islam, Anamul Haque, Mohammad Amran Hossain

Abstract:

Aim: To compare the dosimetric parameters of the flattened and flattening filter free (FFF) beam and to validate the beam data using anisotropic analytical algorithm (AAA). Materials and Methods: All the dosimetric data’s (i.e. depth dose profiles, profile curves, output factors, penumbra etc.) required for the beam modeling of AAA were acquired using the Blue Phantom RFA for 6 MV, 6 FFF, 10MV & 10FFF. Progressive resolution Optimizer and Dose Volume Optimizer algorithm for VMAT and IMRT were are also configured in the beam model. Beam modeling of the AAA were compared with the measured data sets. Results: Due to the higher and lover energy component in 6FFF and 10 FFF the surface doses are 10 to 15% higher compared to flattened 6 MV and 10 MV beams. FFF beam has a lower mean energy compared to the flattened beam and the beam quality index were 6 MV 0.667, 6FFF 0.629, 10 MV 0.74 and 10 FFF 0.695 respectively. Gamma evaluation with 2% dose and 2 mm distance criteria for the Open Beam, IMRT and VMAT plans were also performed and found a good agreement between the modeled and measured data. Conclusion: We have successfully modeled the AAA algorithm for the flattened and FFF beams and achieved a good agreement with the calculated and measured value.

Keywords: commissioning of a Flattening Filter Free (FFF) , using an Anisotropic Analytical Algorithm (AAA), flattened beam, parameters

Procedia PDF Downloads 284

Authors: Anita Kéri

Abstract:

Higher education marketing has been a widely researched field in recent years. Due to the increasing competition among higher education institutions worldwide, it has become crucial to target foreign students with effective marketing tools. Online marketing tools became central to attracting, retaining, and satisfying the needs of foreign students. Therefore, the aim of the current study is to reveal how the online marketing tools of a Hungarian university are perceived visually by its first-year foreign students, with special emphasis on the university webpage content. Eye-camera tracking and retrospective think-aloud interviews were used to measure visual perceptions. Results show that freshmen students remember those online marketing content more that has familiar content on them. Pictures of real-life students and their experiences attract students’ attention more, and they also remember information on these webpage elements more, compared to designs with stock photos. This research is novel in the sense that it uses eye-camera tracking in the field of higher education marketing, thereby providing insight into the perception of online higher education marketing for foreign students.

Keywords: higher education, marketing, eye-camera, visual perceptions

Procedia PDF Downloads 83

Authors: Han Bing, Yin Zhenjie

Abstract:

In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

Procedia PDF Downloads 288

Authors: Alexandre Rabaseda, Emelie Seguin, Marc Doumit

Abstract:

Human mobility exoskeletons have been in development for several years and are becoming increasingly efficient. Unfortunately, user comfort was not always a priority design criterion throughout their development. To further improve this technology, exoskeletons should operate and deliver assistance without causing discomfort to the user. For this, improvements are necessary from an ergonomic point of view. The device’s control method is important when endeavoring to enhance user comfort. Exoskeleton or rehabilitation device controllers use methods of control called interaction controls (admittance and impedance controls). This paper proposes an extended version of an admittance controller to enhance user comfort. The control method used consists of adding an inner loop that is controlled by a proportional-integral-derivative (PID) controller. This allows the interaction force to be kept as close as possible to the desired force trajectory. The force-tracking admittance controller modifies the actuation force of the system in order to follow both the desired motion trajectory and the desired relative force between the user and the exoskeleton.

Keywords: mobility assistive device, exoskeleton, force-tracking admittance controller, user comfort

Procedia PDF Downloads 133

Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

Abstract:

This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

Procedia PDF Downloads 305

Authors: Ali Hosseini

Abstract:

Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

Procedia PDF Downloads 290

Authors: Kaan Koyuncu, Umut Celen Arican, Sevilay Can

Abstract:

In the maritime industry, there have been regulations to prevent pollution, and the first attempt to offer a legal basis was Marpol Convention which was held in 1973 in order to provide a framework for the disposal of ship wastes. Based on this convention, ports are obliged to build waste receiving facilities. European Union regulations make several member countries to follow these directions, In Turkey, under Blue Card System, the quantity and types of wastes, the delivery time, the capacity of the receiving facilities, and other required information can be monitored online. Therefore, yachts and other boats with the bilge, sewage, and waste which illegally discharge into the sea, can be blocked. This system is an outcome of the law adopted from European Union regulations. In this study, the present systems in Turkey which occurred in 2010 after the integration of the system, which has been put in the force in 2000 in Europe will be analyzed and interpreted to provide a useful comparison, a practical guide, and a roadmap for potential improvements.

Keywords: Europe-Turkey, blue card, marine environment, ship waste tracking system

Procedia PDF Downloads 481

Authors: Saumya Srivastava, Rina Maiti

Abstract:

In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 107

Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

Abstract:

The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

Procedia PDF Downloads 466

Authors: Khadidja Belbachir, Hafida Belbachir

Abstract:

subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

Procedia PDF Downloads 382