Search results for: analysis and real time information about liquefaction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 46778

Search results for: analysis and real time information about liquefaction

46388 Analysis of Relative Gene Expression Data of GATA3-AS1 Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients of Luminal B Subtype

Authors: X. Cervantes-López, C. Arriaga-Canon, L. Contreras Espinosa

Abstract:

The goal of this study is to validate the overexpression of the lncRNA GATA3-AS1 associated with resistance to neoadjuvant chemotherapy of female patients with locally advanced mammary adenocarcinoma of luminal B subtype This study involved a cohort of one hundred thirty-seven samples for which total RNA was isolated from formalin fixed paraffin embedded (FFPE) tissue. Samples were cut using a Microtome Hyrax M25 Zeiss and RNA was isolated using the RNeasy FFPE kit and a deparaffinization solution, the next step consisted in the analysis of RNA concentration and quality, then 18 µg of RNA was treated with DNase I, and cDNA was synthesized from 50 ng total RNA, finally real-time PCR was performed with SYBR Green/ROX qPCR Master Mix in order to determined relative gene expression using RPS28 as a housekeeping gene to normalize in a fold calculation ΔCt. As a result, we validated by real-time PCR that the overexpression of the lncRNA GATA3-AS1 is associated with resistance to neoadjuvant chemotherapy in locally advanced breast cancer patients of luminal B subtype.

Keywords: breast cancer, biomarkers, genomics, neoadjuvant chemotherapy, lncRNAS

Procedia PDF Downloads 55
46387 Design and Development of Real-Time Optimal Energy Management System for Hybrid Electric Vehicles

Authors: Masood Roohi, Amir Taghavipour

Abstract:

This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

Procedia PDF Downloads 352
46386 Polarity Classification of Social Media Comments in Turkish

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

Abstract:

People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 146
46385 Online Guidance and Counselling Needs and Preferences of University Undergraduates in a Nigerian University

Authors: Olusegun F. Adebowale

Abstract:

Research has confirmed that the emergence of information technology is significantly reflected in the field of psychology and its related disciplines due to its widespread use at reasonable price and its user-friendliness. It is consequently affecting ordinary life in many areas like shopping, advertising, corresponding and educating. Specifically the innovations of computer technology led to several new forms of communication, all with implications and applicability for counselling and psychotherapy practices. This is premise on which online counselling is based. Most institutions of higher learning in Nigeria have established their presence on the Internet and have deployed a variety of applications through ICT. Some are currently attempting to include counselling services in such applications with the belief that many counselling needs of students are likely to be met. This study therefore explored different challenges and preferences students present in online counselling interaction in a given Nigerian university with the view to guide new universities that may want to invest into these areas as to necessary preparations and referral requirements. The study is a mixed method research incorporating qualitative and quantitative methodologies to sample the preferences and concerns students express in online interaction. The sample comprised all the 876 students who visited the university online counselling platform either voluntarily, by invitation or by referral. The instrument for data collection was the online counselling platform of the university 'OAU Online counsellors'. The period of data collection spanned between January 2011 and October 2012. Data were analysed quantitatively (using percentages and Mann-Whitney U test) and qualitatively (using Interpretative Phenomenological Analysis (IPA)). The results showed that the students seem to prefer real-time chatting as their online medium of communicating with the online counsellor. The majority of students resorted to e-mail when their effort to use real-time chatting were becoming thwarted. Also, students preferred to enter into online counselling relationships voluntarily to other modes of entry. The results further showed that the prevalent counselling needs presented by students during online counselling sessions were mainly in the areas of social interaction and academic/educational concerns. Academic concerns were found to be prevalent, in form of course offerings, studentship matters and academic finance matters. The personal/social concerns were in form of students’ welfare, career related concerns and relationship matters. The study concludes students’ preferences include voluntary entry into online counselling, communication by real-time chatting and a specific focus on their academic concerns. It also recommends that all efforts should be made to encourage students’ voluntary entry into online counselling through reliable and stable internet infrastructure that will be able to support real-time chatting.

Keywords: online, counselling, needs, preferences

Procedia PDF Downloads 290
46384 Effect of Silver Diamine Fluoride on Reducing Fungal Adhesion on Dentin

Authors: Rima Zakzouk, Noriko Hiraishi, Mohamed Mahdi Alshahni, Koichi Makimura, Junji Tagami

Abstract:

Background and Purpose: Silver diamine fluoride (SDF) is used to prevent and arrest dental caries. The aim of this study is to evaluate the effect of SDF on reducing Candida albicans adhesion on dentin. Materials and Methods: Bovine dentin disks (6×6 mm) were cut by Isomet and polished using grit silicon carbide papers down to 2000 in order to obtain flat dentin surfaces. Samples were divided into two groups. The first group (SDF group) was treated with 38% SDF for 3 min, while the other group (control group) did not undergo SDF treatment. All samples were exposed to C. albicans suspension, washed after 6 hours incubation at 30 °C before to be tested using XTT (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) and real time PCR approaches. Statistical analyses of the results were performed at the significance level α = 0.05. Results: SDF inhibited C. albicans adhesion onto dentin. A significant difference was found between the SDF and control groups in both XTT and real time PCR tests. Conclusion: Using SDF to arrest the caries, could inhibit the Candida growth on dentin.

Keywords: silver diamine fluoride, dentin, real time PCR, XTT

Procedia PDF Downloads 162
46383 Real-Time Sensor Fusion for Mobile Robot Localization in an Oil and Gas Refinery

Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

Abstract:

Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

Procedia PDF Downloads 472
46382 A Low Cost and Reconfigurable Experimental Platform for Engineering Lab Education

Authors: S. S. Kenny Lee, C. C. Kong, S. K. Ting

Abstract:

Teaching engineering lab provides opportunity for students to practice theories learned through physical experiment in the laboratory. However, building laboratories to accommodate increased number of students are expensive, making it impossible for an educational institution to afford the high expenses. In this paper, we develop a low cost and remote platform to aid teaching undergraduate students. The platform is constructed where the real experiment setting up in laboratory can be reconfigure and accessed remotely, the aim is to increase student’s desire to learn at which they can interact with the physical experiment using network enabled devices at anywhere in the campus. The platform is constructed with Raspberry Pi as a main control board that provides communication between computer interfaces to the actual experiment preset in the laboratory. The interface allows real-time remote viewing and triggering the physical experiment in the laboratory and also provides instructions and learning guide about the experimental.

Keywords: engineering lab, low cost, network, remote platform, reconfigure, real-time

Procedia PDF Downloads 308
46381 Eye Tracking: Biometric Evaluations of Instructional Materials for Improved Learning

Authors: Janet Holland

Abstract:

Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation

Procedia PDF Downloads 131
46380 Smart Lean Manufacturing in the Context of Industry 4.0: A Case Study

Authors: M. Ramadan, B. Salah

Abstract:

This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping

Procedia PDF Downloads 229
46379 Test Research on Damage Initiation and Development of a Concrete Beam Using Acoustic Emission Technology

Authors: Xiang Wang

Abstract:

In order to validate the efficiency of recognizing the damage initiation and development of a concrete beam using acoustic emission technology, a concrete beam is built and tested in the laboratory. The acoustic emission signals are analyzed based on both parameter and wave information, which is also compared with the beam deflection measured by displacement sensors. The results indicate that using acoustic emission technology can detect damage initiation and development effectively, especially in the early stage of the damage development, which can not be detected by the common monitoring technology. Furthermore, the positioning of the damage based on the acoustic emission signals can be proved to be reasonable. This job can be an important attempt for the future long-time monitoring of the real concrete structure.

Keywords: acoustic emission technology, concrete beam, parameter analysis, wave analysis, positioning

Procedia PDF Downloads 141
46378 An Integrated Approach for Optimizing Drillable Parameters to Increase Drilling Performance: A Real Field Case Study

Authors: Hamidoddin Yousife

Abstract:

Drilling optimization requires a prediction of drilling rate of penetration (ROP) since it provides a significant reduction in drilling costs. There are several factors that can have an impact on the ROP, both controllable and uncontrollable. Numerous drilling penetration rate models have been considered based on drilling parameters. This papers considered the effect of proper drilling parameter selection such as bit, Mud Type, applied weight on bit (WOB), Revolution per minutes (RPM), and flow rate on drilling optimization and drilling cost reduction. A predicted analysis is used in real-time drilling performance to determine the optimal drilling operation. As a result of these modeling studies, the real data collected from three directional wells at Azadegan oil fields, Iran, was verified and adjusted to determine the drillability of a specific formation. Simulation results and actual drilling results show significant improvements in inaccuracy. Once simulations had been validated, optimum drilling parameters and equipment specifications were determined by varying weight on bit (WOB), rotary speed (RPM), hydraulics (hydraulic pressure), and bit specification for each well until the highest drilling rate was achieved. To evaluate the potential operational and economic benefits of optimizing results, a qualitative and quantitative analysis of the data was performed.

Keywords: drlling, cost, optimization, parameters

Procedia PDF Downloads 168
46377 Comparative Study of Deep Reinforcement Learning Algorithm Against Evolutionary Algorithms for Finding the Optimal Values in a Simulated Environment Space

Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

Abstract:

Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

Procedia PDF Downloads 112
46376 Design of Traffic Counting Android Application with Database Management System and Its Comparative Analysis with Traditional Counting Methods

Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

Abstract:

Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

Procedia PDF Downloads 193
46375 Agile Project Management: A Real Application in a Multi-Project Research and Development Center

Authors: Aysegul Sarac

Abstract:

The aim of this study is to analyze the impacts of integrating agile development principles and practices, in particular to reduce project lead time in a multi-project environment. We analyze Arçelik Washing Machine R&D Center in which multiple projects are conducted by shared resources. In the first part of the study, we illustrate the current waterfall model system by using a value stream map. We define all activities starting from the first idea of the project to the customer and measure process time and lead time of projects. In the second part of the study we estimate potential improvements and select a set of these improvements to integrate agile principles. We aim to develop a future state map and analyze the impacts of integrating lean principles on project lead time. The main contribution of this study is that we analyze and integrate agile product development principles in a real multi-project system.

Keywords: agile project management, multi project system, project lead time, product development

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46374 Multidimensional Item Response Theory Models for Practical Application in Large Tests Designed to Measure Multiple Constructs

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

Abstract:

This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

Procedia PDF Downloads 443
46373 Mobile Augmented Reality for Collaboration in Operation

Authors: Chong-Yang Qiao

Abstract:

Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: mobile augmented reality, remote collaboration, user experience, cognition model

Procedia PDF Downloads 197
46372 Modeling User Departure Time Choice for Trips in Urban Streets

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using questionnaire of stated preference models users’ departure time choice affected by congestion pricing plan in downtown Tehran. Experimental results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: modeling, departure time, travel timing, time of the day, congestion pricing, transportation planning

Procedia PDF Downloads 433
46371 Keyloggers Prevention with Time-Sensitive Obfuscation

Authors: Chien-Wei Hung, Fu-Hau Hsu, Chuan-Sheng Wang, Chia-Hao Lee

Abstract:

Nowadays, the abuse of keyloggers is one of the most widespread approaches to steal sensitive information. In this paper, we propose an On-Screen Prompts Approach to Keyloggers (OSPAK) and its analysis, which is installed in public computers. OSPAK utilizes a canvas to cue users when their keystrokes are going to be logged or ignored by OSPAK. This approach can protect computers against recoding sensitive inputs, which obfuscates keyloggers with letters inserted among users' keystrokes. It adds a canvas below each password field in a webpage and consists of three parts: two background areas, a hit area and a moving foreground object. Letters at different valid time intervals are combined in accordance with their time interval orders, and valid time intervals are interleaved with invalid time intervals. It utilizes animation to visualize valid time intervals and invalid time intervals, which can be integrated in a webpage as a browser extension. We have tested it against a series of known keyloggers and also performed a study with 95 users to evaluate how easily the tool is used. Experimental results made by volunteers show that OSPAK is a simple approach.

Keywords: authentication, computer security, keylogger, privacy, information leakage

Procedia PDF Downloads 122
46370 Novel Recommender Systems Using Hybrid CF and Social Network Information

Authors: Kyoung-Jae Kim

Abstract:

Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 289
46369 Tsada-MobiMinder: A Location Based Alarm Mobile Reminder

Authors: Marylene S. Eder

Abstract:

Existing location based alarm applications has inability to give information to user’s particular direction to a specified place of destination and does not display a particular scenic spot from its current location going to the destination. With this problem, a location based alarm mobile reminder was developed. The application is implemented on Android based smart phones to provide services like providing routing information, helping to find nearby hotels, restaurants and scenic spots and offer many advantages to the mobile users to retrieve the information about their current location and process that data to get more useful information near to their location. It reminds the user about the location when the user enters some predefined location. All the user needs to have is the mobile phone with android platform with version 4.0 and above, and then the user can select the destination and find the destination on the application. The main objective of the project is to develop a location based application that provides tourists with real time information for scenic spots and provides alarm to a specified place of destination. This mobile application service will act as assistance for the frequent travelers to visit new places around the City.

Keywords: location based alarm, mobile application, mobile reminder, tourist’s spots

Procedia PDF Downloads 382
46368 Mobility-Aware Relay Selection in Two Hop Unmanned Aerial Vehicles Network

Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

Abstract:

Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

Procedia PDF Downloads 238
46367 Using Deep Learning Real-Time Object Detection Convolution Neural Networks for Fast Fruit Recognition in the Tree

Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

Abstract:

Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

Procedia PDF Downloads 420
46366 Quantile Coherence Analysis: Application to Precipitation Data

Authors: Yaeji Lim, Hee-Seok Oh

Abstract:

The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

Procedia PDF Downloads 390
46365 Vibration Control of Building Using Multiple Tuned Mass Dampers Considering Real Earthquake Time History

Authors: Rama Debbarma, Debanjan Das

Abstract:

The performance of multiple tuned mass dampers to mitigate the seismic vibration of structures considering real time history data is investigated in this paper. Three different real earthquake time history data like Kobe, Imperial Valley and Mammoth Lake are taken in the present study. The multiple tuned mass dampers (MTMD) are distributed at each storey. For comparative study, single tuned mass damper (STMD) is installed at top of the similar structure. This study is conducted for a fixed mass ratio (5%) and fixed damping ratio (5%) of structures. Numerical study is performed to evaluate the effectiveness of MTMDs and overall system performance. The displacement, acceleration, base shear and storey drift are obtained for both combined system (structure with MTMD and structure with STMD) for all earthquakes. The same responses are also obtained for structure without damper system. From obtained results, it is investigated that the MTMD configuration is more effective for controlling the seismic response of the primary system with compare to STMD configuration.

Keywords: Earthquake, multiple tuned mass dampers, single tuned mass damper, Time history.

Procedia PDF Downloads 270
46364 Advances on the Understanding of Sequence Convergence Seen from the Perspective of Mathematical Working Spaces

Authors: Paula Verdugo-Hernandez, Patricio Cumsille

Abstract:

We analyze a first-class on the convergence of real number sequences, named hereafter sequences, to foster exploration and discovery of concepts through graphical representations before engaging students in proving. The main goal was to differentiate between sequences and continuous functions-of-a-real-variable and better understand concepts at an initial stage. We applied the analytic frame of mathematical working spaces, which we expect to contribute to extending to sequences since, as far as we know, it has only developed for other objects, and which is relevant to analyze how mathematical work is built systematically by connecting the epistemological and cognitive perspectives, and involving the semiotic, instrumental, and discursive dimensions.

Keywords: convergence, graphical representations, mathematical working spaces, paradigms of real analysis, real number sequences

Procedia PDF Downloads 143
46363 Analysis of Consumer Preferences for Housing in Saudi Arabia

Authors: Mohammad Abdulaziz Algrnas, Emma Mulliner

Abstract:

Housing projects have been established in Saudi Arabia, by both government and private construction companies, to meet the increasing demand from Saudi inhabitants across the country. However, the real estate market supply does not meet consumer preference requirements. Preferences normally differ depending on the consumer’s situation, such as the household’s sociological characteristics (age, household size and composition), resources (income, wealth, information and experience), tastes and priorities. Collecting information about consumer attitudes, preferences and perceptions is important for the real estate market in order to better understand housing demand and to ensure that this is met by appropriate supply. The aim of this paper is to identify consumer preferences for housing in Saudi Arabia. A quantitative closed-ended questionnaire was conducted with housing consumers in Saudi Arabia in order to gain insight into consumer needs, current household situation, preferences for a number of investigated housing attributes and consumers’ perceptions around the current housing problem. 752 survey responses were obtained and analysed in order to describe preferences for housing attributes and make comparisons between groups. Factor analysis was also conducted to identify and reduce the attributes. The results indicate a difference in preference according to the gender of the respondents and depending on their region of residence.

Keywords: housing attributes, Saudi Arabia, consumer preferences, housing preferences

Procedia PDF Downloads 541
46362 Efficient Subsurface Mapping: Automatic Integration of Ground Penetrating Radar with Geographic Information Systems

Authors: Rauf R. Hussein, Devon M. Ramey

Abstract:

Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.

Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation

Procedia PDF Downloads 92
46361 Smart Brain Wave Sensor for Paralyzed- a Real Time Implementation

Authors: U.B Mahadevswamy UBM, Siraj Ahmed Siraj

Abstract:

As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment. Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.

Keywords: Keywords:-Brainwave sensor , BMI, Brain scan, EEG, MCH

Procedia PDF Downloads 154
46360 A New Intelligent, Dynamic and Real Time Management System of Sewerage

Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

Abstract:

The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

Procedia PDF Downloads 299
46359 Pressure Losses on Realistic Geometry of Tracheobronchial Tree

Authors: Michaela Chovancova, Jakub Elcner

Abstract:

Real bronchial tree is very complicated piping system. Analysis of flow and pressure losses in this system is very difficult. Due to the complex geometry and the very small size in the lower generations is examination by CFD possible only in the central part of bronchial tree. For specify the pressure losses of lower generations is necessary to provide a mathematical equation. Determination of mathematical formulas for calculating the pressure losses in the real lungs is due to its complexity and diversity lengthy and inefficient process. For these calculations is necessary the lungs to slightly simplify (same cross-section over the length of individual generation) or use one of the models of lungs. The simplification could cause deviations from real values. The article compares the values of pressure losses obtained from CFD simulation of air flow in the central part of the real bronchial tree with the values calculated in a slightly simplified real lungs by using a mathematical relationship derived from the Bernoulli equation and continuity equation. Then, evaluate the desirability of using this formula to determine the pressure loss across the bronchial tree.

Keywords: pressure gradient, airways resistance, real geometry of bronchial tree, breathing

Procedia PDF Downloads 323