Search results for: real estate pricing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5556

Search results for: real estate pricing

2796 A Model for Optimizing Inventory Replenishment and Shelf Space Management in Retail Industries

Authors: Nermine A. Harraz, Aliaa Abouali

Abstract:

The retail stores put up for sale multiple items while the spaces in the backroom and display areas constitute a scarce resource. Availability, volume, and location of the product displayed in the showroom influence the customer’s demand. Managing these operations individually will result in sub-optimal overall retail store’s profit; therefore, a non-linear integer programming model (NLIP) is developed to determine the inventory replenishment and shelf space allocation decisions that together maximize the retailer’s profit under shelf space and backroom storage constraints taking into consideration that the demand rate is positively dependent on the amount and location of items displayed in the showroom. The developed model is solved using LINGO® software. The NLIP model is implemented in a real world case study in a large retail outlet providing a large variety of products. The proposed model is validated and shows logical results when using the experimental data collected from the market.

Keywords: retailing management, inventory replenishment, shelf space allocation, showroom, backroom

Procedia PDF Downloads 354
2795 Estimating Occupancy in Residential Context Using Bayesian Networks for Energy Management

Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

Abstract:

A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

Procedia PDF Downloads 372
2794 Fuzzy Inference System for Risk Assessment Evaluation of Wheat Flour Product Manufacturing Systems

Authors: Yas Barzegaar, Atrin Barzegar

Abstract:

The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

Procedia PDF Downloads 104
2793 Weighted Rank Regression with Adaptive Penalty Function

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

Procedia PDF Downloads 478
2792 A Novel RLS Based Adaptive Filtering Method for Speech Enhancement

Authors: Pogula Rakesh, T. Kishore Kumar

Abstract:

Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

Procedia PDF Downloads 485
2791 Data Security: An Enhancement of E-mail Security Algorithm to Secure Data Across State Owned Agencies

Authors: Lindelwa Mngomezulu, Tonderai Muchenje

Abstract:

Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.

Keywords: e-mail security, cyber-attacks, data integrity, authentication

Procedia PDF Downloads 138
2790 Operating System Based Virtualization Models in Cloud Computing

Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

Abstract:

Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

Procedia PDF Downloads 332
2789 Intelligent Earthquake Prediction System Based On Neural Network

Authors: Emad Amar, Tawfik Khattab, Fatma Zada

Abstract:

Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

Procedia PDF Downloads 498
2788 Shifting of Global Energy Security: A Comparative Analysis of Indonesia and China’s Renewable Energy Policies

Authors: Widhi Hanantyo Suryadinata

Abstract:

Efforts undertaken by Indonesia and China to shift the strategies and security of renewable energy on a global stage involve approaches through policy construction related to rare minerals processing or value-adding in Indonesia and manufacturing policies through the New Energy Vehicles (NEVs) policy in China. Both policies encompass several practical regulations and policies that can be utilized for the implementation of Indonesia and China's grand efforts and ideas. Policy development in Indonesia and China can be analyzed using a comparative analysis method, as well as employing a pyramid illustration to identify policy construction phases based on the real conditions of the domestic market and implemented policies. This approach also helps to identify the potential integration of policies needed to enhance the policy development phase of a country within the pyramid. It also emphasizes the significance of integration policy to redefine renewable energy strategy and security on the global stage.

Keywords: global renewable energy security, global energy security, policy development, comparative analysis, shifting of global energy security, Indonesia, China

Procedia PDF Downloads 74
2787 Tourism in the Information Age

Authors: Suleyman Karacor

Abstract:

The main purpose of this study is to investigate tourism marketing in the information age because of the importance and sensitivity. In the twenty-first century as a result of today's the increasing competition and product diversification in the tourism sector, tourism businesses must take into account exogenous variables such as new technological developments, commercial experience and consumer demand. In the information age, tourist product consumers tend to reserve their leisure time and expenditure on more active opportunities for different experiences instead of living the same experience again. Increasing the number of agents in the tourism sector, travel opportunities offering different experiences and more intensive use of modern technology helps to present diversification of leisure activities for tourists. From the perspective of tourists, travel costs are still important for buying the touristic products but maintaining a high level of tourist satisfaction is also of increasing importance. Tourists tend to prefer activities that add value. A real tourist product must be able to create value and new priorities for tourists. Therefore this study aims to review recent significant developments in international tourism marketing research and practices. To this end, this study reviews tourism marketing-focused articles.

Keywords: information age, tourism marketing, tourism marketing mix, management

Procedia PDF Downloads 427
2786 Detection of Image Blur and Its Restoration for Image Enhancement

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

Procedia PDF Downloads 290
2785 Psychological Reactance to Anti-Piracy Messages Explained by Gender and Attitudes

Authors: Kate Whitman, Zahra Murad, Joe Cox

Abstract:

Digital piracy is costly to creative economies across the world. Anti-piracy messages can cause people to pirate more rather than less, suggesting the presence of psychological reactance. Gender differences in message reactance and the moderating impact of attitudes have not been explored. In this paper, we examine whether messages based on real-world anti-piracy campaigns cause reactance and whether this effect is explained by gender and attitudes. An experiment compares two threatening and one prosocial message against a control group, with changes in piracy intention from past behavior for digital TV/film analysed. The results suggest that the prosocial message is ineffective for both genders. However, the threatening messages have significantly opposing effects on men and women. One threatening message influences women to reduce their piracy intentions by over 50% and men to increase it by 18%. Gender effects are moderated by pre-existing attitudes, with men and women who report the most favorable attitudes towards piracy having the most polarised changes in piracy intentions. The results suggest that men and women process threatening messages differently and that the creative industries should take care when targeting their messages.

Keywords: piracy, reactance, persuasive-messages, TV/film, gender

Procedia PDF Downloads 101
2784 The Way We Express vs. What We Express

Authors: Brendan Mooney

Abstract:

We often do not consider the quality of the way we express ourselves as being fundamental to well-being. Society focuses predominantly on what we do, not the way we do it, to our great detriment. For example, those who have experienced domestic violence often comment that it was not what was said that hurt the most but the way it was said. In other words, the quality in the way the words were used communicated far more than the actual words themselves. This is an important area of focus for practitioners who may be inclined to emphasize who said what but not bring equal, if not more, focus to the quality of one’s expression. The aim of this study is to highlight how and why the way we express ourselves is more important than what we express, which includes words and all behaviors. Given we are a sensitive species it matters to pay attention to the communication that is not said. For example, we have the ability to recognize that a person is upset or angry by the way they walk into a room, even if they do not say anything or look at anyone. Our sensitivity allows us to detect even the slightest change in another’s emotional state, irrespective of what their exterior behaviors may be exhibiting. This study will focus on the importance of recognizing the quality in the way we express as being fundamental to wellbeing, as it allows us to easily and simply navigate life and relationships without needing to experience the usual pitfalls that otherwise prevail. This research utilizes clinical experience, client observations and client feedback, and several case studies were utilized to illustrate real-life examples of the above. This study is not so much a model of life but a way of life that confirms our deepest nature, that we are incredibly sensitive and far more so than we appreciate or utilize in everyday practical human life.

Keywords: communication, integrity, quality, sensitivity, wellbeing

Procedia PDF Downloads 37
2783 Holomorphic Prioritization of Sets within Decagram of Strategic Decision Making of POSM Using Operational Research (OR): Analytic Hierarchy Process (AHP) Analysis

Authors: Elias Ogutu Azariah Tembe, Hussain Abdullah Habib Al-Salamin

Abstract:

There is decagram of strategic decisions of operations and production/service management (POSM) within operational research (OR) which must collate, namely: design, inventory, quality, location, process and capacity, layout, scheduling, maintain ace, and supply chain. This paper presents an architectural configuration conceptual framework of a decagram of sets decisions in a form of mathematical complete graph and abelian graph. Mathematically, a complete graph is undirected (UDG), and directed (DG) a relationship where every pair of vertices are connected, collated, confluent, and holomorphic. There has not been any study conducted which, however, prioritizes the holomorphic sets which of POMS within OR field of study. The study utilizes OR structured technique known as The Analytic Hierarchy Process (AHP) analysis for organizing, sorting and prioritizing (ranking) the sets within the decagram of POMS according to their attribution (propensity), and provides an analysis how the prioritization has real-world application within the 21st century.

Keywords: holomorphic, decagram, decagon, confluent, complete graph, AHP analysis, SCM, HRM, OR, OM, abelian graph

Procedia PDF Downloads 404
2782 Automatic Thresholding for Data Gap Detection for a Set of Sensors in Instrumented Buildings

Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

Abstract:

Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

Procedia PDF Downloads 248
2781 PostureCheck with the Kinect and Proficio: Posture Modeling for Exercise Assessment

Authors: Elham Saraee, Saurabh Singh, Margrit Betke

Abstract:

Evaluation of a person’s posture while exercising is important in physical therapy. During a therapy session, a physical therapist or a monitoring system must assure that the person is performing an exercise correctly to achieve the desired therapeutic effect. In this work, we introduce a system called POSTURECHECK for exercise assessment in physical therapy. POSTURECHECK assesses the posture of a person who is exercising with the Proficio robotic arm while being recorded by the Microsoft Kinect interface. POSTURECHECK extracts unique features from the person’s upper body during the exercise, and classifies the sequence of postures as correct or incorrect using Bayesian estimation and majority voting. If POSTURECHECK recognizes an incorrect posture, it specifies what the user can do to correct it. The result of our experiment shows that POSTURECHECK is capable of recognizing the incorrect postures in real time while the user is performing an exercise.

Keywords: Bayesian estimation, majority voting, Microsoft Kinect, PostureCheck, Proficio robotic arm, upper body physical therapy

Procedia PDF Downloads 285
2780 Analyzing the Significance of Online Purchase Behavior of Tourists for the Development of Online Travel Bookings

Authors: April C. Abalos, Marmie R. Poquiz, Paul Nigel S. Abalos

Abstract:

With the advent of the fourth industrial revolution, everything is becoming possible with just a single click through the internet. What is more exciting is that through the power of the technological advancements, options are readily available in one’s fingertips. These technological advancements have greatly affected the perspectives of people in almost all human endeavors, even in their purchasing behavior. Hence, this study is conceptualized. This aims to identify the significance of the online purchase behavior of tourists for the development of travel bookings and provide knowledge to sellers and understanding major factors towards the online purchase behavior of tourists. Social media applications in booking online were also identified, as well as the profile and the marketing strategies influencing the behavior of individuals in an online travel booking. This study also sought to determine which behavioral intention should be given more attention to know where to exert more effort in winning the hearts of consumers. This study used a descriptive-survey design using an online survey questionnaire to gather real-time responses from the tourists visiting and/or planning to visit the scenic spots in the province of Pangasinan, which are highly reliable to formulate conclusions as deemed necessary.

Keywords: behavior, online purchase, tourists, travel bookings

Procedia PDF Downloads 131
2779 In vivo Evaluation of LAB Probiotic Potential with the Zebrafish Animal Model

Authors: Iñaki Iturria, Pasquale Russo, Montserrat Nacher-Vázquez, Giuseppe Spano, Paloma López, Miguel Angel Pardo

Abstract:

Introduction: It is known that some Lactic Acid Bacteria (LAB) present an interesting probiotic effect. Probiotic bacteria stimulate host resistance to microbial pathogens and thereby aid in immune response, and modulate the host's immune responses to antigens with a potential to down-regulate hypersensitivity reactions. Therefore, probiotic therapy is valuable against intestinal infections and may be beneficial in the treatment of Inflammatory Bowel Disease (IBD). Several in vitro tests are available to evaluate the probiotic potential of a LAB strain. However, an in vivo model is required to understand the interaction between the host immune system and the bacteria. During the last few years, zebrafish (Danio rerio) has gained interest as a promising vertebrate model in this field. This organism has been extensively used to study the interaction between the host and the microbiota, as well as the host immune response under several microbial infections. In this work, we report on the use of the zebrafish model to investigate in vivo the colonizing ability and the immunomodulatory effect of probiotic LAB. Methods: Lactobacillus strains belonging to different LAB species were fluorescently tagged and used to colonize germ-free zebrafish larvae gastrointestinal tract (GIT). Some of the strains had a well-documented probiotic effect (L. acidophilus LA5); while others presented an exopolysaccharide (EPS) producing phenotype, thus allowing evaluating the influence of EPS in the colonization and immunomodulatory effect. Bacteria colonization was monitored for 72 h by direct observation in real time using fluorescent microscopy. CFU count per larva was also evaluated at different times. The immunomodulatory effect was assessed analysing the differential expression of several innate immune system genes (MyD88, NF-κB, Tlr4, Il1β and Il10) by qRT- PCR. The anti-inflammatory effect was evaluated using a chemical enterocolitis zebrafish model. The protective effect against a pathogen was also studied. To that end, a challenge test was developed using a fluorescently tagged pathogen (Vibrio anguillarum-GFP+). The progression of the infection was monitored up to 3 days using a fluorescent stereomicroscope. Mortality rates and CFU counts were also registered. Results and conclusions: Larvae exposed to EPS-producing bacteria showed a higher fluorescence and CFU count than those colonized with no-EPS phenotype LAB. In the same way, qRT-PCR results revealed an immunomodulatory effect on the host after the administration of the strains with probiotic activity. A downregulation of proinflammatory cytoquines as well as other cellular mediators of inflammation was observed. The anti-inflammatory effect was found to be particularly marked following exposure to LA% strain, as well as EPS producing strains. Furthermore, the challenge test revealed a protective effect of probiotic administration. As a matter of fact, larvae fed with probiotics showed a decrease in the mortality rate ranging from 20 to 35%. Discussion: In this work, we developed a promising model, based on the use of gnotobiotic zebrafish coupled with a bacterial fluorescent tagging in order to evaluate the probiotic potential of different LAB strains. We have successfully used this system to monitor in real time the colonization and persistence of exogenous LAB within the gut of zebrafish larvae, to evaluate their immunomodulatory effect and for in vivo competition assays. This approach could bring further insights into the complex microbial-host interactions at intestinal level.

Keywords: gnotobiotic, immune system, lactic acid bacteria, probiotics, zebrafish

Procedia PDF Downloads 332
2778 Artificial Intelligence and Distributed System Computing: Application and Practice in Real Life

Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

Abstract:

In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

Procedia PDF Downloads 114
2777 Platform-as-a-Service Sticky Policies for Privacy Classification in the Cloud

Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani

Abstract:

In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy

Procedia PDF Downloads 228
2776 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

Procedia PDF Downloads 341
2775 Parametric Study of Ball and Socket Joint for Bio-Mimicking Exoskeleton

Authors: Mukesh Roy, Basant Singh Sikarwar, Ravi Prakash, Priya Ranjan, Ayush Goyal

Abstract:

More than 11% of people suffer from weakness in the bone resulting in inability in walking or climbing stairs or from limited upper body and limb immobility. This motivates a fresh bio-mimicking solution to the design of an exo-skeleton to support human movement in the case of partial or total immobility either due to congenital or genetic factors or due to some accident or due to geratological factors. A deeper insight and detailed understanding is required into the workings of the ball and socket joints. Our research is to mimic ball and socket joints to design snugly fitting exoskeletons. Our objective is to design an exoskeleton which is comfortable and the presence of which is not felt if not in use. Towards this goal, a parametric study is conducted to provide detailed design parameters to fabricate an exoskeleton. This work builds up on real data of the design of the exoskeleton, so that the designed exo-skeleton will be able to provide required strength and support to the subject.

Keywords: bio-mimicking, exoskeleton, ball joint, socket joint, artificial limb, patient rehabilitation, joints, human-machine interface, wearable robotics

Procedia PDF Downloads 296
2774 EnumTree: An Enumerative Biclustering Algorithm for DNA Microarray Data

Authors: Haifa Ben Saber, Mourad Elloumi

Abstract:

In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of constant rows with a group of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. We introduce a new algorithm called, Enumerative tree (EnumTree) for biclustering of binary microarray data. is an algorithm adopting the approach of enumerating biclusters. This algorithm extracts all biclusters consistent good quality. The main idea of ​​EnumLat is the construction of a new tree structure to represent adequately different biclusters discovered during the process of enumeration. This algorithm adopts the strategy of all biclusters at a time. The performance of the proposed algorithm is assessed using both synthetic and real DNA micryarray data, our algorithm outperforms other biclustering algorithms for binary microarray data. Biclusters with different numbers of rows. Moreover, we test the biological significance using a gene annotation web tool to show that our proposed method is able to produce biologically relevent biclusters.

Keywords: DNA microarray, biclustering, gene expression data, tree, datamining.

Procedia PDF Downloads 372
2773 Improved Acoustic Source Sensing and Localization Based On Robot Locomotion

Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

Abstract:

This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

Procedia PDF Downloads 494
2772 Performance Evaluation of Discrete Fourier Transform Algorithm Based PMU for Wide Area Measurement System

Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

Abstract:

Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of Supervisory Control and Data Acquisition System (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide Area Measurement System (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of MATLAB based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: GPS global positioning system, PMU phasor measurement system, WAMS wide area monitoring system, DFT, PDC

Procedia PDF Downloads 497
2771 Development of Web Application for Warehouse Management System: A Case Study of Ceramics Factory

Authors: Thanaphat Suwanaklang, Supaporn Suwannarongsri

Abstract:

Presently, there are many industries in Thailand producing various products for both domestic distribution and export to foreign countries. Warehouse is one of the most important areas of business needing to store their products. Such businesses need to have a suitable warehouse management system for reducing the storage time and using the space as much as possible. This paper proposes the development of a web application for a warehouse management system. One of the ceramics factories in Thailand is conducted as a case study. By applying the ABC analysis, fixed location, commodity system, ECRS, and 7-waste theories and principles, the web application for the warehouse management system of the selected ceramics factory is developed to design the optimal storage area for groups of products and design the optimal routes of forklifts. From experimental results, it was found that the warehouse management system developed via the web application can reduce the travel distance of forklifts and the time of searching for storage area by 100% once compared with the conventional method. In addition, the entire storage area can be on-line and real-time monitored.

Keywords: warehouse management system, warehouse design method, logistics system, web application

Procedia PDF Downloads 137
2770 A Critical Knowledge of Brand Equity in Thai Academic Works

Authors: Pongsiri Kamkankaew

Abstract:

This paper experiments to consider brand equity thought in Thai academic works. This essay employs that the first emerging of brand equity in Thai academic works and the components of brand equity which explore the extent to the convoluted approach with other Thai social condition. In Thailand, brand equity is supposed to provide branding and brand management replacement. However, the commitment of brand equity imposes in its proposal for seemly application in Thai context – to develop the brand equity framework by the Thai social – culture and Thai utilization style which it is questionable whether the brand equity in western conception is useful for characterizing the brand equity in Thailand context. In this position, brand equity also aspects several major questions: How can western conception lead to apply in Thai business? How can diversification be given within Thai SMEs business running? Can corporate brand valuation approach adopt in real business doing? So this paper argues that Thai brand equity notion should reduce disturb over improvement of its self-restraint and business area. Instead, Thai academic who are interested in brand equity can harmonize different mature bodies of discipline and other investigative a frame of references to complete and open the recognizing of brand equity.

Keywords: Thai brand equity, knowledge critical, brand management, branding

Procedia PDF Downloads 327
2769 A Comparative Analysis on QRS Peak Detection Using BIOPAC and MATLAB Software

Authors: Chandra Mukherjee

Abstract:

The present paper is a representation of the work done in the field of ECG signal analysis using MATLAB 7.1 Platform. An accurate and simple ECG feature extraction algorithm is presented in this paper and developed algorithm is validated using BIOPAC software. To detect the QRS peak, ECG signal is processed by following mentioned stages- First Derivative, Second Derivative and then squaring of that second derivative. Efficiency of developed algorithm is tested on ECG samples from different database and real time ECG signals acquired using BIOPAC system. Firstly we have lead wise specified threshold value the samples above that value is marked and in the original signal, where these marked samples face change of slope are spotted as R-peak. On the left and right side of the R-peak, faces change of slope identified as Q and S peak, respectively. Now the inbuilt Detection algorithm of BIOPAC software is performed on same output sample and both outputs are compared. ECG baseline modulation correction is done after detecting characteristics points. The efficiency of the algorithm is tested using some validation parameters like Sensitivity, Positive Predictivity and we got satisfied value of these parameters.

Keywords: first derivative, variable threshold, slope reversal, baseline modulation correction

Procedia PDF Downloads 412
2768 On Dynamic Chaotic S-BOX Based Advanced Encryption Standard Algorithm for Image Encryption

Authors: Ajish Sreedharan

Abstract:

Security in transmission and storage of digital images has its importance in today’s image communications and confidential video conferencing. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. Advanced Encryption Standard (AES) is a well known block cipher that has several advantages in data encryption. However, it is not suitable for real-time applications. This paper presents modifications to the Advanced Encryption Standard to reflect a high level security and better image encryption. The modifications are done by adjusting the ShiftRow Transformation and using On Dynamic chaotic S-BOX. In AES the Substitute bytes, Shift row and Mix columns by themselves would provide no security because they do not use the key. In Dynamic chaotic S-BOX Based AES the Substitute bytes provide security because the S-Box is constructed from the key. Experimental results verify and prove that the proposed modification to image cryptosystem is highly secure from the cryptographic viewpoint. The results also prove that with a comparison to original AES encryption algorithm the modified algorithm gives better encryption results in terms of security against statistical attacks.

Keywords: advanced encryption standard (AES), on dynamic chaotic S-BOX, image encryption, security analysis, ShiftRow transformation

Procedia PDF Downloads 437
2767 On the Algorithmic Iterative Solutions of Conjugate Gradient, Gauss-Seidel and Jacobi Methods for Solving Systems of Linear Equations

Authors: Hussaini Doko Ibrahim, Hamilton Cyprian Chinwenyi, Henrietta Nkem Ude

Abstract:

In this paper, efforts were made to examine and compare the algorithmic iterative solutions of the conjugate gradient method as against other methods such as Gauss-Seidel and Jacobi approaches for solving systems of linear equations of the form Ax=b, where A is a real n×n symmetric and positive definite matrix. We performed algorithmic iterative steps and obtained analytical solutions of a typical 3×3 symmetric and positive definite matrix using the three methods described in this paper (Gauss-Seidel, Jacobi, and conjugate gradient methods), respectively. From the results obtained, we discovered that the conjugate gradient method converges faster to exact solutions in fewer iterative steps than the two other methods, which took many iterations, much time, and kept tending to the exact solutions.

Keywords: conjugate gradient, linear equations, symmetric and positive definite matrix, gauss-seidel, Jacobi, algorithm

Procedia PDF Downloads 152