Search results for: Human machine interface

Authors: Hyun-Koo Kim, Young-Nam Shin, Sa-gong Kuk, Ju H. Park, Ho-Youl Jung

Abstract:

This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Keywords: Night-time traffic light detection, multi-class classification, driving assistance system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3890

Authors: R. B. Mishra

Abstract:

Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: BDI, HMM, neural activation, optimal states, working conditions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 873

Authors: Solvita Kampuse, Elga Berna, Sandra Muizniece-Brasava, Lija Dukalska, Irisa Murniece, Martins Sabovics, Zanda Kruma, Karina Ruse, Svetlana Sarvi, Kaspars Kampuss

Abstract:

Experiments with pumpkin-rowanberry marmalade candies were carried out at the Faculty of Food Technology of the Latvia University of Agriculture. The objective of this investigation was to evaluate the quality changes of pumpkin-rowanberry marmalade candies packed in different packaging materials during the storage of 15 weeks, and to find the most suitable packaging material for prolongation of low sugar marmalade candies shelf-life. An active packaging in combination with modified atmosphere (MAP, CO2 100%) was examined and compared with traditional packaging in air ambiance. Polymer Multibarrier 60 and paper bags were used. Influence of iron based oxygen absorber in sachets of 500 cc obtained from Mitsubishi Gas Chemical Europe Ageless® on the marmalade candies’ quality was tested during shelf life. Samples of 80±5 g were packaged in polymer pouches (110 mm x 110 mm), hermetically sealed by MULTIVAC C300 vacuum chamber machine, and stored in a room temperature +21±0.5 °C. The physiochemical properties –moisture content, hardness, aw, pH, changes of atmosphere content (CO2 and O2), ascorbic acid, total carotenoids, total phenols in headspace of packs, and microbial conditions were analysed before packaging and in the 1st, 3rd , 5th, 8th, 11th and 15th weeks of storage.

Keywords: Active packaging, marmalade candies, shelf life

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2789

Authors: Nicolò Vaiana, Mariacristina Spizzuoco, Giorgio Serino

Abstract:

In this paper, the results of experimental tests performed on a Helical Wire Rope Isolator (HWRI) are presented in order to describe the dynamic and static behavior of the selected metal device in three different displacements ranges, namely small, relatively large, and large displacements ranges, without and under the effect of a vertical load. A testing machine, allowing to apply horizontal displacement or load histories to the tested bearing with a constant vertical load, has been adopted to perform the dynamic and static tests. According to the experimental results, the dynamic behavior of the tested device depends on the applied displacement amplitude. Indeed, the HWRI displays a softening and a hardening stiffness at small and relatively large displacements, respectively, and a stronger nonlinear stiffening behavior at large displacements. Furthermore, the experimental tests reveal that the application of a vertical load allows to have a more flexible device with higher damping properties and that the applied vertical load affects much less the dynamic response of the metal device at large displacements. Finally, a decrease in the static to dynamic effective stiffness ratio with increasing displacement amplitude has been observed.

Keywords: Base isolation, earthquake engineering, experimental hysteresis loops, wire rope isolators.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1338

Authors: František Mošna

Abstract:

E-learning has become an efficient and widespread means of education at all levels of human activities. Statistics is no exception. Unfortunately the main focus in statistics teaching is usually paid to the substitution in formulas. Suitable websites can simplify and automate calculations and provide more attention and time to the basic principles of statistics, mathematization of real-life situations and following interpretation of results. We now introduce our own web-site for hypothesis testing. Its didactic aspects, the technical possibilities of the individual tools, the experience of use and the advantages or disadvantages are discussed in this paper. This web-site is not a substitute for common statistical software but should significantly improve the teaching of statistics at universities.

Keywords: E-learning, hypothesis testing, PHP, websites.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2355

Authors: M. D. Prokhorov, V. I. Ponomarenko, A. S. Karavaev, A. R. Kiselev, V. I. Gridnev

Abstract:

Synchronization between the slow oscillations of heart rate and blood pressure having in humans a basic frequency close to 0.1 Hz is investigated. A method is proposed for quantitative estimation of synchronization between these oscillating processes based on calculation of relative time of phase synchronization of oscillations. It is shown that healthy subjects exhibit in average substantially longer epochs of synchronization between the slow oscillations in heart rate and blood pressure than patients after acute myocardial infarction

Keywords: Cardiovascular system, slow oscillating processes, synchronization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1553

Authors: M. Soyaslan, A. Fenercioglu, C. Kozkurt

Abstract:

Automated storage and retrieval systems (AS/RS) become frequently used systems in warehouses. There has been a transition from human based forklift applications to fast and safe AS/RS applications in firm-s warehouse systems. In this study, basic components and automation systems of the AS/RS are examined. Proposed system's automation components and their tasks in the system control algorithm were stated. According to this control algorithm the control system structure was obtained.

Keywords: AS/RS, Automatic Storage and Retrieval System, Warehouse Control System

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3527

Authors: A. Bobirca, A. Draghici

Abstract:

The objective of this paper is to construct a creativity composite index designed to capture the growing role of creativity in driving economic and social development for the 27 European Union countries. The paper proposes a new approach for the measurement of EU-27 creative potential and for determining its capacity to attract and develop creative human capital. We apply a modified version of the 3T model developed by Richard Florida and Irene Tinagli for constructing a Euro-Creativity Index. The resulting indexes establish a quantitative base for policy makers, supporting their efforts to determine the contribution of creativity to economic development.

Keywords: European Creativity Index, talent, technology, tolerance

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2957

Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 550

Authors: Ashly Joseph

Abstract:

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 223

Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

Abstract:

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: Cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1168

Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

Abstract:

In this paper an effective approach for segmenting human skin regions in images taken at different environment is proposed. The proposed method uses a color distance map that is flexible enough to reliably detect the skin regions even if the illumination conditions of the image vary. Local image conditions is also focused, which help the technique to adaptively detect differently illuminated skin regions of an image. Moreover, usage of local information also helps the skin detection process to get rid of picking up much noisy pixels.

Keywords: Color Distance map, Reference skin color, Regiongrowing, Skin segmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2012

Authors: Sharan Badiger, Prema T. Akkasaligar

Abstract:

Medical imaging technology has experienced a dramatic change in the last few years. Medical imaging refers to the techniques and processes used to create images of the human body (or parts thereof) for various clinical purposes such as medical procedures and diagnosis or medical science including the study of normal anatomy and function. With the growth of computers and image technology, medical imaging has greatly influenced the medical field. The diagnosis of a health problem is now highly dependent on the quality and the credibility of the image analysis. This paper deals with the various aspects and types of medical imaging.

Keywords: Computed Tomography, Echocardiography, Medical Imaging, Magnetic Resonance, Ultrasound Imaging.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3574

Authors: Salma Siddika, Fayeka Mansura, Mahbub Hasan

Abstract:

The term hybrid composite refers to the composite containing more than one type of fiber material as reinforcing fillers. It has become attractive structural material due to the ability of providing better combination of properties with respect to single fiber containing composite. The eco-friendly nature as well as processing advantage, light weight and low cost have enhanced the attraction and interest of natural fiber reinforced composite. The objective of present research is to study the mechanical properties of jute-coir fiber reinforced hybrid polypropylene (PP) composite according to filler loading variation. In the present work composites were manufactured by using hot press machine at four levels of fiber loading (5, 10, 15 and 20 wt %). Jute and coir fibers were utilized at a ratio of (1:1) during composite manufacturing. Tensile, flexural, impact and hardness tests were conducted for mechanical characterization. Tensile test of composite showed a decreasing trend of tensile strength and increasing trend of the Young-s modulus with increasing fiber content. During flexural, impact and hardness tests, the flexural strength, flexural modulus, impact strength and hardness were found to be increased with increasing fiber loading. Based on the fiber loading used in this study, 20% fiber reinforced composite resulted the best set of mechanical properties.

Keywords: Mechanical Properties; Coir, Jute, Polypropylene, Hybrid Composite.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3704

Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

Abstract:

Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees’ skill efficiently. This study is focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increasing. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, Job Satisfaction, Learning and growth.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2388

Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 531

Authors: Sakthi Priya Balaji R., Vijayendar G.

Abstract:

This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1402

Authors: Lise P. Labéjof, Krisnayne S. Ribeiro, Jackson A. Santos, Nicolle P. dos Santos

Abstract:

An unrecorded experiment of use of the smartphone as a tool for practical classes of histology is presented in this paper. Behavior and learning of students of science courses at the University were analyzed and compared as well as the mode of teaching of this discipline and the appreciation of the students, using either digital photographs taken by phone or drawings for record microscopic observations, analyze and interpret histological sections of human or animal tissues.

Keywords: Cell phone, digital micrographs, learning of sciences, teaching practices.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1705

Authors: Ghassan Kbar, Shady Aly, Ibraheem Elsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

Abstract:

The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: Ambient Intelligence, ICT, Persons with disability PWD, Smart application.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2542

Authors: Dyah P. Srirahayu, Esti Putri Anugrah, Amelia Firdaus

Abstract:

The existence of the current library has met the complex needs of users. However, human resources in the library are often a source of problems in service. This is influenced by the leadership style in each library. This study aims to analyze the impact of leadership style on innovative work behavior. The research method used is a quantitative approach to analyze using SPSS. The findings in this study illustrate that leadership style has an influence on innovative work behavior which is certainly influenced by various existing factors.

Keywords: Leadership, public libraries, innovative behavior, Transactional leadership.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 874

Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1742

Authors: Shuki Dror

Abstract:

This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

Keywords: HOQ, organizational features, service quality.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1871

Authors: Smah Doeban Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2021, until April 4, 2021. Natural language processing (NLP), which is a form of Artificial intelligent was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applied machine learning sentimental method such as Crystal Feel and extended the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 591

Authors: S. Benhamed, S. Hocine, D. Benhamamouch

Abstract:

We try to give a solution of version control for documents in web service, that-s why we propose a new approach used specially for the XML documents. The new approach is applied in a centralized repository, this repository coexist with other repositories in a decentralized system. To achieve the activities of this approach in a standard model we use the ECA active rules. We also show how the Event-Condition-Action rules (ECA rules) have been incorporated as a mechanism for the version control of documents. The need to integrate ECA rules is that it provides a clear declarative semantics and induces an immediate operational realization in the system without the need for human intervention.

Keywords: ECA Rule, Web service, version control system, propagation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1375

Authors: Sky Chou, Joseph C. Chen

Abstract:

This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, Six Sigma, Surface roughness, Taguchi methodology.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1060

Authors: A. Soualem

Abstract:

Springback is a significant problem in the sheet metal forming process. When the tools are released after the stage of forming, the product springs out, because of the action of the internal stresses. In many cases the deviation of form is too large and the compensation of the springback is necessary. The precise prediction of the springback of product is increasingly significant for the design of the tools and for compensation because of the higher ratio of the yield stress to the elastic modulus. The main object in this paper was to study the effect of the anisotropy on the springback for three directions of rolling: 0°, 45° and 90°. At the same time, we highlighted the influence of three different metallic materials: Aluminum, Steel and Galvanized steel. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback according to the direction of rolling. We also showed the role of lubrication in the reduction of the springback. Moreover, in this work, we have studied important characteristics in deep drawing process which is a springback. We have presented defaults that are showed in this process and many parameters influenced a springback. Finally, our results works lead us to understand the influence of grains orientation with different metallic materials on the springback and drawing some conclusions how to concept deep drawing tools. In addition, the conducted work represents a fundamental contribution in the discussion the industry application.

Keywords: Deep-Drawing, Grains orientation, Laminate Tool, Springback.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2092

Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Abstract:

Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: Binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 734

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1863

Authors: Zukisa Nante, Wang Zenghui

Abstract:

Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.

Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 516

Authors: Aleš Florian, Lenka Ševelová

Abstract:

Low volume roads are widely used all over the world. To improve their quality the computer simulation of their behavior is proposed. The FEM model enables to determine stress and displacement conditions in the pavement and/or also in the particular material layers. Different variants of pavement layers, material used, humidity as well as loading conditions can be studied. Among others, the input information about material properties of individual layers made from recycled materials is crucial for obtaining results as exact as possible. For this purpose the cyclic-load triaxial test machine testing of cyclic-load performance of materials is a promising test method. The test is able to simulate the real traffic loading on particular materials taking into account the changes in the horizontal stress conditions produced in particular layers by crossings of vehicles. Also the test specimen can be prepared with different amount of water. Thus modulus of elasticity (Young modulus) of different materials including recycled ones can be measured under the different conditions of horizontal and vertical stresses as well as under the different humidity conditions. Using the proposed testing procedure the modulus of elasticity of recycled materials used in the newly built low volume road is obtained under different stress and humidity conditions set to standard, dry and fully saturated level. Obtained values of modulus of elasticity are used in FEA.

Keywords: FEA, FEM, geotechnical materials, low volume roads, pavement, triaxial test, Young modulus.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1631