Search results for: cross-validation support vector machine

Authors: Leszek Szpakowski, Daniel Celiński, Sławomir Pilip, Grzegorz Michalak

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The aim of the study was to analyse the usefulness of the 'E-rescuer' pilot project planned to be implemented in a chosen area of Eastern Poland in the cases of suspected sudden cardiac arrests in the extra-urban areas. Inventing an application allowing to dispatch simultaneously both Medical Emergency Teams and the E-rescuer to the place of the accident is the crucial assumption of the mentioned pilot project. The E-rescuer is defined to be the trained person able to take effective basic life support and to use automated external defibrillator. Having logged in using a smartphone, the E-rescuer's readiness is reported online to provide cardiopulmonary resuscitation exactly at the given location. Due to the accurately defined location of the E-rescuer, his arrival time is possible to be precisely fixed, and the substantive support through the displayed algorithms is capable of being provided as well. Having analysed the medical records in the years 2015-2016, cardiopulmonary resuscitation was considered to be effective when an early indication of circulation was provided, and the patient was taken to hospital. In the mentioned term, there were 2.291 cases of a sudden cardiac arrest. Cardiopulmonary resuscitation was taken in 621 patients in total including 205 people in the urban area and 416 in the extra-urban areas. The effectiveness of cardiopulmonary resuscitation in the extra-urban areas was much lower (33,8%) than in the urban (50,7%). The average ambulance arrival time was respectively longer in the extra-urban areas, and it was 12,3 minutes while in the urban area 3,3 minutes. There was no significant difference in the average age of studied patients - 62,5 and 64,8 years old. However, the average ambulance arrival time was 7,6 minutes for effective resuscitations and 10,5 minutes for ineffective ones. Hence, the ambulance arrival time is a crucial factor influencing on the effectiveness of cardiopulmonary resuscitation, especially in the extra-urban areas where it is much longer than in the urban. The key role of trained E-rescuers being nearby taking basic life support before the ambulance arrival can effectively support Emergency Medical Services System in Poland.

Keywords: basic life support, bystander, effectiveness, resuscitation

Procedia PDF Downloads 182

Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

Procedia PDF Downloads 492

Authors: Liying Li, Han Guo

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Considering the environmental issues generated by the building sector for its energy consumption, solid waste generation, water use, land use, and global greenhouse gas (GHG) emissions, this review pointed out to LCA as a decision-support tool to substantially improve the sustainability in the building and construction industry. The comprehensiveness and simplicity of LCA make it one of the most promising decision support tools for the sustainable design and construction of future buildings. This paper contains a comprehensive review of existing studies related to LCAs with a focus on their advantages and limitations when applied in the building sector. The aim of this paper is to enhance the understanding of a building life-cycle analysis, thus promoting its application for effective, sustainable building design and construction in the future. Comparisons and discussions are carried out between four categories of LCA methods: building material and component combinations (BMCC) vs. the whole process of construction (WPC) LCA，attributional vs. consequential LCA, process-based LCA vs. input-output (I-O) LCA, traditional vs. hybrid LCA. Classical case studies are presented, which illustrate the effectiveness of LCA as a tool to support the decisions of practitioners in the design and construction of sustainable buildings. (i) BMCC and WPC categories of LCA researches tend to overlap with each other, as majority WPC LCAs are actually developed based on a bottom-up approach BMCC LCAs use. (ii) When considering the influence of social and economic factors outside the proposed system by research, a consequential LCA could provide a more reliable result than an attributional LCA. (iii) I-O LCA is complementary to process-based LCA in order to address the social and economic problems generated by building projects. (iv) Hybrid LCA provides a more superior dynamic perspective than a traditional LCA that is criticized for its static view of the changing processes within the building’s life cycle. LCAs are still being developed to overcome their limitations and data shortage (especially data on the developing world), and the unification of LCA methods and data can make the results of building LCA more comparable and consistent across different studies or even countries.

Keywords: decision support tool, life-cycle analysis, LCA tools and data, sustainable building design

Procedia PDF Downloads 102

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

Procedia PDF Downloads 307

Authors: Blerim Olluri

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A forensic science laboratory in Kosovo has never been organized at the level of most modern forensic science laboratories. This was made possible after the war of 1999 with the help and support from the United States. The United States Government/ICITAP provided 9.5 million dollars to support this project, this support have greatly benefitted law enforcement in Kosovo. With the establishment of Operative Procedures of Work and the law for Kosovo Agency of Forensic, the accreditation with ISO/IEC 17025 of the KAF labs it becomes mandatory. Since 2012 Laboratory’s DNA/Serology and Narcotics has begun reviewing and harmonizing their procedures according to ISO/IEC 17025. The focus of this work was to create quality manuals, procedures, work instructions, quality documentation and quality records. Furthermore, during this time is done the validation of work methods from scientific qualified personnel of KAF, without any help from other foreign agencies or accreditation body.In October 2014 we had the first evaluation based on ISO 17025 standards. According to the initial report of this assessment we have non conformity in test and Calibration methods method’s, and accommodation and environmental conditions. We identified several issues that are of extreme importance to KAF. One the most important issue is to create a professional group with experts of KAF, which will work in all the obligations, requested from ISO/IEC 17025. As conclusions that we earn in this path of accreditation, are that laboratory’s need to take corrective action, and all nonconformance’s must be addressed and corrective action taken before accreditation can be granted.

Keywords: accreditation, assessment, narcotics, DNA

Procedia PDF Downloads 354

Authors: Joseph Salim

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This paper proposes the development of a supervised machine learning system to predict the consequences of untreated bruxism (teeth grinding) on gingival (gum) recession and jaw pain (most often bilateral jaw pain with possible headaches and limited ability to open the mouth). As a general dentist in a multi-specialty practice, the author has encountered many patients suffering from these issues due to uncontrolled bruxism (teeth grinding) at night. The most effective treatment for managing this problem involves wearing a nightguard during sleep and receiving therapeutic Botox injections to relax the muscles (the masseter muscle) responsible for grinding. However, some patients choose to postpone these treatments, leading to potentially irreversible and costlier consequences in the future. The proposed machine learning model aims to track patients who forgo the recommended treatments and assess the percentage of individuals who will experience worsening jaw pain, gingival (gum) recession, or both within a 3-to-5-year timeframe. By accurately predicting these outcomes, the model seeks to motivate patients to address the root cause proactively, ultimately saving time and pain while improving quality of life and avoiding much costlier treatments such as full-mouth rehabilitation to help recover the loss of vertical dimension of occlusion due to shortened clinical crowns because of bruxism, gingival grafts, etc.

Keywords: artificial intelligence, machine learning, predictive insights, bruxism, teeth grinding, therapeutic botox, nightguard, gingival recession, gum recession, jaw pain

Procedia PDF Downloads 65

Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

Procedia PDF Downloads 162

Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

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The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: fatigue life, finite element analysis, tolerance analysis, optimization

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Authors: Ala Hanetite

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The purpose of this article is to present, by means of a model, the determinants of organisational culture which influence creativity and innovation. A literature study showed that a model, based on the open systems theory and the work of Schein, can offer a holistic approach in describing organisational culture. The relationship between creativity, innovation and culture is discussed in this context. Against the background of this model, the determinants of organisational culture were identified. The determinants are strategy, structure, support mechanisms, behaviour that encourages innovation, and open communication. The influence of each determinant on creativity and innovation is discussed. Values, norms and beliefs that play a role in creativity and innovation can either support or inhibit creativity and innovation depending on how they influence individual and group behaviour. This is also explained in the article.

Keywords: attitudes, creativity, innovation, organisational culture

Procedia PDF Downloads 572

Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

Procedia PDF Downloads 63

Authors: Jamal A. Hassan, Ali Q. Abdulrazzaq, Sadiq J. Abass

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In this study, both the photoelastic, as well as the finite element methods, are used to study the stress distribution within human vertebra (L4) under forces similar to those that occur during normal life. Two & three dimensional models of vertebra were created by the software AutoCAD. The coordinates obtained were fed into a computer numerical control (CNC) tensile machine to fabricate the models from photoelastic sheets. Completed models were placed in a transmission polariscope and loaded with static force (up to 1500N). Stresses can be quantified and localized by counting the number of fringes. In both methods the Principle stresses were calculated at different regions. The results noticed that the maximum von-mises stress on the area of the extreme superior vertebral body surface and the facet surface with high normal stress (σ) and shear stress (τ). The facets and other posterior elements have a load-bearing function to help support the weight of the upper body and anything that it carries, and are also acted upon by spinal muscle forces. The numerical FE results have been compared with the experimental method using photoelasticity which shows good agreement between experimental and simulation results.

Keywords: photoelasticity, stress, load, finite element

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Authors: Sunthorn Sittisakuljaroen

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The edge waviness in hot rolled steel is a common defect. Variables that effect for such defect include as raw material and machine. These variables are necessary to consider. This research studied the defect of edge waviness for SS 400 of metal sheet manufacture. Defect of metal sheets divided into two groups. The specimens were investigated on chemical composition and mechanical properties to find the difference. The results of investigate showed that not different to a standard significantly. Therefore the roll milled machine for sample need to adjustable rollers for press on metal sheet which was more appropriate to adjustable at both ends.

Keywords: edge waviness, hot rolling steel, metal sheet defect, SS 400, roll leveller

Procedia PDF Downloads 391

Authors: Parisi L., Hamili D., Azlan N.

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The aim of this study was to design and simulate a particular type of Asynchronous State Machine (ASM), namely a ‘traffic light controller’ (TLC), operated at a frequency of 0.5 Hz. The design task involved two main stages: firstly, designing a 4-bit binary counter using J-K flip flops as the timing signal and subsequently, attaining the digital logic by deploying ASM design process. The TLC was designed such that it showed a sequence of three different colours, i.e. red, yellow and green, corresponding to set thresholds by deploying the least number of AND, OR and NOT gates possible. The software Multisim was deployed to design such circuit and simulate it for circuit troubleshooting in order for it to display the output sequence of the three different colours on the traffic light in the correct order. A clock signal, an asynchronous 4-bit binary counter that was designed through the use of J-K flip flops along with an ASM were used to complete this sequence, which was programmed to be repeated indefinitely. Eventually, the circuit was debugged and optimized, thus displaying the correct waveforms of the three outputs through the logic analyzer. However, hazards occurred when the frequency was increased to 10 MHz. This was attributed to delays in the feedback being too high.

Keywords: asynchronous state machine, traffic light controller, circuit design, digital electronics

Procedia PDF Downloads 414

Authors: Jeonghwan Jeon

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Recently, the industry and academia have been planning development through industry/university cooperation (IUC), and the government has been promoting alternative methods to achieve successful IUC. Representatively, business cultivation involves the lead university (regarding IUC), research and development (R&D), company support, professional manpower cultivation, and marketing, etc., and the scale of support expands every year. Research is performed by many academic researchers to achieve IUC and although satisfaction of their results is high, expectations are not being met and study of the main factor is insufficient. Therefore, this research improves on theirs by analysing the main factors influencing their satisfaction. Each factor is analysed by AHP, and portfolio analysis is performed on the importance and current satisfaction level. This will help improve satisfaction of business participants and ensure effective IUC in the future.

Keywords: industry/university cooperation, satisfaction, portfolio analysis, business participant

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Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

Procedia PDF Downloads 58

Authors: J. Kaabi, Y. Harrath

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This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.

Keywords: flow shop scheduling, genetic algorithm, maintenance, priority rules

Procedia PDF Downloads 458

Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

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Authors: Dodi Ikhsanshaleh

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When subjected to dynamic load, foundation oscillates in the way that depends on the soil behaviour, the geometry and inertia of the foundation and the dynamic exctation. The practical guideline to analysis block-type foundation excitated by dynamic load from vibrating machine is presented. The analysis use Lumped Mass Parameter Method to express dynamic properties such as stiffness and damping of soil. The numerical examples are performed on design block-type foundation supporting gas turbine compressor which is important equipment package in gas processing plant

Keywords: block foundation, dynamic load, lumped mass parameter

Procedia PDF Downloads 472

Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen

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The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.

Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin

Procedia PDF Downloads 541

Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: design of experiment, Taguchi design, optimization, analysis of variance, machining parameters, horizontal boring tool

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Authors: Martha E. Ndeley

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Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.

Keywords: disruption, machine, absenteeism, scheduling

Procedia PDF Downloads 290

Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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Authors: Jaimala Ghambir, Tilak Thakur, Puneet Chawla

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As per the statistical data, the Doubly-fed Induction Generator (DFIG) based wind turbine with variable speed and variable pitch control is the most common wind turbine in the growing wind market. This machine is usually used on the grid connected wind energy conversion system to satisfy grid code requirements such as grid stability, fault ride through (FRT), power quality improvement, grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine, the control strategy is used in both the stator as well as rotor side along with power electronic converters to fulfil the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary In this paper DFIG is modeled using power components as variables and the performance of the DFIG system is analysed under grid voltage fluctuations. The voltage fluctuations are made by lowering and raising the voltage values in the utility grid intentionally for the purpose of simulation keeping in view of different grid disturbances.

Keywords: DFIG, dynamic modeling, DPC, sag, swell, voltage fluctuations, FRT

Procedia PDF Downloads 449

Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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Authors: Barış Ozluoymak, Emin Guzel, Ahmet İnce

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Since chemical fertilizers are used for meeting the deficiency of plant nutrients, its many harmful effects are not taken into consideration for the structure of the earth. These fertilizers are hampering the work of the organisms in the soil immediately after thrown to the ground. This interference is first started with a change of the soil pH and micro organismic balance is disrupted by reaction in the soil. Since there can be no fragmentation of plant residues, organic matter in the soil will be increasingly impoverished in the absence of micro organismic living. Biological activity reduction brings about a deterioration of the soil structure. If the chemical fertilization continues intensively, soils will get worse every year; plant growth will slow down and stop due to the intensity of chemical fertilizers, yield decline will be experienced and farmer will not receive an adequate return on his investment. In this research, a prototype of automatic farm manure spreading machine for orange orchards that not just manufactured in Turkey was designed, constructed, tested and eliminate the human drudgery involved in spreading of farm manure in the field. The machine comprised several components as a 5 m3 volume hopper, automatic controlled hydraulically driven chain conveyor device and side delivery conveyor belts. To spread the solid farm manure automatically, the machine was equipped with an electronic control system. The hopper and side delivery conveyor designs fitted between orange orchard tree row spacing. Test results showed that the control system has significant effects on reduction in the amount of unnecessary solid farm manure use and avoiding inefficient manual labor.

Keywords: automatic control system, conveyor belt application, orchard, solid farm manure

Procedia PDF Downloads 274

Authors: Heungwook Son, Sungjoo Lee

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Recently, due to intensifying competition in several industries, the importance of meeting customer requirements has increased. The role that service plays in satisfying customer‘s requirements is key area of focus. Thus, the concept of using product development-research in the service system has been actively practiced. As strategic decision making tool, various types of the technology roadmap were suggested in the product-service system (PSS). However, the technology roadmap was configured a top-down form around the technologies of the elements. The limitation is that it hard for it to indicate a variety of interrelations. In response, this paper suggests using the planning support tool of PSS for a DSM for the technology roadmap; it consists of the relationship of product-service-technology as a bottom-up form. Therefore, nine types of the technology roadmap of PSS exist. The first defines the relationship of product-service-technology. The second phase identifies output when of the technology roadmaps are adapted to the DSM process. Finally, the DSM-based forms of each type of technology roadmap are presented through case studies.

Keywords: DSM, technology roadmap, PSS, product-service system, bottom-up

Procedia PDF Downloads 360

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

Abstract:

For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.

Keywords: mathematical expectation, filtration, anomalous noise, memory

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Authors: Jyh Jyh Chen, Fu H. Yang, Chen W. Wang, Yu M. Lin

Abstract:

In this work, a reaction chamber is reciprocated among three temperature regions by using an oscillatory thermal cycling machine. Three cartridge heaters are collocated to heat three aluminum blocks in order to achieve PCR requirements in the reaction chamber. The effects of various chamber moving speeds among different temperature regions on the chamber temperature profiles are presented. To solve the evaporation effect of the sample in the PCR experiment, the mineral oil and the cover lid are used. The influences of various extension times on DNA amplification are also demonstrated. The target fragments of the amplification are 385-bp and 420-bp. The results show when the forward speed is set at 6 mm/s and the backward speed is 2.4 mm/s, the temperature required for the experiment can be achieved. It is successful to perform the amplification of DNA fragments in our device.

Keywords: oscillatory, polymerase chain reaction, reaction chamber, thermal cycling machine

Procedia PDF Downloads 507