Search results for: classification system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19311

Search results for: classification system

18261 Biosignal Measurement System Based on Ultra-Wide Band Human Body Communication

Authors: Jonghoon Kim, Gilwon Yoon

Abstract:

A wrist-band type biosignal measurement system and its data transfer through human body communication (HBC) were investigated. An HBC method based on pulses of ultra-wide band instead of using frequency or amplitude modulations was studied and implemented since the system became very compact and it was more suited for personal or mobile health monitoring. Our system measured photo-plethysmogram (PPG) and measured PPG signals were transmitted through a finger to a monitoring PC system. The device was compact and low-power consuming. HBC communication has very strong security measures since it does not use wireless network. Furthermore, biosignal monitoring system becomes handy because it does not need to have wire connections.

Keywords: biosignal, human body communication, mobile health, PPG, ultrawide band

Procedia PDF Downloads 480
18260 Quantitative Structure–Activity Relationship Analysis of Some Benzimidazole Derivatives by Linear Multivariate Method

Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

Abstract:

The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

Procedia PDF Downloads 367
18259 Effect of Integrity of the Earthing System on the Rise of Earth Potential

Authors: N. Ullah, A. Haddad, F. Van Der Linde

Abstract:

This paper investigates the effects of breaks in bonds, breaks in the earthing system and breaks in earth wire on the rise of the earth potential (EPR) in a substation and at the transmission tower bases using various models of an L6 tower. Different approaches were adopted to examine the integrity of the earthing system and the terminal towers. These effects were investigated to see the associated difference in the EPR magnitudes with respect to a healthy system at various locations. Comparisons of the computed EPR magnitudes were then made between the healthy and unhealthy system to detect any difference. The studies were conducted at power frequency for a uniform soil with different soil resistivities. It was found that full breaks in the double bond of the terminal towers increase the EPR significantly at the fault location, while they reduce EPR at the terminal tower bases. A fault on the isolated section of the grid can result in EPR values up to 8 times of those on a healthy system at higher soil resistivities, provided that the extended earthing system stays connected to the grid.

Keywords: bonding, earthing, EPR, integrity, system

Procedia PDF Downloads 332
18258 Security Features for Remote Healthcare System: A Feasibility Study

Authors: Tamil Chelvi Vadivelu, Nurazean Maarop, Rasimah Che Yusoff, Farhana Aini Saludin

Abstract:

Implementing a remote healthcare system needs to consider many security features. Therefore, before any deployment of the remote healthcare system, a feasibility study from the security perspective is crucial. Remote healthcare system using WBAN technology has been used in other countries for medical purposes but in Malaysia, such projects are still not yet implemented. This study was conducted qualitatively. The interview results involving five healthcare practitioners are further elaborated. The study has addressed four important security features in order to incorporate remote healthcare system using WBAN in Malaysian government hospitals.

Keywords: remote healthcare, IT security, security features, wireless sensor application

Procedia PDF Downloads 312
18257 Feature Selection Approach for the Classification of Hydraulic Leakages in Hydraulic Final Inspection using Machine Learning

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

Procedia PDF Downloads 166
18256 Reshaping of Indian Education System with the Help of Multi-Media: Promises and Pitfalls

Authors: Geetu Gahlawat

Abstract:

The education system accustomed information on daily basis in term of variety i.e Multimedia channel. This can create a challenge to pedagogue to get hold on learner. Multimedia enhance the education system with its technology. Educators deliver their content effectively and beyond any limit through multimedia elements on another side it gives easy learning to learners and they are able to get their goals fast. This paper gives an overview of how multimedia reshape the Indian education system with its promises and pitfalls.

Keywords: multimedia, technology, techniques, development, pedagogy

Procedia PDF Downloads 286
18255 Understanding Mudrocks and Their Shear Strength Deterioration Associated with Inundation

Authors: Haslinda Nahazanan, Afshin Asadi, Zainuddin Md. Yusoff, Nik Nor Syahariati Nik Daud

Abstract:

Mudrocks is considered as a problematic material due to their unexpected behaviour specifically when they are contacting with water or being exposed to the atmosphere. Many instability problems of cutting slopes were found lying on high slaking mudrocks. It has become one of the major concerns to geotechnical engineer as mudrocks cover up to 50% of sedimentary rocks in the geologic records. Mudrocks display properties between soils and rocks which can be very hard to understand. Therefore, this paper aims to review the definition, mineralogy, geo-chemistry, classification and engineering properties of mudrocks. As water has become one of the major factors that will rapidly change the behaviour of mudrocks, a review on the shear strength of mudrocks in Derbyshire has been made using a fully automated hydraulic stress path testing system under three states: dry, short-term inundated and long-term inundated. It can be seen that the strength of mudrocks has deteriorated as it condition changed from dry to short-term inundated and finally to long-term inundated.

Keywords: mudrocks, sedimentary rocks, inundation, shear strength

Procedia PDF Downloads 240
18254 Income Analysis of Beef Cattle Breeders for Traditional Profit-Sharing System, Tesang, in South Sulawesi Province

Authors: Sitti Nurani Sirajuddin, Muh. Aminawar, Siti Nurlaelah, Amidah Amrawaty

Abstract:

This study aimed to determine the income of beef cattle breeders from the traditional profit-sharing system named Tesang. This study was conducted in the province of South Sulawesi start from April to July 2014, used quantitative methods and data analysis is of income. The population is all beef cattle breeders who perform for the traditional profit-sharing system (Tesang) in Barru Regency and Bone Regency, province of South Sulawesi. Samples are beef cattle breeders who breeding the cattle with the traditional profit-sharing system (Tesang) in Barru Regency and Bone Regency using breeding system and cattle enlargement system (expense) by fifty breeders. The results showed beef cattle breeder’s income from the profit-sharing system (Tesang) where enlargement system (expense) at6th month maintenance periods higher than the profit-sharing system (Tesang) with using breeding the cattle.

Keywords: income, beef cattle, profit-sharing system, Teseng

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18253 Roughness Discrimination Using Bioinspired Tactile Sensors

Authors: Zhengkun Yi

Abstract:

Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

Procedia PDF Downloads 315
18252 Intelligent Adaptive Learning in a Changing Environment

Authors: G. Valentis, Q. Berthelot

Abstract:

Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

Procedia PDF Downloads 426
18251 Seismic Fragility of Base-Isolated Multi-Story Piping System in Critical Facilities

Authors: Bu Seog Ju, Ho Young Son, Yong Hee Ryu

Abstract:

This study is focused on the evaluation of seismic fragility of multi-story piping system installed in critical structures, isolated with triple friction pendulum bearing. The concept of this study is to isolate the critical building structure as well as nonstructural component, especially piping system in order to mitigate the earthquake damage and achieve the reliable seismic design. Then, the building system and multi-story piping system was modeled in OpenSees. In particular, the triple friction pendulum isolator was accounted for the vertical and horizontal coupling behavior in the building system subjected to seismic ground motions. Consequently, in order to generate the seismic fragility of base-isolated multi-story piping system, 21 selected seismic ground motions were carried out, by using Monte Carlo Simulation accounted for the uncertainties in demand. Finally, the system-level fragility curves corresponding to the limit state of the piping system was conducted at each T-joint system, which was commonly failure points in piping systems during and after an earthquake. Additionally, the system-level fragilities were performed to the first floor and second floor level in critical structures.

Keywords: fragility, friction pendulum bearing, nonstructural component, seismic

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18250 Advanced Magnetic Field Mapping Utilizing Vertically Integrated Deployment Platforms

Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

Abstract:

This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

Procedia PDF Downloads 468
18249 Optimization of the Energy Management for a Solar System of an Agricultural Greenhouse

Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume

Abstract:

To improve the climatic conditions and increase production in the greenhouse during the winter season under the Mediterranean climate, this thesis project proposes a design of an integrated and autonomous solar system for heating, cooling, and conservation of production in an agricultural greenhouse. To study the effectiveness of this system, experiments are conducted in two similar agricultural greenhouses oriented north-south. The first greenhouse is equipped with an active solar system integrated into the double glazing of the greenhouse’s roof, while the second greenhouse has no system, it serves as a controlled greenhouse for comparing thermal and agronomic performance The solar system allowed for an average increase in the indoor temperature of the experimental greenhouse of 6°C compared to the outdoor environment and 4°C compared to the control greenhouse. This improvement in temperature has a favorable effect on the plants' climate and subsequently positively affects their development, quality, and production.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

Procedia PDF Downloads 104
18248 Autonomic Threat Avoidance and Self-Healing in Database Management System

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

Abstract:

Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 508
18247 Spatial Comparative Analysis on Travels of Mackay in Taiwan

Authors: Shao-Chi Chien, Ying-Ju Chen, Chiao-Yu Tseng, Wan-Ting Lee, Yi-Wen Cheng

Abstract:

Dr. George Leslie Mackay arrived at Takoukang (now Port of Kaohsiung) in Taiwan on December 30, 1871. When Dr. Mackay dedicated at Taiwan for 30 years, he has been an important factor in such areas as preaching, medical and engaged in education. Many researchers have thoroughly studied Dr. Mackay's travels to understand his impact on the state of education, medicine and religion in Taiwan. In the 30-year period of hard work, Dr. Mackay's made outstanding influence on the church in Taiwan. Therefore, the present study will be the mission of the establishment of hospitals, schools, churches which preaching, education, and medicine whether there are related the number of comparisons to explore. According to The Diaries of George Leslie Mackay, our research uses the Geographic Information System (GIS) to map the location of Dr. Mackay's travel in Taiwan and compares it with today's local churches, hospitals, and schools whether there are related the number of comparisons to explore. Therefore, our research focuses on the whole of Taiwan, divided into missionary, medical and education as the main content of the three major parts. Additionally, use of point layer, the surface layer of the property table to establish, in-depth mission of Dr. Mackay's development in Taiwan and Today's comparison. The results will be based on the classification of three different colors pictures that the distance of Mackay's contribution of preaching, medicine, and education. Our research will be compared with the current churches, hospitals, schools and the past churches, hospitals, schools. The results of the present study will provide a reference for future research.

Keywords: George Leslie Mackay, geographic information system, spatial distribution, color categories analysis

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18246 Power Management Strategy for Solar-Wind-Diesel Stand-Alone Hybrid Energy System

Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

Abstract:

This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

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18245 Investigation on The Feasibility of a Solar Desiccant Cooling System in Libya

Authors: A. S. Zgalei, B. T. Al-Mabrouk

Abstract:

With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

Procedia PDF Downloads 542
18244 Preliminary Evaluation of Decommissioning Wastes for the First Commercial Nuclear Power Reactor in South Korea

Authors: Kyomin Lee, Joohee Kim, Sangho Kang

Abstract:

The commercial nuclear power reactor in South Korea, Kori Unit 1, which was a 587 MWe pressurized water reactor that started operation since 1978, was permanently shut down in June 2017 without an additional operating license extension. The Kori 1 Unit is scheduled to become the nuclear power unit to enter the decommissioning phase. In this study, the preliminary evaluation of the decommissioning wastes for the Kori Unit 1 was performed based on the following series of process: firstly, the plant inventory is investigated based on various documents (i.e., equipment/ component list, construction records, general arrangement drawings). Secondly, the radiological conditions of systems, structures and components (SSCs) are established to estimate the amount of radioactive waste by waste classification. Third, the waste management strategies for Kori Unit 1 including waste packaging are established. Forth, selection of the proper decontamination and dismantling (D&D) technologies is made considering the various factors. Finally, the amount of decommissioning waste by classification for Kori 1 is estimated using the DeCAT program, which was developed by KEPCO-E&C for a decommissioning cost estimation. The preliminary evaluation results have shown that the expected amounts of decommissioning wastes were less than about 2% and 8% of the total wastes generated (i.e., sum of clean wastes and radwastes) before/after waste processing, respectively, and it was found that the majority of contaminated material was carbon or alloy steel and stainless steel. In addition, within the range of availability of information, the results of the evaluation were compared with the results from the various decommissioning experiences data or international/national decommissioning study. The comparison results have shown that the radioactive waste amount from Kori Unit 1 decommissioning were much less than those from the plants decommissioned in U.S. and were comparable to those from the plants in Europe. This result comes from the difference of disposal cost and clearance criteria (i.e., free release level) between U.S. and non-U.S. The preliminary evaluation performed using the methodology established in this study will be useful as a important information in establishing the decommissioning planning for the decommissioning schedule and waste management strategy establishment including the transportation, packaging, handling, and disposal of radioactive wastes.

Keywords: characterization, classification, decommissioning, decontamination and dismantling, Kori 1, radioactive waste

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18243 Optimum Design of Photovoltaic Water Pumping System Application

Authors: Sarah Abdourraziq, Rachid El Bachtiri

Abstract:

The solar power source for pumping water is one of the most promising areas in photovoltaic applications. The implementation of these systems allows to protect the environment and reduce the CO2 gas emission compared to systems trained by diesel generators. This paper presents a comparative study between the photovoltaic pumping system driven by DC motor, and AC motor to define the optimum design of this application. The studied system consists of PV array, DC-DC Boost Converter, inverter, motor-pump set and storage tank. The comparison was carried out to define the characteristics and the performance of each system. Each subsystem is modeled in order to simulate the whole system in MATLAB/ Simulink. The results show the efficiency of the proposed technique.

Keywords: photovoltaic water pumping system, DC motor-pump, AC motor-pump, DC-DC boost converter

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18242 Partial Least Square Regression for High-Dimentional and High-Correlated Data

Authors: Mohammed Abdullah Alshahrani

Abstract:

The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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18241 The Development of the Website Learning the Local Wisdom in Phra Nakhon Si Ayutthaya Province

Authors: Bunthida Chunngam, Thanyanan Worasesthaphong

Abstract:

This research had objective to develop of the website learning the local wisdom in Phra Nakhon Si Ayutthaya province and studied satisfaction of system user. This research sample was multistage sample for 100 questionnaires, analyzed data to calculated reliability value with Cronbach’s alpha coefficient method α=0.82. This system had 3 functions which were system using, system feather evaluation and system accuracy evaluation which the statistics used for data analysis was descriptive statistics to explain sample feature so these statistics were frequency, percentage, mean and standard deviation. This data analysis result found that the system using performance quality had good level satisfaction (4.44 mean), system feather function analysis had good level satisfaction (4.11 mean) and system accuracy had good level satisfaction (3.74 mean).

Keywords: website, learning, local wisdom, Phra Nakhon Si Ayutthaya province

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18240 Preparation of Papers - Developing a Leukemia Diagnostic System Based on Hybrid Deep Learning Architectures in Actual Clinical Environments

Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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18239 Preparation Control Information and Analyzing of Metering Gas System Based of Orifice Plate

Authors: A. Harrouz, A. Benatiallah, O. Harrouz

Abstract:

This paper presents the search for errors in the measurement instruments in a dynamic system of metering liquid or gas and sees the tolerance defined by the international standards and recommendations. We will implement a program on MATLAB/Simulink which is calculated based on the ISO-5167. This program will take the system parameters on considerations such as: the willingness plates, the size of the orifice, the given design conditions, reference conditions, find pressure drop for a given flow, or flow for a loss of given load. The results are considered very good and satisfactory because the errors identified of measuring instruments system are within the margin of error limit by the regulations.

Keywords: analyzing, control, gas, meters system

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18238 Automatic Integrated Inverter Type Smart Device for Safe Kitchen

Authors: K. M. Jananni, R. Nandini

Abstract:

The proposed wireless, inverter type design of a LPG leakage monitoring system aims to provide a smart and safe kitchen. The system detects the LPG gas leak using Nano-sensors and alerts the concerned individual through GSM system. The system uses two sensors, one attached to the chimney and other to the regulator of the LPG cylinder. Upon a leakage being detected, the sensor at the regulator actuates the system to cut off the gas supply immediately using a solenoid control valve. The sensor at the chimney checks for the permissible level of LPG mix in the air and when the level exceeds the threshold, the system sends an automatic SMS to the numbers saved. Further the sensor actuates the mini suction system fixed at the chimney within 20 seconds of a leakage to suck out the gas until the level falls well below the threshold. As a safety measure, an automatic window opening and alarm feature is also incorporated into the system. The key feature of this design is that the system is provided with a special inverter designed to make the device function effectively even during power failures. In this paper, utilization of sensors in the kitchen area is discussed and this gives the proposed architecture for real time field monitoring with a PIC Micro-controller.

Keywords: nano sensors, global system for mobile communication, GSM, micro controller, inverter

Procedia PDF Downloads 478
18237 Classification of Multiple Cancer Types with Deep Convolutional Neural Network

Authors: Nan Deng, Zhenqiu Liu

Abstract:

Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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18236 A Multiobjective Damping Function for Coordinated Control of Power System Stabilizer and Power Oscillation Damping

Authors: Jose D. Herrera, Mario A. Rios

Abstract:

This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

Procedia PDF Downloads 596
18235 Semantic Differences between Bug Labeling of Different Repositories via Machine Learning

Authors: Pooja Khanal, Huaming Zhang

Abstract:

Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

Procedia PDF Downloads 206
18234 Modelling and Control of Electrohydraulic System Using Fuzzy Logic Algorithm

Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

Abstract:

This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

Procedia PDF Downloads 478
18233 A Linear Relation for Voltage Unbalance Factor Evaluation in Three-Phase Electrical Power System Using Space Vector

Authors: Dana M. Ragab, Jasim A Ghaeb

Abstract:

The Voltage Unbalance Factor (VUF) index is recommended to evaluate system performance under unbalanced operation. However, its calculation requires complex algebra which limits its use in the field. Furthermore, one system cycle is required at least to detect unbalance using the VUF. Ideally unbalance mitigation must be performed within 10 ms for 50 Hz systems. In this work, a linear relation for VUF evaluation in three-phase electrical power system using space vector (SV) is derived. It is proposed to determine the voltage unbalance quickly and accurately and to overcome the constraints associated with the traditional methods of VUF evaluation. Aqaba-Qatrana-South Amman (AQSA) power system is considered to study the system performance under unbalanced conditions. The results show that both the complexity of calculations and the time required to evaluate VUF are reduced significantly.

Keywords: power quality, space vector, unbalance evaluation, three-phase power system

Procedia PDF Downloads 192
18232 Damping Function and Dynamic Simulation of GUPFC Using IC-HS Algorithm

Authors: Galu Papy Yuma

Abstract:

This paper presents a new dynamic simulation of a power system consisting of four machines equipped with the Generalized Unified Power Flow Controller (GUPFC) to improve power system stability. The dynamic simulation of the GUPFC consists of one shunt converter and two series converters based on voltage source converter, and DC link capacitor installed in the power system. MATLAB/Simulink is used to arrange the dynamic simulation of the GUPFC, where the power system is simulated in order to investigate the impact of the controller on power system oscillation damping and to show the simulation program reliability. The Improved Chaotic- Harmony Search (IC-HS) Algorithm is used to provide the parameter controller in order to lead-lag compensation design. The results obtained by simulation show that the power system with four machines is suitable for stability analysis. The use of GUPFC and IC-HS Algorithm provides the excellent capability in fast damping of power system oscillations and improve greatly the dynamic stability of the power system.

Keywords: GUPFC, IC-HS algorithm, Matlab/Simulink, damping oscillation

Procedia PDF Downloads 451