Search results for: intelligent inspection app system

Authors: Radu Pop, Adrian Bot, Vasile Rednic, Emil Bruj, Oana Raita, Liviu Vaida

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Our research presents a study concerning optimization of water flow capture for micro-hydro power plants in order to increase the energy production. It is known that the fish ladder whole, were the water is capture is fix, and the water flow may vary with the river flow, this means that on the fish ladder we will have different servitude flows, sometimes more than needed. We propose to demonstrate that the ‘winter intake’ from micro-hydro power plant, could be automated with an intelligent system which is capable to read some imposed data and adjust the flow in to the needed value. With this automation concept, we demonstrate that the performance of the micro-hydro power plant could increase, in some flow operating regimes, with approx. 10%.

Keywords: energy, micro-hydro, water intake, fish ladder

Procedia PDF Downloads 228

Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 122

Authors: Yudhitya Kusumawati, Yuki Mitsuya, Tomooki Shiba, Mitsuru Uesaka

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After the Fukushima Daiichi nuclear power reactor incident, there are a lot of unaccountable nuclear fuel debris in the reactor core area, which is subject to safeguard and criticality safety. Before the actual precise analysis is performed, preliminary on-site screening and mapping of nuclear debris activity need to be performed to provide a reliable data on the nuclear debris mass-extraction planning. Through a collaboration project with Japan Atomic Energy Agency, an on-site nuclear debris screening system by using dual energy X-Ray inspection and neutron energy resonance analysis has been established. By using the compact and mobile pulsed neutron source constructed from 3.95 MeV X-Band electron linac, coupled with Tungsten as electron-to-photon converter and Beryllium as a photon-to-neutron converter, short-distance neutron Time of Flight measurement can be performed. Experiment result shows this system can measure neutron energy spectrum up to 100 eV range with only 2.5 meters Time of Flightpath in regards to the X-Band accelerator’s short pulse. With this, on-site neutron Time of Flight measurement can be used to identify the nuclear debris isotope contents through Neutron Resonance Transmission Analysis (NRTA). Some preliminary NRTA experiments have been done with Tungsten sample as dummy nuclear debris material, which isotopes Tungsten-186 has close energy absorption value with Uranium-238 (15 eV). The results obtained shows that this system can detect energy absorption in the resonance neutron area within 1-100 eV. It can also detect multiple elements in a material at once with the experiment using a combined sample of Indium, Tantalum, and silver makes it feasible to identify debris containing mixed material. This compact neutron Time of Flight measurement system is a great complementary for dual energy X-Ray Computed Tomography (CT) method that can identify atomic number quantitatively but with 1-mm spatial resolution and high error bar. The combination of these two measurement methods will able to perform on-site nuclear debris screening at Fukushima Daiichi reactor core area, providing the data for nuclear debris activity mapping.

Keywords: neutron source, neutron resonance, nuclear debris, time of flight

Procedia PDF Downloads 231

Authors: Ming-Jyh Chen, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang

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Introduction: Social responsibility is the key to sustainable organizational development. Under the ground Green Health Hospital Declaration signed by our superintendent, we have launched comprehensive energy conservation management in medical services, the community, and the staff’s life. To execute environment-friendly promotion with robust strategies, we build up a low-carbon medical system and community with smart green public construction promotion as well as intensifying energy conservation education and communication. Purpose/Methods: With the support of the board and the superintendent, we construct an energy management team, commencing with an environment-friendly system, management, education, and ISO 50001 energy management system; we have ameliorated energy performance and energy efficiency and continuing. Results: In the year 2021, we have achieved multiple goals. The energy management system efficiently controls diesel, natural gas, and electricity usage. About 5% of the consumption is saved when compared to the numbers from 2018 and 2021. Our company develops intelligent services and promotes various paperless electronic operations to provide people with a vibrant and environmentally friendly lifestyle. The goal is to save 68.6% on printing and photocopying by reducing 35.15 million sheets of paper yearly. We strengthen the concept of environmental protection classification among colleagues. In the past two years, the amount of resource recycling has reached more than 650 tons, and the resource recycling rate has reached 70%. The annual growth rate of waste recycling is about 28 metric tons. Conclusions: To build a green medical system with “high efficacy, high value, low carbon, low reliance,” energy stewardship, economic prosperity, and social responsibility are our principles when it comes to formulation of energy conservation management strategies, converting limited sources to efficient usage, developing clean energy, and continuing with sustainable energy.

Keywords: energy efficiency, environmental education, green hospital, sustainable development

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Authors: Kushakov Kholmurodjon, Muhammadjonov Akbarshox

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This present paper is devoted to a system of second-order nonlinear differential equations with a special right-hand side, exactly, the linear part and a third-order polynomial of a special form. It is shown that for some relations between the parameters, there is a second-order curve in which trajectories leaving the points of this curve remain in the same place. Thus, the curve is invariant with respect to the given system. Moreover, this system is invariant under a non-degenerate linear transformation of variables. The form of this curve, depending on the relations between the parameters and the eigenvalues of the matrix, is proved. All solutions of this system of differential equations are shown analytically.

Keywords: dynamic system, ellipse, hyperbola, Hess system, polar coordinate system

Procedia PDF Downloads 191

Authors: Bohuslava Juhasova, Igor Halenar, Martin Juhas

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The contribution deals with the current situation in modern manufacturing enterprises, which is affected by digital virtualization of different parts of the production process. The overview part of this article points to the fact, that wide informatization of all areas causes substitution of real elements and relationships between them with their digital, often virtual images, in real practice. Key characteristics of the systems implemented using digital twin technology along with essential conditions for intelligent products deployment were identified across many published studies. The goal was to propose a template for the production system realization using digital twin technology as a supplement to standardized concepts for Industry 4.0. The main resulting idea leads to the statement that the current trend of implementation of the new technologies and ways of communication between industrial facilities erases the boundaries between the real environment and the virtual world.

Keywords: communication, digital twin, Industry 4.0, simulation, virtualization

Procedia PDF Downloads 243

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

Procedia PDF Downloads 107

Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Farhad Ghasemi

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Along with transforming the international system into a complex and chaotic system, the fundamental question arises: how can deterrence be reconstructed conceptually and theoretically in this system model? The deterrence system is much more complex today than it was seven decades ago. This article suggests that the perception of deterrence as a linear system is a fundamental mistake because it does not consider the new dynamics of the international system, including network power dynamics. The author aims to improve this point by focusing on complexity and chaos theories, especially their nonlinearity and cascading failure principles. This article proposes that the perception of deterrence as a linear system is a fundamental mistake, as the new dynamics of the surrounding international system do not take into account. The author recognizes deterrence as a nonlinear system and introduces it as a concept in strategic studies.

Keywords: complexity, international system, deterrence, linear deterrence, nonlinear deterrence

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Authors: Volkmar Nolting

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Fatigue crack growth prediction has become an important topic in both engineering and non-destructive evaluation. Crack propagation is influenced by the mechanical properties of the material and is conveniently modelled by the Paris-Erdogan equation. The critical crack size and the total number of load cycles are calculated. From a Larson-Miller plot the maximum operational temperature can for a given stress level be determined so that failure does not occur within a given time interval t. The study is used to determine a reasonable inspection cycle and thus enhances operational safety and reduces costs.

Keywords: fracturemechanics, crack growth prediction, lifetime of a component, structural health monitoring

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: Nora Arbaoui, Rachid Tadili

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This study focuses on a solar system designed to heat an agricultural greenhouse. This solar system is based on the heating of a transfer fluid that circulates inside the greenhouse through a solar copper coil integrated into the roof of the greenhouse. The thermal energy stored during the day will be released during the night to improve the microclimate of the greenhouse. This system was tested in a small agricultural greenhouse in order to ameliorate the different operational parameters. The climatic and agronomic results obtained with this system are significant in comparison with a greenhouse with no heating system.

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

Procedia PDF Downloads 79

Authors: Adamantini Loukodimou, David Weston, Shiladitya Paul

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Offshore structures are subjected to harsh environments. It is documented that carbon steel needs protection from corrosion. The combined effect of UV radiation, seawater splash, and fluctuating temperatures diminish the integrity of these structures. In addition, the possibility of damage caused by floating ice, seaborne debris, and maintenance boats make them even more vulnerable. Their inspection and maintenance when far out in the sea are difficult, risky, and expensive. The most known method of mitigating corrosion of offshore structures is the use of cathodic protection. There are several zones in an offshore wind turbine. In the atmospheric zone, due to the lack of a continuous electrolyte (seawater) layer between the structure and the anode at all times, this method proves inefficient. Thus, the use of protective coatings becomes indispensable. This research focuses on the atmospheric zone. The conversion of commercially available and conventional paint (epoxy) system to an autonomous self-healing paint system via the addition of suitable encapsulated healing agents and catalyst is investigated in this work. These coating systems, which can self-heal when damaged, can provide a cost-effective engineering solution to corrosion and related problems. When the damage of the paint coating occurs, the microcapsules are designed to rupture and release the self-healing liquid (monomer), which then will react in the presence of the catalyst and solidify (polymerization), resulting in healing. The catalyst should be compatible with the system because otherwise, the self-healing process will not occur. The carbon steel substrate will be exposed to a corrosive environment, so the use of a sacrificial layer of Zn is also investigated. More specifically, the first layer of this new coating system will be TSZA (Thermally Sprayed Zn85/Al15) and will be applied on carbon steel samples with dimensions 100 x 150 mm after being blasted with alumina (size F24) as part of the surface preparation. Based on the literature, it corrodes readily, so one additional paint layer enriched with microcapsules will be added. Also, the reaction and the curing time are of high importance in order for this bilayer system of coating to work successfully. For the first experiments, polystyrene microcapsules loaded with 3-octanoyltio-1-propyltriethoxysilane were conducted. Electrochemical experiments such as Electrochemical Impedance Spectroscopy (EIS) confirmed the corrosion inhibiting properties of the silane. The diameter of the microcapsules was about 150-200 microns. Further experiments were conducted with different reagents and methods in order to obtain diameters of about 50 microns, and their self-healing properties were tested in synthetic seawater using electrochemical techniques. The use of combined paint/electrodeposited coatings allows for further novel development of composite coating systems. The potential for the application of these coatings in offshore structures will be discussed.

Keywords: corrosion mitigation, microcapsules, offshore wind turbines, self-healing

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy

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Authors: Amal M. Alrayes

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Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance.Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: data quality, performance, system quality, Kingdom of Bahrain

Procedia PDF Downloads 487

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

Procedia PDF Downloads 113

Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

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The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

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Authors: Ali Akber Jaffri, Asad Naseem, Javeria Khan

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The purpose of this study is to determine safety stock, maximum inventory level, reordering point, and reordering quantity by rearranging lot sizes for supplier and customer in MRO (maintenance repair operations) warehouse of Engro Polymers & Chemicals. To achieve the aim, physical analysis method and excel commands were carried out to elicit the customer and supplier data provided by the company. Initially, we rearranged the current lot sizes and MOUs (measure of units) in SAP software. Due to change in lot sizes we have to determine the new quantities for safety stock, maximum inventory, reordering point and reordering quantity as per company's demand. By proposed system, we saved extra cost in terms of reducing the time of receiving from vendor and in issuance to customer, ease of material handling in MRO warehouse and also reduce human efforts. The information requirements identified in this study can be utilized in calculating Economic Order Quantity.

Keywords: carrying cost, economic order quantity, fast moving, lead time, lot size, MRO, maximum inventory, ordering cost, physical inspection, reorder point

Procedia PDF Downloads 235

Authors: Ahlyum Mun, Ji-Young Moon, Moon-Seok Yoon, Dong-Jin Baek, Doo-Seok Seo, Oun-Kyong Moon

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There is a growing public concern over the standards of farm animal welfare, with higher standards of food safety. In addition, the recent low incidence of Avian Influenza in laying hens among certificated farms is receiving attention. In this study, we introduce animal welfare systems covering the rearing, transport and slaughter of farm animals in South Korea. The concepts of animal welfare farm certification are based on ensuring the five freedoms of animal. The animal welfare is also achieved by observing the condition of environment including shelter and resting area, feeding and water and the care for the animal health. The certification of farm animal welfare is handled by the Animal Protection & Welfare Division of Animal and Plant Quarantine Agency (APQA). Following the full amendment of Animal Protection Law in 2011, animal welfare farm certification program has been implemented since 2012. The certification system has expanded to cover laying hen, swine, broiler, beef cattle and dairy cow, goat and duck farms. Livestock farmers who want to be certified must apply for certification at the APQA. Upon receipt of the application, the APQA notifies the applicant of the detailed schedule of the on-site examination after reviewing the document and conducts the on-site inspection according to the evaluation criteria of the welfare standard. If the on-site audit results meet the certification criteria, APQA issues a certificate. The production process of certified farms is inspected at least once a year for follow-up management. As of 2017, a total of 145 farms have been certified (95 laying hen farms, 12 swine farms, 30 broiler farms and 8 dairy cow farms). In addition, animal welfare transportation vehicles and slaughterhouses have been designated since 2013 and currently 6 slaughterhouses have been certified. Animal Protection Law has been amended so that animal welfare certification marks can be affixed only to livestock products produced by animal welfare farms, transported through animal welfare vehicles and slaughtered at animal welfare slaughterhouses. The whole process including rearing–transportation- slaughtering completes the farm animal welfare system. APQA established its second 5-year animal welfare plan (2014-2019) that includes setting a minimum standard of animal welfare applicable to all livestock farms, transportation vehicles and slaughterhouses. In accordance with this plan, we will promote the farm animal welfare policy in order to truly advance the Korean livestock industry.

Keywords: animal welfare, farm animal, certification system, South Korea

Procedia PDF Downloads 392

Authors: Anuphan Suttimarn, Natcha Wattanaprapa, Suwaree Yordchim

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The aim of this study is to develop the online journal system using a web application to manage the journal service of Suan Sunandha Rajabhat University in order to improve the journal management of the university. The main structures of the system process consist of 1. journal content management system 2. membership system of the journal and 3. online submission or review process. The investigators developed the system based on a web application using open source OJS software and phpMyAdmin to manage a research database. The system test showed that this online system 'Online Journal System (OJS)' could shorten the time in the period of submission article to journal and helped in managing a journal procedure efficiently and accurately. The quality evaluation of Suan Sunandha Rajabhat online journal system (SSRUOJS) undertaken by experts and researchers in 5 aspects; design, usability, security, reducing time, and accuracy showed the highest average value (X=4.30) on the aspect of reducing time. Meanwhile, the system efficiency evaluation was on an excellent level (X=4.13).

Keywords: online journal system, Journal management, Information system development, OJS

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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Authors: Tatyana Gavrilova, Vadim Onufriev

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Knowledge-based systems’ design requires the developer’s owning the advanced analytical skills. The efficient development of that skills within university courses needs a deep understanding of main pitfalls and drawbacks, which students usually make during their analytical work in form of visual modeling. Thus, it was necessary to hold an analysis of 5-th year students’ learning exercises within courses of 'Intelligent systems' and 'Knowledge engineering' in Saint-Petersburg Polytechnic University. The analysis shows that both lack of system thinking skills and methodological mistakes in course design cause the errors that are discussed in the paper. The conclusion contains an exploration of the issues and topics necessary and sufficient for the implementation of the improved practices in educational design for future curricula of teaching programs.

Keywords: knowledge based systems, knowledge engineering, students’ errors, visual modeling

Procedia PDF Downloads 305

Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Xuezhang Hou

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In the present paper, a hybrid hyperbolic dynamic system formulated by partial differential equations with initial and boundary conditions is considered. First, the system is transformed to an abstract evolution system in an appropriate Hilbert space, and spectral analysis and semigroup generation of the system operator is discussed. Subsequently, a sliding model control problem is proposed and investigated, and an equivalent control method is introduced and applied to the system. Finally, a significant result that the state of the system can be approximated by an ideal sliding mode under control in any accuracy is derived and examined.

Keywords: hyperbolic dynamic system, sliding model control, semigroup of linear operators, partial differential equations

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Authors: Stephen A. Akinlabi, Esther T. Akinlabi

Abstract:

The drip irrigation system is one of the important areas that affect the livelihood of farmers directly. The use of drip irrigation system has been the most efficient system compared to the other types of irrigations systems because the drip irrigation helps to save water and increase the productivity of crops. But like any other system, it can be considered inefficient when the filters and the emitters get clogged while in operation. The efficiency of the entire system is reduced when the emitters are clogged and blocked. This consequently impact and affect the farm operations which may result in scarcity of farm products and increase the demand. This design work focuses on how to overcome some of the challenges affecting drip irrigation system through the design of an efficient filtration and flushing system.

Keywords: drip irrigation system, filters, soil texture, mechanical engineering design, analysis

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Authors: Young-Kwan Choi, Han-Sang Jeong

Abstract:

Floating photovoltaic system is a technology that combines photovoltaic power generation with floating structure. However, since floating technology has not been utilized in photovoltaic generation, there are no standardized criteria. It is separately developed and used by different installation bodies. This paper aims to discuss the change of floating photovoltaic system technology based on examples of floating photovoltaic systems installed in Korea.

Keywords: floating photovoltaic system, floating PV installation, ocean floating photovoltaic system, tracking type floating photovoltaic system

Procedia PDF Downloads 555

Authors: Chih Hsing Lin, Wen-Ching Chen, Ssu-Ying Chen, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

Abstract:

Critical structures such as buildings, bridges and dams require periodic inspections to ensure safe operation. The reliable inspection of structures can be achieved by combing temperature sensor and accelerometers. In this work, we propose a building structure health monitoring device (BSHMD) with using three 1-axis accelerometers, gateway, analog to digital converter (ADC), and data logger to monitoring the building structure. The proposed BSHMD achieves the features of low cost by using three 1-axis accelerometers with the data synchronization problem being solved, and easily installation and removal. Furthermore, we develop a packet acquisition program to receive the sensed data and then classify it based on time and date. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 64.3% cost saving. Compared with previous structural monitoring device, the BSHMD achieves 89% area saving. Therefore, with using the proposed device, the realtime diagnosis system for building damage monitoring can be conducted effectively.

Keywords: building structure health monitoring, cost effective, 1-axis accelerometers, real-time diagnosis

Procedia PDF Downloads 359

Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

Abstract:

Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

Procedia PDF Downloads 306

Authors: Issa Hussein Manita

Abstract:

This paper presents an example of industrial information system design and implementation (IIDC), the most common software engineering design steps that are applied to the different design stages. We are going through the life cycle of software system development. We start by a study of system requirement and end with testing and delivering system, going by system design and coding, program integration and system integration step. The most modern software design tools available used in the design this includes, but not limited to, Unified Modeling Language (UML), system modeling, SQL server side application, uses case analysis, design and testing as applied to information processing systems. The system is designed to perform tasks specified by the client with real data. By the end of the implementation of the system, default or user defined acceptance policy to provide an overall score as an indication of the system performance is used. To test the reliability of he designed system, it is tested in different environment and different work burden such as multi-user environment.

Keywords: software engineering, design, system requirement, integration, unified modeling language

Procedia PDF Downloads 567