Search results for: thoughtful decision support system

Authors: M. Takhtravanchi, C. Pathirage

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In the construction industry, project members are conveyor of project knowledge which is, often, not managed properly to be used in future projects. As construction projects are temporary and unique, project members are willing to be recruited once a project is completed. Therefore, poor management of knowledge across construction projects will lead to a considerable amount of knowledge loss; the ignoring of which would be detrimental to project performance. This issue is more prominent in projects undertaken through the traditional procurement system, as this system does not incentives project members for integration. Thus, disputes exist between the design and construction phases based on the poor management of knowledge between those two phases. This paper aims to highlight the challenges of the knowledge management that exists within the traditional procurement system. Expert interviews were conducted and challenges were identified and analysed by the Interpretive Structural Modelling (ISM) approach in order to summarise the relationships among them. Two identified key challenges are the Culture of an Organisation and Knowledge Management Policies. A knowledge of the challenges and their relationships will help project manager and stakeholders to have a better understanding of the importance of knowledge management.

Keywords: challenges, construction industry, knowledge management, traditional procurement system

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Authors: Ezeabasili Chibuike Patrick

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The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

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Authors: Maatoug Hassine, Mourad Hrizi

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In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: geometric inverse source problem, heat equation, topological optimization, topological sensitivity, Kohn-Vogelius formulation

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Authors: Timiebi Aganaba-Jeanty

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Accurate and transparent monitoring, reporting and verification of Greenhouse Gas (GHG) emissions and removals is a requirement of the United Nations Framework Convention on Climate Change (UNFCCC). Several countries are obligated to prepare and submit an annual national greenhouse gas inventory covering anthropogenic emissions by sources and removals by sinks, subject to a review conducted by an international team of experts. However, the process is not without flaws. The self-reporting varies enormously in thoroughness, frequency and accuracy including inconsistency in the way such reporting occurs. The world’s space agencies are calling for a new generation of satellites that would be precise enough to map greenhouse gas emissions from individual nations. The plan is delicate politically because the global system could verify or cast doubt on emission reports from the member states of the UNFCCC. A level playing field is required and an idea that an international system should be perceived as an instrument to facilitate fairness and equality rather than to spy on or punish. This change of perspective is required to get buy in for an international verification system. The research proposes the viability of a satellite system that provides independent access to data regarding greenhouse gas emissions and the policy and governance implications of its potential use as a monitoring and verification system for the Paris Agreement. It assesses the foundations of the reporting monitoring and verification system as proposed in Paris and analyzes this in light of a proposed satellite system. The use of remote sensing technology has been debated for verification purposes and as evidence in courts but this is not without controversy. Lessons can be learned from its use in this context.

Keywords: greenhouse gas emissions, reporting, monitoring and verification, satellite, UNFCCC

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Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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Authors: S. Mahdi Sadatmansouri, Maryam Khalili

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World, nowadays, encounters serious water scarcity problem. During the past few years, by advent of Smart Energy and Water Meter (SEWM) and its installation at the electro-pumps of the water wells, one had believed that it could be the golden key to address the groundwater resources over-pumping issue. In fact, implementation of these Smart Meters managed to control the water table drawdown for short; but it was not a sustainable approach. SEWM has been considered as law enforcement facility at first; however, for solving a complex socioeconomic problem like shared groundwater resources management, more than just enforcement is required: participation to conserve common resources. The well owners or farmers, as water consumers, are the main and direct stakeholders of this system and other stakeholders could be government sectors, investors, technology providers, privet sectors or ordinary people. Designing a socio-technical system not only defines the role of each stakeholder but also can lubricate the communication to reach the system goals while benefits of each are considered and provided. Farmers, as the key participators for solving groundwater problem, do not trust governments but they would trust a fair system in which responsibilities, privileges and benefits are clear. Technology could help this system remained impartial and productive. Social aspects provide rules, regulations, social objects and etc. for the system and help it to be more human-centered. As the design methodology, Design Thinking provides probable solutions for the challenging problems and ongoing conflicts; it could enlighten the way in which the final system could be designed. Using Human Centered Design approach of IDEO helps to keep farmers in the center of the solution and provides a vision by which stakeholders’ requirements and needs are addressed effectively. Farmers would be considered to trust the system and participate in their groundwater resources management if they find the rules and tools of the system fair and effective. Besides, implementation of the socio-technical system could change farmers’ behavior in order that they concern more about their valuable shared water resources as well as their farm profit. This socio-technical system contains nine main subsystems: 1) Measurement and Monitoring system, 2) Legislation and Governmental system, 3) Information Sharing system, 4) Knowledge based NGOs, 5) Integrated Farm Management system (using IoT), 6) Water Market and Water Banking system, 7) Gamification, 8) Agribusiness ecosystem, 9) Investment system.

Keywords: human centered design, participatory management, smart energy and water meter (SEWM), social object, socio-technical system, water table drawdown

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Authors: Hadi Adibi-Asl, Alireza Doosthosseini, Amir Taghavipour

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This paper studies the design of an adaptive control strategy to tune an active steering system for better drivability and maneuverability. In the first step, adaptive control strategy is applied to estimate the uncertain parameters on-line (e.g. cornering stiffness), then the estimated parameters are fed into the pole placement controller to generate corrective feedback gain to improve the steering system dynamic’s characteristics. The simulations are evaluated for three types of road conditions (dry, wet, and icy), and the performance of the adaptive pole placement control (APPC) are compared with pole placement control (PPC) and a passive system. The results show that the APPC strategy significantly improves the yaw rate and side slip angle of a bicycle plant model.

Keywords: adaptive control, active steering, pole placement, vehicle dynamics

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Authors: P. Hajyalikhani, E. Gilmore, C. Petty, J. Duron

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Wood framed construction is the most popular method of construction for residential buildings. The typical roof framing for wood-framed buildings is sloped and consists of several structural members, such as rafters, hips, and valleys that link to the ridge and ceiling joists. The most common type of wood framing used is platform framing, also known as stick framing. Failures of the wood framing structures are among the most common types of wind damage in densely populated regions. Wood-framed buildings are under uplift during tornadoes and hurricanes which cause the failure in the roof. The bracing long structure members such as hip and valley have a large impact on the resilience of wood-framed buildings. As a result, the common failures in wood-framed buildings are reviewed, and the critical support locations for lengthy hips and valleys with various slopes are analyzed and recommended.

Keywords: rafters, hips, valleys, hip, ceiling joist, roof failures, residential and commercial structures, hurricane, tornadoes, building codes

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Seung-Ho Yoo, Jong-Ryeul Sohn

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An environmental friendly or efficient heating & cooling systems attract a great attention, due to the energy or environmental problems. Especially the heat balance of human body is about 50% influenced by radiation exchange in built environment. Therefore, a thermal comfort characteristics in a radiant built environment need to be accessed through the development of an efficient evaluation method. Almost of Korean housings use traditionally the radiant floor heating system. A radiant cooling system attracts also many attention nowadays in the viewpoint of energy conservation and comfort. Thermal comfort characteristics in an enclosure with a radiant heating and cooling system are investigated by experiment, thermal sensation vote analysis and mean radiant temperature simulation. Asymmetric radiation between radiant heating ceiling and air heating system in 9 points of room is compared with each other.

Keywords: radiant heating and cooling ceiling, asymmetric radiation, thermal comfort, thermal sensation vote

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Authors: B. J. Kim, K. W. Nam, S. J. Lee

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Traditional social network services provide users with more information than is needed, and it is not easy to verify the authenticity of the information. This paper proposes a system that can only post messages where users are located to enhance the reliability of social networking services. The proposed system implements a Google Map API to post postings on the map and to read postings within a range of distances from the users’ location. The proposed system will only provide alerts, memories, and information about locations within a given range depending on the users' current location, providing reliable information that they believe will be necessary in real time. It is expected that the proposed system will be able to meet the real demands of users and create a more reliable social network services environment.

Keywords: social network, location, reliability, posting

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Authors: Rossella Marzullo

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Family plays a central role in the Calabrian criminal organization, which draws its strength from blood ties and gender stereotypes that still impose a strong verticalization of intra-family relationships for the benefit of men. However, female figures are of great importance in the organizational structure of the 'Ndrangheta families, despite the fact that they appear to be formally suffocated by the culture of gender subordination still strongly present in the archaic world of criminal organizations. And this is so much true that over time, the women of the 'Ndrangheta have added to the function of ‘internal containment’, the increasingly explicit function of intermediaries in the ‘external’ activities of the clan. But what happens in the 'Ndrangheta if women break the bond and decide to speak? The results are shocking. When a woman starts talking to ask the institutions for help, the system ‘goes crazy’, because the woman is considered the means of consolidating and transmitting family codes: she educates, forges, holds the structure together. If a woman from the 'Ndrangheta decides to speak out and get out of the family bottlenecks of the clan, she does not exclusively destroy the family; she destroys the system. This happens because, while not playing the same roles as men within organizations, women carry out support activities as intermediaries for the circulation of communications, thus ensuring the operability of the gang in practice and on a daily basis. Crossing the border means breaking the bonds of belonging, thus questioning one's own identity and reconstructing it according to other points of reference. How much these disruptive choices are feared by the men of the 'Ndrangheta has been seen in the dramatic stories of Lea Garofalo and Maria Concetta Cacciola: the fear of the breaking of the family pact, of the earthquake that arises from within, has marked their fate of death, useful both to stop the judicial action and to recompose the organization's estate under the aegis of terror. With physical, psychological violence, underhanded torture, and moral blackmail, the men of the mafia family tried to heal the shock caused by the voices of women, relying on violence and yet another attempt to subordinate them. This proves that the 'Ndrangheta is really afraid of them. The female voices of the 'Ndrangheta, who have shaken a consolidated and considered intangible system, represent the anti-'ndrangheta par excellence; in their choices, there is an even stronger desire to break with the mafia world.

Keywords: families, gender, ‘Ndrangheta, stereotypes

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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Authors: Melvin Mothoa

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Small Micro and Medium Enterprises are very significant for the development of their market economies. They are the main creators of the new working places, and they present a vital core of the market economy in countries across the globe. Access to finance is identified as crucial for small, micro, and medium-sized enterprises for their growth and innovation. This paper is conceived to propose a perception-based SMME framework to aid in access to financial support. Furthermore, the study will address issues that impede SMMEs in South Africa from obtaining finance from financial institutions. The framework will be tested against data collected from 200 Small Micro & Medium Enterprises in the Gauteng province of South Africa. The study adopts a quantitative method, and the delivery of self-administered questionnaires to SMMEs will be the primary data collection tool. Structural equation modeling will be used to further analyse the data collected.

Keywords: finance, small business, growth, development

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Authors: Jozef Jurcik, Miroslav Gutten, Milan Sebok, Daniel Korenciak, Jerzy Roj

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The paper presents the research results of electronic fuel injection system, which can be used for diagnostics of automotive systems. In the paper is described the construction and operation of a typical fuel injection system and analyzed its electronic part. It has also been proposed method for the detection of the injector malfunction, based on the analysis of differential current or voltage characteristics. In order to detect the fault state, it is needed to use self-learning process, by the use of an appropriate self-learning algorithm.

Keywords: electronic fuel injector, diagnostics, measurement, testing device

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Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

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This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: fuzzy logic, intelligent system, precision agriculture, renewable energy

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Authors: Daniel C. S. Lim

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There are numerous nutritional supplements, such as multivitamins and nutrition drinks, in the market today. Many of these supplements are expensive and tend to be driven commercially by business decisions and big marketing budgets. Many of the costs are ultimately borne by the end user in the quest for keeping to a healthy lifestyle. This paper proposes a system with a list of ten determinants to gauge how to decide the value of various supplements. It suggests variables such as composition, safety, efficacy and bioavailability, as well as several other considerations. These guidelines can help to tackle many of the issues that people of all ages face in the way that they receive essential nutrients. The system also aims to promote and improve the safety and choice of foods and supplements. In so doing, the system aims to promote the individual’s or population’s control over their own health and reduce the growing health care burden on the society.

Keywords: choice of foods and supplements, essential nutrients, nutritional supplements, system safety

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Authors: Risanda Alirastra Budiantoro, Riesanda Najmi Sasmita, Sri Herianingrum

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Allah has given the guidance in the form of Islam for Muslim to take and lead all the aspects of life including the economic activity. The Islamic economic system is believed to be the answer to the economic problems that exist at this time. The goal is to achieve falah in kaffah by not doing some economic activities that are in violation as prescribed by Islam. An example for this is riba. Discourse on riba can be said ‘classical’ both in the development of Islamic thought and in Islamic civilization because riba often occurs in all aspects of public life, especially economic transactions (in Islam called muamalah). Riba is an additional retrieval, either in a sale and purchase transaction or lending in a false or contrary to the principle of muamalah in Islam. Prohibition of riba is obtained from various sources by the Qur'an and Hadith Rasulullah SAW, so the scholars firmly and clearly defined the prohibition of riba because there are exploitative elements that can harm the others. So, this study is aimed to identify Islamic economic system and the prohibition of riba in historical perspective. From the results of this study, it is expected to be a good reference for the reader to understand the Islamic economic system and riba in the future.

Keywords: economics system, riba, historical perspective, economy

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Authors: Mohammad Jamalabadi, Noemi Zabari, Lukasz Bratasz

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Panel paintings -complex multi-layer structures consisting of wood support and a paint layer composed of a preparatory layer of gesso, paints, and varnishes- are among the category of cultural objects most vulnerable to relative humidity fluctuations and frequently found in museum collections. The current environmental specifications in museums have been derived using the criterion of crack initiation in an undamaged, usually new gesso layer laid on wood. In reality, historical paintings exhibit complex crack patterns called craquelures. The present paper analyses the structural response of a paint layer with a virtual network of rectangular cracks under environmental loadings using a three-dimensional model of a panel painting. Two modes of loading are considered -one induced by one-dimensional moisture response of wood support, termed the tangential loading, and the other isotropic induced by drying shrinkage of the gesso layer. The superposition of the two modes is also analysed. The modelling showed that minimum distances between cracks parallel to the wood grain depended on the gesso stiffness under the tangential loading. In spite of a non-zero Poisson’s ratio, gesso cracks perpendicular to the wood grain could not be generated by the moisture response of wood support. The isotropic drying shrinkage of gesso produced cracks that were almost evenly spaced in both directions. The modelling results were cross-checked with crack patterns obtained on a mock-up of a panel painting exposed to a number of extreme environmental variations in an environmental chamber.

Keywords: fracture saturation, surface cracking, paintings on wood, wood panels

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Authors: Semanur Savruk, Onur Akbatı

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Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: A. Shooshtari, A. R. Masoodi, S. Heyrani Moghaddam

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Free vibration analysis of a gabled frame with elastic support and semi-rigid connections is performed by using a program in OpenSees software. Natural frequencies and mode shape details of frame are obtained for two states, which are semi-rigid connections and elastic supports, separately. The members of this structure are analyzed as a prismatic nonlinear beam-column element in software. The mass of structure is considered as two equal lumped masses at the head of two columns in horizontal and vertical directions. Note that the degree of freedom, allocated to all nodes, is equal to three. Furthermore, the mode shapes of frame are achieved. Conclusively, the effects of connections and supports flexibility on the natural frequencies and mode shapes of structure are investigated.

Keywords: natural frequency, mode shape, gabled frame, semi-rigid connection, elastic support, OpenSees software

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Authors: M. Marsadek, A. Mohamed

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Power system security analysis is the most time demanding process due to large number of possible contingencies that need to be analyzed.  In a power system, any contingency resulting in security violation such as line overload or low voltage may occur for a number of reasons at any time.  To efficiently rank a contingency, both probability and the extent of security violation must be considered so as not to underestimate the risk associated with the contingency. This paper proposed a contingency ranking method that take into account the probabilistic nature of power system and the severity of contingency by using a newly developed method based on risk factor.  The proposed technique is implemented on IEEE 24-bus system.

Keywords: line overload, low voltage, probability, risk factor, severity

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Authors: Melaku Takele Abate, Abbi Lemma Wodajo, Adula Bekele Hunde

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This study aimed at exploring mathematics teachers' reactions, learning, school leaders’ support, and use of the Lesson Study for Transformative Assessment (LSforTA) program ideas in practice. The LSforTA program was new, and therefore, a local and grounded approach was needed to examine teachers’ knowledge and skills acquired using LSforTA. So, a design-based research approach was selected to evaluate and refine the LSforTA approach. The results showed that LSforTA increased teachers' knowledge and use of different levels of mathematics assessment tasks. The program positively affected teachers' practices of transformative assessment and enhanced their knowledge and skills in assessing students in a transformative way. The paper concludes how the LSforTA procedures were adapted in response to this evaluation and provides suggestions for future development and research.

Keywords: classroom assessment, feedback practices, lesson study, mathematics, design-based research

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: Mark Linden, Michael Brown, Lynne Marsh, Maria Truesdale, Stuart Todd, Nathan Hughes, Trisha Forbes, Rachel Leonard

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Background: The COVID-19 pandemic exacerbated the already significant strain placed on family carers of people with profound and multiple intellectual disabilities (PMID), given the withdrawal of many services during lockdown. The aim of this study was to explore the experiences of family carers of people with PMID during the COVID-19 pandemic. Methods: Online focus groups were conducted with family carers (n=126) from across the UK and the Republic of Ireland. Participants were asked about their experiences of the COVID-19 pandemic, coping strategies, and challenges faced. Focus groups were audio recorded, transcribed verbatim and analyzed through thematic analysis. Findings: Three themes emerged from our analysis of the data: (i) COVID-19 as a double-edged sword, (ii) The struggle for support (iii) the Constant nature of caring. These included 11 subthemes: (i) ‘COVID-19 as a catalyst for change’, ‘Challenges during COVID-19: dealing with change’, ‘Challenges during COVID-19: fear of COVID-19’, ‘The online environment: the new normal’ (ii) ‘Invisibility of male carers’, ‘Carers supporting carers’, ‘The only service you get is lip service: non-existent services’, ‘Knowing your rights’ (iii) ‘Emotional response to the caring role: Feeling devalued’, ‘Emotional response to the caring role: Desperation of caring’, ‘Multiple demands of the caring role.’ Conclusions: Poor or inconsistent access to services and support has been an ongoing difficulty for many family carers. The COVID-19 pandemic has only further intensified these difficulties, increasing family carers' stress. There is an urgent need to design services, such as online support programs, in partnership with family carers that adequately address their needs.

Keywords: intellectual disabilities, family carer, COVID-19, disability

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

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Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: rotating shaft, flexible blades, centrifugal stiffness, stability

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Authors: Shenlun Chen, Leonard Wee

Abstract:

Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

Procedia PDF Downloads 130

Authors: Lethamaga Tladi, Ray Kekwaletswe

Abstract:

This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

Procedia PDF Downloads 156