Search results for: decision aided tool

Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

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Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

Procedia PDF Downloads 160

Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

Procedia PDF Downloads 400

Authors: D. O. Ramadan, R. S. Dwyer-Joyce

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The measurement of the interface conditions in a cutting tool contact is essential information for performance monitoring and control. This interface provides the path for the heat flux to the cutting tool. This elevate in the cutting tool temperature leads to motivate the mechanism of tool wear, thus affect the life of the cutting tool and the productivity. This zone is representative by the tool-chip interface. Therefore, understanding and monitoring this interface is considered an important issue in machining. In this paper, an acoustic emission (AE) technique was used to find the correlation between AE parameters and the tool-chip interface. For this reason, a response surface design (RSD) has been used to analyse and optimize the machining parameters. The experiment design was based on the face centered, central composite design (CCD) in the Minitab environment. According to this design, a series of orthogonal cutting experiments for different cutting conditions were conducted on a Triumph 2500 lathe machine to study the sensitivity of the acoustic emission (AE) signal to change in tool-chip contact length. The cutting parameters investigated were the cutting speed, depth of cut, and feed and the experiments were performed for 6082-T6 aluminium tube. All the orthogonal cutting experiments were conducted unlubricated. The tool-chip contact area was investigated using a scanning electron microscope (SEM). The results obtained in this paper indicate that there is a strong dependence of the root mean square (RMS) on the cutting speed, where the RMS increases with increasing the cutting speed. A dependence on the tool-chip contact length has been also observed. However there was no effect observed of changing the cutting depth and feed on the RMS. These dependencies have been clarified in terms of the strain and temperature in the primary and secondary shear zones, also the tool-chip sticking and sliding phenomenon and the effect of these mechanical variables on dislocation activity at high strain rates. In conclusion, the acoustic emission technique has the potential to monitor in situ the tool-chip interface in turning and consequently could indicate the approaching end of life of a cutting tool.

Keywords: Acoustic emission, tool-chip interface, orthogonal cutting, monitoring

Procedia PDF Downloads 463

Authors: Siamak Ghorbani, Nikolay Ivanovich Polushin

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Chatter vibrations, occurring during cutting process, cause vibration between the cutting tool and workpiece, which deteriorates surface roughness and reduces tool life. The purpose of this study is to investigate the influence of cutting parameters and tool construction on surface roughness and vibration in turning of aluminum alloy AA2024. A new design of cutting tool is proposed, which is filled up with epoxy granite in order to improve damping capacity of the tool. Experiments were performed at the lathe using carbide cutting insert coated with TiC and two different cutting tools made of AISI 5140 steel. Taguchi L9 orthogonal array was applied to design of experiment and to optimize cutting conditions. By the help of signal-to-noise ratio and analysis of variance the optimal cutting condition and the effect of the cutting parameters on surface roughness and vibration were determined. Effectiveness of Taguchi method was verified by confirmation test. It was revealed that new cutting tool with epoxy granite has reduced vibration and surface roughness due to high damping properties of epoxy granite in toolholder.

Keywords: ANOVA, damping capacity, surface roughness, Taguchi method, vibration

Procedia PDF Downloads 283

Authors: Ananda Perera

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Computer-Assisted Medical Evaluation of Symptoms (CAMEOS) is a medical expert system designed to help General Practices (GPs) make an accurate diagnosis. CAMEOS comprises a knowledge base, user input, inference engine, reasoning module, and output statement. The knowledge base was developed by the author. User input is an Html file. The physician user collects data in the consultation. Data is sent to the inference engine at servers. CAMEOS uses set theory to simulate diagnostic reasoning. The program output is a list of differential diagnoses, the most probable diagnosis, and the diagnostic reasoning.

Keywords: CDSS, computerized decision support systems, expert systems, general practice, diagnosis, diagnostic systems, primary care diagnostic system, artificial intelligence in medicine

Procedia PDF Downloads 132

Authors: Navdeep Kaur

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The primary focus of this study is to answer “What is the role of corporate governance in corporate failures? Does poor corporate governance lead to corporate failures? If so, how?”. In doing so, the study examines the literature from multiple fields, including corporate governance, corporate failures and organizational decision making, and presents a research gap to analyze and explore the relationship between corporate governance practices and corporate failures through a behavioral lens. In approaching this, a qualitative research methodology is adopted to analyze the failure of Enron Corporation (United States). The research considered the case study organizations as the primary unit of analysis and the decision-makers as the secondary unit of analysis. Based on this research approach, the study reports the analytical results drawn from extensive and triangulated secondary data. The study then interprets the results in the context of the theoretical synthesis. The study contributes towards filling a gap in the research and presents a behaviourally plausible decision centered model of the role of corporate governance in corporate failures. The model highlights the critical role of the behavioral aspects of corporate governance decision making in corporate failures and focuses attention on the under-explored aspects of corporate governance decision making. The study also suggests a further understanding of ‘A Behavioral Theory of the Firm’ in relation to corporate failures.

Keywords: behavior, corporate failure, corporate governance, decision making, values

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Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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Authors: Babak Daneshvar Rouyendegh

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: Decision-Makers (DMs), Multi-Criteria Decision-Making (MCDM), Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE), Intuitionistic Fuzzy Numbers (IFN)

Procedia PDF Downloads 647

Authors: Luís Marques, João Rocha, Andreia Fernandes, Maria Moura, Cláudia Caseiro, Filipa Figueiredo, João Nunes

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The implementation of circularity strategies other than recycling, such as reducing the amount of raw material, as well as reusing or sharing existing products, remains marginal. The European Commission announced that the transition towards a more circular economy could lead to the net creation of about 700,000 jobs in Europe by 2030, through additional labour demand from recycling plants, repair services and other circular activities. Efforts to create new circular business models in accordance with completely circular processes, as opposed to linear ones, have increased considerably in recent years. In order to create a societal Circular Economy transition model, it is necessary to include innovative solutions, where startups play a key role. Early-stage startups based on new business models according to circular processes often face difficulties in creating enough impact. The StartUp Zero Program designs a model and approach to increase the flow of startups in the Circular Economy field, focusing on a systemic decision analysis and multi-generational approach, considering Multi-Criteria Decision Analysis to support a decision-making tool, which is also supported by the use of a combination of an Analytical Hierarchy Process and Multi-Attribute Value Theory methods. We define principles, criteria and indicators for evaluating startup prerogatives, quantifying the evaluation process in a unique result. Additionally, this entrepreneurship program spanning 16 months involved more than 2400 young people, from ages 14 to 23, in more than 200 interaction activities.

Keywords: circular economy, entrepreneurship, startups;, multi-criteria decision analysis

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Authors: Mikel Alonso López

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In order to begin the process of studying the task of making consumer decisions, the main decision models must be analyzed. The objective of this task is to see if there is a presence of emotions in those models, and analyze how authors that have created them consider their impact in consumer choices. In this paper, the most important models of consumer behavior are analysed. This review is useful to consider an unproblematic background knowledge in the literature. The order that has been established for this study is chronological.

Keywords: consumer behaviour, emotions, decision making, consumer psychology

Procedia PDF Downloads 414

Authors: Fabiano Araujo Soares, Sauro Emerick Salomoni, Joao Paulo Lima da Silva, Igor Luiz Moura, Adson Ferreira da Rocha

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This paper presents a tool developed in the Matlab platform. It was developed to simplify the analysis of surface electromyography signals (S-EMG) in a way accessible to users that are not familiarized with signal processing procedures. The tool receives data by commands in window fields and generates results as graphics and excel tables. The underlying math of each S-EMG estimator is presented. Setup window and result graphics are presented. The tool was presented to four non-engineer users and all of them managed to appropriately use it after a 5 minutes instruction period.

Keywords: S-EMG estimators, electromyography, surface electromyography, ARV, RMS, MDF, MNF, CV

Procedia PDF Downloads 528

Authors: M. Pappa, C. Efstathiou, G. Livanos, P. Xidas, D. Vakondios, E. Maravelakis, M. Zervakis, A. Antoniadis

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The choice of cutting tools in manufacturing processes is an essential parameter on which the required manufacturing time, the consumed energy and the cost effort all depend. If the number of tool changing times could be minimized or even eliminated by using a single convex tool providing multiple profiles, then a significant benefit of time and energy saving, as well as tool cost, would be achieved. A typical machine contains a variety of tools in order to deal with different curvatures and material removal rates. In order to minimize the required cutting tool changes, Actively Deformable micro-Cutters (ADmC) will be developed. The design of the Actively Deformable micro-Cutters will be based on the same cutting technique and mounting method as that in typical cutters.

Keywords: deformable cutters, cutting tool, milling, turning, manufacturing

Procedia PDF Downloads 435

Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

Procedia PDF Downloads 953

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

Procedia PDF Downloads 228

Authors: Iting Chiang, Cheng-Yu Wei, Chin-Teng Kuo, Po-Sheng Hsu, Yo-Lun Yang, Yung-Chang Kang, Chien-Chon Chen, Chih-Yuan Chen

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In recent years, it is reported that microalloying of nitrogen atoms within traditional Cr-Mo-V hot work tool steels can achieve better high temperature mechanical properties, which thus leads to such metallurgical approach widely utilized in the several commercial advanced hot work tool steels. Although the performance of hot work tool steel can be improved better by alloy composition design strategy, the influence of processing parameters on the mechanical property, especially on the service life of hot work tool steel, is still not fully understood yet. A longer service life of hot work tool steel can decrease the manufacturing cost effectively and thus become a research hot spot. According to several previous studies, it is generally acknowledged the service life of hot work tool steels can be increased effectively as the steels possessing higher hardness and toughness due to the formation and propagation of microcracks within the steel can be inhibited effectively. Therefore, in the present research, the designed experiments are primarily to explore the synergistic effect of nitrogen content and austenitization conditioning on the mechanical properties of hot work tool steels has been conducted and analyzed. No matter the nitrogen content, the results indicated the hardness of hot work tool steels increased as the austenitization treatment executed at higher temperature. On the other hand, an optimum toughness of hot work tool steel can be achieved as the austenitization treatment performed at a suitable temperature range. The possible explanation of such metallurgical phenomenon has been also proposed and analyzed in the present research.

Keywords: hot work tool steel, Cr-Mo-V, toughness, hardness, TEM

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Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

Procedia PDF Downloads 378

Authors: Onur Özdemir, M.Erhan ORHAN

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Knowledge Development (KD) is just one of the important phases of Knowledge Management (KM). KD is the phase in which intelligence is used to see the big picture. In order to understand whether information is important or not, we have to use the intelligence cycle that includes four main steps: aiming, collecting data, processing and utilizing. KD also needs these steps. To make a precise decision, the decision maker has to be aware of his subordinates’ ideas. If the decision maker ignores the ideas of his subordinates or participants of the organization, it is not possible for him to get the target. KD is a way of using wisdom to accumulate the puzzle. If the decision maker does not bring together the puzzle pieces, he cannot get the big picture, and this shows its effects on the battlefield. In order to understand the battlefield, the decision maker has to use the intelligence cycle. To convert information to knowledge, KD is the main means for the intelligence cycle. On the other hand, the “Z Generation” born after the millennium are really the game changers. They have different attitudes from their elders. Their understanding of life is different - the definition of freedom and independence have different meanings to them than others. Decision makers have to consider these factors and rethink their decisions accordingly. This article tries to explain the relation between KD and Generation Z. KD is the main method of target managing. But if leaders neglect their people, the world will be seeing much more movements like the Arab Spring and other insurgencies.

Keywords: knowledge development, knowledge management, generation Z, intelligence cycle

Procedia PDF Downloads 490

Authors: Mayuri Roy Choudhury

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In recent times the concept of agrivoltaics has gained popularity due to the dual use of land and the added value provided by photovoltaics in terms of renewable energy and crop production on farms. However, the transition towards agrivoltaics has been slow, and our research tries to investigate the obstacles leading towards the slow progress of agrivoltaics. We applied data science decision tree algorithms to quantify qualitative perceptions of farmers in the United States for agrivoltaics. To date, there has not been much research that mentions farmers' perceptions, as most of the research focuses on the benefits of agrivoltaics. Our study adds value by putting forward the voices of farmers, which play a crucial towards the transition to agrivoltaics in the future. Our results show a mixture of responses in favor of agrivoltaics. Furthermore, it also portrays significant concerns of farmers, which is useful for decision-makers when it comes to formulating policies for agrivoltaics.

Keywords: agrivoltaics, decision-tree algorithms, farmers perception, transition

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Authors: Rupita Ghosh, Ritwik Sarkar, Sumit K. Pal, Soumitra Paul

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The use of Hydroxyapatite bioceramics as restorative implants is widely known. These materials can be manufactured by pressing and sintering route to a particular shape. However machining processes are still a basic requirement to give a near net shape to those implants for ensuring dimensional and geometrical accuracy. In this context, optimising the machining parameters is an important factor to understand the machinability of the materials and to reduce the production cost. In the present study a method has been optimized to produce true particulate drilled composite of Hydroxyapatite Yttrium Phosphate. The phosphates are used in varying ratio for a comparative study on the effect of flexural strength, hardness, machining (drilling) parameters and bioactivity.. The maximum flexural strength and hardness of the composite that could be attained are 46.07 MPa and 1.02 GPa respectively. Drilling is done with a conventional radial drilling machine aided with dynamometer with high speed steel (HSS) and solid carbide (SC) drills. The effect of variation in drilling parameters (cutting speed and feed), cutting tool, batch composition on torque, thrust force and tool wear are studied. It is observed that the thrust force and torque varies greatly with the increase in the speed, feed and yttrium phosphate content in the composite. Significant differences in the thrust and torque are noticed due to the change of the drills as well. Bioactivity study is done in simulated body fluid (SBF) upto 28 days. The growth of the bone like apatite has become denser with the increase in the number of days for all the composition of the composites and it is comparable to that of the pure hydroxyapatite.

Keywords: Bioactivity, Drilling, Hydroxyapatite, Yttrium Phosphate

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Authors: Sally Heyeon Hwang

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Within decision theory, there are normative principles that dictate how one should act in addition to empirical theories of actual behavior. As a normative guide to one’s actual behavior, evidential or causal decision-theoretic equations allow one to identify outcomes with maximal utility values. The choice that each person makes, however, will, of course, differ according to varying assignments of weight and probability values. Regarding these different choices, it remains a subject of considerable philosophical controversy whether individual subjects have the capacity to exercise free will with respect to the assignment of probabilities, or whether instead the assignment is in some way constrained. A version of this question is given a precise form in Richard Jeffrey’s assumption that free will is necessary for Newcomb’s paradox to count as a decision problem. This paper will argue, against Jeffrey, that decision theory does not require the assumption of libertarian freedom. One of the hallmarks of decision-making is its application across a wide variety of contexts; the implications of a background assumption of free will is similarly varied. One constant across the contexts of decision is that there are always at least two levels of choice for a given agent, depending on the degree of prior constraint. Within the context of Newcomb’s problem, when the predictor is attempting to guess the choice the agent will make, he or she is analyzing the determined aspects of the agent such as past characteristics, experiences, and knowledge. On the other hand, as David Lewis’ backtracking argument concerning the relationship between past and present events brings to light, there are similarly varied ways in which the past can actually be dependent on the present. One implication of this argument is that even in deterministic settings, an agent can have more free will than it may seem. This paper will thus argue against the view that a stable background assumption of free will or determinism in decision theory is necessary, arguing instead for a compatibilist decision theory yielding a novel treatment of Newcomb’s problem.

Keywords: decision theory, compatibilism, free will, Newcomb’s problem

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Hala Shaari, Nuredin Ahmed

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Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject.

Keywords: factors, novice, programming, visualization

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Authors: Mustafa Kemal Bilici, Memduh Kurtulmuş, İlyas Kartal, Ahmet İrfan Yükler

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Friction stir welding is a solid-state joining process that has gained acceptable progress in recent years. This method which was first used for welding of aluminum and its alloys is now employed for welding of other materials such as polymers and composites. The aim of the present work is to investigate the mechanical properties of butt joints produced by friction stir welding (FSW) in high density polyethylene sheets of 4 mm thickness. The effects of critical welding parameters and tool design have affected on mechanical properties, weld surface and macrostructure of friction stir welded polyethylene. Experiments were performed at tool rotational speeds of 600, 900, 1200 and 1500 r/min and traverse speeds of 30, 45 and 60 mm/min, tool diameters (d) of 4, 5, 6 mm and tool shoulder diameters (D) 20, 25, 30 mm. A strength value of 80 % of the base material was achieved at the isolated optimum welding condition. According to the tool design, the welding parameters and the mechanical properties changed to a great extent. The highest tensile strength was achieved at low feed rates, high tool rotation speeds and shoulder diameters/pin diameters ratio.

Keywords: friction stir welding, mechanical properties, polyethylene, high density polyethylene, tool design

Procedia PDF Downloads 364

Authors: Yuliya Lipshits-Braziler

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For many young adults, career decision making is a difficult and complex process that may lead to indecision. Indecision is frequently associated with great psychological distress and low levels of well-being. One important resource for dealing with indecision is career decision self-efficacy (CDSE), which refers to people’s beliefs about their ability to successfully accomplish certain tasks involved in career choice. Drawing from Social Cognitive Theory, it has been hypothesized that CDSE correlates with (a) people’s likelihood to engage in or avoid career decision making tasks, (b) the amount of effort put into the decision making process, (c) the people’s persistence in decision making efforts when faced with difficulties, and (d) the eventual success in arriving at career decisions. Based on these assumptions, the present study examines the associations between the CDSE and 14 strategies for coping with career indecision among young adults. Using the structural equation modeling (SEM), the results showed that CDSE is positively associated with the use of productive coping strategies, such as information-seeking, problem-solving, positive thinking, and self-regulation. In addition, CDSE was negatively associated with nonproductive coping strategies, such as avoidance, isolation, ruminative thinking, and blaming others. Contrary to our expectations, CDSE was not significantly correlated with instrumental help-seeking, while it was negatively correlated with emotional help-seeking. The results of this study can be used to facilitate the development of interventions aiming to reinforce young adults’ career decision making self-efficacy, which may provide them with a basis for overcoming career indecision more effectively.

Keywords: career decision self-efficacy, career indecision, coping strategies, career counseling

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Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

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The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

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Authors: Daniela Evtimovska, Ivana Srbinovska, Padraig O’Rourke

Abstract:

Kostal Macedonia has the challenge to mill a rigid-flex printed circuit board (PCB). The PCB elaborated in this paper is made of FR4 material covered with polyimide through the whole surface on the one side, including the tabs where PCBs need to be separated. After milling only 1.44 meters, the updraft routing tool isn’t effective and causes polyimide debris on all PCB cuts if it continues to mill with the same tool. Updraft routing tool is used for all another product in Kostal Macedonia, and it is changing after milling 60 meters. Changing the tool adds 80 seconds to the cycle time. One solution is using a laser-cut machine. Buying a laser-cut machine for cutting only one product doesn’t make financial sense. The focus is given to find an internal solution among the options under review to solve the issue with polyimide debris. In the paper, the design of the rigid-flex panel is described deeply. It is evaluated downdraft routing tool as a possible solution which could be used for the flex rigid panel as a specific product. It is done a comparison between updraft and down draft routing tools from a technical and financial aspect of view, taking into consideration the customer requirements for the rigid-flex PCB. The results show that using the downdraft routing tool is the best solution in this case. This tool is more expensive for 0.62 euros per piece than updraft. The downdraft routing tool needs to be changed after milling 43.44 meters in comparison with the updraft tool, which needs to be changed after milling only 1.44 meters. It is done analysis which actions should be taken in order further improvements and the possibility of maximum serving of downdraft routing tool.

Keywords: Kostal Macedonia, rigid flex PCB, polyimide, debris, milling process, up/down draft routing tool

Procedia PDF Downloads 165

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

Abstract:

Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 356

Authors: Tadahiro Wada, Hiroyuki Hanyu

Abstract:

In this study, to clarify the effectiveness of an aluminum/chromium/tungsten-based-coated tool for cutting sintered steel, tool wear was experimentally investigated. The sintered steel was turned with the (Al60,Cr25,W15)N-, (Al60,Cr25,W15)(C,N)- and (Al64,Cr28,W8)(C,N)-coated cemented carbide tools according to the physical vapor deposition (PVD) method. Moreover, the tool wear of the aluminum/chromium/tungsten-based-coated item was compared with that of the (Al,Cr)N coated tool. Furthermore, to clarify the tool wear mechanism of the aluminum/chromium/tungsten-coating film for cutting sintered steel, Scanning Electron Microscope observation and Energy Dispersive x-ray Spectroscopy mapping analysis were conducted on the abraded surface. The following results were obtained: (1) The wear progress of the (Al64,Cr28,W8)(C,N)-coated tool was the slowest among that of the five coated tools. (2) Adding carbon (C) to the aluminum/chromium/tungsten-based-coating film was effective for improving the wear-resistance. (3) The main wear mechanism of the (Al60,Cr25,W15)N-, the (Al60,Cr25,W15)(C,N)- and the (Al64,Cr28,W8)(C,N)-coating films was abrasive wear.

Keywords: cutting, physical vapor deposition coating method, tool wear, tool wear mechanism, (Al, Cr, W)N-coating film, (Al, Cr, W)(C, N)-coating film, sintered steel

Procedia PDF Downloads 354

Authors: Oliveira M., Gonçalves L., Francisco I., Caramelo F., Vale F., Sanz D., Domingues M., Lopes M., Moreia D., Lopes T., Santos T., Cardoso H.

Abstract:

The ARTHUR project consists of a platform that allows the virtual performance of maxillofacial surgeries, offering, in a photorealistic concept, the possibility for the patient to have an idea of the surgical changes before they are performed on their face. For this, the system brings together several image formats, dicoms and objs that, after loading, will generate the bone volume, soft tissues and hard tissues. The system also incorporates the patient's stereophotogrammetry, in addition to their data and clinical history. After loading and inserting data, the clinician can virtually perform the surgical operation and present the final result to the patient, generating a new facial surface that contemplates the changes made in the bone and tissues of the maxillary area. This tool acts in different situations that require facial reconstruction, however this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. Being developed a cloud based solution, with mobile support, the tool aims to reduce the decision time window of patient. Because the current simulations are not realistic or, if realistic, need time due to the need of building plaster models, patient rates on decision, rely on a long time window (1,2 months), because they don’t identify themselves with the presented surgical outcome. On the other hand, this planning was performed time based on average estimated values of the position of the maxilla and mandible. The team was based on averages of the facial measurements of the population, without specifying racial variability, so the proposed solution was not adjusted to the real individual physiognomic needs.

Keywords: 3D computing, image processing, image registry, image reconstruction

Procedia PDF Downloads 175