Papers by turgut ozgu
Industry is responsible for one-quarter of the global CO 2 emissions. In this study, four differe... more Industry is responsible for one-quarter of the global CO 2 emissions. In this study, four different climate pathways are analyzed with a cost minimizing multihorizon stochastic optimization model, in order to analyze possible realizations of carbon capture and storage (CCS) in the power sector and main industrial sectors in Europe. In particular, we aim to achieve a deeper understanding of the distribution of capture by country and key sector (power, steel, cement and refinery), as well as the associated transport and storage infrastructure for CCS. Results point to the synergy effect of sharing common CCS infrastructres among power and major industrial sectors. The contribution of CCS is mainly found in three industrial sectors, particularly steel, cement and refineries) but also in the power sector to a lesser extent. It is worth noting that retrofitting of CCS in the power sector was not considered in this study. The geographical location for capture and storage, as well as timing and capacity needs are presented for different socio-economic pathways and corresponding emission targets. It has been shown that contributions of the three industry sectors in emissions reductions are neither geographically nor sector-wise homogeneous across the pathways.
ROBUST PLANNING OF IRRIGATION CONSIDERING WATER CONSUMPTION AND REVENUE, 2024
Water scarcity is a problem for many regions which requires immediate action, and solutions canno... more Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. In this study, a decision support model of biobjective stochastic linear formulation is proposed. The model is generating annual planting plans together with water consumption projections for each farmer in the region while taking revenue of the overall harvest into account. The structure of the proposed model maintains robustness against the volatilities in precipitation, yield, and market price. The inherent trade-off between water consumption and revenue lends itself to multi-objective planning. This is a perspective especially useful for regional administrations to plan next year's crop pattern together with agricultural incomes and irrigation expenses. Furthermore, it is also shown how the model can be used to investigate the potential of rainwater harvesting or switching to waterefficient irrigation methodologies. The decision support model is especially unique in the sense that it can generate a set of Pareto optimum solutions as opposed to a single objective counterpart. This property is helpful in terms of not only providing a broader perspective to evaluate and project the possibilities but also increasing the applicability of the results by providing flexible design framework
Expert Systems with Applications, 2012
Voice of the customer (VOC) is a critical analysis procedure that provides precise information re... more Voice of the customer (VOC) is a critical analysis procedure that provides precise information regarding customer input requirements for a product/service output. The ability to conduct a voice of the customer analysis, which could be gained through direct and indirect questioning, will enable engineers and other decision makers to successfully understand customer needs, wants, perceptions, and preferences. The information obtained from the customers is then translated into critical targets that will be used to ultimately satisfy the customer requirements. During this research project, different forms of customer input, including qualitative and quantitative data, were transformed to a common data format to develop a correlation between design input requirements and product/service outputs. We have developed a new method for measuring customer satisfaction ratio (CSR) by considering the following: mining both textual and quantitative data, multiple design parameters, mapping output on a scale of 0-1, and a decision template for means of measure. Previous measures of CSR fail to incorporate the cost implication of fixing customer complaints/issues; however, we include this important and unique measure in our research. The implication of this research will reduce Things Gone Wrong (TGW's) and engineering development time and will achieve improvements in JD Power ratings, quality perception, marketing tools, and customer satisfaction.
Expert Systems with Applications, 2012
Voice of the customer (VOC) is a critical analysis procedure that provides precise information re... more Voice of the customer (VOC) is a critical analysis procedure that provides precise information regarding customer input requirements for a product/service output. The ability to conduct a voice of the customer analysis, which could be gained through direct and indirect questioning, will enable engineers and other decision makers to successfully understand customer needs, wants, perceptions, and preferences. The information obtained from the customers is then translated into critical targets that will be used to ultimately satisfy the customer requirements. During this research project, different forms of customer input, including qualitative and quantitative data, were transformed to a common data format to develop a correlation between design input requirements and product/service outputs. We have developed a new method for measuring customer satisfaction ratio (CSR) by considering the following: mining both textual and quantitative data, multiple design parameters, mapping output on a scale of 0-1, and a decision template for means of measure. Previous measures of CSR fail to incorporate the cost implication of fixing customer complaints/issues; however, we include this important and unique measure in our research. The implication of this research will reduce Things Gone Wrong (TGW's) and engineering development time and will achieve improvements in JD Power ratings, quality perception, marketing tools, and customer satisfaction.
Conference Presentations by turgut ozgu
Fair Classification with Ensembles, 2023
Machine learning algorithms are spreading into many essential decision-making procedures of intel... more Machine learning algorithms are spreading into many essential decision-making procedures of intelligent systems. These algorithms rely on big data which contain several sensitive features regarding the training instances such as gender, age, and race. In some contexts, these features might be useful and relevant like in health or other physiology-related frameworks. However, there are some fields where these features should be ignored like legal, financial, or educational incentivizing decisions. In complex decision-making procedures, it is important to guarantee indifference to these sensitive features. Choosing suitable algorithms or designing decision-making procedures that take this aspect of fairness into account is of crucial importance; especially from the reliability of upcoming intelligent systems which directly affects the impact of the new technology. In this study sample fairness assessment, experiments are performed in three different relevant contexts by applying two different ensemble building methods. It is shown how fairness can be assessed without hurting the accuracy. Furthermore, guidelines are provided for experimental design in order to derive more generic observations regarding incorporating the fairness notion into major classification algorithms 1 .
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Papers by turgut ozgu
Conference Presentations by turgut ozgu