Search results for: utility maximization

Authors: R. Sonda, F. Pellini, A. Invento, S. Mirandola, F. Riolfatti, D. Grigolato, G. P. Pollini

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The purpose of study is to assess utility of 18F-FDG PET/CT in patients with breast heteroplasia and possibility of changing the surgery/therapeutic treatment. Among these "under fourty-five" candidated for NAC, the prevalence of change in therapeutic approach in comparison with first and second level exams has been: 43.75%, while by 22% among the "over forty-five". The surgical timing according to first-level exams have been deferred in 31.46% cases; PET/CT has led to a change in therapeutic treatment of 48.31% on the previous given; then the addition of MRI has led to a similar variation. For all the total patients, the prevalent choice was found to the debulking approach by increasing from a prevalence of 12.92% to 15.17%, resulting in a reduction of conservative one.The present study set itself the objective to demonstrate how the FDG PET/CT could improve on breast imaging according to a more appropriate surgery.

Keywords: breast cancer, FGD PET/CT, preoperative staging, surgical approach

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Authors: Athina Thanou, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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The problem of museum visitor experience and congestion management – in various forms - has come increasingly under the spotlight over the last few years, since overcrowding can significantly decrease the quality of visitors’ experience. Evidence suggests that on busy days the amount of time a visitor spends inside a crowded house museum can fall by up to 60% compared to a quiet mid-week day. In this paper we consider the aforementioned problem, by treating museums as evolving social systems that induce constraints. However, in a cultural heritage space, as opposed to the majority of social environments, the momentum of the experience is primarily controlled by the visitor himself. Visitors typically behave selfishly regarding the maximization of their own Quality of Experience (QoE) - commonly expressed through a utility function that takes several parameters into consideration, with crowd density and waiting/visiting time being among the key ones. In such a setting, congestion occurs when either the utility of one visitor decreases due to the behavior of other persons, or when costs of undertaking an activity rise due to the presence of other persons. We initially investigate how visitors’ behavioral risk attitudes, as captured and represented by prospect theory, affect their decisions in resource sharing settings, where visitors’ decisions and experiences are strongly interdependent. Different from the majority of existing studies and literature, we highlight that visitors are not risk neutral utility maximizers, but they demonstrate risk-aware behavior according to their personal risk characteristics. In our work, exhibits are organized into two groups: a) “safe exhibits” that correspond to less congested ones, where the visitors receive guaranteed satisfaction in accordance with the visiting time invested, and b) common pool of resources (CPR) exhibits, which are the most popular exhibits with possibly increased congestion and uncertain outcome in terms of visitor satisfaction. A key difference is that the visitor satisfaction due to CPR strongly depends not only on the invested time decision of a specific visitor, but also on that of the rest of the visitors. In the latter case, the over-investment in time, or equivalently the increased congestion potentially leads to “exhibit failure”, interpreted as the visitors gain no satisfaction from their observation of this exhibit due to high congestion. We present a framework where each visitor in a distributed manner determines his time investment in safe or CPR exhibits to optimize his QoE. Based on this framework, we analyze and evaluate how visitors, acting as prospect-theoretic decision-makers, respond and react to the various pricing policies imposed by the museum curators. Based on detailed evaluation results and experiments, we present interesting observations, regarding the impact of several parameters and characteristics such as visitor heterogeneity and use of alternative pricing policies, on scalability, user satisfaction, museum capacity, resource fragility, and operation point stability. Furthermore, we study and present the effectiveness of alternative pricing mechanisms, when used as implicit tools, to deal with the congestion management problem in the museums, and potentially decrease the exhibit failure probability (fragility), while considering the visitor risk preferences.

Keywords: museum resource and visitor management, congestion management, propsect theory, cyber physical social systems

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Authors: Kalyani Kulkarni, Bharat Chaudhari

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This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.

Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation

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Authors: Alejandro Villegas, Cihan Varol

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Voice over Internet Protocol (VoIP) products is an emerging technology that can contain forensically important information for a criminal activity. Without having the user name and passwords, this forensically important information can still be gathered by the investigators. Although there are a few VoIP forensic investigative applications available in the literature, most of them are particularly designed to collect evidence from the Skype product. Therefore, in order to assist law enforcement with collecting forensically important information from variety of Betamax VoIP tools, CVOIP-FRU framework is developed. CVOIP-FRU provides a data gathering solution that retrieves usernames, contact lists, as well as call and SMS logs from Betamax VoIP products. It is a scripting utility that searches for data within the registry, logs and the user roaming profiles in Windows and Mac OSX operating systems. Subsequently, it parses the output into readable text and html formats. One superior way of CVOIP-FRU compared to the other applications that due to intelligent data filtering capabilities and cross platform scripting back end of CVOIP-FRU, it is expandable to include other VoIP solutions as well. Overall, this paper reveals the exploratory analysis performed in order to find the key data paths and locations, the development stages of the framework, and the empirical testing and quality assurance of CVOIP-FRU.

Keywords: betamax, digital forensics, report utility, VoIP, VoIPBuster, VoIPWise

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Authors: Nuwan Karunarathna, Hemali Seneviratne

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Distribution Utilities inherently present electrical hazards for their workers in addition to the general public especially due to bare overhead lines spreading out over a large geographical area. Therefore, certain procedures such as; de-energization, verification of de-energization, isolation, lock-out tag-out and earthing are carried out to ensure safe working conditions when conducting maintenance work on de-energized overhead lines. However, measures must be taken to coordinate the above procedures and to ensure successful and accurate execution of those procedures. Issuing of 'Work Permits' is such a measure that is used by the Distribution Utility considered in this paper. Unfortunately, the Work Permit method adopted by the Distribution Utility concerned here has not been successful in creating the safe working conditions as expected which was evidenced by four (4) number of fatalities of workers due to electrocution occurred in the Distribution Utility from 2016 to 2018. Therefore, this paper attempts to identify deficiencies in the Work Permit method and related contributing factors through careful analysis of the four (4) fatalities and work place practices to rectify the short comings to prevent future incidents. The analysis shows that the present level of coordination between the 'Authorized Person' who issues the work permit and the 'Competent Person' who performs the actual work is grossly inadequate to achieve the intended safe working conditions. The paper identifies the need of active participation of a 'Control Person' who oversees the whole operation from a bird’s eye perspective and recommends further measures that are derived through the analysis of the fatalities to address the identified lapses in the current work permit system.

Keywords: authorized person, competent person, control person, de-energization, distribution utility, isolation, lock-out tag-out, overhead lines, work permit

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Authors: Anil Khanal, Ali Osareh, Gary Lebby

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Wind energy offers a significant advantage such as no fuel costs and no emissions from generation. However, wind energy sources are variable and non-dispatchable. The utility grid is able to accommodate the variability of wind in smaller proportion along with the daily load. However, at high penetration levels, the variability can severely impact the utility reserve requirements and the cost associated with it. In this paper, the impact of wind energy is evaluated in detail in formulating the total utility cost. The objective is to minimize the overall cost of generation while ensuring the proper management of the load. Overall cost includes the curtailment cost, reserve cost and the reliability cost as well as any other penalty imposed by the regulatory authority. Different levels of wind penetrations are explored and the cost impacts are evaluated. As the penetration level increases significantly, the reliability becomes a critical question to be answered. Here, we increase the penetration from the wind yet keep the reliability factor within the acceptable limit provided by NERC. This paper uses an economic dispatch (ED) model to incorporate wind generation into the power grid. Power system costs are analyzed at various wind penetration levels using Linear Programming. The goal of this study shows how the increases in wind generation will affect power system economics.

Keywords: wind power generation, wind power penetration, cost analysis, economic dispatch (ED) model

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Authors: Joseph Paul Chunga

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The investment universe is awash with a myriad of financial choices that investors have to opt for, which principally culminates into a duality between aggressive or conservative approaches. Howbeit, it is pertinent to emphasize that the investment vehicles with an aggressive approach tend to take on more risk than the latter group in an effort to generate higher future returns for their respective investors. This study examines the conditionality effect that such partiality in financing has on the High-Tech and Public Utility companies listed on the Shenzhen Stock Exchange (SSE). Specifically, it examines the significance of the relationship between capitalization ratios of Total Debt Ratio (TDR), Degree of Financial Leverage (DFL) and profitability ratios of Earnings per Share (EPS) and Returns on Equity (ROE) on the Financial Risk of the two industries. We employ a modified version of the Panel Regression Model used by Rahman (2017) to estimate the relationship. The study finds that there is a significant positive relationship between the capitalization ratios on the financial risk of Public Utility companies more than High-Tech companies and a substantial negative relationship between the profitability ratios and the financial risk of the former than the latter companies. This then spells an important insight for prospective investors with regards to the volatility of earnings of such companies.

Keywords: financial leverage, debt financing, conservative firms, aggressive firms

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Yu-Shan Hsu

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This paper studies a two-sector growth model with a technology of social constant returns and with a utility that features either a zero or a positive income effect on the demand for leisure. The purpose is to investigate how the existence of aggregate instability or equilibrium indeterminacy depends on both the intensity of the income effect on the demand for leisure and the value of the labor supply elasticity. The main finding is that when there is a factor intensity reversal between the private perspective and the social perspective, indeterminacy arises even if the utility has a positive income effect on leisure demand. Moreover, we find that a smaller value of the labor supply elasticity increases the range of the income effect on leisure demand and thus increases the possibility of equilibrium indeterminacy. JEL classification: E3; O41

Keywords: indeterminacy, non-separable preferences, income effect, labor supply elasticity

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Authors: Jaydip De

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Urban parks are open places, green fields and riverside gardens usually maintained by public or private authorities, or eventually by both jointly; and utilized for a multidimensional purpose by the citizens. These parks are indeed the lung of urban centers. In urban socio-environmental setup, parks are the nucleus of social integration, community building, and physical development. In contemporary cities, these green places seem to perform as the panacea of congested, complex and stressful urban life. The alarmingly increasing urban population and the resultant congestion of high-rises are making life wearisome in neo-liberal cities. This has made the citizen always quest for open space and fresh air. In such a circumstance, the mere existence of parks is not capable of satisfying the growing aspirations. Therefore in this endeavour, a structured attempt is so made to empirically identify the utility, visitors’ satisfaction, and future needs through the cases of two urban parks of Kolkata Metropolitan Area, India. This study is principally based upon primary information collected through visitors’ perception survey conducted at the Chinsurah ground and Chandernagore strand. The correlation between different utility categories is identified and analyzed systematically. At the same time, indices like Weighted Satisfaction Score (WSS), Facility wise Satisfaction Index (FSI), Urban Park Satisfaction Index (UPSI) and Urban Park Necessity Index (UPNI) are advocated to quantify the visitors’ satisfaction and future necessities. It is explored that the most important utilities are passive in nature. Simultaneously, satisfaction levels of visitors are average, and their requirements are centred on the daily needs of the next generation, i.e., the children. Further, considering the visitors’ opinion planning measures are promulgated for holistic development of urban parks to revitalize sustainability of citified life.

Keywords: citified life, future needs, visitors’ satisfaction, urban parks, utility

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Authors: Asma Alzahrani, Elizabeth Stojanovski

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This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, factors influence

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Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

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In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

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Authors: Roberta Martino, Viviana Ventre

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Every day we face choices whose consequences are deferred in time. These types of choices are the intertemporal choices and play an important role in the social, economic, and financial world. The Discounted Utility Model is the mathematical model of reference to calculate the utility of intertemporal prospects. The discount rate is the main element of the model as it describes how the individual perceives the indeterminacy of subsequent periods. Empirical evidence has shown a discrepancy between the behavior expected from the predictions of the model and the effective choices made from the decision makers. In particular, the term temporal inconsistency indicates those choices that do not remain optimal with the passage of time. This phenomenon has been described with hyperbolic models of the discount rate which, unlike the linear or exponential nature assumed by the discounted utility model, is not constant over time. This paper explores the problem of inconsistency by tracing the decision-making process through the concept of impatience. The degree of impatience and the degree of decrease of impatience are two parameters that allow to quantify the weight of emotional factors and cognitive limitations during the evaluation and selection of alternatives. In fact, although the theory assumes perfectly rational decision makers, behavioral finance and cognitive psychology have made it possible to understand that distortions in the decision-making process and emotional influence have an inevitable impact on the decision-making process. The degree to which impatience is diminished is the focus of the first part of the study. By comparing consistent and inconsistent preferences over time, it was possible to verify that some anomalies in the discounted utility model are a result of the combination of cognitive bias and emotional factors. In particular: the delay effect and the interval effect are compared through the concept of misperception of time; starting from psychological considerations, a criterion is proposed to identify the causes of the magnitude effect that considers the differences in outcomes rather than their ratio; the sign effect is analyzed by integrating in the evaluation of prospects with negative outcomes the psychological aspects of loss aversion provided by Prospect Theory. An experiment implemented confirms three findings: the greatest variation in the degree of decrease in impatience corresponds to shorter intervals close to the present; the greatest variation in the degree of impatience occurs for outcomes of lower magnitude; the variation in the degree of impatience is greatest for negative outcomes. The experimental phase was implemented with the construction of the hyperbolic factor through the administration of questionnaires constructed for each anomaly. This work formalizes the underlying causes of the discrepancy between the discounted utility model and the empirical evidence of preference reversal.

Keywords: decreasing impatience, discount utility model, hyperbolic discount, hyperbolic factor, impatience

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Authors: Mohamed Saad, Huda Ismail

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The purpose of this research is to examine the impact of cryptocurrency classification on money laundering crimes and to analyze how the preferences of criminals differ according to the type of digital currency used. Specifically, we aim to explore the roles of stablecoins, utility coins, and privacy tokens in facilitating or hindering money laundering activities and to identify the key factors that influence the choices of criminals in using these cryptocurrencies. To achieve our research objectives, we used a dataset for the most highly traded cryptocurrencies (32 currencies) that were published on the coin market cap for 2022. In addition to conducting a comprehensive review of the existing literature on cryptocurrency and money laundering, with a focus on stablecoins, utility coins, and privacy tokens, Furthermore, we conducted several Multivariate analyses. Our study reveals that the classification of cryptocurrency plays a significant role in money laundering activities, as criminals tend to prefer certain types of digital currencies over others, depending on their specific needs and goals. Specifically, we found that stablecoins are more commonly used in money laundering due to their relatively stable value and low volatility, which makes them less risky to hold and transfer. Utility coins, on the other hand, are less frequently used in money laundering due to their lack of anonymity and limited liquidity. Finally, privacy tokens, such as Monero and Zcash, are increasingly becoming a preferred choice among criminals due to their high degree of privacy and untraceability. In summary, our study highlights the importance of understanding the nuances of cryptocurrency classification in the context of money laundering and provides insights into the preferences of criminals in using digital currencies for illegal activities. Based on our findings, our recommendation to the policymakers is to address the potential misuse of cryptocurrencies for money laundering. By implementing measures to regulate stable coins, strengthening cross-border cooperation, fostering public-private partnerships, and increasing cooperation, policymakers can help prevent and detect money laundering activities involving digital currencies.

Keywords: crime, cryptocurrency, money laundering, tokens.

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Authors: Hanefi Cinar, Musa Cibuk, Ismail Erturk, Fikri Aggun, Munip Geylani

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Mobile Wireless Sensor Networks (MWSNs) carry heterogeneous data traffic with different urgency and quality of service (QoS) requirements. There are a lot of studies made on energy efficiency, bandwidth, and communication methods in literature. But delay, high throughput, utility parameters are not well considered. Increasing demand for real-time data transfer makes these parameters more important. In this paper we design new MAC protocol which is delay constrained and targets for improving delay, utility, and throughput performance of the network and finding solutions on collision and interference problems. Protocol improving QoS requirements by using TDMA, FDM, and OFDMA hybrid communication methods with multi-channel communication.

Keywords: MWSN, delay, hybrid MAC, TDMA, FDM, OFDMA

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Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

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The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

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Authors: Linda Márcia Mendes Delazeri, Dênis Antônio Da Cunha

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Over the past few years, the evidence that human activities have altered the concentration of greenhouse gases in the atmosphere have become stronger, indicating that this accumulation is the most likely cause of climate change observed so far. The risks associated with climate change, although uncertain, have the potential to increase social vulnerability, exacerbating existing socioeconomic challenges. Developing countries are potentially the most affected by climate change, since they have less potential to adapt and are those most dependent on agricultural activities, one of the sectors in which the major negative impacts are expected. In Brazil, specifically, it is expected that the localities which form the semiarid region are among the most affected, due to existing irregularity in rainfall and high temperatures, in addition to economic and social factors endemic to the region. Given the strategic limitations to handle the environmental shocks caused by climate change, an alternative adopted in response to these shocks is migration. Understanding the specific features of migration flows, such as duration, destination and composition is essential to understand the impacts of migration on origin and destination locations and to develop appropriate policies. Thus, this study aims to examine whether climatic factors have contributed to rural-urban migration in semiarid municipalities in the recent past and how these migration flows will be affected by future scenarios of climate change. The study was based on microeconomic theory of utility maximization, in which, to decide to leave the countryside and move on to the urban area, the individual seeks to maximize its utility. Analytically, we estimated an econometric model using the modeling of Fixed Effects and the results confirmed the expectation that climate drivers are crucial for the occurrence of the rural-urban migration. Also, other drivers of the migration process, as economic, social and demographic factors were also important. Additionally, predictions about the rural-urban migration motivated by variations in temperature and precipitation in the climate change scenarios RCP 4.5 and 8.5 were made for the periods 2016-2035 and 2046-2065, defined by the Intergovernmental Panel on Climate Change (IPCC). The results indicate that there will be increased rural-urban migration in the semiarid region in both scenarios and in both periods. In general, the results of this study reinforce the need for formulations of public policies to avoid migration for climatic reasons, such as policies that give support to the productive activities generating income in rural areas. By providing greater incentives for family agriculture and expanding sources of credit for the farmer, it will have a better position to face climate adversities and to settle in rural areas. Ultimately, if migration becomes necessary, there must be the adoption of policies that seek an organized and planned development of urban areas, considering migration as an adaptation strategy to adverse climate effects. Thus, policies that act to absorb migrants in urban areas and ensure that they have access to basic services offered to the urban population would contribute to the social costs reduction of climate variability.

Keywords: climate change, migration, rural productivity, semiarid region

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Authors: Ana Ferreira, Ines Costa, Patricia Polónia, Josué Pereira, Olinda Faria, Pedro Alberto Silva

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Introduction: Optical coherence tomography (OCT) and visual field tools are pivotal in evaluating neurological deficits and predicting potential visual improvement following surgical decompression in neurosurgical patients. Despite their clinical significance, a comprehensive understanding of their utility in this context is lacking in the literature. This study aims to elucidate the applications of OCT and visual field assessment, delineating distinct patterns of visual deficit presentations within the studied cohort. Methods: This retrospective analysis considered all adult patients who underwent a single surgery for pituitary adenoma or anterior skull base meningioma with optic nerve involvement, coupled with neuro-ophthalmology evaluation, between July 2020 and January 2023. A minimum follow-up period of 6 months was deemed essential. Results: A total of 24 patients, with a median age of 61, were included in the analysis. Three primary patterns emerged: 1) Low visual field involvement with compromised OCT, 2) High visual field involvement with relatively unaffected OCT, and 3) Significant compromise observed in both OCT and visual fields. Conclusion: This study delineates various findings in OCT and visual field assessments with illustrative examples. Based on the current findings, a prospective cohort will be systematically collected to further investigate and validate these patterns and their prognostic significance, enhancing our understanding of the utility of OCT and visual fields in neurosurgical patients.

Keywords: OCT, neurosurgery, visual field, optic nerve

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Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.

Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant

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Authors: Carlson Murray, Ali Lazrak

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Robust experimental evidence of systematic violations of expected utility (EU) establishes that individuals facing risk overweight utility from low probability gains and losses when making choices. These findings motivated development of models of preferences with probability weighting functions, such as rank dependent utility (RDU). We solve for the optimal investing strategy of an RDU investor in a dynamic binomial setting from which we derive implications for investing behavior. We show that relative to EU investors with constant relative risk aversion, commonly measured probability weighting functions produce optimal RDU terminal wealth with significant downside protection and upside exposure. We additionally find that in contrast to EU investors, RDU investors optimally choose a portfolio that contains fair bets that provide payo↵s that can be interpreted as lottery outcomes or exposure to idiosyncratic returns. In a calibrated version of the model, we calculate that RDU investors would be willing to pay 5% of their initial wealth for the freedom to trade away from an optimal EU wealth allocation. The dynamic trading strategy that supports the optimal wealth allocation implies portfolio weights that are independent of initial wealth but requires higher risky share after good stock return histories. Optimal trading also implies the possibility of non-participation when historical returns are poor. Our model fills a gap in the literature by providing new quantitative and qualitative predictions that can be tested experimentally or using data on household wealth and portfolio choice.

Keywords: behavioral finance, probability weighting, portfolio choice

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Authors: Eko Adhi Setiawan, Duli Asih Siregar, Aiman Setiawan

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Solar energy is abundant in nature, particularly in the tropics which have peak sun hour that can reach 8 hours per day. In the fabrication process, Photovoltaic’s (PV) performance are tested in standard test conditions (STC). It specifies a module temperature of 25°C, an irradiance of 1000 W/ m² with an air mass 1.5 (AM1.5) spectrum and zero wind speed. Thus, the results of the performance testing of PV at STC conditions cannot fully represent the performance of PV in the tropics. For example Indonesia, which has a temperature of 20-40°C. In this paper, the effect of temperature on the choice of the 5 kW AC inverter topology on the PV system such as the Central Inverter, String Inverter and AC-Module specifically for the tropics will be discussed. The proper inverter topology can be determined by analysis of the effect of temperature and irradiation on the PV panel. The effect of temperature and irradiation will be represented in the characteristics of I-V and P-V curves. PV’s characteristics on high temperature would be analyzed using Solar panel modeling through MATLAB Simulink based on mathematical equations that form Solar panel’s characteristic curve. Based on PV simulation, it is known then that temperature coefficients of short circuit current (ISC), open circuit voltage (VOC), and maximum output power (PMAX) consecutively as high as 0.56%/oC, -0.31%/oC and -0.4%/oC. Those coefficients can be used to calculate PV’s electrical parameters such as ISC, VOC, and PMAX in certain earth’s surface’s certain point. Then, from the parameters, the utility of the 5 kW AC inverter system can be determined. As the result, for tropical area, string inverter topology has the highest utility rates with 98, 80 %. On the other hand, central inverter and AC-Module Topology has utility rates of 92.69 % and 87.7 % eventually.

Keywords: Photovoltaic, PV-Inverter Configuration, PV Modeling, Solar Panel Characteristics.

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Authors: Jai Heui Kim, Sotheara Veng

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This paper studies the portfolio optimization problem for a pension fund under a hybrid model of stochastic volatility and constant elasticity of variance (CEV) using asymptotic analysis method. When the volatility component is fast mean-reverting, it is able to derive asymptotic approximations for the value function and the optimal strategy for general utility functions. Explicit solutions are given for the exponential and hyperbolic absolute risk aversion (HARA) utility functions. The study also shows that using the leading order optimal strategy results in the value function, not only up to the leading order, but also up to first order correction term. A practical strategy that does not depend on the unobservable volatility level is suggested. The result is an extension of the Merton's solution when stochastic volatility and elasticity of variance are considered simultaneously.

Keywords: asymptotic analysis, constant elasticity of variance, portfolio optimization, stochastic optimal control, stochastic volatility

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Authors: Rony Tawk, Boutros Ghannam, Maroun Nemer

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Topology optimization technique presents a potential tool for the design and optimization of structures involved in mass and heat transfer. The method starts with an initial intermediate domain and should be able to progressively distribute the solid and the two fluids exchanging heat. The multi-objective function of the problem takes into account minimization of total pressure loss and maximization of heat transfer between solid and fluid subdomains. Existing methods account for the presence of only one fluid, while the actual work extends optimization distribution of solid and two different fluids. This requires to separate the channels of both fluids and to ensure a minimum solid thickness between them. This is done by adding a third objective function to the multi-objective optimization problem. This article uses density approach where each cell holds two local design parameters ranging from 0 to 1, where the combination of their extremums defines the presence of solid, cold fluid or hot fluid in this cell. Finite volume method is used for direct solver coupled with a discrete adjoint approach for sensitivity analysis and method of moving asymptotes for numerical optimization. Several examples are presented to show the ability of the method to find a trade-off between minimization of power dissipation and maximization of heat transfer while ensuring the separation and continuity of the channel of each fluid without crossing or mixing the fluids. The main conclusion is the possibility to find an optimal bi-fluid domain using topology optimization, defining a fluid to fluid heat exchanger device.

Keywords: topology optimization, density approach, bi-fluid domain, laminar steady state regime, fluid-to-fluid heat exchanger

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Authors: Chan Jong Park, Hye Min Park, Jeong Ho Kim, Ki Hyun Park, Koan Sik Joo

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This research used the MCNPX simulation program to evaluate the utility of a filter that was developed to minimize the damage to a semiconductor device during defect testing with X-ray. The X-ray generator was designed using the MCNPX code, and the X-ray absorption spectrum of the semiconductor device was obtained based on the designed X-ray generator code. To evaluate the utility of the filter, the X-ray absorption rates of the semiconductor device were calculated and compared for Ag, Rh, Mo and V filters with thicknesses of 25μm, 50μm, and 75μm. The results showed that the X-ray absorption rate varied with the type and thickness of the filter, ranging from 8.74% to 49.28%. The Rh filter showed the highest X-ray absorption rates of 29.8%, 15.18% and 8.74% for the above-mentioned filter thicknesses. As shown above, the characteristics of the X-ray absorption with respect to the type and thickness of the filter were identified using MCNPX simulation. With these results, both time and expense could be saved in the production of the desired filter. In the future, this filter will be produced, and its performance will be evaluated.

Keywords: X-ray, MCNPX, filter, semiconductor, damage

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Ahmad Umar, Ahmed A. Ibrahim, Mohsen A. Alhamami

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This study introduces a facile synthesis method for synthesizing reduced graphene oxide (rGO) nanosheets with surface decoration of polyaniline (PANI). The resultant rGO@PANI nanocomposite (NC) exhibit substantial potential as advanced electrode materials for high-performance supercapacitors. The strategic integration of PANI onto the rGO surface serves dual purposes, effectively mitigating the agglomeration of rGO films and augmenting their utility in supercapacitor applications. The PANI coating manifests a highly porous and nanosized morphology, fostering increased surface area and optimized mass transport by reducing diffusion kinetics. The nanosized structure of PANI contributes to the maximization of active sites, thereby bolstering the efficacy of the nanocomposites for diverse applications. The inherent conductive nature of the rGO surface significantly expedites electron transport, thereby amplifying the overall electrochemical performance of the nanocomposites. To systematically evaluate the influence of PANI concentration on the electrode performance, varying concentrations of PANI were incorporated. Notably, an elevated PANI concentration was found to enhance the response owing to the unique morphology of PANI. Remarkably, the 5% rGO@PANI NC emerged as the most promising candidate, demonstrating exceptional response characteristics with a specific capacitance of 314.2 F/g at a current density of 1 A/g. Furthermore, this catalyst exhibits outstanding long-term stability, retaining approximately 92% of its capacitance even after enduring 4000 cycles. This research underscores the significance of the synergistic integration of rGO and PANI in the design of high-performance supercapacitors. The elucidation of the underlying mechanisms governing the improved electrochemical properties contributes to the fundamental understanding of nanocomposite behavior, thereby paving the way for the rational design of next-generation energy storage materials.

Keywords: reduced graphene oxide, polyaniline, nanocomposites, supercapacitors, energy storage

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Dwi Endarti, Susi a Kristina, Rizki Noorizzati, Akbar E Nugraha, Fera Maharani, Kika a Putri, Asninda H Azizah, Sausanzahra Angganisaputri, Yunisa Yustikarini

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Cost utility analysis is the most recommended pharmacoeconomic method since it allows widely comparison of cost-effectiveness results from different interventions. The method uses outcome of quality-adjusted life year (QALY) or disability-adjusted life year (DALY). Measurement of QALY requires the data of utility dan life years gained. Utility is measured with the instrument for quality of life measurement such as EQ-5D. Recently, the EQ-5D is available in two versions which are EQ-5D-3L and EQ-5D-5L. This study aimed to compare the EQ-5D-3L and EQ-5D-5L to examine the most suitable version for Indonesian population. This study was an observational study employing cross sectional approach. Data of quality of life measured with EQ-5D-3L and EQ-5D-5L were collected from several groups of population which were respondent with chronic diseases, respondent with acute diseases, and respondent from general population (without illness) in Yogyakarta Municipality, Indonesia. Convenience samples of hypertension patients (83), diabetes mellitus patients (80), and osteoarthritis patients (47), acute respiratory tract infection (81), cephalgia (43), dyspepsia (42), and respondent from general population (293) were recruited in this study. Responses on the 3L and 5L versions of EQ-5D were compared by examining the psychometric properties including agreement, internal consistency, ceiling effect, and convergent validity. Based on psychometric properties tests of EQ-5D-3L dan EQ-5D-5L, EQ-5D-5L tended to have better psychometric properties compared to EQ-5D-3L. Future studies for health related quality of life (HRQOL) measurements for pharmacoeconomic studies in Indonesia should apply EQ-5D-5L.

Keywords: EQ-5D, Health Related Quality of Life, Indonesian Population, Psychometric Properties

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Authors: Megha Chavda, Parth Thummar, Rahul Ghetia

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This paper presents the voltage and current control of microgrid accompanied by the synchronization of microgrid with the main utility grid in both islanded and grid-connected modes. Distributed Energy Resources (DERs) satisfy the wide-spread power demand of consumer by behaving as a micro source for a low voltage (LV) grid or microgrid. Synchronization of the microgrid with the main utility grid is done using PLL and PWM gate pulse generation technique is used for the Voltage Source Converter. Potential Function method achieves the voltage and current control of this microgrid in both islanded and grid-connected modes. A low voltage grid consisting of three distributed generators (DG) is considered for the study and is simulated in time-domain using PSCAD/EMTDC software. The simulation results depict the appropriateness of voltage and current control of microgrid and synchronization of microgrid with the medium voltage (MV) grid.

Keywords: microgrid, distributed energy resources, voltage and current control, voltage source converter, pulse width modulation, phase locked loop

Procedia PDF Downloads 386