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Yayın Pros and cons of using building information modeling in the AEC industry(ASCE-AMER Soc Civil Engineers, 2019-08-01) Seyis Kazazoğlu, SenemAlthough a plethora of studies on building information modeling (BIM) have been conducted in the last decade, none of the previous studies collate and/or prioritize the benefits, risks, and challenges of BIM based on the data collected from a comprehensive literature review and subject matter experts (SMEs). In order to allow architecture, engineering, and construction (AEC) professionals and academics see the true potential of BIM in a wider context and help them understand its multiorganizational and multidisciplinary functions, there is an obvious necessity for identifying, classifying, and prioritizing the pros and cons of BIM; however, such a study is still currently absent in the AEC literature. The aim of this study is to identify, classify, and rank the pros and cons of BIM that address the benefits, challenges, and risks of BIM in the transition from computer-aided design (CAD). A literature review was performed and face-to-face semistructured interviews with SMEs on BIM were conducted for identification and classification purposes. A total of 41 types of benefits, 11 types of risks, and 13 types of challenges of BIM were identified via triangulation of literature review and face-to-face semistructured interviews with SMEs. The Delphi method was performed for prioritizing the benefits of BIM in terms of time, cost, and sustainability as well as the risks and challenges of BIM encountered in the transition process from CAD to BIM. The interrater agreement and significance-level statistics were performed to analyze and validate the consensus reached by the Delphi panel experts. This paper contributes to the existing body of knowledge on BIM by providing comprehensive identification and classification of the benefits, challenges, and risks of BIM, and prioritization of the benefits for BIM in terms of time, cost, and sustainability as well as the risks and challenges of BIM. The priority rankings of benefits, risks, and challenges of BIM ensure successful completion of projects and create additional value by allowing professionals to make well-informed decisions that support decreasing time and cost-related waste in the transition process from CAD to BIM.Yayın Modeling repair demand in existence of a nonstationary installed base(Elsevier B.V., 2023-09) Hekimoğlu, Mustafa; Karlı, DenizLife cycles of products consist of 3 phases, namely growth, maturity, and decline phases. Modeling repair demand is particularly difficult in the growth and decline stages due to nonstationarity. In this study, we suggest respective stochastic models that capture the dynamics of repair demand in these two phases. We apply our theory to two different operations management problems. First, using the moments of spare parts demand, we suggest an algorithm that selects a parametric distribution from the hypergeometric family (Ord, 1967) for each period in time. We utilize the algorithm in a single echelon inventory control problem. Second, we focus on investment decisions of Original Equipment Manufacturers (OEMs) to extend economic lifetimes of products with technology upgrades. Our results indicate that the second moment is sufficient for growing customer bases, whereas using the third moment doubles the approximation quality of theoretical distributions for a declining customer base. From a cost minimization perspective, using higher moments of demand leads to savings up to 13.6% compared to the single-moment approach. Also, we characterize the optimal investment policy for lifetime extension decisions from risk-neutral and risk-averse perspectives. We find that there exists a critical level of investment cost and installed base size for profitability of lifetime extension for OEMs. From a managerial point of view, we find that a risk-neutral decision maker finds the lifetime extension problem profitable. In contrast, even a slight risk aversion can make the lifetime extension decision economically undesirable.Yayın A low complexity modulation classification algorithm for MIMO systems(IEEE-INST Electrical Electronics Engineers Inc, 2013-10) Mühlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jondral, Friedrich K.A novel algorithm is proposed for automatic modulation classification in multiple-input multiple-output spatial multiplexing systems, which employs fourth-order cumulants of the estimated transmit signal streams as discriminating features and a likelihood ratio test (LRT) for decision making. The asymptotic likelihood function of the estimated feature vector is analytically derived and used with the LRT. Hence, the algorithm can be considered as asymptotically optimal for the employed feature vector when the channel matrix and noise variance are known. Both the case with perfect channel knowledge and the practically more relevant case with blind channel estimation are considered. The results show that the proposed algorithm provides a good classification performance while exhibiting a significantly lower computational complexity when compared with conventional algorithms.Yayın Semantic communications in networked systems: a data significance perspective(IEEE, 2022-07-01) Uysal, Elif; Kaya, Onur; Ephremides, Anthony; Gross, James; Codreanu, Marian; Popovski, Petar; Assaad, Mohamad; Liva, Gianluigi; Munari, Andrea; Soret, Beatriz; Soleymani, Touraj; Johansson, Karl HenrikWe present our vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information for communications and control in networked systems. We define semantics of information, not as the meaning of the messages, but as their significance, possibly within a real time constraint, relative to the purpose of the data exchange. We argue that research efforts must focus on laying the theoretical foundations of a redesign of the entire process of information generation, transmission and usage in unison by developing: advanced semantic metrics for communications and control systems; an optimal sampling theory combining signal sparsity and semantics, for real-time prediction, reconstruction and control under communication constraints and delays; semantic compressed sensing techniques for decision making and inference directly in the compressed domain; semantic-aware data generation, channel coding, feedback, multiple and random access schemes that reduce the volume of data and the energy consumption, increasing the number of supportable devices. This paradigm shift targets jointly optimal information gathering, information dissemination, and decision making policies in networked systems.Yayın Decision making, emotion recognition and childhood traumatic experiences in murder convicts ımprisoned with aggravated life sentence: a prison study(Turkish Neuropsychiatric Society, 2025-03) Çıkrıkçılı, Uğur; Yıldırım, Elif; Buker, Seda; Ger, Can; Erözden, Ozan; Gürvit, Hakan; Saydam, BilginIntroduction: Decision-making and emotion recognition are two fundamental themes in social cognition. Disorders in these areas can lead to interpersonal, psychosocial, and legal problems for the individual and society. The likelihood of consequent aggression and crime makes them foci of forensic psychiatry over time. In this study, two developmental disorders that have a clear relationship with crime, that are antisocial personality disorder (ASPD), and psychopathy are investigated for their relationship with these social cognitive deficits.Methods: The present study involved 23 male prison inmates who were diagnosed with both antisocial personality disorder and psychopathy, as well as 23 control participants who were matched for age, gender, and level of education. Following the psychiatric interview, Reading the Mind in the Eyes Test (RMET), the Iowa Gambling Test (IGT), Toronto Alexithymia Scale (TAS), Defense Styles Questionnaire (DSQ), Childhood Psychic Trauma Scale (CTQ), Hare Psychopathy Checklist (PCL-R) were administered to all participants. Results: The results of the study showed that ASPD group performed statistically worse than healthy controls in TAS, CTQ, all items of DSQ, PCL-R Factor 1 and 2, and all the IGT scores (p<0.05). There were no statistically significant difference between in the RMET test performancesConclusion: These results suggest that ASPD and psychopathy lead to impaired decision-making behaviors due to the inability to recognize one’s own emotions and impulsivity, and that these characteristics play a critical role in the criminal behavior of individuals. In addition, contrary to expectations, the results of affective theory of mind assessed with the RMET showed similar characteristics in homicide convicts and healthy controls. These data indicate the need for further research in the field of forensic psychiatry.Yayın Designing a scalable agricultural information system for pest detection and decision support in hazelnut cultivation(World Scientific Publishing Company, 2025-11-12) Aydın, ŞahinThis study presents a microservices-based, multi-tiered information system to detect, monitör and manage pest species that cause yield losses in hazelnut production. The system integrates a deep learning model for classifying pest images submitted by field users, the generation of pest density maps and location-based early warning mechanisms for growers. Delivered through mobile, web and desktop platforms, the system enables data sharing among farmers, researchers and decision-makers, supporting agricultural decisions. Experimental findings show that the DNN+ResNet50 architecture achieved the highest accuracy (91.88%) among all tested CNN models. Performance evaluations indicated that the Authentication and Heatmap services sustained high stability under loads of up to 1000 requests, while the Bug Classification Service was reliable up to 750 requests before reaching a critical resource threshold. The usability test resulted in an overall score of 38 out of 50, with sub-scores of Appropriateness Recognizability (0.73, Acceptable), Learnability (0.71, Acceptable), Operability (0.65, Questionable), User Error Protection (0.86, Good), User Interface Aesthetics (0.83, Good) and Accessibility (0.74, Acceptable). With its robust technical architecture and practical implementation, the proposed system can generate economic, social and commercial outcomes. This study provides a software engineering-oriented approach to the digitalization of agricultural production and the sustainable management of pests.Yayın Automating cyber risk assessment with public LLMs: an expert-validated framework and comparative analysis(Institute of Electrical and Electronics Engineers Inc., 2026-03-26) Ünal, Nezih Mahmut; Çeliktaş, BarışTraditional cyber risk assessment methodologies face a critical dilemma: they are either quantitative yet static and context-agnostic (e.g., CVSS), or context-aware yet highly labor-intensive and subjective (e.g., NIST SP 800-30). Consequently, organizations struggle to scale risk assessment to match the pace of evolving threats. This paper presents an automated, context-aware risk assessment framework that leverages the reasoning capabilities of publicly available Large Language Models (LLMs) to operationalize expert knowledge. Rather than positioning the LLM as the final decision-maker, the framework decouples semantic interpretation from risk scoring authority through a transparent, deterministic Dynamic Metric Engine. Unlike complex closed box machine learning models, our approach anchors the AI's reasoning to this expert-validated metric schema, with weights derived using the Rank Order Centroid (ROC) method from a survey of 101 cybersecurity professionals. We evaluated the framework through a comparative study involving 15 diverse real-world vulnerability scenarios (C1-C15) and three supplementary sensitivity stress tests (C16-C18). The validation scenarios were independently assessed by a cohort of ten senior human experts and two state-of-the-art LLM agents (GPT-4o and Gemini 2.0 Flash). The results show that the LLM-driven agents achieve scoring consistency closely aligned with the human median (Pearson r ranging from 0.9390 to 0.9717, Spearman ρ from 0.8472 to 0.9276) against a highly reliable expert baseline (Cronbach's α =0.996), while reducing the assessment cycle time by more than 100× (averaging under 4 seconds per case vs. a human average of 6 minutes). Furthermore, a dedicated context sensitivity analysis (C13-C15) indicates that the framework adapts risk scores based on organizational context (e.g., SME vs. Critical Infrastructure) for identical technical vulnerabilities. Importantly, the system is designed not merely to replicate expert intuition, but to enforce bounded, policy-consistent risk evaluation under predefined governance constraints. Overall, these findings suggest that commercially available LLMs, when constrained by expert-validated metric schemas, can support reproducible, transparent, and real-time risk assessments.
