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Intelligent health monitoring in 6G networks: machine learning-enhanced VLC-based medical body sensor networks
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-23) Antaki, Bilal; Dalloul, Ahmed Hany; Miramirkhani, Farshad
Recent advances in Artificial Intelligence (AI)-driven wireless communication are driving the adoption of Sixth Generation (6G) technologies in crucial environments such as hospitals. Visible Light Communication (VLC) leverages existing lighting infrastructure to deliver high data rates while mitigating electromagnetic interference (EMI); however, patient movement induces fluctuating signal strength and dynamic channel conditions. In this paper, we present a novel integration of site-specific ray tracing and machine learning (ML) for VLC-enabled Medical Body Sensor Networks (MBSNs) channel modeling in distinct hospital settings. First, we introduce a Q-learning-based adaptive modulation scheme that meets target symbol error rates (SERs) in real time without prior environmental information. Second, we develop a Long Short-Term Memory (LSTM)-based estimator for path loss and Root Mean Square (RMS) delay spread under dynamic hospital conditions. To our knowledge, this is the first study combining ray-traced channel impulse response modeling (CIR) with ML techniques in hospital scenarios. The simulation results demonstrate that the Q-learning method consistently achieves SERs with a spectral efficiency (SE) lower than optimal near the threshold. Furthermore, LSTM estimation shows that D1 has the highest Root Mean Square Error (RMSE) for path loss (1.6797 dB) and RMS delay spread (1.0567 ns) in the Intensive Care Unit (ICU) ward, whereas D3 exhibits the highest RMSE for path loss (1.0652 dB) and RMS delay spread (0.7657 ns) in the Family-Type Patient Rooms (FTPRs) scenario, demonstrating high estimation accuracy under realistic conditions.
Relationships among organizational-level maturities in artificial intelligence, cybersecurity, and digital transformation: a survey-based analysis
(Institute of Electrical and Electronics Engineers Inc., 2025-05-19) Kubilay, Burak; Çeliktaş, Barış
The rapid development of digital technology across industries has highlighted the growing need for enhanced competencies in Artificial Intelligence (AI), Cyber security (CS), and Digital Transformation (DT). While there is extensive research on each of these domains in isolation, few studies have investigated their relationship and joint impact on organizational maturity. This study aims to address this gap by analyzing the relationships among the maturity levels of AI, CS, and DT at the organizational level using Structural Equation Modeling (SEM) and descriptive statistical methods. A mixed-methods design combines quantitative survey data with synthetic modeling techniques to assess organizational preparedness. The findings demonstrate significant bidirectional correlations among AI, CS, and DT, with technology and finance being more advanced than government and education. The research highlights the necessity of an integrated AI-CS strategy and provides actionable recommendations to increase investments in these domains. In contrast to the preceding fragmented evaluations, the current research establishes a comprehensive, empirically grounded framework that acts as a strategic reference point for digital resilience. Follow-up studies will involve collecting real-world industry data in support of empirical validation and predictive ability in measuring AI and CS maturity. This research adds to the existing literature by filling the gaps among fragmented digital maturity models and providing a consistent empirical base for organizations to thrive in an evolving technological environment.
Goal-Oriented Random Access (GORA)
(Institute of Electrical and Electronics Engineers Inc., 2025-08) Topbaş, Ahsen; Ari, Çağrı; Kaya, Onur; Uysal, Elif
We propose Goal-Oriented Random Access (GORA), where transmitters jointly optimize what to send and when to access the shared channel to a common access point, considering the ultimate goal of the information transfer at its final destination. This goal is captured by an objective function, which is expressed as a general (not necessarily monotonic) function of the Age of Information. Our findings reveal that, under certain conditions, it may be desirable for transmitters to delay channel access intentionally and, when accessing the channel, transmit aged samples to reach a specific goal at the receiver.
Drought analysis based on nonparametric multivariate standardized drought index in the Seyhan River Basin
(Springer Science and Business Media B.V., 2025-05) Terzi, Tolga Barış; Önöz, Bihrat
Drought is a detrimental natural hazard that is a threat to the social and ecological aspects of life. Unlike other natural hazards, drought occurs slowly and gradually, making it difficult to detect its formation, leading to severe consequences in the affected area. Therefore, precise and reliable monitoring of drought is crucial to implement effective drought mitigation strategies. Drought indices are significant tools for drought monitoring; single variable indices are quite frequently used in the literature to assess drought conditions. Although these indices are generally accurate at characterizing the specific type of drought they were developed for, they fail to provide a comprehensive representation of drought conditions. Hence, this study applies a nonparametric multivariate standardized drought index (MSDI) that integrates meteorological and hydrological drought to investigate the dynamics of drought events within the Seyhan River Basin (SRB). Trend analyses were conducted to detect any directional changes in the drought patterns within the SRB. Additionally, this study examined the potential effects of El Nino-Southern Oscillation events on the MSDI series to determine their impact on drought conditions in the SRB. The results indicate that the MSDI outperforms the single variable indices in characterizing drought conditions within the basin. The calculations conducted for 5 different time scales 1, 3, 6, 9 and 12-months showed satisfactory results in multivariate analysis of drought. Upon examining the trend analyses, MSDI series showed an insignificant negative trend in all stations within the SRB. The MSDI series was strongly influenced by Nino 3.4 and Arctic Oscillation (AO) indices while sunspot activities had a relatively weak impact on the MSDI series.
Grammar or crammer? the role of morphology in distinguishing orthographically similar but semantically unrelated words
(Institute of Electrical and Electronics Engineers Inc., 2025) Ercan, Gökhan; Yıldız, Olcay Taner
We show that n-gram-based distributional models fail to distinguish unrelated words due to the noise in semantic spaces. This issue remains hidden in conventional benchmarks but becomes more pronounced when orthographic similarity is high. To highlight this problem, we introduce OSimUnr, a dataset of nearly one million English and Turkish word-pairs that are orthographically similar but semantically unrelated (e.g., grammar - crammer). These pairs are generated through a graph-based WordNet approach and morphological resources. We define two evaluation tasks - unrelatedness identification and relatedness classification - to test semantic models. Our experiments reveal that FastText, with default n-gram segmentation, performs poorly (below 5% accuracy) in identifying unrelated words. However, morphological segmentation overcomes this issue, boosting accuracy to 68% (English) and 71% (Turkish) without compromising performance on standard benchmarks (RareWords, MTurk771, MEN, AnlamVer). Furthermore, our results suggest that even state-of-the-art LLMs, including Llama 3.3 and GPT-4o-mini, may exhibit noise in their semantic spaces, particularly in highly synthetic languages such as Turkish. To ensure dataset quality, we leverage WordNet, MorphoLex, and NLTK, covering fully derivational morphology supporting atomic roots (e.g., '-co_here+ance+y' for 'coherency'), with 405 affixes in Turkish and 467 in English.
Cognitive reserve and aging: impacts on theory of mind and executive functions
(Routledge, 2025-03) Şandor, Serra; Hıdıroğlu Ongun, Ceren; Yıldırım, Elif
Aim: This study examines the effects of cognitive reserve (CR) on Executive Functions (EF) and Theory of Mind (ToM). While CR is suggested to mitigate age-related cognitive decline, its relationship with social cognition remains limited and inconsistent in the literature. It was hypothesized that the effect of CR on ToM might be indirect, mediated by EF and working memory. Methods: 225 cognitively healthy participants were included. CR was measured with the Cognitive Reserve Index Questionnaire, EF with verbal fluency and the Stroop Test, and WM using digit span tasks. Structural Equation Modeling was used to analyze the relationships among CR, EF, WM, and SC, controlling for age and gender. Results: CR was significantly associated with both RMET and FPRT performances. Mediation analysis revealed the direct effects of CR on RMET performance, while the effects on FPRT performance were mediated by executive functions. WM had a partial mediating effect on EF and ToM, but did not directly influence FPRT. Education was most strongly associated with RMET performance, while leisure activities were linked to FPRT performance. Conclusion: These findings suggest that CR indirectly supports ToM by enhancing EF and highlight the importance of interventions aimed at strengthening executive control to support social cognition in aging.
Exploring the impact of Flash technique on test anxiety among adolescents
(SAGE Publications Ltd, 2025-07) Çitil Akyol, Canan; İnci İzmir, Sevim Berrin
This study aims to investigate the specific effects of Flash Technique (FT) on adolescents with test anxiety. This follow-up study consists of 38 adolescents, 14–17 years of age (M = 15.39, SD = 1.13). Pre-post assessments were conducted using the Test Anxiety Inventory (TAI), Scale of Attitudes Negatively Affecting the Performance I/Test (POET), and Beck Anxiety Inventory (BAI) at baseline, at the end of the 4thand 12thweeks of therapy. The FT was applied for 12 weeks, with one weekly session as an intervention. As a result of the therapy process, the baseline means of total BAI scores decreased from 25.26 to 2.18; the baseline means of TAI decreased from 149.79 to 39.13, and the baseline mean of POET decreased from 298.47 to 73.84 at the end of the 12th week of therapy. Also, the baseline means of SUD scores decreased from 9.42 to zero at the end of the 12th week of treatment. All the adolescents showed complete improvement after the 12th week of the FT. The study findings showed that the test anxiety symptoms significantly decreased with the treatment of the FT. FT can be an effective intervention for test anxiety in adolescents.
Treatment and long-term outcome of mental disorders: The grim picture from a quasi-epidemiological investigation in 54,826 subjects from 40 countries
(Elsevier Ireland Ltd, 2025-06) Fountoulakis, Konstantinos N.; Karakatsoulis, Gregory; Abraham, Seri; Adorjan, Kristina; Uddin Ahmed, Helal; Alarcòn, Renato Daniel; Arai, Kiyomi; Auwal, Sani Salihu; Berk, Michael; Levaj, Sarah; Yılmaz Kafalı, Helin
Introduction: This study registered rates of specific treatment options for mental disorders as well as their long-term outcome. Material and methods: The history of mental disorders was used as a proxy for diagnosis. The data came from the COMET-G study (40 countries; 54,826 subjects, 64.73 % females, 35.45±13.51 years old). The analysis included descriptive statistics, Risk Ratios, t-tests, and ANCOVA's. Results: 24.14 % reported a history of any mental disorder (depression >12 %, non-affective psychosis and Bipolar disorder 1 % each, >20 % self-injury, >10 % had attempted suicide, 7.17 % illegal substance abuse). Most patients were not under any kind of treatment (59.44 %) and most were not receiving treatment as recommended (e.g. 90 % of Bipolar and 2/3 of psychotic patients). No treatment at all and psychotherapy as monotherapy were consistently related to poorer outcomes. In anxiety or depression, only antidepressant monotherapy and benzodiazepines, in Bipolar disorder only antipsychotic monotherapy in males and antidepressant monotherapy in females and in non-affective psychosis antipsychotics and psychotherapy in females only, were related to good outcomes. No treatment modality was related to a good outcome in those with a history of self-harm, suicidal attempts, or illegal substance use. Only depression and treatment with antidepressants were related to metabolic syndrome. Discussion: In the community, the overwhelming majority of mental patients do not receive appropriate treatment or, even worse, no treatment at all. The outcome is unfavourable for the majority and only a few selective treatment options seem to make a difference.
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, Bilgin
Introduction: 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.
Design and control of high-frequency buck converter fed six-step drive for air-core PMSM
(Institute of Electrical and Electronics Engineers Inc., 2025-02) Jena, Sritam; Kumar, Saurabh; Deshmukh, Akshay Vijayrao; Hava, Ahmet Masum; Akın, Bilal; Gabrys, Christopher; Rodgers, Timothy
Air-core permanent magnet synchronous motors (PMSMs) machines are becoming known for their higher efficiency, lighter weight designs, and superior performance compared to widely utilized induction motors (IMs). They hold great potential for diverse industrial applications. However, effectively harnessing this potential requires overcoming drive hardware and control challenges. This research introduces a silicon carbide (SiC)-based two-phase interleaved buck-converter-fed quasi-current source inverter (quasi-CSI) drive tailored for driving low-inductance air-core PMSMs which is ideal for heavy-duty fan and pump applications. Operating in the discontinuous current mode (DCM) with an effective switching frequency of 1 MHz, this drive is designed to address efficiency and the very low-cost market constraints while simultaneously reducing control complexity an issue associated with its high switching frequency. The article also analyzes two critical control challenges of mitigating high current spikes due to air-core machines' low inductance and finding solutions to overcome microcontroller resource limitations when executing time-critical functions within interrupt subroutines (ISRs). The culmination of this work is a 300 V dc-bus and five-horsepower electric drive prototype with closed-loop speed control. Experimental results illustrate a 2% enhancement in overall efficiency compared to conventional induction machine (IM) drives in similar applications (e.g., fan and pump) and ratings, alongside a significant 50% reduction in drive volume.
A practical control method for single-phase input PMSM drives with small DC-Link capacitor
(Institute of Electrical and Electronics Engineers Inc., 2025-03) Deshmukh, Akshay Vijayrao; Afshar, Mojtaba; Jena, Sritam; Hava, Ahmet Masum; Yu, Zhen; Akın, Bilal
The primary function of the large electrolytic dc-link capacitor in the single-phase input motor drives is to enhance dc voltage stability by minimizing voltage fluctuations. Because they are both bulky and unreliable components, reducing the size of dc-link capacitors or substituting them with significantly low capacitance value film capacitors offers numerous advantages. This article introduces a method that allows using a voltage source inverter with a small film dc-link capacitor, which results in equivalent performance to high-value capacitor drives. In this approach, the effect of dc-link voltage ripple is designed as a periodic disturbance in the current loop. A proportional-integral-resonant (PIR) control strategy is implemented to eliminate the designed double-line frequency disturbance observed in motor currents, thereby ensuring a smooth motor torque response. This solution meets crucial criteria for home appliances, specifically addressing input current harmonic requirements through power factor correction while effectively reducing the adverse effects of substantial dc-link ripple on motor torque, even when employing a film capacitor (10–50 µF range). The proposed framework is experimentally tested on permanent magnet synchronous motors with fan-load and dynamometers. Experimental results demonstrate, with PIR, an 80% reduction in current and torque ripple occurring due to the use of a low-value dc-link film capacitor. This also achieves performance within ±5% of the results obtained with a drive equipped with a 1200 µF dc capacitor. In addition, the line-side power factor exceeds 0.98 for loads exceeding 8% of the rated power.
Emotion dysregulation as a mediator between parental emotional availability and game addiction among Turkish late adolescents
(Routledge, 2025-02) Ülkümen, İpek; Aktan, Zekeriya Deniz
This study aimed to examine how difficulty in emotion regulation mediates the relationship between parental emotional availability and game addiction among Turkish late adolescents. 537 adolescents completed the Lum Emotional Availability of Parents, the Difficulties in Emotion Regulation Scale, Internet Gaming Disorder Short Form, and Sociodemographic Characteristics and Data Form. The results show that difficulty in emotion regulation fully mediates between parental emotional availability scores and adolescents’ game addiction scores. It can be concluded that interventions for the prevention and treatment of game addiction in late adolescents should focus on improving the parents’ emotional support and adolescents’ emotion regulation skills.
Turkish validity and reliability study of the childhood illness attitude scale
(Routledge, 2025-03) Aktan, Zekeriya Deniz; İnci İzmir, Sevim Berrin; Ünlü, Beyza; Yılmaz Kahraman, İpek Su
Severe forms of health anxiety cause serious dysfunction in people’s lives. Childhood Illness Attitude Scales (CIAS) is an assessment tool used to evaluate childhood health anxiety yet has not been validated for use in Turkey. The study aimed to examine the psychometric properties and factor structure of the Turkish version of the CIAS (CIAS-TR). The scale was administered to 306 children aged between 8 and 15 years. In addition to the CIAS-TR, participants were asked to complete the Screen for Child Anxiety-Related Emotional Disorders (SCARED) and the Pediatric Quality of Life Inventory (PedsQL). To measure test-retest reliability, CIAS-TR was completed by participants 15 days later. Results demonstrated good psychometric properties with high internal consistency and test-retest reliability. A positive correlation with SCARED and a negative correlation with PedsQL. Results from Confirmatory Factor Analysis suggested that a four-factor model best fit the data. The findings of the study indicate that the Turkish adaptation of the CIAS is an appropriate tool for assessing health anxiety in children.
Critical digital data enabling traceability for smart honey value chains
(Taylor and Francis Ltd., 2025-02) Ziemba, Ewa Wanda; Maruszewska, Ewa Wanda; Karmanska, Anna; Aydın, Mehmet Nafiz; Aydın, Şahin
Data analysis and sharing are becoming increasingly important in creating value within food supply chains, including honey value chains. While some data is readily shared between supply chain actors, unlocking further benefits requires additional investments in digital data capturing, particularly for value-based claims such as sustainability, equity, and traceability from hives to customers. This study aims to identify critical digital data necessary for smart honey value chains to ensure traceability and transparency while fostering trust among beekeepers, intermediaries, and consumers. Semi-structured interviews with 30 beekeeping experts were conducted to explore their perspectives. The analysis identified four critical categories of data—beekeeper data, apiary data, honey data, and apiary practices data—encompassing 21 specific data points essential for ensuring transparency, traceability, and trust. These findings provide novel insights into the digital data requirements necessary to support the honey industry’s evolving needs for transparent and traceable value chains.
DroughtStats: a comprehensive software for drought monitoring and analysis
(Springer Science and Business Media Deutschland GmbH, 2025-01) Terzi, Tolga Barış; Önöz, Bihrat
The significance of drought monitoring and prediction systems has grown substantially due to the escalating impacts of climate change. However, existing tools for drought analysis face several limitations, including restricted functionality to single-variable indices, reliance on predefined probability distributions, lack of flexibility in choosing distributions, and the need for advanced programming expertise. These constraints hinder comprehensive and accurate drought assessments. This study introduces DroughtStats, a novel, user-friendly software designed to overcome these challenges and enhance drought analysis capabilities. DroughtStats integrates advanced statistical tools to analyze hydrometeorological data, compute both single-variable and multivariable drought indices using empirical and parametric methods, and evaluate drought characteristics with improved accuracy. Notably, it supports a broader range of probability distributions, performs copula-based analyses, and estimates potential evapotranspiration using multiple methods, including Penman–Monteith. Additionally, DroughtStats can analyze the relationship between different datasets using techniques like copula-based Kendall’s tau. By addressing the limitations of existing tools, DroughtStats provides a more flexible and comprehensive approach to drought monitoring. Its versatility and global applicability are demonstrated through a case study in Turkey’s Çoruh River Basin (CRB), where drought indices based on precipitation and streamflow are calculated to characterize drought conditions. The results show that DroughtStats can successfully identify and characterize drought events at various time scales, providing valuable insights into drought severity, frequency, and recovery, and offering a reliable tool for ongoing drought monitoring and management.
Advanced drought analysis using a novel copula-based multivariate index: a case study of the Ceyhan River Basin
(Springer Science and Business Media Deutschland GmbH, 2025-02) Terzi, Tolga Barış; Önöz, Bihrat
Drought is a severe natural disaster that poses significant risks to both social and ecological systems. Detecting drought is challenging due to its gradual development, which makes it difficult to identify and predict, often resulting in significant impacts on the affected regions. Therefore, accurate and dependable monitoring of drought conditions is essential for the development and implementation of effective mitigation strategies. Drought indices play a crucial role in monitoring drought conditions, with single-variable indices commonly employed in the literature to evaluate drought severity. While these indices are typically effective at characterizing the specific type of drought for which they were designed, they often fall short in offering a comprehensive view of overall drought conditions. The multivariate standardized drought index (MSDI) is a comprehensive tool that assesses drought conditions by integrating multiple hydrometeorological variables. Widely employed in the literature in both parametric and empirical forms, the MSDI is recognized for its effectiveness in detecting drought in an integrated manner. This study focuses on a particular challenge related to the calculation of MSDI using copula families. The novel methodology introduced in this paper involves selecting the most suitable copula family for each data subset using AIC and BIC criteria. Rather than applying a single copula family to the entire dataset, this approach utilizes multiple copula families for different subsets, thereby ensuring optimal modeling for each distinct group of data. The Ceyhan River Basin (CRB) is used as a case study to apply the proposed methodology. The drought characteristics of the basin are analyzed using both the newly developed MSDI and conventional single-variable indices, and the performance of the new methodology is evaluated. The application of this approach in the CRB demonstrated its effectiveness in identifying both concurrent and isolated occurrences of meteorological and hydrological droughts, thereby facilitating a more integrated and precise assessment of drought characteristics. Results indicated that the proposed MSDI detected drought events that were overlooked by single-variable indices and improved classification accuracy over the conventional MSDI.
Drought analysis in the Seyhan River Basin based on standardized drought indices using a new approach considering seasonality
(Springer Science and Business Media Deutschland GmbH, 2025-01) Terzi, Tolga Barış; Önöz, Bihrat
Drought is a significant natural disaster with adverse effects on both social and ecological systems. Unlike other natural disasters, drought develops slowly and gradually, complicating its early detection and often resulting in severe impacts on affected regions. Consequently, accurate and dependable drought monitoring is essential for devising effective mitigation strategies. Standardized drought indices are vital tools in drought monitoring, providing a means to quantify and characterize drought events. Most standardized drought indices utilize the Standardized Precipitation Index (SPI) method, which is valued for its simplicity and flexibility. However, this study contends that the SPI method lacks several critical elements, particularly in practice, such as determining the most suitable probability distribution for hydrometeorological variables. Therefore, this study proposes a novel methodology for calculating standardized drought indices and assesses its performance against conventional and nonparametric standardized indices, employing various methods capable of capturing complex dependencies. The novel methodology involves identifying the best-fit probability distributions for each data group through various goodness-of-fit tests. This approach ensures that each group is modeled optimally, considering the seasonal variations inherent to each group. The Seyhan River Basin has been chosen as a case study for the proposed methodology. The drought characteristics of the basin are analyzed using indices derived from the new methodology, the conventional SPI method, and the nonparametric method. Additionally, trend analyses were performed on the calculated indices to identify any directional changes in drought patterns within the Seyhan River Basin. The performance of the proposed methodology was evaluated by analyzing its relationship with nonparametric standardized indices and comparing it to the relationship between conventional standardized indices and nonparametric standardized indices. The results show that the newly proposed methodology outperforms the conventional SPI method across various dependence measures, suggesting it captures the underlying data structure more effectively than the SPI method.
A new local path planning approach by synthesis of PRM and RRT* algorithms for an autonomous mobile robot
(Springer, 2025-02) Göktaş, Anıl Gökhan; Sezer, Semih
Many research efforts have been and continue to be carried out to make human life easier through the use of new technologies. The ability to shift labor to non-humans and reduce the workforce demonstrates the scope of innovation. In this investigation, a new approach is proposed to address several shortcomings of the PRM and RRT algorithms used for path planning in mobile robots. The proposed approach differs by building markers around it, avoiding dynamic obstacles and providing a shorter path. Simulation studies of the PRM and RRT* algorithms, along with the Circular Nodes (CN) approach, were conducted in real and virtual environments. Meanwhile, experimental studies for the CN approach were carried out in a real environment, with obstacles. When compared to other methods, the proposed approach has demonstrated an increase in node efficiency by up to five times. Moreover, implementing node points that are approximately 10% of those used in the PRM and RRT* algorithms has resulted in a shorter path. The reduction in the number of nodes and path length leads to a reduction in energy consumption and processing power.
Reliability of direct-to-home teleneuropsychological assessment: a within-subject design study
(Routledge, 2025-07-04) Yıldırım, Elif; Soncu Büyükişcan, Ezgi; Akça Kalem, Şükriye; Gürvit, Hakan
Objective: During the COVID-19 pandemic, the need to continue diagnosis and treatment processes, in addition to scientific research, led to a rapid shift towards direct-to-home tele-neuropsychology administrations, the reliability and validity of which had not been clearly established then. This study, therefore, aimed to examine the reliability of direct-to-home tele-neuropsychological assessment (TNP). Method: The sample included 105 cognitively healthy individuals aged between 50–83 years, and 47 patients diagnosed with neurocognitive disorders (mild cognitive impairment and early-stage Alzheimer’s type dementia). All participants underwent both face-to-face and teleneuropsychological assessments in a counterbalanced order. Results: The results revealed that performances across measures of attention, working memory, verbal fluency, verbal and visual memory, and visual perception were comparable across assessment modalities. Intraclass correlation coefficients of the tests ranged from.54 to.92. Conclusions: The findings of the study provide support for direct-to-home teleneuropsychological assessment among patients with neurocognitive disorders. Neuropsychological tests relying on verbal administration and independent of motor performance may represent a reliable alternative for this patient group when administered in settings where external distractions or technological limitations are controlled. For cognitively healthy individuals, on the other hand, the reliability of the TNP application is more questionable for memory and some executive function tests and therefore needs further exploration.
Dogu Anadolu Gözlemevi (DAG) integrated dome and telescope on-site assembly
(SPIE, 2024) Marchiori, Gianpietro; Rampini, Francesco; Amalfi, Manfredi; Bressan, Riccardo; Ghedin, Leonardo; Battistel, Cristina; Manfrin, Cristiana; Vio, L.; Niero, Tiziano; Marchiori, Tommaso; Pirnay, Olivier; Gabriel, Eric; Méant, Laurence; Yeşilyaprak, Cahit; Keskin, Onur
The Dogu Anadolu Gözlemevi (DAG) Eastern Anatolia Observatory is an astronomical project fully funded by Turkish Ministry of Development and the Atatürk University of Astrophysics Research Telescope (ATASAM). DAG Observatory will be provided with a 4m-class optical and infrared telescope, equipped with secondary (0.76m) and tertiary mirrors which furnish the telescope with two Nasmyth foci. Since 2015, the project has seen the crucial contribution of EIE GROUP in the Design, Production and on-site Installation of the 4m class optical/near-infrared telescope (DAG Telescope) in contract with AMOS company. EIE GROUP is also the main contractor of the 18.6m-diameter Rotating Building (DAG Dome) at an altitude of 3170m asl on the Erzurum Plateau, Turkey. The telescope was completely pre-assembled and successfully tested at the Integration Area Facilities of the EIE GROUP. Subsequently disassembled and transported to the final installation site. Despite the serious effects of the pandemic, the EIE GROUP, in agreement with its final Customer, has adopted a telescope assembly strategy integrated with the final assembly phases of the Dome. This allowed EIE to mount the entire telescope, in a single summer season, in total safety (thanks to the special measures adopted). This paper focuses on the development of this on-site assembly EIE activities of DAG Telescope, which at present have exceeded the 95% of completion. The main critical issues and related engineering solutions will be analyzed, with emphasis on both managerial and erection approaches adopted by EIE GROUP for this integrated phase of the project completion.

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