Distribution Management Systems

Mevcut elektrik dağıtım şebekelerinin kontrolünün zorluğu, elektrik dağıtım şebekelerinde enerji verimliliği sağlanması, operasyonel maliyetlerinin düşürülmesi ve bu sayede çevreye katkıda bulunulması için enerji otomasyon sistemleri geliştirilmektedir. Bu sistemlerin diğer bir önemli getirisi de yasaların zorunlu kıldığı enerji kalitesi, sürdürülebilirlik, güvenilirlik ve sistem performansına katkıda bulunmalarıdır. Dağıtım şebekelerine entegre edilen ve birbiriyle haberleşen akıllı ekipmanlar ve bunlardan toplanan bilgilerin kompleks algoritmalarla işlenmesiyle şebekeler optimize edilebilir. Dağıtım Yönetim Sistemleri (DMS(Distributed Management Systems)) şebekeden toplanan bilgileri kompleks algoritmalar kullanarak operatöre kontrol, analiz optimizasyon ve planlama fonksiyonları sunmaktadır. Energy automation systems are developped due to the difficulty of existing electricity distribution networks, providing energy efficiency in electricity distribution networks, decreasing operational costs and thus contributing to the environment. Another important return of these systems is that they contribute to the energy quality, sustainability, reliability and system performance that is obliged by law. Grids can be optimised with smart equipments that are integrated in distribution networks and communicate with each other and processing the data collected out of these with complex algortihms. Distribution Management Systems offer control, analysis optimisation and planning functions to operators by using complex algorithms for data gathered from the network

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs

Resting-State EEG Alpha Rhythms Are Related to CSF Tau Biomarkers in Prodromal Alzheimer\u27s Disease

\ua9 2025 by the authors. Patients with mild cognitive impairment due to Alzheimer’s disease (ADMCI) typically show abnormally high delta (<4 Hz) and low alpha (8–12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) activity. Here, we hypothesized that the abnormalities in rsEEG activity may be greater in ADMCI patients than in those with MCI not due to AD (noADMCI). Furthermore, they may be associated with the diagnostic cerebrospinal fluid (CSF) amyloid–tau biomarkers in ADMCI patients. An international database provided clinical–demographic–rsEEG datasets for cognitively unimpaired older (Healthy; N = 45), ADMCI (N = 70), and noADMCI (N = 45) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. Posterior rsEEG alpha source activities were reduced in the ADMCI group compared not only to the Healthy group but also to the noADMCI group (p < 0.001). Negative associations between the CSF phospho-tau and total tau levels and posterior rsEEG alpha source activities were observed in the ADMCI group (p < 0.001), whereas those with CSF amyloid beta 42 levels were marginal. These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through rsEEG alpha rhythms are mainly affected by brain tauopathy in ADMCI patients

Resting-state electroencephalographic rhythms depend on sex in patients with dementia due to Parkinson\u27s and Lewy Body diseases: An exploratory study

\ua9 2025 The Authors. Parkinson\u27s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are more prevalent in males than females. Furthermore, they typically showed abnormally high delta (< 4 Hz) and low alpha (8–10 Hz) rhythms from resting-state electroencephalographic (rsEEG) activity. Here, we hypothesized that those abnormalities may depend on the patient\u27s sex. An international database provided clinical-demographic-rsEEG datasets for cognitively unimpaired older (Healthy; N = 49; 24 females), PDD (N = 39; 13 females), and DLB (N = 38; 15 females) participants. Each group was stratified into matched female and male subgroups. The rsEEG rhythms were investigated across the individual rsEEG delta, theta, and alpha frequency bands based on the individual alpha frequency peak. The eLORETA freeware was used to estimate cortical rsEEG sources. In the Healthy group, widespread rsEEG alpha source activities were greater in the females than in the males. In the PDD group, widespread rsEEG delta source activities were lower and widespread rsEEG alpha source activities were greater in the females than in the males. In the DLB group, central-parietal rsEEG delta source activities were lower, and posterior rsEEG alpha source activities were greater in the females than in the males. These results suggest sex-dependent hormonal modulation of neuroprotective-compensatory neurophysiological mechanisms in PDD and DLB patients underlying the generation of rsEEG delta and alpha rhythms, which should be considered in the treatment of vigilance dysregulation in those patients

Three-dimensional underwater target tracking with acoustic sensor networks

Using traditional sonar arrays may be difficult and impractical in some mission-critical scenarios, because they should be mounted on or towed by a ship or a submersible. Alternatively, underwater acoustic sensor networks (UW-ASNs) offer a promising solution approach. In this paper, a target-tracking algorithm for UW-ASNs, i.e., 3-D underwater target tracking (3DUT), is presented. The objective of 3DUT is to collaboratively accomplish accurate tracking of underwater targets with minimum energy expenditure. Based on the time of arrival of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target. The location and the calculated velocity of the target are then exploited to achieve tracking. To realize energy-effective target tracking, 3DUT incorporates a new target-movement-based duty-cycle mechanism. To avoid rapid depletion of the energy resources of boundary nodes due to continuous surveillance, 3DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Performance evaluation shows that 3DUT is a promising alternative to the traditional sonar-based target-tracking approaches, particularly for on-demand surveillance applications. © 2011 IEEE