3D Transition Matrix Solution for a Path Dependency Problem of Markov Chains-Based Prediction in Cellular Networks

Handover (HO) management is one of the critical challenges in current and future mobile communication systems due to new technologies being deployed at a network level, such as small and femtocells. Because of the smaller sizes of cells, users are expected to perform more frequent HOs, which can increase signaling costs and also decrease user's performance, if a HO is performed poorly. In order to address this issue, predictive HO techniques, such as Markov chains (MC), have been introduced in the literature due to their simplicity and generality. This technique, however, experiences a path dependency problem, specially when a user performs a HO to the same cell, also known as a re-visit. In this paper, the path dependency problem of this kind of predictors is tackled by introducing a new 3D transition matrix, which has an additional dimension representing the orders of HOs, instead of a conventional 2D one. Results show that the proposed algorithm outperforms the classical MC based predictors both in terms of accuracy and HO cost when re-visits are considered

Introducing a Novel Minimum Accuracy Concept for Predictive Mobility Management Schemes

In this paper, an analytical model for the minimum required accuracy for predictive methods is derived in terms of both handover (HO) delay and HO signaling cost. After that, the total HO delay and signaling costs are derived for the worst-case scenario (when the predictive process has the same performance as the conventional one), and simulations are conducted using a cellular environment to reveal the importance of the proposed minimum accuracy framework. In addition to this, three different predictors; Markov Chains, Artificial Neural Network (ANN) and an Improved ANN (IANN) are implemented and compared. The results indicate that under certain circumstances, the predictors can occasionally fall below the applicable level. Therefore, the proposed concept of minimum accuracy plays a vital role in determining this corresponding threshold

Prediction of Emergency Preparedness Level On-Board Ships Using Discrete Event Simulation: the Case of Firefighting Drill

This paper proposes a hybrid approach, including Fuzzy Dematel (FD) integrated with Discrete Event Simulation (DES), to predict emergency preparedness levels on-board ships. The FD used critical factors that affect emergency preparedness to conduct a DES based on real firefighting drill records collected from 45 merchant ships. The simulation results showed the average duration of on-board drills in ideal conditions (27.47 min.), in the worst-case scenario (51.49 min.), for Ship A (29.99 min.), and Ship B (28.12 min.). Based on the findings, recovery actions linked to the factors have been recommended to promote on-board implementation. The proposed model is of great importance to shore-based managers, allowing them to monitor the emergency preparedness level of the fleet continuously, even during pandemics. Further studies are planned to develop a remote monitoring system that would digitalize the existing response procedures in emergency situations

Morphological Changes of Anterior Cerebral Artery (ACA) in Hydrocephalic Pediatric Patients

How to Cite This Article: Ozturk S, Ayan E, Kaplan M. Morphological Changes of Anterior Cerebral (ACA) Artery in Hydrocephalic Pediatric Patients. Iran J Child Neurol. Winter 2017; 11(1):37-42. AbstractObjectiveThe morphology of anterior cerebral artery (ACA) in patients with hydrocephalus (HCP) was analyzed, and its importance was discussed in maintaining cerebral perfusion.Materials & MethodsA total of 84 cases in 2 groups between 0 and 3 months, followed-up at Firat Universitesi Hastanesi, Beyin Cerrahisi Klinigi, Elazig, Turkiye due to in 2010-2013, were enrolled. Two groups were created for the study. Group 1; patients with HCP and Group 2; as control group without HCP. In both groups, the length of the A2 segment of ACA was measured from its origin to the junction of the genu and body portions of the corpus callosum on T2 mid-sagittal magnetic resonance (MR) scans. For all cases, axial MR imaging scans were used to calculate Evans’ index (EI), and the cases were divided into three groups: Group A, EI ≥50%; Group B, EI of 40-50% and Group C, EI <40%. The two groups (Groups 1 and 2) were compared with respect to ACA length, and the correlation with the EI was quantified. P values below 0.05 were considered statistically significant.ResultsMean length of ACA was 57.3 mm in Group 1 and 37.5 mm in Group 2. EI increased as the length of ACA increased. A statistical comparison of the two groups revealed that the ACA length was significantly greater in Group 1. The relationship between EI and ACA length was statistically significant.ConclusionReducing ventricular size appears to be an important factor in addition to reducing intracranial pressure in an attempt to maintain normal cerebral perfusion(CP).References1. Westra SJ, Lazareff J, Curran JG, Sayre JW, Kawamoto H Jr. Transcranial Doppler ultrasonography to evaluate need for cerebrospinal fluid drainage in hydrocephalic children. J Ultrasound Med 1998; 17): 561-569.2. Kolarovszki B, Zubor P, Kolarovszka H, Benco M, Richterova R, Matasova K. The assessment of intracranial dynamics by transcranial Doppler sonography in perioperative period in paediatric hydrocephalus. Arch Gynecol Obstet 2013; 287: 229-238.3. Tritton DJ. Fluid Mechanics. Physical fluid Dynamics. Tritton, DJ: 2nd ed. Oxford, Clarendon Press 1988; pp:536-540.4. de Oliveira RS, Machado HR. Transcranial color-coded Doppler ultrasonography for evaluation of children with hydrocephalus. Neurosurg Focus 2003; 15: ECP3. 5. Kempley ST, Gamsu HR. Changes in cerebral artery blood flow velocity after intermittent cerebrospinal fluid drainage. Arch Dis Child 1993; 69: 74-76.6. Hanlo PW, Gooskens RH, Nijhuis IJ, Faber JA, Peters RJ, van Huffelen AC and et al. Value of transcranial Doppler indices in predicting raised ICP in infantile hydrocephalus. A study with review of the literature. Childs Nerv Syst 1995; 11: 595-603.7. Nishimaki S, Yoda H, Seki K, Kawakami T, Akamatsu H, Iwasaki Y. Cerebral blood flow velocities in the anterior cerebral arteries and basilar artery in hydrocephalus before and after treatment. Surg Neurol 1990; 34: 373- 377.8. Wang B, Cheng Z, Mu X, Fan B, Guo Z. Preoperative and postoperative transcranial Doppler sonographic evaluations of the cerebral hemodynamics of craniostenosis. J Craniofac Surg 2010; 21: 432-435.9. Bell SR, Vo AH, Armanda RA. Applied neurovascular anatomy of the brain and skull. In: Hurst RW, Rosenwasser RH, editors. Interventional Neuroradiology. New York: Informa; 2008: pp: 22-27.10. Kaplan M, Berilgen MS, Erol FS, Artas H, Serhatlioglu S, Ozveren MF. Relationship between Clinical Grade, Cerebral Blood Flow, and Electroencephalographic Alterations in Patients with Chronic Subdural Hemorrhage. Neurosurgery Q 2006; 16: 157-160.11. Riggo JD, Kolarovszki B, Richterova R, Kolarovszka H, Sutovsky J, Durdikc P. Measurement of the blood flow velocity in the pericallosal artery of children with hydrocephalus by transcranial Doppler ultrasonography-preliminary results. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 2007; 151: 285-289.12. Zenger MN, Kabataş S, Zenger S, Cakmakçi H. The value of power Doppler ultrasonography in the differential diagnosis of intracranial extraaxial fluid collections. Diagn Interv Radiol. 2007; 13: 61-63.13. Kaplan M, Erol FS, Bozgeyik Z, Koparan M: The effectiveness of simple drainage technique in improvement of cerebral blood flow in patients with chronic subdural hemorrhage. Turk Neurosurg 2007; 17: 202-206.14. Rozenfeld A. Ultrasound in diagnostics of blood vessels: the role of the assessment of both extra- and intracranial flows by Doppler ultrasonography. Neurol Neurochir Pol 1994; 28: 51-66.15. Miller SP, Cozzio CC, Goldstein RB, Ferriero DM, Partridge JC, Vigneron DB and et al. Comparing the diagnosis of white matter injury in premature newborns with serial MR imaging and transfontanel ultrasonography findings. AJNR Am J Neuroradiol 2003; 24: 1661-1669

Novel Methods for Load Estimation in Cell Switching in HAPS-Assisted Sustainable 6G Networks

In the evolving landscape of vertical heterogeneous networks, the practice of cell switching particularly for small base stations faces a significant challenge due to the lack of accurate data on the traffic load of sleeping SBSs. This information gap is crucial as it hinders the feasibility and applicability of existing power consumption optimization methods; however, the studies in the literature predominantly assume perfect knowledge about the traffic load of sleeping SBSs. Addressing this critical issue, our study introduces innovative methodologies for estimating the traffic load of sleeping SBSs in a vHetNet including the integration of a high altitude platform as a super macro base station into the terrestrial network. We propose three distinct spatial interpolation-based estimation schemes: clustering-based, distance based, and random neighboring selection. Employing a real data set for empirical validations, we compare the estimation performance of the developed traffic load estimation schemes and assess the impact of estimation errors. Our findings demonstrate that accurate estimation of sleeping SBSs' traffic loads is essential for making network power consumption optimization methods both feasible and applicable in vHetNets.Comment: 6 pages, 5 figures, ICC Conferenc

Energy-aware smart connectivity for IoT networks: enabling smart ports

The Internet of Things (IoT) is spreading much faster than the speed at which the supporting technology is maturing. Today, there are tens of wireless technologies competing for IoT and a myriad of IoT devices with disparate capabilities and constraints. Moreover, each of many verticals employing IoT networks dictates distinctive and differential network qualities. In this work, we present a context-aware framework that jointly optimises the connectivity and computational speed of the IoT network to deliver the qualities required by each vertical. Based on a smart port application, we identify energy efficiency, security, and response time as essential quality features and consider a wireless realisation of IoT connectivity using short range and long-range technologies. We propose a reinforcement learning technique and demonstrate significant reduction in energy consumption while meeting the quality requirements of all related applications

Addressing the Load Estimation Problem: Cell Switching in HAPS-Assisted Sustainable 6G Networks

This study aims to introduce and address the problem of traffic load estimation in the cell switching concept within the evolving landscape of vertical heterogeneous networks (vHetNets). The problem is that the practice of cell switching faces a significant challenge due to the lack of accurate data on the traffic load of sleeping small base stations (SBSs). This problem makes the majority of the studies in the literature, particularly those employing load-dependent approaches, impractical due to their basic assumption of perfect knowledge of the traffic loads of sleeping SBSs for the next time slot. Rather than developing another advanced cell switching algorithm, this study investigates the impacts of estimation errors and explores possible solutions through established methodologies in a novel vHetNet environment that includes the integration of a high altitude platform (HAPS) as a super macro base station (SMBS) into the terrestrial network. In other words, this study adopts a more foundational perspective, focusing on eliminating a significant obstacle for the application of advanced cell switching algorithms. To this end, we explore the potential of three distinct spatial interpolation-based estimation schemes: random neighboring selection, distance-based selection, and clustering-based selection. Utilizing a real dataset for empirical validations, we evaluate the efficacy of our proposed traffic load estimation schemes. Our results demonstrate that the multi-level clustering (MLC) algorithm performs exceptionally well, with an insignificant difference (i.e., 0.8%) observed between its estimated and actual network power consumption, highlighting its potential to significantly improve energy efficiency in vHetNets.Comment: arXiv admin note: substantial text overlap with arXiv:2402.0438

Bovine Viral Diarrhea Virus Infection in Cattle - Antioxidant Status and Some Biochemical Parameters

Background: Bovine viral diarrhea virus (BVDV) infections in cattle result in significant economic losses due to reproductive performance deficiencies caused by gastrointestinal, respiratory system infections, and transplacental infections. BVDV is one of the most important and widespread pathogens in cattle worldwide, including Turkey. Methods such as virus neutralization, enzyme-linked immunosorbent assay (ELISA), reverse transcriptase and polymerase chain reaction (RT-PCR) are used for the detection of the disease. The diagnosis of the disease in its subclinical form is challenging due to the lengthy and costly procedures involved. Investigating oxidative stress parameters in ruminants with various diseases contributes significantly to diagnosis and prognosis. This study aimed to investigate some oxidative stress and biochemical parameters in cattle infected with BVDV. Materials, Methods & Results: In the study, blood samples were collected from 80 Simmental breed cows aged between approximately 4 and 8 years to determine the presence of BVDV antibodies using the ELISA method. Based on the results obtained, study groups were organized. The study included a group of 10 animals with positive antibody levels as the infected group, and a group of 10 animals with negative antibody levels as the healthy group. Blood samples were taken from the animals, and serum separation was ensured. In the obtained serum samples, levels of vitamin E, vitamin A, β-Carotene, catalase, GSH-Px, and MDA were determined using spectrophotometric methods. In addition, serum total protein, albumin, alkaline phosphatase (ALP), aspartate aminotransferase (AST), glucose, low-density lipoprotein (LDL), high-density lipoprotein (HDL), calcium (Ca), and phosphorus (P) were measured using commercial test kits and an autoanalyzer. In the study, it was observed that the differences in serum MDA, vitamin E, vitamin A, β-carotene, and catalase levels were statistically significant between the healthy and BVDV-infected groups (P < 0.001). The activity of GSH-Px was also found to be statistically different between the groups (P < 0.01). Among the biochemical parameters, HDL, LDL, and AST levels were found to be statistically significant between the healthy and BVDV-infected groups (P < 0.001). Additionally, ALP and glucose levels were found to be statistically significant (P < 0.01). However, although there were differences in the levels of total protein, albumin, Ca, and P between the groups, these results were not statistically significant.Discussion: Although the diagnosis of the disease was partially made based on clinical observations in BVDV infections, the ELISA method was used for accurate diagnosis. Furthermore, it was found that there was a significant difference in MDA concentration between the healthy and infected groups, indicating oxidative damage caused by the virus. Similarly,significant differences in vitamin E, vitamin A, β-carotene, GSH-Px, and catalase levels were observed between the groups, indicating a decrease in antioxidant values due to the infection. In addition, differences in ALP, AST, glucose, LDL, and HDL levels were found between the groups. This difference is thought to be related to the effects of the disease agent on the liver and systemically. This study demonstrates that, in addition to the viral pathogen, antioxidant and biochemical values are important criteria in the detection of the disease. Keywords: antioxidant, bovine, BVDV, MDA, serum biochemistry

Q-learning Assisted Energy-Aware Traffic Offloading and Cell Switching in Heterogeneous Networks

Cell switching has been identified as a major approach to significantly reduce the energy consumption of Heterogeneous Networks (HetNets). The main idea behind cell switching is to turn off idle or lightly loaded Base Stations (BSs) and to offload their traffic to neighbouring active cell(s). However, the impact of the offloaded traffic on the power consumption of the neighbouring cell(s) has not been studied sufficiently in the literature, thereby leading to the development of sub-optimal cell switching mechanisms. In this work, we first considered a Control/Data Separated Architecture (CDSA) with a macro cell serving as the Control Base Station (CBS) and multiple small cells as Data Base Stations (DBS). Then, a Q-learning assisted cell switching algorithm is developed in order to determine the small cells to switch off by considering the increase in power consumption of the macro cell due to offloaded traffic from the sleeping cells. The capacity of the macro cell is also taken into consideration to ensure that the Quality of Service (QoS) requirements of users are maintained. Simulation results show that the proposed cell switching algorithm can achieve up to 50% reduction in the total energy consumption of the considered HetNet scenario