Search results for: node points

Authors: Thanin Sitthiwirattham, Jiraporn Reunsumrit

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We study the existence of positive solutions to the three points difference summation boundary value problem. We show the existence of at least one positive solution if f is either superlinear or sublinear by applying the fixed point theorem due to Krasnoselskii in cones.

Keywords: positive solution, boundary value problem, fixed point theorem, cone

Procedia PDF Downloads 439

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Safeer Hussain Khan

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In this paper, we prove a strong convergence result using a recently introduced iterative process with contractive-like operators. This improves and generalizes corresponding results in the literature in two ways: the iterative process is faster, operators are more general. In the end, we indicate that the results can also be proved with the iterative process with error terms.

Keywords: contractive-like operator, iterative process, fixed point, strong convergence

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Authors: Jihuai Wu, Zeyu Song, Zhang Lan, Liuxue Sun

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Solar energy is clean, open, and infinite, but solar radiation on the earth is fluctuating, intermittent, and unstable. So, the sustainable utilization of solar energy requires a combination of high-efficient energy conversion and low-loss energy storage technologies. Hence, a photo capacitor integrated with photo-electrical conversion and electric-chemical storage functions in single device is a cost-effective, volume-effective and functional-effective optimal choice. However, owing to the multiple components, multi-dimensional structure and multiple functions in one device, especially the mismatch of the functional modules, the overall conversion and storage efficiency of the photocapacitors is less than 13%, which seriously limits the development of the integrated system of solar conversion and energy storage. To this end, two typical photocapacitors were studied. A three-terminal photocapacitor was integrated by using perovskite solar cell as solar conversion module and symmetrical supercapacitor as energy storage module. A function portfolio management concept was proposed the relationship among various efficiencies during photovoltaic conversion and energy storage process were clarified. By harmonizing the energy matching between conversion and storage modules and seeking the maximum power points coincide and the maximum efficiency points synchronize, the overall efficiency of the photocapacitor surpassed 18 %, and Joule efficiency was closed to 90%. A voltage adjustable hybrid supercapacitor (VAHSC) was designed as energy storage module, and two Si wafers in series as solar conversion module, a three-terminal photocapacitor was fabricated. The VAHSC effectively harmonizes the energy harvest and storage modules, resulting in the current, voltage, power, and energy match between both modules. The optimal photocapacitor achieved an overall efficiency of 15.49% and Joule efficiency of 86.01%, along with excellent charge/discharge cycle stability. In addition, the Joule efficiency (ηJoule) was defined as the energy ratio of discharge/charge of the devices for the first time.

Keywords: joule efficiency, perovskite solar cell, photocapacitor, silicon solar cell, supercapacitor

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Authors: Qin Zhu

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Under the background of accelerating the construction of Beautiful and Livable Park City in Chengdu, the Tianfu greenway system, as an important support system for the construction of parks in the whole region, its accessibility is one of the key indicators to measure the effectiveness of the greenway construction. In recent years, cycling has become an important transportation mode for residents to go to the greenways because of its low-carbon, healthy and convenient characteristics, and the study of greenway accessibility under cycling mode can provide reference suggestions for the optimization and improvement of greenways. Taking Jincheng Greenway in Chengdu City as an example, the Baidu Map Application Programming Interface (API) and questionnaire survey was used to improve the two-step floating catchment area (2SFCA) method from the three dimensions of search threshold, supply side and demand side, to calculate the cycling accessibility of the greenway and to explore the spatial matching relationship with the population density, the number of entrances and the comprehensive attractiveness. The results show that: 1) the distribution of greenway accessibility in Jincheng shows a pattern of "high in the south and low in the north, high in the west and low in the east", 2) the spatial match between greenway accessibility and population density of the residential area is imbalanced, and there is a significant positive correlation between accessibility and the number of selectable greenway access points in residential areas, as well as the overall attractiveness of greenways, with a high degree of match. On this basis, it is proposed to give priority to the mismatch area to alleviate the contradiction between supply and demand, optimize the greenway access points to improve the traffic connection, enhance the comprehensive quality of the greenway and strengthen the service capacity, to further improve the cycling accessibility of the Jincheng Greenway and improve the spatial allocation of greenway resources.

Keywords: accessibility, Baidu maps API, cycling, greenway, 2SFCA

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Authors: Lucélia Alcântara

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Reading has been seen as a passive skill by many people for a long time. However, when one comes to study it deeply and in a such a way that the act of reading equals acquiring knowledge through living an experience that belongs to him/her, passive definitely becomes active. Material development with a focus on reading has to consider much more than reading strategies. The following questions are asked: Is the material appropriate to the students’ reality? Does it make students think and state their points of view? With that in mind a lesson has been developed to illustrate theory becoming practice. Knowledge, criticality, intercultural experience and social interaction. That is what reading is for.

Keywords: reading, culture, material development, learning

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Noritaka Shigei, Kazuto Matsumoto, Yoshiki Nakashima, Hiromi Miyajima

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Although Mobile Wireless Sensor Networks (MWSNs), which consist of mobile sensor nodes (MSNs), can cover a wide range of observation region by using a small number of sensor nodes, they need to construct a network to collect the sensing data on the base station by moving the MSNs. As an effective method, the network construction method based on Virtual Rails (VRs), which is referred to as VR method, has been proposed. In this paper, we propose two types of effective techniques for the VR method. They can prolong the operation time of the network, which is limited by the battery capabilities of MSNs and the energy consumption of MSNs. The first technique, an effective arrangement of VRs, almost equalizes the number of MSNs belonging to each VR. The second technique, an adaptive movement method of MSNs, takes into account the residual energy of battery. In the simulation, we demonstrate that each technique can improve the network lifetime and the combination of both techniques is the most effective.

Keywords: mobile sensor node, relay of sensing data, residual energy, virtual rail, wireless sensor network

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Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

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Authors: Ho Young Son, Bu Seog Ju, Woo Young Jung

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This study presents the seismic safety evaluation of weir structure subjected to strong earthquake ground motions, as a flood defense structure in civil engineering structures. The seismic safety analysis procedure was illustrated through development of Finite Element (FE) and InFinite Element (IFE) method in ABAQUS platform. The IFE model was generated by CINPS4, 4-node linear one-way infinite model as a sold continuum infinite element in foundation areas of the weir structure and then nonlinear FE model using friction model for soil-structure interactions was applied in this study. In order to understand the complex behavior of weir structures, nonlinear time history analysis was carried out. Consequently, it was interesting to note that the compressive stress gave more vulnerability to the weir structure, in comparison to the tensile stress, during an earthquake. The stress concentration of the weir structure was shown at the connection area between the weir body and stilling basin area. The stress both tension and compression was reduced in IFE model rather than FE model of weir structures.

Keywords: seismic, numerical analysis, FEM, weir, boundary condition

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Authors: Enrico Gugliandolo, Salvatore Cuzzocrea, Rosalia Crupi

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Osteoarthritis (OA) is one of the most common chronic pain conditions in dogs and cats. OA pain is currently viewed as a mixed phenomenon involving both inflammatory and neuropathic mechanisms at the peripheral (joint) and central (spinal and supraspinal) levels. Oxidative stress has been implicated in OA pain. Although nonsteroidal anti-inflammatory drugs are commonly prescribed for OA pain, they should be used with caution in pets because of adverse effects in the long term and controversial efficacy on neuropathic pain. An unmet need remains for safe and effective long-term treatments for OA pain. Palmitoyl-glucosamine (PGA) is an analogue of the ALIAamide palmitoylethanolamide, i.e., a body’s own endocannabinoid-like compound playing a sentinel role in nociception. PGA, especially in the micronized formulation, was shown safe and effective in OA pain. The aim of this study was to investigate the effect of a co-micronized formulation of PGA with the natural antioxidant curcumin (PGA-cur) on OA pain. Ten Sprague-Dawley male rats were used for each treatment group. The University of Messina Review Board for the care and use of animals authorized the study. On day 0, rats were anesthetized (5.0% isoflurane in 100% O2) and received intra-articular injection of MIA (3 mg in 25 μl saline) in the right knee joint, with the left being injected an equal volume of saline. Starting the third day after MIA injection, treatments were administered orally three times per week for 21 days, at the following doses: PGA 20 mg/kg, curcumin 10 mg/kg, PGA-cur (2:1 ratio) 30 mg/kg. On day 0 and 3, 7, 14 and 21 days post-injection, mechanical allodynia was measured using a dynamic plantar Von Frey hair aesthesiometer and expressed as paw withdrawal threshold (PWT) and latency (PWL). Motor functional recovery of the rear limb was evaluated on the same time points by walking track analysis using the sciatic functional index. On day 21 post-MIA injection, the concentration of the following inflammatory and nociceptive mediators was measured in serum using commercial ELISA kits: tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), nerve growth factor (NGF) and matrix metalloproteinase-1-3-9 (MMP-1, MMP-3, MMP-9). The results were analyzed by ANOVA followed by Bonferroni post-hoc test for multiple comparisons. Micronized PGA reduced neuropathic pain, as shown by the significant higher PWT and PWL values compared to vehicle group (p < 0.0001 for all the evaluated time points). The effect of PGA-cur was superior at all time points (p < 0.005). PGA-cur restored motor function already on day 14 (p < 0.005), while micronized PGA was effective a week later (D21). MIA-induced increase in the serum levels of all the investigated mediators was inhibited by PGA-cur (p < 0.01). PGA was also effective, except on IL-1 and MMP-3. Curcumin alone was inactive in all the experiments at any time point. The encouraging results suggest that PGA-cur may represent a valuable option in OA pain management and warrant further confirmation in well-powered clinical trials.

Keywords: ALIAmides, curcumin, osteoarthritis, palmitoyl-glucosamine

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Palaniraj Rama Raj, Himeesh Kumar, Paul Adler

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Purpose: To investigate the effect of ultrasound energy, expressed as cumulative dissipated energy (CDE), on short and long-term outcomes after uncomplicated cataract surgery by phacoemulsification. Methods: In this single-surgeon, two-center retrospective study, non-glaucomatous participants who underwent uncomplicated cataract surgery were investigated. Best-corrected visual acuity (BCVA) and intraocular pressure (IOP) were measured at 3 separate time points: pre-operative, Day 1 and ≥1 month. Anterior chamber (AC) inflammation and corneal odema (CO) were assessed at 2 separate time points: Pre-operative and Day 1. Short-term changes (Day 1) in BCVA, IOP, AC and CO and long-term changes (≥1 month) in BCVA and IOP were evaluated as a function of CDE using a multivariate multiple linear regression model, adjusting for age, gender, cataract type and grade, preoperative IOP, preoperative BCVA and duration of long-term follow-up. Results: 110 eyes from 97 non-glaucomatous participants were analysed. 60 (54.55%) were female and 50 (45.45%) were male. The mean (±SD) age was 73.40 (±10.96) years. Higher CDE counts were strongly associated with higher grades of sclerotic nuclear cataracts (p <0.001) and posterior subcapsular cataracts (p <0.036). There was no significant association between CDE counts and cortical cataracts. CDE counts also had a positive correlation with Day 1 CO (p <0.001). There was no correlation between CDE counts and Day 1 AC inflammation. Short-term and long-term changes in post-operative IOP did not demonstrate significant associations with CDE counts (all p >0.05). Though there was no significant correlation between CDE counts and short-term changes in BCVA, higher CDE counts were strongly associated with greater improvements in long-term BCVA (p = 0.011). Conclusion: Though higher CDE counts were strongly associated with higher grades of Day 1 postoperative CO, there appeared to be no detriment to long-term BCVA. Correspondingly, the strong positive correlation between CDE counts and long-term BCVA was likely reflective of the greater severity of underlying cataract type and grade. CDE counts were not associated with short-term or long-term postoperative changes in IOP.

Keywords: cataract surgery, phacoemulsification, cumulative dissipated energy, CDE, surgical outcomes

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Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: Marco Tulio C. Faria

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Fixed-geometry hydrodynamic journal bearings are one of the best supporting systems for several applications of rotating machinery. Cylindrical journal bearings present excellent load-carrying capacity and low manufacturing costs, but they are subjected to the oil-film instability at high speeds. An attempt of overcoming this instability problem has been the development of non-circular journal bearings. This work deals with an analysis of oil-lubricated elliptical journal bearings using the finite element method. Steady-state and dynamic performance characteristics of elliptical bearings are rendered by zeroth- and first-order lubrication equations obtained through a linearized perturbation method applied on the classical Reynolds equation. Four-node isoparametric rectangular finite elements are employed to model the bearing thin film flow. Curves of elliptical bearing load capacity and dynamic force coefficients are rendered at several operating conditions. The results presented in this work demonstrate the influence of the bearing ellipticity on its performance at different loading conditions.

Keywords: elliptical journal bearings, non-circular journal bearings, hydrodynamic bearings, finite element method

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Authors: Yibo Shao, Jiajie Liu

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This article uncovers the practice of pragmatism of Singaporean foreign policy by analyzing its foreign diplomatic behavior. It also points out the Singapore’s hedging strategy on the relations between China and American and how to balance these two greater powers in Southeast Asian. This paper used qualitative approach by reviewing literature and policy documents intensively to find out the responses to our research questions.

Keywords: hedging, pragmatism, Sino-Singapore relations, South China Sea

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Authors: Rahaf Mandura

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Background: Idiopathic intracranial hypertension (IIH) is a disorder with elevated intracranial pressure (ICP) more than 250 mm H₂O, without evidence of meningeal inflammation, space-occupying lesion, or venous thrombosis. The aim of this research is to study the clinical profile, evaluation, management, and visual outcome in a hospital-based population of IIH cases in Jeddah. Methodology: This is a retrospective observational study that included the medical records of all patients referred to neuro-ophthalmology service for evaluation of papilledema. The medical records have been reviewed from October 2018 to February 2020 at Jeddah Eye Hospital (JEH), Saudi Arabia. A total of fifty-one patients presented with papilledema in the studied period. Forty-seven patients met our inclusion criteria and were included in the study. Results: Most of the patients were females (43, 91.5%) with a mean age of presentation of 30.83±11.40 years. The most common presenting symptom was headache (40 patients, 85.1%), followed by transient visual obscuration (20 patients, 42.6%), and reduced visual acuity (15 patients, 31.9%). All 47 patients were started on medical treatment with oral acetazolamide with four patients (8.5%) shifted to topiramate because of the lack of response or intolerance to acetazolamide while four patients (8.5%) underwent lumbar-peritoneal shunt because of inadequate control of the disease despite the treatment with medical therapy. For both eyes, the change in visual acuity across all assessment points was statistically significant. Nevertheless, there were no significant changes in the visual field findings among all of the compared assessment points. Conclusion: The present study has shown that IIH-related papilledema is common in young female patients with headaches, transient visual obscurations and reduced visual acuity. Those are the commonest symptoms in our IIH population. Medical treatment of IIH is significantly efficacious and should be considered in order to enhance the prognosis of IIH-related complications. Therefore, the visual status should be frequently monitored for these patients.

Keywords: idiopathic intracranial hypertension, intracranial hypertension, papilledema, headache

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Authors: Noha E. Hassan

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Little is known regarding the influence of lymphatic microvessel density (LMVD) on prognosis in endometrial cancer. Prospective study was done in tertiary education and research hospital (Shatby Alexandria university hospital) on sixty patients presented with endometrial carcinoma underwent complete surgical staging. Our aim was to assess the intratumoral and peritumoral Lymphatic microvessel density (LMVD) of endometrial carcinomas identified by immunohistochemical staining using an antibody against podoplanin and to investigate their association with classical clinicopathological factors and prognosis. The result shows that high LMVD was associated with endometroid type of tumors, lesser myometrial, adnexal, cervical and peritoneal infiltration, lower tumor grade and stage and lesser recurrent cases. There is lower lymph node involvement among cases with high intratumoral LMVD and cases of high peritumoral LMVD; that reach statistical significance only among cases of high intratumoral LMVD. No association was seen between LMVD and lymphovascular space invasion. On the other hand, low LMVD was associated with poor outcome. Finally, we can conclude that increased LMVD is associated with favorable prognosis in endometrial cancer patients.

Keywords: endometrial carcinoma, lymphatic microvessel, microvessel density, prognosis

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Authors: Khairil I. Othman, Mahfuzah Mahayaddin, Zarina Bibi Ibrahim

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We develop and demonstrate a computationally efficient numerical technique to solve first order stiff differential equations. This technique is based on block method whereby three approximate points are calculated. The Cholistani of varied step sizes are presented in divided difference form. Stability regions of the formulae are briefly discussed in this paper. Numerical results show that this block method perform very well compared to existing methods.

Keywords: block method, divided difference, stiff, computational

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Authors: Tobias Horstmann, Thomas Le Garrec, Daniel-Ciprian Mincu, Emmanuel Lévêque

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Despite the efficiency and low dissipation of the stream-collide formulation of the Lattice Boltzmann (LB) algorithm, which is nowadays implemented in many commercial LBM solvers, there are certain situations, e.g. mesh transition, in which a classical finite-volume or finite-difference formulation of the LB algorithm still bear advantages. In this paper, we present an algorithm that combines the node-based streaming of the distribution functions with a second-order finite volume discretization of the advection term of the BGK-LB equation on a uniform D2Q9 lattice. It is shown that such a coupling is possible for a multi-domain approach as long as the overlap, or buffer zone, between two domains, is achieved on at least 2Δx. This also implies that a direct coupling (without buffer zone) of a stream-collide and finite-volume LB algorithm on a single grid is not stable. The critical parameter in the coupling is the CFL number equal to 1 that is imposed by the stream-collide algorithm. Nevertheless, an explicit filtering step on the finite-volume domain can stabilize the solution. In a further investigation, we demonstrate how such a coupling can be used for mesh transition, resulting in an intrinsic conservation of mass over the interface.

Keywords: algorithm coupling, finite volume formulation, grid refinement, Lattice Boltzmann method

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Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

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Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

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Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: T. R. Sreeram, S. Natarajan, C. Jena

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Civil engineering construction is a network of tasks involving varying degree of complexity and streamlining, and standardization is the only way to establish a systemic approach to design. While there are off the shelf tools such as AutoCAD that play a role in the realization of design, the repeatable process in which these tools are deployed often is ignored. The present paper addresses this challenge through a sustainable design process and effective standardizations at all stages in the design workflow. The same is demonstrated through a case study in the context of construction, and further improvement points are highlighted.

Keywords: syste, lean, value stream, process improvement

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Authors: Yibin Qiu, Yubo Ouyang, Shihan Li, Guorui Zhang, Qi Li, Weirong Chen

Abstract:

This paper aims at exploring the impacts of high dimensional dependencies of wind speed among wind farms on probabilistic optimal power flow. To obtain the reactive power optimization faster and more accurately, a mixture vine Copula structure model combining the K-means clustering, C vine copula and D vine copula is proposed in this paper, through which a more accurate correlation model can be obtained. Moreover, a Modified Backtracking Search Algorithm (MBSA), the three-point estimate method is applied to probabilistic optimal power flow. The validity of the mixture vine copula structure model and the MBSA are respectively tested in IEEE30 node system with measured data of 3 adjacent wind farms in a certain area, and the results indicate effectiveness of these methods.

Keywords: mixture vine copula structure model, three-point estimate method, the probability integral transform, modified backtracking search algorithm, reactive power optimization

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Authors: Anu S. Nair, V. Anantha Subramanian

Abstract:

This paper presents a surface development and fairing technique combining the features of a modern computer-aided design tool namely the Non-Uniform Rational Basis Spline (NURBS) with an algorithm to obtain a rapidly faired hull form. Some of the older series based designs give sectional area distribution such as in the Wageningen-Lap Series. Others such as the FORMDATA give more comprehensive offset data points. Nevertheless, this basic data still requires fairing to obtain an acceptable faired hull form. This method uses the input of sectional area distribution as an example and arrives at the faired form. Characteristic section shapes define any general ship hull form in the entrance, parallel mid-body and run regions. The method defines a minimum of control points at each section and using the Golden search method or the bisection method; the section shape converges to the one with the prescribed sectional area with a minimized error in the area fit. The section shapes combine into evolving the faired surface by NURBS and typically takes 20 iterations. The advantage of the method is that it is fast, robust and evolves the faired hull form through minimal iterations. The curvature criterion check for the hull lines shows the evolution of the smooth faired surface. The method is applicable to hull form from any parent series and the evolved form can be evaluated for hydrodynamic performance as is done in more modern design practice. The method can handle complex shape such as that of the bulbous bow. Surface patches developed fit together at their common boundaries with curvature continuity and fairness check. The development is coded in MATLAB and the example illustrates the development of the method. The most important advantage is quick time, the rapid iterative fairing of the hull form.

Keywords: computer-aided design, methodical series, NURBS, ship design

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Authors: Adam M. Yates, Julie E. Byles

Abstract:

Hypertension has been identified as a prominent co-morbidity of obesity. To improve clinical intervention of hypertension, it is critical to identify metrics that most accurately reflect risk for increased morbidity. Two of the most relevant and accurate measures for increased risk of hypertension due to excess adipose tissue are Body Mass Index (BMI) and Waist-Height Ratio (WHtR). Previous research has examined these measures in cross-national and cross-ethnic studies, but has most often relied on secondary means such as meta-analysis to identify and evaluate the efficacy of individual body mass measures. In this study, we instead use cross-sectional analysis to assess the cross-ethnic discriminative power of BMI and WHtR to predict risk of hypertension. Using the WHO SAGE survey, which collected anthropometric and biometric data from respondents in six middle-income countries (China, Ghana, India, Mexico, Russia, South Africa), we implement logistic regression to examine the discriminative power of measured BMI and WHtR with a known population of hypertensive and non-hypertensive respondents. We control for gender and age to identify whether optimum cut-off points that are adequately sensitive as tests for risk of hypertension may be different between groups. We report results for OR, RR, and ROC curves for each of the six SAGE countries. As seen in existing literature, results demonstrate that both WHtR and BMI are significant predictors of hypertension (p < .01). For these six countries, we find that cut-off points for WHtR may be dependent upon gender, age and ethnicity. While an optimum omnibus cut-point for WHtR may be 0.55, results also suggest that the gender and age relationship with WHtR may warrant the development of individual cut-offs to optimize health outcomes. Trends through multiple countries show that the optimum cut-point for WHtR increases with age while the area under the curve (AUROC) decreases for both men and women. Comparison between BMI and WHtR indicate that BMI may remain more robust than WHtR. Implications for public health policy are discussed.

Keywords: hypertension, obesity, Waist-Height ratio, SAGE

Procedia PDF Downloads 478

Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

Abstract:

Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

Procedia PDF Downloads 527