Search results for: network screening

Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

Abstract:

In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results.

Keywords: adaptive control, pendulum dynamical system, nonlinear control, adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

Procedia PDF Downloads 654

Authors: S. Beekrum, B. Odhav, R. Lalloo, E. O. Amonsou

Abstract:

Marine microalgae are rich sources of the novel and biologically active metabolites; therefore, they may be used in the food industry as natural food ingredients and functional foods. They have several biological applications related with health benefits, among others. In the past decades, food scientists have been searching for natural alternatives to replace synthetic antioxidants. The use of synthetic antioxidants has decreased due to their suspected activity as promoters of carcinogenesis, as well as consumer rejection of synthetic food additives. The aim of the study focused on screening of phytochemicals from Cymbella biomass extracts, and to examine the in vitro antioxidant and antimicrobial potential. Cymbella biomass was obtained from CSIR (South Africa), and four different solvents namely methanol, acetone, n-hexane and water were used for extraction. To take into account different antioxidant mechanisms, seven different antioxidant assays were carried out. These include free radical scavenging (DPPH assay), Trolox equivalent antioxidant capacity (TEAC assay), radical cation (ABTS assay), superoxide anion radical scavenging, reducing power, determination of total phenolic compounds and determination of total flavonoid content. The total content of phenol and flavonoid in extracts were determined as gallic acid equivalent, and as rutin equivalent, respectively. The in vitro antimicrobial effect of extracts were tested against some pathogens (Staphylococcus aureus, Listeria monocytogenes, Bacillus subtilis, Salmonella enteritidis, Escherichia coli, Pseudomonas aeruginosa and Candida albicans), using the disc diffusion assay. Qualitative analyses of phytochemicals were conducted by chemical tests to screen for the presence of tannins, flavonoids, terpenoids, phenols, steroids, saponins, glycosides and alkaloids. The present investigation revealed that all extracts showed relatively strong antibacterial activity against most of the tested bacteria. The methanolic extract of the biomass contained a significantly high phenolic content of 111.46 mg GAE/g, and the hexane extract contained 65.279 mg GAE/g. Results of the DPPH assay showed that the biomass contained strong antioxidant capacity, 79% in the methanolic extract and 85% in the hexane extract. Extracts have displayed effective reducing power and superoxide anion radical scavenging. Results of this study have highlighted potential antioxidant activity in the methanol and hexane extracts. The obtained results of the phytochemical screening showed the presence of terpenoids, flavonoids, phenols and saponins. The use of Cymbella as a natural antioxidant source and a potential source of antibacterial compounds and phytochemicals in the food industry appears promising and should be investigated further.

Keywords: antioxidants, antimicrobial, Cymbella, microalgae, phytochemicals

Procedia PDF Downloads 435

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

Abstract:

Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 150

Authors: Bingquan Shen

Abstract:

Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

Procedia PDF Downloads 334

Authors: Jennifer Reese, Josh Biber, Howard Weeks, Rachel Hess

Abstract:

Aim: The Edinburgh Postnatal Depression Screen (EPDS) is a mental health screening for pregnant women that has been widely used over the last 30 years. This screen is typically given in clinic on paper to patients throughout pregnancy and postpartum. The screen helps identify patients who may be at risk for pregnancy related depression or postpartum depression. In early 2016, University of Utah Health implemented an electronic version of the EPDS as well as the PROMIS Depression v1.0 instrument for all pregnant and postpartum patients. We asked patients both instruments to understand coverage of patients identified as at risk for each instrument. Methods: The EPDS is currently administered as part of our PRO template for pregnant and postpartum women. We also administer the PROMIS Depression as part of a standard PRO assessment to all patients. Patients are asked to complete an assessment no more often than every eight weeks. PRO assessments are either completed at home or in clinic with a tablet computer. Patients with a PROMIS score of ≥ 65 or a EPDS score of ≥ 10 were identified as at risk for depression Results: From April 2016 to April 2017, 1,330 unique patients were screened at University of Utah Health in OBGYN clinics with both the EPDS and PROMIS depression instrument on the same day. There were 28 (2.1%) patients were identified as at risk for depression using the PROMIS depression screen, while 262 (19.7%) patients were identified as at risk for postpartum depression using the EPDS screen. Overall, 27 (2%) patients were identified as at risk on both instruments. Conclusion: The EPDS identified a higher percent (19.7%) of patients at risk for depression when compared to the PROMIS depression (2.1%). Ninety-six percent of patients who screened positive on the PROMIS depression screen also screened positive on the EPDS screen. Mental health is an important component to a patient’s overall wellbeing. We want to ensure all patients, particularly pregnant or post-partum women, receive screening and treatment when necessary. A combination of screenings may be necessary to provide the overall best care for patients and to identify the highest percentage of patients at risk.

Keywords: patient reported outcomes, mental health, maternal, depression

Procedia PDF Downloads 357

Authors: Hala Zaghloul, Taymoor Nazmy

Abstract:

One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 263

Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

Abstract:

Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

Procedia PDF Downloads 230

Authors: Samia Dardouri, Ridha Bouallegue

Abstract:

Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

Procedia PDF Downloads 369

Authors: Chothmal

Abstract:

In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

Procedia PDF Downloads 232

Authors: Senay Yitmen

Abstract:

This research investigated individual’s support and helping intentions towards Syrian refugees in Turkey. This is examined in relation to perceived threat and negative emotions, and also to the perceptions of whether one’s intimate social network (family and friends) considers Syrians a threat (descriptive network norm) and whether this network morally supports Syrian refugees (injunctive norms). A questionnaire study was conducted among Turkish participants (n= 565) and the results showed that perception of threat was associated with negative emotions which, in turn, were related to less support of Syrian refugees. Additionally, descriptive norms moderated the relationship between perceived threat and negative emotions towards Syrian refugees. Furthermore, injunctive norms moderated the relationship between negative emotions and support to Syrian refugees. Specifically, the findings indicate that perceived threat is associated with less support of Syrian refugees through negative emotions when descriptive norms are weak and injunctive norms are strong. Injunctive norms appear to trigger a dilemma over the decision to conform or not to conform: when one has negative emotions as a result of perceived threat, it becomes more difficult to conform to the moral obligation of injunctive norms which is associated with less support of Syrian refugees. Hence, these findings demonstrate that both descriptive and injunctive norms are important and play different roles in individual’s support of Syrian refugees.

Keywords: descriptive norms, emotions, injunctive norms, the perception of threat

Procedia PDF Downloads 172

Authors: Sajida Rasheed, Imran Hashmi, Luiza Campos, Qizhi Zhou, Kim Keu

Abstract:

A quadratic model (p ˂ 0.0001) was developed by using central composite design of 50 experimental runs (42 non-center + 8 center points) to assess efficiency of background chlorine residuals in combating accidental microbial episode in a prototype distribution network (DN) (rig). A known amount of background chlorine residuals were maintained in DN and a required number of bacteria, Escherichia coli K-12 strain were introduced by an injection port in the pipe loop system. Samples were taken at various time intervals at different pipe lengths. Spread plate count was performed to count bacterial number. The model developed was significant. With microbial concentration and time (p ˂ 0.0001), pipe length (p ˂ 0.022), background chlorine residuals (p ˂ 0.07) and time^2 (p ˂ 0.09) as significant factors. The ramp function of variables shows that at the microbial count of 10^6, at 0.76 L/min, and pipe length of 133 meters, a background residual chlorine 0.16 mg/L was enough for complete inactivation of microbial episode in approximately 18 minutes.

Keywords: central composite design (CCD), distribution network, Escherichia coli, residual chlorine

Procedia PDF Downloads 449

Authors: Mohammad S. Razai, Jan Williams, Rachel Nestel, Dermot Dalton

Abstract:

Purpose: This descriptive qualitative study aimed to obtain parents recommendations for improving the notification process and communication of positive newborn screening result for cystic fibrosis (CF). Methods: Thematic analysis of semi-structured open-ended interviews with 11 parents of 7 children with confirmed diagnosis of CF between 2 months — 2 years of age. Results: Parents preferred face to face disclosure of positive NBS results by a pediatrician with CF professional qualification. They trusted a pediatrician more than any other professional in providing accurate, credible and comprehensive information about the diagnosis and its implications. Parents recommended that health professionals be knowledgeable and provide clear, succinct and understandable information. Providers should also explore parents concerns and acknowledge feelings and emotions. Most parents reported that they preferred to be notified immediately as soon as the results were available. Several parents preferred to be told once the diagnosis was certain. Most parents regarded open access to CF team as the most significant part of care coordination. In addition to health professionals, most parents used internet as an important source of information, interaction and exchange of experiences. Most parents also used social networking sites such as Facebook groups and smart phone apps. Conclusion: This study provides significant new evidence from parental perspective in emphasizing the pivotal role of good communication skills deployed by a knowledgeable CF specialist in person. Parents use of social media and internet has replaced some traditional methods of information exchange and may reduce the need for professional input for newly diagnosed CF patients.

Keywords: care coordination, cystic fibrosis, newborn screening, notification process, parental preferences, professional-paren communication

Procedia PDF Downloads 388

Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

Abstract:

In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks（EBCAM）based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

Procedia PDF Downloads 265

Authors: Daniel Fulus Fom, Gau Patrick Damulak

Abstract:

In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

Procedia PDF Downloads 259

Authors: C. Vázquez, L. M. Gigirey, C. P. del Oro, S. Seoane

Abstract:

Poor vision is common among older people, and several studies show connections between visual impairment and cognitive function. 15 older adult live in Galician Government nursing homes, and cognitive decline is one of the main reasons of admission. Objectives: (1) To evaluate functional far and near vision of older people with cognitive impairment. (2) To determine connections between visual and cognitive state of “our” residents. Methodology: A total of 364 older adults (aged 65 years or more) underwent a visual and cognitive screening. We tested presenting visual acuity (binocular visual acuity with habitual correction if warn) for distance and near vision (E-Snellen, usual working distance for near vision). Binocular presenting visual acuity less than 0.3 was used as cut point for diagnosis of visual impairment. Exclusion criteria included immobilized residents unable to reach the USC Dual Sensory Loss Unit for visual screening. To screen cognition we employed the mini-mental examination test (Spanish version). Analysis of categorical variables was performed using chi-square tests. We utilized Pearson and Spearman correlation tests and the variance analysis to determine differences between groups of interest (SPSS 19.0 version). Results: the percentage of residents with cognitive decline reaches 32.2% Prevalence of visual impairment for distance and near vision increases among those subjects with cognitive impairment respect those with normal cognition. Shift correlation exists between distance visual acuity and mini-mental test (age and sex controlled), and moderate association was found in case of near vision (p<0.01). Conclusion: First results shows that people with cognitive impairment have poor functional distance and near vision than those with normal cognition. Next step will be to analyse the individual contribution of distance and near vision loss on cognition.

Keywords: visual impairment, cognition, aging, nursing homes

Procedia PDF Downloads 417

Authors: Kais Manai

Abstract:

The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

Procedia PDF Downloads 486

Authors: Mikheil Kalmakhelidze

Abstract:

Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

Procedia PDF Downloads 262

Authors: Nazmul Shahadat, Anthony S. Maida

Abstract:

In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

Procedia PDF Downloads 65

Authors: M. L. Mangena, N. Mokoena, K. Rashamuse, M. G. Tlou

Abstract:

Tertiary alcohol ester (TAE) hydrolases are a group of esterases (EC 3.1.1.-) that catalyze the kinetic resolution of TAEs and as a result, they are sought-after for the production of optically pure tertiary alcohols (TAs) which are useful as building blocks for number biologically active compounds. What sets these enzymes apart is, the presence of a GGG(A)X-motif in the active site which appears to be the main reason behind their activity towards the sterically demanding TAEs. The genome of Pseudomonas syringae pv. maculicola (Psm) comprises a multitude of genes that encode esterases. We therefore, hypothesize that some of these genes encode TAE hydrolases. In this study, Psm was screened for TAE hydrolase activity using the linalyl acetate (LA) plate assay and a positive reaction was observed. As a result, the genome of Psm was screened for esterases with a GGG(A)X-motif using the motif search tool and two potential TAE hydrolase genes (PsmEST1 and 2, 1100 and 1000bp, respectively) were identified, PsmEST1 was amplified by PCR and the gene sequenced for confirmation. Analysis of the sequence data with the SingnalP 4.1 server revealed that the protein comprises a signal peptide (22 amino acid residues) on the N-terminus. Primers specific for the gene encoding the mature protein (without the signal peptide) were designed such that they contain NdeI and XhoI restriction sites for directional cloning of the PCR products into pET28a. The gene was expressed in E. coli JM109 (DE3) and the clones screened for TAE hydrolase activity using the LA plate assay. A positive clone was selected, overexpressed and the protein purified using nickel affinity chromatography. The activity of the esterase towards LA was confirmed using thin layer chromatography.

Keywords: hydrolases, tertiary alcohol esters, tertiary alcohols, screening, Pseudomonas syringae pv., maculicola genome, esterase activity, linalyl acetate

Procedia PDF Downloads 342

Authors: Chuan Yang, Jing Bie, Zhong Wang, Panagiotis Psimoulis

Abstract:

Contemporary studies investigating the association between the spatial configuration of the urban network and economic activities at the street level were mostly conducted within space syntax conceptual framework. These findings supported the theory of 'movement economy' and demonstrated the impact of street configuration on the distribution of pedestrian movement and land-use shaping, especially retail activities. However, the effects varied between different urban contexts. In this paper, the relationship between economic activity distribution and the urban configurational characters was examined at the segment level. In the study area, three kinds of neighbourhood types, urban, suburban, and rural neighbourhood, were included. And among all neighbourhoods, three kinds of urban network form, 'tree-like', grid, and organic pattern, were recognised. To investigate the nested effects of urban configuration measured by space syntax approach and urban context, multilevel zero-inflated negative binomial (ZINB) regression models were constructed. Additionally, considering the spatial autocorrelation, spatial lag was also concluded in the model as an independent variable. The random effect ZINB model shows superiority over the ZINB model or multilevel linear (ML) model in the explanation of economic activities pattern shaping over the urban environment. And after adjusting for the neighbourhood type and network form effects, connectivity and syntax centrality significantly affect economic activities clustering. The comparison between accumulative and new established economic activities illustrated the different preferences for economic activity location choice.

Keywords: space syntax, economic activities, multilevel model, Chinese city

Procedia PDF Downloads 111

Authors: Yu Song, Yuefei Jin

Abstract:

Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

Procedia PDF Downloads 61

Authors: Pavan Shah

Abstract:

In an Embedded system, Virtualization and visualization technology can provide us an effective response and measurable work in a software development environment. In addition to work of virtualization and virtualization can be easily deserved to provide the best resource sharing between real-time hardware applications and a healthy environment. However, the virtualization is noticeable work to minimize the I/O work and utilize virtualization & virtualization technology for either a software development environment (SDE) or a runtime environment of real-time embedded systems (RTMES) or real-time operating system (RTOS) eras. In this Paper, we particularly focus on virtualization and visualization overheads data of network which generates the I/O and implementation of standardized I/O (i.e., Virto), which can work as front-end network driver in a real-time operating system (RTOS) hardware module. Even there have been several work studies are available based on the virtualization operating system environment, but for the Virto on a general-purpose OS, my implementation is on the open-source Virto for a real-time operating system (RTOS). In this paper, the measurement results show that implementation which can improve the bandwidth and latency of memory management of the real-time operating system environment (RTMES) for getting more accuracy of the trained model.

Keywords: virtualization, visualization, network driver, operating system

Procedia PDF Downloads 118

Authors: Kalyani Kulkarni, Bharat Chaudhari

Abstract:

This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.

Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation

Procedia PDF Downloads 456

Authors: Kyere Francis, Sun Dongying, Asante Dennis, Nkrumah Nana Kwame Edmund, Naana Yaa Gyamea Kumah

Abstract:

With a focus on renewable energy to achieve low-carbon transition objectives, there is a greater demand for effective collaborative strategies for planning, strategic decision mechanisms, and long-term policy designs to steer the transitions. Government agencies, NGOs, the private sector, and individual citizens play an important role in sustainable energy production. In Ghana, however, such collaboration is fragile in the fight against climate change. This current study seeks to re-examine the position or potential of network governance in Ghana's renewable energy transition. The study adopted a qualitative approach and employed semi-structured interviews for data gathering. To explore network governance and low carbon transitions in Ghana, we examine key themes such as political environment and impact, actor cooperation and stakeholder interactions, financing and the transition, market design and renewable energy integration, existing regulation and policy gaps for renewable energy transition, clean cooking accessibility, and affordability. The findings reveal the following; Lack of comprehensive consultations with relevant stakeholders leads to lower acceptance of the policy model and sometimes lack of policy awareness. Again, the unavailability and affordability of renewable energy technologies and access to credit facilities is a significant hurdle to long-term renewable transition. Ghana's renewable energy transitions require strong networking and interaction among the public, private, and non-governmental organizations. The study participants believe that the involvement of relevant energy experts and stakeholders devoid of any political biases is instrumental in accelerating renewable energy transitions, as emphasized in the proposed framework. The study recommends that the national renewable energy transition plan be evident to all stakeholders and political administrators. Such policy may encourage renewable energy investment through stable and fixed lending rates by the financial institutions and build a network with international organizations and corporations. These findings could serve as valuable information for the transition-based energy process, primarily aiming to govern sustainability changes through network governance.

Keywords: actors, development, sustainable energy, network governance, renewable energy transition

Procedia PDF Downloads 66

Authors: Amandeep Singh Dhaliwal

Abstract:

Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

Procedia PDF Downloads 410

Authors: Xiaoqian Cheng, Jon Kleppe, Ole Torsaeter

Abstract:

One objective of this work is to analyze the effects of surfactant properties (viscosity, concentration, and adsorption) on surfactant enhanced oil recovery at laboratory scale. The other objective is to obtain the functional relationships between surfactant properties and the ultimate oil recovery and oil recovery rate. A core is cut into two parts from the middle to imitate the matrix with a horizontal fracture. An injector and a producer are at the left and right sides of the fracture separately. The middle slice of the core is used as the model in this paper, whose size is 4cm x 0.1cm x 4.1cm, and the space of the fracture in the middle is 0.1 cm. The original properties of matrix, brine, oil in the base case are from Ekofisk Field. The properties of surfactant are from literature. Eclipse is used as the simulator. The results are followings: 1) The viscosity of surfactant solution has a positive linear relationship with surfactant oil recovery time. And the relationship between viscosity and oil production rate is an inverse function. The viscosity of surfactant solution has no obvious effect on ultimate oil recovery. Since most of the surfactant has no big effect on viscosity of brine, the viscosity of surfactant solution is not a key parameter of surfactant screening for surfactant flooding in fractured reservoirs. 2) The increase of surfactant concentration results a decrease of oil recovery rate and an increase of ultimate oil recovery. However, there are no functions could describe the relationships. Study on economy should be conducted because of the price of surfactant and oil. 3) In the study of surfactant adsorption, assume that the matrix wettability is changed to water-wet when the surfactant adsorption is to the maximum at all cases. And the ratio of surfactant adsorption and surfactant concentration (Cads/Csurf) is used to estimate the functional relationship. The results show that the relationship between ultimate oil recovery and Cads/Csurf is a logarithmic function. The oil production rate has a positive linear relationship with exp(Cads/Csurf). The work here could be used as a reference for the surfactant screening of surfactant enhanced oil recovery from fractured reservoirs. And the functional relationships between surfactant properties and the oil recovery rate and ultimate oil recovery help to improve upscaling methods.

Keywords: fractured reservoirs, surfactant adsorption, surfactant concentration, surfactant EOR, surfactant viscosity

Procedia PDF Downloads 160

Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

Abstract:

Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

Procedia PDF Downloads 371

Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

Abstract:

With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

Procedia PDF Downloads 77

Authors: Teja Sai Puligadda

Abstract:

Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

Procedia PDF Downloads 141

Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

Abstract:

One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

Procedia PDF Downloads 51