Search results for: looping pipe networks

Authors: Lotfi Beji, Laredj Benchikh

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Underground tunnel face bolting and pipe umbrella reinforcement are one of the most challenging tasks in construction whether industrial or not, and infrastructures such as roads or pipelines. It is one of the first sectors of economic activity in the world. Through a variety of soil and rock, a cyclic Conventional Tunneling Method (CTM) remains the best one for projects with highly variable ground conditions or shapes. CTM is the only alternative for the renovation of existing tunnels and creating emergency exit. During the drilling process, a wide variety of non-desired vibrations may arise, and a method using a robot arm is proposed. The main kinds of drilling through vibration here is the bit-bouncing phenomenon (resonant axial vibration). Hence, assisting the task by a robot arm may play an important role on drilling performances and security. We propose to control the axial-vibration phenomenon along the drillstring at a practical resonant frequency, and embed a Resonant Sonic Drilling Head (RSDH) as a robot end effector for drilling. Many questionable industry drilling criteria and stability are discussed in this paper.

Keywords: drilling, resonant vibration, robot arm, control

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Authors: Mingshu Liu, Laura Santamaria, Xavier Carmaniu Mainadé

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As one of the sectors most affected by the COVID-19 pandemic, tourism is facing challenges in revitalizing the industry. But at the same time, it would be a good opportunity to take advantage of digital communication as an effective tool for tourism promotion. Our proposal aims to verify the linguistic operations on online platforms in China. The research is carried out based on the theory of Eco-traductology put forward by Gengshen Hu, whose contribution focuses on the translator's adaptation to the ecosystem environment and the three elaborated parameters (linguistic, cultural and communicative). We also relate it to Even-Zohar's and Toury's theoretical postulates on the Polysystem to elaborate on interdisciplinary methodology. Such a methodology allows us to analyze personal treatments and phraseology in the target text. As for the corpus, we adopt the official Spanish-language website of Turismo de España as the source text and the postings on the two major social networks in China, Weibo and Wechat, in 2019. Through qualitative analysis, we conclude that, in the tourism advertising campaign on Chinese social networks, chengyu (Chinese phraseology) and honorific titles are used very frequently.

Keywords: digital communication, eco-traductology, polysystem theory, tourism advertising

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Authors: Aradhna Pandarum

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South Africa is experiencing an exponential growth of distributed solar PV installations. This is due to various factors with the predominant one being increasing electricity tariffs along with decreasing installation costs, resulting in attractive business cases to some end-users. Despite there being a variety of economic and environmental advantages associated with the installation of PV, their potential impact on distribution grids has yet to be thoroughly investigated. This is especially true since the locations of these units cannot be controlled by Network Service Providers (NSPs) and their output power is stochastic and non-dispatchable. This report details two case studies that were completed to determine the possible voltage and technical losses impact of increasing PV penetration in the Northern Cape of South Africa. Some major impacts considered for the simulations were ramping of PV generation due to intermittency caused by moving clouds, the size and overall hosting capacity and the location of the systems. The main finding is that the technical impact is different on a constrained feeder vs a non-constrained feeder. The acceptable PV penetration level is much lower for a constrained feeder than a non-constrained feeder, depending on where the systems are located.

Keywords: medium voltage networks, power system losses, power system voltage, solar photovoltaic

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Authors: M. Macchiaroli, V. Pellecchia, L. Dolores

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Within any European and world model of management of the integrated water service (in Italy only since 2012 is regulated by a national Authority, that is ARERA), a significant part is covered by the development of assets in terms of hydraulic networks and wastewater collection networks, including all their relative building works. The process of selecting the investments to be made starts from the preventive analysis of critical issues (water losses, unserved areas, low service standards, etc.) who occur in the managed territory of the Operator. Through the Program of Interventions (Provision by ARERA n. 580/2019/R/idr), the Operator provides to program the projects that can meet the emerged needs to determine the improvement of the water service levels. This phase (analyzed and solved by the author with a work published in 2019) involves the use of evaluation techniques (cost-benefit analysis, multi-criteria, and multi-objective techniques, neural networks, etc.) useful in selecting the most appropriate design answers to the different criticalities. However, at this point, the problem of establishing the time priorities between the various works deemed necessary remains open. That is, it is necessary to hierarchize the investments. In this decision-making moment, the interests of the private Operator are often opposed, which favors investments capable of generating high profitability, compared to those of the public controller (ARERA), which favors investments in greater social impact. In support of the concertation between these two actors, the protocol set out in the research has been developed, based on the AHP and capable of borrowing from the programmatic documents an orientation path for the settlement of the conflict. The protocol is applied to a case study of the Campania Region in Italy and has been professionally applied in the shared decision process between the manager and the local Authority.

Keywords: analytic hierarchy process, decision making, economic evaluation of projects, integrated water service

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: Sa'ad Ali

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This study explores wasta as an example of a social network and how it impacts business practice in the Arab Middle East, drawing links with social network impact in different regions of the world. In doing so, particular attention will be paid to the socio-economic and cultural influences on business practice. In exploring relationships in business, concepts such as social network analysis, social capital and group identity are used to explore the different forms of social networks and how they influence business decisions and practices in the regions and countries where they prevail. The use of social networks to achieve objectives is known as guanxi in China, wasta in the Arab Middle East and blat in ex-Soviet countries. Wasta can be defined as favouritism based on tribal and family affiliation and is a widespread practice that has a substantial impact on political, social and business interactions in the Arab Middle East. Within the business context, it is used in several ways, such as to secure a job or promotion or to cut through bureaucracy in government interactions. The little research available is fragmented, and most studies reveal a negative attitude towards its usage in business. Paradoxically, while wasta is widely practised, people from the Arab Middle East often deny its influence. Moreover, despite the regular exhibition of a negative opinion on the practice of wasta, it can also be a source of great pride. This paper addresses this paradox by conducting a positional literature review, exploring the current literature on wasta and identifying how the identified paradox can be explained. The findings highlight how wasta, to a large extent, has been treated as an umbrella concept, whilst it is a highly complex practice which has evolved from intermediary wasta to intercessory wasta and therefore from bonding social capital relationships to more bridging social capital relationships. In addition, the research found that Islam, as the predominant religion in the region and the main source of ethical guidance for the majority of people from the region, plays a substantial role in this paradox. Specifically, it is submitted that wasta can be viewed positively in Islam when it is practised to aid others without breaking Islamic ethical guidelines, whilst it can be viewed negatively when it is used in contradiction with the teachings of Islam. As such, the unique contribution to knowledge of this study is that it ties together the fragmented literature on wasta, highlighting and helping us understand its complexity. In addition, it sheds light on the role of Islam in wasta practices, aiding our understanding of the paradoxical nature of the practice.

Keywords: Islamic ethics, social capital, social networks, Wasta

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Authors: Gupta Rajesh, Paudel Sagar, Sharma Utkarsh, Singh Amit Kumar

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Thermal stratification has drawn much attention because of the malfunctions at various nuclear plants in U.S.A that raised significant safety concerns. The concerns due to this phenomenon relate to thermal stresses in branch pipes connected to the reactor coolant system piping. This stress limits the lifetime of the piping system, and even leading to penetrating cracks. To assess origin of valve damage in the pipeline, it is essential to determine the effect of turbulence penetration on valve leakage; since stratified flow is generally generated by turbulent penetration or valve leakage. As a result, we concluded with the help of coupled fluent-structural analysis that the pipe with less turbulence has less chance of failure there by requiring less maintenance.

Keywords: nuclear reactor coolant system, thermal stratification, turbulent penetration, coupled fluent-structural analysis, Von-Misses stress

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Authors: Lim Kar Sing, Siti Nur Afifah Azraai, Norhazilan Md Noor, Nordin Yahaya

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Polymeric composites are being increasingly used as repair material for repairing critical infrastructures such as building, bridge, pressure vessel, piping and pipeline. Technique in repairing damaged pipes is one of the major concerns of pipeline owners. Considerable researches have been carried out on the repair of corroded pipes using composite materials. This article attempts a short review of the subject matter to provide insight into various techniques used in repairing corroded pipes, focusing on a wide range of composite repair systems. These systems including pre-cured layered, flexible wet lay-up, pre-impregnated, split composite sleeve and flexible tape systems. Both advantages and limitations of these repair systems were highlighted. Critical technical aspects have been discussed through the current standards and practices. Research gaps and future study scopes in achieving more effective design philosophy are also presented.

Keywords: composite materials, pipeline, repair technique, polymers

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Wichan Lertlop

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This research is to study the solubility of oxygen in water taking the form of aeration pipes that have different shaped objectives of the research to compare the amount of oxygen dissolved in the water, whice take the form of aeration pipes. Shaped differently When aeration 5 minutes on air for 10 minutes, and when air fills 30 minutes, as well as compare the durability of the oxygen is dissolved in the water of the inlet air refueling shaped differently when you fill the air 30 minutes and when. aeration and 60 minutes populations used in this study, the population of pond water from Rajabhat University in February 2014 used in this study consists of 1. Aerator 2. Hose using a hose to fill the air with 3 different shape, different shapes pyramid whose base is on the water tank. Shaped rectangular water tank onto the ground. And shapes in a vertical pipe. 3 meter, dissolved oxygen, dissolved in water to get the calibration standard. 4. The clock for timer 5. Three water tanks which are 39 cm wide, 51 cm long and 32 cm high.

Keywords: aeration, dissolve oxygen, different shapes

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Authors: Noel Jeygar Robert, V. K.Vidya

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Cognitive radio is a software-defined radio technology that allows cognitive users to operate on the vacant bands of spectrum allocated to licensed users. Cognitive radio plays a vital role in the efficient utilization of wireless radio spectrum available between cognitive users and licensed users without making any interference to licensed users. The spectrum allocation followed by spectrum sharing is done in a fashion where a cognitive user has to wait until spectrum holes are identified and allocated when the licensed user moves out of his own allocated spectrum. In this paper, we propose a self –coexistence strategy using bargaining and Cournot game model for achieving spectrum allocation in cognitive radio networks. The game-theoretic model analyses the behaviour of cognitive users in both cooperative and non-cooperative scenarios and provides an equilibrium level of spectrum allocation. Game-theoretic models such as bargaining game model and Cournot game model produce a balanced distribution of spectrum resources and energy consumption. Simulation results show that both game theories achieve better performance compared to other popular techniques

Keywords: cognitive radio, game theory, bargaining game, Cournot game

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Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle

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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.

Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3

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Authors: Lori W. Gordon, Karen A. Jones

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Today’s high-speed data connectivity depends on a vast global network of infrastructure across space, air, land, and sea, with undersea cable infrastructure (UCI) serving as the primary means for intercontinental and ‘long-haul’ communications. The UCI landscape is changing and includes an increasing variety of state actors, such as the growing economies of Brazil, Russia, India, China, and South Africa. Non-state commercial actors, such as hyper-scale content providers including Google, Facebook, Microsoft, and Amazon, are also seeking to control their data and networks through significant investments in submarine cables. Active investments by both state and non-state actors will invariably influence the growth, geopolitics, and security of this sector. Beyond these hyper-scale content providers, there are new commercial satellite communication providers. These new players include traditional geosynchronous (GEO) satellites that offer broad coverage, high throughput GEO satellites offering high capacity with spot beam technology, low earth orbit (LEO) ‘mega constellations’ – global broadband services. And potential new entrants such as High Altitude Platforms (HAPS) offer low latency connectivity, LEO constellations offer high-speed optical mesh networks, i.e., ‘fiber in the sky.’ This paper focuses on understanding the role of submarine cables within the larger context of the global data commons, spanning space, terrestrial, air, and sea networks, including an analysis of national security policy and geopolitical implications. As network operators and commercial and government stakeholders plan for emerging technologies and architectures, hedging risks for future connectivity will ensure that our data backbone will be secure for years to come.

Keywords: communications, global, infrastructure, technology

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Authors: Ioannis Binas, Marios Moschakis

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Electrical faults in transmission and distribution networks can have great impact on the electrical equipment used. Fault effects depend on the characteristics of the fault as well as the network itself. It is important to anticipate the network’s behavior during faults when planning a new equipment installation, as well as troubleshooting. Moreover, working backwards, we could be able to estimate the characteristics of the fault when checking the perceived effects. Different transformer winding connections dominantly used in the Greek power transfer and distribution networks and the effects of 1-phase to neutral, phase-to-phase, 2-phases to neutral and 3-phase faults on different locations of the network were simulated in order to present voltage sag characteristics. The study was performed on a generic network with three steps down transformers on two voltage level buses (one 150 kV/20 kV transformer and two 20 kV/0.4 kV). We found that during faults, there are significant changes both on voltage magnitudes and on phase angles. The simulations and short-circuit analysis were performed using the PSCAD simulation package. This paper presents voltage characteristics calculated for the simulated network, with different approaches on the transformer winding connections during symmetrical and asymmetrical faults on various locations.

Keywords: Phase angle shift, power quality, transformer winding connections, voltage sag propagation

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Authors: Yasmina Houda Bendahma, Tewfik Bouchaour, Meriem Merad, Ulrich Maschke

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The purpose of this work is to study retention of dye dissolved in distilled water, by an hydrophilic acrylic polymer network. The polymer network considered is Poly (2-hydroxyethyl methacrylate) (PHEMA): it is prepared by photo-polymerization under UV irradiation in the presence of a monomer (HEMA), initiator and an agent cross-linker. PHEMA polymer network obtained can be used in the retention of dye molecules present in the wastewater. The results obtained are interesting in the study of the kinetics of swelling and de-swelling of cross linked polymer networks PHEMA in colored aqueous solutions. The dyes used for retention by the PHEMA networks are eosin Y and Malachite Green, dissolved in distilled water. Theoretical conformational study by a simplified molecular model of system cross linked PHEMA / dye (eosin Y and Malachite Green), is used to simulate the retention phenomenon (or Docking) dye molecules in cavities in nano-domains included in the PHEMA polymer network.

Keywords: dye retention, molecular modeling, photochemically crosslinked polymer network, swelling deswelling, PHEMA, HEMA

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Authors: Seyed-Mohammad-Kazem Emami, Behrang Saki, Majid Mohammadian

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The wastewater flow field inside a sewage network including pipe and ‎manhole was investigated using a Computational Fluid Dynamics ‎‎(CFD) model. The numerical model is developed by incorporating a ‎rheological model to calculate the viscosity of wastewater fluid by ‎means of open source toolbox OpenFOAM. The rheological ‎properties of prepared wastewater fluid suspensions are first measured ‎using a BrookField LVDVII Pro+ viscometer with an enhanced UL ‎adapter and then correlated the suitable rheological viscosity model ‎values from the measured rheological properties. The results show the ‎significant effects of rheological characteristics of wastewater fluid on ‎the flow domain of sewer system. Results were compared and ‎discussed with the commonly used Newtonian model to evaluate the ‎differences for velocity profile, pressure and shear stress. ‎

Keywords: Non-Newtonian flows, Wastewater, Numerical simulation, Rheology, Sewage Network

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Authors: Jessica Hemberg, Amanda Sundqvist, Yulia Korzhina, Lillemor Östman, Sofia Gylfe, Frida Gädda, Lisbet Nyström, Henrik Groundstroem, Pia Nyman-Kurkiala

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Purpose: There are large gaps in the literature on COVID-19 pandemic-related mental health outcomes and after-effects specific to adolescents and young adults. The study's aim was to explore adolescents’ and young adults’ experiences of well-being, health, and loneliness during the COVID-19 pandemic. Method: A qualitative exploratory design with qualitative content analysis was used. Twenty-three participants (aged 19-27; four men and 19 women) were interviewed. Results: Four themes emerged: Changed social networks – fewer and closer contacts, changed mental and physical health, increased physical and social loneliness, well-being, internal growth, and need for support. Conclusion: Adolescents’ and young adults’ experiences of well-being, health, and loneliness are subtle and complex. Participants experienced changed social networks, mental and physical health, and well-being. Also, internal growth, need for support, and increased loneliness were seen. Clear information on how to seek help and support from professionals should be made available.

Keywords: adolescents, COVID-19 pandemic, health, interviews, loneliness, qualitative, well-being, young adults

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Authors: Sefik Can Karakaya, Ibrahim Demir

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In this study, the relationship between musical preferences and personality traits has been investigated in terms of Spotify audio analysis features. The aim of this paper is to build such a classifier capable of segmenting people into their Myers-Briggs Type Index (MBTI) personality type based on their Spotify playlists. Music takes an important place in the lives of people all over the world and online music streaming platforms make it easier to reach musical contents. In this context, the motivation to build such a classifier is allowing people to gain access to their MBTI personality type and perhaps for more reliably and more quickly. For this purpose, logistic regression and deep neural networks have been selected for classifier and their performances are compared. In conclusion, it has been found that musical preferences differ statistically between personality traits, and evaluated models are able to distinguish personality types based on given musical data structure with over %60 accuracy rate.

Keywords: myers-briggs type indicator, music psychology, Spotify, behavioural user profiling, deep neural networks, logistic regression

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie

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Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.

Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

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Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

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In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

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Authors: Liuyu Zhang, Di Mo, Qiang Yan, Min Liu

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As the important equipment in the construction field, cuplock scaffold plays an important role in the construction process. As a scaffold connecting member, cuplock joint is of great importance. In order to explore the rotational stiffness nonlinear characteristics changing features of different structural forms of cuplock joint in different tightening torque condition under different conditions of load, ANSYS is used to establish four kinds of cuplock joint models with different forces to simulate the real force situation. By setting the different load conditions which means the cuplock is loaded at a certain distance from the cuplock joint in a certain direction until the cuplock is damaged and considering the gap between the cross bar joint and the vertical bar, the differences in the influence of the structural form and tightening torque on the rotation stiffness of the cuplock under different load conditions are compared. It is significantly important to improve the accuracy of calculating bearing capacity and stability of the cuplock steel pipe scaffold.

Keywords: cuplock joint, highway tunnel, non-linear characteristics, rotational stiffness, scaffold stability, theoretical analysis

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Authors: W. Sun, W. Wen, J. Lu, A. A. Becker

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In this work, methods for determining creep properties which can be used to represent the full life until failure from miniature specimen creep tests based on analytical solutions are presented. Examples used to demonstrate the application of the methods include a miniature rectangular thin beam specimen creep test under three-point bending and a miniature two-material tensile specimen creep test subjected to a steady load. Mathematical expressions for deflection and creep strain rate of the two specimens were presented for the Kachanov-Rabotnov creep damage model. On this basis, an inverse procedure was developed which has potential applications for deriving the full life creep damage constitutive properties from a very small volume of material, in particular, for various microstructure constitutive  regions, e.g. within heat-affected zones of power plant pipe weldments. Further work on validation and improvement of the method is addressed.

Keywords: creep damage property, miniature specimen, inverse approach, finite element modeling

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

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This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

Abstract:

Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

Procedia PDF Downloads 192

Authors: Aishwarya Shekhar, Devesh Kumar Srivastava

Abstract:

Cloud computing has emerged as a promising direction for cost efficient and reliable service delivery across data communication networks. The dynamic location of service facilities and the virtualization of hardware and software elements are stressing the communication networks and protocols, especially when data centres are interconnected through the internet. Although the computing aspects of cloud technologies have been largely investigated, lower attention has been devoted to the networking services without involving IT operating overhead. Cloud computing has enabled elastic and transparent access to infrastructure services without involving IT operating overhead. Virtualization has been a key enabler for cloud computing. While resource virtualization and service abstraction have been widely investigated, networking in cloud remains a difficult puzzle. Even though network has significant role in facilitating hybrid cloud scenarios, it hasn't received much attention in research community until recently. We propose Network as a Service (NaaS), which forms the basis of unifying public and private clouds. In this paper, we identify various challenges in adoption of hybrid cloud. We discuss the design and implementation of a cloud platform.

Keywords: cloud computing, networking, infrastructure, hybrid cloud, open stack, naas

Procedia PDF Downloads 403

Authors: Khalid Kaddoura, Tarek Zayed

Abstract:

Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

Procedia PDF Downloads 334