Search results for: node insertion
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 711

Search results for: node insertion

261 Lithium Ion Supported on TiO2 Mixed Metal Oxides as a Heterogeneous Catalyst for Biodiesel Production from Canola Oil

Authors: Mariam Alsharifi, Hussein Znad, Ming Ang

Abstract:

Considering the environmental issues and the shortage in the conventional fossil fuel sources, biodiesel has gained a promising solution to shift away from fossil based fuel as one of the sustainable and renewable energy. It is synthesized by transesterification of vegetable oils or animal fats with alcohol (methanol or ethanol) in the presence of a catalyst. This study focuses on synthesizing a high efficient Li/TiO2 heterogeneous catalyst for biodiesel production from canola oil. In this work, lithium immobilized onto TiO2 by the simple impregnation method. The catalyst was evaluated by transesterification reaction in a batch reactor under moderate reaction conditions. To study the effect of Li concentrations, a series of LiNO3 concentrations (20, 30, 40 wt. %) at different calcination temperatures (450, 600, 750 ºC) were evaluated. The Li/TiO2 catalysts are characterized by several spectroscopic and analytical techniques such as XRD, FT-IR, BET, TG-DSC and FESEM. The optimum values of impregnated Lithium nitrate on TiO2 and calcination temperature are 30 wt. % and 600 ºC, respectively, along with a high conversion to be 98 %. The XRD study revealed that the insertion of Li improved the catalyst efficiency without any alteration in structure of TiO2 The best performance of the catalyst was achieved when using a methanol to oil ratio of 24:1, 5 wt. % of catalyst loading, at 65◦C reaction temperature for 3 hours of reaction time. Moreover, the experimental kinetic data were compatible with the pseudo-first order model and the activation energy was (39.366) kJ/mol. The synthesized catalyst Li/TiO2 was applied to trans- esterify used cooking oil and exhibited a 91.73% conversion. The prepared catalyst has shown a high catalytic activity to produce biodiesel from fresh and used oil within mild reaction conditions.

Keywords: biodiesel, canola oil, environment, heterogeneous catalyst, impregnation method, renewable energy, transesterification

Procedia PDF Downloads 149
260 A Study on Using Network Coding for Packet Transmissions in Wireless Sensor Networks

Authors: Rei-Heng Cheng, Wen-Pinn Fang

Abstract:

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

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

Procedia PDF Downloads 362
259 Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

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

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

Procedia PDF Downloads 495
258 A Mixture Vine Copula Structures Model for Dependence Wind Speed among Wind Farms and Its Application in Reactive Power Optimization

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

Abstract:

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

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

Procedia PDF Downloads 230
257 A Preparatory Method for Building Construction Implemented in a Case Study in Brazil

Authors: Aline Valverde Arroteia, Tatiana Gondim do Amaral, Silvio Burrattino Melhado

Abstract:

During the last twenty years, the construction field in Brazil has evolved significantly in response to its market growing and competitiveness. However, this evolving path has faced many obstacles such as cultural barriers and the lack of efforts to achieve quality at the construction site. At the same time, the greatest amount of information generated on the designing or construction phases is lost due to the lack of an effective coordination of these activities. Face this problem, the aim of this research was to implement a French method named PEO which means preparation for building construction (in Portuguese) seeking to understand the design management process and its interface with the building construction phase. The research method applied was qualitative, and it was carried out through two case studies in the city of Goiania, in Goias, Brazil. The research was divided into two stages called pilot study at Company A and implementation of PEO at Company B. After the implementation; the results demonstrated the PEO method's effectiveness and feasibility while a booster on the quality improvement of design management. The analysis showed that the method has a purpose to improve the design and allow the reduction of failures, errors and rework commonly found in the production of buildings. Therefore, it can be concluded that the PEO is feasible to be applied to real estate and building companies. But, companies need to believe in the contribution they can make to the discovery of design failures in conjunction with other stakeholders forming a construction team. The result of PEO can be maximized when adopting the principles of simultaneous engineering and insertion of new computer technologies, which use a three-dimensional model of the building with BIM process.

Keywords: communication, design and construction interface management, preparation for building construction (PEO), proactive coordination (CPA)

Procedia PDF Downloads 135
256 Research on Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System

Authors: Zhou Mo, Dennis Chow

Abstract:

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

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

Procedia PDF Downloads 423
255 Social Ties and Integration of the Offenders

Authors: C. Chaillou

Abstract:

The dominant theoretical approaches in Criminology are interested in the phenomenon of delinquency from the question of the management of the risks incurred by the population. Thus, this research advocate prevention of this phenomenon by a tracking of early disorders in children. Treatments offered to rely on medical research (genetics and biology are cited as a reference) and assuming a high naturalization of delinquent behaviour. Programs that are offered also reduce to a recovery of the deviant behaviour, and rely readily on behavioral guidelines, with an educational grant. Public policy then rely on these programs to prevent unwanted behaviour within a given population and to reduce the risk for the company. This is the case in France, with national institutes making (juvenile) violence a public health problem. We consider that other approaches, issues of sociology, are more relevant to the treatment of offenders. These approaches are moving, not on its prevention, but from its inputs and its outputs. Several modalities of entries and exits of delinquency can find and analyze in terms of process. We assume that there is a dynamic inherent in the individual and it is important to take into account the environment of the offender. These different types of processes can illuminate from the derived work of the Psychoanalytical psychopathology and lead to more effective treatment of delinquent acts. Psychoanalytic concepts have enabled us to offer a new look means to treat delinquency, placing several types of relationship with the other and relating to the clinical structure and the uniqueness of the case, we have been able to enter subjective and unconscious logics at work in delinquent acts. This research has facilitated the reduction of these types of subjective responses and proposed others, opening to a reintegration of offenders in a social link them being more favourable and in a longer term.

Keywords: delinquency, insertion, social link, unconscious

Procedia PDF Downloads 349
254 New Approach for Minimizing Wavelength Fragmentation in Wavelength-Routed WDM Networks

Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

Abstract:

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

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

Procedia PDF Downloads 498
253 Photoelectrochemical Water Splitting from Earth-Abundant CuO Thin Film Photocathode: Enhancing Performance and Photo-Stability through Deposition of Overlayers

Authors: Wilman Septina, Rajiv R. Prabhakar, Thomas Moehl, David Tilley

Abstract:

Cupric oxide (CuO) is a promising absorber material for the fabrication of scalable, low cost solar energy conversion devices, due to the high abundance and low toxicity of copper. It is a p-type semiconductor with a band gap of around 1.5 eV, absorbing a significant portion of the solar spectrum. One of the main challenges in using CuO as solar absorber in an aqueous system is its tendency towards photocorrosion, generating Cu2O and metallic Cu. Although there have been several reports of CuO as a photocathode for hydrogen production, it is unclear how much of the observed current actually corresponds to H2 evolution, as the inevitability of photocorrosion is usually not addressed. In this research, we investigated the effect of the deposition of overlayers onto CuO thin films for the purpose of enhancing its photostability as well as performance for water splitting applications. CuO thin film was fabricated by galvanic electrodeposition of metallic copper onto gold-coated FTO substrates, followed by annealing in air at 600 °C. Photoelectrochemical measurement of the bare CuO film using 1 M phosphate buffer (pH 6.9) under simulated AM 1.5 sunlight showed a current density of ca. 1.5 mA cm-2 (at 0.4 VRHE), which photocorroded to Cu metal upon prolonged illumination. This photocorrosion could be suppressed by deposition of 50 nm-thick TiO2, deposited by atomic layer deposition. In addition, we found that insertion of an n-type CdS layer, deposited by chemical bath deposition, between the CuO and TiO2 layers was able to enhance significantly the photocurrent compared to without the CdS layer. A photocurrent of over 2 mA cm-2 (at 0 VRHE) was observed using the photocathode stack FTO/Au/CuO/CdS/TiO2/Pt. Structural, electrochemical, and photostability characterizations of the photocathode as well as results on various overlayers will be presented.

Keywords: CuO, hydrogen, photoelectrochemical, photostability, water splitting

Procedia PDF Downloads 194
252 DCASH: Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y Synchronizing Mobile Database Systems

Authors: Gunasekaran Raja, Kottilingam Kottursamy, Rajakumar Arul, Ramkumar Jayaraman, Krithika Sairam, Lakshmi Ravi

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The synchronization server maintains a dynamically changing cache, which contains the data items which were requested and collected by the mobile node from the server. The order and presence of tuples in the cache changes dynamically according to the frequency of updates performed on the data, by the server and client. To synchronize, the data which has been modified by client and the server at an instant are collected, batched together by the type of modification (insert/ update/ delete), and sorted according to their update frequencies. This ensures that the DCASH (Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y synchronizing Mobile Database Systems) gives priority to the frequently accessed data with high usage. The optimal memory management algorithm is proposed to manage data items according to their frequency, theorems were written to show the current mobile data activity is reverse Y in nature and the experiments were tested with 2g and 3g networks for various mobile devices to show the reduced response time and energy consumption.

Keywords: mobile databases, synchronization, cache, response time

Procedia PDF Downloads 363
251 A 3D Model of the Sustainable Management of the Natural Environment in National Parks

Authors: Paolo Russu

Abstract:

This paper investigates the economic and ecological dynamics that emerge in Protected Areas (PAs) as a result of interactions between visitors to the area and the animals that live there. We suppose that the PAs contain two species whose interactions are determined by the Lotka-Volterra equations system. Visitors' decisions to visit PAs are influenced by the entrance cost required to enter the park as well as the chance of witnessing the species that live there. Visitors have contradictory effects on the species and thus on the sustainability of the protected areas: on the one hand, an increase in the number of tourists damages the natural habitat of the areas and thus the species living there; on the other hand, it increases the total amount of entrance fees that the managing body of the PAs can use to perform defensive expenditures that protect the species from extinction. For a given set of parameter values, the existence of saddle-node bifurcation, Hopf bifurcation, homoclinic orbits, and a Bogdanov–Takens bifurcation of codimension two has been investigated. The system displays periodic doubling and chaotic solutions, as demonstrated by numerical examples. Pontryagin's Maximum Principle was utilized to develop an optimal admission charge policy that maximized both social gain and ecosystem conservation.

Keywords: environmental preferences, singularities point, dynamical system, chaos

Procedia PDF Downloads 69
250 Investigation of FoxM1 Gene Expression in Breast Cancer and Its Relationship with miR-216b-5p Expression Level

Authors: Neda Menbari, Ramin Mehdiabadi

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Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions.

Keywords: breast cancer, gene expression, FOXM1, microRNA

Procedia PDF Downloads 18
249 Agent Based Location Management Protocol for Mobile Adhoc Networks

Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

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The dynamic nature of Mobile adhoc network (MANET) due to mobility and disconnection of mobile nodes, leads to various problems in predicting the movement of nodes and their location information updation, for efficient interaction among the application specific nodes. Location management is one of the main challenges to be considered for an efficient service provision to the applications of a MANET. In this paper, we propose a location management protocol, for locating the nodes of a MANET and to maintain uninterrupted high-quality service for distributed applications by intelligently anticipating the change of location of its nodes. The protocol predicts the node movement and application resource scarcity, does the replacement with the chosen nodes nearby which have less mobility and rich in resources, with the help of both static and mobile agents, and maintains the application continuity by providing required network resources. The protocol has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. It consumes much less time (response time), gives better location accuracy, utilize less network resources, and reduce location management overhead.

Keywords: mobile agent, location management, distributed applications, mobile adhoc network

Procedia PDF Downloads 360
248 A Comparison of Implant Stability between Implant Placed without Bone Graft versus with Bone Graft Using Guided Bone Regeneration (GBR) Technique: A Resonance Frequency Analysis

Authors: R. Janyaphadungpong, A. Pimkhaokham

Abstract:

This prospective clinical study determined the insertion torque (IT) value and monitored the changes in implant stability quotient (ISQ) values during the 12 weeks healing period from implant placement without bone graft (control group) and with bone graft using the guided bone regeneration (GBR) technique (study group). The relationship between the IT and ISQ values of the implants was also assessed. The control and study groups each consisted of 6 patients with 8 implants per group. The ASTRA TECH Implant System™ EV 4.2 mm in diameter was placed in the posterior mandibular region. In the control group, implants were placed in bone without bone graft, whereas in the study group implants were placed simultaneously with the GBR technique at favorable bone defect. IT (Ncm) of each implant was recorded when fully inserted. ISQ values were obtained from the Osstell® ISQ at the time of implant placement, and at 2, 4, 8, and 12 weeks. No difference in IT was found between groups (P = 0.320). The ISQ values in the control group were significantly higher than in the study group at the time of implant placement and at 4 weeks. There was no significant association between IT and ISQ values either at baseline or after the 12 weeks. At 12 weeks of healing, the control and study groups displayed different trends. Mean ISQ values for the control group decreased over the first 2 weeks and then started to increase. ISQ value increases were statistically significant at 8 weeks and later, whereas mean ISQ values in the study group decreased over the first 4 weeks and then started to increase, with statistical significance after 12 weeks. At 12 weeks, all implants achieved osseointegration with mean ISQ values over the threshold value (ISQ>70). These results indicated that implants, in which guided bone regeneration technique was performed during implant placement for treating favorable bone defects, were as predictable as implants placed without bone graft. However, loading in implants placed with the GBR technique for correcting favorable bone defects should be performed after 12 weeks of healing to ensure implant stability and osseointegration.

Keywords: dental implant, favorable bone defect, guided bone regeneration technique, implant stability

Procedia PDF Downloads 266
247 WSN System Warns Atta Cephalotes Climbing in Mango Fruit Trees

Authors: Federico Hahn Schlam, Fermín Martínez Solís

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Leaf-cutting ants (Atta cephalotes) forage from mango tree leaves and flowers to feed their colony. Farmers find it difficult to control ants due to the great quantity of trees grown in commercial orchards. In this article, IoT can support farmers for ant detection in real time, as production losses can be considered of 324 US per tree.A wireless sensor network, WSN, was developed to warn the farmer from ant presence in trees during a night. Mango trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller, and the other eight trees presented slave microcontrollers (nodes). At each node, anemitter diode-photodiode unitdetects ants climbing up. A capacitor is chargedand discharged after being sampled every ten minutes. The system usesBLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE.When ants were detected the number of the tree was transmitted via LoRa from the masterto the producer smartphone to warn him. In this paper, BLE, LoRa, and energy consumption were studied under variable vegetation in the orchard. During 2018, 19 trees were attacked by ants, and ants fed 26.3% of flowers and 73.7% of leaves.

Keywords: BLE, atta cephalotes, LoRa, WSN-smartphone, energy consumption

Procedia PDF Downloads 127
246 Trajectory Optimization of Re-Entry Vehicle Using Evolutionary Algorithm

Authors: Muhammad Umar Kiani, Muhammad Shahbaz

Abstract:

Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

Procedia PDF Downloads 383
245 A Study on the Microbilogical Profile and Antibiotic Sensitivity Pattern of Bacterial Isolates Causing Urinary Tract Infection in Intensive Care Unit Patients in a Tertiary Care Hospital in Eastern India

Authors: Pampita Chakraborty, Sukumar Mukherjee

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The study was done to determine the microbiological profile and changing pattern of the pathogens causing UTI in the ICU patients. All the patients admitted to the ICU with urinary catheter insertion for more than 48hours were included in the study. Urine samples were collected in a sterile container with aseptic precaution using disposable syringe and was processed as per standards. Antimicrobial susceptibility test was done by Disc Diffusion method as per CLSI guidelines. A total of 100 urine samples were collected from ICU patients, out of which 30% showed significant bacterial growth and 7% showed growth of candida spp. Prevalence of UTI was more in female (73%) than male (27.%). Gram-negative bacilli 26(86.67%) were more common in our study followed by gram-positive cocci 4(13.33%). The most common uropathogens isolated were Escherichia coli 14 (46.67%), followed by Klebsiella spp 7(23.33%), Staphylococcus aureus 4(13.33%), Acinetobacter spp 3(10%), Enterococcus faecalis 1(3.33%) and Pseudomonas aeruginosa 1(3.33%). Most of the Gram-negative bacilli were sensitive to amikacin (80%) and nitrofurantoin (80%), where as all gram-positive organisms were sensitive to Vancomycin. A large number ESBL producers were also observed in this study. The study finding showed that E.coli is the predominant pathogen and has increasing resistance pattern to the commonly used antibiotics. The study proposes that the adherence to antibiotic policy is the key ingredients for successful outcome in ICU patients and also emphasizes that repeated evaluation of microbial characteristics and continuous surveillance of resistant bacteria is required for selection of appropriate antibiotic therapy.

Keywords: antimicrobial sensitivity, intensive care unit, nosocomial infection, urinary tract infection

Procedia PDF Downloads 245
244 Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks

Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

Procedia PDF Downloads 171
243 High Performance Field Programmable Gate Array-Based Stochastic Low-Density Parity-Check Decoder Design for IEEE 802.3an Standard

Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

Abstract:

This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

Procedia PDF Downloads 272
242 Hemodynamics of a Cerebral Aneurysm under Rest and Exercise Conditions

Authors: Shivam Patel, Abdullah Y. Usmani

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Physiological flow under rest and exercise conditions in patient-specific cerebral aneurysm models is numerically investigated. A finite-volume based code with BiCGStab as the linear equation solver is used to simulate unsteady three-dimensional flow field through the incompressible Navier-Stokes equations. Flow characteristics are first established in a healthy cerebral artery for both physiological conditions. The effect of saccular aneurysm on cerebral hemodynamics is then explored through a comparative analysis of the velocity distribution, nature of flow patterns, wall pressure and wall shear stress (WSS) against the reference configuration. The efficacy of coil embolization as a potential strategy of surgical intervention is also examined by modelling coil as a homogeneous and isotropic porous medium where the extended Darcy’s law, including Forchheimer and Brinkman terms, is applicable. The Carreau-Yasuda non-Newtonian blood model is incorporated to capture the shear thinning behavior of blood. Rest and exercise conditions correspond to normotensive and hypertensive blood pressures respectively. The results indicate that the fluid impingement on the outer wall of the arterial bend leads to abnormality in the distribution of wall pressure and WSS, which is expected to be the primary cause of the localized aneurysm. Exercise correlates with elevated flow velocity, vortex strength, wall pressure and WSS inside the aneurysm sac. With the insertion of coils in the aneurysm cavity, the flow bypasses the dilatation, leading to a decline in flow velocities and WSS. Particle residence time is observed to be lower under exercise conditions, a factor favorable for arresting plaque deposition and combating atherosclerosis.

Keywords: 3D FVM, Cerebral aneurysm, hypertension, coil embolization, non-Newtonian fluid

Procedia PDF Downloads 207
241 Simplified 3R2C Building Thermal Network Model: A Case Study

Authors: S. M. Mahbobur Rahman

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Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model

Procedia PDF Downloads 115
240 Development of Materials Based on Phosphates of NaZr2(PO4)3 with Low Thermal Expansion

Authors: V. Yu. Volgutov, A. I. Orlova, S. A. Khainakov

Abstract:

NaZr2(PO4)3 (NZP) and their structural analogues are characterized by a peculiar behaviors on heating – they have different expansion and contraction along different crystallographic directions due to specific arrangements of crystal structure in these compounds. An important feature of such structures is the ability to incorporate into their structural analogues wide variety of metal cations having different size and oxidation states, with different combinations and concentrations. These cations are located in different crystallographic non-equivalent positions of octahedral tetrahedral crystal framework as well as in inter-framework cavities. Through, due to iso- and hetero-valent isomorphism of the cations (and the anions) in NZP, it becomes possible to tuning the compositions and to obtain the compounds with ‘on a plan’ properties. For the design of compounds with low and ultra-low thermal expansion including those with tailored thermal expansion properties, the following crystallochemical principles it seems are promising: 1) Insertion into crystal M1 position the cations having different sizes and, 2) the variation in the composition of compounds, providing different occupation of crystal M1 position. Following these principles we have designed and synthesized the next NZP-type phosphates series: a) where radii of the cations in the M1 crystal position was varied: Zr1/4Zr2(PO4)3 - Th1/4Zr2(PO4)3 (series I); R1/3Zr2(PO4)3 where R= Nd, Eu, Er (series II), b) where the occupation of M1 crystal position was varied: Zr1/4Zr2(PO4)3-Er1/3Zr2(PO4)3 (series III) and Zr1/4Zr2(PO4)3-Sr1/2Zr2(PO4)3 (series IV). The thermal expansion parameters were determined over the range of 25-800ºC. For each series the minimum axial coefficient of thermal expansion αa = αb, αc and their anisotropy Δα = Iαa - αcI, 10-6 K-1 was found as next: -1.51, 1.07, 2.58 for Th1/4Zr2(PO4)3 (series I); -0.72, 0.10, 0.81 for Nd1/3Zr2(PO4)3 (series II); -2.78, 1.35, 4.12 for Er1/6Zr1/8Zr2(PO4)3 (series III); 2.23, 1.32, 0.91 for Sr1/2Zr2(PO4)3 (series IV). The measured tendencies of the thermal expansion of crystals were in good agreement with predicted ones. For one of the members from the studied phosphates namely Th1/16Zr3/16Zr2(PO4)3 structural refinement have been carried out at 25, 200, 600, and 800°C. The dependencies of the structural parameters with the temperature have been determined.

Keywords: high-temperature crystallography, NaZr2(PO4)3, (NZP) analogs, structural-chemical principles, tuning thermal expansion

Procedia PDF Downloads 211
239 Using Hidden Markov Chain for Improving the Dependability of Safety-Critical Wireless Sensor Networks

Authors: Issam Alnader, Aboubaker Lasebae, Rand Raheem

Abstract:

Wireless sensor networks (WSNs) are distributed network systems used in a wide range of applications, including safety-critical systems. The latter provide critical services, often concerned with human life or assets. Therefore, ensuring the dependability requirements of Safety critical systems is of paramount importance. The purpose of this paper is to utilize the Hidden Markov Model (HMM) to elongate the service availability of WSNs by increasing the time it takes a node to become obsolete via optimal load balancing. We propose an HMM algorithm that, given a WSN, analyses and predicts undesirable situations, notably, nodes dying unexpectedly or prematurely. We apply this technique to improve on C. Lius’ algorithm, a scheduling-based algorithm which has served to improve the lifetime of WSNs. Our experiments show that our HMM technique improves the lifetime of the network, achieved by detecting nodes that die early and rebalancing their load. Our technique can also be used for diagnosis and provide maintenance warnings to WSN system administrators. Finally, our technique can be used to improve algorithms other than C. Liu’s.

Keywords: wireless sensor networks, IoT, dependability of safety WSNs, energy conservation, sleep awake schedule

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238 Impact of Breed and Physiological Status on Blood Content of Goats in Arid Conditions of Algeria

Authors: Lilia Belkacem, Zahra Rouabah, Assia Allaoui, Karina Bachtarzi, Souhila Belkadi, Boubakeur Safsaf, Madjid Tlidjane

Abstract:

The Damascus breed, known for its prolificacy and milking ability, is recently imported in Algeria. Farmers tend to improve the local native herds by crossbreeding with Damascus bucks. The aim of the current investigation was to study the effects of physiological status on blood progesterone and some biochemical parameters in Shami goats and their crosses with local breed in arid conditions of Algeria. Ten does with an age range of 1.5- 3 years and BSC between 2.5 and 3.5 were used. Female goats were divided into two groups of five animals each: Damascus, and crossbred (Damascus x Arbia). All females were estrus synchronized and naturally mated. Blood samples were collected before intravaginal sponge insertion (non- pregnant), in early (30 days after sponge removal), mid (90 days), late pregnancy (130 days) and after kidding (30 days post-partum). Results demonstrate a significant effect of the reproductive stage on progesterone (P4) levels in both groups, on glycemia and cholesterolemia in crossbred does (p<0.05) and on albuminemia and uremia in Damascus ones. Concentrations of triglycerides, total proteins, globulin and creatinine revealed no significant difference between physiological phases in both groups (p>0.05). Breed effect was detected in early and mid-pregnancy for P4, in early pregnancy and lactation for total proteins and in lactation for globulin with lower concentrations in Damascus compared to crossbred does. Changes in P4 and biochemical profiles of both groups reflect the female goat’s adaptation to increased requirement of gestation and lactation in arid conditions of Algeria.

Keywords: damascus goat, crossbred, reproductive status, progesterone, biochemical metabolites

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237 Data Clustering in Wireless Sensor Network Implemented on Self-Organization Feature Map (SOFM) Neural Network

Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

Abstract:

Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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236 Explainable Graph Attention Networks

Authors: David Pham, Yongfeng Zhang

Abstract:

Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

Procedia PDF Downloads 140
235 Towards Reliable Mobile Cloud Computing

Authors: Khaled Darwish, Islam El Madahh, Hoda Mohamed, Hadia El Hennawy

Abstract:

Cloud computing has been one of the fastest growing parts in IT industry mainly in the context of the future of the web where computing, communication, and storage services are main services provided for Internet users. Mobile Cloud Computing (MCC) is gaining stream which can be used to extend cloud computing functions, services and results to the world of future mobile applications and enables delivery of a large variety of cloud application to billions of smartphones and wearable devices. This paper describes reliability for MCC by determining the ability of a system or component to function correctly under stated conditions for a specified period of time to be able to deal with the estimation and management of high levels of lifetime engineering uncertainty and risks of failure. The assessment procedures consists of determine Mean Time between Failures (MTBF), Mean Time to Failure (MTTF), and availability percentages for main components in both cloud computing and MCC structures applied on single node OpenStack installation to analyze its performance with different settings governing the behavior of participants. Additionally, we presented several factors have a significant impact on rates of change overall cloud system reliability should be taken into account in order to deliver highly available cloud computing services for mobile consumers.

Keywords: cloud computing, mobile cloud computing, reliability, availability, OpenStack

Procedia PDF Downloads 372
234 A New DIDS Design Based on a Combination Feature Selection Approach

Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

Abstract:

Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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233 Autism Spectrum Disorder Classification Algorithm Using Multimodal Data Based on Graph Convolutional Network

Authors: Yuntao Liu, Lei Wang, Haoran Xia

Abstract:

Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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232 A Virtual Grid Based Energy Efficient Data Gathering Scheme for Heterogeneous Sensor Networks

Authors: Siddhartha Chauhan, Nitin Kumar Kotania

Abstract:

Traditional Wireless Sensor Networks (WSNs) generally use static sinks to collect data from the sensor nodes via multiple forwarding. Therefore, network suffers with some problems like long message relay time, bottle neck problem which reduces the performance of the network. Many approaches have been proposed to prevent this problem with the help of mobile sink to collect the data from the sensor nodes, but these approaches still suffer from the buffer overflow problem due to limited memory size of sensor nodes. This paper proposes an energy efficient scheme for data gathering which overcomes the buffer overflow problem. The proposed scheme creates virtual grid structure of heterogeneous nodes. Scheme has been designed for sensor nodes having variable sensing rate. Every node finds out its buffer overflow time and on the basis of this cluster heads are elected. A controlled traversing approach is used by the proposed scheme in order to transmit data to sink. The effectiveness of the proposed scheme is verified by simulation.

Keywords: buffer overflow problem, mobile sink, virtual grid, wireless sensor networks

Procedia PDF Downloads 352