Search results for: time workflow network

Authors: Heitor Oliveira, Gabriele De-Waal, Juergen Schmenger, Lynsey Godfrey, Tibor Kovacs

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Rheolaser MASTER™ makes use of multiple scattering of light, caused by scattering objects in a continuous medium (such as droplets and particles in colloids), to characterize the viscoelasticity of soft materials. It offers an alternative to conventional rheometers to characterize viscoelasticity of products such as hair cosmetics. Up to six simultaneous measurements at controlled temperature can be carried out simultaneously (10-15 min), and the method requires only minor sample preparation work. Conversely to conventional rheometer based methods, no mechanical stress is applied to the material during the measurements. Therefore, the properties of the exact same sample can be monitored over time, like in aging and stability studies. We determined the elastic index (EI) of water/emulsion mixtures (1 ≤ fat alcohols (FA) ≤ 5 wt%) and emulsion/gel-network mixtures (8 ≤ FA ≤ 17 wt%) and compared with the elastic/sorage mudulus (G’) for the respective samples using a TA conventional rheometer with flat plates geometry. As expected, it was found that log(EI) vs log(G’) presents a linear behavior. Moreover, log(EI) increased in a linear fashion with solids level in the entire range of compositions (1 ≤ FA ≤ 17 wt%), while rheometer measurements were limited to samples down to 4 wt% solids level. Alternatively, a concentric cilinder geometry would be required for more diluted samples (FA > 4 wt%) and rheometer results from different sample holder geometries are not comparable. The plot of the rheolaser output parameters solid-liquid balance (SLB) vs EI were suitable to monitor product aging processes. These data could quantitatively describe some observations such as formation of lumps over aging time. Moreover, this method allowed to identify that the different specifications of a key raw material (RM < 0.4 wt%) in the respective gel-network (GN) product has minor impact on product viscoelastic properties and it is not consumer perceivable after a short aging time. Broadening of a RM spec range typically has a positive impact on cost savings. Last but not least, the photon path length (λ*)—proportional to droplet size and inversely proportional to volume fraction of scattering objects, accordingly to the Mie theory—and the EI were suitable to characterize product destabilization processes (e.g., coalescence and creaming) and to predict product stability about eight times faster than our standard methods. Using these parameters we could successfully identify formulation and process parameters that resulted in unstable products. In conclusion, Rheolaser allows quick and reliable characterization of viscoelastic properties of hair cosmetics that are related to their performance and stability. It operates in a broad range of product compositions and has applications spanning from the formulation of our hair cosmetics to fast release criteria in our production sites. Last but not least, this powerful tool has positive impact on R&D development time—faster delivery of new products to the market—and consequently on cost savings.

Keywords: colloids, hair cosmetics, light scattering, performance and stability, soft materials, viscoelastic properties

Procedia PDF Downloads 172

Authors: José Anderson Rodrigues de Souza, Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, Jeronimo Silva Rocha

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Mobile devices are increasingly occupying sectors of society and one of its most important features is mobility. However, the use of mobile devices is subject to the lifetime of the batteries. Thus, the use of energy batteries has become an important issue in the study of wireless network technologies. In this context, new solutions that enable aggregate energy efficiency not only through energy saving, and principally they are evaluated from a more realistic model of energy discharge, if easy adaptation to existing protocols. This paper presents a study on the energy needed and the lifetime for Wireless Sensor Networks (WSN) using a heterogeneous network and applying the LEACH protocol.

Keywords: wireless sensor networks, energy efficiency, heterogeneous, LEACH protocol

Procedia PDF Downloads 580

Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

Procedia PDF Downloads 628

Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

Procedia PDF Downloads 123

Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control

Procedia PDF Downloads 339

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 133

Authors: Lina Abou Haibeh, Nadir Hakem, Ousama Abu Safia

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In this paper, the performance and quality of Voice over IP (VoIP) calls carried over a Mobile Ad Hoc Network (MANET) which has a number of SIP nodes registered on a SIP Proxy are analyzed. The testing campaigns are carried out in an indoor corridor structure having a well-defined channel’s characteristics and model for the different voice codecs, G.711, G.727 and G.723.1. These voice codecs are commonly used in VoIP technology. The calls’ quality are evaluated using four Quality of Service (QoS) metrics, namely, mean opinion score (MOS), jitter, delay, and packet loss. The relationship between the wireless channel’s parameters and the optimum codec is well-established. According to the experimental results, the voice codec G.711 has the best performance for the proposed MANET topology

Keywords: wireless channel modelling, Voip, MANET, session initiation protocol (SIP), QoS

Procedia PDF Downloads 228

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

Procedia PDF Downloads 329

Authors: Mohd Salmi Md Noorani, Ghada Al-Mahbashi, Sakhinah Abu Bakar

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This paper investigates projective lag synchronization (PLS) behavior in drive response dynamical networks (DRDNs) model with identical nodes. A hybrid feedback control method is designed to achieve the PLS with mismatch and without mismatch terms. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Moreover, the numerical simulations results demonstrate the validity of the proposed method.

Keywords: drive-response dynamical network, projective lag synchronization, hybrid feedback control, stability theory

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

Procedia PDF Downloads 164

Authors: Igor Astrov, Natalya Berezovski

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This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMA-L2 neurocontroller for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Keywords: NARMA-L2 neurocontroller, situational awareness, vectored thrust aerial vehicle, aviation

Procedia PDF Downloads 420

Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

Procedia PDF Downloads 144

Authors: Bilal Haider, Farhan Aadil

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A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

Procedia PDF Downloads 170

Authors: Tzu-Jung Huang, Hsun-Jung Cho, Chien-Chia Liäm Huang

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To improve the level of service (LoS) of urban arterial systems containing a series of signalized intersections, a proper design of offsets for all intersections associated is of great importance. The MAXBAND model has been the most common approach for this purpose. In this paper, we propose a MAXBAND model with phase constraints so that the lengths of the phases in a cycle are variable. In other words, the length of a cycle is also variable in our setting. We conduct experiments on a real-world traffic network, having several major paths, in Taiwan for numerical evaluations. Actual traffic data were collected through on-site experiments. Numerical evidences suggest that the improvements are around 32%, on average, in terms of total delay of the entire network.

Keywords: arterial progression, MAXBAND, signal control, offset

Procedia PDF Downloads 358

Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

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Authors: Karina Guimaraes, Lilian Santos

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This study has the purpose of planning and instituting monitoring actions as a way of knowing the scenario of assistance to the patient with stoma, treated in the public health network in Brazil, from January to November of the year 2016, from the elaboration of a technical document containing the survey of the number of procedures offered and the value of the ostomy services, accredited in the Unified Health System-SUS. The purpose of this document is to improve the quality of these services in the efficient management of available financial resources, making it indispensable for the creation of strategies for the implementation and implementation of care services for people with stomata as a strategic tool in the promotion, prevention, qualification and efficiency in health care.

Keywords: health economic, management, ostomy, unified health system

Procedia PDF Downloads 311

Authors: T. Pedersen, A. Lindfeldt

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The minimum dwell time is an important part of railway timetable planning. Due to its stochastic behaviour, the minimum dwell time should be considered to create resilient timetables. While there has been significant focus on how to determine and estimate dwell times, to our knowledge, little research has been carried out regarding temporal and running direction variations of these. In this paper, we examine how the minimum dwell time varies depending on temporal factors such as the time of day, day of the week and time of the year. We also examine how it is affected by running direction and station type. The minimum dwell time is estimated by means of track occupation data. A method is proposed to ensure that only minimum dwell times and not planned dwell times are acquired from the track occupation data. The results show that on an aggregated level, the average minimum dwell times in both running directions at a station are similar. However, when temporal factors are considered, there are significant variations. The minimum dwell time varies throughout the day with peak hours having the longest dwell times. It is also found that the minimum dwell times are influenced by weekday, and in particular, weekends are found to have lower minimum dwell times than most other days. The findings show that there is a potential to significantly improve timetable planning by taking minimum dwell time variations into account.

Keywords: minimum dwell time, operations quality, timetable planning, track occupation data

Procedia PDF Downloads 198

Authors: N. Sabiyath Fatima, R. K. Shanmugasundaram

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In Mobile Ad-hoc Networks (MANETS), every node performs both as transmitter and receiver. The existing backoff models do not exactly forecast the performance of the wireless network. Also, the existing models experience elevated packet collisions. Every time a collision happens, the station’s contention window (CW) is doubled till it arrives at the utmost value. The main objective of this paper is to diminish collision by means of contention window Multiplicative Increase Decrease Backoff (CWMIDB) scheme. The intention of rising CW is to shrink the collision possibility by distributing the traffic into an outsized point in time. Within wireless Ad hoc networks, the CWMIDB algorithm dynamically controls the contention window of the nodes experiencing collisions. During packet communication, the backoff counter is evenly selected from the given choice of [0, CW-1]. At this point, CW is recognized as contention window and its significance lies on the amount of unsuccessful transmission that had happened for the packet. On the initial transmission endeavour, CW is put to least amount value (C min), if transmission effort fails, subsequently the value gets doubled, and once more the value is set to least amount on victorious broadcast. CWMIDB is simulated inside NS2 environment and its performance is compared with Binary Exponential Backoff Algorithm. The simulation results show improvement in transmission probability compared to that of the existing backoff algorithm.

Keywords: backoff, contention window, CWMIDB, MANET

Procedia PDF Downloads 277

Authors: Chih-Chiang Hua, Yi-Hsiung Fang, Yuan-Jhen Siao

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A bridgeless boost (BLB) power factor correction (PFC) rectifier with hold-up time extension circuit is proposed in this paper. A full bridge rectifier is widely used in the front end of the ac/dc converter. Since the shortcomings of the full bridge rectifier, the bridgeless rectifier is developed. A BLB rectifier topology is utilized with the hold-up time extension circuit. Unlike the traditional hold-up time extension circuit, the proposed extension scheme uses fewer active switches to achieve a longer hold-up time. Simulation results are presented to verify the converter performance.

Keywords: bridgeless boost (BLB), boost converter, power factor correction (PFC), hold-up time

Procedia PDF Downloads 417

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

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In this work, we have described a new 3-dimensional (3D) network of cross-linked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: redox enzyme, nanomaterials, biosensors, electrical communication

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

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Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

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Authors: Mostafa Mjahed

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Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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Authors: Jia-Jane Shuai

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Purpose of this research aims to improve understanding of the nature of online religion by examining the religious social websites. What motivates individual users to use the online religious social websites, and which factors affect those motivations. We survey various online religious social websites provided by different religions, especially the Taiwanese folk religion. Based on the theory of the Content Analysis and Social Network Analysis, religious social websites and religious web activities are examined. This research examined the folk religion websites’ presentation and contents that promote the religious use of the Internet in Taiwan. The difference among different religions and religious websites also be compared. First, this study used keywords to examine what types of messages gained the most clicks of “Like”, “Share” and comments on Facebook. Dividing the messages into four media types, namely, text, link, video, and photo, reveal which category receive more likes and comments than the others. Meanwhile, this study analyzed the five dialogic principles of religious websites accessed from mobile phones and also assessed their mobile readiness. Using the five principles of dialogic theory as a basis, do a general survey on the websites with elements of online religion. Second, the project analyzed the characteristics of Taiwanese participants for online religious activities. Grounded by social network analysis and text mining, this study comparatively explores the network structure, interaction pattern, and geographic distribution of users involved in communication networks of the folk religion in social websites and mobile sites. We studied the linkage preference of different religious groups. The difference among different religions and religious websites also be compared. We examined the reasons for the success of these websites, as well as reasons why young users accept new religious media. The outcome of the research will be useful for online religious service providers and non-profit organizations to manage social websites and internet marketing.

Keywords: content analysis, online religion, social network analysis, social websites

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Authors: Saeed Sayyad Hagh Shomar

Abstract:

Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

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Authors: Azadeh Mohajer Milani

Abstract:

Urbanization constitutes an irreversible global trend, presenting myriad challenges such as heightened energy consumption, pollution, congestion, and the depletion of natural resources. Today's urban landscapes have emerged as focal points for economic, social, and environmental challenges, underscoring the pressing need for sustainable development. This article delves into the realm of sustainable urban development, concentrating on the pivotal role played by integrated green spaces as an optimal solution to address environmental concerns within cities. The study utilizes Tehran as a case study. Our findings underscore the imperative of preserving and expanding green spaces in urban areas, coupled with the establishment of well-designed ecological networks, to enhance environmental quality and elevate the sustainability of cities. Notably, Tehran's urban green spaces exhibit a disjointed design, lacking a cohesive network to connect various patches and corridors, resulting in significant environmental impacts. The results emphasize the necessity of a balanced and proportional distribution of urban green spaces and the creation of a cohesive patch-corridor-matrix network tailored to the ecological and social needs of residents. This approach is crucial for fostering a more sustainable and livable urban environment for all species, with a specific focus on humans.

Keywords: ecology, sustainable urban development, sustainable landscape, urban green space network

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Authors: Huang Yong, Chen Qianting, Zhao Shurong

Abstract:

In order to identify the role and effect of Characteristic Towns as an important means to promote urban-rural integration, this paper uses Flow Theory and complex network analysis methods to jointly construct the identification path of urban-rural integration capabilities of Characteristic Towns. Take the National Characteristic Towns of Yunnan Province as the empirical objects to identify their role laws. The study found that in the implementation of the National Characteristic Town Project in Yunnan Province, (1) the population is more susceptible to the impact of the Characteristic Town Project than the technical elements, but the stability is poor; (2) The flow capacity of urban and rural technical elements is weak, and the quality of the enterprise cooperation network in general; (3) Compared with the batch of Characteristic Towns in 2016, its ability to promote urban-rural integration is higher in 2017; (4) The role of the Characteristic Town Project on urban-rural integration focuses on the improvement of the number of urban and rural flow elements. This paper analyzes the mode of the role of Characteristic Towns on urban-rural integration from the perspective of ‘flow,’ establishes a research paradigm for evaluating the role of Characteristic Towns in urban-rural integration capabilities, and builds a path for the application of Characteristic Towns to support the realization of urban-rural integration goals.

Keywords: characteristic town, urban-rural integration, flow theory, complex network analysis

Procedia PDF Downloads 140