Search results for: wireless sensor network (wsn)

Authors: Mehrnaz Aminifar

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The relation between textural parameters and casein network on release of aromatic compounds was investigated over 90-days of ripening. Low DE maltodextrin and WPI were used to modify the textural properties of low fat brined cheese. Hardness, brittleness and compaction of casein network were affected by addition of maltodextrin and WPI. Textural properties and aroma release from cheese texture were affected by interaction of WPI protein-cheese protein and maltodexterin-cheese protein.

Keywords: aroma release, brined cheese, maltodexterin, WPI

Procedia PDF Downloads 338

Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

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In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: personnel evaluation, pairwise comparison, analytic network process (ANP), two-ways

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Danladi Ali, Onah Festus Iloabuchi

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In this paper, GSM signal strength was measured in order to detect the type of the signal fading phenomenon using one-dimensional multilevel wavelet residual method and neural network clustering to determine the average GSM signal strength received in the study area. The wavelet residual method predicted that the GSM signal experienced slow fading and attenuated with MSE of 3.875dB. The neural network clustering revealed that mostly -75dB, -85dB and -95dB were received. This means that the signal strength received in the study is a weak signal.

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment

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Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

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On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

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Authors: Jun-Ho Park, Kwang-Woo Nam, Seung-Mo Hong, Tae-Heon Moon, Sang-Ho Lee, Youn-Taik Leem

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The aim of this study was to build ‘Ubi-Net’, a decision-making support system for systematic establishment in U-City planning. We have experienced various urban problems caused by high-density development and population concentrations in established urban areas. To address these problems, a U-Service contributes to the alleviation of urban problems by providing real-time information to citizens through network connections and related information. However, technology, devices, and information for consumers are required for systematic U-Service planning in towns and cities where there are many difficulties in this regard, and a lack of reference systems. Thus, this study suggests methods to support the establishment of sustainable planning by providing comprehensive information including IT technology, devices, news, and social networking services(SNS) to U-City planners through intelligent searches. In this study, we targeted Smart U-Parking Planning to solve parking problems in an ‘old’ city. Through this study, we sought to contribute to supporting advances in U-Space and the alleviation of urban problems.

Keywords: desigin and decision support system, smart u-parking planning, social network analysis, urban engineering

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

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

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

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Authors: H. M. Fayzan Shakir, Khadija Zubair, Tingkai Zhao

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Electromagnetic (EM) waves are being used widely now a days. Cell phone signals, WIFI signals, wireless telecommunications etc everything uses EM waves which then create EM pollution. EM pollution can cause serious effects on both human health and nearby electronic devices. EM waves have electric and magnetic components that disturb the flow of charged particles in both human nervous system and electronic devices. The shielding of both humans and electronic devices are a prime concern today. EM waves can cause headaches, anxiety, suicide and depression, nausea, fatigue and loss of libido in humans and malfunctioning in electronic devices. Polyaniline (PANI) and polypyrrole (PPY) were successfully synthesized using chemical polymerizing using ammonium persulfate and DBSNa as oxidant respectively. Barium ferrites (BaFe) were also prepared using co-precipitation method and calcinated at 10500C for 8h. Nanocomposite thin films with various combinations and compositions of Polyvinylchloride, PANI, PPY and BaFe were prepared. X-ray diffraction technique was first used to confirm the successful fabrication of all nano fillers and particle size analyzer to measure the exact size and scanning electron microscopy is used for the shape. According to Electromagnetic Interference theory, electrical conductivity is the prime property required for the Electromagnetic Interference shielding. 4-probe technique is then used to evaluate DC conductivity of all samples. Samples with high concentration of PPY and PANI exhibit remarkable increased electrical conductivity due to fabrication of interconnected network structure inside the Polyvinylchloride matrix that is also confirmed by SEM analysis. Less than 1% transmission was observed in whole NIR region (700 nm – 2500 nm). Also, less than -80 dB Electromagnetic Interference shielding effectiveness was observed in microwave region (0.1 GHz to 20 GHz).

Keywords: nanocomposites, polymers, EMI shielding, thermal imaging

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

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

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

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Authors: Udayan Patankar, Shashwati Bhagat, Vilas Nitneware, Ants Koel

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An ISM band power amplifier is a type of electronic amplifier used to convert a low-power radio-frequency signal into a larger signal of significant power, typically used for driving the antenna of a transmitter. Due to drastic changes in telecommunication generations may lead to the requirements of improvements. Rapid changes in communication lead to the wide implementation of WLAN technology for its excellent characteristics, such as high transmission speed, long communication distance, and high reliability. Many applications such as WLAN, Bluetooth, and ZigBee, etc. were evolved with 2.4GHz to 5 GHz ISM Band, in which the power amplifier (PA) is a key building block of RF transmitters. There are many manufacturing processes available to manufacture a power amplifier for desired power output, but the major problem they have faced is about the power it consumed for its proper working, as many of them are fabricated on the GaN HEMT, Bi COMS process. In this paper we present a CMOS Base two stage cascode design of power amplifier working on 2.4GHz ISM frequency band. To lower the costs and allow full integration of a complete System-on-Chip (SoC) we have chosen 0.13µm low power CMOS technology for design. While designing a power amplifier, it is a real task to achieve higher power efficiency with minimum resources. This design showcase the Multi biased Cascode methodology to implement a two-stage CMOS power amplifier using ADS and LTSpice simulating tool. Main source is maximum of 2.4V which is internally distributed into different biasing point VB driving and VB driven as required for distinct stages of two stage RF power amplifier. It shows maximum power added efficiency near about 70.195% whereas its Power added efficiency calculated at 1 dB compression point is 44.669 %. Biased MOSFET is used to reduce total dc current as this circuit is designed for different wireless applications comes under 2.4GHz ISM Band.

Keywords: RFIC, PAE, RF CMOS, impedance matching

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Authors: Bingquan Shen

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

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

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Authors: Hala Zaghloul, Taymoor Nazmy

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

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

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Authors: Samia Dardouri, Ridha Bouallegue

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

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

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Authors: Chothmal

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

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

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Authors: Senay Yitmen

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

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

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

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

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

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Authors: Daniel Fulus Fom, Gau Patrick Damulak

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

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

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Authors: Kais Manai

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

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

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Authors: Mikheil Kalmakhelidze

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

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

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Authors: Nazmul Shahadat, Anthony S. Maida

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

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

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Authors: O. S. Ebrahim, K. O. Shawky, M. O. S. Ebrahim, P. K. Jain

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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). It was illustrated that changing the connection of the stator windings from delta to star at no load could achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: ANN, ESM, IM, star/delta switch, supervisory control, FT, reliability, power quality

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

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

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

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Authors: Yu Song, Yuefei Jin

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

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

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Authors: Pavan Shah

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

Keywords: virtualization, visualization, network driver, operating system

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Authors: Kalyani Kulkarni, Bharat Chaudhari

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

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

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

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

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

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Authors: Wahab Ali Shah, Junjia He

Abstract:

Transferring electrical power without any wiring has been a dream since late 19^th century. There were some advances in this area as to know more about microwave systems. However, this subject has recently become very attractive due to their practiScal systems. There are low power applications such as charging the batteries of contactless tooth brushes or implanted devices, and higher power applications such as charging the batteries of electrical automobiles or buses. In the first group of applications operating frequencies are in microwave range while the frequency is lower in high power applications. In the latter, the concept is also called inductive power transfer. The aim of the paper is to have an overview of the inductive power transfer for electrical vehicles with a special concentration on coil design and power converter simulation for static charging. Coil design is very important for an efficient and safe power transfer. Coil design is one of the most critical tasks. Power converters are used in both side of the system. The converter on the primary side is used to generate a high frequency voltage to excite the primary coil. The purpose of the converter in the secondary is to rectify the voltage transferred from the primary to charge the battery. In this paper, an inductive power transfer system is studied. Inductive power transfer is a promising technology with several possible applications. Operation principles of these systems are explained, and components of the system are described. Finally, a single phase 2 kW system was simulated and results were presented. The work presented in this paper is just an introduction to the concept. A reformed compensation network based on traditional inductor-capacitor-inductor (LCL) topology is proposed to realize robust reaction to large coupling variation that is common in dynamic wireless charging application. In the future, this type compensation should be studied. Also, comparison of different compensation topologies should be done for the same power level.

Keywords: coil design, contactless charging, electrical automobiles, inductive power transfer, operating frequency

Procedia PDF Downloads 237

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

Abstract:

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

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

Procedia PDF Downloads 371