Search results for: Radial Basis Function Network (RBFN)

Authors: Sung Hoon Jung

Abstract:

In this paper, we propose a selective mutation method for improving the performances of genetic algorithms. In selective mutation, individuals are first ranked and then additionally mutated one bit in a part of their strings which is selected corresponding to their ranks. This selective mutation helps genetic algorithms to fast approach the global optimum and to quickly escape local optima. This results in increasing the performances of genetic algorithms. We measured the effects of selective mutation with four function optimization problems. It was found from extensive experiments that the selective mutation can significantly enhance the performances of genetic algorithms.

Keywords: Genetic algorithm, selective mutation, function optimization

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Authors: Yahia Salah, Med Lassaad Kaddachi, Rached Tourki

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This paper presents the design, implementation and evaluation of a micro-network, or Network-on-Chip (NoC), based on a generic pipeline router architecture. The router is designed to efficiently support traffic generated by multimedia applications on embedded multi-core systems. It employs a simplest routing mechanism and implements the round-robin scheduling strategy to resolve output port contentions and minimize latency. A virtual channel flow control is applied to avoid the head-of-line blocking problem and enhance performance in the NoC. The hardware design of the router architecture has been implemented at the register transfer level; its functionality is evaluated in the case of the two dimensional Mesh/Torus topology, and performance results are derived from ModelSim simulator and Xilinx ISE 9.2i synthesis tool. An example of a multi-core image processing system utilizing the NoC structure has been implemented and validated to demonstrate the capability of the proposed micro-network architecture. To reduce complexity of the image compression and decompression architecture, the system use image processing algorithm based on classical discrete cosine transform with an efficient zonal processing approach. The experimental results have confirmed that both the proposed image compression scheme and NoC architecture can achieve a reasonable image quality with lower processing time.

Keywords: Generic Pipeline Network-on-Chip Router Architecture, JPEG Image Compression, FPGA Hardware Implementation, Performance Evaluation.

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Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

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Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: Wireless sensor network, node, application, monitoring, insecurity, environment.

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Authors: Ahmed Mohsen, Yoshinobu Kitamura, Katsuyuki Shimizu

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The improvement of irrigation systems in the Nile Delta is one of the most important attempts in Egypt to implement more effective irrigation technology by improving the existing irrigation networks. Demand delivery system in the existing irrigation network is using of mechanical gates structures to automatically divert water from one portion of an agricultural field to another in the desired amount and sequence. This paper discusses evaluating main irrigation networks system under the government managed before and after improvement systems in the Nile Delta. The overall results indicate that policy of using the demand delivery concept through irrigation networks is successful by improving water delivery performance among them than the rotation delivery concept that used before. It is provided fair share of water delivery among irrigation districts and available water in the end of irrigation network, although this system located in an end of irrigation networks in the Nile Delta.

Keywords: Automation system, Irrigation district, Rotation system, Water delivery performance

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Authors: Jafar Biazar, Behzad Ghanbari

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In this paper, we are concerned with the further study for system of nonlinear equations. Since systems with inaccurate function values or problems with high computational cost arise frequently in science and engineering, recently such systems have attracted researcher-s interest. In this work we present a new method which is independent of function evolutions and has a quadratic convergence. This method can be viewed as a extension of some recent methods for solving mentioned systems of nonlinear equations. Numerical results of applying this method to some test problems show the efficiently and reliability of method.

Keywords: System of nonlinear equations.

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Authors: Takashi Sakai, Shinsaku Kikuta, Jun-ichi Koyama

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Using a texture database, a statistical estimation of spring-back was conducted in this study on the basis of statistical analysis. Both spring-back in bending deformation and experimental data related to the crystal orientation show significant dispersion. Therefore, a probabilistic statistical approach was established for the proper quantification of these values. Correlation was examined among the parameters F(x) of spring-back, F(x) of the buildup fraction to three orientations after 92° bending, and F(x) at an as-received part on the basis of the three-parameter Weibull distribution. Consequent spring-back estimation using a texture database yielded excellent estimates compared with experimental values.

Keywords: Bending, Spring-back, Database, Crystallographic Orientation, Texture, SEM-EBSD, Weibull distribution, Statistical analysis.

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Authors: H. F. A. Abdul Ghani, R. R. Porle

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Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.  

Keywords: Feed-Forward Neural Network, FFNN, Malay speech recognition, Mel Frequency Cepstrum Coefficient, MFCC, speech-to-text.

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Authors: Md. Armin Islam, Les Dallin, Mark Boland, W. J. Zhang

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This paper reports a study on the optimal magnetic design of a compact quadrupole electromagnet for the Canadian Light Source (CLS 2.0). The nature of the design is to determine a quadrupole with low relative higher order harmonics and better field quality. The design problem was formulated as an optimization model, in which the objective function is the higher order harmonics (multipole errors) and the variable to be optimized is the material distribution on the pole. The higher order harmonics arose in the quadrupole due to truncating the ideal hyperbola at a certain point to make the pole. In this project, the arisen harmonics have been optimized both transversely and longitudinally by adjusting material on the poles in a controlled way. For optimization, finite element analysis (FEA) has been conducted. A better higher order harmonics amplitudes and field quality have been achieved through the optimization. On the basis of the optimized magnetic design, electrical and cooling calculation has been performed for the magnet.

Keywords: Drift, electrical, and cooling calculation, integrated field, higher order harmonics (multipole errors), magnetic field gradient, quadrupole.

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Authors: Vasileios Anastopoulos

Abstract:

Cyber threat intelligence assists organisations in understanding the threats they face and helps them make educated decisions on preparing their defences. Sharing of threat intelligence and threat information is increasingly leveraged by organisations and enterprises, and various software solutions are already available, with the open-source malware information sharing platform (MISP) being a popular one. In this work, a methodology for the production of cyber threat intelligence using the threat information stored in MISP is proposed. The methodology leverages the discipline of social network analysis and the diamond model, a model used for intrusion analysis, to produce cyber threat intelligence. The workings of the proposed methodology are demonstrated with a case study on a production MISP instance of a real organisation. The paper concludes with a discussion on the proposed methodology and possible directions for further research.

Keywords: Cyber threat intelligence, diamond model, malware information sharing platform, social network analysis.

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Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna

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Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.

Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).

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Authors: Bhavana Prakash Shrivastava, Kavita Khare

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This paper presents a synthesis and simulation of proposed enhanced buffer. The design provides advantages of both buffer and bufferless network for that two cross bar switches are used. The concept of virtual channel (VC) is eliminated from the previous design by using an efficient flow-control scheme that uses the storage already present in pipelined channels in place of explicit input VCBs. This can be addressed by providing enhanced buffers on the bufferless link and creating two virtual networks. With this approach, VCBs act as distributed FIFO buffers. Without VCBs or VCs, deadlock prevention is achieved by duplicating physical channels. An enhanced buffer provides a function of hand shaking by providing a ready valid handshake signal and two bit storage. Through this design the power is reduced to 15.65% and delay is reduced to 97.88% with respect to virtual channel router.

Keywords: Enhanced buffer, Gate delay, NOC, VCs, VCB.

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Authors: Charmaine du Plessis

Abstract:

The brand storytelling themes and emotional appeals of three major global brands were analysed by means of visual rhetoric in a digital environment focusing on the ethos communication technique. A well-known framework of five basic brand personality dimensions was used to delineate the analysis. Brand storytelling as a branding technique is becoming increasingly popular, especially since all brands can tell a story to connect and engage with consumers on an emotional level. Social media have changed the way in which brand stories are shared with online consumers, while social video networking sites in particular create an opportunity to share brand stories with a much greater target audience through electronic word of mouth (eWOM). The findings not only confirm three dimensions in the traditional brand personality framework, but can also serve as a heuristic tool for other researchers analyzing brand storytelling in a social video sharing network environment.

Keywords: Communication technique, visual rhetoric, social video sharing network, brand storytelling.

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

Abstract:

As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: Biological pathway, gene identification, object detection, Siamese network, ResNet.

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Authors: Yong-Gyu Lee, Jin-Hee Park, Gilwon Yoon

Abstract:

In this study, we introduced a communication system where human body was used as medium through which data were transferred. Multiple biosignal sensing units were attached to a subject and wireless personal area network was formed. Data of the sensing units were shared among them. We used wideband pulse communication that was simple, low-power consuming and high data rated. Each unit functioned as independent communication device or node. A method of channel search and communication among the modes was developed. A protocol of carrier sense multiple access/collision detect was implemented in order to avoid data collision or interferences. Biosignal sensing units should be located at different locations due to the nature of biosignal origin. Our research provided a flexibility of collecting data without using electrical wires. More non-constrained measurement was accomplished which was more suitable for u-Health monitoring.

Keywords: Human body communication, wideband pulse communication, personal area network, biosignal.

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Authors: Dragan Kljajic, Nikola Djuric, Karolina Kasas-Lazetic, Danka Antic

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Wireless communications have been expanded very fast in recent decades. This technology relies on an extensive network of base stations and antennas, using radio frequency signals to transmit information. Devices that use wireless communication, while offering various services, basically act as sources of non-ionizing electromagnetic fields (EMF). Such devices are permanently present in human vicinity and almost constantly radiate, causing EMF pollution of the environment. This fact has initiated development of modern systems for observation of the EMF pollution, as well as for risk assessment. This paper presents the Serbian electromagnetic field monitoring network – SEMONT, designed for automated, remote and continuous broadband monitoring of EMF in the environment. Measurement results of the SEMONT monitoring at one of the test locations, within the main campus of the University of Novi Sad, are presented and discussed, along with corresponding exposure assessment of the general population, regarding the Serbian legislation.

Keywords: EMF monitoring, exposure assessment, sensor nodes, wireless network.

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco, I. Garcia-Moral

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Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure.

Keywords: Robust stability, neural network control, unstructured uncertainty, singular values, distillation column.

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: Wei Zhang, Xin Zhao, Yi-Fan Zhu, Xin-Jian Zhang

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Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.

Keywords: admissible support vector kernel, reproducing kernel, reproducing kernel Hilbert space, Green function, support vectorregression

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Authors: P. S. Prakash, S. Selvan

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QoS Routing aims to find paths between senders and receivers satisfying the QoS requirements of the application which efficiently using the network resources and underlying routing algorithm to be able to find low-cost paths that satisfy given QoS constraints. The problem of finding least-cost routing is known to be NP-hard or complete and some algorithms have been proposed to find a near optimal solution. But these heuristics or algorithms either impose relationships among the link metrics to reduce the complexity of the problem which may limit the general applicability of the heuristic, or are too costly in terms of execution time to be applicable to large networks. In this paper, we concentrate an algorithm that finds a near-optimal solution fast and we named this algorithm as optimized Delay Constrained Routing (ODCR), which uses an adaptive path weight function together with an additional constraint imposed on the path cost, to restrict search space and hence ODCR finds near optimal solution in much quicker time.

Keywords: QoS, Delay, Routing, Optimization.

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Authors: Khin Thida Latt, Mineo Kaneko, Yoichi Shinoda

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In Partitioned Optical Passive Stars POPS network,nodes and couplers become free after slot to slot in some computation.It is necessary to efficiently utilize free couplers and nodes to be cost effective. Improving parallelism, we present the fast data summation algorithm for multiple problem spaces on P OP S(g, g) with smaller number of nodes for the case of d =n = g. For the case of d >n > g, we simulate the calculation of large number of data items dedicated to larger system with many nodes on smaller system with smaller number of nodes. The algorithm is faster than the best know algorithm and using smaller number of nodes and groups make the system low cost and practical.

Keywords: Partitioned optical passive stars network, parallelcomputing, optical computing, data sum

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Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

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SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

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Authors: T. T. Manikandan, Rajeev Sukumaran

Abstract:

For maintaining the biodiversity of many ecosystems the existence of coral reefs play a vital role. But due to many factors such as pollution and coral mining, coral reefs are dying day by day. One way to protect the coral reefs is to farm them in a carefully monitored underwater environment and restore it in place of dead corals. For successful farming of corals in coral farms, different parameters of the water in the farming area need to be monitored and maintained at optimal level. Sensing underwater parameters using wireless sensor nodes is an effective way for precise and continuous monitoring in a highly dynamic environment like oceans. Here the sensed information is of varying importance and it needs to be provided with desired Quality of Service(QoS) guarantees in delivering the information to offshore monitoring centers. The main interest of this research is Stochastic Network Calculus (SNC) based modeling of network layer design for underwater wireless sensor communication. The model proposed in this research enforces differentiation of service in underwater wireless sensor communication with the help of buffer sizing and link scheduling. The delay and backlog bounds for such differentiated services are analytically derived using stochastic network calculus.

Keywords: Underwater Coral Farms, SNC, differentiated service, delay bound, backlog bound.

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Authors: K. G. Anilkumar, T. Tanprasert

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This paper presents a subjective job scheduler based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy alignment procedure in order formulates a real-life situation. The BPNN estimates critical values of jobs based on the given subjective criteria. The scheduler is formulated in such a way that, at each time period, the most critical job is selected from the job queue and is transferred into a single machine before the next periodic job arrives. If the selected job is one of the oldest jobs in the queue and its deadline is less than that of the arrival time of the current job, then there is an update of the deadline of the job is assigned in order to prevent the critical job from its elimination. The proposed satisfiability criteria indicates that the satisfaction of the scheduler with respect to performance of the BPNN, validity of the jobs and the feasibility of the scheduler.

Keywords: Backpropagation algorithm, Critical value, Greedy alignment procedure, Neural network, Subjective criteria, Satisfiability.

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Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva

Abstract:

The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.

Keywords: Automatic cell counting, neural network, region growing, Sanger net.

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Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun

Abstract:

In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Keywords: Grey relational degree, multiple linear regression, membership function, nonlinear programming.

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Authors: Meenakshi Bansal, Iqbal Singh, Parvinder S. Sandhu

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In over deployed sensor networks, one approach to Conserve energy is to keep only a small subset of sensors active at Any instant. For the coverage problems, the monitoring area in a set of points that require sensing, called demand points, and consider that the node coverage area is a circle of range R, where R is the sensing range, If the Distance between a demand point and a sensor node is less than R, the node is able to cover this point. We consider a wireless sensor network consisting of a set of sensors deployed randomly. A point in the monitored area is covered if it is within the sensing range of a sensor. In some applications, when the network is sufficiently dense, area coverage can be approximated by guaranteeing point coverage. In this case, all the points of wireless devices could be used to represent the whole area, and the working sensors are supposed to cover all the sensors. We also introduce Hybrid Algorithm and challenges related to coverage in sensor networks.

Keywords: Wireless sensor networks, network coverage, Energy conservation, Hybrid Algorithms.

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Authors: Jie Zhao, Meng Su

Abstract:

Image recognition enables machine-like robotics to understand a scene and plays an important role in computer vision applications. Computer vision platforms as physical infrastructure, supporting Neural Networks for image recognition, are deterministic to leverage the performance of different Neural Networks. In this paper, three different computer vision platforms – edge AI (Jetson Nano, with 4GB), a standalone laptop (with RTX 3000s, using CUDA), and a web-based device (Google Colab, using GPU) are investigated. In the case study, four prominent neural network architectures (including AlexNet, VGG16, GoogleNet, and ResNet (34/50)), are deployed. By using public ImageNets (Cifar-10), our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: AlexNet, VGG, GoogleNet, ResNet, ImageNet, Cifar-10, Edge AI, Jetson Nano, CUDA, GPU.

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Authors: S. Y. Choi, Y. H. Na, J. H. Kim

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In this work, thermoelastic damping effect on the hemi- spherical shells is investigated. The material is selected silicon, and heat conduction equation for thermal flow is solved to obtain the temperature profile in which bending approximation with inextensional assumption of the model. Using the temperature profile, eigen-value analysis is performed to get the natural frequencies of hemispherical shells. Effects of mode numbers, radii and radial thicknesses of the model on the natural frequencies are analyzed in detail. Furthermore, the quality factor (Q-factor) is defined, and discussed for the ring and hemispherical shell.

Keywords: Thermoelastic damping, hemispherical shell, quality factor

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Authors: A. Derardja, L. Baroura, M. Brioua

Abstract:

The nanotechnology based on epitaxial systems includes single or arranged misfit dislocations. In general, whatever is the type of dislocation or the geometry of the array formed by the dislocations; it is important for experimental studies to know exactly the stress distribution for which there is no analytical expression [1, 2]. This work, using a numerical analysis, deals with relaxation of epitaxial layers having at their interface a periodic network of edge misfit dislocations. The stress distribution is estimated by using isotropic elasticity. The results show that the thickness of the two sheets is a crucial parameter in the stress distributions and then in the profile of the two sheets. A comparative study between the case of single dislocation and the case of parallel network shows that the layers relaxed better when the interface is covered by a parallel arrangement of misfit. Consequently, a single dislocation at the interface produces an important stress field which can be reduced by inserting a parallel network of dislocations with suitable periodicity.

Keywords: Parallel array of misfit, interface, isotropic elasticity, single crystalline substrates, coherent interface

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Authors: Anirudh Sunil Warrier, Saba Al-Rubaye, Dimitrios Panagiotakopoulos, Gokhan Inalhan, Antonios Tsourdos

Abstract:

The demand for increased data transfer rate and network traffic capacity has given rise to the concept of heterogeneous networks. Heterogeneous networks are wireless networks, consisting of devices using different underlying radio access technologies (RAT). For Unmanned Aerial Vehicles (UAVs) this enhanced data rate and network capacity are even more critical especially in their applications of medicine, delivery missions and military. In an urban heterogeneous network environment, the UAVs must be able switch seamlessly from one base station (BS) to another for maintaining a reliable link. Therefore, seamless handover in such urban environments has become a major challenge. In this paper, a scheme to achieve seamless handover is developed, an algorithm based on Received Signal Strength (RSS) criterion for network selection is used and Entropy Weighted Method (EWM) is implemented for decision making. Seamless handover using EWM decision-making is demonstrated successfully for a UAV moving across fifth generation (5G) and long-term evolution (LTE) networks via a simulation level analysis. Thus, a solution for UAV-5G communication, specifically the mobility challenge in heterogeneous networks is solved and this work could act as step forward in making UAV-5G architecture integration a possibility.

Keywords: Air to ground, A2G, fifth generation, 5G, handover, mobility, unmanned aerial vehicle, UAV, urban environments.

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