Search results for: Conventional Neural Networks

Authors: R. Arulmurugan, P. Sengottuvelan

Abstract:

Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.

Keywords: Object Detection, Cross-point Searching, Wavelet Neural Network, Object Determination, Gabor Wavelet Transform, Tagged Grid Matching.

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Authors: M. Zeydan, G. Toğa

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This study deals with a multi-criteria optimization problem which has been transformed into a single objective optimization problem using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Grey Relational Analyses (GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques which can be used for solving multi-criteria optimization problem. There have been two main purposes of this research as follows. 1. To determine optimum and robust fiber dyeing process conditions by using RSM and ANN based on GRA, 2. To obtain the best suitable model by comparing models developed by different methodologies. The design variables for fiber dyeing process in textile are temperature, time, softener, anti-static, material quantity, pH, retarder, and dispergator. The quality characteristics to be evaluated are nominal color consistency of fiber, maximum strength of fiber, minimum color of dyeing solution. GRA-RSM with exact level value, GRA-RSM with interval level value and GRA-ANN models were compared based on GRA output value and MSE (Mean Square Error) performance measurement of outputs with each other. As a result, GRA-ANN with interval value model seems to be suitable reducing the variation of dyeing process for GRA output value of the model.

Keywords: Artificial Neural Network, Grey Relational Analysis, Optimization, Response Surface Methodology

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Authors: Samit Ari, Goutam Saha

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Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

Keywords: ANN, Classification of heart diseases, murmurs, optimization, Phonocardiogram, QRcp, SVD.

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Authors: Ahmad Sobri bin Hashim, Wan Fatimah Bt. Wan Ahmad, Rohiza Bt. Ahmad

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Mobile Learning (M-Learning) is a new technology which is to enhance current learning practices and activities for all people especially students and academic practitioners UTP is currently, implemented two types of learning styles which are conventional and electronic learning. In order to improve current learning approaches, it is necessary for UTP to implement m-learning in UTP. This paper presents a study on the students- perceptions on mobile utilization in the learning practices in UTP. Besides, this paper also presents a survey that was conducted among 82 students from System Analysis and Design (SAD) course in UTP. The survey includes basic information of mobile devices that have been used by the students, opinions on current learning practices and also the opinions regarding the m-learning implementation in the current learning practices especially in SAD course. Based on the results of the survey, majority of the students are using the mobile devices that can support m-learning environment. Other than that, students also agreed that current learning practices are ineffective and they believe that m-learning utilization can improve the effectiveness of current learning practices.

Keywords: m-learning, conventional learning, electronic learning, mobile devices.

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Authors: Alluru Gopala Krishna, Thella Babu Rao

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In machining, there is always a problem with heat generation and friction produced during the process as they consequently affect tool wear and surface finish. An instant heat transfer mechanism could protect the cutting tool edge and enhance the tool life by cooling the cutting edge of the tool. In the present work, carbon nanotube (CNT) based nano-cutting fluid is proposed for machining a hard-to-cut material. Tool wear and surface roughness are considered for the evaluation of the nano-cutting fluid in turning process. The performance of nanocoolant is assessed against the conventional coolant and dry machining conditions and it is observed that the proposed nanocoolant has produced better performance than the conventional coolant.

Keywords: CNT based nanocoolant, turning, tool wear, surface roughness.

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Authors: Salvatore Pinna

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The growth of organic farming practices in the last few decades is continuing to stimulate the international debate about this alternative food market. As a part of a PhD project research about embeddedness in Alternative Food Networks (AFNs), this paper focuses on the promotional aspects of organic farms websites from the Madrid region. As a theoretical tool, some knowledge categories drawn on the geographic studies literature are used to classify the many ideas expressed in the web pages. By analysing texts and pictures of 30 websites, the study aims to question how and to what extent actors from organic world communicate to the potential customers their personal beliefs about farming practices, products qualities, and ecological and social benefits. Moreover, the paper raises the question of whether organic farming laws and regulations lack of completeness about the social and cultural aspects of food.

Keywords: Alternative food networks, de-commoditisation, organic farming, Madrid, reconnection of food.

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Authors: A. Alsaadi, B. Gholami

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An effective approach for unbalanced three-phase distribution power flow solutions is proposed in this paper. The special topological characteristics of distribution networks have been fully utilized to make the direct solution possible. Two matrices–the bus-injection to branch-current matrix and the branch-current to busvoltage matrix– and a simple matrix multiplication are used to obtain power flow solutions. Due to the distinctive solution techniques of the proposed method, the time-consuming LU decomposition and forward/backward substitution of the Jacobian matrix or admittance matrix required in the traditional power flow methods are no longer necessary. Therefore, the proposed method is robust and time-efficient. Test results demonstrate the validity of the proposed method. The proposed method shows great potential to be used in distribution automation applications.

Keywords: Distribution power flow, distribution automation system, radial network, unbalanced networks.

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Authors: Evgeniy Burlutskiy

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The paper presents a one-dimensional transient mathematical model of compressible thermal multi-component gas mixture flows in pipes. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved. Thermo-physical properties of multi-component gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas mixture viscosity is calculated on the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical analysis on rapid decompression in conventional dry gases is performed by using the proposed mathematical model. The model is validated on measured values of the decompression wave speed in dry natural gas mixtures. All predictions show excellent agreement with the experimental data at high and low pressure. The presented model predicts the decompression in dry natural gas mixtures much better than GASDECOM and OLGA codes, which are the most frequently-used codes in oil and gas pipeline transport service.

Keywords: Mathematical model, Rapid Gas Decompression

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Authors: Hung-Pei Hsu, Jyi-Tsong Lin, Po-Hsieh Lin, Cheng-Hsien Chang, Ming-Tsung Shih, Chan-Hsiang Chang, Shih-Chuan Tseng, Min-Yan Lin, Shih-Wen Hsu

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In this paper, we propose a novel metal oxide semiconductor field effect transistor with L-shaped channel structure (LMOS), and several type of L-shaped structures are also designed, studied and compared with the conventional MOSFET device for the same average gate length (Lavg). The proposed device electrical characteristics are analyzed and evaluated by three dimension (3-D) ISE-TCAD simulator. It can be confirmed that the LMOS devices have higher on-state drain current and both lower drain-induced barrier lowering (DIBL) and subthreshold swing (S.S.) than its conventional counterpart has. In addition, the transconductance and voltage gain properties of the LMOS are also improved.

Keywords: Average gate length (Lavg), drain-induced barrier lowering (DIBL), L-shaped channel MOSFET (LMOS), subthreshold swing (S.S.).

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Authors: M. Gunasekaran, K. Premalatha

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Privacy and Security have emerged as an important research issue in Mobile Ad Hoc Networks (MANET) due to its unique nature such as scarce of resources and absence of centralized authority. There are number of protocols have been proposed to provide privacy and security for data communication in an adverse environment, but those protocols are compromised in many ways by the attackers. The concept of anonymity (in terms of unlinkability and unobservability) and pseudonymity has been introduced in this paper to ensure privacy and security. In this paper, a Secure Onion Throat (SOT) protocol is proposed to provide complete anonymity in an adverse environment. The SOT protocol is designed based on the combination of group signature and onion routing with ID-based encryption for route discovery. The security analysis demonstrates the performance of SOT protocol against all categories of attacks. The simulation results ensure the necessity and importance of the proposed SOT protocol in achieving such anonymity.

Keywords: Routing, anonymity, privacy, security and MANET.

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Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari

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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.

Keywords: Water pipe networks, maintenance management, reliability analysis, optimum maintenance plan.

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Authors: Rameshwar Kawitkar

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With the exponentially increasing demand for wireless communications the capacity of current cellular systems will soon become incapable of handling the growing traffic. Since radio frequencies are diminishing natural resources, there seems to be a fundamental barrier to further capacity increase. The solution can be found in smart antenna systems. Smart or adaptive antenna arrays consist of an array of antenna elements with signal processing capability, that optimize the radiation and reception of a desired signal, dynamically. Smart antennas can place nulls in the direction of interferers via adaptive updating of weights linked to each antenna element. They thus cancel out most of the co-channel interference resulting in better quality of reception and lower dropped calls. Smart antennas can also track the user within a cell via direction of arrival algorithms. This implies that they are more advantageous than other antenna systems. This paper focuses on few issues about the smart antennas in mobile radio networks.

Keywords: Smart/Adaptive Antenna, Multipath fading, Beamforming, Radio propagation.

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Authors: Lija Dukalska, Sandra Muizniece-Brasava, Irisa Murniece, Ilona Dabina-Bicka, Emils Kozlinskis, Svetlana Sarvi

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Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Soft cheese Kleo produced in Latvia was packed in a biodegradable PLA without barrierproperties and VC999 BioPack lidding film PLA, coated with a barrier of pure silicon oxide (SiOx) and in combination with modified atmosphere (MAP) the influence on the shelf life was investigated and compared with some conventional (OPP, PE/PA, PE/OPA and Multibarrier 60) polymer film impact. Modified atmosphere consisted of carbon dioxide CO2 (E 290) 30% and nitrogen N2 (E 941) 70%. The analyzable samples were stored at the temperature of +4.0±0.5 °C up to 32 days- and analyzed before packaging and in the 0, 5th, 11th, 15th, 18th, 22nd, 25th, 29th and 32nd day of storage. The shelf life was extended along to 32 days, good outside appearance and lactic acid aroma was observed.

Keywords: Soft cheese, modified atmosphere, conventional andbiodegradable PLA film, shelf life

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: Opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: Ramaswamy Palaniappan, Nai-Jen Huan

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Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.

Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.

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Authors: Susmi Routray, A. M. Sherry, B. V. R. Reddy

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Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.

Keywords: Asynchronous Transfer Mode(ATM), GeneticAlgorithm(GA), Tabu Search(TS).

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Authors: Bang Young Kim, Sang Hoon Park, Chul Gyu Song

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A conventional optical coherence tomography (OCT) system has limited imaging depth, which is 1-2 mm, and suffers unwanted noise such as speckle noise. The motorized-stage-based OCT system, using a common-path Fourier-domain optical coherence tomography (CP-FD-OCT) configuration, provides enhanced imaging depth and less noise so that we can overcome these limitations. Using this OCT systems, OCT images were obtained from an onion, and their subsurface structure was observed. As a result, the images obtained using the developed motorized-stage-based system showed enhanced imaging depth than the conventional system, since it is real-time accurate depth tracking. Consequently, the developed CP-FD-OCT systems and algorithms have good potential for the further development of endoscopic OCT for microsurgery.

Keywords: Common-path OCT, FD-OCT, OCT, Tracking algorithm.

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Authors: Wipada Chiawchan

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This study found that most corporate personnel are using social media to communicate with colleagues to make the process of working more efficient. Complete satisfaction occurred on the use of security within the University’s computer network. The social network usage for communication, collaboration, entertainment and demonstrating concerns accounted for fifty percent of variance to predict interpersonal relationships of corporate personnel. This evaluation on the effectiveness of social networking involved 213 corporate personnel’s. The data was collected by questionnaires. This data was analyzed by using percentage, mean, and standard deviation. The results from the analysis and the effectiveness of using online social networks were derived from the attitude of private users and safety data within the security system. The results showed that the effectiveness on the use of an online social network for corporate personnel of Suan Sunandha Rajabhat University was specifically at a good level, and the overall effects of each aspect was (Ẋ=3.11).

Keywords: Behaviors, Social Media, Social Network.

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Authors: K. Kasiri, M. J. Dehghani

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In this paper we propose a blind algorithm for peakto- average power ratio (PAPR) reduction in OFDM systems, based on selected mapping (SLM) algorithm as a distortionless method. The main drawback of the conventional SLM technique is the need for transmission of several side information bits, for each data block, which results in loss in data rate transmission. In the proposed method some special number of carriers in the OFDM frame is reserved to be rotated with one of the possible phases according to the number of phase sequence blocks in SLM algorithm. Reserving some limited number of carriers wont effect the reduction in PAPR of OFDM signal. Simulation results show using ML criteria at the receiver will lead to the same system-performance as the conventional SLM algorithm, while there is no need to send any side information to the receiver.

Keywords: Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), Selected Mapping(SLM), Blind SLM (BSLM).

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Authors: Jae Moon Lee

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Most of researches for conventional simulations were studied focusing on flocks with a single species. While there exist the flocking behaviors with a single species in nature, the flocking behaviors are frequently observed with multi-species. This paper studies on the flocking simulation for heterogeneous agents. In order to simulate the flocks for heterogeneous agents, the conventional method uses the identifier of flock, while the proposed method defines the feature vector of agent and uses the similarity between agents by comparing with those feature vectors. Based on the similarity, the paper proposed the attractive force and repulsive force and then executed the simulation by applying two forces. The results of simulation showed that flock formation with heterogeneous agents is very natural in both cases. In addition, it showed that unlike the existing method, the proposed method can not only control the density of the flocks, but also be possible for two different groups of agents to flock close to each other if they have a high similarity.

Keywords: Flocking behavior, heterogeneous agents, similarity, simulation

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Authors: Colette Malyack, Pius Egbelu

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Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.

Keywords: Network planning, Last Mile Delivery, LMD, omnichannel delivery network, omnichannel logistics.

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Authors: Ahmad Anzaar, Husain Shahnawaz, Chand Mukesh, S. C. Gupta, R. Gowri, H. L. Mandoria

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Due to insufficient frequency band and tremendous growth of the mobile users, complex computation is needed for the use of resources. Long distance communication began with the introduction of telegraphs and simple coded pulses, which were used to transmit short messages. Since then numerous advances have rendered reliable transfer of information both easier and quicker. Wireless network refers to any type of computer network that is wireless, and is commonly associated with a telecommunications network whose interconnections between nodes is implemented without the use of wires. Wireless network can be broadly categorized in infrastructure network and infrastructure less network. Infrastructure network is one in which we have a base station to serve the mobile users and in the infrastructure less network is one in which no infrastructure is available to serve the mobile users this kind of networks are also known as mobile Adhoc networks. In this paper we have simulated the result for different scenarios with protocols like AODV and DSR; we simulated the result for throughput, delay and receiving traffic in the given scenario.

Keywords: Adhoc network, AODV, DSR. mobility.

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Authors: Pavel Dostrašil, Petr Jirásko

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The paper deals with the kinematics and automated calculation of intermittent mechanisms with radial cams. Currently, electronic cams are increasingly applied in the drives of working link mechanisms. Despite a huge advantage of electronic cams in their reprogrammability or instantaneous change of displacement diagrams, conventional cam mechanisms have an irreplaceable role in production and handling machines. With high frequency of working cycle periods, the dynamic load of the proper servomotor rotor increases and efficiency of electronic cams strongly decreases. Though conventional intermittent mechanisms with radial cams are representatives of fixed automation, they have distinct advantages in their high speed (high dynamics), positional accuracy and relatively easy manufacture. We try to remove the disadvantage of firm displacement diagram by reducing costs for simple design and automated calculation that leads reliably to high-quality and inexpensive manufacture.

Keywords: Cam mechanism, displacement diagram, intermittentmechanism, radial parallel cam

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Authors: Nazirah Zainul Abidin, Nurul Zahirah Mokhtar Azizi

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Cost has always been the leading concern in green building development. The perception that construction cost for green building is higher than conventional buildings has only made the discussion of green building cost more difficult. Understanding the factors that will influence the cost of green construction is expected to shed light into what makes green construction more or at par with conventional projects, or perhaps, where cost can be optimised. This paper identifies the elements of cost before shifting the attention to the influencing factors. Findings from past studies uncovered various factors related to cost which are grouped into five focal themes i.e. awareness, knowledge, financial, technical, and government support. A conceptual framework is produced in a form of a flower diagram indicating the cost influencing factors of green building development. These factors were found to be both physical and non-physical aspects of a project. The framework provides ground for the next stage of research that is to further explore how these factors influence the project cost and decision making.

Keywords: Green project, factors influencing cost, hard cost, soft cost.

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: A-shaped compact microstrip antenna, Artificial Neural Network (ANN), adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM).

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Authors: Mochammad Dewo, Sumarsono Sudarto

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The Exponential Triple Smoothing Algorithm approach nowadays, which is used to anticipate the export value of Indonesia's two major commodities, coal and palm oil, has a Mean Percentage Absolute Error (MAPE) value of 30-50%, which may be considered as a "reasonable" forecasting mistake. Forecasting errors of more than 30% shall have a domino effect on industrial output, as extra production adds to raw material, manufacturing and storage expenses. Whereas, reaching an "excellent" classification with an error value of less than 10% will provide new investors and exporters with confidence in the commercial development of related sectors. Industrial growth will bring out a positive impact on economic development. It can be applied for other commodities if the forecast error is less than 10%. The purpose of this project is to create a forecasting technique that can produce precise forecasting results with an error of less than 10%. This research analyzes forecasting methods such as ARIMA (Autoregressive Integrated Moving Average), ANN (Artificial Neural Network) and LSTM (Long-Short Term Memory). By providing a MAPE of 1%, this study reveals that ANN is the most successful strategy for forecasting coal and palm oil commodities in Indonesia.

Keywords: ANN, Artificial Neural Network, ARIMA, Autoregressive Integrated Moving Average, export value, forecast, LSTM, Long Short Term Memory.

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: Brain machine interface, decision-making, local field potentials, mobile robot, navigation, neural network, rat, signal processing.

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Authors: Ghassan A. Abed, Mahamod Ismail, Samir I. Badrawi, Bayan M. Sabbar

Abstract:

Long Term Evolution Advanced (LTE-Advanced) LTE-Advanced is not new as a radio access technology, but it is an evolution of LTE to enhance the performance. This generation is the continuation of 3GPP-LTE (3GPP: 3rd Generation Partnership Project) and it is targeted for advanced development of the requirements of LTE in terms of throughput and coverage. The performance evaluation process of any network should be based on many models and simulations to investigate the network layers and functions and monitor the employment of the new technologies especially when this network includes large-bandwidth and low-latency links such as LTE and LTE-Advanced networks. Therefore, it’s necessary to enhance the proposed models of high-speed and high-congested link networks to make these links and traffics fulfill the needs of the huge data which transferred over the congested links. This article offered an innovative model of the most correlated links of LTE-Advanced system using the Network Simulator 2 (NS-2) with investigation of the link parameters.

Keywords: 3GPP, LTE, LTE-Advanced, NS-2.

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