Search results for: general variable neighborhood search algorithm.

Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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Authors: Mostafa Osman, Ata El-Kareim Shoeib Soliman

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Since columns are the most important elements of the structures, failure of one column in a critical location can cause a progressive collapse. In this respect, the repair and strengthening of columns is a very important subject to reduce the building failure and to keep the columns capacity. Twenty columns with different parameters is tested and analysis. Eleven typical confined reinforced concrete (RC) columns with different types of techniques are assessment. And also, four confined concrete columns with plastic tube (PVC) are tested with and with four paralleling tested of unconfined plain concrete. The techniques of confined RC columns are mortar strengthening, Steel rings strengthening, FRP strengthening. Moreover, the technique of confined plain concrete (PC) column is used PVC tubes. The columns are tested under uniaxial compressive loads studied the effect of confinement on the structural behavior of circular RC columns. Test results for each column are presented in the form of crack patterns, stress-strain curves. Test results show that confining of the RC columns using different techniques of strengthening results significant improvement of the general behavior of the columns and can used in construction. And also, tested confined PC columns with PVC tubes results shown that the confined PC with PVC tubes can be used in economical building. The theoretical model for predicted column capacity is founded with experimental factor depends on the confined techniques used and the strain reduction.

Keywords: Confined reinforced concrete column, CFRP, GFRP, Mortar.

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Authors: B. Malarkodi, S. K. Riyaz Hussain, B. Venkataramani

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Power consumption of nodes in ad hoc networks is a critical issue as they predominantly operate on batteries. In order to improve the lifetime of an ad hoc network, all the nodes must be utilized evenly and the power required for connections must be minimized. In this project a link layer algorithm known as Power Aware medium Access Control (PAMAC) protocol is proposed which enables the network layer to select a route with minimum total power requirement among the possible routes between a source and a destination provided all nodes in the routes have battery capacity above a threshold. When the battery capacity goes below a predefined threshold, routes going through these nodes will be avoided and these nodes will act only as source and destination. Further, the first few nodes whose battery power drained to the set threshold value are pushed to the exterior part of the network and the nodes in the exterior are brought to the interior. Since less total power is required to forward packets for each connection. The network layer protocol AOMDV is basically an extension to the AODV routing protocol. AOMDV is designed to form multiple routes to the destination and it also avoid the loop formation so that it reduces the unnecessary congestion to the channel. In this project, the performance of AOMDV is evaluated using PAMAC as a MAC layer protocol and the average power consumption, throughput and average end to end delay of the network are calculated and the results are compared with that of the other network layer protocol AODV.

Keywords: AODV, PAMAC, AOMDV, Power consumption.

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Authors: Marcus Banda

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In this article the influence of higher frequency effects in addition to a special damper design on the electrical behavior of a synchronous generator main exciter machine is investigated. On the one hand these machines are often highly stressed by harmonics from the bridge rectifier thus facing additional eddy current losses. On the other hand the switching may cause the excitation of dangerous voltage peaks in resonant circuits formed by the diodes of the rectifier and the commutation reactance of the machine. Therefore modern rotating exciters are treated like synchronous generators usually modeled with a second order equivalent circuit. Hence the well known Standstill Frequency Response Test (SSFR) method is applied to a test machine in order to determine parameters for the simulation. With these results it is clearly shown that higher frequencies have a strong impact on the conventional equivalent circuit model. Because of increasing field displacement effects in the stranded armature winding the sub-transient reactance is even smaller than the armature leakage at high frequencies. As a matter of fact this prevents the algorithm to find an equivalent scheme. This issue is finally solved using Laplace transfer functions fully describing the transient behavior at the model ports.

Keywords: Synchronous exciter machine, Linear transfer function, SSFR, Equivalent Circuit

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: Joe Walsh, Mike Climstein, Ian Timothy Heazlewood, Stephen Burke, Jyrki Kettunen, Kent Adams, Mark DeBeliso

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Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the prevalence of obesity in this unique population was of particular interest. Data gathered on a sub-sample of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p<0.001), reduced classification of obesity using Body Mass Index (BMI) when compared to data on the Australian national population. This evidence of improved classification in one index of health (BMI<30) implies there are either improved levels of this index of health due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport. Given the worldwide focus on the obesity epidemic and the need for a multi-faceted solution to this problem, demonstration of these middle to older aged adults having improved BMI over the general population is of particular interest.

Keywords: BMI, masters athlete, rugby union, soccer, touch football

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Authors: M.R. Mansoujian, N. Hedayat, M. Mashal, H, Kiamanesh

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Analytical investigation of the sedimentation processes in the river engineering and hydraulic structures is of vital importance as this can affect water supply for the cultivating lands in the command area. The reason being that gradual sediment formation behind the reservoir can reduce the nominal capacity of these dams. The aim of the present paper is to analytically investigate sedimentation process along the river course and behind the storage reservoirs in general and the Eastern Intake of the Dez Diversion weir in particular using the SHARC software. Results of the model indicated the water level at 115.97m whereas the real time measurement from the river cross section was 115.98 m which suggests a significantly close relation between them. The average transported sediment load in the river was measured at 0.25mm , from which it can be concluded that nearly 100% of the suspended loads in river are moving which suggests no sediment settling but indicates that almost all sediment loads enters into the intake. It was further showed the average sediment diameter entering the intake to be 0.293 mm which in turn suggests that about 85% of suspended sediments in the river entre the intake. Comparison of the results from the SHARC model with those obtained form the SSIIM software suggests quite similar outputs but distinguishing the SHARC model as more appropriate for the analysis of simpler problems than other model.

Keywords: SHARC, Eastern Intake, Dez Diversion Weir.

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Authors: Rishabh Garg

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Traditionally, business parties build trust with a centralized operating mechanism, such as payment by letter of credit. However, the increase in cyber-attacks and malicious hacking has jeopardized business operations and finance practices. Emerging markets, due to their high banking risks and the large presence of digital financing, are looking for technology that enables transparency and traceability of any transaction in trade, finance or supply chain management. Blockchain systems, in the absence of any central authority, enable transactions across the globe with the help of decentralized applications. DApps consist of a front-end, a blockchain back-end, and middleware, that is, the code that connects the two. The front-end can be a sophisticated web app or mobile app, which is used to implement the functions/methods on the smart contract. Web apps can employ technologies such as HTML, CSS, React and Express. In this wake, fintech and blockchain products are popping up in brokerages, digital wallets, exchanges, post-trade clearance, settlement, middleware, infrastructure and base protocols. The present paper provides a technology driven solution, financial inclusion and innovative working paradigm for business and finance.

Keywords: Authentication, blockchain, channel, cryptography, DApps, data portability, Decentralized Public Key Infrastructure, Ethereum, hash function, Hashgraph, Privilege creep, Proof of Work algorithm, revocation, storage variables, Zero Knowledge Proof.

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

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This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: Flexible job shop scheduling, Decision tree, Priority rules, Case study.

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: Curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering.

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Authors: Andrew Hwang

Abstract:

The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion.

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Authors: Zohreh Orshesh

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In this study, a 3D combustion chamber was simulated using FLUENT 6.32. Aims to obtain accurate information about the profile of the combustion in the furnace and also check the effect of oxygen enrichment on the combustion process. Oxygen enrichment is an effective way to reduce combustion pollutant. The flow rate of air to fuel ratio is varied as 1.3, 3.2 and 5.1 and the oxygen enriched flow rates are 28, 54 and 68 lit/min. Combustion simulations typically involve the solution of the turbulent flows with heat transfer, species transport and chemical reactions. It is common to use the Reynolds-averaged form of the governing equation in conjunction with a suitable turbulence model. The 3D Reynolds Averaged Navier Stokes (RANS) equations with standard k-ε turbulence model are solved together by Fluent 6.3 software. First order upwind scheme is used to model governing equations and the SIMPLE algorithm is used as pressure velocity coupling. Species mass fractions at the wall are assumed to have zero normal gradients.Results show that minimum mole fraction of CO2 happens when the flow rate ratio of air to fuel is 5.1. Additionally, in a fixed oxygen enrichment condition, increasing the air to fuel ratio will increase the temperature peak. As a result, oxygen-enrichment can reduce the CO2 emission at this kind of furnace in high air to fuel rates.

Keywords: Combustion chamber, Oxygen enrichment, Reynolds Averaged Navier- Stokes, CO2 emission

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Authors: Hyun-Koo Kim, Ju H. Park, Ho-Youl Jung

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This paper presents an effective traffic lights recognition method at the daytime. First, Potential Traffic Lights Detector (PTLD) use whole color source of YCbCr channel image and make each binary image of green and red traffic lights. After PTLD step, Shape Filter (SF) use to remove noise such as traffic sign, street tree, vehicle, and building. At this time, noise removal properties consist of information of blobs of binary image; length, area, area of boundary box, etc. Finally, after an intermediate association step witch goal is to define relevant candidates region from the previously detected traffic lights, Adaptive Multi-class Classifier (AMC) is executed. The classification method uses Haar-like feature and Adaboost algorithm. For simulation, we are implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM and tested in the urban and rural roads. Through the test, we are compared with our method and standard object-recognition learning processes and proved that it reached up to 94 % of detection rate which is better than the results achieved with cascade classifiers. Computation time of our proposed method is 15 ms.

Keywords: Traffic Light Detection, Multi-class Classification, Driving Assistance System, Haar-like Feature, Color SegmentationMethod, Shape Filter

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Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

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Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: Finite Element Method, Fluence Distribution, Monte Carlo Method, Photoacoustic Imaging.

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Authors: Smita S. D. Goorah, Melisha Panchoo

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In Mauritius, much emphasis is put on measures to combat the high prevalence of non-communicable diseases (NCDs). Health promotion campaigns for the adoption of healthy behaviors and screening programs are done regularly by local authorities and NCD surveys are carried out at intervals. However, the health behaviors of the poor have not been investigated so far. This study aims to give an insight on the perceptions of health status and lifestyle health behaviors of poor people in Mauritius. A crosssectional study among 83 persons benefiting from social aid in a selected urban district was carried out. Results showed that 51.8% of respondents perceived that they had good health status. 57.8% had no known NCD whilst 25.3% had hypertension, followed by diabetes (16.9%), asthma (9.6%) and heart disease (7.2%).They had low smoking (10.8%) and alcohol consumption (6.0%) as well as high physical activity prevalence (54.2%). These results were significantly different from the NCD survey carried out in the general population. Consumption of vegetables in the study was high. Overweight and obesity trends were however similar to the NCD survey report 2009. These findings contrast with other international studies showing poor people having poor perceptions of health status and unhealthy behavioral choices. Whether these positive health behaviors of poor people in Mauritius arise out of choice or whether it is because the alternative behavior is too costly remains to be investigated further.

Keywords: Health behavior, non-communicable diseases, poor people.

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Authors: Sharif E. Guseynov, Jekaterina V. Aleksejeva, Janis S. Rimshans

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A filtering problem of almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain is studied. In this work general approaches to the solution of twodimensional filtering problems in ananisotropic, inhomogeneous and multilayered medium are developed, and on the basis of the obtained results mathematical models are constructed (according to Ollendorff method) for studying the certain engineering and technical problem of filtering the almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain. For some of the formulated mathematical problems with additional requirements for the structure of the porous inhomogeneous medium, namely, its isotropy, spatial periodicity of its permeability coefficient, solution algorithms are proposed. Continuation of the current work titled ”On one mathematical model for filtration of weakly compressible chemical compound in the porous heterogeneous 3D medium. Part II: Determination of the reference directions of anisotropy and permeabilities on these directions” will be prepared in the shortest terms by the authors.

Keywords: Porous media, filtering, permeability, elliptic PDE.

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Authors: N. Khiati

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The present paper attempts to report on some findings that emerged out of a larger scale doctorate research into English language needs of a renowned Algerian company of Hydrocarbon industry. From a multifaceted English for specific purposes (ESP) research perspective, the paper considers the English needs of the finance/legal department staff in the midst of the conflicting needs perspectives involving both objective needs indicators (i.e., the pressure of globalised business) and the general negative attitudes among the administrative -mainly jurists- staff towards English (favouring a non-adaptation strategy). The researcher’s unearthing of the latter’s needs is an endeavour to concretise the concepts of unmet, or unconscious needs, among others. This is why, these initially uncovered hidden needs will be detailed questioning educational background, namely previous language of instruction; training experiences and expectations; as well as the actual communicative practices derived from the retrospective interviews and preliminary quantitative data of the questionnaire. Based on these rough clues suggesting real needs, the researcher will tentatively propose some implications for both pre-service and in-service training organisers as well as for educational policy makers in favour of an English course in legal English for the jurists mainly from pre-graduate phases to in-service training.

Keywords: English for specific purposes, ESP, legal and finance staff, needs analysis, unmet/unconscious needs, training implications.

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Authors: Mrs.K.Kavitha, S.Arivazhagan

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A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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Authors: R. Bremananth, A. Chitra

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Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

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Authors: Ki Hyun Kim, Jang-Hee Yoo, Kyo Il Chung

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This paper proposes a VPN Accelerator Board (VPN-AB), a virtual private network (VPN) protocol designed for trust channel security system (TCSS). TCSS supports safety communication channel between security nodes in internet. It furnishes authentication, confidentiality, integrity, and access control to security node to transmit data packets with IPsec protocol. TCSS consists of internet key exchange block, security association block, and IPsec engine block. The internet key exchange block negotiates crypto algorithm and key used in IPsec engine block. Security Association blocks setting-up and manages security association information. IPsec engine block treats IPsec packets and consists of networking functions for communication. The IPsec engine block should be embodied by H/W and in-line mode transaction for high speed IPsec processing. Our VPN-AB is implemented with high speed security processor that supports many cryptographic algorithms and in-line mode. We evaluate a small TCSS communication environment, and measure a performance of VPN-AB in the environment. The experiment results show that VPN-AB gets a performance throughput of maximum 15.645Gbps when we set the IPsec protocol with 3DES-HMAC-MD5 tunnel mode.

Keywords: TCSS(Trust Channel Security System), VPN(VirtualPrivate Network), IPsec, SSL, Security Processor, Securitycommunication.

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: Social networks, community detection, modularity optimization, geographically dispersed communities.

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Authors: Safaa Mahmoud Issa

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Architecture, as an art and science of designing, has always been the medium to create environments that fulfill their users’ needs. It could create an inclusive environment that would not isolate any individual regardless of his /her disabilities. It could help, hopefully, in setting the strategies that provide a supportive, educational environment that would allow the inclusion of students with autism. Architects could help in the battle against this neuro-developmental disorder by providing the accommodating environment, at home and at school, in order to prevent institutionalizing these children. Through a theoretical approach and a review of literature, this study will explore and analyze best practices in autism-friendly, supportive, teaching environments. Additionally, it would provide the range of measures, and set the strategies to deal with the students with autism sensory peculiarities, and that, in order to allow them to concentrate in the school environment, and be able to succeed, and to be integrated as an important addition to society and the social mainstream. Architects should take into consideration the general guidelines for an autism-friendly built environment, and apply them to specific buildings systems. And that, as certain design elements have great effect on children’s behavior, by appropriating architecture to provide inclusive accommodating environments, the basis for equalization of opportunities is set allowing these individuals a better, normal, non-institutional life, as the discussion presented in this study would reveal.

Keywords: Architecture, inclusion, students with autism, mainstream society.

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Authors: Giorgi Chichinadze, David Shengelia, Tamara Tsutsunava, Nikoloz Maisuradze, Giorgi Beridze

Abstract:

The Jalovchat intrusive is built up of hornblende gabbros, gabbro-norites and norites. Within the intrusive hornblende-bearing gabbro-pegmatites are widespread. That is a coarse-grained rock with gigantic hornblende crystals. By its unusual composition, the Jalovchat intrusive has no analogue in the Caucasus. However, petrologically and geochemically, the intrusive rocks were studied insufficiently. For comprehensive investigations, the authors applied appropriate methodologies: Microscopic study of thin sections, petro- and geochemical analyses of the samples and also different petrogenic, rare and rare earth elements diagrams and spidergrams. Analytical study established that the Jalovchat intrusive by its composition corresponds mainly to the mid-ocean ridge basalts and according to geodynamic type belongs to the subduction type. In general, it is an anomalous phenomenon, as in the rocks of such composition crystallization of hornblende and especially of its gigantic crystals is atypical. The authors believe that the water-rich magma reservoir, which was necessary for the crystallization of gigantic hornblende crystals, appeared as a result of melting of water-rich mid-ocean ridge basaltic rocks during the subduction process in Bajocian time.

Keywords: Gabbroic intrusive, petrology, geochemistry, genesis, the Caucasus.

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Authors: C. Ardil

Abstract:

In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.

Keywords: Distance Education, Online Learning, Web BasedLearning, Learning Circles, e-Collaborative Learning Circles

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Authors: Jian Du, Shui Hong Hong, Lu Meng, Qing Wei Meng

Abstract:

This work addresses the problem of optimizing completely batch water-using network with multiple contaminants where the flow change caused by mass transfer is taken into consideration for the first time. A mathematical technique for optimizing water-using network is proposed based on source-tank-sink superstructure. The task is to obtain the freshwater usage, recycle assignments among water-using units, wastewater discharge and a steady water-using network configuration by following steps. Firstly, operating sequences of water-using units are determined by time constraints. Next, superstructure is simplified by eliminating the reuse and recycle from water-using units with maximum concentration of key contaminants. Then, the non-linear programming model is solved by GAMS (General Algebra Model System) for minimum freshwater usage, maximum water recycle and minimum wastewater discharge. Finally, numbers of operating periods are calculated to acquire the steady network configuration. A case study is solved to illustrate the applicability of the proposed approach.

Keywords: Completely batch process, flow change, multiple contaminants, water-using network.

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Authors: Walid A. M. Ghoneim, Hamdy A. Ashour, Asmaa E. Abdo

Abstract:

In this paper, linear analysis of a Switched Reluctance Generator (SRG) model is applied on the most common configurations (4/2, 6/4 and 8/6) for both conventional short-pitched and fully-pitched designs, in order to determine the optimum stator/rotor pole angles at which the maximum output voltage is generated per unit excitation current. This study is focused on SRG analysis and design as a proposed solution for renewable energy applications, such as wind energy conversion systems. The world’s potential to develop the renewable energy technologies through dedicated scientific researches was the motive behind this study due to its positive impact on economy and environment. In addition, the problem of rare earth metals (Permanent magnet) caused by mining limitations, banned export by top producers and environment restrictions leads to the unavailability of materials used for rotating machines manufacturing. This challenge gave authors the opportunity to study, analyze and determine the optimum design of the SRG that has the benefit to be free from permanent magnets, rotor windings, with flexible control system and compatible with any application that requires variable-speed operation. In addition, SRG has been proved to be very efficient and reliable in both low-speed or high-speed applications. Linear analysis was performed using MATLAB simulations based on the (Modified generalized matrix approach) of Switched Reluctance Machine (SRM). About 90 different pole angles combinations and excitation patterns were simulated through this study, and the optimum output results for each case were recorded and presented in detail. This procedure has been proved to be applicable for any SRG configuration, dimension and excitation pattern. The delivered results of this study provide evidence for using the 4-phase 8/6 fully pitched SRG as the main optimum configuration for the same machine dimensions at the same angular speed.

Keywords: Generalized matrix approach, linear analysis, renewable applications, switched reluctance generator, SRG.

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Authors: N. Manavizadeh, M. Hosseini, M. Rabbani

Abstract:

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Keywords: Mixed-Model Assembly Line, particle swarmoptimization, Multi-objective sequencing problem, MTO system, kitto-assembly, rest time

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

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