Search results for: one side class algorithm

Authors: Hong Lu, Xiong Xiao

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Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

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Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

Procedia PDF Downloads 218

Authors: Patompong Satapornpong, Therdpong Tempark, Pawinee Rerknimitr, Jettanong Klaewsongkram, Chonlaphat Sukasem

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Dapsone (4, 4’-diaminodiphenyl sulfone, DDS) is broadly used for the treatment of inflammatory diseases and infections such as; leprosy, Pneumocystis jiroveci pneumonia in patients with HIV infection, neutrophilic dermatoses, dermatitis herpetiformis and autoimmune bullous disease. The severe cutaneous adverse drug reactions (SCARs) including, Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN) and drug reaction with eosinophilia and systemic symptoms (DRESS) are rare but severe life-threatening adverse drug reactions. Dapsone is one of many culprit drugs induced SJS, TEN and DRESS. Notwithstanding, to our knowledge, there are no studies of the association of HLA class I alleles and dapsone-induced SCARs in non-leprosy Thai patients. This investigation was a prospective cohort study, which performed in a total of 45 non-leprosy patients. Fifteen patients of dapsone-induced SCARs were classified as following the RegiSCAR criteria, and 30 dapsone-tolerant controls were exposed to dapsone more than 6 months without any evidence of cutaneous reactions. The genotyping of HLA-A, -B and –C were performed using sequence-specific oligonucleotides (PCR-SSOs). The Ethics Committee of Ramathibodi hospital, Mahidol University, approved this study. Among all HLA class I alleles, HLA-A*24:07, HLA-B*13:01, HLA-B*15:02, HLA-C*03:04 and HLA-C*03:09 were significantly associated with dapsone-induced SCARs (OR = 10.55, 95% CI = 1.06 – 105.04, p = 0.0360; OR = 56.00, 95% CI = 8.27 – 379.22, p = 0.0001; OR = 7.00, 95% CI = 1.17 – 42.00, p = 0.0322; OR = 6.00, 95% CI = 1.24 – 29.07, p = 0.0425 and OR = 17.08, 95% CI = 0.82 – 355.45, p = 0.0321, respectively). Furthermore, HLA-B*13:01 allele had strong association with dapsone-induced SJS-TEN and DRESS when compared with dapsone-tolerant controls (OR = 42.00, 95% CI = 2.88 – 612.31, p = 0.0064 and OR = 63.00, 95% CI = 7.72 – 513.94 and p = 0.0001, respectively). Consequently, HLA-B*13:01 might serve as a pharmacogenetic marker for screening before initiating the therapy with dapsone for prevention of dapsone-induced SCARs.

Keywords: dapsone-induced SCARs, HLA-B*13:01, HLA class I alleles, severe cutaneous adverse reactions, Thai

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Authors: Tabrej Khan

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Examination Scheduling System (ESS) is a scheduling system that targets as an exam committee in any academic institute to help them in managing the exams automatically. We present an algorithm for Examination Scheduling System. Nowadays, many universities have challenges with creating examination schedule fast with less confliction compared to hand works. Our aims are to develop a computerized system that can be used in examination scheduling in an academic institute versus available resources (Time, Hall, Invigilator and instructor) with no contradiction and achieve fairness among students. ESS was developed using HTML, C# language, Crystal Report and ASP.NET through Microsoft Visual Studio 2010 as developing tools with integrated SQL server database. This application can produce some benefits such as reducing the time spent in creating an exam schedule and achieving fairness among students

Keywords: examination scheduling system (ESS), algorithm, ASP.NET, crystal report

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Authors: A. Baviskar, C. Sandeep, K. Shankar

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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.

Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)

Procedia PDF Downloads 279

Authors: Mabrouka Algherinai, Fatma Karkouri

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Today, Short Message Service (SMS) is an important means of communication. SMS is not only used in informal environment for communication and transaction, but it is also used in formal environments such as institutions, organizations, companies, and business world as a tool for communication and transactions. Therefore, there is a need to secure the information that is being transmitted through this medium to ensure security of information both in transit and at rest. But, encryption has been identified as a means to provide security to SMS messages in transit and at rest. Several past researches have proposed and developed several encryption algorithms for SMS and Information Security. This research aims at comparing the performance of common Asymmetric encryption algorithms on SMS security. The research employs the use of three algorithms, namely RSA, McEliece, and RABIN. Several experiments were performed on SMS of various sizes on android mobile device. The experimental results show that each of the three techniques has different key generation, encryption, and decryption times. The efficiency of an algorithm is determined by the time that it takes for encryption, decryption, and key generation. The best algorithm can be chosen based on the least time required for encryption. The obtained results show the least time when McEliece size 4096 is used. RABIN size 4096 gives most time for encryption and so it is the least effective algorithm when considering encryption. Also, the research shows that McEliece size 2048 has the least time for key generation, and hence, it is the best algorithm as relating to key generation. The result of the algorithms also shows that RSA size 1024 is the most preferable algorithm in terms of decryption as it gives the least time for decryption.

Keywords: SMS, RSA, McEliece, RABIN

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Authors: Delowar Hossain, Genci Capi

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This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

Procedia PDF Downloads 357

Authors: Sirilak Kongkaew, Pathumwadee Yodmanee, Nopporn Kaiyawet, Arthitaya Meeprasert, Thanyada Rungrotmongkol, Toshikatsu Kaburaki, Hiroshi Noguchi, Fujio Takeuch, Nawee Kungwan, Supot Hannongbua

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Behçet’s disease (BD) is a genetic autoimmune expressed by multisystemic inflammatory disorder mostly occurred at the skin, joints, gastrointestinal tract, and genitalia, including ocular, oral, genital, and central nervous systems. Most BD patients in Japan and Korea were strongly indicated by the genetic factor namely HLA-B*51 (especially, HLA-B*51:01) marker in HMC class I, while HLA-A*26:01 allele has been detected from the BD patients in Greek, Japan, and Taiwan. To understand the selective binding of the MICA-TM peptide towards the HLAs associated with BD, the molecular dynamics simulations were applied on the four HLA alleles (B*51:01, B*35:01, A*26:01, and A*11:01) in complex with such peptide. As a result, the key residues in the binding groove of HLA protein which play an important role in the MICA-TM peptide binding and stabilization were revealed. The Van der Waals force was found to be the main protein-protein interaction. Based on the binding free energy prediction by MM/PBSA method, the MICA-TM peptide interacted stronger to the HLA alleles associated to BD in the identical class by 7-12 kcal/mol. The obtained results from the present study could help to differentiate the HLA alleles and explain a source of Behçet’s disease.

Keywords: Behçet’s disease, MD simulations, HMC class I, autoimmune

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Masoud Abedi, Abbas Malekpour, Peter Luksch, Mohammad Reza Mojtabaei

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The use of short texts in communication has been greatly increasing in recent years. Applying different languages in short texts has led to compulsory use of Unicode strings. These strings need twice the space of common strings, hence, applying algorithms of compression for the purpose of accelerating transmission and reducing cost is worthwhile. Nevertheless, other compression methods like gzip, bzip2 or PAQ due to high overhead data size are not appropriate. The Huffman algorithm is one of the rare algorithms effective in reducing the size of short Unicode strings. In this paper, an algorithm is proposed for compression of very short Unicode strings. At first, every new character to be sent to a destination is inserted in the proposed mapping table. At the beginning, every character is new. In case the character is repeated for the same destination, it is not considered as a new character. Next, the new characters together with the mapping value of repeated characters are arranged through a specific technique and specially formatted to be transmitted. The results obtained from an assessment made on a set of short Persian and Arabic strings indicate that this proposed algorithm outperforms the Huffman algorithm in size reduction.

Keywords: Algorithms, Data Compression, Decoding, Encoding, Huffman Codes, Text Communication

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Authors: Sajjad Seifoori

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Impact behavior of striker on graphene sheet and carbon nanotube is investigated based on molecular dynamics (MD) simulations. A MD simulation is conducted to obtain the maximum dynamic deflections of a square and rectangular single-layered graphene sheets (SLGSs) with various values of side-length and striker parameter. Effect of (i) chirality, (ii) graphene side-length and nanotube length, (iii) striker mass on the maximum dynamic deflections of graphene and nanotube are investigated. The effect of different types of boundary condition on the maximum dynamic deflections is studied for zigzag and armchair SWCNTs with various aspect ratios (Length/Diameter).

Keywords: impact, molecular dynamic, graphene, spring mass

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Authors: A. Gün Güneş

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This study aims to explicate the functionality of the responsibility to protect (R2P) in terms of order and justice within the context of the main traditions of the English School theory. The conflicts in Libya and Syria and the response of the international society to these crises are analyzed in the pluralism-solidarism dichotomy of the English School. In this regard, the intervention under R2P in Libya exemplifies the solidaristic side emphasizing justice, while the non-intervention in Syria exemplifies the pluralistic side emphasizing order. This study discusses the cases of Libya and Syria on the basis of Great Powers.

Keywords: English school theory, international society, order, justice, responsibility to protect

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Authors: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

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The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

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Authors: N. Larbi, F. Debbat

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Wireless communication systems have changed dramatically and shown spectacular evolution over the past two decades. These radio technologies are engaged in a quest endless high-speed transmission coupled to a constant need to improve transmission quality. Various radio communication systems being developed use code division multiple access (CDMA) technique. This work analyses a hybrid honey bees mating optimization algorithm (HBMO) applied to multiuser detection (MuD) in CDMA communication systems. The HBMO is a swarm-based optimization algorithm, which simulates the mating process of real honey bees. We apply a hybridization of HBMO with simulated annealing (SA) in order to improve the solution generated by the HBMO. Simulation results show that the detection based on Hybrid HBMO, in term of bit error rate (BER), is viable option when compared with the classic detectors from literature under Rayleigh flat fading channel.

Keywords: BER, DS-CDMA multiuser detection, genetic algorithm, hybrid HBMO, simulated annealing

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: Niharika Verma, Sandeep Santosh

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DOA technique is a localization technique used in the communication field. Various algorithms have been developed for direction of arrival estimation like MUSIC, ROOT MUSIC, etc. These algorithms depend on various parameters like antenna array elements, number of snapshots and various others. Basically the MUSIC spectrum is evaluated and peaks obtained are considered as the angle of arrivals. The angles evaluated using this process depends on the scanning interval chosen. The accuracy of the results obtained depends on the coarseness of the interval chosen. In this paper, golden section search is applied to the MUSIC algorithm and therefore, more accurate results are achieved. Initially the coarse DOA estimations is done using the MUSIC algorithm in the range -90 to 90 degree at the interval of 10 degree. After the peaks obtained then fine DOA estimation is done using golden section search. Also, the partitioning method is applied to estimate the number of signals incident on the antenna array. Dependency of the algorithm on the number of snapshots is also being explained. Hence, the accurate results are being determined using this algorithm.

Keywords: Direction of Arrival (DOA), golden section search, MUSIC, number of snapshots

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: T. Karech A. Noui, T. Bouzid

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This article presents a comparative study by numerical analysis of the behavior of reinforcements of clayey soils by flexible columns (stone columns) and rigid columns (piles). The numerical simulation was carried out in 3D for an assembly of foundation, columns and a pile of a bridge. Particular attention has been paid to take into account the installation of the columns. Indeed, in practice, due to the compaction of the column, the soil around it sustains a lateral expansion and the horizontal stresses are increased. This lateral expansion of the column can be simulated numerically. This work represents a comparative study of the interaction between the soil on one side, and the two types of reinforcement on the other side, and their influence on the behavior of the soil and of the pile of a bridge.

Keywords: piles, stone columns, interaction, foundation, settlement, consolidation

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Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

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

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

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Authors: Ateeqa Aslam, Hans J. Nauwynck

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Porcine hemagglutinating encephalomyelitis virus (PHEV) is a betacoronavirus that has been studied in the past as a cause of vomiting and wasting disease (VWD) in young piglets (<3 weeks). Nowadays, the virus is still circulating on most farms in Belgium, but there are no descriptions anymore of VWD. Therefore, we are interested in differences between the old and new strains. We compared the replication kinetics of the old well-studied strain VW572 (1972) and the recent isolate P412 (2020) in a susceptible continuous cell line (RPD cells) and in primary porcine respiratory epithelial cells (PoRECs). The RPD cell line was inoculated with each PHEV strain at an m.o.i. of 1 the supernatant was collected, and the cells were fixed at different time points post-inoculation. The supernatant was titrated (extracellular virus titer), and the infected cells were revealed by immunofluorescence staining and quantitated by fluorescence microscopy. We found that VW572 replicated better in the RPD cell line at earlier time points when compared to P412. Porcine respiratory epithelial cells (PoREC) were isolated, grown at air-liquid interphase in transwells and inoculated with both strains of PHEV at a virus titer of 106.6TCID50 per 200 µl either at the apical side or at the basal side of the cells. At different time points after inoculation, the transwells were fixed and stained for infected cells. VW572 preferentially infected the epithelial cells via the basolateral side of porcine nasal epithelial cells, whereas P412 preferred the apical side. These findings suggest that there has been an evolution of PHEV in its interaction with the respiratory epithelial cells. In the future, more virus strains will be enclosed and the tropism of the strains for different neuronal cell types will be examined for the change in virus neurotropism.

Keywords: porcine hemagglutinating encephalomyelitis virus (PHEV), primary porcine respiratory epithelial cells (PoRECs), virus tropism, vomiting and wasting disease (VWD)

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Naufal Ahmed, Michael Lwin

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Background: MPFL reconstructions are ideally performed with au-tografts like gracilis semitendinosus tendon, which may be associated with donor site morbidity and complications. In this case series, we have tried to use fiber tape, which avoids the above complications and also keeps the graft virgin. This kind of synthetic graft has been used successfully in rotator cuffs and ACJ reconstructions with good results. Materials and methods: It was a retrospective data analysis of 45 patients who underwent this procedure from 2014-2020 under a single consultant in a DGH . These patiens have been followed up at 6 weeks, 6 months, 1 year, and 1 ½ years with clinical assessment and KOOS scores. We compared the results with the NJR and also with the Belgium report and was found to be satisfactory and comparable with them. Surgical technique : We used Arthrex fiber tape for the reconstruction of MPFL . Initially, two parallel holes drilled over sup aspect of the patella with help of an image intensifier, and then fiber wire passed through them from the medial to the lateral side and back to the medial side. The fiber wire was attached to the schottle point on the femoral side, giving a good extra articular internal brac-ing to the MPFL. All patients were scoped before the procedure, and the final tightening over the femoral side was done directly under vision to see the position of the patella. Results: We had 45 MPFL reconstructions along with 4 additional procedures 1 ACLR, 2 ACL REPAIR, 1 TTT advancement ( revision MPFL ). There were 14 males and 31 females, and their average age was 25 (13-55 ). We did not have any donor site morbidity, no infection, no fractures, no recurrent dislocations, no reoperations yet. Conclusion: Fiber tape is a feasible and appropriate option for MPFL reconstruction. We haven’t seen any re -operation in our 5 year follow up. This technique avoids the use of autograft, which can be used in the future if needed for revision surgeries. We don’t lose anything by following this simple novel technique.

Keywords: arthroscopy, fibertape, MPFL reconstruction, recurrent patella dislocation

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Authors: Goh Yung Hong, Mona Masood

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This paper explores the effects of gamification on lower secondary school students’ motivation and engagement in the classroom. Two-group posttest-only experimental design were employed to study the influence of gamification teaching method (GTM) when compared with conventional teaching method (CTM) on 60 lower secondary school students. The Student Engagement Instrument (SEI) and Intrinsic Motivation Inventory (IMI) were used to assess students’ intrinsic motivation and engagement level towards the respective teaching method. Finding indicates that students who completed the GTM lesson were significantly higher in intrinsic motivation to learn than those from the CTM. Although the result were insignificant and only marginal difference in the engagement mean, GTM still show better potential in raising student’s engagement in class when compared with CTM. This finding proves that the GTM is likely to solve the current issue of low motivation to learn and low engagement in class among lower secondary school students in Malaysia. On the other hand, despite being not significant, higher mean indicates that CTM positively contribute to higher peer support for learning and better teacher and student relationship when compared with GTM. As a conclusion, gamification approach is flexible and can be adapted into many learning content to enhance the intrinsic motivation to learn and to some extent, encourage better student engagement in class.

Keywords: conventional teaching method, gamification teaching method, motivation, engagement

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Authors: Jaimin Patel

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Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

Keywords: Cloud computing, encryption algorithm, secure hashing algorithm, brute force attack, birthday attack, plaintext attack, man in middle attack

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Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

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With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation

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Authors: Martina I. Reinhold, Theresa Bacon-Baguley

Abstract:

Background: Medical knowledge continuously evolves and to help health care providers to stay up-to-date, evidence-based medicine (EBM) has emerged as a model. The practice of EBM requires new skills of the health care provider, including directed literature searches, the critical evaluation of research studies, and the direct application of the findings to patient care. This paper describes the integration and evaluation of an evidence-based medicine course sequence into a Physician Assistant curriculum. This course sequence teaches students to manage and use the best clinical research evidence to competently practice medicine. A survey was developed to assess the outcomes of the EBM course sequence. Methodology: The cornerstone of the three-semester sequence of EBM are interactive small group discussions that are designed to introduce students to the most clinically applicable skills to identify, manage and use the best clinical research evidence to improve the health of their patients. During the three-semester sequence, the students are assigned each semester to participate in small group discussions that are facilitated by faculty with varying background and expertise. Prior to the start of the first EBM course in the winter semester, PA students complete a knowledge-based survey that was developed by the authors to assess the effectiveness of the course series. The survey consists of 53 Likert scale questions that address the nine objectives for the course series. At the end of the three semester course series, the same survey was given to all students in the program and the results from before, and after the sequence of EBM courses are compared. Specific attention is paid to overall performance of students in the nine course objectives. Results: We find that students from the Class of 2016 and 2017 consistently improve (as measured by percent correct responses on the survey tool) after the EBM course series (Class of 2016: Pre- 62% Post- 75%; Class of 2017: Pre- 61 % Post-70%). The biggest increase in knowledge was observed in the areas of finding and evaluating the evidence, with asking concise clinical questions (Class of 2016: Pre- 61% Post- 81%; Class of 2017: Pre- 61 % Post-75%) and searching the medical database (Class of 2016: Pre- 24% Post- 65%; Class of 2017: Pre- 35 % Post-66 %). Questions requiring students to analyze, evaluate and report on the available clinical evidence regarding diagnosis showed improvement, but to a lesser extend (Class of 2016: Pre- 56% Post- 77%; Class of 2017: Pre- 56 % Post-61%). Conclusions: Outcomes identified that students did gain skills which will allow them to apply EBM principles. In addition, the outcomes of the knowledge-based survey allowed the faculty to focus on areas needing improvement, specifically the translation of best evidence into patient care. To address this area, the clinical faculty developed case scenarios that were incorporated into the lecture and discussion sessions, allowing students to better connect the research studies with patient care. Students commented that ‘class discussion and case examples’ contributed most to their learning and that ‘it was helpful to learn how to develop research questions and how to analyze studies and their significance to a potential client’. As evident by the outcomes, the EBM courses achieved the goals of the course and were well received by the students. 

Keywords: evidence-based medicine, clinical education, assessment tool, physician assistant

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Authors: Yifan Hou, Haibo Liu, Le Jiang, Wandong Su, Binqing Wang

Abstract:

Road defect detection is crucial for modern urban management and infrastructure maintenance. Traditional road defect detection methods mostly rely on manual labor, which is not only inefficient but also difficult to ensure their reliability. However, existing deep learning-based road defect detection models have poor detection performance in complex environments and lack robustness to multi-scale targets. To address this challenge, this paper proposes a distinct detection framework based on the one stage algorithm network structure. This article designs a deep feature extraction network based on RCSDarknet, which applies channel shuffling to enhance information fusion between tensors. Through repeated stacking of RCS modules, the information flow between different channels of adjacent layer features is enhanced to improve the model's ability to capture target spatial features. In addition, a multi-scale feature fusion mechanism with weighted dual flow paths was adopted to fuse spatial features of different scales, thereby further improving the detection performance of the model at different scales. To validate the performance of the proposed algorithm, we tested it using the RDD2022 dataset. The experimental results show that the enhancement algorithm achieved 84.14% mAP, which is 1.06% higher than the currently advanced YOLOv8 algorithm. Through visualization analysis of the results, it can also be seen that our proposed algorithm has good performance in detecting targets of different scales in complex scenes. The above experimental results demonstrate the effectiveness and superiority of the proposed algorithm, providing valuable insights for advancing real-time road defect detection methods.

Keywords: roads, defect detection, visualization, deep learning

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

Abstract:

Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 130