Search results for: range migration algorithm

Authors: Viana Hassan

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Each year, 600 million tourists travelled abroad to practice several types of tourism. Nowadays, whatever is the type of tourism practiced it considered as a real public health problem which can contribute the spread of several diseases such as AIDS, H1N1, NDM1 With regard to HIV/AIDS, Lebanon is always considered as a low HIV prevalence country. However, the potential risks associated with the mobility of the population, migration and tourism. The total number of cases reported by the ministry of health since 1989 until the end of 2011 is of 1455 cases, with an average of 85 new cases per year over the last three years. The main reason of the increased number is Travel and migration which represent 50% of the risks reported by cumulative cases. Given the interest of this kind of epidemic it would be interesting to study the Evolution of HIV/ AIDS and its relation with travel and tourism The main aim of this research is to study in general the relation between tourism and health, more specific to understand the relation between Tourism and AIDS, the problem of the transmission of HIV in Lebanon, the ways of contamination and the countries in which these people are contaminated.

Keywords: AIDS, tourism, health, Lebanon

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: P. Subbuthai, S. Muruganand

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Diabetic Retinopathy is one of the complicated diseases and it is caused by the changes in the blood vessels of the retina. Extraction of retina image through Fundus camera sometimes produced poor contrast and noises. Because of this noise, detection of blood vessels in the retina is very complicated. So preprocessing is needed, in this paper, a novel algorithm is implemented to remove the noisy pixel in the retina image. The proposed algorithm is Extended Median Filter and it is applied to the green channel of the retina because green channel vessels are brighter than the background. Proposed extended median filter is compared with the existing standard median filter by performance metrics such as PSNR, MSE and RMSE. Experimental results show that the proposed Extended Median Filter algorithm gives a better result than the existing standard median filter in terms of noise suppression and detail preservation.

Keywords: fundus retina image, diabetic retinopathy, median filter, microaneurysms, exudates

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Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

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Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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Authors: Aynur Charkasova

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The scientific and economic contributions of international students cannot be underestimated. International education continues to be a competitive global industry, and many countries are seeking to recruit the best and the brightest to reinforce scientific innovations, boost intercultural learning, and bring more funding to the universities and colleges. Substantial changes in international educational policies and migration regulations have been made in the hopes of recruiting global talent. This paper explores and compares recruitment strategies, employment opportunities, and a legal path to permanent residency policies related to international students in the United States of America and Canada. This study will utilize the legal information available by the government websites of both countries, peer-reviewed scholarly articles and will highlight which approach promises a better path in recruiting and retention of international students. The findings from the study will be discussed and recommendations will be provided.

Keywords: international students, current immigration policies, STEM, visa reforms for international students

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Authors: ِAbdallah A. A. Shaheen

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Gaza Strip faces economic and political issues such as conflict, siege and urbanization; all these have led to an increase in the air pollution over Gaza Strip. In this study, Particulate matter 10 (PM10) concentration over Gaza Strip has been estimated by Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) data, based on a multispectral algorithm. Simultaneously, in-situ measurements for the corresponding particulate are acquired for selected time period. Landsat and ground data for eleven years are used to develop the algorithm while four years data (2002, 2006, 2010 and 2014) have been used to validate the results of algorithm. The developed algorithm gives highest regression, R coefficient value i.e. 0.86; RMSE value as 9.71 µg/m³; P values as 0. Average validation of algorithm show that calculated PM10 strongly correlates with measured PM10, indicating high efficiency of algorithm for the mapping of PM10 concentration during the years 2000 to 2014. Overall results show increase in minimum, maximum and average yearly PM10 concentrations, also presents similar trend over urban area. The rate of urbanization has been evaluated by supervised classification of the Landsat image. Urban sprawl from year 2000 to 2014 results in a high concentration of PM10 in the study area.

Keywords: PM10, landsat, atmospheric reflectance, Gaza strip, urbanization

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Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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Authors: Christina Y. P. Ting

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Migration is a global phenomenon with movements of migrants from developed and developing countries to the host societies. Migrants have changed the host countries’ demography – its population structure and also its ethnic cultural diversity. Acculturation of migrants in terms of their adoption of the host culture is seen as important to ensure that they ‘fit into’ their adopted country so as to participate in everyday public life. However, this research found that the increase of the China-born migrants’ post-migration consumption level had impact on Australia’s environment reflected not only because of their adoption of elements of the host culture, but also retention of aspects of Chinese culture – indicating that the influence of bi-culturalism was in operation. This research, which was based on the face-to-face interview with 61 China-born migrants in the suburb of Box Hill, Melbourne, investigated the pattern of change in the migrants’ consumption upon their settlement in Australia. Using an ecological footprint calculator, their post-migration footprints were found to be larger than pre-migration footprint. The uniquely-derived CALD (Culturally and Linguistically Diverse) Index was used to measure individuals’ strength of connectedness to ethnic culture. Multi-variant analysis was carried out to understand which independent factors that influence consumption best explain the change in footprint (which is the difference between pre-and post-migration footprints, as a dependent factor). These independent factors ranged from socio-economic and demographics to the cultural context, that is, the CALD Index and indicators of acculturation. The major findings from the analysis were: Chinese culture (as measured by the CALD Index) and indicators of acculturation such as length of residency and using English in communications besides the traditional factors such as age, income and education level made significant contributions to the large increase in the China-born group’s post-migration consumption level. This paper as part of a larger study found that younger migrants’ large change in their footprint were related to high income and low level of education. This group of migrants also practiced bi-cultural consumption in retaining ethnic culture and adopting the host culture. These findings have importantly highlighted that for a host society to tackle environmental crisis, governments need not only to understand the relationship between age and consumption behaviour, but also to understand and embrace the migrants’ ethnic cultures, which may act as bridges and/or fences in relationships. In conclusion, for governments to deal with national issues such as environmental crisis within a cultural diverse population, it necessitates an understanding of age and aspects of ethnic culture that may act as bridges and fences. This understanding can aid in putting in place policies that enable the co-existence of a hybrid of the ethnic and host cultures in order to create and maintain a harmonious and secured living environment for population groups.

Keywords: bicultural consumer, CALD index, consumption, ethnic culture, migrants

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Authors: A. Belmeguenai, K. Mansouri, R. Djemili

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This work present a new algorithm based on the nonlinear filter generator for speech encryption and decryption. The proposed algorithm consists on the use a linear feedback shift register (LFSR) whose polynomial is primitive and nonlinear Boolean function. The purpose of this system is to construct Keystream with good statistical properties, but also easily computable on a machine with limited capacity calculated. This proposed speech encryption scheme is very simple, highly efficient, and fast to implement the speech encryption and decryption. We conclude the paper by showing that this system can resist certain known attacks.

Keywords: nonlinear filter generator, stream ciphers, speech encryption, security analysis

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Authors: Qing Lyu, Hang Zhu

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Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: flow path, latency, middlebox, network

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Alison Marshall

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“Santo Niño in Canada – Religion, Migration, and the Filipino Underside” seeks to explore the intersection of religion, migration and the Filipino underside through research participant narratives, archival research, and fieldwork on the cult of Santo Niño in Canada. Santo Niño is the single most revered saint in Filipino religiosity. According to popular lore, the original statue of Santo Niño was brought to the Philippines by Portuguese explorer Ferdinand Magellan in 1521, who claimed the islands on behalf of Spain. While Santo Niño is meant to be a manifestation of Jesus as a child, in Filipino thought and culture he very much resembles pre-Hispanic spirits, as well as patron saints introduced by the Spanish. Santo Niño shrines appear in churches, restaurants, businesses, and homes throughout the diaspora suggesting that he was much more than a Catholic image. He represents a deity who often shares a business or home shrine with non-Christian statues such as lucky cats, the Buddha, Guanyin, and Guangong, and sometimes the Chinese God of the Earth. He represents how Christian culture has been refashioned through indigenous, Chinese, Malay, and Indonesian influences. He embodies the religious superstructure that defines Christian piety and habits. On the one hand, he stands for Jesus, a pious son of God, and yet, on the other hand, he can be a simple vindictive child who punishes those who ignore him. Santo Niño is a complex character linked to the past before Christianity. As Filipinos engage with Santo Niño in Canada, they connect to him as Jesus, the son of God. They are also connecting to a childlike figure who sometimes uses his spiritual power to punish. A hybrid figure who comes came into being at the beginning of the Spanish colonial moment, he is maintained throughout the American one and continues to be a powerful reminder of Filipino identity and resilience when people leave the Philippines for migrant work. As this paper argues, Santo Niño beliefs, practices, and stories unite people in the diaspora regardless of language, gender, or nation. Santo Niño enables one to think about and understand what it means to be Filipino and living migrant lives in the diaspora today. In this way, the cult of Santo Niño expresses both Catholic orthodoxy and the heterodox Filipino underside that includes the use of magical amulets, healing, visions, and spirit mediumship.

Keywords: ethnography, migration, Philippines, religion

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Authors: Dinara Ikramova, Karin A. Hing, Simon C. F. Rawlinson

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Silicate-substituted hydroxyapatite (SiHA) has been shown to enhance bone regeneration in vivo compared with phase pure stoichiometric hydroxyapatite. Evidence suggests that substrate chemistry dependent formation of a permissive protein layer on the surface of synthetic bone graft substitute materials is key for bioactivity and cell attachment. However, little information is available on whether the substrate chemistry may affect cell migration and recruitment. The aim of this study is to investigate whether or not human Mesenchymal Stem Cells (hMSCs) exhibit a chemotactic response to SiHA porous granules and if it can be linked to either the ion exchange or protein sequestering and enrichment on the surface of the material. 150mg of SiHA granules with 80% total porosity and 20% strut porosity were incubated in 1ml of either Serum Free Media (SFM) or 10% Serum Containing Media (SCM) under static cell culture conditions (37°C, 5% CO2) in absence of cells. Protein sequestering and exchange of calcium, phosphate and silicate ions were analysed at 0.5, 1, 2, 4, 8, 16 and 24 hours with n=12 per time point. Migration of hMSCs in the presence of 150mg of SiHA granules was assessed over 24 hours using a modified transwell migration system in either SFM or SCM (n=6) with 30% serum containing media acting as a positive control. At 24 hours protein sequestering and ionic exchange were analysed, and the number of cells was quantified using a high throughput confocal microscope (IN Cell Analyser 6000). In acellular condition, both calcium and phosphate ion concentrations in media showed a decrease at 24 hours which was greater in SFM than in SCM. This suggests possible formation and precipitation of a bone like apatite on the surface of SiHA. Reduction in this activity observed in SCM indicates that the presence of serum proteins is interfering with the ion exchange at the material and media interface. Adsorbed protein levels showed fluctuation over time followed by sharp decrease at 24 hours, suggesting a possible protein rearrangement on the surface of the material. The ion analysis performed on SFM and SCM after 24-hour incubation with cells in the presence of granules showed a greater reduction in phosphate concentration in both SFM and SCM compared to phosphate levels in acellular condition. Silicate concentration in SCM increased from 1.6mM (absence of cells) to 5.1mM (presence of cells). This indicates that the cells are promoting the uptake of phosphate and release of silicate ions. No significant change was seen in levels of adsorbed proteins in the presence and absence of cells. Further analysis is required to determine whether the species of these proteins change over time. The analysis of cell migration after 24-hour incubation showed more cells migrating towards the granules, 12.7% in SFM and 8.3% in SCM, than in positive control, 4.5% in SFM and 3.6% in SCM respectively. These results suggest that SiHA has a chemotactic activity independent of serum proteins. A property which has not previously been demonstrated for a synthetic bone graft material.

Keywords: cell migration, hMSCs, SiHA, transwell migration system

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Jamileh Darsareh, Mohammad Nikafrooz

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Some teachers and e-content producers, based on their experiences, try to produce educational videos using screen recording software. There are many challenges that they may encounter while producing screen-recorded videos. These are in the domains of technical and pedagogical challenges like designing the roadmap, preparing the screen, setting the recording software and recording the screen, editing, etc. This study is a descriptive study and tries to present some procedures for producing acceptable and well-made videos. These procedures are presented in the form of an algorithm for producing screen-recorded video. This algorithm presents the main producing phases, including design, pre-production, production, post-production, and distribution. These phases consist of some steps which are supported by several technical and pedagogical considerations. Following these phases and steps according to the suggested order helps the producers to produce their intended and desired video by saving time and also facing fewer technical problems. It is expected that by using this algorithm, e-content producers and teachers gain better performance in producing educational videos.

Keywords: e-content producing algorithm, screen-recorded videos, screen recording software, technical and pedagogical considerations

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Authors: Rimmy Yadav, Avtar Singh

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—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

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Authors: Richard Mitchell, Robert Mitchell, Thai Duong, Kyungbin Bae, Daegon Kim, Youngsub Lee, Inho Kim, Inho Park, Hyungseok Lee

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Although X-band radar is commonly used to measure the properties of ocean waves, the use of a higher frequency has several advantages, such as increased backscatter coefficient, better Doppler sensitivity, lower power, and a smaller package. A low-power Ku-band radar system was developed to demonstrate these advantages. It is fully coherent, and it interleaves short and long pulses to achieve a transmit duty ratio of 25%, which makes the best use of solid-state amplifiers. The range scales are 2 km, 4 km, and 8 km. The minimum range is 100 m, 200 m, and 400 m for the three range scales, and the range resolution is 4 m, 8 m, and 16 m for the three range scales. Measurements of the significant wave height, wavelength, wave period, and wave direction have been made using traditional 3D-FFT methods. Radar and ultrasonic sensor results collected over an extended period of time at a coastal site in South Korea are presented.

Keywords: measurement of ocean wave parameters, Ku-band radar, coherent radar, compact radar

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

Abstract:

Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

Abstract:

One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

Abstract:

This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

Procedia PDF Downloads 129