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International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Erdal Başaran Abdülkadir Şengür Zafer Cömert Ümit Budak Yüksel Çelık Subha Velappan Dept. of Computer Engineering Karabük University Karabük Turkey Dept. of Electrical and Electronics Eng. Firat University Elazlğ Turkey Dept. of Software Engineering Samsun University Samsun Turkey Dept. of Electrical and Electronics Eng. Bitlis Eren University Bitlis Turkey Dept. of Computer Science and Eng. Manonmaniam Sundaranar University Tirunelveli India

Otitis Media (OM) is the general name of middle ear inflammation. In order to diagnose this disease, it is important to examine the middle ear tympanic membrane (TM) by a standard otoscopy device. In recent years, biomedical image processing and machine learning algorithms have become quite effective in diagnostic applications. To this aim, we propose a combination of gray-level co-occurrence matrix (GLCM) and artificial neural network (ANN) to distinguish acute tympanic membrane otoscope images from normal images. For the experiment, totally 223 middle ear otoscope images were collected from the volunteer patients admitted to Van Özel Akdamar Hospital. In the experimental study, the texture features are obtained separately from R, G, and B channels and then consolidated. In addition to the texture features provided by GLCM, the average values of each channels of the otoscope images are taken into account so as to determine whether the otoscope image belongs to acute or normal class. Lastly, this feature set is applied as the input to ANN. By experimental studies, we achieved 76.14% accuracy and with this model, we achieved promising results in diagnosing normal and acute OM disease. Consequently, the texture features were found as useful to classify normal and acute OM disease.

关键词： Artificial neural networks Feature extraction Biomembranes Ear Diseases Measurement

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Efficient Ising Model Mapping for Induced Subgraph Isomorphism Problems Using Ising Machines

Efficient Ising Model Mapping for Induced Subgraph Isomorphi...

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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Natsuhito Yoshimura Masashi Tawada Shu Tanaka Junya Arai Satoshi Yagi Hiroyuki Uchiyama Nozomu Togawa Dept. of Computer Science and Communications Engineering Waseda University Green Computing System Research Organization Waseda University NTT Software Innovation Center

Ising machines have attracted attention as they are expected to solve combinatorial optimization problems at high speed with Ising models corresponding to those problems. An induced subgraph isomorphism problem is one of the decision problems, which determines whether a specific graph structure is included in a whole graph or not. The problem can be represented by equality constraints. By using the penalty functions correspond to the equality constraints, we can utilize an Ising machine to the induced subgraph isomorphism problem. The induced subgraph isomorphism problem can be seen in many practical problems, for example, finding out a particular malicious circuit in a device or particular network structure of chemical bonds in a compound. However, due to the limitation of the number of spin variables in the current Ising machines, reducing the number of spin variables is a major concern. Here, we propose an efficient Ising model mapping method to solve the induced subgraph isomorphism problem by Ising machines. Our proposed method theoretically solves the induced subgraph isomorphism problem. Furthermore, the number of spin variables in the Ising model generated by our proposed method is theoretically smaller than that of the conventional method. Experimental results demonstrate that our proposed method can successfully solve the induced subgraph isomorphism problem using the Ising-model based simulated annealing.

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Investigation of Empirical Wave Propagation Models in Precision Agriculture

Investigation of Empirical Wave Propagation Models in Precis...

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2017 Malaysian Technical Universities Conference on engineering and Technology, MUCET 2017

作者： Sabri, N. Mohammed, S.S. Fouad, Sarah Syed, A.A. Al-Dhief, Fahad Taha Raheemah, Auda Computer and Communication Engineering School University Malaysia Perlis Malaysia Laser and Optoelectronics Engineering Dept. Malaysia Microelectronic Engineering School University Malaysia Perlis Malaysia Center of Software Technology and Management University Kebangsaan Malaysia Malaysia Computer Engineering Dept. College of Engineering ALMuthana University Iraq Computer Eng. Dept. AlNahrain University Iraq

Wireless Sensor Networks have highly proved its contribution in precision agriculture. Communication channel modelling investigation is a highly demanded to achieve a successful communication system where a good wave propagation model is crucially needed. Precision agriculture degrades the traveling waves in various forms in addition to the effects of the large-scale path losses models. This paper reviews the most known theoretical large-scale path losses models such as free space (FSPL) and Plane earth (PE) models as well as the vegetation models represented by Weissberger, ITU-R, FITU-R and COS235 models. Indeed, this work illustrates the effects of many factors on the total path losses such as separation distance between transceivers, antenna heights and the dept. of vegetation that presence in the path propagation. In conclusion, the total path loss is computed based on large-scale path losses and the vegetation losses in protected vegetation environment. © The Authors, published by EDP Sciences, 2018.

关键词： Vegetation

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Toponym identification in epidemiology articles - A deep learning approach

arXiv

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arXiv 2019年

作者： Davari, Mohammad Reza Kosseim, Leila Bui, Tien D. Dept. Computer Science and Software Engineering Concordia University MontrealQCH3G 1M8 Canada

When analyzing the spread of viruses, epidemiologists often need to identify the location of infected hosts. This information can be found in public databases, such as GenBank [3], however, information provided in these databases are usually limited to the country or state level. More fine-grained localization information requires phylogeographers to manually read relevant scientific articles. In this work we propose an approach to automate the process of place name identification from medical (epidemiology) articles. The focus of this paper is to propose a deep learning based model for toponym detection and experiment with the use of external linguistic features and domain specific information. The model was evaluated using a collection of 105 epidemiology articles from PubMed Central [33] provided by the recent SemEval task 12 [28]. Our best detection model achieves an F1 score of 80:13%, a significant improvement compared to the state of the art of 69:84%. These results underline the importance of domain specific embedding as well as specific linguistic features in toponym detection in medical journals. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Hull Parametric Modeling of a Small Waterplane Area Twin Hull ships

Hull Parametric Modeling of a Small Waterplane Area Twin Hul...

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International Conference on CAD Systems in Microelectronics (CADSM)

作者： Anzhela Boiko Oleksandr Bondarenko Yevhen Davydenko Dept. of Computer Engineering Petro Mohyla Black Sea National University Mykolaiv Ukraine Dept. of Theory and Ship Design Admiral Makarov National University of Shipbuilding Mykolaiv Ukraine Dept. of Software Engineering Petro Mohyla Black Sea National University Mykolaiv Ukraine

The paper proposes a method of a hull parametric modeling of a small waterplane area twin hull (SWATH) ship. This approach allows you to create and transform the hull of the ship with desired parameters in a quick and effective way. The presented method gives a complete mathematical description of the hull surface with the help of geometric optimization. The authors have proposed two SWATH parametric models both for one strut and for two struts on each lower hull, modeled with the use of T-FLEX CAD system. The use of hull parametric models of SWATH ships allows calculating navigation and strength properties of the ship, optimizing the hull form and finding the most successful design solutions before proceeding with detailed design.

关键词： Marine vehicles Solid modeling Shape Parametric statistics Three-dimensional displays Nose Mathematical model

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Aptamers-based gold-micro-array for high-selective detection of bacteria using fluorescence microscopy

Aptamers-based gold-micro-array for high-selective detection...

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2018 IEEE Life Sciences Conference, LSC 2018

作者： Salami, M. Abadi, M.H. Shahrokh Shahrokh Abadi, Kh. Nejad Sawan, M. Dept. Electrical and Computer Engineering Hakim Sabzevari University Sabzevar Iran Dept. Biology Islamic Azad University Mashhad Iran Polystim Neurotech Lab Polytechnique Montreal MontrealQc Canada

ISBN: (纸本)9781538667095

The monitoring of Escherichia coli (E. coli) bacteria in food and water is an effective preventive measure in controlling the outbreaks of serious food-related diseases. Moreover, the accurate detection of its early stage of the bacteria can ensure the public health and safety. In this study, a target-selective aptamer-based platform is proposed as a reliable procedure for the detection of the E. coli in Phosphate-buffered saline (PBS) using fluorescent microscopy. The results show that the aptamer sequences, immobilized on an array of Au-micro-squares, are very high selective towards the target bacteria cells. This platform, presented for the first time, can be potentially used to detect different kinds of cells simultaneously. Also, an important cell-counting application, based on Neubauer Lam high accuracy method, is proposed and implemented and validated by experimental results. © 2018 IEEE.

关键词： Escherichia coli

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Road user abnormal trajectory detection using a deep autoencoder

arXiv

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arXiv 2018年

作者： Roy, Pankaj Raj Bilodeau, Guillaume-Alexandre LITIV lab Dept. of computer & software eng Polytechnique Montréal

In this paper, we focus on the development of a method that detects abnormal trajectories of road users at traffic intersections. The main difficulty with this is the fact that there are very few abnormal data and the normal ones are insufficient for the training of any kinds of machine learning model. To tackle these problems, we proposed the solution of using a deep autoencoder network trained solely through augmented data considered as normal. By generating artificial abnormal trajectories, our method is tested on four different outdoor urban users scenes and performs better compared to some classical outlier detection methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Trajectories

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Performance Evaluation of Parallel Particle Swarm Optimization for Multicore Environment

Performance Evaluation of Parallel Particle Swarm Optimizati...

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2018 International Conference on Advanced Science and engineering, ICOASE 2018

作者： Abdullah, Eman Abdulaziz Ahmed Saleh, Ibrahim Al Saif, Omar Ibrahim Computer Science Dept. Mosul University Mosul Iraq Dept. of Software Engineering Mosul University Mosul Iraq Technical Institute in Mosul Northern Technical University Mosul Iraq

ISBN: (纸本)9781538666968

Particle swarm optimization (PSO) has become universal due to its simplicity and effectiveness in solving many problems in various applications with low computational cost. This algorithm consumes time as dealing with large tasks programs. The main goal of this paper is to introduce a parallel particle swarm optimization (PPSO) on multi-core processing kernel to decrease the determination. In order to ease transfer information among particles of shared area and exchange information by switching randomly. Most of serial PSO algorithms allow updating information among particles which takes a long time during the implementation period. The algorithm was applied to the standard optimization test set CEC (Congress on Evolutionary Computation) 2014 and gave good results compared to the previous algorithm. The empirical results show the execution time of Shared-PSO is more efficient than the serial PSO's. The proposed algorithm using a multicore CPU technique to improve it via parallelization and enhanced the efficiency of an algorithm by increase the range of PSO application. © 2018 IEEE.

关键词： Particle swarm optimization (PSO)

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Joint long-term cache allocation and short-term content delivery in green cloud small cell networks

arXiv

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arXiv 2019年

作者： Wu, Xiongwei Li, Qiang Li, Xiuhua Leung, Victor C.M. Ching, P.C. Dept. of Electronic Engineering Chinese University of Hong Kong Shatin Hong Kong School of Info. & Comm. Eng. University of Electronic Science and Technology of China Chengdu China School of Big Data & Software Engineering Chongqing University Chongqing China College of Computer Science & Software Engineering Shenzhen University Shenzhen China Dept. of Electrical & Computer Engineering University of British Columbia Vancouver Canada

Recent years have witnessed an exponential growth of mobile data traffic, which may lead to a serious traffic burn on the wireless networks and considerable power consumption. Network densification and edge caching are effective approaches to addressing these challenges. In this study, we investigate joint long-term cache allocation and short-term content delivery in cloud small cell networks (C-SCNs), where multiple smallcell BSs (SBSs) are connected to the central processor via fronthaul and can store popular contents so as to reduce the duplicated transmissions in networks. Accordingly, a long-term power minimization problem is formulated by jointly optimizing multicast beamforming, BS clustering, and cache allocation under quality of service (QoS) and storage constraints. The resultant mixed timescale design problem is an anticausal problem because the optimal cache allocation depends on the future file requests. To handle it, a two-stage optimization scheme is proposed by utilizing historical knowledge of users' requests and channel state information. Specifically, the online content delivery design is tackled with a penalty-based approach, and the periodic cache updating is optimized with a distributed alternating method. Simulation results indicate that the proposed scheme significantly outperforms conventional schemes and performs extremely close to a genie-aided lower bound in the low caching region. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel state information

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Communication Management in Global software Development Projects 4

Communication Management in Global Software Development Proj...

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4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018

作者： Jusoh, Yusmadi Yah Haizan Nor, Rozi Nor Mahmood, Bashar Amir Wafeeq, Mustafa Thamir Ali, Mohamed Abdullahi Baihaqi Jusoh, Muhammad Nur Dept. of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Selangor43400 Malaysia

ISBN: (纸本)9781538638125

Many organizations that have the global software development (GSD) projects use communication technologies to connect their virtual teams. However, the virtual team faces various challenges and issues in the process of the GSD. One of the significant challenges is obtaining an efficient communication among team members. This study focuses on the communication factors among the virtual teams highlighted in the literature. The communication factors are related to the temporal distances, geographical distances, socio-cultural, access to training, technological problems that hindering communications, the communication within the status of development process, personal communication skills and language differences. The objective of this study is to examine the communication factors and identify the related issues which are commonly occurring between the virtual teams in the global software development. A survey was conducted in different sectors. The findings indicate that some of important points related to the communication factors contribute to the success of the GSD. © 2018 IEEE.

关键词： Project management

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