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Cloud-RAN Factory: Instantiating virtualized mobile networks with ONAP

Cloud-RAN Factory: Instantiating virtualized mobile networks...

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international conference on the Network of the Future (NOF)

作者： Veronica Quintuna Rodriguez Romuald Corbel Fabrice Guillemin Alexandre Ferrieux Orange Labs 2 Avenue Pierre Marzin Lannion France

ISBN: (数字)9781728180557

ISBN: (纸本)9781728180564

In this demo, we exhibit the negotiation based on the TM Forum framework (Customer Facing Service and Resource Facing Service) and the deployment of a fully virtualized end-to-end mobile network (including a RAN desegregated into Remote Unit, distributed Unit and Centralized Unit) by using ONAP, an open-source network automation platform. the various components of mobile network are containerized and deployed by ONAP on top of Kubernetes. the demo is the first illustration of an end-to-end mobile network, which is fully virtualized up to the remote unit, whose architecture is compatible with the Open-RAN framework, and which implements a PHY layer on the basis of 3GPP 7.3 functional split in Open Air Interface code.

关键词： Cloud computing Automation Communication channels 3GPP Open source software Graphical user interfaces

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Human Behaviour Impact to Use of Smartphones with the Python Implementation Using Naive Bayesian

Human Behaviour Impact to Use of Smartphones with the Python...

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international conference on computing and networking Technology (ICCNT)

作者： Iftakhar Mohammad Talha Imrus Salehin Susanta Chandra Debnath Mohd. Saifuzzaman Nazmun Nessa Moon Fernaz Narin Nur Daffodil International University Sobhanbag Mirpur Rd Dhaka Notre Dame University 2/A Toyenbee Circular Rd Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

A change of behavior in special groups and many sustainable smart populations increasing day by day for excessive uses of smartphones. In recent years, the use of smartphones and mental imbalances have become a major problem with increasing negative effects. In our study, we find out the major problem of the negative side and its different sources like mental imbalance, stress, depression, loneliness, etc. Bayes' theorem and classifier, support vector machine, special data set of human behavior, and probability are used to calculate accuracy. For collecting data from three major sections, we use the physical methods, virtual methods, and medical reports. So, a vast data set is trained by data to compare method, and also probability is used for predicting the validity of the data model. Naive Bayes' theorem accurate 71% positive which is indicated the negative impact of human behavior. Based on the SVM classifier, we separate the barrier between the impact of positive and negative data. In SVM, we set up a parameter to measure negative and positive values. Python library function is a major component to calculate all instructions and also use for data training. Finally, we compare the results obtained by our proposed specialization with the results obtained from the three baseline landmarks.

关键词： Support vector machines Smart phones Hidden Markov models Stress Computer science Classification algorithms Decision trees

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How Can Machine Learning Impact on Wireless Network and IoT? – A Survey

How Can Machine Learning Impact on Wireless Network and IoT?...

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international conference on computing and networking Technology (ICCNT)

作者： Swarnalina Laha Nilanjan Chowdhury Raja Karmakar Techno International New Town INDIA

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Machines can be trained by human beings by feeding them massive amount of data, like examples and instructions. they have to learn without human interventions. the Internet of things (IoT) is still in its outset and is in the developing front. IoT consisting of devices/machines with diverse sensors associated together in wireless networks, needs great amount of security for avoiding unauthorized access to the network as it collects and transmit data packets. With industrial fields showing much interest in the forefront, intrusion threats can make it vulnerable. In this paper, we are addressing several positive measures regarding the use of machine learning (ML) modalities like supervised learning (SL), unsupervised learning (UL), semi- supervised learning (SSL), reinforcement learning (RL), support vector machines (SVM) which are used for training IoT devices. this paper also addresses a brief survey of the scenarios where machine learning algorithms have been applied in various IoT devices and networks such as signal authentication, security, network flow, information retrieval, traffic management, spectrum sensing. It also indicates the necessity of surveying the scattered works on machine and deep learning applications for various aspects like security, congestion control over wireless computer networks, embedded sensor systems for IoT applications. Several limitations of existing researches and a number of open research issues which fellow researchers may find useful in the future have also been discussed.

关键词： Internet of things Machine learning Support vector machines Wireless sensor networks Sensors Wireless networks Machine learning algorithms

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CIFAS: Community Inspired Firefly Algorithm with fuzzy cross-entropy for feature selection in Twitter Spam detection

CIFAS: Community Inspired Firefly Algorithm with fuzzy cross...

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international conference on computing and networking Technology (ICCNT)

作者： E. Elakkiya S. Selvakumar R. Leela Velusamy National Institute of Technology Tiruchirappalli India IIIT Una Himachal Pradesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Social network sites such as Facebook, Twitter, YouTube, etc., are very popular among internet users for information sharing and communication. this popularity also attracts cybercriminals to spread their malicious activities including spams using social networks. Spam may contain unsolicited information or malicious links that may harm Twitter users and make them feel insecure. So there is a crucial need for effective spam detection which requires the distinctive features that clearly portray the spammer behavior. this is accomplished by information theoretic-based feature selection methods, as these methods select the informative features that retain the original meaning. Most of the existing information theory-based feature selection methods focus on retaining the features that contain more information while removing features that contain less information for improving the performance. this may lead to the information loss. Also, the features that are individually less significant may be useful when combined with other features. So, Community Inspired Firefly Algorithm for Spam detection (CIFAS) is proposed to handle combination search for the features that provide good performance using fuzzy cross entropy as the fitness function. Fuzzy cross-entropy is used in this work, to preserve the information contained in the selected feature subset equally to the information contained in full feature set. From the experimental result, it has been proven that the proposed CIFAS offers defense against spam similar to the original feature set and performs better than the existing approaches in terms of accuracy, false-positive rate, and F measure for the two standard twitter datasets.

关键词： Feature extraction Social networking (online) Blogs Entropy Mutual information Mathematical model Fuzzy sets

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Logical Unit Design using Reversible HSG1 Gate and Its Application in ALU Design

Logical Unit Design using Reversible HSG1 Gate and Its Appli...

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international conference on computing and networking Technology (ICCNT)

作者： Harsh Pallav Govind Rao Shiva Dwivedi Thapar Institute of Engineering & Technology Patiala India Buddha Institute of Technology Gorakhpur India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Due to reduced size and increase in component density, controlling heat dissipation is becoming a big challenge for chip designers and manufacturers and thus researchers, scientists, and engineers throughout the world are looking for newer technologies for remedy. One such technology that is providing a solution to the above-stated problem is Reversible Logic Technology (RL T). RLT is a new paradigm and finding its application in Quantum computing, Nano-Electronics, Cryptography, Low-Power Low-Dissipation circuit designs. In this paper based on RLT, 16×16 Harsh Shiva Gate 1 (HSG1) is proposed. HSG1 gate can be programmed for performing 16, 1024, and 16384 logical output operations using 4, 10, and 14 programmable input pins respectively on two operand A and B in a single clock cycle. HSG1 gate has 2 Output Modes - Simultaneous and Cascade Mode. In Simultaneous Mode, a total of 14 programmable and 2 operand input pins are available for performing 65536 logical output operations at the output pins from x0 to x15. While in Cascade Mode, based on 4 selection input pins, X, Y, N, and P, 16 logical output operations are performed at the output pin L OUT . the main advantage of cascade mode is using L OUT as the input to the control unit of ALU when HSG 1 gate is used as a logical unit in designing of ALU. It has been also proved that the proposed HSG1 gate is better than its counterpart for implementing logical unit in terms of garbage output, the number of gates, and logical operations to be performed. All the results have been verified using VHDL simulation.

关键词： Logic gates Pins VHDL Transistors Very large scale integration Quantum computing Programming

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

引用

11th international conference on Machine Learning and computing, ICMLC 2019

ISBN: (纸本)9781450366007

the proceedings contain 96 papers. the topics discussed include: model loss and distribution analysis of regression problems in machine learning;quantifying customer review by integrating multiple source of knowledge;a comparative study on machine learning approaches to thunderstorm gale identification;a robust mature tomato detection in greenhouse scenes using machine learning and color analysis;distributed machine learning over directed network with fixed communication delays;machine learning techniques for heart disease datasets: a survey;a survey of feature selection for vulnerability prediction using feature-based machine learning;a review of methods used in machine learning and data analysis;and a study on the performance evaluation of machine learning models for phoneme classification.

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Retinal Blood Vessel Segmentation by Multi-channel Deep Convolutional Autoencoder 13th

Retinal Blood Vessel Segmentation by Multi-channel Deep Conv...

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Int Joint Conf of the 13th Int Conf on Soft Comp Models in Ind and Environm Applicat (SOCO) / 11th Int Conf on Computat Intelligence in Secur for Informat Syst (CISIS) / 9th Int Conf on European Transnat Educ (ICEUTE)

作者： Ortiz, Andres Ramirez, Javier Cruz-Arandiga, Ricardo Garcia-Tarifa, Maria J. Martinez-Murcia, Francisco J. Gorriz, Juan M. Univ Malaga Commun Engn Dept Malaga 29004 Spain Univ Granada Dept Signal Theory Commun & Networking Granada 18060 Spain

ISBN: (纸本)9783319941202;9783319941196

the evaluation and diagnosis of retina pathologies are usually made by the analysis of different image modalities that allows to explore its structure. the most popular retina image method is the retinography, a technique to show the retina and other structures in the fundus of the eye. this paper deals with an important stage of the retina image processing for a diagnosis tool which aims to show the blood vessel structure. Our proposal is based on a deep convolutional neural network, that avoids any preprocessing stage such as gray scale conversion, histogram equalization, and other image transformations that determine the final result. thus, we obtain the blood vessel segmentation directly from the original RGB color retinography image. the results obtained with our method are comparable to the state-of-the art methods but using a smaller network with less memory and computation requirements. Our approach has been assessed using the DRIVE database.

关键词： Blood vessels

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Classification Improvement for Parkinson's Disease Diagnosis Using the Gradient Magnitude in DaTSCAN SPECT Images 13th

Classification Improvement for Parkinson's Disease Diagnosis...

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作者： Castillo-Barnes, Diego Segovia, Fermin Martinez-Murcia, Francisco J. Salas-Gonzalez, Diego Ramirez, Javier Gorriz, Juan M. Univ Granada Dept Signal Theory Networking & Commun Granada 18071 Spain

ISBN: (纸本)9783319941202;9783319941196

In this work, we propose a novel imaging preprocessing step based on the use of the gradient magnitude for medical DaTSCAN SPECT images. As Parkinson's Disease (PD) is characterized by a marked reduction of intensity at striatum area, measuring intensities in this region is considered as a good marker for this neurological disorder. To extend this idea, we have been studying how quick these values decrease. A simple way to do this was using the gradient of each image. Applying Machine Learning algorithms, we have classified the gradient images and obtained an accuracy improvement of almost 2%. these results prove that the gradient magnitude is even a better marker for PD diagnosis and opens the door to new future investigations about this pathology.

关键词： Parkinson's Disease Gradient SVM Classification Machine Learning alpha-Stable distributions Parkinson's Progression Markers Initiative (PPMI) SPECT DaTSCAN Neuroimaging

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Toward an Enhanced Bengali Text Classification Using Saint and Common Form

Toward an Enhanced Bengali Text Classification Using Saint a...

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international conference on computing and networking Technology (ICCNT)

作者： Nushrat Jahan Ria Sharun Akter Khushbu Mohammad Abu Yousuf Abu Kaisar Mohammad Masum Sheikh Abujar Syed Akhter Hossain Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Language processing tool has been strengthened by the measurements of text classification. Due to this concern many approaches investigate through the text documentation problem. Behalf of this conception we have focused on our bengali text written format. A long period of time bengali people are familiar with two bengali accents about saint and common form. With concern text document processing becomes easier to translate. Most well-known supervised six classifiers we have used to classify these two bengali forms of saint and common. Classifiers prediction will determine whether it is saint or common form. Collection of text documents more than 1200 mix sentences grabbed from bengali written sources. Each text needs preprocess to classify the text into a solid form of output. Before applying algorithms there has been some prerequisite ability to split the sentences, stemming, remove stop words, construct contraction. Ending with preprocess, the processed bengali text had been taken as input on machine learning classifiers that have raised very spontaneous outcomes over the accent of bengali data. Foremost output produced by NB classifier to identify the actual form about 77% on bengali text of saint and common form. Apart from that, other ML classifiers XGB, RB, DT, SVC, KNN showed nearly prediction upto 77% -64% accuracy which we have proposed in different segments of this paper.

关键词： Text categorization Natural language processing Writing Machine learning Training Data models Support vector machine classification

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the vive controllers vs. leap motion for interactions in virtual environments: A comparative evaluation 11th

The vive controllers vs. leap motion for interactions in vir...

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11th international KES conference on Intelligent Interactive Multimedia: Systems and Services, KES-IIMSS 2018

作者： Caggianese, Giuseppe Gallo, Luigi Neroni, Pietro Institute for High Performance Computing and Networking National Research Council of Italy Naples Italy

ISBN: (纸本)9783319922300

In recent years, virtual reality technologies have been improving in terms of resolution, convenience and portability, fostering their adoption in real life applications. the Vive Controllers and Leap Motion are two of the most commonly used low-cost input devices for interactions in virtual environments. this paper discusses their differences in terms of interaction design, and presents the results of a user study focusing on manipulation tasks, namely Walking box and blocks, Block tower and Numbered cubes tasks, taking into account both quantitative and qualitative observations. the experimental findings show a general preference for the Vive Controllers, but also highlight that further work is needed to simplify complex tasks. © Springer international Publishing AG, part of Springer Nature 2019.

关键词： Human computer interaction

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