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Bengali Question Answering System Using Seq2Seq Learning Based on General Knowledge Dataset 11

Bengali Question Answering System Using Seq2Seq Learning Bas...

引用

11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Keya, Mumenunnessa Masum, Abu Kaisar Mohammad Majumdar, Bhaskar Hossain, Syed Akhter Abujar, Sheikh Daffodil International University Dept. of CSE Dhaka Bangladesh

ISBN: (纸本)9781728168517

Context-based QA system is a leading research area in NLP. An automatic QA system that can respond to the answer, and which is related to the given context. A deep learning-based model provides a more factual result for today's QA system. Here we introduce a deep learning-based Seq2Seq model for Bengali context-based QA system using general knowledge dataset. Where context and question are part of the encoder and related answer is part of the decoder. All automatic system can discern any language by machine translation. Sequence wise learning is a good solution for those types of automatic system learning. Input tokens are encoded by the encoder and output tokens are decoded by the decoder. Each sequence is stored in LSTM cell that maintains the sequence of input and output. Most of the AI system is developed in different languages. Compared with other languages the Bengali language needs to expand research this field. the major perspective of this research to develop an AI based QA system for the Bengali language. For experiment total, two thousand Bengali general knowledge data is used that also provides a dataset for Bengali QA system. In the dataset, the context contains the main feature for the question. After training our model it gives 99 % accuracy for this dataset and 89% accuracy for validation. the trained model gives a good response in answer prediction. © 2020 IEEE.

关键词： Decoding

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Workload Diffusion Modeling for distributed Applications in Fog/Edge computing Environments 20

Workload Diffusion Modeling for Distributed Applications in ...

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11th ACM/SPEC international conference on Performance Engineering (ICPE)

作者： thang Le Duc Leznik, Mark Domaschka, Jorg Ostberg, Per-Olov Umea Univ Dept Comp Sci S-90187 Umea Sweden Ulm Univ Inst Informat Resource Management D-89081 Ulm Germany

ISBN: (纸本)9781450369916

this paper addresses the problem of workload generation for distributed applications in fog/edge computing. Unlike most existing work that tends to generate workload data for individual network nodes using historical data from the targeted node, this work aims to extrapolate supplementary workloads for entire application / infrastructure graphs through diffusion of measurements from limited subsets of nodes. A framework for workload generation is proposed, which defines five diffusion algorithms that use different techniques for data extrapolation and generation. Each algorithm takes into account different constraints and assumptions when executing its diffusion task, and individual algorithms are applicable for modeling different types of applications and infrastructure networks. Experiments are performed to demonstrate the approach and evaluate the performance of the algorithms under realistic workload settings, and results are validated using statistical techniques.

关键词： Workload generation load propagation load diffusion edge computing fog computing cloud computing

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A Decision Support System of Selecting Groups (Science/ Business Studies/ Humanities) for Secondary School Students in Bangladesh 11

A Decision Support System of Selecting Groups (Science/ Busi...

引用

11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Hasan, Rifat Ovy, Md. Khairul Alam Nishi, Ifrat Zahan Hakim, Md. Azizul Hafiz, Rubaiya Daffodil International University Department of CSE Dhaka Bangladesh

ISBN: (纸本)9781728168517

As education is the only way to turn a person into human resource, every country tries to give her citizens proper scope of bringing out their inner ability by offering the appropriate education. According to the education system of Bangladesh, an 8th grade completing student has to choose a group (science, Business Studies, humanity) for further studies. this group will be his/her initial highway for higher education. But it is a matter of sorrow that, in Bangladesh this crucial event is done by some rumors and some traditional old school ways, which are mostly wrong and destructive. From the perspective of this country, the only way of choosing those groups is previous result. Of course, result is one of the most important attribute, but it should not be the only thing. Again in this country, Science is thought to be superior than other groups. that's why, parents have the tendency to impose this group to their children without knowing their ability and interest and leads them towards an uncertain future. therefore, the aim of this paper is to build a model of group selection by analyzing some random attributes of higher level students who have already gone through this event of selecting groups with the help of data mining and some machine learning algorithms, so that a newly 9th grade student could have the proper direction of selecting a group which is best for him/her. For the purpose of experimentation we have used three machine learning algorithms: Naïve Bayes, Sequential Minimal Optimization (SMO) and Random Forest. Among these algorithms Random forest gives the best prediction result with an accuracy of 84.9%. © 2020 IEEE.

关键词： Students

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A Model for Mobile Fog computing in the IoT 22nd

A Model for Mobile Fog Computing in the IoT

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11th international conference on Intelligent networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Gima, Kosuke Oma, Ryuji Nakamura, Shigenari Enokido, Tomoya Takizawa, Makoto Hosei Univ Tokyo Japan Rissho Univ Tokyo Japan

ISBN: (纸本)9783030290290;9783030290283

In the IoT (Internet of things), millions of devices with sensors and actuators are interconnected with clouds of servers in networks. In order to reduce the traffic of networks and servers in the IoT, types of the fog computing (FC) models are proposed, which are composed of fog nodes which process data from devices and forward the processed data to servers. In most FC models, fog nodes are located in fixed locations and do not move in networks. In this paper, we newly propose a mobile FC (MFC) model where fog nodes communicate with other nodes in wireless networks while moving like vehicles. Here, each fog node processes input data received from other nodes and devices and sends output data obtained by processing the input data to other fog nodes in the opportunistic way. In the opportunistic protocols, only data is exchanged among nodes. We propose an MFC protocol where not only data but also subprocesses are exchanged among nodes so that the electric energy to be consumed by the nodes can be reduced.

关键词： IoT Fog computing model Mobile fog computing (MFC) model Subprocess and Data transmission

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Elastic distributed Rendering Service Placement in Capacitated Cloud/Fog Gaming Systems 11

Elastic Distributed Rendering Service Placement in Capacitat...

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11th international conference on Information, Intelligence, Systems and Applications (IISA)

作者： Tsipis, Athanasios Komianos, Vasileios Oikonomou, Konstantinos Stavrakakis, Ioannis Ionian Univ Dept Informat Corfu Greece Ionian Univ Dept Audio & Visual Arts Corfu Greece Natl & Kapodistrian Univ Athens Dept Informat & Telecommmun Athens Greece

ISBN: (纸本)9780738123462

Fog-assisted cloud computing advances have paved the way for new solutions in online gaming, by integrating all rendering resources directly into the edges of the cloud. However, despite the numerous benefits, these systems still remain prone to network delays, ergo, the discovery of an optimal rendering service placement in the fog layer, that effectively reduces capital deployment cost for the game providers and access latency cost for the game clients, is a challenging issue. In fact, it falls into the category of the well-known (NP-hard) facility location problems. As such, conventional centralized approaches, that require global network knowledge, in most cases are deemed unscalable and cost-prohibitive, thus, distributed solutions must be further explored. the approach followed here, introduces a Rendering Service Allocation Policy (RSAP) to autonomously allocate services towards an optimal placement, based strictly on local information available to the fog renderers regarding their aggregate rendering demands, yielding reduced access latency and deployment costs, whilst meeting their stringent capacity bounds. Simulation results showcase the efficiency of RSAP and verify its elastic behavior under different deployment scenarios.

关键词： Cloud/Fog Gaming Capacitated Facility Location Problems Rendering Service Placement Resource Allocation Cost Reduction

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Robust Graph based Deep Anomaly Detection on Attributed networks

Robust Graph based Deep Anomaly Detection on Attributed netw...

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： G. Victor Daniel M. Venkatesan NITK Surathkal India

the following topics are dealt with: learning (artificial intelligence); pattern classification; neural nets; diseases; feature extraction; regression analysis; text analysis; image classification; support vector mach... 详细信息

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

关键词： Social networking (online) Aggregates Feature extraction Task analysis Anomaly detection

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Data and Subprocess Transmission on the Edge Node of TWTBFC Model 11th

Data and Subprocess Transmission on the Edge Node of TWTBFC ...

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11th international conference on Intelligent networking and Collaborative Systems (INCoS) / 22nd international conference on Network-Based Information Systems (NBiS)

作者： Guo, Yinzhe Oma, Ryuji Nakamura, Shigenari Duolikun, Dilawaer Enokido, Tomoya Takizawa, Makoto Hosei Univ Tokyo Japan Rissho Univ Tokyo Japan

ISBN: (纸本)9783030290351;9783030290344

In our previous studies, the TBFC (Tree-Based Fog computing) model is proposed to reduce the electric energy consumed by fog nodes and servers in the fog computing model. Here, fog nodes are hierarchically structured in a height-balanced tree, where a root node is a cloud of servers and leaf nodes are edge nodes which communicate with devices. Each node receives data from child nodes and sends the processed data to a parent node. In the TWTBFC (Two-Way TBFC) model, is nodes send processed data not only to a parent node but also to each child node. then, edge nodes make a decision on actions of their child actuators. However, in addition to messages to be delivered to servers, more number of messages are transmitted to edge nodes. In this paper, in order to reduce the number of messages which each fog node sends to the child nodes, each node only at some level of the tree collect output data of the other nodes of the same level. the nodes are referred to as aggregate nodes. then, each aggregate node sends the collected data to the descendant edge nodes. Each edge node makes a decision or actions and send actions to the child actuators by using the data.

关键词： Energy-efficient fog computing IoT (Internet of things) Tree-based fog computing (TBFC) model Two-way TBFC (TWTBFC) model Aggregate nod

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Human Behaviour Impact to Use of Smartphones with the Python Implementation Using Naive Bayesian 11

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

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11th international conference on computing, Communication and networking Technologies, ICCCNT 2020

作者： Talha, Iftakhar Mohammad Salehin, Imrus Debnath, Susanta Chandra Saifuzzaman, Mohd. Moon, Ms. Nazmun Nessa Nur, Fernaz Narin Daffodil International University Dept. of Computer Science and Engineering Sobhanbag Mirpur Rd Dhaka1207 Bangladesh Notre Dame University Dep. of Computer Science and Engineering 2/A Toyenbee Circular Rd Dhaka1000 Bangladesh

ISBN: (纸本)9781728168517

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. © 2020 IEEE.

关键词： Smartphones

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NDN-based Emergency Communication over Edge computing Infrastructure 11

NDN-based Emergency Communication over Edge Computing Infras...

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11th international conference on Information and Communication Technology Convergence, ICTC 2020

作者： Tran, Minh-Ngoc Kim, Younghan Soongsil University School of Electronic Engineering Seoul Korea Republic of

ISBN: (纸本)9781728167589

Accurate and reliable communication between emergency teams when dealing with disaster situations plays a decisive part in an effective disaster recovery phase for any country. To support communication between large, frequently roles and location change responder team members, network need to be flexible, scalable, and has mobility built-in feature. Recently, Named Data networking (NDN) has emerged as a promising network solution for those requirements. However, because network infrastructure is usually heavily damaged when disaster happens, quickly installing a network architecture to enable communication over NDN with limited resources is a challenging issue. In this paper, we solve the mentioned problem by proposing our integrated NDN-edge computing system, with KubeEdge as the implementation edge platform. We also introduce an NDN message delivery design that satisfies requirements for emergency communication between responder devices. © 2020 IEEE.

关键词： Edge computing

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DLSDN: Deep Learning for DDOS attack detection in Software Defined networking

DLSDN: Deep Learning for DDOS attack detection in Software D...

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international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Nisha Ahuja Gaurav Singal Debajyoti Mukhopadhyay Bennett University Greater Noida India

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Software defined networking is going to be an essential part of networking domain which moves the traditional networking domain to automation network. Data security is going to be an important factor in this new networking architecture. Paper aim to classify the traffic into normal and malicious classes based on features given in dataset by using various deep learning techniques. the classification of traffic into one of the classes after pre-processing of the dataset is done. We got accuracy score of 99.75% by applying Stacked Auto-Encoder Multi-layer Perceptron (SAE-MLP) which is explained in the paper. thus, the purpose of network traffic classification using deep learning techniques was fulfilled.

关键词： Deep learning Automation Data security Telecommunication traffic Computer architecture Denial-of-service attack Software defined networking

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