Day 1 28/11/2019
Room #1

Opening of the Conference 08:30 - 09:00

Keynote Speech given by Prof. Herwig Unger 09:00 - 09:45

Chaired by Prof. Phayung Meesad

Coffee Break 09:45 - 10:00

Keynote Speech given by Prof. Phayung Meesad 10:05 - 10:50

Chaired by Prof. Herwig Unger

Session One: Context-Aware Systems and Applications 10:55 - 12:30

Chaired by Prof. Waralak V. Siricharoen
10:55 - 11:10
Planquarium A ContextAware RuleBased Indoor Kitchen Garden

Planquarium is a contextaware indoor kitchen garden system where a user can grow fresh plants and vegetables without prior knowledge Further the Planquarium will take care of the plants that are inside it using a RuleBased ContextAware environment that is capable to monitor different aspects of the plant and can provide an ideal environment for the plant inside Different plants have different requirements therefore we have integrated profiling systems so that a person can select a plant and the Planquarium will adjust itself accordingly Initially we have deployed temperature humidity moisture water and lightArtificial sunlight full spectrum sensors to monitor the plants In the future we can further add soil quality monitors to optimum growth Planquarium is suitable for congested smart cities smart homes and for people who care for organic food
Authors: ijaz uddin (University of Nottingham), altaf uddin (AWKUM), rahat khan (UET peshawar), Rashid Naseem (CUSIT), Arshad Ahmad (University of Sawabi),
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11:15 - 11:30
Highthroughput Machine Learning Approaches for Network Attacks Detection on FPGA

The popularity of applying Articial Intelligence to perform prediction automation tasks has become one of the most conspicuous trends in computer science However existent researches in this eld are rarely meet the realtime criteria because of heavy computational tasks In this work we proposed to deploy machine learning algorithms which are classication techniques on FPGA platform The first prototype version based on the architecture with VerilogHDL is trained and tested by Decision Tree and Neural Network model built based on NSLKDD dataset Our experiments with NetFPGA10G platforms show that the Neural Network core can detect attacks at 178 Gbps and up to 986 Gbps with packets size from 64B to 1500B which thoroughly faster the Geforce GTX 850M GPU and i5 8th generation CPU 11x and 83x times respectively The Neural Network classifier system can function at 104091 MHz and achieve the accuracy at 873
Authors: Duc-Minh Ngo (Ho Chi Minh City University of Technology), Binh Tran-Thanh (Ho Chi Minh City University of Technology (HCMUT)), Truong Dang (Ho Chi Minh City University of Technology), Tuan Tran (Ho Chi Minh City University of Technology), Thinh Tran Ngoc (Ho Chi Minh City University of Technology), Cuong Pham-Quoc (Ho Chi Minh City University of Technology (HCMUT) - Vietnam),
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11:35 - 11:50
ContextAware Mobility based on PiCalculus in Internet of Thing A Survey

Nowadays the computing is becoming faster and faster to support very other scientific areas Internet of Thing IoT is taking much advantage from it At the beginning of IoT the static things joined in IoT such as cameras sensors and vending machines Due to the progress of computing science IoT is expanding on mobile things such as cars patients cellphones and other mobile things for traffic controlling health care or getting information The network of mobile things is called as Internet of Mobile Things IoMT There are some problems to be solved in IoMT as Security and Privacy Mobile Data Collection and Analysis The data collected from the mobile things can help to improve the security and privacy better or using for special purposes To get the data of mobile things moved from one cluster to another one we need an algorithm to solve following things mobility of mobile nodes and changing in number of the mobile nodes The picalculus is one solution for this problem Picalculus is introduced by Milner as a formal language for modeling and verifying system requirements In this paper a survey is performed on picalculus for IoMT and other related calculi
Authors: Phan Cong Vinh (Nguyen Tat Thanh University (NTTU)), Vu Tuan Anh (IUH, Vietnam), Pham Quoc Cuong (HCMUT, Vietnam),
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11:55 - 12:10
An Approach of Taxonomy of Multidimensional Cubes Representing Visually Multivariable Data

In data visualization graphs representing multivariable data on multidimensional coordinates shaped cubes enable human to understand better the significance of data There are various types of cubes for representing different datasets The paper aims at classifying kinds of cubes to enable human to design cubes representing multivariable datasets Mathematically the functional relations among five groups of variables result in the way to structure cubes The paper classifies cubes as three kinds by the characteristics of datasets including nonspace 2Dspace and 3Dspace multidimensional cubes The nonspace multidimensional cubes are applied for nonspace multivariable datasets with variables of objects attributes and time The 2Dspace multidimensional cubes are applied for the datasets of movers or objects located on ground at time units The 3Dspace multidimensional cubes are applied for the datasets of flyers or objects positioned in elevated space at time units The correlation in space andor time shown on the cubes enables human to discover new valuable information
Authors: Phuoc Tran (Open University, Hochiminh City, Vietnam), Hong Nguyen (Rubber Industrial College, 1428 Phuriengdo, Dongxoai, Binhphuoc Province, Vietnam), Truong Le (Open University, Hochiminh City, Vietnam), Dang Pham (Nguyen Tat Thanh University),
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12:15 - 12:30
PREDICTING OF FLOODING IN THE MEKONG DELTA USING SATELLITE IMAGES

Flooding is a natural risk large floods have occurred almost every year These are major issues that researchers are interested and to identify flooded areas or assess the risk of flooding the researchers using image LiDAR or image RADAR to flood mapping flood risk management observation and change detection in floodable area However flood modeling or flood assessment dont solve the problem of flood risks Therefore in this paper we propose a new approach of processing methodology based on time series analysis that enables predicting of the floodable areas in the Mekong Delta using new satellite images such as Lansat 7 ETM Landsat 8 OLI and sentinel2 MSI
Authors: Toan Huynh Phung (CTU, Vietnam), Hiep Huynh (CTU, Vietnam), Tran Loi (FSoft Cantho, Vietnam), Simona Niculescu (Université de Bretagne Occidentale - UBO),
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Lunch 12:30 - 14:00

Keynote Speech given by Prof. Waralak V. Siricharoen 14:05 - 14:50

Chaired by Prof. Herwig Unger

Coffee Break 14:50 - 15:05

Session Three: Context-Aware Systems and Applications 15:10 - 16:45

Chaired by Prof. Herwig Unger
15:10 - 15:25
Declarative Approach to Model Checking for Contextaware Applications

Systems need to be formally verified to ensure that their claimed properties hold at all times of system operation Deterministic Finite State Machines FSM are widely used as model checkers to verify system properties However for contextaware systems that have regular inputs and contextual inputs FSM models become more complex and less intuitive and do not precisely represent the system behavior In this paper we use simple examples to introduce the declarative reasoning framework Contelog a theoretically and practically well grounded work in progress as a complementary approach that can be used to represent reason verify datacentric and contextual properties of contextaware systems
Authors: Ammar Alsaig (Concordia University), Vangalur Alagar (Concordia University), Shiri Nematollaah (Concordia University),
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15:30 - 15:45
IoTbased AirPollution Hazard Maps Systems for Ho Chi Minh City

Hazard map is a major part in the architecture of a Smart City which gives citizens an overview of a particular hazard in different areas within the city In this paper we research and implement an IoTbased AirPollution Hazard Map System for Ho Chi Minh City The system consists of Sensor and Gateway nodes Server and maps The collected sensor values include temperature dust CO and CO2 Datacollected by Sensor node is transmitted to Gateway and then to Server Server saves the received data to database and queries according to request from users A web application have been built to display the data and give users an overview of air pollution state around them
Authors: Anh Nguyen (Ho Chi Minh City University of Technology), Ri Le (Ho Chi Minh City University of Technology), Loc Nguyen (Ho Chi Minh City University of Technology), Cuong Pham-Quoc (Ho Chi Minh City University of Technology (HCMUT) - Vietnam),
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15:50 - 16:05
Integrating Retinal Variables into Graph Visualizing Multivariate Data to Increase Visual Features

The efficiency of a graph visualizing multivariate data is not only subjectively evaluated by human visual perception but also objectively estimated by visual features of graph For a designed graph it is necessary to improve visual features to enable human to extract better information from data Integrating retinal variables into graph is an approach to increasing visual features of graph In this study the constituents of graph are grouped into planar mark classes by qualitative and quantitative characteristics The retinal variables are studied and structured to integrate into planar mark classes A process of five steps is proposed to increase visual features by integrating retinal variables into graph The process is illustrated with two case studies increasing visual features of bus spacetime map with qualitative planar mark classes and increasing visual features of the graph representing the data of handfootmouth epidemic in Binhduong with qualitative and quantitative planar mark classes
Authors: Phuoc Tran (Open University, Hochiminh City, Vietnam), Hong Nguyen (Rubber Industrial College, 1428 Phuriengdo, Dongxoai, Binhphuoc Province, Vietnam), Ngoc Cam Huynh (Vovankiet High School, Kiengiang, Vietnam), My Thuan Pham (Open University, Hochiminh City, Vietnam), Van Anh Tran (College of Economics, Hochiminh City, Vietnam), Dang Pham (Nguyen Tat Thanh University), Lieu Le (Thu Dau Mot University),
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16:10 - 16:25
A FCABased Concept Clustering Recommender System

Recommender systems are information filtering software which is capable of resolving the recent issue of internets information overload The recommender system generate the recommendation more suitably based on the data gathered either implicitly like user profile click information web log history or explicitly like ratings scale 15 likes dislikes feedbacks The most important challenge to the recommender system is the growing number of online users making it a high dimensional data which leads to the data sparsity problem where the accuracy of recommendation depends on the availability of the data In this paper a new approach called formal concept analysis is employed to handle the high dimensional data and a FCAbased recommender algorithm Userbased concept clustering recommendation algorithm UBCCRA is proposed The UBCCRA out performs by accurately generating the recommendation for the groupbased users called cluster users The experimental result is shown to prove the cluster recommendation with good result
Authors: Chemmalar Selvi G (VIT Vellore), Lakshmi Priya G.G. (VIT Vellore), Rose Joseph (Christ Academy Institute For Advanced Studies),
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16:30 - 16:45
Hedge Algebra Approach For SemanticsBased Algorithm To Improve Result Of Time Series Forecasting

During the recent years many different methods of using fuzzy time series for forecasting have been published However computation in the linguistic environment one term has two parallel semantics one represented by fuzzy sets computationsemantics it humanimposed and the rest contextsemantic is due to the context of the problem If the latter semantics is not paid attention despite the computation accomplished high level of exactly but it has been distorted about semantics That means the result does not suitable the context of the problem Hedge Algebras an algebraic Approach to domains of linguistic variables unifying the above two semantics of each term is the basis of convenient calculation in the language environment and does not distort the semantics of terms A new approach is proposed through a semanticbased algorithm focus on two key steps partitioning the universe of discourse of time series into a collection of intervals and mining fuzzy relationships from fuzzy time series that outperforms accuracy and friendliness in computingThe experimental results forecasting enrollments at the University of Alabama and forecasting TAIEX Index demonstrate that the proposed method significantly outperforms the published ones about accurate level the ease and friendliness on computing
Authors: Yen Phạm Thế (), Loc Vu (Giadinh University, Ho Chi Minh City, Vietnam), Dung Quach (Van Hien University,Ho Chi Minh City, Vietnam),
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Free Time 17:00 - 19:00

Gala Diner & Best Papers Awards 19:00 - 21:00

Room #2

Session Two: Nature of Computation and Communication 10:55 - 12:30

Chaired by Prof. Phan Cong Vinh
10:55 - 11:10
Postquantum Commutative Encryption Algorithm

It is considered an extended notion of the commutativity of the encryption Using the computational difficulty of the hidden discrete logarithm problem a new method and postquantum probabilistic algorithm for commutative encryption are proposed The finite noncommutative associative algebra containing a large set of the global leftsided unites is used as the algebraic carrier of the proposed method and probabilistic commutative cipher The latter is secure to the knowplaintext attack and therefore efficient to implement on its base a postquantum nokey encryption protocol Main properties of the algebraic carrier which are used in the commutative encryption method are described
Authors: Nguyen Minh (Academy of Cryptography Techniques), Moldovyan Dmitriy (Laboratory of Cybersecurity and Post-quantum Cryptosystems St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)), Moldovyan Alexandr (Laboratory of Cybersecurity and Post-quantum Cryptosystems St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)), Phieu Han (Academy of Cryptography Techniques),
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11:15 - 11:30
An Android Business Card Reader Based on Google Vision Design and Evaluation

Business cards have been widely used to greet business professionals and exchange contact information However the current paperbased way to manage business cards impedes their effective usage leading to a need for digitalising and extracting business card information This paper aims to design a business card reader BCR application for Android devices Based on Google vision library the application digitalises and extracts business card information We evaluate the application on a dataset of 170 business cards The results show that the application can digitalise business cards and extract contact information with 884 of accuracy We then further conduct a comparative analysis of our application and other commercial BCR applications Based on the results the paper suggests several recommendations for future research
Authors: Nguyen Hoang Thuan (Can Tho University of Technology), Dinh Thanh Nhan (Can Tho University of Technology), Lam Thanh Toan (Can Tho University of Technology), Nguyen Xuan Ha Giang (Can Tho University of Technology), Quoc Bao Truong (Can Tho University),
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11:35 - 11:50
Predicted concentration TSS Total Suspended Solids pollution for water quality at the time A case study of Tan Hiep station in Dong Nai river

Water is essential for human life and socioeconomic development Water pollution is a concern for all mankind In Vietnam due to the development of factories and factories water pollution has become more severe including the Dong Nai River In this article the author uses the concentration of TSS at the Tan Hiep control station in Dong Nai River using the Kriging interpolation method to find the appropriate model and give the results of water pollution prediction Dong Nai river area over time with high reliability TSS data were monitored continuously for three months from the beginning of February 2018 to the end of April 2018 the predicted results using Kriging interpolation with high accuracy with regression coefficient equal to 1005 the coefficient is 0859 the best value is 1 the forecast error is 2258 the standard error is 0044 It shows that using the Kriging interpolation method is an effective and suitable solution in mathematical problems with time information
Authors: Cong Nhut Nguyen (Auther),
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11:55 - 12:10
Toward Aggregating Fuzzy Graphs A Model Theory Approach

In this paper we study fuzzy graph represents by using model theory We use hedge algebra and linguistic variables for modeling and aggregating two graphs We prove theorem of limiting in models state space We also figure out preserved property of aggregation operator
Authors: Nguyen Van Han (College of Science, Hue University), Nguyen Cong Hao (Hue University), Phan Cong Vinh (Nguyen Tat Thanh University (NTTU)),
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12:15 - 12:30
Applying geostatistics to predict dissolvent oxygen DO in water on the rivers in Ho Chi Minh city

Geostatistics is briefly concerned with estimation and prediction for spatially continuous phenomena using data measured at a finite number of spatial locations to estimate values of interest at unmeasured locations In practice the costs of installing new observational stations to observe metropolitan water pollution sources as DO Dissolvent Oxygen COD Chemical Oxygen Demand and BOD Biochemical oxygen Demand concentrations are economically high In this study spatial analysis of water pollution of 32 stations monitored during 3 years was carried out Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial structure of water pollution fluctuation In this article I use the recorded DO concentrations is the amount of dissolvent oxygen in water required for the respiration of aquatic organisms at several observational stations on the rivers in Ho Chi Minh City HCMC employ the Kriging interpolation method to find suitable models then predict DO concentrations at some unmeasured stations in the city Our key contribution is finding good statistical models by several criteria then fitting those models with high precision From the data set I found the best forecast model with the smallest forecast error to predict DO concentration on rivers in Ho Chi Minh City From there we propose to the authorities to improve areas where DO concentrations exceed permissible levels
Authors: Cong Nhut Nguyen (Auther),
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Session Four: Context-Aware Systems and Applications 15:10 - 16:45

Chaired by Prof. Phayung Meesad
15:10 - 15:25
Text to Code Pseudo code generation

The evolutions in programming from machine language to these days programming software have made it easy to some extent to develop software but it is not as easy as programming in natural language In order to transfer natural language text to any programming language code it felt necessary to first transform natural language text into pseudo code algorithm then with the help of right API library such algorithms can be transform into any programming language code The main aim of this research work is to produce pseudo code from text however this work is very loosely bound to natural language processing Main components of this proposed work is text analyser that utilizes language tools spelling check grammar check to remove type errors and then eliminate different ambiguities For this step of ambiguity removal an adaptive solution is proposed that learning from manual assistance Once the text is cleared pattern matching techniques is applied to it and later on parsed into a pseudo code The concept model is tested with user scenario approach and also practically implemented by developing a prototype This model is examined using 100 example of different categories and achieved 73 accuracy In this era of computing transformation of natural language text to programming language code is at very early stage thus the proposed model is small contribution toward making such big system
Authors: Altaf uddin altaf (AWKUM, KP, Pakistan),
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15:30 - 15:45
A System and Model of Visual Data Analytics Related to Junior High School Students

The assessment of students learning ability for career guidance in the future is a huge challenge The development stage of students learning ability is considered from the sixth grade to the ninth grade Students transcripts from grade 6 to grade 9 are used to assess students learning abilities A transcript comparison of grades 6 through 9 is essential for each parent and analyst from there they can guide their children to comprehensive development of knowledge The objective of this paper is to visually analyze student data using visual analysis approach proposes a visual analysis system for data discovery with many variables VAS a visual data analysis model visual data analysis criteria visual data variables multidimensional cube representing student data and some visual data analysis questions based on visual graphs related to Junior High School students JHSSs Visual analysis of student data helps parents or analysts observe and extract useful information that they interact visual on visual graphs by asking themselves or answering the visual data analysis questions themselves when observing visual graphs by the retina to guide their children to choose the right knowledge chain and future jobs Visual graphs represent the correlation between subjects and especially the comparison of a subject in the academic years together to help parents and analysts see clearly the trend of the development of students learning abilities by visual data analysis model
Authors: Dang Pham (Faculty of Information Technology, Nguyen Tat Thanh University, Hochiminh City, Vietnam), Phuoc Tran (Ho Chi Minh City Open University, Hochiminh City, Vietnam),
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15:50 - 16:05
CDNN Model for Insect Classification Based on Deep Neural Network Approach

The Mekong Delta has made great progress in rice production over the past ten years Intensive cultivation with multicropping brings many benefits to farmers as well as the food export industry However this is also an opportunity for raising epidemic outbreak Brown Planthoppers can directly damage by sucking the rices vitality and they can cause the wilting and complete drying of rice plants a noncontagious disease known as Hopperburn In this article we propose the CDNN model for insect classification based on Neural Network and Deep Learning approach First insect images are collected and extracted features based on Dense ScaleInvariant Feature Transform Then Bag of Features is used for image representation as feature vectors Lastly these feature vectors are trained and classified using CDNN model based on Deep Neural Network The approach is demonstrated with experiments and measured by a large amount of Brown Planthoppers and Ladybugs samples
Authors: HIEP HUYNH (Can Tho University, Vietnam), DUY LAM (Mekong University, Vietnam), TU HO (Can Tho University, Vietnam), DIEM LE (Can Tho University, Vietnam), LY LE (Can Tho University, Vietnam),
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16:10 - 16:25
Development English Pronunciation Practicing System Based on Speech Recognition

The relevance of the research is caused by the need of application of speech recognition technology for language teaching The speech recognition is one of the most important tasks of the signal processing and pattern recognition fields The speech recognition technology allows computers to understand human speech and it plays very important role in peoples lives This technology can be used to help people in a variety way such as controlling smart homes and devices using robots to perform job interviews converting audio into text etc But there are not many applications of speech recognition technology in education especially in English teaching The main aim of the research is to propose an algorithm in which speech recognition technology is used English language teaching Objects of researches are speech recognition technologies and frameworks English spoken sounds system Research results The authors have proposed an algorithm based on speech recognition framework for English pronunciation learning This proposed algorithm can be applied to another speech recognition framework and different languages Besides the authors also demonstrated how to use the proposed algorithm for development English pronunciation practicing system based on iOS mobile app platform The system also allows language learners can practice English pronunciation anywhere and anytime without any purchase
Authors: Ngoc Hoang Phan (Ba Ria-Vung Tau University), Thi Thu Trang Bui (Ba Ria-Vung Tau University),
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16:30 - 16:45
Document Classification by Using Hybrid Deep Learning Approach

Text classification is an essential component in a variety of applications of natural language processing While the deep learningbased approach is becoming more popular using vectors of word as an input for the models has proved to be a good way for the machine to learn the relation between words in a document This paper proposes a solution for the text classification using hybrid deep learning approaches Every existing deep learning approach has its own advantages and the hybrid deep learning model we are introducing is the combination of the superior features of CNN and LSTM models The proposed models CNNLSTM LSTMCNN show enhanced accuracy over another approach
Authors: Hung Bui Thanh (Data Analytics & Artificial Intelligence Laboratory, Thu Dau Mot University),
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Day 2 29/11/2019
Room #1

Day Trip Tour 08:00 - 17:00

Mekong River Tour & Fruit Gardens Visit