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Day 1 26/11/2020
Room #1

ICCASA 2020 Welcome message by the General Chair Prof. Phan Cong Vinh 09:00 - 09:05

starts at 9:00 AM, Vietnam local time (GMT+7)

Welcome message by EAI Conference Manager 09:05 - 09:10

Welcome message by EAI Community Manager 09:10 - 09:15

Keynote speaker : Assistant Prof. Dr. Waralak Vongdoiwang Siricharoen 09:15 - 09:45

Title: Using Personas as Empathizing and Defining Methods of Design Thinking Process

Session 1 09:45 - 11:40

09:45 - 10:05
Formal Verifi cation of Multi-agent Plans for Vehicle Platoon

The collaboration and coordination of autonomous vehicles into convoys or platoons have been used on our highways. However, before deploying such vehicles on the real road, their autonomous behaviors must be certified to act safely. The vehicle platooning can be considered as a multi-agent system where each agent can make its own autonomous decisions. In order to ensure that these decision-making agents in the platoon never violate safety properties, we use the Uppaal model checker to verify them. Furthermore, to facilitate the checking process and create a consistent translation process, we have developed an automated translation program that can map our multi-agent plans to the Uppaal model checker format.
Authors: Thảo Nguyễn Văn (Kassel University), Kurt Geihs (Kassel University),
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10:05 - 10:25
Contextual Defeasible Reasoning Framework for Heterogeneous System

This paper presents a contextual defeasible reasoning (CDL) based multi-agent formalism to model heterogeneous systems using the notion of a multi-context system. This framework relies on the semantic knowledge sources which allow us to model context-aware non-monotonic reasoning agents to infer the desired goals using the extracted rules from the ontologies and handles inconsistencies using conflicting contextual information. We illustrate the validity and correctness of the proposed formalism using a simple case study of a smart healthcare system with the prototypal implementation of the system.
Authors: Hafiz Mahfooz Ul Haque (Department of Software Engineering, The University of Lahore, Pakistan), Salwa Akhtar (Department of Computer Science, University of Lahore, Pakistan),
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10:25 - 10:40
Abnormality Bone Detection in X-ray Images using Convolutional Neural Network

Medical imaging plays a role as a crucial source of data for disease detection and diagnosis. Recent advancements in machine learning and deep learning have become an efficient tool for medical image analysis. Medical image research laboratories are rapidly creating machine learning systems to achieve the professional performance of humans. However, both machine learning and deep learning methods are complex and require a lot of expertise, resources, knowledge, and time to train. Those create a significant barrier for researchers. In this study, we propose a convolutional neural network architecture to detect abnormalities in bone images. The proposed method provides insight into medical images and explains in detail how the model supports the diagnosis.
Authors: Hiep Huynh (Can Tho University), Hang Nguyen (Vinh Long University of Technology Education), Cang Phan (Vinh Long University of Technology Education), Hai Nguyen (Can Tho University),
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10:40 - 11:05
Statistical Properties and Modelling of DDoS Attacks

The work presented in this paper is an implementation of a design of a DDoS simulation testbed that uses parameter estimation and probability fitting of source IP address features of a network. We explored the issue of lack of adequate and recent evaluation datasets, we therefore designed a way that can be used to generate synthetic data that simulates a DDoS attack. We found that the Gaussian probability distribution best represents the normal operations of a network, while the Poisson probability distribution represents the operations of a network under a DDoS attack.
Authors: Pheeha Machaka (University of South Africa), Antoine Bagula (University of the Western Cape),
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11:05 - 11:25
Estimating Surface Land Temperature and Emissivity in Ho Chi Minh City Using Remote Sensing Images

As the biggest city in Vietnam, Ho Chi Minh City usually suffers from a number of environmental issues such as air pollution, high temperature, and traffic jam. Therefore, we are building a hazard maps system to help the city government and population understand well environmental risks. One of the main data sources for such system is remote sensing images, especially the Landsat and MODIS data. In this paper, we present a cloud-based automated processing service for estimating land surface temperature in Ho Chi Minh City using remote sensing data. The service can be integrated as a part of a hazard map system when data can be collected from different sources such as sensors or machine learning.
Authors: Phan Hien Vu (International University), Tan Long Le (HCMUT), Cuong Pham-Quoc (Ho Chi Minh City University of Technology (HCMUT) - Vietnam),
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11:25 - 11:40
A Comparison between Stack Auto-Encoder and Deep Belief Network in River Run-off Prediction

The application of deep neural networks in forecasting hydrological time series data is increasingly popular, aiming to improve prediction accuracy in this challenging problem. In this study, we apply stacked autoencoder (SAE) neural network in river runoff prediction. We compare the performance of SAE model with that of Deep belief network (DBN) on the runoff data of Srepok river in Central Highlands of Vietnam. The experimental results show that, SAE brings out better prediction accuracy than DBN in terms of coefficient of correlation, root mean square error, mean absolute percentage error.
Authors: Kinh Bui (Ho Chi Minh University of Technology), Anh Duong (Ho Chi Minh University of Technology), Hieu Duong (Ho Chi Minh University of Technology),
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Coffee break 11:40 - 11:50

Session 2 11:50 - 13:35

11:50 - 12:15
Developing Data Model Managing Residents by Space and Time in Three-Dimensional Geographic Space

A major challenge currently of levels of government and construction contractors is how to manage population growth by geographic location and over time. The population increases by geographic location and over time leading to the increase of positive and negative aspects in the community. Managing people living and working on the territory by space and time is a very important and urgent job. The levels of government must regularly manage the people living and working on their localities, which are always associated with the management of permanent populations, temporary populations, blood relations, social relations, previous conviction relations, previous offence relations and birth or death relations that all of this management takes place at a specific geographic location and time. The paper proposes to develop a spatial - temporal - residential data model that is capable of managing human activities at the place of residence, at the workplace and at the location of the relations by geographic location and over time, this model is called STRDM. The paper illustrates empirical results with visual forms through the use of queries by space, time, resident, and search for ancestor and descendant. These empirical results show that it can be applied to residential data management systems in new urban areas.
Authors: Dang Pham (Faculty of Information Technology, Nguyen Tat Thanh University, Hochiminh City, Vietnam),
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12:15 - 12:30
Trigger2B: A Tool Generating Event-B Models from Database Triggers

A database trigger is a human readable block code without any formal semantics. We usually can check if a trigger is designed correctly after it is executed or with human inspection. Formal methods are techniques to complement to testing to ensure the correctness of the system. This paper first introduces a set of translation rules to translate DML triggers to Event-B models. Following the proposed rules, we implement a tool named Trigger2B which partly supports for automatic translation. From the targeted model, we can verify the data constraints and detect in finite loops of trigger execution with RODIN. Finally, we take an example for illustration purpose. The proposed tool overcomes the complexity of formal modeling and makes them practical in the development.
Authors: Le Hong Anh (Hanoi University of Mining and Geology),
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12:30 - 12:45
Predicting the level of Hypertension Using Machine Learning

In recent years, data mining has been put into research and application in many different areas in the world such as economy, education, sports, telecommunications, etc. And the health - health care [1] sector is not out of this trend. If it is possible to successfully analyze the data [2] [3] [4] from the huge amount of data of diseases, patients and hospitals every day, it can help a lot of doctors in the process of diagnosis, examination and treatment of diseases for patients. The problem raised here is whether we can accurately diagnose the patient’s disease based on the information provided. The information provided may be age, gender, occupation, symptoms, test information, etc. from which it is necessary to achieve the most accurate diagnosis possible to minimize the work pressure for the medical team as well as minimize the time of diagnosis.
Authors: Nguyen Thanh tung (ISVNU),
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12:45 - 13:05
Can Blockchain Fly the Silver Fern? Exploring the opportunity in New Zealand’s primary industries

Blockchain is an emerging technology perceived as ground-breaking. Yet, technology service providers are not realising the untapped market potential as quick as it was predicted. New Zealand is not any different. Currently, the number of blockchain-based solutions available in the country is rather limited. A clear understanding of the market of blockchain is critical for service providers to recognise the opportunities and the challenges. It has been suggested that multiple industries could utilise blockchain technology to attain numerous benefits. The primary industries of New Zealand will be one of them that remains underexplored. Therefore, in this study, we use total addressable market (TAM), a technique to estimate the market size, to explore the available economic opportunity of blockchain-based solutions in New Zealand’s primary industries. Our estimation suggests that it may be close to NZ$1.65 billion per year, including self-employed enterprises; or NZ$496 million per year, excluding self-employed enterprises. Besides, our review of secondary sources indicates that blockchain technology could tackle some of the challenges the primary industries are facing like food fraud and foodborne illness. However, lack of strong and practical use cases, lack of streamlined practice for data management, lack of understanding of the technology and its implication to business, and lack of regulation and legislation are the major impediments to blockchain adoption.
Authors: Mahmudul Hasan (University of Auckland), Johnny Chan (University of Auckland),
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13:05 - 13:25
Design and Implementation of a real-time web service for monitoring soil moisture and landslide in Lai Chau province, Viet Nam

Web service technology has been recognized as one of key factors for developing natural hazards monitoring systems. This study proposes an open source web service solution for monitoring soil moisture in Lai Chau, a northern province of Vietnam. The system supports a real-time mechanism for data communication with gateway and mobile applications via http-based protocol. It receives structured data packets from the gateway, then makes the visualization on map and immediately alerts users if data is in warning range. Mobile applications are also capable to retrieve web map services by using provided RESTful APIs. The system has made a great contribution to the local government for natural disasters monitoring and management in Lai Chau province.
Authors: Le Hong Anh (Hanoi University of Mining and Geology), Dinh Bao Ngoc (Hanoi University of Mining and Geology), Nguyen Mai Dung (Hanoi University of Mining and Geology),
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13:25 - 13:35
Optimizing the operational time of IoT devices in Cloud-Fog systems

With the increasing number of connected devices, sensors, data generated need to be analyzed. The current cloud computing model, which concentrate on computing and storage resources in a few large data centers, will inevitably lead to excessive network load, end-to-end service latency, and overall power consumption. This leads to the creation of new network architectures that extend computing and storage capabilities to the edge of the network, close to end-users. The emerging problem is how to efficiently deploy the services to the system that satisfies service resource requirements and QoS constraints while maximizing resource utilization. In this paper, we investigate the problem of IoT services deployment in Cloud Fog system to provide IoT services with minimal energy consumption. We formulate the problem using a Linear Programming (LP) model taking into account the characteristics of energy resources in Cloud-Fog system as well as the IoT services specific requirements [1]. We propose heuristic algorithm for solving the problem. We compare the efficiency of our solutions with the optimal solution solved by LP solver. The experimental results show that our proposed solution is very close to optimum solutions in terms of energy efficiency.
Authors: Nguyen Thanh Tung (ISVNU),
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Lunch break 13:35 - 14:05

Short Talk: Prof. Phan Cong Vinh 14:05 - 14:25

Context--Aware Computing: New Research Trends

Session 3 14:25 - 16:25

14:25 - 14:55
Proposing Spatial - Temporal - Semantic Data Model Managing Genealogy and Space Evolution History of Objects in 3D Geographical Space

Managing construction projects in new urban areas is an essential work for construction contractors as well as authorities at all levels. In this management, managing the spatial evolutionary history of two-dimensional (2D), two-point-five-dimensional (2.5D) and three-dimensional (3D) spatial objects over time and semantics in 3D geographical space is an urgent and extremely important work. This paper proposes a spatial - temporal - semantic data model (STSDM), spatial queries over time and semantics, and algorithms finding the ancestors and descendants of space objects (ASA and DSA). The paper presents some empirical results about the spatial evolutionary history of spatial objects over time and semantics. The experimental results show that it can completely be used to trace the space evolution history of bridges, houses, tenements, and apartments at a given time or in a given period in new urban management applications.
Authors: Dang Pham (Faculty of Information Technology, Nguyen Tat Thanh University, Hochiminh City, Vietnam),
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14:55 - 15:15
Modelling Situation-aware Formalism using BDI Reasoning Agents

Natural or man-made disasters are unavoidable situations that can occur anytime and anywhere. Timely disaster response plays a vital role in reducing its after-effects and can save countless lives. Over the years, people have been developing the guidelines and processes to cope up with such kinds of hazardous situations. In recent years, situation-awareness has been considered to be the most fascinating approach for the situation assessment and provides decision support accordingly. Situation-aware systems observe/perceive dynamic changes in the environment, understand/comprehend the situation, and perform actions according to the environment. Although state-of-the-art formalisms have been developed to handle such kinds of hazardous situations intelligently and rescue the victims. However, there are still many uncontrolled challenging issues. In this paper, we present a Belief-Desire-Intention (BDI) based multi-agent formalism to model context-aware decision support system dynamically in order to achieve the desired goals. To illustrate the use of the proposed formalism, we develop a simple case study in which BDI agents are modeled and simulated to present results in terms of agents’ reasoning processes. The behavior of the system has been tested using the NetLogo simulation environment to rigorously evaluate the validity of the system.
Authors: Hafiz Mahfooz Ul Haque (Department of Software Engineering, University of Lahore), Kiran Saleem (Department of Computer Science, University of Lahore),
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15:15 - 15:35
Using Empathy Mapping in Design Thinking Process for Personas Discovering

Exploring user attitudes and behaviors within the domain of interests helps the user experience team to match the user with a deeper understanding. The mapping process also reveals any gap in existing user data. Design thinking is the ground-breaking and cooperative approach to problem-solving that puts the user first to make user-centered products and services. There are many various design thinking activities that use to generate a thoughtful of the users or customer, including the conception of personas. This paper revisits the concept of persona and draws the connection of using empathy map to build persona within the design thinking process. Also showing the benefit of empathizing method to construct the effective persona. This can be used for the benefit in HCI designing processes or marketing analysis.
Authors: Waralak Vongdoiwang Siricharoen (Faculty of Information and Communication Technology, Silpakorn University),
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15:35 - 15:45
Taiwanese Stock Market Forecasting with a Shallow Long Short-term memory Architecture

The trading of stock in companies holds an important part in numerous economies. Stock Forecast which is popularly published in the public domain in the forms of newsletters, investment promotion organizations, public/private forums, and scientific forecast services is very necessary to contribute successes in financial for individuals or organizations. Leveraging advancements in machine learning, we propose an approach based on Long Short-Term Memory algorithms and compare the performance with robust classic machine learning algorithms such as Random Forests and Support Vector Regression when we do forecast tasks on Taiwanese stock market. The proposed method with deep learning algorithm shows better performance comparing to classic machine learning in the tasks of forecasting data collected from stock market in Taiwan during more than 10 years.
Authors: Phuong Ha Dang Bui (Can Tho University), Toan Tran (Duy Tan University), Hai Thanh Nguyen (Can Tho University),
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15:45 - 16:05
A Convolutional Neural Network on X-ray Images for Pneumonia Diagnosis

The application of AI in general and Deep learning, in particular, is becoming increasingly popular in human life. AI has been able to replace people in many fields, with data already synthesized and stored by computers that will help AI become smarter. One of the areas where AI can be applied very well is the medical field, especially X-ray imaging. In this study, we propose a convolutional network architecture to classify chest X-ray images as well as apply explanatory methods to trained models to support disease diagnosis. The proposed method provides insight into medical imaging to support the diagnosis of Pneumonia.
Authors: Hiep Huynh (Can Tho University), Son Dang (Vinh Long University of Technology Education), Cang Phan (Vinh Long University of Technology Education), Hai Nguyen (Can Tho University),
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16:05 - 16:25
Counterbalancing Asymmetric Information: A Process Driven Systems Thinking Approach to Information Sharing of Decentralized Databases

This paper explores asymmetric information and how to counterbalance it. It utilizes the case study of a hypothetical company called “Hashable”. The purpose of this case study is to exemplify a proposed solution to address the information asymmetry faced by buyers of residential real estate in New Zealand. A procedural response is provided for organizing the information needed to make an informed decision on purchasing a property. A causal loop diagram is introduced to develop an understanding of the various stakeholders involved in the proposed solution and their interaction with the information they provide. This paper highlights the core problems regarding information asymmetry within a transaction. It also provides procedural and technological solutions to counterbalance this information asymmetry while simultaneously reducing information costs and increasing reliability of the information provided.
Authors: Mark Hoksbergen (University of Auckland), Johnny Chan (University of Auckland), Gabrielle Peko (University of Auckland), David Sundaram (University of Auckland),
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Closing Speech and Best Paper Award by the General Chair Prof. Phan Cong Vinh 16:25 - 16:30

Day 2 27/11/2020
Room #1

ICTCC 2020 Welcome message by the General Chair Phan Cong Vinh 09:00 - 09:05

Starts at 9:00 AM, Vietnam local time (GMT+7)

Welcome message by EAI Conference Manager 09:05 - 09:10

Welcome message by EAI Community Manager 09:10 - 09:15

Keynote speaker: Prof. Herwig Unger 09:15 - 10:15

Title: Brain Inspired methods for Natural Language Processing

Session 1 10:15 - 11:25

10:15 - 10:35
Towards Service Co-evolution in SOA environments: A Survey

In Service-Oriented Architecture (SOA), the need for service evolution comes from both service providers and their clients due to the change of requirements and environments. However, enabling control evolution of service is a critical challenge for the developers since services may be part of different business processes and depend on other services. This paper addresses the state of the art of service evolution and towards service co-evolution. Different visions of service evolution, service co-evolution paradigm are reported and enabling technologies reviewed. What emerges are still major issues such as dynamic independence among services that shall be faced by the research community. Our goal is to provide high-level guidelines to researchers and practitioners to meet the challenges of building industrial strength adaptive applications with a spectrum of processes, techniques, and facilities provided within the service co-evolution paradigm.
Authors: Tran Huu Tam (Kassel University, Germany), Nguyen Van Thao (Kassel University, Germany), Phan Cong Vinh (Nguyen Tat Thanh University,Vietnam),
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10:35 - 10:50
Analysis of a HIPS Solution Use in Power Systems

The aim of this paper is to conduct a performance comparative analysis of open-source HIPS (Host Intrusion Prevention System) solutions in order to improve security measures in power systems. First, the HIPS technology is introduced with an emphasis on its use for increasing security within power systems. Secondly, selected HIPS solutions are introduced in order to conduct the comparative analysis. Finally, the results of the comparative analysis of the individual solutions are presented with an emphasis on the use of system resources in the deployment of HIPS solutions on Windows workstations.
Authors: Vladimir Sobeslav (University of Hradec Kralove), Tomas Svoboda (University of Hradec Kralove), Josef Horalek (University of Hradec Kralove),
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10:50 - 11:05
Behavioral Analysis of SIEM Solutions for Energy Technology Systems

The aim of this article is to analyze SIEM solutions. Emphasizing the use of these systems to ensure data confidentiality, availability, and integrity monitoring energy technology systems. First, the issue of security in the ar-ea of energy systems is introduced. In order to maintain the availability, confidentiality and data integrity, the user behavioral analysis modules in SIEM systems are also introduced. The next section presents specific SIEM solutions that can be currently used not only in ICS environments and which will be subject to comparative analysis. This is IBM Security QRadar SIEM and LogRhythm NextGen SIEM. What follows is the introduction and implementation of modules for user behavioral analysis in the men-tioned SIEM solutions, including testing own Use Case for testing user be-havioral analysis modules. The results of the comparative analysis of user behavioral analysis modules in selected SIEM solutions are presented in the last section.
Authors: Vladimir Sobeslav (University of Hradec Kralove), Tomas Svoboda (University of Hradec Kralove), Josef Horalek (University of Hradec Kralove),
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11:05 - 11:15
Threads Efficiency Analysis of Selected Operating Systems

The aim of the article is to present results of the testing focused on efficiency of CPU performance and its threads in single-threading and multithreading modes in various versions of operating systems from the family of Microsoft Windows. The main task was to verify whether the chosen operating system version affects the efficiency of using threads by the operating system, with the emphasis of their upgrade in technological and industrial systems.
Authors: Vladimir Sobeslav (University of Hradec Kralove), Josef Horalek (University of Hradec Kralove), Matej Drdla (University of Hradec Kralove), Hana Svecova (University of Hradec Kralove),
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11:15 - 11:25
An Architecture for Intelligent e-Learning Platform for Student's Lab Deployment

For better understanding and better learning of new technologies, there is welcome to have some hands-on experiences with these subjects. This helps with knowledge adoption and also increases learning efficiency. In this article, there is analyzed inputs for a proposal of this system and requirements, which should be meet for such system, and also there is identified learning subjects and areas, which could use this tool. This article deals with and describes an architecture, which can help with automation and deployment labs, which can students use for learning and their research. There is described the architecture for a system, which is able to deploy these environments into more cloud type providers and also is open and able to handle more types run-time technologies, especially virtualization (e.g. OpenStack, Kubernetes and more). The architecture describes platform, which consists a portal or a learning web-based tool, which can be used for learning and also for interface of student labs, which can be automatically deployed based on input conditions with automation tools to some public or private cloud services.
Authors: Vladimir Sobeslav (University of Hradec Kralove), Peter Mikulecky (University of Hradec Kralove), Matej Drdla (University of Hradec Kralove), Hana Svecova (University of Hradec Kralove),
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Coffee break 11:25 - 11:40

Keynote speaker: Prof. Phayung Meesad 11:40 - 12:20

Title: The Trends and Challenges in Big Data Analytics

Short Talk: Prof. Phan Cong Vinh 12:20 - 12:50

Nature-Inspired Networking: Theory and Applications

Lunch break 12:50 - 13:20

Session 2 13:20 - 14:30

13:20 - 13:35
Improved Packet Delivery for Wireless Sensor Networks using Local Automate based Autonomic Network Architecture in a ZigBee Environment

A low cost, low power personal area network is formalized by IEEE 802.15.4 standard ZigBee Wireless Sensor Network. The most common way to con-struct a WSN using ZigBee is to use tree type network topology. This leads to large amount of energy consumption because of congestion in network. The node failures in a network topology, results in reconstructing the route of existing structure. Thus, a Local automate based autonomic network ar-chitecture is deployed at the MAC layer of ZigBee protocol. The architecture considers previous occurrences of probabilities of nodes and learns their be-havior during transmission. This record an active state of each node, that in-turn reduces congestion when neighboring node failure occurs. Simulation results provide 20% increase in unicast and multicast delivery rate. Finally, throughput of an entire network in a larger density dynamic environment increases.
Authors: Sanjay Nagendra (Visvesvaraya Technological University), Shaila K (Visveswaraya Technological University),
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13:35 - 13:55
Hybrid Domain Steganography for Embedding DES Encrypted QR code using Random Bit Binary Search

Steganography is a technology used for hiding the digital information into an electronic document so that it can be used only by the authorized entity and not available to trespassers. In the recent era, QR code is used versatile in all the applications. The data capacity of QR code is more as the information is codified in the form of image. Image Steganography can be achieved in spatial, transformation or hybrid domain. In this paper, a novel hybrid domain Steganography is employed for embedding encrypted QR code image in Source Image to get stego Image using Discrete Wavelet Transforms and Random Bit Binary Search Replacement (DWT - RBBS) technique. The information is encrypted using DES encryption algorithm and is codified to QR code image. This QR code image is then embedded into the source image using DWT- RBBS technique resulting in multiple level of security.
Authors: Shashikiran B S (VTU),
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13:55 - 14:10
DESIGN AND TESTING A SINGLE-PASSENGER ECO-VEHICLE

Protection of the living environment for sustainable development is a concern of mankind. In particular, reducing CO2 emissions is the top criteria. A number of technologies that include a method of improving fossil fuel consumption effec-tiveness have been introduced into new automobiles in order to limit the negative effects caused by CO2. In this paper, new technological solutions will be pro-posed. They are combined in a novel method in order to improve vehicle engine performance, to improve ignition and air return systems and to reduce friction be-tween vehicle and environment when it is moving. The propsed method is applied into a new implemented vehicle for Eco Mileage Challenge (EMC) 2019 which is organized annually by Honda Vietnam Compapy. All tests and tournament re-sults of 240 kilometters per liter of RON98 gasoline in average prove that the propsed method is feasible and effective in fuel savings.
Authors: Tri Nhut Do (Van Lang University), Quang Minh Pham (Van Lang University), Hoa Binh Le-Nguyen (Van Lang University), Cao Tri Nguyen (Van Lang University), Hai Minh Nguyen-Tran (Van Lang University),
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14:10 - 14:30
A study on methodology of improvement the hydraulic system for cometto self-propelled trailer system

In recent years, the transport of large packages with super weight from 100 tons to several thousand tons is no longer a difficult problem due to the continuous development of technology. Experienced transport companies, specializing in transporting heavy goods in Vietnam, have invested in very modern equipment and machinery such as self-propelled trailers of Cometto (Italy) in order to transport safely mentioned parcels of great economic value arrive at the requested location. This trailer can be self-propelled, does not need to use a tractor, and only needs to use a remote control handheld device. Moreover, the trailer axes can rotate 360 degrees. In particular, the hydraulic system supports trailers operating with high accuracy and absolute safety including functions such as 360 degree rotation, lifting, transmission, braking, etc. In order to improve the performance of trailers when actually used in large projects, an important detail in the trailers hydraulic system has been inserted a throttle valve with to increase the safety of the hydraulic pump and the entire system as well as the safety of the goods that trailers are transporting. The trailer system has transported the rig with a capacity of up to 3,200 tons in Vietnam, the shipment of 15,000 tons in the world and beyond in the future.
Authors: Hai Minh Nguyen Tran (Van Lang University), Quang Minh Pham (Van Lang University), Hoa Binh Le Nguyen (Van Lang University), Cao Tri Nguyen (Van Lang University), Tri Nhut Do (Van Lang University),
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Closing Speech by the General Chair Prof Phan Cong Vinh 14:30 - 14:35