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2020 International computer Symposium, ICS 2020

作者： Joseph, S.P Wijerathna, L.L.M.C. Epa, K.G.R.D. Egalla, E.K.W.A.P.K. Abeygunawardhana, P.W.K. De Silva, R Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Faculty of Computing Malabe10115 Sri Lanka Sri Lanka Institute of Information Technology Dep. of Software Engineering Faculty of Computing Malabe10115 Sri Lanka

ISBN: (纸本)9781728192550

Vision device is a critical component of fruit harvesting mobile robot which is designed for recognizing and harvesting of tomato fruits. The system of vision device of the moving robot, for a dedicated path identification with the use of colour detection algorithms and contour detection algorithms could be stated as an additional usage of the image-based technology. When the robot operates in real life, varying environmental parameters would not affect its activity, since the robot will be functioning mainly indoors, specifically in a greenhouse. Robust fruit segmentation algorithms for the visual system and the fruit plucking mechanism using a readymade robot arm with a soft gripper where it operates with basic hardware components like motors, controlled by a microcontroller with the intervention of kinematic theories, is being used with the goal of collecting fruit objects efficiently in the natural world. Plucking only the ripe and healthy object fruit without damaging both the fruit and the tree is the intended task of the system. The aim is to reduce human effort by promoting automation concepts in agriculture in developing countries like Sri Lanka with great potential, where agriculture plays a vital role in the development of the economy while indoor plantation and harvesting mechanism are also being developing to cater to the economy of the country as well. The way that this system is implemented will be discussed in this paper. © 2020 IEEE.

关键词： Fruits

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An Efficient Localization for Indoor Environment using Classification Algorithms

An Efficient Localization for Indoor Environment using Class...

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2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020

作者： Mulahuwaish, Aos Towne, Wyatt Ghafoor, Kayhan Zrar Maghdid, Halgurd S. Saginaw Valley State University Dept. of Computer Science and Information Systems Michigan United States Salahaddin University-Erbil Dep. of Software Engineering and Informatics Iraq Koya University Faculty of Engineering Dept. of Software Engineering Kurdistan Region-F.R. Iraq

ISBN: (纸本)9781728176246

The positioning accuracy of various kinds of devices is often calculated by using Wi-Fi fingerprints as a data source of Received Signal Strength (RSS). Through different matching algorithms, these RSS values are related to corresponding positioning coordinates for positioning estimation. In this paper, we compare two well known Machine Learning (ML) structures for calculating positioning accuracy: Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) and a Decision Tree (DT). Both matching algorithms run through a series of datasets in two parts. In the first part, the datasets contain raw, non-normalized RSS values. In the second part, the RSS values are all normalized to remove noise in the datasets. After extensive testing and simulations, the tests showed that as long as RSS values are first normalized, a Decision Tree offers better average positioning accuracy. © 2020 IEEE.

关键词： Decision trees

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Emerging case oriented agents for sustaining educational institutions going green towards environmental responsibility

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Journal of systems and Information Technology 2019年第2期21卷 186-214页

作者： Anthony Jnr, Bokolo Abdul Majid, Mazlina Romli, Awanis Department of Computer Science Norwegian University of Science and Technology NTNU Trondheim Norway Universiti Malaysia Pahang Faculty of Computer Systems and Software Engineering Kuantan Malaysia

Purpose: The purpose of this paper is to design a system deployment model that integrates case-based agent technique to develop an eco-responsibility decision support tool for greening educational institutions toward environmental responsibility. Design/methodology/approach: Data were collected through questionnaires distributed among a statistical population that comprised practitioners across educational institutions in Malaysia that implement green practices. The questionnaire measured the feasibility of the developed tool based on factors derived from the literature. Accordingly, descriptive, exploratory and factor analysis approach using statistical package for social sciences (SPSS) was used to test the feasibility of the developed tool. Findings: Results from descriptive analysis confirm the tool is feasible based on mean values that range from 4.1619 to 3.6508 on a five-point scale, indicating that the tool is effective in sustaining educational institutions going green. Besides, results from exploratory analysis verify the reliability of the tool based on the acceptable Cronbach’s alpha reliability coefficient score higher than 0.7 and Kaiser–Meyer–Olkin value being above 0.5. Finally, results from factor analysis reveal that the developed tool is usable, efficient, helpful, flexible and credible and supports educational institutions in going green at 88.44 per cent of the total variance, suggesting that the respondents are satisfied with the tool. Research limitations/implications: The sample population in this study comprises only practitioners from educational institutions in Malaysia. Theoretically, this research provides feasibility factors and associated items that can be used in evaluating developed information systems. Practical implications: Practically, this study develops an eco-responsibility decision support tool to facilitate green strategies and provides information on how practitioners in educational institutions can improve green growth. So

关键词： Sustainable development

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DDoS Detection Using Active and Idle Features of Revised CICFlowMeter and Statistical Approaches

DDoS Detection Using Active and Idle Features of Revised CIC...

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International Conference on Advanced Science and engineering (ICOASE)

作者： Basheer Husham Ali Nasri Sulaiman S.A.R. Al-Haddad Rodziah Atan Siti Lailatul Mohd Hassan Department of Electrical and Electronic Engineering Universiti Putra Malaysia (UPM) Serdang Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia (UPM) Serdang Malaysia Department of Computer and Communication Systems Engineering Universiti Putra Malaysia (UPM) Serdang Malaysia Software Eng. and Information Systems Dept Universiti Putra Malaysia (UPM) Serdang Malaysia School of Electrical Engineering Universiti Teknologi MARA Shah Alam Malaysia

Distributed Denial of services (DDoS) attack is one of the most dangerous attacks that targeted servers. The main consequence of this attack is to prevent users from getting their legitimate services by bringing down targeted victim. CICFlowMeter tool generates bi-directional flows from packets. Each flow generates 83 of different features. The research focuses on 8 features which are active min (f1), active mean (f2), active max (f3), active std (f4), idle min (f5), idle mean (f6), idle max (f7), and idle std (f8). CICFlowMeter tool has several problems that affected on the detection accuracy of DDoS attacks. The idle and active based feature of Shannon entropy and sequential probability ratio test (SE-SPRT) approach was implemented in this research. The problems of original CICFlowMeter were presented, and the differences between original and revised version of CICFlowMeter tool were explored. The DARPA database and confusion matrix were used to evaluate the detection technique and present the comparison between two versions of CICFlowMeter. The detection method detected neptune and smurf attacks and had higher accuracy, f1-score, sensitivity, specificity, and precision when revised version of CICFlowMeter used to generate flows. However, the detection method failed to detect neptune attack and had higher miss-rate, lower accuracy, lower f1-score, and lower specificity, and lower precision when original version used in generating flows.

关键词： Sensitivity Databases Scalability Bidirectional control Denial-of-service attack Feature extraction Entropy

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Method for Testing and Debugging Flow Formal Specification in Full-Stack Embedded systems Designs

Method for Testing and Debugging Flow Formal Specification i...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Vasiliy Pinkevich Alexey Platunov Faculty of Software Engineering and Computer Systems ITMO University Saint Petersburg Russia

ISBN: (数字)9781728169491

ISBN: (纸本)9781728169507

Modern embedded computing systems (ES) include heterogeneous components connected “horizontally” and “vertically”, and it demands developing individual quality control design flows for each project. This article discusses the problem of formalizing end-to-end testing and debugging processes in full-stack ES designs. An ontology of ES testing and debugging processes from the multi-level organization point of view and a number of models are proposed using a unified representation of testing, verification, validation and debugging problems at various levels of abstraction. This allows to formally specify a testing and debugging flow of an arbitrary ES design with transition systems describing different states of design process. The application of the proposed solutions provides: control of the coverage of system components by verification and validation processes; identification of gaps in the testing and debugging processes; monitoring of the completed verification and validation steps of system components at different levels.

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Fuzzy min-max classifier based on new membership function for pattern classification: A conceptual solution 8

Fuzzy min-max classifier based on new membership function fo...

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8th IEEE International Conference on Control System, Computing and engineering, ICCSCE 2018

作者： Alhroob, Essam Ghani, Ngahzaifa Ab Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Malaysia

ISBN: (纸本)9781538663240

The fuzzy min-max (FMM) neural network is one of the most powerful neural networks that combines neural network and fuzzy set theory into a common framework for tackling pattern classification problems. FMM neural network carries out learning processes that consist of hyperbox expansion, hyperbox overlap test and hyperbox contraction to execute pattern classification. Although these processes provide FMM with several outstanding features and make it a unique pattern classifier, the contraction process is considered a major limitation that affects the FMM learning process and hinders it from handling hyperbox overlapped boundaries appropriately. This drawback could affect membership decision making and cause the classifier to provide random decisions when test samples have the same fitness values with different hyperboxes from different classes (ambiguity issue). The performance of the classifier consequently declines. Thus, this study aims to provide a conceptual solution called 'fuzzy min-max classifier based on new membership function' through a new method, 'Euclidean distance', in the test phase to handle the hyperbox overlapping boundaries of different classes. The conceptual solution has not been implemented and tested in a real scenario. Hence, the application of the conceptual solution to real scenarios is recommended in future studies to assess its performance. © 2018 IEEE.

关键词： Membership functions

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The development of point cloud registration algorithm using geometrical features of the multi-sensor 3D scanner 10

The development of point cloud registration algorithm using ...

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10th Majorov International Conference on software engineering and computer systems, MICSECS 2018

作者： Gromov, Vladimir Kustarev, Pavel ITMO University Faculty of Software Engineering and Computer Systems Saint-Petersburg Russia

The aim of the research is a 3D point matching which uses models from different sources to union them in the general coordinate system to create a high-accuracy scene from the 3D scanner. There are several images from the stereo camera (dual optical camera) at the device output to construct a 3D high-resolution model with 360 degrees horizontal field of view. There is a high-accuracy point cloud from the LIDAR module (laser rangefinder) to correct the full field view from the stereo camera. The research process is called point cloud registration and will help to create an output 3D representation with advantages of both sources. The presented algorithm has low computational complexity and,in the future, will be implemented on the scanner embedded system. The results of the data processing are presented in this paper. © 2019 CEUR-WS. All rights reserved.

关键词： Optical radar

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Verification of the CAD System for an Application-Specific Processor by Property-Based Testing

Verification of the CAD System for an Application-Specific P...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Daniil Prohorov Aleksandr Penskoi Faculty of Software Engineering and Computer Systems ITMO University Saint-Petersburg Russia

ISBN: (数字)9781728169491

ISBN: (纸本)9781728169507

An application-specific processor CAD system is a complex software system with high dependability requirement. Verification of such system is a complicated process which involves many closely connected components, different computational process representation and tools, and requires much time and work. In the article, the authors describe their experience of usage property-based testing in the NITTA project (application-specific reconfigurable processor CAD for real-time application). Property-based testing allowed to significantly improve source code coverage and identify many hard to find bugs. The article will be interesting to CAD developers and as a real-world property-based testing application example.

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Development and analysis of authentication method for Iot devices software on the network using blockchain technologies 12

Development and analysis of authentication method for Iot de...

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12th International Scientific and Practical Conference on Environment. Technology. Resources

作者： Shtennikov, Dmitry Gennadievich Kuzmin, Kirill Sergeevich Letov, Nikolay Evgenievich Faculty of Software Engineering and Computer Systems ITMO Universaty Saint-Petersburg Russia

Currently, there is an unsolved problem of IoT device authentication in networks to ensure their security. Due to low performance, work with traditional methods of protection is complicated and therefore a different approach is required. The article proposes a method for authenticating IoT devices (devices and software) by verifying their data and then entering it into the data storage. The implementation of a data storage using blockchain technology and the comparison of its efficiency with a classical database are considered. The aim of research is evelopment of the IoT device authentication method, analysis of the effectiveness and applicability of the developed method and comparison of various technological approaches to solving the problem. Obtained results is evaluation parameters of the resulting system and methods for constructing systems based on this method. © 2019 Shtennikov Dmitry Gennadievich, Kuzmin Kirill Sergeevich, Letov Nikolay Evgenievich.

关键词： Blockchain

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Graph Schema Storage in SQL Object-Relational Database and NoSQL Document-Oriented Database: A Comparative Study

Graph Schema Storage in SQL Object-Relational Database and N...

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作者： Ait El Mouden, Zakariyaa Jakimi, Abdeslam Hajar, Moha Boutahar, Mohamed Software Engineering and Information Systems Engineering Team Faculty of Sciences Technologies Errachidia Moulay Ismail University Meknes Morocco Operational Research and Computer Science Team Faculty of Sciences Technologies Errachidia Moulay Ismail University Meknes Morocco Faculty of Sciences Institute of Mathematics of Marseille Marseille France

Over the past years, the main objective of database management systems was to store data and give users the possibility to manipulate those data. SQL databases were sufficient in the first time, but with the evolution of computer science technologies, other factors start to appear;such as the volume of the stored data, the velocity of the transactions between the user and data, the possibility to store heterogeneous data (variety) and many other Big Data challenges. This paper presents the major differences between the SQL and NoSQL databases in term of variety, velocity and ease of programming. For SQL, we used the Oracle object-relational database and for NoSQL, we used MongoDB document-oriented database. The comparative study was applied to data modeled by graphs, where we consider a set of graphs and for each graph, we measure the time needed to insert the graph in the database, the size of the graph in the database and other factors. Measurements presents in this process are generally automatic and supported by a set of developed algorithms. © 2020, Springer Nature Switzerland AG.

关键词： Digital storage

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