Evan R.M. Debenham and Roberto Solis-Oba
The University of Western Ontario, Canada

ABSTRACT

The aim of this paper is to propose new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game.

We summarize existing algorithms for FOV computation, describe their limitations, and present new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather than recalculating an FOV from scratch.

We compare our algorithms to existing FOV algorithms and show they provide substantial improvements to running time. Our algorithms provide the largest improvement over existing FOV algorithms at large grid sizes, thus allowing the possibility of the design of high resolution FOV-based video games.

KEYWORDS

Field of Vision (FOV), Computer Games, Visibility Determination, Algorithms.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101801.pdf

Volume Link :
http://airccse.org/csit/V10N18.html

John Hawkins
Transitional AI Research Group, Australia

ABSTRACT

Prioritization of machine learning projects requires estimates of both the potential ROI of the business case and the technical difficulty of building a model with the required characteristics. In this work we present a technique for estimating the minimum required performance characteristics of a predictive model given a set of information about how it will be used. This technique will result in robust, objective comparisons between potential projects. The resulting estimates will allow data scientists and managers to evaluate whether a proposed machine learning project is likely to succeed before any modelling needs to be done. The technique has been implemented into the open source application MinViME (Minimum Viable Model Estimator) which can be installed via the PyPI python package management system, or downloaded directly from the GitHub repository. Available at https://github.com/john-hawkins/MinViME.

KEYWORDS

Machine Learning, ROI Estimation, Machine Learning Metrics, Cost Sensitive Learning

For More Details :
https://aircconline.com/csit/papers/vol10/csit101803.pdf

Volume Link :
http://airccse.org/csit/V10N18.html

Jiawei LI and Tad Gonsalves
Sophia University, Japan

ABSTRACT

This paper presents a Genetic Algorithm approach to solve a specific examination timetabling problem which is common in Japanese Universities. The model is programmed in Excel VBA programming language, which can be run on the Microsoft Office Excel worksheets directly. The model uses direct chromosome representation. To satisfy hard and soft constraints, constraint-based initialization operation, constraint-based crossover operation and penalty points system are implemented. To further improve the result quality of the algorithm, this paper designed an improvement called initial population pre-training. The proposed model was tested by the real data from Sophia University, Tokyo, Japan. The model shows acceptable results, and the comparison of results proves that the initial population pre-training approach can improve the result quality.

KEYWORDS

Examination timetabling problem, Excel VBA, Direct chromosome representation, Genetic Algorithm Improvement.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101701.pdf

Volume Link :
http://airccse.org/csit/V10N17.html

Yoshiaki Okubo
Hokkaido University, Japan

ABSTRACT

In this paper, we present a method of finding conceptual clusters of music objects based on Formal Concept Analysis. A formal concept (FC) is defined as a pair of extent and intent which are sets of objects and terminological attributes commonly associated with the objects, respectively. Thus, an FC can be regarded as a conceptual cluster of similar objects for which its similarity can clearly be stated in terms of the intent. We especially discuss FCs in case of music objects, called music FCs. Since a music FC is based solely on terminological information, we often find extracted FCs would not always be satisfiable from acoustic point of view. In order to improve their quality, we additionally require our FCs to be consistent with acoustic similarity. We design an efficient algorithm for extracting desirable music FCs. Our experimental results for The MagnaTagATune Dataset shows usefulness of the proposed method.

KEYWORDS

Formal concept analysis, music formal concepts, music objects, terminological similarity, acoustic similarity.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101601.pdf

Volume Link :
http://airccse.org/csit/V10N16.html

Yakoop Razzaz Hamoud Qasim, Habeb Abdulkhaleq Mohammed Hassan, Abdulelah Abdulkhaleq Mohammed Hassan
Taiz University, Yemen

ABSTRACT

In this paper we present a Convolutional Neural Network consisting of NASNet and MobileNet in parallel (concatenation) to classify three classes COVID-19, normal and pneumonia, depending on a dataset of 1083 x-ray images divided into 361 images for each class. VGG16 and RESNet152-v2 models were also prepared and trained on the same dataset to compare performance of the proposed model with their performance. After training the networks and evaluating their performance, an overall accuracy of 96.91%for the proposed model, 92.59% for VGG16 model and 94.14% for RESNet152. We obtained accuracy, sensitivity, specificity and precision of 99.69%, 99.07%, 100% and 100% respectively for the proposed model related to the COVID-19 class. These results were better than the results of other models. The conclusion, neural networks are built from models in parallel are most effective when the data available for training are small and the features of different classes are similar.

KEYWORDS

Deep Learning, Concatenation Technique, Convolutional Neural Networks, COVID-19, Transfer Learning.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101602.pdf

Volume Link :
http://airccse.org/csit/V10N16.html

Sergio Hidalgo-Espinoza, Kevin Chamorro-Cupuerán and Oscar Chang-Tortolero
University of Yachay Tech, Ecuador

ABSTRACT

Intrusion detection into computer networks has become one of the most important issues in cybersecurity. Attackers keep on researching and coding to discover new vulnerabilities to penetrate information security system. In consequence computer systems must be daily upgraded using up-to-date techniques to keep hackers at bay. This paper focuses on the design and implementation of an intrusion detection system based on Deep Learning architectures. As a first step, a shallow network is trained with labelled log-in [into a computer network] data taken from the Dataset CICIDS2017. The internal behaviour of this network is carefully tracked and tuned by using plotting and exploring codes until it reaches a functional peak in intrusion prediction accuracy. As a second step, an autoencoder, trained with big unlabelled data, is used as a middle processor which feeds compressed information and abstract representation to the original shallow network. It is proven that the resultant deep architecture has a better performance than any version of the shallow network alone. The resultant functional code scripts, written in MATLAB, represent a re-trainable system which has been proved using real data, producing good precision and fast response.

KEYWORDS

Artificial Neural Networks, Information Security, Deep Learning, intrusion detection & hacking attacks.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101501.pdf

Volume Link :
http://airccse.org/csit/V10N15.html

Qile He¹and Yu Sun^2
1Webber Academy, Canada ²California State Polytechnic University, USA

ABSTRACT

Many robot applications depend on solving the Complete Coverage Path Problem (CCPP). Specifically, robot vacuum cleaners have seen increased use in recent years, and some models offer room mapping capability using sensors such as LiDAR. With the addition of room mapping, applied robotic cleaning has begun to transition from random walk and heuristic path planning into an environment-aware approach. In this paper, a novel solution for pathfinding and navigation of indoor robot cleaners is proposed. The proposed solution plans a path from a priori cellular decomposition of the work environment. The planned path achieves complete coverage on the map and reduces duplicate coverage. The solution is implemented inside the ROS framework, and is validated with Gazebo simulation. Metrics to evaluate the performance of the proposed algorithm seek to evaluate the efficiency by speed, duplicate coverage and distance travelled.

KEYWORDS

Complete Coverage Path Planning, Mobile Robots, Graph Theory.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101502.pdf

Volume Link :
http://airccse.org/csit/V10N15.html

Saadia Drissi, Soukaina Elhasnaoui, Hajar Iguer, Siham Benhadou and Hicham Medromi
Hassan II University, Morocco

ABSTRACT

Cloud computing gives a relevant and adaptable support for Big Data by the ease of use, access to resources, low cost use of resources, and the use of strong equipment to process big data. Cloud and big data center on developing the value of a business while reducing capital costs.

Big data and cloud computing, both favor companies and by cause of their benefit, the use of big data growths extremely in the cloud. With this serious increase, there are several emerging risk security concerns. Big data has more vulnerabilities with the comparison to classical database, as this database are stored in servers owned by the cloud provider. The various usage of data make safety-related big data in the cloud intolerable with the traditional security measures.

The security of big data in the cloud needs to be looked at and discussed. In this current paper, my colleagues and me will present and discuss the risk assessment of big-data applications in cloud computing environments and present some ideas for assessing these risks.

KEYWORDS

Cloud computing, risk assessment, big data, security.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101503.pdf

Volume Link :
http://airccse.org/csit/V10N15.html

Richard Zhang¹, Mary Zhao¹, Yucheng Jiang², Sophadeth Rithya²and Yu Sun^2
1Irvine High School. 4321 Walnut Ave Irvine, CA 92604 ²California State Polytechnic University, Pomona, CA, 91768

ABSTRACT

Through our app, it is aimed to teach and tell the patients how to use the drug properly taking off the chances of putting their lives in danger, especially the elderly. It is also efficient to give patients these instructions as well as saving lots of paper. Because of the law, every drug that is given from the pharmacy to the user includes a receipt that lists information of, patient’s information, drug information, insurance information, directions on taking the medicine (black box warning issued by FDA), medication details on how it works, side effects, storage rules, and etc. These pieces of information are crucial to patients, where it tells them how to use the drug properly, but most people would throw these receipts away, which is a risk as well as a waste. Through using this app, the patient can efficiently get information on how to properly use the drug. This application is also helpful, where the user can choose to set reminders on when to eat this drug each week or month.

KEYWORDS

Cloud computing, risk assessment, big data, security.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101504.pdf

Volume Link :
http://airccse.org/csit/V10N15.html

Sami Ouali
College of Applied Sciences, Ibri, Oman

ABSTRACT

Software Product Lines (SPL) are recognized as a successful approach to reuse in software development. Its purpose is to reduce production costs. This approach allows products to be different with respect of particular characteristics and constraints in order to cover different markets. Software Product Line engineering is the production process in product lines. It exploits the commonalities between software products, but also to preserve the ability to vary the functionality between these products. Sometimes, an inappropriate implementation of SPL during this process can conduct to code smells or code anomalies. Code smells are considered as problems in source code which can have an impact on the quality of the derived products of an SPL. The same problem can be present in many derived products from an SPL due to reuse. A possible solution to this problem can be the refactoring which can improve the internal structure of source code without altering external behavior. This paper proposes an approach for building SPL from source code. Its purpose is to reduce code smells in the obtained SPL using refactoring source code. Another part of the approach consists on obtained SPL’s design based on reverse engineering.

KEYWORDS

Software Product Line, Code smells, Refactoring, Reverse Engineering.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101422.pdf

Volume Link :
http://airccse.org/csit/V10N14.html

Abhilash Pani, Jinendra Gugaliya and Mekapati Srinivas
Industrial Automation Technology Centre, ABB, India

ABSTRACT

Gas sample is conditioned using sample handling system (SHS) to remove particulate matter and moisture content before sending it through Continuous Emission Monitoring (CEM) devices. The performance of SHS plays a crucial role in reliable operation of CEMs and therefore, sensor-based condition monitoring systems (CMSs) have been developed for SHSs. As sensor failures impact performance of CMSs, a data driven soft-sensor approach is proposed to improve robustness of CMSs in presence of single sensor failure. The proposed approach uses data of available sensors to estimate true value of a faulty sensor which can be further utilized by CMSs. The proposed approach compares multiple methods and uses support vector regression for development of soft sensors. The paper also considers practical challenges in building those models. Further, the proposed approach is tested on industrial data and the results show that the soft sensor values are in close match with the actual ones.

KEYWORDS

Sample Handling System, Soft-Sensor, Variance Inflation Factor (VIF), Local Outlier Factor (LOF), Support Vector Regression.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101423.pdf

Volume Link :
http://airccse.org/csit/V10N14.html

Waleed Bin Owais, Iyad W. J. Alkhazendar and Mohammad Saleh
Qatar University, Qatar

ABSTRACT

Genetic Algorithm is an evolutionary algorithm and a metaheuristic that was introduced to overcome the failure of gradient based method in solving the optimization and search problems. The purpose of this paper is to evaluate the impact on the convergence of Genetic Algorithm vis-a‘-vis 0/1 knapsack. By keeping the number of generations and the initial population fixed, different crossover methods like one point crossover and two-point crossover were evaluated and juxtaposed with each other. In addition to this, the impact of different selection methods like rank-selection, roulette wheel and tournament selection were evaluated and compared. Our results indicate that convergence rate of combination of one point crossover with tournament selection, with respect to 0/1 knapsack problem that we considered, is the highest and thereby most efficient in solving 0/1 knapsack.

KEYWORDS

Genetic, Crossover, Selection, Knapsack, Roulette, Tournament, Rank, Single Point, Two Point, Convergence

For More Details :
https://aircconline.com/csit/papers/vol10/csit101101.pdf

Volume Link :
http://airccse.org/csit/V10N11.html

Jin-Chul Heo, Eun-Bin Park, Chan-Il Kim, Hee-Joon Park and Jong-Ha Lee
Keimyung University, Korea

ABSTRACT

For electromagnetic induction wireless power transmission using an elliptical receiving coil, we investigated changes in magnetic field distribution and power transmission efficiency due to changes in the position of the transmitting and receiving coils. The simulation results using the high-frequency structure simulator were compared with the actual measurement results. It has been shown that even if the alignment between the transmitting coil and the receiving coil is changed to some extent, the transmission efficiency on the simulator can be maintained relatively stable. The transmission efficiency showed the maximum when the center of the receiving coil was perfectly aligned with the center of the transmitting coil. Although the reduction in efficiency was small when the center of the receiving coil was within ± 10 mm from the center of the transmitting coil, it was found that the efficiency was greatly reduced when the receiving coil deviated by more than 10 mm. Accordingly, it has been found that even if the perfect alignment is not maintained, the performance of the wireless power transmission system is not significantly reduced. When the center of the receiving coil is perfectly aligned with the center of the transmitting coil, the transmission efficiency is maximum, and even if the alignment is slightly changed, the performance of wireless power transmission maintains a certain level. This result proposes a standardized wireless transmission application method in the use of wireless power for implantable sensors.

KEYWORDS

ECG, Implantable sensors, Simulation, Power transmission efficiency, Wireless power transmission

For More Details :
https://aircconline.com/csit/papers/vol10/csit101102.pdf

Volume Link :
http://airccse.org/csit/V10N11.html

Sangwoo Cho and Jong-Ha Lee
Keimyung University, South Korea

ABSTRACT

Usability evaluation of wireless device can find improvement about user convenience. This study investigated natural finger pressure range when presses touch sensor. Fifteen adults (Male: 10, Female: 5, Age: 26.13 ± 3.98 years) were recruited in this experiment. Subjects carried out a usability evaluation about wireless device operation. The usability evaluation measured finger pressure on touch sensor operation of wireless device using finger pressure sensor. Subjects performed 1.76±0.95 times until pressing the touch sensor to complete task (t = 3.091, p = 0.008). In comparisons between natural movement and the movement to complete task, more finger pressure value was decreased in natural movement than the movement to complete task (t = -2.277, p = 0.039). This study found a finger pressure values to improve effectiveness of wireless device operation interface. Finger pressure value was presented to induce natural movement for the use of touch sensor.

KEYWORDS

Usability Evaluation, Operation Interface, Finger Pressure Range, Wireless Device.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101104.pdf

Volume Link :
http://airccse.org/csit/V10N11.html

Smaranjit Ghose and Suhrid Datta
SRM Institute of Science and Technology, India

ABSTRACT

The pandemic of COVID-19 has been rapidly spreading across the globe since it first surfaced in the Wuhan province of China. Several governments are forced to have nationwide lockdowns due to the progressive increase in a daily number of cases. The hospitals and other medical facilities are facing difficulties to cope with the overwhelming number of patients they can provide support due to the shortage in the number of required medical professionals and resources for meeting this demand. While the vaccine to cure this disease is still on the way, early diagnosis of patients and putting them in quarantine has become a cumbersome task too. In this study, we propose to build an artificial intelligence-based system for classifying patients as COVID-19 positive or negative within a few seconds by using their chest CT Scans. We use a transfer learning approach to build our classifier model using a dataset obtained from openly available sources. This work is meant to assist medical professionals in saving hours of their time for the diagnosis of the Coronavirus using chest radiographs and not intended to be the sole way of diagnosis.

KEYWORDS

COVID-19, Deep Learning, CT Scans, Deep Convolutional Neural Networks, computer tomography scans

For More Details :
https://aircconline.com/csit/papers/vol10/csit101105.pdf

Volume Link :
http://airccse.org/csit/V10N11.html

Jan Stodt and Christoph Reich
University of Applied Sciences Furtwangen, Germany

ABSTRACT

Increased collaborative production and dynamic selection of production partners within industry 4.0 manufacturing leads to ever-increasing automatic data exchange between companies. Automatic and unsupervised data exchange creates new attack vectors, which could be used by a malicious insider to leak secrets via an otherwise considered secure channel without anyone noticing. In this paper we reflect upon approaches to prevent the exposure of secret data via blockchain technology, while also providing auditable proof of data exchange. We show that previous blockchain based privacy protection approaches offer protection, but give the control of the data to (potentially not trustworthy) third parties, which also can be considered a privacy violation. The approach taken in this paper is not utilize centralized data storage for data. It realizes data confidentiality of P2P communication and data processing in smart contracts of blockchains.

KEYWORDS

Blockchain, Privacy Protection, P2P Communication, Smart Contracts, Industry 4.0.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101001.pdf

Volume Link :
http://airccse.org/csit/V10N10.html

Amr Adel¹and Brian Cusack^2
1Whitecliffe College of Technology & Innovation, New Zealand ²Auckland University of Technology, New Zealand

ABSTRACT

Enhancements in technologies and shifting trends in customer behaviour have resulted in an increase in the variety, volume, veracity and velocity of available data for conducting digital forensic analysis. In order to conduct intelligent forensic investigation, open source information and entity identification must be collected. Challenge of organised crimes are now involved in drug trafficking, murder, fraud, human trafficking, and high-tech crimes. Criminal Intelligence using Open Source Intelligence Forensic (OSINT) is established to perform data mining and link analysis to trace terrorist activities in critical. In this paper, we will investigate the activities done by a suspect employee. Data mining is to be performed and link analysis as well to confirm all participating parties and contacted persons used in the communications. The proposed solution was to identify the scope of the investigation to limit the results, ensure that expertise and correct tools are ready to be implemented for identifying and collecting potential evidences. This enhanced information and knowledge achieved are of advantage in research. This form of intelligence building can significantly support real world investigations with efficient tools. The major advantage of analysing data links in digital forensics is that there may be case-related information included within unrelated databases.

KEYWORDS

Open Source Intelligence, Information Retrieval,Digital Forensics, Cyber-Crimes & Data Mining.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101002.pdf

Volume Link :
http://airccse.org/csit/V10N10.html

Gholam Aghashirin¹, Hoda S. Abdel-Aty-Zohdy¹, Mohamed A. Zohdy¹, Darrell Schmidt¹and Adam Timmons^2
1Oakland University, USA ²McMaster University, Canada

ABSTRACT

Antenna module is a vital component of automated driving systems, it should function as needed in dGPS, HD map correction services, and radio and navigation systems. The proposed antenna model for GPS only patch antenna operating at 1.57542 GHz and the GNSS patch antenna resonating at 1.5925 GHz are developed. This work presents the design, modelling, determining passive gain of the GPS patch vs. GNSS antenna with intended targeted applications within the automotive system. Simulation are undertaken to evaluate the performance of the proposed GNSS antenna. Simulation conducted in FEKO software rather than mathematical modelling. The two antennas are also compared from the size standpoint. The goal of this paper is to test, measure and evaluate the performance of GPS against GNSS antennas. Another emphasis of this paper is how to obtain the equivalent amount of total passive gain in a GPS vs. that of GNSS antenna.

KEYWORDS

Differential Global Position System (dGPS), Global Navigation Satellite System (GNSS), Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS), Advanced Driver Assistance Systems (ADAS), Automated Driving (AD), Modelling, comparison, measurements, analysis.

For More Details :
https://aircconline.com/csit/papers/vol10/csit101002.pdf

Volume Link :
https://aircconline.com/csit/papers/vol10/csit100901.pdf

Muhammad Azam, Derek Jacoby and Yvonne Coady
University of Victoria, Canada

ABSTRACT

Electroencephalogram (EEG) records electrical activity at different locations in the brain. It is used to identify abnormalities and support the diagnoses of different disease conditions. The accessibility of low-cost EEG devices has seen the analysis of this data become more common in other research domains. In this work, we assess the performance of using Approximate entropy, Sample entropy, and Reyni entropy as features in the classification of fatigue from EEG data captured by a MUSE 2 headset. We test 5 classifiers: Naive Bayes, Radial Basis Function Network, Support Vector Machine, K-Nearest Neighbor, and Best First Decision Tree. We achieved the highest accuracy of 77.5% using the Support Vector Machine classifier and present possible enhancements to improve this.

KEYWORDS

EEG, Electroencephalogram, Approximate entropy, Sample entropy, Reyni entropy, Fatigue detection, Automatic classification, MUSE 2

For More Details :
https://aircconline.com/csit/papers/vol10/csit100902.pdf

Volume Link :
https://aircconline.com/csit/papers/vol10/csit100901.pdf

Camille Salinesi¹, Clotilde Rohleder², Asmaa Achtaich^1,3, IndraKusumah^1,2
1CRI -Paris 1 Sorbonne University, Paris, France ²University of Applied Science HTWG Constanz, Germany ³Siweb – Université Mohammed 5, Rabat, Maroc

ABSTRACT

System engineering focuses on the realization of complex systems, from design all the way to management. Meanwhile, in the era of Industry 4.0 and Internet of Things, systems are getting more and more complex. This complexity comes from the usage of smart sub systems (e.g. smart objects, new communication protocols, etc.) and new engineering product development processes (e.g. through Open Innovation). These two aspects namely the IoTrelated sub system and product development process are our main discussion topics in our research work. The creation of smart objects such as innovative fleets of connected devices is a compelling case. Fleets of devices in smart buildings, smart cars or smart consumer products (e.g. cameras, sensors, etc.) are confronted with complex, dynamic, rapidly changing and resource-constrained environments. In order to align with these context fluctuations, we develop a framework representing the dimensions for building Self-adaptive fleets for IoT applications. The emerging product development process Open Innovation is proven to be three time faster and ten times cheaper than conventional ones. However, it is relatively new to the industry, and therefore, many aspects are not clearly known, starting from the specific product requirements definition, design and engineering process (task assignment), until quality assurance, time and cost. Therefore, acceptance of this new approach in the industry is still limited. Research activities are mainly dealing with high and qualitative levels. Whereas methods that supply more transparent numbers remain unlikely. The project-related risks are therefore unclear, consequently, the Go / noGo decisions become difficult. This paper contributes ideas to handle issues mentioned above by proposing a new integrated method, we call it InnoCrowd. This approach, from the perspective of IoT, can be used as a base for the establishment of a related decision support system.

KEYWORDS

Industry 4.0, Internet of Thing, Crowdsourcing, Neural Network, Decision Support System

For More Details :
https://aircconline.com/csit/papers/vol10/csit101002.pdf

Volume Link :
https://aircconline.com/csit/papers/vol10/csit100901.pdf