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IoT based security system and intelligent home automation multi monitoring and control systems

10.11591/ijra.v8i3.pp205-210
Mohammed H. Ali , Nisreen K. Ali
This paper presents the execution of savvy Smart Home with frameworks and propelled advances. A Home Automation System uses the technology of IoT for the screening and controlling of the electrical and electronic appliances at home from any remote area by essentially utilizing a Smartphone. The key control framework utilizes a remote Bluetooth system and a remote IoT strategy that gives remote access to the advanced cells. The framework configuration does not expel the current electrical switches yet it gives a more secure control over it with the low voltage utilization method. This framework is intended to control electrical gadgets all through the house easily by introducing it, usability, savvy plan and actualize. There has been rising interest for a secure framework that must be tried, true and fast in reaction to the ventures and organization. Arduino makes the circuit and programming technology to design and operate wireless water monitoring system. The Water level in the tank is displayed on the Smartphone by the Water level app.
Volume: 8
Issue: 3
Page: 205-210
Publish at: 2019-09-01

Fuzzy neuro-genetic approach for feature selection and image classification in augmented reality systems

10.11591/ijra.v8i3.pp194-204
Rajendra Thilahar C. , Sivaramakrishnan R.
In this paper, a new approach for implementing an Augmented Reality system by applying fuzzy genetic neural networks is proposed. It consists of two components namely feature selection and classification modules. For feature detection, extraction and selection, the proposed model uses a fuzzy logic based incremental feature selection algorithm which has been proposed in this work in order to recognize the important features from 3D images. Moreover, this paper explains the implementation and results of the proposed algorithms for an Augmented Reality system using image recognition, feature extraction, feature selection and classification by  considering the global and local features of the images. For this purpose, we propose a three layer fuzzy neural network that has been implemented based on weight adjustments using fuzzy rules in the convolutional neural networks with genetic algorithm for effective optimization of rules. The classification algorithm is also based on fuzzy neuro-genetic approach which consists of two phases namely Training phase and testing phase. During the training phase, rules are formed based on objects and these rules are applied during the testing phase for recognizing the objects which can be used in robotics for effective object recognition. From the experiments conducted in this work, it is proved that the proposed model is more accurate in 3D object recognition.
Volume: 8
Issue: 3
Page: 194-204
Publish at: 2019-09-01

A crucial study focuses on demand based Indian hotel industry energy efficiency needs by comparing two model theory by Cholesky decomposition

10.11591/ijra.v8i3.pp211-216
Pankaj Aswal , Manish Kumar , Prateek Negi
Hotels operate on a stringent 24/7 operational model, every day operational model. They offer both top notch facilities and various civilities, including nearby workplaces, world-class wellness focuses, spas, warmed swimming pools, 24-hour eateries, and then some. These advantages add to visitor comforts additionally increment add up to vitality cost. While inn vitality utilization can appear to be stunning, the plenty of administrations and conveniences offer various open doors for vitality funds. The test for inn proprietors is choosing the ideal course to vitality reduction. Two methods top the list: energy audits and retro-commissioning To pick the best game-plan for a particular inn property, proprietors must survey the two strategies and recognize which arrangement would have the best effect on their building. The two procedures handle vitality use from various points, so here's a manual for what every involves and how it can enhance inn operations.
Volume: 8
Issue: 3
Page: 211-216
Publish at: 2019-09-01

Radial basis function neural network for head roll prediction modelling in a motion sickness study

10.11591/ijeecs.v15.i3.pp1637-1644
Sarah ‘Atifah Saruchi , Mohd Hatta Mohammed Ariff , Mohd Ibrahim Shapiai , Nurhaffizah Hassan , Nurbaiti Wahid , Noor Jannah Zakaria , Mohd Azizi Abdul Rahman , Hairi Zamzuri
Motion Sickness (MS) is the result of uneasy feelings that occurs when travelling. In MS mitigation studies, it is necessary to investigate and measure the occupant’s Motion Sickness Incidence (MSI) for analysis purposes. One way to mathematically calculate the MSI is by using a 6-DOF Subjective Vertical Conflict (SVC) model. This model utilises the information of the vehicle lateral acceleration and the occupant’s head roll angle to determine the MSI. The data of the lateral acceleration can be obtained by using a sensor. However, it is impractical to use a sensor to acquire the occupant’s head roll response. Therefore, this study presents the occupant’s head roll prediction model by using the Radial Basis Function Neural Network (RBFNN) method to estimate the actual head roll responses. The prediction model is modelled based on the correlation between lateral acceleration and head roll angle during curve driving. Experiments have been conducted to collect real naturalistic data for modelling purposes. The results show that the predicted responses from the model are similar with the real responses from the experiment. In future, it is expected that the prediction model will be useful in measuring the occupant’s MSI level by providing the estimated head roll responses.
Volume: 15
Issue: 3
Page: 1637-1644
Publish at: 2019-09-01

Emotional speech feature selection using end-part segmented energy feature

10.11591/ijeecs.v15.i3.pp1374-1381
Noor Aina Zaidan , Md Sah Hj Salam
The accuracy of human emotional detection is crucial in the industry to ensure effective conversations and messages delivery. The process involved in identifying emotions must be carried out properly and using a method that guarantees high level of emotional recognition. Energy feature is said to be a prosodic information encoder and there are still studies on energy use in speech prosody and it motivate us to run an experiment on energy features. We have conducted two sets of studies: 1) whether local or global features that contribute most to emotional recognition and 2) the effect of the end-part segment length towards emotion recognition accuracy using 2 types of segmentation approach. This paper discussed about Absolute Time Intervals at Relative Positions (ATIR) segmentation approach and global ATIR (GATIR) using end-part segmented global energy feature extracted from Berlin Emotional Speech Database (EMO-DB). We observed that global feature contribute more to the emotional recognition and global features that are derived from longer segments give higher recognition accuracy than global feature derived from short segments. The addition of utterance-based feature (GTI) to ATIR segmentation somewhat contributes to increase the accuracy by 5% up to 8% and conclude that GATIR outperformed ATIR segmentation approached in term of its higher recognition rate. The results of this study where almost all the sub-tests provide an increased result proving that global feature derived from longer segment lengths acquire more emotional information and enhance the system performance.
Volume: 15
Issue: 3
Page: 1374-1381
Publish at: 2019-09-01

Interval type-2 fuzzy logic controller design for distillation column process

10.11591/ijra.v8i3.pp155-163
Mohammed Y. Hassan , Sebal S. Ezzaten
Distillation columns are the most units used in oil refineries, and chemical factories. This is a very difficult process and non-linear. Therefore, the development of intelligent control systems for the columns of the distillation is very difficult. In this paper, an intelligent control strategy using Mamdani type Interval Type-2 PI Like Fuzzy Logic Controller (IT2FLC) is used. The controller consists of PD-Like FLC with integrated output. Kernek Mendel (KM) algorithm is used as the type reduction method for the IT2FLC. This controller is applied to control a continuous binary trays distillation column. The controller has three tunable gains to reach minimum overshoot, minimum error and minimum settling time at least variables can be controlled. The controller is a variable of the molar fraction of distillate and the reflex ratio is the manipulated variable. Integral Time Absolute Error (ITAE) is employed as an objective function to measure the improvement in time response where the error is between desired and output product composition. The performance of IT2FLC is compared with Type-1 PI Like FLC (T1FLC). The results of the simulations have shown that the project of IT2FLC works efficiently to no- disturbance and the effects of disturbance. Improve average is of 85% for a constant set-point without a disturbance and 80% with a disturbance. Furthermore, the average improvement for a step set-point is 53% without disturbance and 74% with disturbance. All results of the simulation confirmed the hardiness and control any consistent inaccurate with obvious advantages for the IT2FLC.
Volume: 8
Issue: 3
Page: 155-163
Publish at: 2019-09-01

A survey on readiness of cloud based queuing management system implementation to mobile users

10.11591/ijeecs.v15.i3.pp1544-1552
A. H., Mohd Saleh , N. A., Mohamed Radzi , W. S. H. M., Wan Ahmad , C. B. M. Rashidi
Queuing Management System (QMS) has been used in medical facilities to manage crowd systematically and reduce customer dissatisfaction. However, customers that use conventional QMS needs to be within the facility to have access to the QMS information. With the integration of mobile application and cloud based QMS, customers are able to access QMS information anywhere. However, migrating to a new technology requires a study on the readiness of the system. Hence, the objective of this study is to understand the effect of implementing QMS by investigating the effect of time efficiency, cost efficiency, accessibility, reliability, variety, convenience towards customer satisfaction. 311 respondents were given survey questions with 100% response rate. The results were analysed using Statistical Package for the Social Sciences. For reliability analysis, the survey questions were proven to be valid, where factor analysis done supports the results to be effective for further analysis. Correlation and regression analysis done also show that there are influences between the independent variables and the dependent variable.
Volume: 15
Issue: 3
Page: 1544-1552
Publish at: 2019-09-01

Developing an expert system method for assessment of destructive information-psychological influence

10.11591/ijeecs.v15.i3.pp1571-1577
Bilal Zahran , Jamil AL-Azzeh , Andrii Gizun , Vladyslav Griga , Bogdana Bystrova
Nowadays solving practical problems in various sectors using intelligent solutions, based on expert systems are becoming more and more widespread. In this paper an expert system method is proposed for assessment and prediction of destructive influences. All disadvantages of existing assessment systems are taken into account during the development and analysis phases. The most important estimated parameters are determined. This method is based on quantitative methods of expert evaluation, which gives the advantage: there is no need to collect large amounts of statistical data and clear formalization of the current situation.
Volume: 15
Issue: 3
Page: 1571-1577
Publish at: 2019-09-01

What is critical thinking? A longitudinal study with teacher candidates

10.11591/ijere.v8i3.20254
Serap Yılmaz Özelçi , Gürbüz Çalışkan
Critical thinking skills that enhance the ability of individuals to understand and make sense of the world and events and situations around them are one of the foremost research areas in the educational system of various countries. As a critical thinking individual, decisions made by the teacher in his/her class, the activities he/she has performed and the explicit and implicit messages given by him/her to the class are clearly observed by the students. It is believed that the situation of teachers’ having critical thinking skills and critical thinking personality effects on students' perceptions and achievements about critical thinking. In this context, the aim of the research is to determine the perceptions of the teacher candidates about critical thinking and to observe the changes in these perceptions over time. Interviews were held with 11 prospective teachers for two times for 4 years and their thoughts on critical thinking were examined. According to the findings obtained, the thoughts of the teacher candidates regarding the critical thinking do not change over time but they are not seen enough. Teacher candidates make decisions with emotional references and they are reluctant to inquire and research.
Volume: 8
Issue: 3
Page: 495-509
Publish at: 2019-09-01

Modified fingerprinting localization technique of indoor positioning system based on coordinates

10.11591/ijeecs.v15.i3.pp1345-1355
Rhowel M. Dellosa , Arnel C. Fajardo , Ruji P. Medina
The fingerprinting localization technique is the most commonly used localization technique of the indoor positioning system. It is used by several technologies for short and long range position estimation like wireless fidelity and radio frequency. There are several schemes used to estimate a location for the indoor environment but the drawbacks resulted in complexity issues. These drawbacks have negative effects on location estimation. In order to address these drawbacks, this work attempted to explore the fingerprinting localization technique for location estimation of the indoor environment that focuses on position estimation. Results showed that the simplicity of the design of position estimation without compromising the functionality of the operations was observed with 100% accuracy on position estimation.
Volume: 15
Issue: 3
Page: 1345-1355
Publish at: 2019-09-01

Image and audio fractal compression: comprehensive review, enhancements and research directions

10.11591/ijeecs.v15.i3.pp1564-1570
Ahmed Huaasin Ali , Ali Nihad Abbas , Loay Edwar George , Mohd Rosmadi Mokhtar
This study aims to review the recent techniques in digital multimedia compression with respect to fractal coding techniques. It covers the proposed fractal coding methods in audio and image domain and the techniques that were used for accelerating the encoding time process which is considered the main challenge in fractal compression. This study also presents the trends of the researcher's interests in applying fractal coding in image domain in comparison to the audio domain. This review opens directions for further researches in the area of fractal coding in audio compression and removes the obstacles that face its implementation in order to compare fractal audio with the renowned audio compression techniques.
Volume: 15
Issue: 3
Page: 1564-1570
Publish at: 2019-09-01

A novel intelligent model for classify and evaluating non-functional security requirements form scenarios

10.11591/ijeecs.v15.i3.pp1578-1585
Akram AbdelKarim AbdelQader
Software requirements with its functional and non-functional methods are the first important phase in producing a software system with free errors. The functional requirements are the visual actions that may easily evaluated from the developer and from the user, but non-functional requirements are not visual and need a lot of efforts to be evaluated. One of the main important non-functional requirements is security, which focuses on generating secure systems from strangers. Evaluating the security of the system in earlier steps will help to reduce the efforts of reveals critical system threats. Security threats found because of leaking of security scenarios in requirement phase. In this paper, we purpose an intelligent model to extract and evaluate security features from scenarios based on set of security system goals and a set of security requirements saved on rich story scenarios dataset (RSSD). This model will used a support vector machine (SVM) classifier to classify the security requirement based on RSS dataset.  The using of SVM will enhance the overall process of evaluating the security requirements. The results show a significant enhancement in security improvements.
Volume: 15
Issue: 3
Page: 1578-1585
Publish at: 2019-09-01

A review on data clustering using spiking neural network (SNN) models

10.11591/ijeecs.v15.i3.pp1392-1400
Siti Aisyah Mohamed , Muhaini Othman , Mohd Hafizul Afifi
The evolution of Artificial Neural Network recently gives researchers an interest to explore deep learning evolved by Spiking Neural Network clustering methods. Spiking Neural Network (SNN) models captured neuronal behaviour more precisely than a traditional neural network as it contains the theory of time into their functioning model [1]. The aim of this paper is to reviewed studies that are related to clustering problems employing Spiking Neural Networks models. Even though there are many algorithms used to solve clustering problems, most of the methods are only suitable for static data and fixed windows of time series. Hence, there is a need to analyse complex data type, the potential for improvement is encouraged. Therefore, this paper summarized the significant result obtains by implying SNN models in different clustering approach. Thus, the findings of this paper could demonstrate the purpose of clustering method using SNN for the fellow researchers from various disciplines to discover and understand complex data.
Volume: 15
Issue: 3
Page: 1392-1400
Publish at: 2019-09-01

A predictive model for prediction of heart surgery procedure

10.11591/ijeecs.v15.i3.pp1615-1620
Aufzalina Mohd Yusof , Nor Azura Md. Ghani , Khairul Asri Mohd Ghani , Khairul Izan Mohd Ghani
Coronary heart disease (CHD) is a disease in which plague in the form of waxy substance builds up inside the coronary arteries. Coronary artery bypass grafting (CABG) is used as treatment on CHD patients but the role of CABG has been challenged by percutaneous coronary intervention (PCI) when it was introduced in 1977.  Drug eluting stents (DES) was introduced with the development of PCI. The purpose of this study was to find the potential risk factors that associated with the procedures (CABG and DES) and to model procedure (CABG vs DES) on coronary heart disease male patients aged 45 years old and below. The study sample was among male patients aged 45 years old and below who has undergone CABG or DES procedure at either IJN or HUKM  from January 2007 until December 2010. Logistic regression was used to model treatment selection on coronary heart disease with 87.3% of the classification rate. Patient who i) smoke, ii) obese, or ii) had dyslipidemia was significantly associated with DES, and the other factors were prone to have CABG as their treatment.
Volume: 15
Issue: 3
Page: 1615-1620
Publish at: 2019-09-01

Intelligent risk management framework

10.11591/ijai.v8.i3.pp278-285
Wissam Abbass , Zineb Bakraouy , Amine Baina , Mostafa Bellafkih
The Internet of Things (IoT) is rapidly increasing and enhancing today’s world by introducing a large set of interconnected devices. Several beneficial services are produced by these devices as for area monitoring and process control. However, IoT security is still a major problem. In fact, IoT’ security beggings largely whith an effective Risk Management process. However, the essense of this process is to acquire a risk inventory cibling the IoT devices. Nevertheless, it is quite difficult to obtaining this latter which significantly adds complication issues to the Risk Management. Without the ability of holisticly identify the IoT critical devices, inaccurate Risk Management is achieved which leads unfortunately to novel risk exposures. Traditional Riskbased approaches fails drastically at apprending IoT’ potential attacks. The dynamic structure, the heteregouns nature of devices, the various security objectives and infrastructure pervasiveness are key factors impacting the overall perfomance. Thus, a holistic Risk Management witihin the IoT is indispensable. Accordingly, we propose an intelligent Risk Management framework using Mobile Agents in order to deliver preventive and responsive assessment.
Volume: 8
Issue: 3
Page: 278-285
Publish at: 2019-09-01
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