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Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System Teddy Surya Gunawan; Muhammad Hamdan Hasan Gani; Farah Diyana Abdul Rahman; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 5, No 4: December 2017
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v5i4.361

Nowadays, there is a growing interest in the smart home system using Internet of Things. One of the important aspect in the smart home system is the security capability which can simply lock and unlock the door or the gate. In this paper, we proposed a face recognition security system using Raspberry Pi which can be connected to the smart home system. Eigenface was used the feature extraction, while Principal Component Analysis (PCA) was used as the classifier. The output of face recognition algorithm is then connected to the relay circuit, in which it will lock or unlock the magnetic lock placed at the door. Results showed the effectiveness of our proposed system, in which we obtain around 90% face recognition accuracy. We also proposed a hierarchical image processing approach to reduce the training or testing time while improving the recognition accuracy.

A novel optimization harmonic elimination technique for cascaded multilevel inverter Ezzidin Hassan Aboadla; Sheroz Khan; Mohamed H. Habaebi; Teddy Surya Gunawan; Belal A. Hamida; Mashkuri Bin Yaacob; Ali Aboadla
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

The main goal of utilizing Selective Harmonic Elimination (SHE) techniques in Multilevel Inverters (MLI) is to produce a high-quality output voltage signal with a minimum Total Harmonic Distortion (THD). By calculating N switching angles, SHE technique can eliminate (N-1) low order odd harmonics of the output voltage waveform. To optimized and obtained these switching angles, N of nonlinear equations should be solved using a numerical method. Modulation index (m) and duty cycle play a big role in selective harmonic elimination technique to obtain a minimum harmonic distortion and desired fundamental component voltage. In this paper, a novel Optimization Harmonic Elimination Technique (OHET) based on SHE scheme is proposed to re-mitigate Total Harmonic Distortion. The performance of seven-level H-bridge cascade inverter is evaluated using PSIM and validated experimentally by developing a purposely built microcontroller-based printed circuit board.

The disruptometer: an artificial intelligence algorithm for market insights Mimi Aminah binti Wan Nordin; Dmitry Vedenyapin; Muhammad Fahreza Alghifari; Teddy Surya Gunawan
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters-Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies.

A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.

On the use of voice activity detection in speech emotion recognition Muhammad Fahreza Alghifari; Teddy Surya Gunawan; Mimi Aminah binti Wan Nordin; Syed Asif Ahmad Qadri; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Emotion recognition through speech has many potential applications, however the challenge comes from achieving a high emotion recognition while using limited resources or interference such as noise. In this paper we have explored the possibility of improving speech emotion recognition by utilizing the voice activity detection (VAD) concept. The emotional voice data from the Berlin Emotion Database (EMO-DB) and a custom-made database LQ Audio Dataset are firstly preprocessed by VAD before feature extraction. The features are then passed to the deep neural network for classification. In this paper, we have chosen MFCC to be the sole determinant feature. From the results obtained using VAD and without, we have found that the VAD improved the recognition rate of 5 emotions (happy, angry, sad, fear, and neutral) by 3.7% when recognizing clean signals, while the effect of using VAD when training a network with both clean and noisy signals improved our previous results by 50%.

A novel optimization harmonic elimination technique for cascaded multilevel inverter Ezzidin Hassan Aboadla; Sheroz Khan; Mohamed H. Habaebi; Teddy Surya Gunawan; Belal A. Hamida; Mashkuri Bin Yaacob; Ali Aboadla
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

The main goal of utilizing Selective Harmonic Elimination (SHE) techniques in Multilevel Inverters (MLI) is to produce a high-quality output voltage signal with a minimum Total Harmonic Distortion (THD). By calculating N switching angles, SHE technique can eliminate (N-1) low order odd harmonics of the output voltage waveform. To optimized and obtained these switching angles, N of nonlinear equations should be solved using a numerical method. Modulation index (m) and duty cycle play a big role in selective harmonic elimination technique to obtain a minimum harmonic distortion and desired fundamental component voltage. In this paper, a novel Optimization Harmonic Elimination Technique (OHET) based on SHE scheme is proposed to re-mitigate Total Harmonic Distortion. The performance of seven-level H-bridge cascade inverter is evaluated using PSIM and validated experimentally by developing a purposely built microcontroller-based printed circuit board.

The disruptometer: an artificial intelligence algorithm for market insights Mimi Aminah binti Wan Nordin; Dmitry Vedenyapin; Muhammad Fahreza Alghifari; Teddy Surya Gunawan
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters-Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies.

A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.

On the use of voice activity detection in speech emotion recognition Muhammad Fahreza Alghifari; Teddy Surya Gunawan; Mimi Aminah binti Wan Nordin; Syed Asif Ahmad Qadri; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Emotion recognition through speech has many potential applications, however the challenge comes from achieving a high emotion recognition while using limited resources or interference such as noise. In this paper we have explored the possibility of improving speech emotion recognition by utilizing the voice activity detection (VAD) concept. The emotional voice data from the Berlin Emotion Database (EMO-DB) and a custom-made database LQ Audio Dataset are firstly preprocessed by VAD before feature extraction. The features are then passed to the deep neural network for classification. In this paper, we have chosen MFCC to be the sole determinant feature. From the results obtained using VAD and without, we have found that the VAD improved the recognition rate of 5 emotions (happy, angry, sad, fear, and neutral) by 3.7% when recognizing clean signals, while the effect of using VAD when training a network with both clean and noisy signals improved our previous results by 50%.

On the Review and Setup of Security Audit using Kali Linux Teddy Surya Gunawan; Muhammad Kassim Lim; Nurul Fariza Zulkurnain; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp51-59

The massive development of technology especially in computers, mobile devices, and networking has bring security issue forward as primarily concern. The computers and mobile devices connected to Internet are exposed to numerous threats and exploits. With the utilization of penetration testing, vulnerabilities of a system can be identified and simulated attack can be launched to determine how severe the vulnerabilities are. This paper reviewed some of the security concepts, including penetration testing, security analysis, and security audit. On the other hand, Kali Linux is the most popular penetration testing and security audit platform with advanced tools to detect any vulnerabilities uncovered in the target machine. For this purpose, Kali Linux setup and installation will be described in more details. Moreover, a method to install vulnerable server was also presented. Further research including simulated attacks to vulnerable server on both web and firewall system will be conducted.

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