ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION

It has been successfully designed an Electronic Nose (e-Nose) instrumentation system consisting of 6 MQ gas sensors, namely, MQ2, MQ4, MQ5, MQ7, MQ9, MQ135. The E-nose system is used to identify halal-haram food. This E-Nose system uses an Arduino Nano microcontroller. The Graphic User Interface (GUI) system is built with Visual Studio 2008. Then, the data responses will be evaluated by using 2 patterns recognition methods called Principle Component Analysis (PCA). The classification results can be explained by the value of the score plot on the PCA of the data. PC1 accounts for 19% of the variance, and PC2 accounts for 5% of the variance, data obtained is stored and displayed on personal computers in Excel format. Each sample was tested for up to ten repetitions. The data obtained from the six sensors in the e-nose was processed using Minitab 18 and it was necessary to obtain classification data on lard, pig oil, and sample B, which were fried crackers using pork oil.

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Portable Electronic Nose Sebagai Instrumen Untuk Diskriminasi Aroma Kopi Robusta Jawa Dan Robusta Sumatera Yang Terkorelasi Dengan Gas Chromatography Mass Spectrometry

JURNAL ILMU FISIKA | UNIVERSITAS ANDALAS ◽

10.25077/jif.10.2.113-124.2018 ◽

2018 ◽

Vol 10 (2) ◽

pp. 113-124

Author(s):

Yesiana Arimurti ◽

Kuwat Triyana ◽

Sri Anggrahini

Keyword(s):

Mass Spectrometry ◽

Gas Chromatography ◽

Electronic Nose ◽

Principle Component Analysis ◽

Component Analysis ◽

Gas Chromatography Mass Spectrometry ◽

Principle Component ◽

Chromatography Mass Spectrometry

Kualitas kopi sangat dipengaruhi oleh aromanya. Sedangkan aroma kopi dapat diperngaruhi oleh banyak faktor, salah satunya daerah asal kopi. Oleh karena itu, instrumen uji aroma sangat dibutuhkan terutama untuk kendali mutu pada saat proses pengolahannya. Dalam penelitian ini, aroma kopi diuji menggunakan electronic nose yang hasilnya dikorelasi dengan gas chromatography mass spectrometry (GC-MS). Biji kopi jenis robusta yang berasal dari Pulau Jawa (DIY) dan Sumatera digunakan sebagai sampel uji. Penyangraian (roasting) dilakukan selama 20 menit pada suhu 210 °C. Setelah proses roasting, selanjutnya biji kopi dihaluskan menjadi bubuk dengan grinder. Pola respon masing-masing sensor gas dalam electronic nose terhadap setiap sampel bubuk kopi, direkam. Kemudian dilakukan ekstraksi ciri dengan menggunakan dua metode, yakni ekstraksi ciri gradien dikalikan dengan nilai puncak dan ekstraksi nilai rerata. Principle Component Analysis (PCA), diterapkan untuk proses diskriminasi aroma bubuk kopi. Hasil analisa GCMS menunjukkan bahwa ada perbedaan senyawa aromatik yang terdeteksi antara kopi robusta yang berasal dari pulau Jawa dan dari pulau Sumatera. Hasil ini terkorelasi dengan hasil diskriminasi aroma kopi robusta dengan menggunakan electronic nose. Selanjutnya, electronic nose mempunyai potensi digunakan pada industri kopi sebagai instrumen untuk keperluan kendali mutu selama proses pengolahan.Kata kunci: kopi robusta Jawa, robusta Sumatera, aroma, electronic nose, GC-MS

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ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

Recent Patents on Computer Science ◽

10.2174/2213275912666190819113541 ◽

2019 ◽

Vol 12 ◽

Cited By ~ 1

Author(s):

Basavaraj N Hiremath ◽

Malini M Patilb

Keyword(s):

Feature Extraction ◽

Computer Program ◽

Principle Component Analysis ◽

Voice Recognition ◽

Component Analysis ◽

Recognition System ◽

Principle Component ◽

Whole Process ◽

The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

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Four challenges for cognitive neuroscience and the cortico-hippocampal division of memory

Behavioral and Brain Sciences ◽

10.1017/s0140525x03370153 ◽

2003 ◽

Vol 26 (6) ◽

pp. 681-682

Author(s):

Harry Howard

Keyword(s):

Independent Component Analysis ◽

Recent Work ◽

Cognitive Neuroscience ◽

Principle Component Analysis ◽

Pattern Analysis ◽

Component Analysis ◽

Independent Component ◽

Principle Component ◽

Complementary Methods ◽

Current State

Jackendoff's criticisms of the current state of theorization in cognitive neuroscience are defused by recent work on the computational complementarity of the hippocampus and neocortex. Such considerations lead to a grounding of Jackendoff's processing model in the complementary methods of pattern analysis effected by independent component analysis (ICA) and principle component analysis (PCA).

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