Espectroscopia de absorção de intracavidade com lasers de fibra dopada com Er3+

Mestrado em Engenharia FísicaEspectroscopia de absorção de intracavidade com um laser de banda larga de fibra dopada com Er3+ é aplicada para medidas resolvidas no tempo de moléculas de CO2 revelando informações quantitativas sobre a concentração do gás exalado na respiração humana. A gama espectral das medições estende-se de 1.52 μm – 1.61 μm através da deslocação da lente de intracavidade. Com um laser pulsado aplicado nesta experiência, a sensibilidade à absorção corresponde a um comprimento do percurso de absorção efectiva de 6 km assumindo que a cavidade está completamente preenchida com a amostra. O aumento da sensibilidade é alcançada através da construção de um laser de configuração em anel unidirecional. O comprimento do percurso de absorção efectiva é aumentado por um factor de três comparando com uma configuração linear com o mesmo comprimento da cavidade.Intracavity absorption spectroscopy with a broadband Er3+-doped fiber laser is applied for time-resolved measurements of CO2 molecules revealing quantitative information about the gas concentration in exhaled human breath. The spectral range of measurements extends from 1.52 to 1.61 μm by moving an intracavity lens. With a pulsed laser applied in this experiment, the sensitivity to absorption corresponds to an effective absorption path length of 6 km assuming the cavity is completely filled with the sample. Sensitivity enhancement is achieved by employing an unidirectional ring laser. The effective absorption path length is enhanced by a factor of three compared to a linear configuration with the same cavity length

SELEKSI FITUR AIR MENGGUNAKAN RANK SPEARMAN DAN PRODUCT MOMENT PEARSON PADA PENGENALAN POLA STATUS MUTU AIR SUNGAI

Air sungai merupakan salah satu komoditas penting dalam kehidupan. Pemantauan kualitas air sangat perlu dilakukan untuk menjamin mutu baku air. Pada saat ini pengujian mutu baku air dilakukan dengan banyak parameter sehingga membuat biaya semakin meningkat dan memakan banyak waktu. Penelitian ini menggunakan data yang diperoleh peneliti dari PT JASA TIRTA 1 yaitu kualitas mutu baku sungai Brantas. Data yang diberikan menggunakan 22 parameter penentuan mutu baku air sehingga dirasakan jika nantinya dikembangkan suatu sistem maka akan memakan banyak memori dan membuat biaya semakin meningkat. Sehingga diperlukan pengurangan jumlah parameter namun tingkat akurasi yang dihasilkan tidak jauh berbeda. Berdasarkan hal tersebut peneliti mencoba melakukan seleksi fitur untuk menentukan parameter berpengaruh menggunakan metode Rank Spearman dan Product Moment Pearson. Proses klasifikasi dilakukan dengan Learning Vektor Quantization. Dari penelitian yang dilakukan di dapatkan 5 parameter paling berpengaruh yaitu “DHL, BOD, COD, TSS, NO2N”. Pada proses klasifikasi didapat Tingkat akurasi sebelum seleksi fitur adalah tertinggi dengan α 0.5 dan reduce α 0.5 sebesar 66,625%, dan terendah α 1 reduce α 0.25 sebesar 56,65 %. Dan Tingkat akurasi setelah seleksi fitur dengan mengguakan metode LVQ adalah tertinggi dengan α 0.5 dan reduce α 0.5 sebesar 67,475 % serta nilai terendah α 1 dan reduce α 0.25 sebesar 61,55 %. Dari peneltian ini disimpulkan bahwa metode Rank Spearman dan Product Moment Pearson dapat digunakan sebagai metode seleksi fitur kualitas mutu baku air karena memiliki tingkat akurasi yang mendekati sama dengan sebelum dilakukan seleksi fitur. Kata kunci : Pengenalan Pola, Seleksi Fitur, Rank Spearman, Product Moment Pearson, Learning Vektor Quantizatio

Detection and Identification of Odorants Using an Electronic Nose

Gas sensing systems for detection and identification of odor-ant molecules are of crucial importance in an increasing number of applications. Such applications include environmental moni-toring, food quality assessment, airport security, and detection of hazardous gases. In this paper, we describe a gas sensing system for detecting and identifying volatile organic compounds (VOCs), and discuss the unique problems associated with the separability of signal patterns obtained by using such a system. We then present solutions for enhancing the separability of VOC pattems to enable classification. A new incremental leaming algorithm that allows new odorants to be leamed is also introduced. 1

Detection And Identification Of Odorants Using An Electronic Nose

Gas sensing systems for detection and identification of odorant molecules are of crucial importance in an increasing number of applications. Such applications include environmental monitoring, food quality assessment, airport security, and detection of hazardous gases. In this paper, we describe a gas sensing system for detecting and identifying volatile organic compounds (VOCs), and discuss the unique problems associated with the separability of signal patterns obtained by using such a system. We then present solutions for enhancing the separability of VOC patterns to enable classification. A new incremental learning algorithm that allows new odorants to be learned is also introduced