Hasil Pencarian  ::  Simpan CSV :: Kembali

Abstrak :
Latar Belakang: Indonesia menduduki urutan kedua terbanyak kasus karsinoma nasofaring (KNF) di dunia. CT masih menjadi modalitas awal untuk mendeteksi KNF. Akan tetapi gambaran CT pada KNF kadang sulit untuk dibedakan dengan nasofaringitis kronis (NFK) terutama jika ukuran tumor masih kecil. Texture analysis (TA) merupakan suatu metode matematika yang digunakan untuk menganalisis distribusi dan hubungan pixel gray level suatu gambar. TA banyak diteliti di bidang onkologi kepala dan leher untuk membedakan karakteristik tumor, jinak atau ganas, menilai respon terapi serta memprediksi prognosis pasien. Metode: Studi komparatif dengan desain potong lintang. Terdapat 27 sampel KNF dan 18 sampel NFK yang dilakukan ROI pada regio tumor, kemudian dilakukan pengukuran nilai histogram yang terdiri dari mean, skewness, kurtosis dan nilai grey level co-occurencce matrix (GLCM) terdiri dari homogeinity, energy, contrast, correlation, entropy. Nilai yang diperoleh dari kedua kelompok kemudian dibandingkan dengan menggunakan T-test atau Mann-Whitney U Test. Hasil: Tidak didapatkan perbedaan signifikan secara statistik untuk mean (P = 0,098), kurtosis (P = 0,914), skewness (P = 0,775), Homogeinity (P = 0,943), Energy (P = 0,745), Contrast (P = 0,891), Correlation (P = 0,517), Entropy (P = 0,286) antara kelompok KNF dan NFK Kesimpulan: Tidak terdapat perbedaan signifikan dari nilai histogram (mean, skewness, kurtosis) dan nilai GLCM (homogeinity, energy, contrast, correlation, entropy) antara kelompok KNF dan NFK. ......Background: : Indonesia is the second country with most nasopharyngeal carcinoma (NPC) cases in the world. CT is still the initial modality for detecting NPC. However, CT imaging of NPC are sometimes difficult to distinguish from chronic nasopharyngitis (CNP), especially with small tumor size. Texture analysis (TA) is a mathematical method used to analyze the distribution and relationship of gray level pixels of an image. TA is widely studied in head and neck oncology to distinguish the characteristics of tumors, benign or malignant, assess response to therapy and predict patient prognosis. Methods: This is a cross-sectional comparative study. There were 27 NPC samples and 18 CNP samples with ROI performed on the tumor region, then measured the histogram value consisting of mean, skewness, kurtosis and the gray level co-occurrence matrix (GLCM) consisting of homogeinity, energy, contrast, correlation, entropy. The values between two groups were then compared using the T-test or the Mann-Whitney U Test. Results: There were no statistically significant differences for mean (P = 0.098), kurtosis (P = 0.914), skewness (P = 0.775), Homogeinity (P = 0.943), Energy (P = 0.745), Contrast (P = 0.891), Correlation (P = 0.517), Entropy (P = 0.286) between NPC and CNP group. Conclusion: There were no significant difference for histogram values (mean, skewness, kurtosis) and GLCM values (homogeinity, energy, contrast, correlation, entropy) between the NPC and NFK groups.

Abstrak :
World Health Organisation (WHO) has predicted 300 million peoples will suffer of diabetic in 2025. Long-term diabetics can lead to diabetic retinopathy that can cause blindness in developing countries. One of the abnormalities of diabetic retinopathy is exudate. Exudates are classified into two categories, i.e. hard and soft exudates. This paper proposes feature extraction based on texture for distinguishing hard, soft and non-exudates. The green channel of the original images is enhanced by CLAHE and followed by median filtering and thresholding in red channel to detect and remove the optic disc. The enhanced image is segmented based on clustering to obtain the region of interest of exudates. Feature extraction based on texture is conducted by using GLCM and lacunarity. Results show that classification based on NaïveBayes algorithm achieves accuracy, specificity and sensitivity of 92.13%, 96% and 87.18%, respectively.

Abstrak :
ABSTRAK
Digitally reconstructed radiographs (DRRs) merupakan citra hasil rekonstruksi data set citra CT simulator yang digunakan untuk verifikasi dalam perencanaan radioterapi eksternal. Penelitian ini mencoba untuk mengimplementasikan algoritma ray casting dan hardware texture mapping sehingga dapat menghasilkan citra DRR. Akuisisi citra CT simulator dilakukan terhadap fantom modifikasi, fantom Catphan, dan fantom RANDO. Citra CT simulator kemudian dikomputasi dengan menggunakan algoritma yang digunakan serta algoritma di dalam treatment planning system (TPS). Evaluasi hasil citra DRR dilakukan secara kuantitatif dan kualitatif. Evaluasi kuantitatif meliputi evaluasi keakurasian geometri, evaluasi kontras tinggi, evaluasi kontras rendah, evaluasi uniformitas, dan evaluasi running time. Evaluasi kualitatif berupa kuesioner yang berisi pendapat praktisi radioterapi mengenai kualitas citra DRR dalam hal kontras, resolusi, dan uniformitas. Hasil evaluasi kuantitatif menunjukkan kualitas citra DRR dari algoritma dalam penelitian ini hampir sama dengan algoritma di dalam TPS dan hasil tersebut didukung oleh hasil evaluasi kualitatif.

---

ABSTRACT
Digitally reconstructed radiographs (DRRs) are the CT simulator image reconstruction that used for verification in external radiotherapy planning. This thesis aims to implementation of ray casting and hardware texture mapping algorithm to produce DRR images. CT image acquisition is made to modification phantom, Catphan phantom, and RANDO phantom. These images then computed become DRR images using ray casting and hardware texture mapping algorithm, as well as the algorithm used in the treatment planning system (TPS) . Evaluation of the DRR images conducted quantitatively and qualitatively. Quantitative evaluation includes evaluation of geometric accuracy, high contrast, low contrast, grey scale uniformity running time. Qualitative evaluations are questionnaires which contain the opinion of radiotherapy practitioners regarding DRR image quality in terms of contrast, resolution, and grey scale uniformity. Quantitative evaluation shows that there are some similarities of DRR image quality between algorithm used in this thesis study is similar to the algorithm in the TPS. This also supported by the results of a qualitative evaluation.

Abstrak :
ABSTRAK
Pembahasan mengenai karakteristik deformasi dan pembentukan tekstur pada paduan kuningan masih menyisakan banyak perdebatan, khususnya tingkat deformasi kritis yang merupakan titik awal terjadinya perubahan karakteristik deformasi serta proses transisi dari tekstur tembaga menuju tekstur kuningan dan juga tekstur yang terbentuk selama anil. Beberapa penelitian tentang proses pemaduan mikro dengan menambahkan unsur pemadu seperti Bi, Mn dan Al pada paduan kuningan menunjukkan adanya fenomena penghalusan butir dan perubahan sifat mekanik, akan tetapi pembahasan mengenai pengaruh unsur pemadu tersebut terhadap karakteristik deformasi dan proses pembentukan tekstur paduan kuningan masih belum dilakukan. Pada penelitian ini dilakukan proses pemaduan mikro dengan menambahkan unsur Bi, Mn dan Al pada paduan Cu-29Zn. Proses pemaduan mikro dilakukan melalui proses pengecoran dengan metode gravity die casting. Penambahan Bi dilakukan dengan variasi sebesar 0.5 dan 1 berat, sedangkan Mn dan Al ditambahkan dengan kadar sebesar 2, 4 dan 6 berat. Pelat hasil proses pengecoran dilakukan homogenisasi pada temperatur 800 oC selama 2 jam. Selanjutnya sampel hasil proses homogenisasi akan dilakukan proses pengerolan dingin dengan tingkat deformasi sebesar 20, 40 dan 70 . Pada tahap berikutnya, sampel hasil proses pengerolan dingin akan di anil pada temperatur 300, 400, 500 dan 600 oC selama 30 menit. Proses karakterisasi yang dilakukan meliputi pengujian komposisi kimia, pengamatan struktur menggunakan mikroskop optik dan SEM, pengujian kekerasan, pengujian tarik dan juga pengukuran tekstur.Hasil penelitian menunjukkan bahwa pemaduan mikro dengan Bi tidak berpengaruh terhadap nilai kekerasan paduan Cu-29Zn, sedangkan pemaduan dengan Mn dan Al memberikan peningkatan kekerasan yang cukup signifikan. Pemaduan mikro dengan Bi cenderung meningkatkan kepadatan slip, twinning dan shear band, disisi lain pemaduan dengan Mn justru menurunkan kepadatan slip meskipun cenderung menaikkan kepadatan twinning dan juga shear band. Pemaduan mikro dengan Al pada kadar 5.7 berat membuat paduan Cu-29Zn semakin getas dan menurunkan sifat mampu bentuk. Selama proses anil, pemaduan dengan Bi meningkatkan laju rekristalisasi serta menghambat petumbuhan butir. Disisi lain, pemaduan dengan Mn cenderung menurunkan laju rekristalisasi dan juga proses pertumbuhan butir. Selama proses pengerolan dingin, pemaduan Mikro dengan Bi dan Mn cenderung mempercepat proses pembentukan tektur kuningan dan Goss. Disisi lain, selama proses anil, pemaduan mikro dengan Bi dan Mn cenderung menghasilkan tekstur yang lebih kompleks meliputi komponen tembaga, kuningan dan Goss.

---

ABSTRACT
Deformation characteristic and texture development on brass alloy are still under discussion, particularly concerning the critical deformation level of which change of deformation characteristic and transition from copper to brass type texture begins during cold rolling and annealing process. Previous research showed that the addition of alloying elements such as Bi, Mn, and Al on brass alloys resulted in grain refinement and altered mechanical properties of the alloys. However, the effects of those alloying elements on the deformation characteristic and texture development of brass alloys have not been investigated yet. In this research, microalloying process was conducted by adding pure Bi, Mn, and Al to Cu 29Zn alloys. The samples were manufactured by gravity casting. Bi addition was employed with variation of 0.5 and 1 wt. . On the other hand, both Mn and Al were added with variations of 2, 4, and 6 wt. . As cast samples were homogenized at 800 oC for 2 hours in a muffle furnace. The samples were then cold rolled with the level of deformation of 20, 40, and 70 . Subsequently, as rolled samples were annealed at 300, 400, 500, and 600 oC for 30 minutes. Final samples were characterized using chemical composition analysis, optical and scanning electron microscopy for microstructure observation, tensile and hardness testing, and texture measurement. The results showed that the addition of Bi did not affect the hardness of Cu 29Zn alloy. While on the contrary, Mn and Al addition resulted in significant increase on the alloy hardness. The addition of Bi tended to increase the slip, twin, and shear band density. In contrast, the addition of Mn resulted in decreasing slip density in spite of the increasing twin and shear band density of the alloy. Addition of 5.7 wt. Al reduced the formability of Cu 29Zn alloy by escalating its brittleness. During annealing process, Bi addition tended to increase the rate of recrystallization, while addition of Mn and Al showed contrary results. In the cold rolling process, the addition of Bi and Mn accelerated the development of brass and Goss texture components, and resulted in more complicated texture including copper, brass, and Goss components in the annealing process afterwards.

Abstrak :
Telah dikembangkan sistem otomasi pengenalan cacat pada pengelasan metal berbasis ciri tektur sehagai pengekslraksi ciri dan jaringan neural buatan sebagai pengklasifikasinya. Sebuah lilin sinar-X hasil proses radiografi dua buah metal yang disambung dengan teknik pcngelasan menjadi input sistem otomatisasi ini. Film Sinar-X didigitalisasi terlcbih dahulu kemudian diproses dengan menggunakan komputer agar didapalkan informasi jenis cacat dalam pengelasan. Fkslraksi ciri teklur I larralick munjadi basis pengolahan citra film sinar-X agar dapal dikelahui karakter yang dimiliki oleh citra radiograli. Jaringan Neural Buatan Back Propagation digunakan sehagai sistem pengklasifikasi jenis cacat. Hasil akurasi pengenalan terbaik untuk citra yang belum diketahui jenis cacatnya mencapai 82.87 % untuk perbandingan data pelalthan dan data pengujian I : 1.

---

An automation system for welding defect recognition in metal weld has been developed. The recognition method base on texture feature as feature extraction and neural network as classifier. The input of automatic systems is an X-ray film developed from radiographic technique. The films were digitalised before processing the defect information using computer. Tor extracting the feature of"X-ray films image was used Harralick texture. Rack Propagation Neural Network is used to classify the output welding defect automatic systems. The best resull is about 82.87% using training testing paradigm 1:1.

Abstrak :
Interferometric SAR (IFSAR) offers a solution for a country like Indonesia to map areas that are covered by cloud all year long. In using IFSAR data for producing topographic maps, our main requirement is to set the procedures that resemble photogrametric process as close as possible due to the operators, background and the already available sofware and haedware....

Abstrak :
This paper present an automated medicinal plant leaf identification system. The Colour Texture analysis of the leaves is done using the statistical, the Grey Tone Spatial Dependency Matrix (GTSDM) and the Local Binary Pattern (LBP) based features with 20 different color spaces (RGB, XYZ, CMY, YIQ, YUV, YCbCr, YES, U*V*W*, L*a*b*, L*u*v, lms, l𝛼𝛼𝛼𝛼, I1I2I3, HSV, HIS, IHLS, HIS, TSL, LSLM, and KLT). Classification of the medicinal plant is carried out with 70% of the dataset in training set and 30% in the test set. The classification performance is analysed with Stochastic Gradient Descent (SGD), k Nearest Neighbour(kNN), Support Vector Machines based on Radial basis function kernel(SVM-RBF), Linear Discriminant Analysis(LDA) and Quadratic Discriminant Analysis(QDA) classifiers. Results of classification on a dataset of 250 leaf images belonging to five different species of plants show the identification rate of 98.7 %. The results certainly show better identification due to the use of YUV, L*a*b* and HSV colour spaces.

Makalah ini menyajikan sebuah tanaman obat sistem identifikasi daun otomatis. Analisis Warna Tekstur dari daun dilakukan dengan menggunakan statistik, Grey Tone Spatial Dependency Matrix (GTSDM) dan Pola Binary lokal (LBP) fitur berbasis dengan 20 ruang warna yang berbeda (RGB, XYZ, CMY, YIQ, YUV, YCbCr, YES, u * V * W *, L * a * b *, L * u * v, LMS, l𝛼𝛼𝛼𝛼, I1I2I3, HSV, HIS, IHLS, HIS, TSL, LSLM, dan KLT). Klasifikasi tanaman obat dilakukan dengan 70% dari dataset di set pelatihan dan 30% dalam tes set. Kinerja klasifikasi dianalisis dengan Stochastic Gradient Descent (SGD), k Tetangga terdekat (kNN), Dukungan Mesin Vector berdasarkan Radial fungsi dasar kernel (SVM-RBF), Linear Discriminant Analysis (LDA) dan kuadrat Analisis Diskriminan (QDa) pengklasifikasi. Hasil klasifikasi pada dataset dari 250 gambar daun milik lima spesies yang berbeda dari tanaman menunjukkan tingkat identifikasi 98,7%. Hasil tentu menunjukkan identifikasi yang lebih baik karena penggunaan YUV, L * a * b * dan ruang warna HSV.

Abstrak :
In this research, it is designed a simple inspection model for defect detection on woven fabrics at the weaving stage of processing, based on texture analysis. Textural features that extracted by using the NGLDM (Neighboring Greylevel Dependence Matrices) from the several avail-able samples either for normal or defective weaving products, are intelligently recognized by a neural network computational system. The model is useful in textile industry, which provide woven qualities produced by weaving machines, therefore, from the defect's information one can separates those products which have different grades to be processed at the dye finishing stage, and may check previous yarn's treatment, mechanical failures, etc. The inspection system is equipped by a flatbed conveyor, a CCD camera, and a microcomputer IBM-PC/AT 386 with a Computer Eyes image grabber card. The testing results of defect detection on the available samples, indicate more than 80% of recognition level can be achieved. In the future, it is anticipated that the system may be developed, in order to reduce much more human intervention for the defect detection.

Abstrak :
Asam amino esensial yang terkandung pada protein nabati maupun hewani, penting untuk asupan nutrisi manusia. Namun, protein lemak yang ada dihewani dikenal dengan Low Density Lipoprotein LDL dapat menyebabkan penyakit tertentu yang berbahaya. Protein nabati dapat menjadi konsumsi alternatif untuk menurunkan kadar kolesterol LDL tersebut. Teknologi yang berkembang saat ini adalah protein nabati yang direstrukturisasi teksturnya menyerupai tekstur daging hewan. Salah satu sumber protein nabati yang memiliki kualitas gizinya mendekati dengan daging hewan adalah protein kedelai. Penelitian ini bertujuan untuk mengetahui pengaruh enzim transglutaminase TG-ase sebagai agen pengikat silang pada campuran Texturized Soy Protein TSP dan tepung kedelai. Sampel akan di uji melalui tingkat keasaman, gugus fungsi, profil tekstur, organoleptik dan proksimat. Melalui hasil uji tersebut akan diperoleh jumlah dosis transgluminase dan suhu inkubasi yang optimal. Variasi yang digunakan adalah dosis enzim 0,0; 0,5; 1,0; 1,5; 2 dan suhu inkubasi 50C; 150C; 250C dengan durasi 24 jam inkubasi. Hasilnya menunjukkan bahwa karakteristik dari setiap sampel yang diamati, peningkatan dosis enzim transglutaminase mempengaruhi tekstur sampel yang dibuktikan dengan uji profil tekstur dan organoleptik. Sedangkan, reaksi enzimatik dibuktikan dengan uji FTIR dan tingkat keasaman. Pada penelitian ini enzim optimum adalah 1,5 . Namun, hasil dari karakteristik variasi perbedaan suhu pada penelitian ini tidak signifikan. ...... The essential amino acids contain in vegetable and animal protein is important for human nutrition intake. However, the presence of the animal protein in the the animal meat generally exists with a lot of fat and cholesterol type Low Density Lipoprotein LDL that can cause a certain disease. Vegetable protein should be the alternative consumption to decrease the LDL cholesterol content. The current growing technology, the vegetable protein could be restructured to resemble the texture of animal meat. One of the vegetable protein sources that has the same nutritional quality similar to animal meat is soybean protein. This study aims to determine the effect of transglutaminase TG ase enzyme as a crosslinking agent on mixture of Texturized Soy Protein TSP and soybean powder. The sample would be examined by acidity level test, function group, texture profile, organoleptic and proximate analysis. By these tests, it could be obtained the optimum of amount transgluminase dosage and the incubation temperature. The experimenatal variations are the enzyme dosage 0.0 0.5 , 1,0 1.5 2 and the incubation temperature 5oC 15 oC 25oC with the duration of 24 h incubation. The result showed that the characteristic of each sample observed, increased dosage of transglutaminase enzyme affects the texture of sample as evedenced by TPA and organoleptic test. While, enzimatic reaction evidenced by FTIR and acidity level test. In this research the optimum enzyme is 1,5 . However, the characteristic of this variations temperature was insignificant different.