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"The topics addressed in this proceedings volume include active brazing (an area of increasing R&D interest); conventional brazing an soldering alloys; wetting and fundamental properties studies; modeling and mechanical analysis and/or characterization; and process technology. All of the papers in this volume have been editorially reviewed. Both the hardcopy and CD contain an author s index for easy reference, and the CD volume is fully searchable by keyword."

"The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The conference was sponsored by the Center for Applied Scientific Computing at the Lawrence Livermore National Laboratory and the American Statistical Association, continuing a trend towards greater collaboration between the two communities."

"Dilakukan studi literatur mengenai uji tak rusak menggunakan emisi positron.Studi literatur yang di lakukan melalui sumber radiasi pemancar posireon,proses interaksi positron dengan materi ,teknik pengujian,sistem spektroskopi dan jenis material serta cacat yang dapat diuji.Hasil studi literatur disusun dalam suatu makalah."

"This volume presents the Proceedings of the Sixth International Conference on Green and Human Information Technology (ICGHIT), held in Chiang Mai, Thailand, Jan 31-Feb 2, 2018.ICGHIT is the unique global conference for researchers, industry professionals, and academics interested in the latest development of green and human information technology. Its broad scope ranges from electronics to communications, computers, multimedia and signal processing, control and intelligent systems, IC and convergence technologies, which are related to green and human issues such as energy saving and human welfare. Specially in this volume, ICGHIT covers state-of-the-art technologies for the 4th industrial revolution, for example, cyber security, big data and cloud service, smart medical system, machine learning and its applications."

"Pengecekan akurasi kualitas citra dalam program kontrol kualitas quality control, QC dapat ditingkatkan dengan penggunaan fantom yang mendekati kondisi realistis pada pemindaian klinis. Penelitian ini ditujukan untuk mengembangkan fantom desain khusus yang terdiri dari material organik ekuivalen-hati dan otot jaringan lunak . Karakterisasi sifat radiologi material ekuivalen jaringan menunjukan bahwa material ekuivalen jaringan lunak otot yang tersusun atas campuran Gondorukem, Malam Cecek, dan tepung beras dengan rasio massa 70/20/10 memiliki CT Number -20.27 0.33 HU, densitas massa 1.055 g/cm3 dan densitas elektron 3.461 1023 e/m3. Material ekuivalen jaringan hati yang tersusun atas campuran Malam Cecek dan tepung beras dengan rasio massa 60/40 memiliki CT Number 74.17 1.48 HU, densitas massa 1.024 g/cm3 dan densitas elektron 3.396 1023 e/m3. Penggunaan fantom desain khusus dalam mengevaluasi kualitas citra PET berdasarkan parameter full-width-half-maximum FWHM resolusi dan signal-to-noise ratio SNR menunjukan bahwa detektabilitas sistem pemindaian PET bergantung terhadap ukuran pixel dan metode rekonstruksi citra yang digunakan. Sistem pencitraan PET/CT Siemens Biograph dengan rekonstruksi True-X dan filter Butterworth menggunakan ukuran pixel 1 x 1 mm2, memberikan ukuran obyek pada citra PET lebih kecil daripada ukuran obyek sebenarnya, kecuali pada obyek 4.02 mm. Sistem pemindaian PET/CT Philips Gemini TOF 16 dengan ukuran pixel 4 x 4 mm2 menunjukan adanya perbesaran ukuran obyek kecil dengan diameter kurang dari 16 mm. Kedua pesawat PET/CT menunjukan bahwa ukuran obyek pada citra cenderung lebih kecil atau mencapai threshold 80 dari ukuran sebenarnya pada obyek berdiameter lebih besar sama dengan 16.30 mm. Sebaliknya, overestimation nilai FWHM terjadi pada obyek berukuran kecil 4.20 mm sebagai akibat dari terjadinya partial volume effect. Studi pengukuran kualitas citra dengan fantom desain khusus ini menunjukan bahwa pemilihan metode rekonstruksi, filter post processing, dan ukuran pixel mempengaruhi resolusi atau detektabilitas dan SNR pada citra PET. Pada akhirnya, fantom desain khusus ini mampu memberikan analisa kualitas.

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The purpose of this research was to develop a phantom for quality control QC of PET CT image quality. The phantom was constructed by tissue equivalent materials which consist six cylindrical hot lesions with diameter of 4.20, 6.20, 8.30, 9,80, 16.30, and 19.00 mm. Wax and rice starch were combined to produce the tissue equivalent materials. The results showed that combination 70 20 10 of gondorukem cecek wax rice starch and 60 40 of cecek wax rice starch yielded liver and muscle surrogate materials respectively. Liver equivalent material LEM was 74.17 1.48 HU, 1.024 g cm3 of mass density, and 3.396 1023 e m3 of electron density. While, muscle equivalent material MEM was 20.27 0.33 HU, 1.055 g cm3 of mass density and 3.461 1023 e m3 of electron density.

Then, the phantom was scanned using two different PET CT scanner to determine the detectability and signal to noise ratio SNR as measure PET CT imaging performance. It showed that the detectability of PET CT scanner was affected by pixel size and reconstruction method for image acquisitions. For Siemens Biograph PET CT scanned using pixel sixe of 1 1 mm2, FWHMs were smaller than the actual size of the hot lesions. Meanwhile, for Philips Gemini PET CT scanned using pixel sixe of 4 4 mm2, FWHMs were larger than the actual size of the hot lesions.

For both PET CT scanner, ratio of FWHM actual size reached the threshold of 80 at object diameter ge 16.30 mm. In contrast, overestimation of FWHM occurred at smaller object diameter 4.20 mm significantly caused by the partial volume effect. The study also indicated that image reconstructions, post processing smoothing filter, and pixel size may give impact to the detectability and SNR performed by a PET CT system. It was concluded that the phantom could be used to analyze the image quality performance in PET CT imaging."

"ABSTRAKPositron Emission Tomography (PET) telah dikenal sebagai modalitas molecular imaging yang sering memberikan informasi yang mendahului hasil pencitraan anatomi dari modalitas lain seperti Computed Tomography (CT) dan Magnetic Resonance (MR). Keunggulan PET untuk mendeteksi uptake yang sangat sedikit dari FDG dapat memberikan informasi abnormalitas pada organ, salah satunya pada otak. Pencitraan modalitas PET digunakan untuk mendiagnosis apabila terdapat abnormalitas dalam organ serta untuk memantau keberhasilan perlakuan radioterapi. Pada pencitraan otak menggunakan 2-Deoxy-2-[18F] fluoroglucose (FDG) uptake yang kecil tidak mudah dikenali secara visual, sehingga perlu menggunakan metode yang dapat membantu untuk mendeteksi. Dengan adanya teknik Computer-Aided Diagnosis (CAD) berupa segmentasi dan klasifikasi menggunakan citra PET diharapkan memberikan informasi abnormalitas dengan ukuran kecil yang tidak tampak secara visual. Pada penelitian ini, dikembangkan CAD menggunakan citra otak dengan modalitas PET untuk mendeteksi abnormalitas otak dengan metode klasifikasi menggunakan ekstraksi fitur berupa Gray Level Co-Occurrance Matrix (GLCM), intensity histogram, dan Gray Level Run Length Matrix (GLRLM) sebagai dataset dari klasifikasi teknik Artificial Neural Network (ANN). Hasil klasifikasi yang dievaluasi menggunakan Receiver Operating Characteristic (ROC) dengan hasil error pelatihan terkecil 1.92 ± 0.70 % dan error pengujian terkecil 12.30 ± 3.47%. Hasilnya menunjukkan bahwa sistem CAD yang dikembangkan dapat mengenali citra otak normal dan abnormal.

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ABSTRACTPositron Emission Tomography (PET) is well known as a molecular imaging modality that provides functional organ information. This information supports the results of anatomical imaging from other modalities such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This superiority is due to the ability of PET to detect of small amount uptake from 2-Deoxy-2-[18F] fluoroglucose (FDG) which provide for information about abnormalities of organs, especially in the brain. Therefore, PET imaging is powerful to diagnose the presence of abnormalities, staging cancer, and evaluating radiotherapy treatment results. In brain PET imaging sometimes, small uptake is not easily visual recognized, hence an additional supporting method for its detection is needed. In this study, Computer-Aided Diagnosis (CAD) of brain abnormalities from PET images using classification methods based on a feature in the form of Gray Level Co-Occurrence Matrix (GLCM), intensity histogram, dan Gray Level Run Length Matrix (GLRLM) as a dataset of Artificial Neural Network (ANN). The result based on Receiver Operating Characteristic (ROC) illustrated that the training error was 1.92 ± 0.70 % and the test error was 12.30 ± 3.47%. These results mean that this developed CAD system can recognize normal and abnormal brain images."

"This book constitutes the refereed proceedings of the ACM/IFIP/USENIX 13th International Middleware Conference, held in Montreal, Canada, in December 2012. The 24 revised full papers presented were carefully reviewed and selected from 125 submissions. The papers are organized in topical sections on mobile middleware, tracing and diagnosis, architecture and performance; publish/subscribe middleware, and big-data and cloud computing, availability, security and privacy."

"This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Unconventional Computation, UC 2012, held in Orléans, France, during September 3-7, 2012. The 28 revised full papers presented were carefully selected from numerous submissions. Conference papers are organized in 4 technical sessions, covering topics of hypercomputation, chaos and dynamical systems based computing, granular, fuzzy and rough computing, mechanical computing, cellular, evolutionary, molecular, neural, and quantum computing, membrane computing, amorphous computing, swarm intelligence; artificial immune systems, physics of computation, chemical computation, evolving hardware, the computational nature of self-assembly, developmental processes, bacterial communication, and brain processes."