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"This paper presents a continuing study of the human cognitive aspect application in the technical systems. The laststudies design a human-centered design based on the German culture. The result shows a significant difference ofhuman performance between Germans and Indonesians. Therefore, this study examines the human cognitive modelbased on Indonesian culture to investigate whether the different cognitive model based on the culture aspect canimprove the human performance. The study was conducted on 60 people classified by age, young (16-34 years old) andold (older than 34 years old). Participants render predictions on an assembly activity for two interim states of twodifferent types of products which are the Builderific brick and the Pulley Release based on four types of the assemblystrategy model (Reference, Combination, Human Behavior 1, and Human Behavior 2). The dependent variables areprediction time, mental workload, and predictive accuracy. The results show that the models of human assemblystrategies and the products have significant influences on mental workload and predictive capability. The age variablesignificantly influences mental workload, performance, and prediction capabilities."

"ABSTRAK A significant share of the U.S federal R&D budget is devoted to large-scale, complex technological system commonly referred to as "big science". Over the last two decades, these systems have continued to grow in size, complexity, development time, and cost. At the same time, political changes in the US, particulary the concern over goverment spending and the federal budget deficit, have made it more difficult for proponents to secure and preserve support for these programs over their (increasingly long) lifetimes. Using the U.S space shuttle and space station programs as examples, the article shows that the political requirements for obtaining approval and funding for large and expensive research and development projects create conditions that reduce the likelihood that they will succeed technologically. The problems of technology-based projects like those of the US space program are in fact deeply rooted in the American political process itself. "

"In recent years, the rising competitive environment with shorter product life cycles and high customization forcesindustries to increase their flexibility, speed up their response, and enhance concurrent engineering designs. To integratethese prospects, supply chain collaboration becomes a pertinent strategy for industries to strengthen theircompetitiveness. The network design problem is used to implement supply chain collaboration. In the buying andselling process, sharing information between buyer and supplier are important to obtain a transaction decision. Theoptimimum supply chain profit can be identified by mathematical model of network design problem. The MathematicalModel takes into consideration the uncertainity in negotiation of supply chain, transportation problems, and locationallocationof products from supplier to buyer in the planning based on the time value of money. The results show thatthe model can be used to optimize the supply chain profit. The supplier gets a profit because income were received inthe initial contract, while the buyer profit comes from lower pay."

"Biofilm is an aggregate of consortium bacteria that adhere to each other on a surface. It is usually protected by the exopolysaccharide layer. Various invasive medical procedures, such as catheterization, endotracheal tube installation, and contact lens utilization, are vulnerable to biofilm infection. The National Institute of Health (NIH) estimates 65% of all microbial infections are caused by biofilm. Periplasmic α-amylase (MalS) is an enzyme that hydrolyzes α-1, 4- glicosidic bond in glycogen, starch, and others related polysaccharides in periplasmic space. Another protein called hemolysin-α (HlyA) is a secretion signal protein on C terminal of particular peptide in gram negative bacteria. We proposed a novel recombinant plasmid expressing α-amylase and hemolysin-α fusion in pSB1C3 which is cloned into E.coli to enable α-amylase excretion to extracellular for degrading biofilm polysaccharides content, as in starch agar. Microtiter assay was performed to analyze the reduction percentage of biofilm by adding recombinant E.coli into media. This system is more effective in degrading biofilm from gram positive bacteria i.e.: Bacillus substilis (30.21%) and Staphylococcus aureus (24.20%), and less effective degrading biofilm of gram negative i.e.: Vibrio cholera (5.30%), Pseudomonas aeruginosa (8.50%), Klebsiella pneumonia (6.75%) and E. coli (-0.6%). Gram positive bacteria have a thick layer of peptidoglycan, causing the enzyme to work more effectively in degrading polysaccharides."

"ABSTRAKCellular symptoms present a model system for the analysis of living structures in laboratories such as metabolic studies and drug screening. In living organisms, cells are often encountered with compaction, tension, and shear. Most cells are intangible and balanced when a solid or seminal stratification (monolayer culture) is connected. In distortion reaction, cells experience intense biochemical changes. The stressed cells on the culture combine in the Vivo environment, which creates dramatic shape changes and biochemical reactions. These microsystems can meet broad applications in the biomedical research field since deformation, compression or fluid flow have been found to induce biochemical changes in cells derived from various tissues. The aim of this project is to design and to develop a microfluidic device which will allow for the culturing of adhered cells in microfluidic chambers (micro-wells) while controlling, at the micro scale, the mechanical deformation applied on the substrate on which cells are attached. During this work, a Polydimethylsiloxane (PDMS) double layered microfluidic device was designed and fabricated which enables controlled micro-sized deformation of the cell culturing microwells. Moreover, a relation was found between measured deformation values and simulations."

"Pengembangan NLP di Indonesia terbilang lambat, terutama penelitian terkait bahasa daerah Indonesia. Alasannya adalah sumber data bahasa daerah tidak terdokumentasikan dengan baik sehingga sumber daya NLP yang ditemukan juga sedikit. Penelitian ini membahas metode ekstraksi kamus-kamus bahasa daerah di Indonesia untuk menghasilkan suatu sumber daya NLP yang dapat dibaca oleh mesin. Tahap penelitian dimulai dari pengumpulan data kamus, perancangan dan eksperimen metode ekstraksi, serta evaluasi hasil ekstraksi. Hasil penelitian berupa korpus paralel, leksikon bilingual, dan pasangan kata dasar-kata berimbuhan dalam format CSV dari beberapa kamus dwibahasa di Indonesia. Beberapa bahasa di antaranya adalah bahasa Minangkabau, Sunda, Mooi, Jambi, Bugis, Bali, dan Aceh. Perancangan metode ekstraksi berfokus pada kamus Minangkabau yang kemudian dilakukan eksperimen pada kamus-kamus bahasa daerah lainnya. Evaluasi dilakukan terhadap hasil ekstraksi kamus Minangkabau dengan melakukan anotasi data. Perhitungan akurasi dilakukan terhadap penempatan kelompok kata dari hasil anotasi. Hasil perhitungan menunjukkan 99% hasil ekstraksi sudah tepat untuk penentuan kelompok kata pada leksikon bilingual dan 88% untuk korpus paralel. Tim peneliti menemukan bahwa struktur dalam kamus bahasa daerah Indonesia sangat beragam, sehingga menuntut perlakuan yang berbeda pada setiap kamus, seperti perihal penomoran halaman. Selain itu, tim peneliti menemukan banyak kamus bahasa daerah Indonesia dengan kualitas yang kurang baik. Kualitas yang kurang baik ditunjukan dengan banyaknya kesalahan baca akibat noise yang terdapat pada tampilan berkas kamus.

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The development of NLP in Indonesia is relatively slow, especially for Indonesian local languages. Indonesian local language data sources are not well-documented so that there are only few NLP resources found. This study discusses the extraction method of Indonesian local language dictionaries to produce a machine-readable NLP resource. Starting from collecting dictionary data, designing and experimentation of the extraction method, and evaluating the extraction results. The extraction results are parallel corpus, bilingual lexicon, and words’ morphological form in CSV format from several Indonesian Local Language bilingual dictionaries that are Baso Minangkabau, Sundanese, Moi, Jambinese, Buginese, Balinese, and Acehnese. The designed method is also applied to some other local language dictionaries. Data annotation has been done to evaluate the extraction results so that we can calculate its accuracy of word classification for parallel corpus and bilingual lexicon. Extraction method design focuses on the Minangkabau dictionary which is then applied to other dictionaries. Data annotation has been done to evaluate the extraction results.The evaluation results show that 99% of the extraction results are correct for word classifying in the bilingual lexicon and 88% correct for parallel corpus. We found that the structure of dictionaries varies, so it requires different approaches for each dictionary, for example regarding page numbering. We also found many dictionaries with poor quality. The poor quality is indicated by the number of reading errors due to noise contained in the original dictionary file."

"Pengembangan NLP di Indonesia terbilang lambat, terutama penelitian terkait bahasa daerah Indonesia. Alasannya adalah sumber data bahasa daerah tidak terdokumentasikan dengan baik sehingga sumber daya NLP yang ditemukan juga sedikit. Penelitian ini membahas metode ekstraksi kamus-kamus bahasa daerah di Indonesia untuk menghasilkan suatu sumber daya NLP yang dapat dibaca oleh mesin. Tahap penelitian dimulai dari pengumpulan data kamus, perancangan dan eksperimen metode ekstraksi, serta evaluasi hasil ekstraksi. Hasil penelitian berupa korpus paralel, leksikon bilingual, dan pasangan kata dasar-kata berimbuhan dalam format CSV dari beberapa kamus dwibahasa di Indonesia. Beberapa bahasa di antaranya adalah bahasa Minangkabau, Sunda, Mooi, Jambi, Bugis, Bali, dan Aceh. Perancangan metode ekstraksi berfokus pada kamus Minangkabau yang kemudian dilakukan eksperimen pada kamus-kamus bahasa daerah lainnya. Evaluasi dilakukan terhadap hasil ekstraksi kamus Minangkabau dengan melakukan anotasi data. Perhitungan akurasi dilakukan terhadap penempatan kelompok kata dari hasil anotasi. Hasil perhitungan menunjukkan 99% hasil ekstraksi sudah tepat untuk penentuan kelompok kata pada leksikon bilingual dan 88% untuk korpus paralel. Tim peneliti menemukan bahwa struktur dalam kamus bahasa daerah Indonesia sangat beragam, sehingga menuntut perlakuan yang berbeda pada setiap kamus, seperti perihal penomoran halaman. Selain itu, tim peneliti menemukan banyak kamus bahasa daerah Indonesia dengan kualitas yang kurang baik. Kualitas yang kurang baik ditunjukan dengan banyaknya kesalahan baca akibat noise yang terdapat pada tampilan berkas kamus.

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The development of NLP in Indonesia is relatively slow, especially for Indonesian local languages. Indonesian local language data sources are not well-documented so that there are only few NLP resources found. This study discusses the extraction method of Indonesian local language dictionaries to produce a machine-readable NLP resource. Starting from collecting dictionary data, designing and experimentation of the extraction method, and evaluating the extraction results. The extraction results are parallel corpus, bilingual lexicon, and words’ morphological form in CSV format from several Indonesian Local Language bilingual dictionaries that are Baso Minangkabau, Sundanese, Moi, Jambinese, Buginese, Balinese, and Acehnese. The designed method is also applied to some other local language dictionaries. Data annotation has been done to evaluate the extraction results so that we can calculate its accuracy of word classification for parallel corpus and bilingual lexicon. Extraction method design focuses on the Minangkabau dictionary which is then applied to other dictionaries. Data annotation has been done to evaluate the extraction results.The evaluation results show that 99% of the extraction results are correct for word classifying in the bilingual lexicon and 88% correct for parallel corpus. We found that the structure of dictionaries varies, so it requires different approaches for each dictionary, for example regarding page numbering. We also found many dictionaries with poor quality. The poor quality is indicated by the number of reading errors due to noise contained in the original dictionary file."

"This book presents state-of-the-art probabilistic methods for the reliability analysis and design of engineering products and processes. It seeks to facilitate practical application of probabilistic analysis and design by providing an authoritative, in-depth, and practical description of what probabilistic analysis and design is and how it can be implemented. The text is packed with many practical engineering examples (e.g., electric power transmission systems, aircraft power generating systems, and mechanical transmission systems) and exercise problems. It is an up-to-date, fully illustrated reference suitable for both undergraduate and graduate engineering students, researchers, and professional engineers who are interested in exploring the fundamentals, implementation, and applications of probabilistic analysis and design methods."