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"Artikel ini akan mencoba membahas pemecahan masalah penjadwal kuliah dengan pendekatan ilmu Intelegensia Semu (Artificial Intelligence), yakni dengan menggunakan Constrain Satisfaction Problem. Penulis telah merancang dan menguji sebuah teknik baru pencarian solusi dengan intelligent search yang dikombinasikan dengan algoritma Smart Backtracking.Algoritma yang kami kembangkan ini telah dicoba dengan sejumlah studi kasus berskala kecil (7 dosen 7 matakuliah 23 kelas 2 ruang 35 jam perkulaiahan tiap minggu dan lebih dari 1380 mahasiswa) dan menghasilkan output yang diinginkan dalam waktu yang sangat singkat.Percobaan dengan real data (1198 dosen, 1457 matakuliah, 2311 kelas, 122 ruang, 40 jam perkuliahan tiap minggu dan lebih dari 20000 mahasiswa) telah menghasilkan solusi yang baik meskipun tidak dapat mencapai solusi 100% lengkap. Sejumlah constraint terutama yang berkaitan dengan dosesn dan mahasiswa kelas paket seringkali sulit dipenuhi karena adanya sejumlah kelas yang merupakan gabungan beberapa paker (dapat mencapai 12)"

"Proyek ini bertujuan untuk menentukan peringkat tahan api dari dinding baja ringan di bawah kondisi api menggunakan aplikasi kecerdasan buatan. Dua bagian bagian saluran yang diberi lipatan (LCS) dan bagian saluran berongga flange (HFC) grade 500 dan kelas 250 disajikan dalam penelitian ini. LCS adalah jenis konvensional yang digunakan dalam bingkai baja ringan, sementara HFC memperkenalkan memiliki kinerja api yang unggul. Baru-baru ini pemodelan elemen hingga dan uji skala penuh telah digunakan untuk menentukan kinerja api dinding LSF. Meskipun demikian, pemodelan elemen hingga ditemukan memiliki prosedur yang rumit, dan uji skala penuh adalah eksperimen yang memakan waktu. Oleh karena itu, opsi alternatif sebagai pembelajaran mesin diperlukan untuk mengatasi situasi ini. Pendekatan jaringan saraf pembelajaran mesin akan diadopsi untuk melatih data. Masukan akan menjadi data aktual dari FEA dan proyek uji penuh skala sebelumnya. Temperatur dan suhu flensa dan flensa dingin seksi dari suatu bagian diperoleh sebagai input. Kapasitas pengurangan rasio bertindak sebagai output yang akan diprediksi dalam pembelajaran yang diawasi. Pelatihan dan uji coba dilakukan melalui jaringan saraf tiruan dengan menggabungkan parameter yang berbeda seperti fungsi kehilangan, menjaga faktor probabilitas, tingkat pembelajaran, jumlah lapisan, dan neuron. Rasio pengurangan kapasitas yang diperoleh dari pelatihan mesin dapat diplot dan dibandingkan keakuratannya dengan hasil FEA sebelumnya.

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This project aims to determine fire resistance rating of Light Gauge Steel Frame (LSF) walls under fire condition using artificial intelligence application. Two section of lipped channel section (LCS) and hollow flange channel section (HFC) grade 500 and grade 250 is presented in this research. LCS is a conventional section used in LSF framing, while HFC introduced having superior fire performance. Recently finite element modelling and a full-scale test have been employed to determine fire performance of LSF walls. Nonetheless, finite element modelling was found to have a complicated procedure, and the full-scale test was a time-consuming experiment. Therefore, an alternative option as machine learning is necessary to overcome this situation. A neural network approach of machine learning will be adopted to train the data. The input would be the actual data from FEA and full-scale test previous project. Hot flange and cold flange temperature and dimension of a section are obtained as the input. Capacity reduction ratio act as an output that will be predicted in supervised learning. Training and testing trialare done through the artificial neural network by combining different parameters such as loss function, keep probability factor, learning rate, the number of layers, and neurons. Capacity reduction ratio attained from machine training can be plotted and compared its accuracy with previous FEA results."

"Constitutes the refereed post-conference proceedings of the 7th International Conference on Intelligent Computing, ICIC 2011, held in Zhengzhou, China, in August 2011. This title features papers that are organized in topical sections on intelligent computing in scheduling; local feature descriptors for image processing and recognition; and, more"

"This book discusses the principle of automotive intelligent technology from the point of view of modern sensing and intelligent control. Based on the latest research in the field, it explores safe driving with intelligent vision; intelligent monitoring of dangerous driving; intelligent detection of automobile power and transmission systems; intelligent vehicle navigation and transportation systems; and vehicle-assisted intelligent technology. It draws on the author’s research in the field of automotive intelligent technology to explain the fundamentals of vehicle intelligent technology, from the information sensing principle to mathematical models and the algorithm basis, enabling readers to grasp the concepts of automotive intelligent technology. Opening up new scientific horizons and fostering innovative thinking, the book is a valuable resource for researchers as well as undergraduate and graduate students."

"Skripsi ini membahas tentang peran dan identitas ilustrator di tengah maraknya penggunaan AI Art. Keberadaan AI Art yang mampu menciptakan ilustrasi secara otomatis telah menimbulkan pertanyaan kritis apakah kehadiran kecerdasan buatan ini akan menggantikan peran tradisional ilustrator di masa depan. Metode penelitian yang digunakan dalam skripsi ini adalah wawancara mendalam dengan tiga subjek yang merupakan ilustrator berpengalaman, serta dilakukan observasi terhadap aktivitas mereka di media sosial. Hasil penelitian ini menunjukkan bahwa pemahaman dan pandangan beragam para ilustrator tentang potensi mereka akan digantikan oleh AI. Ilustrator meyakini memiliki kelebihan tersendiri dibandingkan dengan AI yang mendasari tindakan mereka dalam membuat ilustrasi yang berbeda dengan hasil ilustrasi buatan AI.

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This paper discusses the role and identity of the illustrator in the midst of the widespread use of AI Art. The existence of AI Art which is able to create illustrations automatically has raised a critical question whether the presence of artificial intelligence will replace the traditional role of the illustrator in the future. The research method used for this paper is in-depth interviews with three subjects who are experienced illustrators, as well as observing their activities on social media. The results of this study show that illustrators has diverse understanding and views of their potential will be replaced by AI. Illustrators believe they have their own advantages compared to AI which underlies their actions in making illustrations that are different from the illustrations made by AI."

"This book introduces a new generation of metrological systems and their application in a digital quality concept. It discusses the development of an optimal collision-free measuring path based on CAD geometry and tolerances defined in knowledge base and AI techniques such as engineering ontology, ACO and GA. This new approach, combining both geometric and metrological features, allows the following benefits: reduction of a preparation time based on the automatic generation of a measuring protocol; developed mathematical model for the distribution of measuring points and collision avoidance; the optimization of a measuring probe path; the analysis of a part placement based on the accessibility analysis and automatic configuration of measuring probes. The application of this new system is particularly useful in the inspection of complex prismatic parts with a large number of tolerances, in all of type production. The implementation is demonstrated using several case studies relating to high-tech industries and advanced, non-conventional processes."

"In the concluding chapters of this book the author introduces GIM, the Global Intelligent Machine. GIM is a huge global hybrid machine, a combination of production machinery, information machinery and mechanized networks. In the future it may very well encompass all machinery on the globe.The author discusses the development of machines from the Stone Age until the present and pays particular attention to the rise of the science of machines and the development of the relationship between science and technology.The first production and information tools were invented in the Stone Age. In the Agricultural empires tools and machinery became more complex. During and after the Industrial Revolution the pace of innovation accelerated. In the 20th century the mechanization of production, information processing and networks became increasingly sophisticated. GIM is the culmination of this development.GIM is no science fiction. GIM exists and is growing and getting smarter and smarter. Individuals and institutions are trying to control parts of this giant global robot. By looking at its history and by putting GIM in the context of the current developments, this book seeks to reach a fuller understanding of this phenomenon."