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"This book aims to be a comprehensive and accurate survey of state-of-art research on intuitionistic fuzzy sets theory and could be considered a continuation and extension of the authorś previous book. The research activity of the author within the area of intuitionistic fuzzy sets has been expanding into many directions. The results of the authorś most recent work covering the past 12 years as well as the newest general ideas and open problems in this field have been therefore collected in this new book. "

"Thesis ini menyajikan implementasi prilaku robot yang didasarkan pada fuzzy perception. Prilaku yang berdasarkan input dari sensor yang mengukur jarak suatu rintangan. Rintangan yang mengelilingi robot, dipetakan ke dalam suatu sistem koordinat gambar. Sekumpulan aturan fuzzy digunakan untuk menentukan prilaku robot ketika menemui suatu rintangan. Kumpulan aturan yang berbeda akan meng-hasilakan prilaku yang berbeda pula. Suatu prilaku dari robot dengan mudah dapat dimodikasi, dengan menambahkan, menghilangkan, ataupun mengganti aturan tertentu. Keuntungan dari tur ini dil-ihat di dalam eksperimen pada bagian gerakan kompleks. Pada dua eksperimen pertama, ketika robot bergerak mendekati suatu rintangan berbentuk sudut, robot akan selalu menabrak sudut tersebut. Hal ini terjadi, karena tidak cukupnya aturan fuzzy yang digunakan. Dengan menambahkan satu aturan fuzzy ekstra, permasalahan dengan rintangan yang berbentuk sudut dapat diselesaikan, seperti ditunjukkan pada eksperimen lainnya.Implementasi dari prilaku ini diterapkan pada Scorpion Robot. Robot yang memiliki dua roda, dimana setiap rodanya adalah roda difrensial, sehingga setiap roda dimungkinkan untuk memiliki kecepatan yang berbeda. Robot dilengkapi dengan sensor inframerah. Terdapat 13 sensor yang menghadap ke arah luar, yang digunakan pada implementasi ini. Perangkat lunak yang digunakan pada implementasi iniadalah Behavior Execution Layer (BEL) dari arsitektur Evolution Robotics Software Platform (ERSP) [Evolution, 2004d] dan OpenCV library dari Intel [Bradski, 2008]."

"Federated Cloud Architecture is a heterogeneous and distributed model that providesinfrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task toselect the optimal service cloud provider for the customer and then deploy it. In this paper,a new provider discoveryalgorithm and fuzzy sets ranking model is proposed in the modified federatedarchitecture and thenthe performance isevaluated. The proposeddiscovery method shortlists the provider based on the Quality of Service (QoS)indicators suggested by the Service Measurement Index (SMI) with the Service LevelAgreement (SLA) thatprovides improved performance. In addition to that, the cost is also included thatrepresents thefulfillment at the level of the end user. The ranking mechanism is based on a Fuzzy set approach, having three general phases, such as problem decomposition, judgment ofpriorities and an aggregationof these priorities. With some simple rules, the fuzzy set may be combined with the QoS indicators. The WeightedTuned Queuing Scheduling (WTOS) Algorithm is proposed to resolve the issue of starvation in theexisting architecture and manage the requests effectively. Experimental resultsshow that the proposedarchitecture has abetter successful selection rate, average response time and less overhead,compared to the existing architecture that had supported the Cloud environment."