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"The book provides answers by developing a general principle, homeokinesis, the dynamical symbiosis between brain, body, and environment. That is shown to drive robots to self- determined, individual development in a playful and obviously embodiment- related way, a dog-like robot starts playing with a barrier, eventually jumping or climbing over it, a snakebot develops coiling and jumping modes, humanoids develop climbing behaviors when fallen into a pit, or engage in wrestling-like scenarios when encountering an opponent. The book also develops guided self-organization, a new method that helps to make the playful machines fit for fulfilling tasks in the real world.The book provides two levels of presentation. Students and scientific researchers interested in the field of robotics, self-organization and dynamical systems theory may be satisfied by the in-depth mathematical analysis of the principle, the bootstrapping scenarios, and the emerging behaviors. But the book additionally comes with a robotics simulator inviting also the non- scientific reader to simply enjoy the fabulous world of playful machines by performing the numerous experiments."

"The theme of this book is to examine the feasibility of creating such robots within the limitations of current mechanical engineering. The topics comprise the following aspects of such a pursuit : the philosophy of design of self-organizing mechanical systems, self-organization in biological systems, the history of self-organizing mechanical systems, a case study of a self-assembling/self-repairing system as an autonomous distributed system, a self-organizing robot that can create its own shape and robotic motion, implementation and instrumentation of self-organizing robots, and the future of self-organizing robots. All topics are illustrated with many up-to-date examples."

"This book constitutes the refereed proceedings of the 6th IFIP TC 6 International Workshop on Self-Organizing Systems, IWSOS 2012, held in Delft, The Netherlands, in March 2012. The 5 revised full papers and 5 short papers presented together with 2 invited papers were carefully selected from 25 full paper and 8 short paper submissions. The papers address the following key topics, design and analysis of self-organizing and self-managing systems, inspiring models of self-organization in nature and society, structure, characteristics and dynamics of self-organizing networks, techniques and tools for modeling self-organizing systems, robustness and adaptation in self-organizing systems, self-organization in complex networks like peer-to-peer, sensor, ad-hoc, vehicular and social networks, control of self-organizing systems, decentralized power management in the smart grid, self-organizing group and pattern formation, self-organizing mechanisms for task allocation, coordination and resource allocation, self-organizing information dissemination and content search, and risks and limits of self-organization."

"[Autonomous robots must carry out useful tasks all by themselves relying entirely on their own perceptions of their environment. The cognitive abilities required for autonomous action are largely independent of robot size, which makes mini robots attractive as artefacts for research, education and entertainment. Autonomous mini robots must be small enough for experimentation on a desktop or a small laboratory. They must be easy to carry and safe for interaction with humans. They must not be expensive. Mini robot designers have to work at the leading edge of technology so that their creations can carry out purposeful autonomic action under these constraints. Since 2001 researchers have met every two years for an international symposium to report on the advances achieved in Autonomous Mini Robots for Research and Edutainment (AMiRE). The AMiRE Symposium is a single track conference that offers ample opportunities for discussion and exchange of ideas. This volume contains the contributed papers of the 2011 AMiRE Symposium held from 23 to 25 May 2011 at Bielefeld University, Germany. The contributions in this volume represent the state-of-the-art of autonomous mini robots; they demonstrate what is currently technically feasible and show some of the applications for autonomous mini robots. , Autonomous robots must carry out useful tasks all by themselves relying entirely on their own perceptions of their environment. The cognitive abilities required for autonomous action are largely independent of robot size, which makes mini robots attractive as artefacts for research, education and entertainment. Autonomous mini robots must be small enough for experimentation on a desktop or a small laboratory. They must be easy to carry and safe for interaction with humans. They must not be expensive. Mini robot designers have to work at the leading edge of technology so that their creations can carry out purposeful autonomic action under these constraints. Since 2001 researchers have met every two years for an international symposium to report on the advances achieved in Autonomous Mini Robots for Research and Edutainment (AMiRE). The AMiRE Symposium is a single track conference that offers ample opportunities for discussion and exchange of ideas. This volume contains the contributed papers of the 2011 AMiRE Symposium held from 23 to 25 May 2011 at Bielefeld University, Germany. The contributions in this volume represent the state-of-the-art of autonomous mini robots; they demonstrate what is currently technically feasible and show some of the applications for autonomous mini robots. ]"

"People have dreamed of machines, which would free them from unpleasant, dull, dirty and dangerous tasks and work for them as servants, for centuries if not millennia. Service robots seem to finally let these dreams come true. But where are all these robots that eventually serve us all day long, day for day? A few service robots have entered the market: domestic and professional cleaning robots, lawnmowers, milking robots, or entertainment robots. Some of these robots look more like toys or gadgets rather than real robots. But where is the rest? This is a question, which is asked not only by customers, but also by service providers, care organizations, politicians, and funding agencies. The answer is not very satisfying. Today’s service robots have their problems operating in everyday environments. This is by far more challenging than operating an industrial robot behind a fence. There is a comprehensive list of technical and scientific problems, which still need to be solved. To advance the state of the art in service robotics towards robots, which are capable of operating in an everyday environment, was the major objective of the DESIRE project (Deutsche Service Robotik Initiative – Germany Service Robotics Initiative) funded by the German Ministry of Education and Research (BMBF) under grant no. 01IME01A. This book offers a sample of the results achieved in DESIRE."

"This book represents the fourth part of a larger work dedicated to the structural synthesis of parallel robots. This book offers other topologies of parallel robotic manipulators with two and three degrees of freedom systematically generated by using the structural synthesis approach proposed in Part 1."

"Sejak adanya penemuan tentang struktur DNA yang berupa double helix, terdapat perkembangan tentang interaksi kompleks yang dibutuhkan untuk clustering (mengelompokkan) DNA menjadi clusters (kelompok-kelompok) yang memiliki kesamaan sifat ataupun fungsinya. Clustering DNA dapat dilakukan dengan metode partisi maupun metode hirarki. Dua metode tersebut dapat dipadukan dengan melakukan tahap partisi dan hirarki secara bergantian yang dikenal dengan nama HOPACH clustering. Tahap partisi dapat dilakukan dengan algoritma SOM, PAM, dan K-Means. Algoritma SOM dipilih karena menggunakan metode unsupervised learning dan efisien untuk digunakan pada data yang besar. Proses partisi dilanjutkan dengan proses ordering kemudian dilakukan collapsing dengan proses agglomerative, sehingga hasil clustering yang diperoleh menjadi lebih akurat. Penentuan cluster utama dilakukan dengan menghitung nilai kehomogenan hasil clustering menggunakan MSS (Mean Split Silhoutte). Kriteria penentuan cluster utama adalah pilih nilai MSS yang terkecil. Barisan 136 DNA EVD (Ebola Virus Disease) diperoleh dari Genbank NCBI dengan proses melakukan ekstraksi ciri DNA, selanjutnya melakukan normalisasi, dan dilanjutkan dengan menghitung jarak genetik menggunakan Jarak Euclidean. Matriks jarak genetik dapat dijadikan dasar untuk melakukan partisi serta clustering dengan menggunakan algoritma partisi SOM dalam metode HOPACH clustering. Proses ekstraksi ciri, normalisasi, dan penerapan algoritma partisi SOM dalam metode HOPACH clustering menggunakan bantuan program open source . Pada hasil clustering penerapan algoritma partisi SOM dalam metode HOPACH clustering diperoleh 9 cluster dengan nilai MSS sebesar 0,50280. Cluster yang dihasilkan dapat diidentifikasikan berdasarkan spesies dan tahun pertama kali mewabah.

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Since the discovery of DNA structure in form of double helix, there is a development about the complex interaction required, DNA clustering into clusters which have the same features or functions. DNA clustering can be done by applying partitional or hierarchical method. Those two methods can be combined by doing partitional and hierarchical stage alternately known as HOPACH clustering. The partitional stage can be done by using SOM Algorithm, PAM, and K-Means. SOM algorithm is chosen because it uses unsupervised learning method and efficient to be used for large data. The partitional process is continued by ordering process and then performed collapsing with agglomerative process, so that the clustering result which is obtained will be more accurate. The determination of the main cluster done by calculating homogeneous value of the clustering result uses MSS (Mean Split Silhouette).

The determination criteria of the main cluster is choosing the smallest MSS value. 136 sequences of DNA EVD (Ebola Virus Disease) are obtained from NCBI Genbank by applying extraction of DNA sequence, after that doing normalization, and then calculating the genetic distance use Euclidean Distance. Genetic distance matrix can be used as a basis to do partitional and clustering by implementation SOM partitioning algorithm in HOPACH clustering method. The extraction of DNA sequence, normalization, and the implementation of SOM partitioning algorithm in HOPACH clustering method use open source program . On the result of implementation SOM partitioning algorithm in HOPACH clustering method retrieved 9 clusters with MSS value of 0,50280. The cluster which is obtained can be identified according to species and the first year of becoming an epidemic."

"Pengelompokan nasabah asuransi berdasarkan Self-Organizing Map (SOM) dan analisis cluster hierarki I Gde Angga Surjana (0399010211) Self-Organizing Map (SOM) merupakan metode pengelompokan yang dapat digunakan untuk memvisualisasikan sekaligus mengeksplorasi karakteristik data. Kombinasi antara SOM dan analisis cluster hierarki dapat menjadi metode pengelompokan yang efektif apabila digunakan pada data yang berukuran relatif besar, seperti pada data nasabah dari suatu perusahaan asuransi. Kedua metode ini digunakan untuk membentuk kelompok nasabah berdasarkan produk asuransi yang diikuti agar perusahaan dapat mengidentifikasi kebutuhan para nasabahnya akan asuransi. Hasil pengelompokan dari kedua metode ini adalah tiga kelompok utama, yaitu kelompok nasabah yang sadar asuransi, kelompok nasabah asuransi jiwa dan kelompok nasabah satu jenis asuransi tertentu. "

"Salah satu misi pembangunan adalah mewujudkan kualitas hidup manusia Indonesia yang tinggi, maju, dan sejahtera, dengan salah satu agenda prioritasnya meningkatkan kualitas hidup manusia Indonesia. Untuk mengevaluasi terlaksananya misi dan agenda prioritas tersebut diperlukan indikator yang terukur. Hasil evaluasi tersebut dapat dijadikan pertimbangan dalam membuat kebijakan untuk memperbaiki tingkat kesejahteraan.Salah satu pengukuran yang dapat digunakan adalah Indikator Kesejahteraan Rakyat (Inkesra) yang disusun Badan Pusat Statistik (BPS) yang diolah dari data Survei Sosial Ekonomi Nasional (SUSENAS). Indikator ini mengukur kesejahteraan dengan menggunakan pendekatan kebutuhan dasar (basic needs).Untuk mengukur perubahan tingkat kesejahteraan kabupaten/kota, perlu dilakukan analisis perpindahan cluster dari periode ke periode. Salah satu metode yang dapat digunakan untuk melakukan clustering adalah Self-organizing Maps (SOM). Hasil clustering dengan SOM kemudian dapat dianalisis menggunakan Relative Density Self-Organizing Maps (ReDSOM).Variabel yang digunakan pada penelitian ini sebanyak 22 variabel dengan jumlah record 497 kabupaten/kota. Data yang dibandingkan adalah data tahun 2011 dan 2014. Dari hasil penelitian ini terdapat enam cluster pada tahun 2011 dan tujuh cluster pada tahun 2014. Variabel yang berubah secara signifikan pada sebagian besar perpindahan cluster adalah Angka Partisipasi Sekolah.

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One of the development goal is to improve Indonesian people’s quality of life including welfare. A measurable indicator is needed to evaluate the realisation of the goal. The evaluation results can be used to make beter policy to improve welfare.

In Indonesia we can use Welfare Indicator (Indikator Kesejahteraan Rakyat/Inkesra) to measure welfare. This indicator is based on basic needs. This indicator is processed from SUSENAS.

To measure welfare improvement, we need to analyze cluster change over periods. A method that can be used clustering is Self-organizing Maps (SOM). Based on clustering result of data from different period, we can analyze cluster change.

This research used 22 variables and 497 records. The result of this research is regencies/municipalities in 2011 can be divided into six clusters and seven clusters in 2014. Variable that changed significantly in most of migrated clusters is School Participation."