The Application of Swarm Intelligence to Collective Robots

2006 ◽  
pp. 157-185 ◽  
Author(s):  
Amanda J.C. Sharkey ◽  
Noel Sharkey
Keyword(s):  
Swarm Intelligence ◽  
Proof Of Concept ◽  
Practical Application ◽  
Predator Prey ◽  
Expected Benefits ◽  
Intelligent Approach ◽  
Intelligence Approach ◽  
Robotic Applications ◽  
Study Application

This chapter considers the application of swarm intelligence principles to collective robotics. Our aim is to identify the reasons for the growing interest in the intersection of these two areas, and to evaluate the progress that has been made to date. In the course of this chapter, we will discuss the implications of taking a swarm intelligent approach, and review recent research and applications. The area of “swarm robotics” offers considerable promise for practical application, although it is still in its infancy, and many of the tasks that have been achieved are better described as “proof-of-concept” examples, rather than full-blown applications. In the first part of the chapter, we will examine what taking a swarm intelligence approach to robotics implies, and outline its expected benefits. We shall then proceed to review recent swarm robotic applications, before concluding with a case study application of predator-prey robotics that illustrates some of the potential of the approach.

The Application of Swarm Intelligence to Collective Robots

2011 ◽  
pp. 1444-1470
Author(s):  
Amanda J.C. Sharkey ◽  
Noel Sharkey
Keyword(s):  
Swarm Intelligence ◽  
Proof Of Concept ◽  
Practical Application ◽  
Predator Prey ◽  
Expected Benefits ◽  
Intelligent Approach ◽  
Intelligence Approach ◽  
Robotic Applications ◽  
Study Application

This chapter considers the application of swarm intelligence principles to collective robotics. Our aim is to identify the reasons for the growing interest in the intersection of these two areas, and to evaluate the progress that has been made to date. In the course of this chapter, we will discuss the implications of taking a swarm intelligent approach, and review recent research and applications. The area of “swarm robotics” offers considerable promise for practical application, although it is still in its infancy, and many of the tasks that have been achieved are better described as “proof-of-concept” examples, rather than full-blown applications. In the first part of the chapter, we will examine what taking a swarm intelligence approach to robotics implies, and outline its expected benefits. We shall then proceed to review recent swarm robotic applications, before concluding with a case study application of predator-prey robotics that illustrates some of the potential of the approach.

ANALISIS KINERJA KEUANGAN IAIN PONTIANAK TAHUN 2014-2018 BERDASARKAN PENDEKATAN BALANCE SCORECARD

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
JATRIANA B2041142013
Keyword(s):  
Higher Education ◽  
Balanced Scorecard ◽  
Six Sigma ◽  
Balance Scorecard ◽  
The Balanced Scorecard ◽  
College And University ◽  
University Planning ◽  
Education Journal ◽  
Study Application

Penelitian ini bertujuan untuk mengukur kinerja keuangan kampus IAIN Pontianak menggunakan pendekatan Balance Scorecard. Metode penelitian ini adalah kuantitatif dengan menggunakan statistika untuk menganalisis sampel yang digunakan sebanyak 664 orang mahasiswa dan 193 orang dosen dan pegawai. Hasil penelitian menyatakan bahwa variabel perspektif pelanggan, perpektif bisnis internal dan variabel perspektif pertumbuhan dan pembelajaran, masing-masing berpengaruh positif dan signifikan terhadap peningkatan kinerja keuangan IAIN Pontianak.Kata Kunci : Balance Scorecard, IAIN Pontianak, Kinerja KeuanganDAFTAR PUSTAKA Andriyanto, R. W., & Metalia, M. (2010). Efektivitas Balanced Scorecard Dalam Maningkatkan Kinerja Manajerial Badan Usaha Milik Negara (Bumn). Jurnal Akuntansi dan Investasi, 11(2), 97-114.Arikunto, S. 1992. Prosedur penelitian: Suatu pendekatan praktik. Rineka Cipta.Bastian, Indra. 2006. Akutansi Sektor Publik, Suatu Pengantar. Jakarta: Airlangga.Brown, Cindy. 2012. Application of the Balanced Scorecard in Higher Education: Opportunities and Challenges - An Evaluation of Balanced Scorecard Implementation at the College of St. Scolastica. SCUP; Society for College and University Planning. www.scup.org/phe.html.Effendi, R. (2012). Pengukuran Kinerja Sektor Publik Dengan Menggunakan Balanced Scorecard (Studi Kasus Kanwil DJP Sumsel dan Kep. Babel). Jurnal Ilmiah Stie Mdp, 1(2), 67-73.Gaspersz, Vicent. 2002. Sistem Manajemen Kinerja Terintegrasi: Balanced Scorecard dengan Six Sigma untuk Organisasi Bisnis dan Pemerintah. Cet ke-3, Jakarta: Gramedia Pustaka UtamaHandayani, S. (2017). Analisis Balanced Scorecard Sebagai Tolok Ukur Kinerja Perusahaan Pada Pt Pos Indonesia ( Persero ) Lamongan. Jurnal Penelitian Ekonomi dan Akuntansi, II(3), 589-601.IAIN Pontianak. 2019. “Sistem Informasi Akademik Institut Agama Islam Negeri Pontianak.” Mahasiswa IAIN Pontianak. www.sia.iainptk.ac.id.Kaplan, S. Robert, and David P. Norton. 2000. Balanced Scorecard, Menerapkan Strategi Menjadi Aksi. Jakarta: Penerbit Erlangga.Karathanos, Dementrius, and Patricia Karathanos. 2005. “Appliying the Balanced Scoredard to Education.” Journal of Education for Business: 222–30.Kemenristek Dikti RI. 2019. “Pangkalan Data Pendidikan Tinggi:  Kementrian Riset , Teknologi, Dan Pendidikan Tinggi.” Tenaga Pendidik  IAIN Pontianak. www/forlap.ristekdikti.go.id.Kementrian Agama RI. 2019. “Seleksi Prestasi Akademik Nasional APerguruan Tinggi Keagamaan Islam Negeri.” SPAN PTKIN 2019. https://span-ptkin.ac.id.Mahsun, Muhammad. 2006. Pengukuran Kinerja Sektor Publik. 1st ed. Yogyakarta: BPFE.Mardiasmo. 2004. Akuntansi Sektor Publik. 1st ed. Yogyakarta: BPFE.Mulyadi. 2007. Balanced Scorecard, Alat Manajemen Kontemporer Untuk Pelipatganda Kinerja Keuangan Perusahaan. 1st ed. Jakarta: Penerbit Salemba Empat.Nugrahini, I. A. P., Ratnadi, N. M. D., & Putri, I. G. A. M. A. D. (2016). Penilaian Kinerja Berdasarkan Balanced Scorecard Pada Badan Penanaman Modal Dan Perijinan Daerah Kabupaten Tabanan. E-Jurnal Ekonomi dan Bisnis Universitas Udayana, 5(4), 829-856.Rollins, Andrea Mae. 2011. “A Case Study: Application of Balanced Scorecard in Hingher Education.” PhD Dissertation. San Diego State University.Singarimbun, Masri, and Sofian Effendi. 1989. Metode Penelitian Survey. Jakarta: LP3ES.Sugiono. 2005. Metode Penelitian Bisnis. Bandung: Alfabeta.Suta, I. W. P., & Dwiastuti, G. A. A. S. A. (2016). Pengukuran Kinerja Dengan Pendekatan Balanced Scorecard Pada Kantor Pusat Pt Bank Pembangunan Daerah Bali. Jurnal Bisnis Dan Kewirausahaan, 12(1), 32-41.Syarbaini, Khatib. 1986. “Fakultas Tarbiyah (Ketikan Manual).”Yassin, A., Musadieq, M. A., & Afrianty, T. W. (2016). Pengaruh Balanced Scorecard Dan Knowledge Management Terhadap Kinerja Karyawan Dan Kinerja Perusahaan (Studi Pada Karyawan Pt Semen Indonesia (Persero) Tbk). Jurnal Administrasi Bisnis, 33(2), 125-134.

Design of water allocation model: efficiency and risk aspects

2005 ◽  
Vol 5 (3-4) ◽  
pp. 9-16
Author(s):  
C. Kim ◽  
D. Han
Keyword(s):  
Water Allocation ◽  
Primary Objective ◽  
Allocation Model ◽  
Proportional Allocation ◽  
Model Efficiency ◽  
Service Sectors ◽  
Expected Benefits ◽  
Water Allocation Model ◽  
Allocation Methods

The primary objective of this study is to improve the methodology for water allocation focused on efficiency and risk aspects. To attain the primary objective, this study sets up an objective function to maximize social expected benefits, and considers three types of allocation methods. Three types of allocation methods are optimal, proportional, and fixed allocation between regions and service sectors. The results of case study area shows that the fixed allocation method is preferred to the proportional allocation in most cases except that the variance of flow is small with respect to efficiency. Also, efficient and less-risky allocation is simultaneously obtained in some cases, while efficiency and risk show the relation of trade-off in other cases.

scholarly journals Intelligent Approach for Improvement of BIPV Systems Performance: Case Study

2019 ◽  
Vol 471 ◽  
pp. 112015
Author(s):  
Dan Craciunescu ◽  
Laurentiu Fara ◽  
Ana-Maria Dabija ◽  
Paul Sterian ◽  
Silvian Fara
Keyword(s):  
Intelligent Approach

Optimizing preventive maintenance over a finite planning horizon in a semi-Markov framework

2020 ◽  
Author(s):  
Antonio Sánchez Herguedas ◽  
Adolfo Crespo Márquez ◽  
Francisco Rodrigo Muñoz
Keyword(s):  
Preventive Maintenance ◽  
Recurrence Relations ◽  
Direct Calculation ◽  
Planning Horizon ◽  
Practical Implementation ◽  
Practical Application ◽  
Mathematical Solution ◽  
Accumulated Reward ◽  
Finite Planning Horizon

Abstract This paper describes the optimization of preventive maintenance (PM) over a finite planning horizon in a semi-Markov framework. In this framework, the asset may be operating, and providing income for the asset owner, or not operating and undergoing PM, or not operating and undergoing corrective maintenance following failure. PM is triggered when the asset has been operating for τ time units. A number m of transitions specifies the finite horizon. This system is described with a set of recurrence relations, and their z-transform is used to determine the value of τ that maximizes the average accumulated reward over the horizon. We study under what conditions a solution can be found, and for those specific cases the solution τ* is calculated. Despite the complexity of the mathematical solution, the result obtained allows the analyst to provide a quick and easy-to-use tool for practical application in many real-world cases. To demonstrate this, the method has been implemented for a case study, and its accuracy and practical implementation were tested using Monte Carlo simulation and direct calculation.

scholarly journals R–R–T (resistance–resilience–transformation) typology reveals differential conservation approaches across ecosystems and time

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Guillaume Peterson St-Laurent ◽  
Lauren E. Oakes ◽  
Molly Cross ◽  
Shannon Hagerman
Keyword(s):  
Climate Change ◽  
Empirical Evidence ◽  
Climate Change Adaptation ◽  
Conservation Practices ◽  
Practical Application ◽  
Empirical Assessment ◽  
Transformative Action ◽  
Conservation Actions

AbstractConservation practices during the first decade of the millennium predominantly focused on resisting changes and maintaining historical or current conditions, but ever-increasing impacts from climate change have highlighted the need for transformative action. However, little empirical evidence exists on what kinds of conservation actions aimed specifically at climate change adaptation are being implemented in practice, let alone how transformative these actions are. In response, we propose and trial a novel typology—the R–R–T scale, which improves on existing concepts of Resistance, Resilience, and Transformation—that enables the practical application of contested terms and the empirical assessment of whether and to what extent a shift toward transformative action is occurring. When applying the R–R–T scale to a case study of 104 adaptation projects funded since 2011, we find a trend towards transformation that varies across ecosystems. Our results reveal that perceptions about the acceptance of novel interventions in principle are beginning to be expressed in practice.

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