RETRACTED : Web Application To Monitor Logistics Distribution of Disaster Relief Using the CodeIgniter Framework

Following a rigorous, carefully concerns and considered review of the article published in International Journal of Artificial Intelligence Research to article entitled “Web Application To Monitor Logistics Distribution of Disaster Relief Using the CodeIgniter Framework” Vol 1, No 2, pp. 54-61, December 2017, DOI: 10.29099/ijair.v1i2.23 This paper has been found to be in violation of the International Journal of Artificial Intelligence Research Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in IOP Conference Series: Materials Science and Engineering Volume 325 on International Conference on Information Technology and Digital Applications (ICITDA 2017), https://iopscience.iop.org/article/10.1088/1757-899X/325/1/012015/metaThe document and its content have been removed from International Journal of Artificial Intelligence Research, and reasonable effort should be made to remove all references to this article

On potential cognitive abilities in the machine kingdom

The final publication is available at Springer via http://dx.doi.org/10.1007/s11023-012-9299-6Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent.We thank the anonymous reviewers for their comments, which have helped to significantly improve this paper. This work was supported by the MEC-MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, GVA project PROMETEO/2008/051, the COST - European Cooperation in the field of Scientific and Technical Research IC0801 AT. Finally, we thank three pioneers ahead of their time(s). We thank Ray Solomonoff (1926-2009) and Chris Wallace (1933-2004) for all that they taught us, directly and indirectly. And, in his centenary year, we thank Alan Turing (1912-1954), with whom it perhaps all began.Hernández-Orallo, J.; Dowe, DL. (2013). On potential cognitive abilities in the machine kingdom. Minds and Machines. 23(2):179-210. https://doi.org/10.1007/s11023-012-9299-6S179210232Amari, S., Fujita, N., Shinomoto, S. (1992). Four types of learning curves. Neural Computation 4(4), 605–618.Aristotle (Translation, Introduction, and Commentary by Ross, W.D.) (1924). Aristotle’s Metaphysics. Oxford: Clarendon Press.Barmpalias, G. & Dowe, D. L. (2012). 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(Eds.), Proceedings of 3rd international conference on artificial general intelligence (pp. 25–30). New York: Atlantis Press.Hernández-Orallo, J., & Dowe, D. L. (2010). Measuring universal intelligence: Towards an anytime intelligence test. Artificial Intelligence, 174(18), 1508–1539.Hernández-Orallo, J. & Dowe, D. L. (2011, April). Mammals, machines and mind games. Who’s the smartest?. The conversation, http://theconversation.edu.au/mammals-machines-and-mind-games-whos-the-smartest-566 .Hernández-Orallo J., Dowe D. L., España-Cubillo S., Hernández-Lloreda M. V., & Insa-Cabrera J. (2011). On more realistic environment distributions for defining, evaluating and developing intelligence. In: J. Schmidhuber, K. R. Thórisson, & M. Looks (Eds.), Artificial general intelligence 2011, volume 6830, LNAI series, pp. 82–91. New York: Springer.Hernández-Orallo, J., Dowe, D. L., & Hernández-Lloreda, M. V. (2012a, March). 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Dry Lab – Laboratorium Virtual Untuk Anlisa Rekayasa Lumpur Pemboran

Abstract Dry Lab is a virtual laboratory design. We called also as a laboratory of the future. Dry Lab was designed because of the increasingly advanced computerized especially Artificial Intelligence for making a simulator that can function to simulate a tool wich is can similiar with the real condition so that it gets the same results as when run in a conventional laboratory. With the existence of this Simulator technology, then I try to make a virtual simulator for drilling mud analysis which is very much needed in the world of oil engineering education especially and also needed in the world of oil and gas industry, especially when conducting drilling activities. Keywords: Dry Lab, Artificial Intelligence, virtual simulator, drilling mud. Abstrak Dry Lab adalah suatu rancangan virtual laboratorium. Dapat juga dikatakan sebagai Laboratorium masa depan. Dry Lab dirancang karena semakin majunya ilmu komputerisasi Artificial intelligence dalam membuat suatu simulator yang dapat berfungsi mensimulasikan suatu alat sesuai dengan cara kerja aslinya sehingga mendapatkan hasil yang sama seperti saat dijalankan di Laboratorium konvensional.Dengan adanya teknologi Simulator ini, maka saya mencoba membuat suatu simulator virtual untuk analisa lumpur pemboran yang sangat dibutuhkan dalam dunia pendidikan Teknik perminyakan khususnya dan juga dibutuhkan di dalam dunia industri Migas terutama saat melakukan kegiatan pemboran. Kata kunci: Dry Lab, Artificial intelligence, simulator virtual, lumpur pemboran. Reference: Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43. Aly Rasyid, A. R. (2021). Seleksi Material Untuk Casing Sumur Migas & Geothermal–Buku Referensi. Composition and Properties of Drilling and Completion Fluids: Seventh Edition, Caenn, RyenDarley, H. C.H. and Gray, George R. (2016) Composion And Properties Of Drilling And Complition Fluids,  H.C.H Darley and George R. Gray J.T. Patton (New Mexico State U.) P.F. Phelan (Los Alamos Natl Laboratory), Well Damage Hazards Associated With Conventional Completion Fluids Khodja, M., Khodja-Saber, M., Canselier, J. P., Cohaut, N. and Bergaya, F. (2010) ‘Drilling fluid technology: performances and environmental considerations’, Product and Services, From R&D to final solutions, pp. 227-232. Available at: http://cdn.intechopen.com/pdfs-wm/12330.pdf Nasution, M. M., Rasyid, A., & Pahrudin, G. (2022). Desain Formulasi Lumpur Untuk Pemboran Panas Bumi Di Sumur GG-01. JURNAL BHARA PETRO ENERGI, 11-18. Rasyid, A., Mardiana, R. Y., Budiono, K., & Noviasta, B. (2021, December). Drilling optimization in geothermal exploration wells using enhanced design of conical diamond element bit. In Asia Pacific Unconventional Resources Technology Conference, Virtual, 16–18 November 2021 (pp. 1795-1808). Unconventional Resources Technology Conference (URTeC). Rasyid, A., Soesanto, E., & Nababan, E. N. (2022). Evaluasi dan Optimasi Desain Casing Sumur Pemboran dengan Metode Maximum Load di Sumur ENN-1 di Lapangan Batuwangi. JURNAL BHARA PETRO ENERGI, 1-10. Rasyid, A. (2019). Pemanfaatan Wellbore Strengthening Agent Selama Pengeboran di Onshore Sumatera Bagian Utara Indonesia. Jurnal Jaring SainTek, 1(2). Rudi Rubiandini R.S, Buku Teknik Pemboran Volume 1, Bandung, 2015 Virtual and Physical Experimentation in Inquiry-Based Science Labs: Attitudes, Performance  and Access.Journal of Science Education and TechnologyPyatt, Kevin.,Sims, Rod, 2012 Virtual laboratories in engineering education: the simulation lab and remote labComputer Applications in Engineering Education.Balamuralithara, B. Woods, P. C. 2009 Agusman, A. R., Rasyid, A., & Lesmana, D. L. (2022). Evaluasi Water Shut Off Dan Membuka Lapisan Baru Sumur Bagong Di Lapangan Lesma. JURNAL BHARA PETRO ENERGI, 38-43.  

Image and interpretation using artificial intelligence to read ancient Roman texts

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes a system that assists expert papyrologists in the interpretation of the Vindolanda writing tablets. A model-based approach is taken that relies on models of the written form of characters, and statistical modelling of language, to produce plausible interpretations of the documents. Fusion of the contributions from the language, character, and image feature models is achieved by utilizing the GRAVA agent architecture that uses Minimum Description Length as the basis for information fusion across semantic levels. A system is developed that reads in image data and outputs plausible interpretations of the Vindolanda tablets

Novel Artificial Human Optimization Field Algorithms - The Beginning

New Artificial Human Optimization (AHO) Field Algorithms can be created from scratch or by adding the concept of Artificial Humans into other existing Optimization Algorithms. Particle Swarm Optimization (PSO) has been very popular for solving complex optimization problems due to its simplicity. In this work, new Artificial Human Optimization Field Algorithms are created by modifying existing PSO algorithms with AHO Field Concepts. These Hybrid PSO Algorithms comes under PSO Field as well as AHO Field. There are Hybrid PSO research articles based on Human Behavior, Human Cognition and Human Thinking etc. But there are no Hybrid PSO articles which based on concepts like Human Disease, Human Kindness and Human Relaxation. This paper proposes new AHO Field algorithms based on these research gaps. Some existing Hybrid PSO algorithms are given a new name in this work so that it will be easy for future AHO researchers to find these novel Artificial Human Optimization Field Algorithms. A total of 6 Artificial Human Optimization Field algorithms titled "Human Safety Particle Swarm Optimization (HuSaPSO)", "Human Kindness Particle Swarm Optimization (HKPSO)", "Human Relaxation Particle Swarm Optimization (HRPSO)", "Multiple Strategy Human Particle Swarm Optimization (MSHPSO)", "Human Thinking Particle Swarm Optimization (HTPSO)" and "Human Disease Particle Swarm Optimization (HDPSO)" are tested by applying these novel algorithms on Ackley, Beale, Bohachevsky, Booth and Three-Hump Camel Benchmark Functions. Results obtained are compared with PSO algorithm.Comment: 25 pages, 41 figure

A Hybrid Reasoning Model for “Whole and Part” Cardinal Direction Relations

We have shown how the nine tiles in the projection-based model for cardinal directions can be partitioned into sets based on horizontal and vertical constraints (called Horizontal and Vertical Constraints Model) in our previous papers (Kor and Bennett, 2003 and 2010). In order to come up with an expressive hybrid model for direction relations between two-dimensional single-piece regions (without holes), we integrate the well-known RCC-8 model with the above-mentioned model. From this expressive hybrid model, we derive 8 basic binary relations and 13 feasible as well as jointly exhaustive relations for the x- and y-directions, respectively. Based on these basic binary relations, we derive two separate composition tables for both the expressive and weak direction relations. We introduce a formula that can be used for the computation of the composition of expressive and weak direction relations between “whole or part” regions. Lastly, we also show how the expressive hybrid model can be used to make several existential inferences that are not possible for existing models

An open learning environment for the diagnosis, assistance and evaluation of students based on artificial intelligence

The personalized diagnosis, assistance and evaluation of students in open learning environments can be a challenging task, especially in cases that the processes need to be taking place in real-time, classroom conditions. This paper describes the design of an open learning environment under development, designed to monitor the comprehension of students, assess their prior knowledge, build individual learner profiles, provide personalized assistance and, finally, evaluate their performance by using artificial intelligence. A trial test has been performed, with the participation of 20 students, which displayed promising results