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Scientific discovery in the age of artificial intelligence

NATURE 2023年第7978期621卷 E33-E33页

作者： Wang, Hanchen Fu, Tianfan Du, Yuanqi Gao, Wenhao Huang, Kexin Liu, Ziming Chandak, Payal Liu, Shengchao Van Katwyk, Peter Deac, Andreea Anandkumar, Anima Bergen, Karianne Gomes, Carla P. Ho, Shirley Kohli, Pushmeet Lasenby, Joan Leskovec, Jure Liu, Tie-Yan Manrai, Arjun Marks, Debora Ramsundar, Bharath Song, Le Sun, Jimeng Tang, Jian Velickovic, Petar Welling, Max Zhang, Linfeng Coley, Connor W. Bengio, Yoshua Zitnik, Marinka Department of Engineering University of Cambridge Cambridge UK Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA NVIDIA Santa Clara CA USA Department of Computational Science and Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Science Cornell University Ithaca NY USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Stanford University Stanford CA USA Department of Physics Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Mila – Quebec AI Institute Montreal Quebec Canada Université de Montréal Montreal Quebec Canada HEC Montréal Montreal Quebec Canada CIFAR AI Chair Toronto Ontario Canada Department of Earth Environmental and Planetary Sciences Brown University Providence RI USA Data Science Institute Brown University Providence RI USA Center for Computational Astrophysics Flatiron Institute New York NY USA Department of Astrophysical Sciences Princeton University Princeton NJ USA Department of Physics Carnegie Mellon University Pittsburgh PA USA Department of Physics and Center for Data Science New York University New York NY USA Google DeepMind London UK Department of Computer Science and Technology University of Cambridge Cambridge UK Microsoft Research Beijing China Department of Biomedical Informatics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Harvard Data Science Initiative Cambridge MA USA Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Cambridge MA USA Department of Systems Biology Harvard Medical School Boston MA USA Deep Forest Sciences Palo Alto CA USA BioMap Beijing China Mo

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A conceptual model of inquiry laboratory-based ethnosocioecology

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Journal of Physics: Conference Series 2019年第1期1175卷

作者： Aynin Mashfufah J Nurkamto Sajidan Wiranto Doctoral Program of Education Science Universitas Sebelas Maret Surakarta Indonesia Education Science Faculty IKIP PGRI Jember East Java Indonesia Teacher Training and Education Faculty Universitas Sebelas Maret Surakarta Indonesia Postgraduate Program of Science Education Universitas Sebelas Maret Surakarta Indonesia Informatics Study Program Universitas Sebelas Maret Surakarta Indonesia

The article is a literature review to emerge as a conceptual model of inquiry-based instruction. It was a study of literature and an analysis of the necessary to integrate local environmental knowledge into the instructional model, also the excessiveness and weakness of the inquiry cycle and especially inquiry lab. According to the analysis, the authors consider to design inquiry laboratory cycle based on ethnosocioecology and add one stage of the previous cycle which is consist of only five steps. The content of ethnosocioecology is expected to cultivate pre-service teacher awareness toward the environment. The additional step is an investigation. In addition to bridge the differences between upper and lower intellectual skills of the pre-service teacher, the investigation facilitates pre-service teacher to enlarge their knowledge, experience, and understanding about local practices in nature conservation to be applied in solving the environmental crisis. Hence, a new model of inquiry laboratory-based ethnosocioecology consists of six phases that are observation, investigation, manipulation, generalization, verification, and application. That phase is grounded to ethnosocioecology as a guide to conduct each stage of inquiry laboratory cycle. The new instructional model is predicted as a model to empower the environmental literacy among university student, especially biology pre-service teachers.

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Pool Water Acidity Gauge Using Fuzzy Mamdani Method

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Journal of Physics: Conference Series 2019年第1期1361卷

作者： Abdul Jabbar Lubis Ummul Khair Arnes Sembiring Ade Zulkarnain Dodi Siregar Student Doctor of Philosophy Computer Engineering Universitiy Malaysia Perlis Study Program of Informatics Faculty of Engineering and Computer Science Universitas Harapan Medan Jl. H.M. Jhoni No. 70 C Medan 20217 Indonesia

Swimming pool is one of the means of sports and play that is fun. Swimming pools must also be considered clean. In order to be replaced with new water. The goal is so that pool users are not infected with infectious diseases due to the dirty water inside the pool. The Mamdani method is the most common method when discussing fuzzy methodology. It was Ebrahim Mamdani who first proposed this method in 1975 when building a steam engine and boiler control system. Mamdani uses a collection of IF-THEN rules obtained from experienced operators / experts. Mamdani's work is actually based on the article 'The Father of Fuzzy, Lotfi A. Zadeh: fuzzy algorithms for complex systems and decision processes.

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Neural and phenotypic representation under the free-energy principle

arXiv

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arXiv 2020年

作者： Ramstead, Maxwell J.D. Hesp, Casper Tschantz, Alec Smith, Ryan Constant, Axel Friston, Karl Division of Social and Transcultural Psychiatry Department of Psychiatry McGill University MontrealQC Canada Culture Mind and Brain Program McGill University MontrealQC Canada Wellcome Centre for Human Neuroimaging University College London LondonWC1N3BG United Kingdom Department of Psychology University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Amsterdam Brain and Cognition Centre University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Institute for Advanced Study University of Amsterdam Oude Turfmarkt 147 Amsterdam1012 GC Netherlands Laureate Institute for Brain Research TulsaOK United States Theory and Method in Biosciences University of Sydney Level 6 Charles Perkins Centre D17 Johns Hopkins Drive NSW2006 Australia Sackler Centre for Consciousness Science University of Sussex Brighton United Kingdom Department of Informatics University of Sussex Brighton United Kingdom

The aim of this paper is to leverage the free-energy principle and its corollary process theory, active inference, to develop a generic, generalizable model of the representational capacities of living creatures;that is, a theory of phenotypic representation. Given their ubiquity, we are concerned with distributed forms of representation (e.g., population codes), whereby patterns of ensemble activity in living tissue come to represent the causes of sensory input or data. The active inference framework rests on the Markov blanket formalism, which allows us to partition systems of interest, such as biological systems, into internal states, external states, and the blanket (active and sensory) states that render internal and external states conditionally independent of each other. In this framework, the representational capacity of living creatures emerges as a consequence of their Markovian structure and nonequilibrium dynamics, which together entail a dual-aspect information geometry. This entails a modest representational capacity: internal states have an intrinsic information geometry that describes their trajectory over time in state space, as well as an extrinsic information geometry that allows internal states to encode (the parameters of) probabilistic beliefs about (fictive) external states. Building on this, we describe here how, in an automatic and emergent manner, information about stimuli can come to be encoded by groups of neurons bound by a Markov blanket;what is known as the neuronal packet hypothesis. As a concrete demonstration of this type of emergent representation, we present numerical simulations showing that self-organizing ensembles of active inference agents sharing the right kind of probabilistic generative model are able to encode recoverable information about a stimulus array. Copyright © 2020, The Authors. All rights reserved.

关键词： Free energy

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Designing of Android Based Learning (Mobile Learning) for Multidiscipline Students

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Journal of Physics: Conference Series 2020年第2期1569卷

作者： SC Wibawa IKD Nuryana IGPE Prismana DA Dermawan A Manyu A Frianto E Rahmadyanti DE Susetyaningsih N Shofiyah RM Yusron Mashudi Informatics Engineering Department Universitas Negeri Surabaya Indonesia 60231 Economics Department Universitas Negeri Surabaya Indonesia 60231 Civil Engineering Department Universitas Negeri Surabaya Indonesia 60231 Center of Information Technology Development Universitas Negeri Surabaya Indonesia Culinary Department Vocational State High School of 8 Surabaya Indonesia 60231 Department of Mechanical Engineering University of Trunojoyo Madura Indonesia Islamic Education Study Program The State Islamic Institute of Jember (IAIN) Indonesia 68136

A breakthrough in the multimedia field is needed by creating varied learning strategies to attract students' interest in learning. The purpose of this study is to create learning media M-Learning to support the learning process in Vocational High School and to know the level of prevalence M-Learning as a medium of learning. The research method using Research and Development which has eight stages: 1) Identification of Research Needs, 2) Purpose Formulation, 3) Formulation of material items, 4) Formulation of success tools, 5) Media manuscript formulation, 6) Tests or product trials, 7) Revisions, 8) Manuscripts are ready to be produced. This media is developed using Android Studio. The result of this research is a dynamic Android-based application that is run online as a supporter of learning. The results of validator assessment and student response can be obtained from the media expert value at 65% in the sense of valid, acquiring a low score due to a lot of revision of the application. According to the material experts, the media obtains the value of 85% which means valid, and a validity score of 94.7% is obtained from students' responses that mean valid. The conclusion shows that validator assessments of learning media can be used as supporting self-study, especially for multidiscipline students.

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Load balancing factor using greedy algorithm in the routing protocol for improving internet access

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IOP Conference Series: Materials Science and Engineering 2018年第1期420卷

作者： Ady Satria Poltak Sihombing Sawaluddin Informatics Engineering Study Program Magister Faculty of Computer Science and Information Technology University of Sumatera Utara

Load Balancing is very well applied to the distribution of internet access at any point of the Wi-Fi area so that the use of limited devices can be optimal and on target. The proper use of the Greedy Algorithms when applied to an access point device is very capable in resolving excessive loading in a single resource to take the best choice at every stage in an optimum process. Access point device is also a success factor in running the optimization of the distribution of Wi-Fi access on the Access Point is strongly influenced by the parameters set. In this research, user access factor in one very high Wi-Fi area also influences the possibility of incoming access failure. For the application of the results of this study can be utilized on all access point devices that have limits, but for speed internet access remains at the capacity provided bandwidth.

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Inter-comparison of multiple Global Climate Model (GCM) data based on spatial pattern of rainfall over Indonesia

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IOP Conference Series: Earth and Environmental Science 2019年第1期284卷

作者： Elania Aflahah Arnida Lailatul Latifah Rahmat Hidayat Rini Hidayati Andi Ihwan Applied Climatology Study Program Graduate School Bogor Agricultural University Bogor 16680 Laboratorium of High-Performance Computing Research Center for Informatics Indonesian Institute of Sciences Bogor West Java 16916 Department of Geophysics and Meteorology Bogor Agricultural University Bogor 16680

The Coupled Model Inter-comparison Project Phase 5 (CMIP5) is the output of many coupled atmosphere-ocean of global climate models (GCMs) and widely used for climate research, especially for driving regional climate model. There are more than 40 CMIP5 GCMs data available, but no single model can be considered as the best for every region. The use of CMIP5 GCMs data for rainfall projection in Indonesia is important to improve the accuracy of the monthly and seasonal rainfall forecast. Then, this study evaluates the capability of the CMIP5 GCMs data for Indonesia region by quantitatively comparing the spatial pattern of the precipitation mean and standard deviation of the CMIP5 data against GPCP, GPCC, and CRU data in the period 1980-2005. Furthermore, the composite analysis is conducted to observe the model performance in reproducing the precipitation characteristic over some areas in Indonesia. In conclusion, the models NorESM1-M, NorESM1-ME, GFDL-ESM2M, CSIRO-MK3-6-0 perform the rainfall mean better than others, while the standard deviation of the rainfall show that the models NorESM1-M, BNU-ESM, CMCC-CMS are superior in which NorESM1-M gives the best performance. The annual precipitation pattern of the model NorESM1-M over various areas in Indonesia is also highly correlated with the observations. Thus, the most suitable model for Indonesia region is NorESM1-M.

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Implementation of preference ranking organization method for enrichment evaluation (Promethee) on selection system of student's achievement

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IOP Conference Series: Materials Science and Engineering 2018年第1期332卷

作者： L Karlitasari D Suhartini L Nurrosikawati Computer Science Study Program Pakuan University Bogor Indonesia D3 Program of Management Informatics Pakuan University Bogor Indonesia

Selection of Student Achievement is conducted every year, starting from the level of study program, Faculty, to University, which then rank one will be sent to Kopertis level. The criteria made for the selection are Academic and Rich Scientific, Organizational, Personality, and English. In order for the selection of Student Achievement is Objective, then in addition to the presence of the jury is expected to use methods that support the decision to be more optimal in determining the Student Achievement. One method used is the Promethee Method. Preference Ranking Organization Method for Enrichment Evaluation (Promethee) is a method of ranking in Multi Criteria Decision Making (MCDM). PROMETHEE has the advantage that there is a preference type against the criteria that can take into account alternatives with other alternatives on the same criteria. The conjecture of alternate dominance over a criterion used in PROMETHEE is the use of values in the relationships between alternative ranking values. Based on the calculation result, from 7 applicants between Manual and Promethee Matrices, rank 1, 2, and 3, did not change, only 4 to 7 positions were changed. However, after the sensitivity test, almost all criteria experience a high level of sensitivity. Although it does not affect the students who will be sent to the next level, but can bring psychological impact on prospective student's achievement

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Analysis backpropagation methods with neural network for prediction of children's ability in psychomotoric

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Journal of Physics: Conference Series 2018年第1期978卷 012085-012085页

作者： Izhari, F Dhany, H W Zarlis, M Sutarman Informatics Engineering Study Program Master Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

A good age in optimizing aspects of development is at the age of 4-6 years, namely with psychomotor development. Psychomotor is broader, more difficult to monitor but has a meaningful value for the child's life because it directly affects his behavior and deeds. Therefore, there is a problem to predict the child's ability level based on psychomotor. This analysis uses backpropagation method analysis with artificial neural network to predict the ability of the child on the psychomotor aspect by generating predictions of the child's ability on psychomotor and testing there is a mean squared error (MSE) value at the end of the training of 0.001. There are 30% of children aged 4-6 years have a good level of psychomotor ability, excellent, less good, and good enough.

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Improvement in speech to text for bahasa Indonesia through homophone impairment training

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Journal of Computers (Taiwan) 2017年第5期28卷 1-10页

作者： Areni, Intan Sari Indrabayu Bustamin, Anugrayani Department of Electrical Engineering Electrical Study Program Universitas Hasanuddin Indonesia Department of Electrical Engineering Informatics Study Program Universitas Hasanuddin Indonesia Department of Electrical Engineering Universitas Hasanuddin Indonesia Research Group of Artificial Intelligence Multimedia Processing Universitas Hasanuddin Makassar Indonesia

In this research, an approach for increasing accuracy in speech to text application is done using Mel Frequency Cepstral Coefficient (MFCC) trained by Backpropagation Neural Network (BPNN). A set of Bahasa Indonesia homophones data speech is used for training and validation. The record is taken from 6 native adults comprising 3 males and 3 females. Working in 16 KHz sampling mode, the data is stored in WAV format. A confusion matrix is used to validate the system with and without homophone locking learning. A significant improvement is observed from the experiment. The percentage of accuracy is increased from 53.33 to 93.4 from male samples. From females' records, the increment is even higher. The accuracy percentage has risen from 36.8 to 93.33.

关键词： Neural networks

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