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Food Self-sufficiency Decision Support Model Based on Provinces in Indonesia Using the Clustering Method

Journal of Physics: Conference Series 2019年第1期1255卷

作者： M. Safii Mochamad Wahyudi Solikhun Muhammad Zarlis Syahril Effendi Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

In Indonesia rice is a staple food as a major source of carbohydrates. Rice is also a staple food of the people of most countries in Asia and even most of the population in the world. Food security for Indonesia is closely linked to the adequacy of rice provision. The indicators of national food security are (1) the availability of food every time; (2) the ability or purchasing power of the people towards food; (3) guarantee of distribution and supply of food; and (4) the ability to import in urgent conditions. Rice as a rice-producing crop is a very important commodity for Indonesia, besides being the main food producer, rice commodity is also the main source of income from millions of farmers. The availability of rice at affordable prices to communities is an important factor for national security, security and stability. Indonesia has a large population, the fourth largest in the world after China, America and India. Dependence on rice imports has a high risk not only of food dependency on other countries, but also limited availability of rice in the international market. In 1977 Indonesia imported 2 million tons of rice and accounted for one third of the rice available on the international market, affecting the price of rice. Increased rice production can be achieved through increased productivity with the application of technology varieties and better cultivation and expansion of planting areas with increased intensity of planting and printing or opening of new rice cultivation area. Based on the above explanation, the researcher uses Data Mining Clustering with K-Means to get the assessment result of all rice production provinces. With this method the results of the research can be used as a model of decision makers for the government to give priority attention to areas that have the potential to increase rice production.

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Understanding and applying biological resilience, from genes to ecosystems

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NPJ Biodiversity 2023年第1期2卷 16页

作者： Thorogood, Rose Mustonen, Ville Aleixo, Alexandre Aphalo, Pedro J. Asiegbu, Fred O. Cabeza, Mar Cairns, Johannes Candolin, Ulrika Cardoso, Pedro Eronen, Jussi T. Hällfors, Maria Hovatta, Iiris Juslén, Aino Kovalchuk, Andriy Kulmuni, Jonna Kuula, Liisa Mäkipää, Raisa Ovaskainen, Otso Pesonen, Anu-Katriina Primmer, Craig R. Saastamoinen, Marjo Schulman, Alan H. Schulman, Leif Strona, Giovanni Vanhatalo, Jarno HiLIFE Helsinki Institute of Life Science University of Helsinki Helsinki Finland Research Programme in Organismal & Evolutionary Biology Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Computer Science Faculty of Science University of Helsinki Helsinki Finland Helsinki Institute for Information Technology University of Helsinki Helsinki Finland Institute of Biotechnology HiLIFE Helsinki Institute for Life Science University of Helsinki Helsinki Finland LUOMUS Finnish Museum of Natural History University of Helsinki Helsinki Finland Viikki Plant Science Centre University of Helsinki Helsinki Finland Department of Forest Sciences Faculty of Agriculture and Forestry University of Helsinki Helsinki Finland HELSUS Helsinki Institute of Sustainability Science University of Helsinki Helsinki Finland CE3C - Centre for Ecology Evolution and Environmental Changes CHANGE—Global Change and Sustainability Institute Faculty of Sciences University of Lisbon Lisbon 1749-016 Portugal Research Programme in Ecosystems and Environment Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland BIOS Research Unit Helsinki Finland Research Centre for Ecological Change Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Syke Finnish Environment Institute Helsinki Finland SleepWell Research Program Faculty of Medicine University of Helsinki Helsinki Finland Department of Psychology and Logopedics Faculty of Medicine University of Helsinki Helsinki Finland Neuroscience Center HiLIFE Helsinki Institute for Life Science University of Helsinki Helsinki Finland VTT Technical Research Centre of Finland Ltd Espoo Finland Department of Evolutionary and Population Biology Institute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam Netherlands Natural Resources Institute Finland (Luke) Helsinki Finland Centre for Biodiversity Dynamics

The natural world is under unprecedented and accelerating pressure. Much work on understanding resilience to local and global environmental change has, so far, focussed on ecosystems. However, understanding a system’s behaviour requires knowledge of its component parts and their interactions. Here we call for increased efforts to understand ‘biological resilience’, or the processes that enable components across biological levels, from genes to communities, to resist or recover from perturbations. Although ecologists and evolutionary biologists have the tool-boxes to examine form and function, efforts to integrate this knowledge across biological levels and take advantage of big data (e.g. ecological and genomic) are only just beginning. We argue that combining eco-evolutionary knowledge with ecosystem-level concepts of resilience will provide the mechanistic basis necessary to improve management of human, natural and agricultural ecosystems, and outline some of the challenges in achieving an understanding of biological resilience. © The Author(s) 2023.

关键词： Ecology Biodiversity Community ecology Ecological modelling Ecosystem ecology Evolutionary ecology Molecular ecology Palaeoecology

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Resource-optimized fermionic local-hamiltonian simulation on a quantum computer for quantum chemistry

arXiv

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arXiv 2020年

作者： Wang, Qingfeng Li, Ming Monroe, Christopher Nam, Yunseong Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ College ParkMD20740 United States Joint Quantum Institute Department of Physics Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States Department of Physics University of Maryland College ParkMD20742 United States

The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the rz and t gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than 20%, in small instances, is possible. © 2020, CC BY.

关键词： Fault tolerance

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Preventing bad behavior in academia

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四川生理科学杂志 2024年第7期46卷 1615-1615页

作者： Rayane da Cruz Albino Faculty of Pharmacy Federal University of Rio de Janeiro Rio de Janeiro RJ Brazil. Department of Host-Microbe Interactions St. Jude Children’s Research Hospital Memphis TN USA. School of the Environment The University of Queensland Whiterock QLD Australia. KU Leuven Ghent Belgium. Laboratory for Computational Social Systems Indraprastha Institute of Information Technology Delhi New Delhi India. University Medical College Shantou Guangdong China. Department of Ecoscience Aarhus Universitet Aarhus Denmark. Institute of Environment and Sustainable Development Banaras Hindu University Varanasi Uttar Pradesh India. Department of Medical Parasitology Faculty of Medicine and Health Sciences Sana’a University Sana’a Yemen and Tropical Disease Research Center Faculty of Medicine and Health Sciences University of Science and Technology Sana’a Yemen. Department of Medicine University of Montreal Montreal QC Canada. Electricity Infrastructure and Buildings Division Pacific Northwest National Laboratory Portland OR USA. Department of Biological Sciences University of New Brunswick Saint John Saint John NB Canada. Department of Biomedical Engineering The University of Melbourne Melbourne VIC Australia. Vagelos Molecular Life Sciences Program University of Pennsylvania Philadelphia PA USA. Doctoral Program in Neurobiology and Behavior Columbia University New York NY USA. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA. Department of Engineering University of Cambridge Cambridge Cambridgeshire UK. Department of Geography Liverpool John Moores University Liverpool UK. Department of Biology Stanford University Stanford CA USA. Department of Psychology University of Nicosia Nicosia Cyprus. Department of Global Ecology Carnegie Institution for Science Stanford CA USA. Research and Support Division Stellenbosch University Cape Town South Africa.

We gave young scientists this prompt:Describe one change to scientific policy or culture that would substantially decrease incidents of scientific misconduct or other unethical behavior.

关键词： behavior. prompt culture

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Evaluation of PHP Framework Measured Using Object-Oriented Metrics with the Analytic Hierarchy Process

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IOP Conference Series: Materials science and Engineering 2020年第1期874卷

作者： R Setiyawan W Gata Elbiansyah D Ardiansyah D Yuliandari D Wijayanti F P Harmono Y Komalasari M Lase M H Fakhriza Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Indonesia Information System Universitas Bina Sarana Informatika Indonesia Information Technology Universitas Bina Sarana Informatika Indonesia Information Technology Postgraduate Program STMIK Nusa Mandiri Indonesia

The existence of various PHP frameworks may become one alternative choice in developing a web application that PT XYZ wants to evaluate its Wisanggeni internal PHP framework in order to measure how far the design quality of Wisanggeni framework is working. An evaluation on PHP framework using object-oriented metric parameter and design quality is then conducted in this research. The results of measurement conducted using object-oriented metric parameters for each framework are evaluated with the Analytic Hierarchy Process (AHP) method to determine the best framework model design quality used as a reference for the development of Wisanggeni. This study also uses a combination of PHPDepend and PHPMetrics devices to measure the values of object-oriented metrics in each PHP framework. The research final result is that each framework has one value representing each framework's quality in which the quality of Wisanggeni framework is almost to the same with the Laravel and CodeIgniter framework.

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Improving Probabilistic Flooding Using Topological Indexes

Improving Probabilistic Flooding Using Topological Indexes

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Dawit Kifle Gabriele Gianini Mulugeta Libsie IT Doctoral Program Addis Ababa University Addis Ababa Ethiopia EBTIC/Khalifa University of Science and Technology Abu Dhabi UAE Università degli Studi di Milano Milano Italy Department of Computer Science Addis Ababa University Addis Ababa Ethiopia

ISBN: (数字)9781728156866

ISBN: (纸本)9781728156873

Unstructured networks are characterized by constrained resources and require protocols that efficiently utilize bandwidth and battery power. Probabilistic flooding, allows nodes to rebroadcast RREQ packets with some probability p, thus reducing the overhead. The key issue in of this algorithm consists of determining p. The techniques proposed so far either use a fixed p determined by a priori considerations, or a p variable from one node to the other - set, for instance based on node degree or distance between source and destination - or even a dynamic p based on the number of redundant messages received by the nodes. In order to make the computation of forwarding probability p works optimally regardless of changing of topology, we propose to set p based on the node role within the message dissemination process. Specifically, we propose to identify such role based on the nodes' clustering coefficients (the lower the coefficient, the higher the forwarding probability). The performance of the algorithm is evaluated in terms of routing overhead, packet delivery ratio, and end-to-end delay. The algorithm pays a price in terms of computation time for discovering the clustering coefficient, however reduces unnecessary and redundant control messages and achieves a significant improvements in both dense and sparse networks in terms of packet delivery ratio. We compare by simulation the performance of this algorithm with the one of the most representative competing algorithms.

关键词： Topology Clustering algorithms Probabilistic logic Protocols Routing Delays Simulation

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The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot 3

The Application of AGNES Algorithm to Optimize Knowledge Bas...

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3rd International Conference on information Management and technology, ICIMTech 2018

作者： Sano, Albert Verasius Dian Imanuel, Tanto Daud Intanadias Calista, Mega Nindito, Hendro Condrobimo, Andreas Raharto Bina Nusantara Institute of Creative Technology Computer Science Study Program Malang65126 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Most tourists have limited time and schedule when they are visiting a particular tourism area. One of the main issues faced by those tourists is that they can not make simple queries to search engines about, for example, which sites or places to visit optimally if we only have one day or two-day visit? Search engines are better and better in replying users' queries with relevant answers. However, search engines are not always able to respond queries suited to users' characteristics such as their styles, personalities, knowledge backgrounds, etc. Also, search engines are not as flexible as chatbots in enabling dialogical-communication-queries. This case study aims to respond aformentioned issue by applying hierarchical cluster analysis on a set of tourism sites around Malang city, Malang regency, and Batu city based on AGNES (Agglomerative Nesting) algorithm. The result, then, is fed into chatbot's knowledge base. This chatbot will assist tourists to get information on which possible sites they have to visit optimally if they are under limited vacancy-Time constraints. © 2018 IEEE.

关键词： Search engines

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Service Quality Improvement by Using the Quality Function Deployment (QFD) Method at the Government General Hospital 1

Service Quality Improvement by Using the Quality Function De...

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1st Workshop on Environmental science, Society, and technology, WESTECH 2018

作者： Hasibuan, Abdurrozzaq Parinduri, Luthfi Sulaiman, Oris Krianto Suleman, Abdul Rahman Harahap, Adek Khadijatul Z Hasibuan, Masnilam Rupilele, Frits Gerit John Simarmata, Janner Kurniasih, Nuning Achmad Daengs, G.S. Abdussakir Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Faculty of Computer Science Universitas Victory Sorong Sorong Indonesia Faculty of Economic Universitas Graha Nusantara Padangsidimpuan Indonesia Universitas Negeri Medan Medan Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Faculty of Economic Universitas 45 Surabaya Surabaya Indonesia Faculty of Science and Technology Universitas Islam Negeri Maulana Malik Ibrahim Malang Indonesia

In the face of increasingly competitive competition in the hospital industry, RSU managers are required to be able to develop strategies, policies or new breakthroughs related to improving the quality of their services, through improving the characteristics of hospital services, which focus on patient needs, so that the risk of errors or discrepancies between service characteristics that are enhanced by what the patient wants can be avoided or minimized. From the results of research conducted there are 21 variables of patient needs from a health service at the Government General Hospital (RSU). Whereas the patient's research on the service quality of the Government Hospital is 1 variable that has fulfilled the needs of patients, namely that they are satisfied with the quality of hospital services. Variable is the state and completeness of modern medical facilities. Whereas for other variables there are gaps so that they cannot meet patient expectations until the highest quality limit is very satisfied, it is necessary to have a direction of improvement. To obtain the suitability, the technique used to improve the characteristics of the service is the application of the QFD method. The QFD method in this study is in the form of a quality service matrix at the Government General Hospital. From the HOQ matrix, the service quality of the Government Hospital is obtained from the input of the Government Hospital/management that there are priority variables needed to improve their quality, which is generally the patient's needs related to the recovery of patients, including the knowledge and abilities of doctors, medicines the treatment given in the healing of patients, the service of examination, treatment and care that is fast and precise, guarantee of security and trust in the services provided and the completeness of the readiness and cleanliness of the equipment used. So there are 33 service quality characteristics prioritized for further improvement, with the main pr

关键词： Quality function deployment

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Web Security and Vulnerability: A Literature Review

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Journal of Physics: Conference Series 2020年第2期1477卷

作者： H Yulianton H L H S Warnars B Soewito F L Gaol E Abdurachman Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Information Technology Universitas Stikubank Semarang Indonesia 50243

The web continues to grow and attacks against the web continue to increase. This paper focuses on the literature review on scanning web vulnerabilities and solutions to mitigate web attacks. Vulnerability scanning methods will be reviewed as well as frameworks for improving web security. This research is the basis for future work that will end with the elaboration of web scanning and security with the aim of proposing better innovations.

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