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Liquid-Solid Partitioning of Precipitation along an Altitude Gradient and Its Statistical Properties: An Italian Case Study

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American Journal of Climate Change 2014年第1期3卷 71-82页

作者： Francesco Avanzi Carlo De Michele Antonio Ghezzi Department of Civil and Environmental Engineering Politecnico di Milano Milan Italy

Climate change is a living topic when dealing with modern natural sciences. The increase in the average air temperature, as measured in the last decades, is considered as the most relevant effect of climate change on the Earth system. Since the air temperature has a key role in determining the partitioning between liquid and solid precipitation events at a site, important changes in rainfall dynamics are expected, especially in mountainous areas. Thus, an important issue for modern hydrology is to determine how climate change would affect the liquid-solid partitioning of precipitation and its statistical properties. The main aim here is to determine, via statistical analysis and goodness-of-fit tests, whether the duration of precipitation events under the different forms (namely solid, liquid and mixed) may be characterized by the same probability distribution. Similar issue is tested for the volume of precipitation. For this aim, our study pays attention to hourly data collected along an altitude gradient identified through six automatic weather stations in Trentino region, northeast Italy. To distinguish the different types of events from observed heated pluviometers’ data, a partitioning procedure has been used and validated, through some disdrometer data. Sample data of duration and volume, relatively to solid, liquid and mixed events, are extracted, and univariate and bivariate statistics are calculated. Then, the two-sample Kolmogorov-Smirnov test is used to test if the data distinguished by different types of precipitation can be considered extracted from the same distribution. The results showed that in most cases, durations, as well as volumes of the different types of events, cannot be considered equally distributed. This consideration is particularly clear at high elevations.

关键词： Climate Change Statistical inference Precipitation Events Partitioning Snow Mountainous Hydrology

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Intelligent Biometric Information Management

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Intelligent Information Management 2010年第9期2卷 499-511页

作者： Harry Wechsler 不详

We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.

关键词： Authentication Biometrics Boosting Change Detection Complexity Cross-Matching Data Fusion Ensemble Methods Forensics Identity Management Imposters inference Intelligent Information Management Margin gain MDL Multi-Sensory Integration Outlier Detection P-Values Quality Randomness Ranking Score Normalization Semi-Supervised Learning Spectral Clustering Strangeness Surveillance Tracking Typicality Transduction

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Fuzzy Rules to Improve Traffic Light Decisions in Urban Roads

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Journal of Intelligent Learning Systems and Applications 2018年第2期10卷 36-45页

作者： J. A. Castá n Rocha S. Ibarra Martí nez J. Laria Menchaca J. D. Terá n Villanueva M. G. Treviñ o Berrones J. Pé rez Cobos D. Uribe Agundis Faculty of Engineering Autonomous University of Tamaulipas Ciudad Victoria Mexico TecNM/Instituto Tecnoló gico de La Laguna Torreon Mexico

Many researchers around the world are looking for developing techniques or technologies that cover traditional and recent constraints in urban traffic con-trol. Normally, such traffic devices are facing with a large scale of input data when they must to response in a reliable, suitable and fast way. Because of such statement, the paper is devoted to introduce a proposal for enhancing the traffic light decisions. The principal goal is that a semaphore can provide a correct and fluent vehicular mobility. However, the traditional semaphore operative ways are outdated. We present in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach. However, this proposal should include whether it is needed to modify such light duration. To do this, the paper proposes the adaptation of a fuzzy inference system helping to decide when the semaphore should try to fix the green light interval according to specific road requirements. Some experiments are conducted in a simulated environment to evaluate the pertinence of implementing a decision-making before the CBR methodology. For example, using a fuzzy inference approach the decisions of the system improve almost 18% in a set of 10,000 experiments. Finally, some conclusions are drawn to emphasize the benefits of including this technique in a methodology to implement intelligent semaphores.

关键词： Fuzzy inference System Urban Traffic Control Vehicular Mobility Intelligent Transport System

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Empirical Analysis of Interactions of Agricultural Sector and HIV/AIDS Pandemic in Africa

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World Journal of AIDS 2013年第2期3卷 92-104页

作者： Temidayo Gabriel Apata Department of Agricultural Economics and Extension Services Joseph Ayo Babalola University Ikeji-Aakeji Nigeria.

This study examines long run economic cost of HIV/AIDS on agriculture. Twenty-two African Countries were identified through purposive sampling. The sampling procedure helped to identify 1420 affected households. However, 1300 observations were found suitable for the subsequent analysis. Data were subjected to descriptive statistics and Overlapping Generation (OLG) model. The causes of high prevalence rates are the issue of poverty, fertility, myth and migration among others. Factors responsible for the classification of high HIV/AIDS prevalence rates were the patterns of spread of infectious disease that are closely associated with patterns of human mobility. For lower HIV/AIDS prevalence rate factors were low values of procreation and high values placed on morals. A positive correlation between HIV prevalence and GDP per capita was found. The study found out that there is a curvilinear relationship between the course of the HIV/AIDS epidemic and agricultural/economic growth in terms of human capita development.

关键词： HIV/AIDS Prevalence Rates Long-Run Economic Cost Overlapping Generation (OLG) Model Econometric inference Africa

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CANFIS—a computer aided diagnostic tool for cancer detection

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Journal of Biomedical Science and Engineering 2009年第5期2卷 323-335页

作者： Latha Parthiban R. Subramanian Department of Computer Science Pondicherry University Puducherry India. Research Scholar in Pondicherry University and working in Aarupadai Veedu Institute of Technology Chennai India

In this investigation, an approach using Coac-tive Neuro-Fuzzy inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their

关键词： Neural Network Coactive Neuro-Fuzzy inference Systems Probabilistic Neural Network Principal Component Analysis Stern Series Wisconsin Breast Cancer Data

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Healing Dysfunctional Identity: Bridging Mind-Body Intervention to Brain Systems

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Journal of Behavioral and Brain Science 2017年第3期7卷 137-164页

作者： S. Shaun Ho Yoshio Nakamura Department of Psychiatry Stony Brook University Stony Brook NY USA Department of Psychiatry University of Michigan Ann Arbor MI USA Department of Anesthesiology Pain Research Center University of Utah School of Medicine Salt Lake City UT USA

In this paper, we aim to use an innovative model to integrate applied work on a fast-acting mind-body intervention, Mind-Body Bridging (MBB), with theoretical work based on psychology and neuroscience. In an affect-object generative inference and regulation (AGIR) model, we propose that functional dynamics between two systems, the affect-object thought generation system and the cognitive control system, can guide an individual to achieve homeostasis within self and harmonious relationships with others. We used Neurosynth (***), an automated meta-analysis database, to identify potential brain substrates underlying the key components in the AGIR model. Based on the findings, some brain regions are implicated as the key cortical substrates in this model, corroborating our central hypothesis that a hallmark of mind-body wellbeing can be characterized as a low-frequency anti-correlantion between 1) the cognitive control system including the dorsal anterior/middle cingulate cortex, and 2) the affect-object thought generation system including the ventromedial prefrontal cortex and posterior cingulate cortex. MBB provides an efficient strategy for responding to and dissolving a fundamental problem that impairs mind-body wellbeing, i.e., unrealistic identity-grasping consisting of self-centered embodied expectations of self and others. We demonstrated how theoretical and applied work could be integrated by drawing evidence from the neuroscience literature to support the AGIR model, and then we applied the AGIR model to elucidate how MBB might work.

关键词： Active inference Affects Brain Cortical Networks Embodied Beliefs Emotions Emotion Regulation Identity Intervention Mind-Body Wellbeing Mind-Body Bridging Neuroimaging Psychopathology Self

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Bayesian Decision Analysis for Recurrent Cervical Cancer

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Open Journal of Clinical Diagnostics 2014年第2期4卷 71-77页

作者： Chi-Chang Chang School of Medical Informatics Chung Shan Medical University Taichung Chinese Taipei

Risk modeling for recurrent cervical cancer requires the development of new concepts and methodologies. Unlike most daily decisions, many medical decision making have substantial consequences, and involve important uncertainties and trade-offs. The uncertainties may be about the accuracy of available diagnostic tests, the natural history of the cervical cancer, the effects of treatment in a patient or the effects of an intervention in a group or population as a whole. With such complex decisions, it can be difficult to comprehend all options “in our heads”. This study applied Bayesian decision analysis to an inferential problem of recurrent cervical cancer in survival analysis. A formulation is considered where individual was expected to experience repeated events, along with concomitant variables. In addition, the sampling distribution of the observations is modelled through a proportional intensity Nonhomogeneous Poisson process. The proposed decision models can provide decision support techniques not only for taking action in the light of all available relevant information, but also for minimizing expected loss. The decision process is useful in selecting the best alternative when a patient with recurrent cervical cancer, in particular, the proposed decision process can provide more realistic solutions.

关键词： Bayesian inference Recurrent Event Nonhomogeneous Poisson Process Cervical Cancer

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A Game Comparative Study:Object-Oriented Paradigm and Notification-Oriented Paradigm

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Journal of Software Engineering and Applications 2012年第9期5卷 722-736页

作者： Jean M.Simao Danillo L.Belmonte Glauber Z.Valenca Márcio V.Batista Robson R.Linhares Roni F.Banaszewski Joao A.Fabro Cesar A.Tacla Paulo C.Stadzisz Adriano F.Ronszcka Graduate School in Electrical Engineering&Industrial Computer Science(CPGEI) Federal University of Technology-ParanáCu-ritibaBrazil Graduate School of Applied Computing(PPGCA) Federal University of Technology-ParanáCuritibaBrazil

This paper presents a new programming paradigm named Notification-Oriented Paradigm (NOP) and analyses the performance aspects of NOP programs by means of an experiment. NOP provides a new manner to conceive, structure, and execute software, which would allow better performance, causal-knowledge organization, and decoupling than standard solutions based upon usual paradigms. These paradigms are essentially Imperative Paradigm (IP) and Declarative Paradigm (DP). In short, DP solutions are considered easier to use than IP solutions due to the concept of high-level programming. However, they are considered slower in execution and less flexible in development. Anyway, both paradigms present similar drawbacks such as redundant causal-evaluation and strongly coupled entities, which decrease the software performance and the processing distribution feasibility. These problems exist due to an orientation to a monolithic inference mechanism based upon sequential evaluation by searching on passive computational entities. NOP proposes another way to structure software and make its inferences, which is based upon small, collaborative, and decoupled computational entities whose interaction happens through precise notifications. In this context, this paper presents a quantitative comparison between two equivalent implementations of a computer game simulator (Pacman simulator), one developed according to the principles of Object-Oriented Paradigm (OOP/IP) in C++ and other developed according to the principles of NOP. The results obtained from the experiments demonstrate, however, a quite lower performance of NOP implementation. This happened because NOP applications are still developed using a framework based on C++. Besides, the paper shows that optimizations in the NOP framework improve NOP program performance, thereby evidencing the necessity of developing a NOP language/compiler.

关键词： Notification Oriented Paradigm Notification Oriented inference NOP and OOP Comparison

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A New Way to Implement Quantum Computation

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Journal of Quantum Information Science 2013年第4期3卷 127-137页

作者： Gennaro Auletta University of Cassino Cassino Italy

In this paper, I shall sketch a new way to consider a Lindenbaum-Tarski algebra as a 3D logical space in which any one (of the 256 statements) occupies a well-defined position and it is identified by a numerical ID. This allows pure mechanical computation both for generating rules and inferences. It is shown that this abstract formalism can be geometrically represented with logical spaces and subspaces allowing a vectorial representation. Finally, it shows the application to quantum computing through the example of three coupled harmonic oscillators.

关键词： Lindenbaum-Tarski Algebra 3D Logical Space Mechanical Computation inference Quantum Com-puting Raising Operators Lowering Operators

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Electrical Load Forecasting Using Fuzzy System

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Journal of Computer and Communications 2019年第9期7卷 27-37页

作者： Mahir Faysal Md. Jahirul Islam Md. Mohiuddin Murad Md. Imdadul Islam M. Ruhul Amin Department of Electronics and Communications Engineering East West University Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Savar Bangladesh Deparment of Mathematical and Physical Sciences East West University Dhaka Bangladesh

To cope with the demand and supply of electrical load of an interconnected power system of a country, we need to forecast its demand in advance. In this paper, we use a fuzzy system to forecast electrical load on short-term basis. Here, we consider temperature, humidity, seasons of a year and time segments of a day as the parameters, which govern the demand of electrical load. For each of the parameter, we use several membership functions (MFs) and then apply the Mamdani rule on MFs and the output is determined by using the centroid method. Finally, the surface plot reveals the real scenario of the load demand. The difference between actual load and the output of the fuzzy system is found as +1.65% to -13.76%. The concept of the paper can be applied in interconnected power system of Bangladesh to reduce power loss, especially when generation is higher than the demand.

关键词： Defuzzification Fuzzy inference Centroid Method Surface Plot APE

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