Relevant bibliographies by topics / Predictive Patterns

Academic literature on the topic 'Predictive Patterns'

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Published: 11 March 2023

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Journal articles on the topic "Predictive Patterns"

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Tao, Lv, Yongtao Hao, Hao Yijie, and Shen Chunfeng. "K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/3096917.

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Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1) the predictive power of a pattern varies a great deal for different shapes and (2) each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.
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Kaufmann, Mareile, Simon Egbert, and Matthias Leese. "Predictive Policing and the Politics of Patterns." British Journal of Criminology 59, no. 3 (December 7, 2018): 674–92. http://dx.doi.org/10.1093/bjc/azy060.

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AbstractPatterns are the epistemological core of predictive policing. With the move towards digital prediction tools, the authority of the pattern is rearticulated and reinforced in police work. Based on empirical research about predictive policing software and practices, this article puts the authority of patterns into perspective. Introducing four ideal-typical styles of pattern identification, we illustrate that patterns are not based on a singular logic, but on varying rationalities that give form to and formalize different understandings about crime. Yet, patterns render such different modes of reasoning about crime, and the way in which they feed back into policing cultures, opaque. Ultimately, this invites a stronger reflection about the political nature of patterns.
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Rew, Jehyeok, Sungwoo Park, Yongjang Cho, Seungwon Jung, and Eenjun Hwang. "Animal Movement Prediction Based on Predictive Recurrent Neural Network." Sensors 19, no. 20 (October 11, 2019): 4411. http://dx.doi.org/10.3390/s19204411.

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Observing animal movements enables us to understand animal behavior changes, such as migration, interaction, foraging, and nesting. Based on spatiotemporal changes in weather and season, animals instinctively change their position for foraging, nesting, or breeding. It is known that moving patterns are closely related to their traits. Analyzing and predicting animals’ movement patterns according to spatiotemporal change offers an opportunity to understand their unique traits and acquire ecological insights into animals. Hence, in this paper, we propose an animal movement prediction scheme using a predictive recurrent neural network architecture. To do that, we first collect and investigate geo records of animals and conduct pattern refinement by using random forest interpolation. Then, we generate animal movement patterns using the kernel density estimation and build a predictive recurrent neural network model to consider the spatiotemporal changes. In the experiment, we perform various predictions using 14 K long-billed curlew locations that contain their five-year movements of the breeding, non-breeding, pre-breeding, and post-breeding seasons. The experimental results confirm that our predictive model based on recurrent neural networks can be effectively used to predict animal movement.
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Peppler-Lisbach, Cord. "Predictive modelling of historical and recent land-use patterns." Phytocoenologia 33, no. 4 (November 19, 2003): 565–90. http://dx.doi.org/10.1127/0340-269x/2003/0033-0565.

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Choi, Minkyu, and Jun Tani. "Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatiotemporal Scales RNN Model." Neural Computation 30, no. 1 (January 2018): 237–70. http://dx.doi.org/10.1162/neco_a_01026.

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This letter proposes a novel predictive coding type neural network model, the predictive multiple spatiotemporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN learns to predict visually perceived human whole-body cyclic movement patterns by exploiting multiscale spatiotemporal constraints imposed on network dynamics by using differently sized receptive fields as well as different time constant values for each layer. After learning, the network can imitate target movement patterns by inferring or recognizing corresponding intentions by means of the regression of prediction error. Results show that the network can develop a functional hierarchy by developing a different type of dynamic structure at each layer. The letter examines how model performance during pattern generation, as well as predictive imitation, varies depending on the stage of learning. The number of limit cycle attractors corresponding to target movement patterns increases as learning proceeds. Transient dynamics developing early in the learning process successfully perform pattern generation and predictive imitation tasks. The letter concludes that exploitation of transient dynamics facilitates successful task performance during early learning periods.
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Collins, Tom, Robin Laney, Alistair Willis, and Paul H. Garthwaite. "Modeling Pattern Importance in Chopin's Mazurkas." Music Perception 28, no. 4 (April 1, 2011): 387–414. http://dx.doi.org/10.1525/mp.2011.28.4.387.

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This study relates various quantifiable characteristics of a musical pattern to subjective assessments of a pattern's salience. Via score analysis and listening, twelve music undergraduates examined excerpts taken from Chopin's mazurkas. They were instructed to rate already discovered patterns, giving high ratings to patterns that they thought were noticeable and/or important. Each undergraduate rated thirty specified patterns and ninety patterns were examined in total. Twenty-nine quantifiable attributes (some novel but most proposed previously) were determined for each pattern, such as the number of notes a pattern contained. A model useful for relating participants' ratings to the attributes was determined using variable selection and cross-validation. Individual participants were much poorer than the model at predicting the consensus ratings of other participants. While the favored model contains only three variables, many variables were identified as having some predictive value if considered in isolation. Implications for music psychology, analysis, and information retrieval are discussed.
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Daniel Breslin, Mg Ing Roberto. "ANALYSIS MODEL FOR NON-PREDICTIVE PATTERNS OF NON-IONIZING RADIATIONS." Engineering and Technology Journal 07, no. 12 (December 21, 2022): 1755–68. http://dx.doi.org/10.47191/etj/v7i12.01.

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Non-ionizing radiations have been, and still are, a problem whose approach arouses great social interest, due to its controversial implications for human health and the interest of telecommunications companies in the development and implementation of technologies wireless networks based on the propagation of electromagnetic waves. The recurring question generated from society is related to the possibility that said radiation affects health in some way. The present study is based on the hypothesis that, if there is any degree of affectation, it could be due to an effect found regarding non-predictive patterns of propagation of electromagnetic waves and punctual concentration of radiation in very small areas, generating differentials in the level of density of immission. A field work has been carried out looking for the elements of the urban and suburban environment that facilitate and/or enhance the concentration of radiation at a point and were analyzed with qualitative statistical models with binary logistic regression and association analysis, to develop a prediction pattern. possibility of existence of a point of high density of electromagnetic immersion depending on elements of the environment.
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Ju, Yeong Jo, Jeong Ran Lim, and Euy Sik Jeon. "Prediction of AI-Based Personal Thermal Comfort in a Car Using Machine-Learning Algorithm." Electronics 11, no. 3 (January 23, 2022): 340. http://dx.doi.org/10.3390/electronics11030340.

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Defining a passenger’s thermal comfort in a car cabin is difficult because of the narrow environment and various parameters. Although passenger comfort is predicted using a thermal-comfort scale in the overall cabin or a local area, the scale’s range of passenger comfort may differ owing to psychological factors and individual preferences. Among the many factors affecting such comfort levels, the temperature of the seat is one of the direct and significant environmental factors. Therefore, it is necessary to predict the cabin environment and seat-related personal thermal comfort. Accordingly, machine learning is used in this research to predict whether a passenger’s seat-heating-operation pattern can be predicted in a winter environment. The experiment measures the ambient factor and collects data on passenger heating-operation patterns using a device in an actual winter environment. The temperature is set as the input parameter in the measured data and the operation pattern is used as the output parameter. Based on the parameters, the predictive accuracy of the heating-operation pattern is investigated using machine learning. The algorithms used in the machine-learning train are Tree, SVM, and kNN. In addition, the predictive accuracy is tested using SVM and kNN, which shows a high validation accuracy based on the prediction results of the algorithm. In this research, the parameters predicting the personal thermal comfort of three passengers are investigated as a combination of input parameters, according to the passengers. As a result, the predictive accuracy of the operation pattern according to the tested input parameter is 0.96, showing the highest accuracy. Considering each passenger, the predictive accuracy has a maximum deviation of 30%. However, we verify that it indicates the level of accuracy in predicting a passenger’s heating-operation pattern. Accordingly, the possibility of operating a heating seat without a switch operation is confirmed through machine learning. The primary-stage research result reveals whether it is possible to predict objective personal thermal comfort using the passenger seat’s heating-operation pattern. Based on the results of this research, it is expected to be utilized for system construction based on the AI prediction of operation patterns according to the passenger through machine learning.
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Chien, Wen T., and W. C. Hung. "Investigation on the Predictive Model for Burr in Laser Cutting Titanium Alloy." Materials Science Forum 526 (October 2006): 133–38. http://dx.doi.org/10.4028/www.scientific.net/msf.526.133.

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The purpose of this study is to develop two predictive models for burr height in cutting titanium alloy plates by using Nd:YAG laser. Firstly, Taguchi method has been used to arrange the experimental scheme and analyze the results via analysis of mean . The important laser cutting parameters affecting burr height can be found. It shows that the pressure of assistant gas, the focusing position and the pulsed frequency are the most important cutting parameters in order. Then they have been chosen as the input variables for response surface methodology and used to construct a mathematical equation for predicting burr height. Secondly, the laser cutting parameters and experimental results obtained from conducting the schematic arrangement using Taguchi method and response surface methodology have been treated as training patterns and recalling patterns for the back-propagation neural network. As a result, a predictive model for burr height prediction in laser cutting titanium alloy has been established. To verify the accuracy of above two prediction models, there are 9 sets of experiment have been performed. It shows that the average error for predicting burr height by the mathematical equation derived from response surface methodology is 5.52% and by the predictive model established by back-propagation neural network is 4.51%, respectively. Obviously, both predictive models are good enough for the relational research and practical applications. It can be concluded that the procedure used in this research and the obtaining predictive models can be used practically in correlate industry.
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Ding, Jun, Anthony S. Wexler, and Stuart A. Binder-Macleod. "A predictive model of fatigue in human skeletal muscles." Journal of Applied Physiology 89, no. 4 (October 1, 2000): 1322–32. http://dx.doi.org/10.1152/jappl.2000.89.4.1322.

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Fatigue is a major limitation to the clinical application of functional electrical stimulation. The activation pattern used during electrical stimulation affects force and fatigue. Identifying the activation pattern that produces the greatest force and least fatigue for each patient is, therefore, of great importance. Mathematical models that predict muscle forces and fatigue produced by a wide range of stimulation patterns would facilitate the search for optimal patterns. Previously, we developed a mathematical isometric force model that successfully identified the stimulation patterns that produced the greatest forces from healthy subjects under nonfatigue and fatigue conditions. The present study introduces a four-parameter fatigue model, coupled with the force model that predicts the fatigue induced by different stimulation patterns on different days during isometric contractions. This fatigue model accounted for 90% of the variability in forces produced by different fatigue tests. The predicted forces at the end of fatigue testing differed from those observed by only 9%. This model demonstrates the potential for predicting muscle fatigue in response to a wide range of stimulation patterns.
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Dissertations / Theses on the topic "Predictive Patterns"

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Villaume, Erik. "Predicting customer level risk patterns in non-life insurance." Thesis, KTH, Matematisk statistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103590.

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Several models for predicting future customer profitability early into customer life-cycles in the property and casualty business are constructed and studied. The objective is to model risk at a customer level with input data available early into a private consumer’s lifespan. Two retained models, one using Generalized Linear Model another using a multilayer perceptron, a special form of Artificial Neural Network are evaluated using actual data. Numerical results show that differentiation on estimated future risk is most effective for customers with highest claim frequencies.
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Ferguson, Haylie Anne. "A GIS Approach to Archaeological Settlement Patterns and Predictive Modeling in Chihuahua, Mexico." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7069.

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In this study I analyzed the pattern of settlement for known Medio period (A.D. 1200–1450) sites in the Casas Grandes region of Chihuahua, Mexico. Locational data acquired from survey projects in the Casas Grandes region were evaluated within a Geographic Information Systems (GIS) framework to reveal patterns in settlement and site distribution. Environmental and cultural variables, including aspect, cost distance to nearest ballcourt, ecoregion, elevation, local relief, cost distance to nearest oven, cost distance to Paquimé, slope, soil, terrain texture, topographic position index, cost distance to nearest trincheras, vegetation, vegetation variety to 100 meters, vegetation variety to 500 meters, cost distance to nearest intermittent lake, cost distance to nearest intermittent stream, cost distance to nearest perennial lake, and cost distance to nearest perennial stream were calculated for each site in this region. It was expected that the relationships of correspondence between known sites and these variables would provide a quantitative framework that could be used to model the locational probability of unknown sites in the region. Through the use of GIS and statistical analyses, the results of this study were used to produce an archaeological site sensitivity map for this region of northern Mexico.
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Ferguson, Megan Caton. "Cetacean population density in the Eastern Pacific Ocean : analyzing patterns with predictive spatial models /." Online version in PDF format, 2005. http://swfsc.noaa.gov/uploadedFiles/Divisions/PRD/Programs/Coastal_Marine_Mammal/Ferguson2005dissertation.pdf.

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Thesis (Ph. D.)--University of California, San Diego, 2005.
Vita. Includes bibliographical references. Also available online in PDF format via the National Marine Fisheries Service Coastal Marine Mammal Program (CMMP) home page.
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Daughtrey, Cannon Stewart. "Pima County's Open Space Ranch Preserves: Predictive Modeling of Site Locations for Three Time Periods at Rancho Seco." Thesis, The University of Arizona, 2014. http://hdl.handle.net/10150/318809.

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The initiatives of open space conservation, as outlined in the Sonoran Desert Conservation Plan, have been implemented through the purchase of nearly 65 thousand acres by Pima County. This land abuts sections of grazing leases held by state and federal agencies, forming largely unfragmented landscapes surrounding the city's urban core. Much of the outlying acreage is rural historic working ranches, now managed as open space conservation preserves. Ranches are landscapes of low-intensity impact, where the archaeological record of centuries of human land use is well preserved. Much of the land, however, remains relatively unstudied. To refine spatial predictions of archaeologically sensitive areas in southern Pima County, I use multivariate logistic regression to develop predictive models of probable archaeological site locations for three time periods at Rancho Seco as a case study. Results suggest portions Rancho Seco might contain additional Preceramic and Historic cultural resources but additional data collection is needed.
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Brownlow, Briana Nicole. "Patterns of Heart Rate Variability Predictive of Internalizing Symptoms in a Non-Clinical Youth Sample." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1518179804584445.

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Beam, Lauren. "Are holding patterns predictive of infant attachment classification in 12 to 18 month old infants?" Click here to access thesis, 2009. http://www.georgiasouthern.edu/etd/archive/spring2009/lauren_d_beam/beam_lauren_d_200905_ms.pdf.

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Thesis (M.S.)--Georgia Southern University, 2009.
"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Science." Directed by Janice Kennedy. ETD. Includes bibliographical references (p. 54-61) and appendices.
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Castillo, Guevara Ramon Daniel. "The emergence of cognitive patterns in learning: Implementation of an ecodynamic approach." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396531855.

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Saha, Sourabh Kumar. "Predictive design and fabrication of complex micro and nano patterns via wrinkling for scalable and affordable manufacturing." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/93860.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 189-193).
There is a demonstrated need for scalable and affordable manufacturing of complex micro and nano scale structures for applications such as fluidics-based medical diagnostics and photonicsbased sensing. Although high-rate patterning of these structures is feasible via template/stamp based processes, scalability and affordability are often limited by expensive and slow template fabrication processes. The purpose of this work was to develop a wrinkling-based manufacturing process that eliminates the need for an expensive and slow template fabrication step. Wrinkling of thin films is a low-cost buckling-driven patterning process that provides an alternate route to manufacturing scale-up. However, this process is currently of limited practical import because predictive design is restricted to a small set of simple/elementary patterns. In this work, predictive models, tools, and techniques were developed to enable the design and fabrication of a variety of complex wrinkled patterns. The shape and size of wrinkled patterns is determined by the interaction among geometry, material properties, and loading. Complexity in wrinkle patterns often arises due to uncontrolled/undesirable non-uniformities in these process parameters. Due to the confounding effect of simultaneously acting non-uniformities, it is difficult to link wrinkle shape/size to process parameters for such systems. To solve this problem, experimental and computational tools were developed to (i) individually tune/control the non-uniformities in these parameters and (ii) probe the effect of these parameters on the wrinkled pattern. The data generated from these tools was then used to link process parameters to pattern complexity. Contributions were made in the following specific areas: (1) Tunable hierarchical wrinkled patterns via geometric pre-patterning Although complex hierarchical wrinkled patterns have been fabricated via geometric prepatterning in the past, predictive design of such patterns is not feasible. This is primarily because of lack of appropriate process models that can accurately capture the physical effect of prepatterns on the wrinkle generation process. Herein, an analytical model was developed and verified to predict the hierarchical patterns that arise due to geometric non-uniformity. This model elucidates and captures the fundamental energetic response of the system to pre-patterns that distinguishes a pre-patterned system from a flat non-patterned system. The ability to capture this essential physics provides valuable insight into the process that is not available via empirical models that are based on a limited data set. This insight enables one to (i) explore the full design space and identify optimal operating regions, (ii) design and fabricate tunable wrinkled patterns that can be deterministically switched across hierarchical and non-hierarchical states and (iii) explain and predict patterns that are theoretically feasible yet practically inaccessible. (2) Period doubling via high compressive strains Although period doubling at high compressive strains has been demonstrated in the past, models that accurately predict the onset of period doubling are not available. This is due to the inability of existing models to capture the nonlinear stress versus strain material response as the physical basis for period doubling. For example, existing models erroneously assume that the onset of period doubling is independent of stiffness moduli. Herein, models driven by finite element analysis were developed to accurately link the onset of period doubling to nonlinearities that arise during large deformations. These models enable one to accurately separate the effect of individual process parameters on the onset of period doubling. This enables one to extract valuable process-relevant information from the observation of the period doubling phenomenon that is otherwise not available. (3) Attractors and repellers as localized material defects for curved wrinkles Curved wrinkles have been demonstrated in the past during equibiaxial compression of nonuniform materials. However, predictive design of target patterns via curved wrinkles is not feasible at present due to the lack of simple yet effective design rules. Generation of such design rules is hindered by the confounding effect of biaxial compression and localized material nonuniformities. Herein, an elegant design rule for in-plane bending of wrinkles has been generated for the case of uniaxial compression. Based on this, the concept of attractors and repellers as distinct localized material defects has been proposed and experimentally verified. Attractors are relatively compliant defects that pull wrinkles toward them; whereas repellers are relatively stiffer defects that push wrinkles away. These defects may be used as the building blocks to locally alter the in-plane orientation of otherwise uniformly aligned wrinkles during uniaxial compression. The set of predictive models generated in this work would enable a designer to perform inverse pattern design of complex wrinkled structures, i.e., to select the appropriate set of process parameters that are required to fabricate the desired pattern. By replacing other expensive processes for complex patterning, this would reduce the time and cost of manufacturing a variety of functional micro and nano scale patterns by a factor of ~10 for low-volume applications and by ~10% for high-volume applications.
by Sourabh Kumar Saha.
Ph. D.
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Burton, A. Kim. "Patterns of lumbar sagittal mobility and their predictive value in the natural history of back and sciatic pain." Thesis, University of Huddersfield, 1987. http://eprints.hud.ac.uk/id/eprint/8663/.

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Chhaya, Mohamed. "Traditional and modern medicine in primary care - prevalence, patterns and predictive factors of utilisation in Makwarela township, Vhembe district, Limpopo." Thesis, Stellenbosch : University of Stellenbosch, 2015. http://hdl.handle.net/10019.1/97229.

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C. ABSTRACT Introduction: Medical pluralism is a worldwide phenomenon. The reality in South Africa is that healthcare is provided by both orthodox and traditional healthcare providers. There is a great reliance on traditional medicine (TM) especially in rural communities. The complex interplay between patient centeredness and empowerment, health economics, failure of the biomedical approach and many other factors has resulted in an increasing prevalence of medical pluralism. Aim: The aim of the study was to explore the existence and extent of medical pluralism in my practice population, to quantify the prevalence of use and to qualify the determinants of choice. Methods: A cross sectional community household survey was conducted in the Makwarela Township of the Thulamela municipality (which forms part of the Vhembe district in the Limpopo Province in South Africa) using systematic sampling based on interval numbers. Interviewer administered questionnaires were used to obtain information from 65 households. Information was collected regarding the dependent variables (illness episodes, consultation behaviour, choice of primary health care provider) and the independent variables (socio-demographics, characteristics of illness, characteristics of health services). These were then analysed to assess prevalence of use and to elucidate significant associations. Results: Only 48 households representing 73,8% of the sample agreed to be interviewed. The total household members numbered 242. There were 364 illness episodes experienced by the household members in the 6 months prior to the survey. The ever use of TM in the sample was 70,8% (57,9% - 83,7%, 95% CI), whereas the ever use of orthodox medicine was 100%. The percentage of respondents who feel that they would probably use TM in future was 50%. The only significant correlates of TM use were highest education, household size, health belief model, waiting times at OM practitioner and past utilisation of TM. Conclusion: The study confirms the hypothesis of the existence of a pluralistic primary healthcare system and high prevalence of use of TM in the sample. The pattern of use of TM is that of an adjunct rather than as exclusive therapy. The study also confirms the complex interplay of a myriad of factors in healthcare choice. Despite the limitations of the study it can serve as a preliminary investigation prompting further studies to elucidate healthcare utilisation in the province and nationally. There are many ensuing implications for healthcare providers, funders and health system planners.
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Books on the topic "Predictive Patterns"

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Leenaars, Antoon A. Suicide notes: Predictive clues and patterns. New York, N.Y: Human Sciences Press, 1988.

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G, Moore Donald, and Geological Survey (U.S.), eds. Predictive spatial modeling of narcotic crop growth patterns. Sioux Falls, S.D: U.S. Dept. of the Interior, U.S. Geological Survey, 1986.

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G, Moore Donald, and Geological Survey (U.S.), eds. Predictive spatial modeling of narcotic crop growth patterns. Sioux Falls, S.D: U.S. Dept. of the Interior, U.S. Geological Survey, 1986.

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Bartlett, Sheryl Anne. Predictive and posterior distributions for normal multivariate data with missing monotone patterns. Toronto: University of Toronto, Dept. of Statistics, 1985.

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G, Anderson David. Archaeology, history, and predictive modeling research at Fort Polk, 1972-2002. Tuscaloosa: University of Alabama Press, 2003.

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Dietrich, Daniel S. Predicting radiation characteristics from antenna physical dimensions. Monterey, Calif: Naval Postgraduate School, 1992.

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Tremblay, Pierre. Patterns in criminal achievement: Wilson and Abrahamse revisited. Montréal: Université de Montréal, 1999.

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1939-, Wyss Max, Shimazaki K. 1946-, and Ito Akihiko, eds. Seismicity patterns, their statistical significance and physical meaning. Basel: Birkhäuser Verlag, 1999.

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Lundholm, Steven E. Predicting antenna parameters from antenna physical dimensions. Monterey, Calif: Naval Postgraduate School, 1993.

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Pham, Duc Truong. Neural Networks for Identification, Prediction and Control. London: Springer London, 1995.

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Book chapters on the topic "Predictive Patterns"

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Zettersten, Martin. "Learning by predicting: How predictive processing informs language development." In Patterns in Language and Linguistics, edited by Beatrix Busse and Ruth Moehlig-Falke, 255–88. Berlin, Boston: De Gruyter, 2019. http://dx.doi.org/10.1515/9783110596656-010.

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Hannachi, Abdelwaheb. "Persistent, Predictive and Interpolated Patterns." In Springer Atmospheric Sciences, 171–200. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67073-3_8.

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Lv, Tao, and Yongtao Hao. "Further Analysis of Candlestick Patterns’ Predictive Power." In Communications in Computer and Information Science, 73–87. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6385-5_7.

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Finkelstein, Martin, and Wendiann Sethi. "Patterns of Faculty Internationalization: A Predictive Model." In The Internationalization of the Academy, 237–57. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7278-6_11.

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Mihelčić, Matej, Sašo Džeroski, Nada Lavrač, and Tomislav Šmuc. "Redescription Mining with Multi-target Predictive Clustering Trees." In New Frontiers in Mining Complex Patterns, 125–43. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39315-5_9.

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Shen, Cheng-Dong, Tie-Jun Li, and Si-Kun Li. "A Predictive Direction Guided Fast Motion Estimation Algorithm." In Computer Analysis of Images and Patterns, 188–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11556121_24.

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Torim, Ants, Innar Liiv, Chahinez Ounoughi, and Sadok Ben Yahia. "Pattern Based Software Architecture for Predictive Maintenance." In Communications in Computer and Information Science, 26–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17030-0_3.

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AbstractMany industrial sectors are moving toward Industry Revolution (IR) 4.0. In this respect, the Internet of Things and predictive maintenance are considered the key pillars of IR 4.0. Predictive maintenance is one of the hottest trends in manufacturing where maintenance work occurs according to continuous monitoring using a healthiness check for processing equipment or instrumentation. It enables the maintenance team to have an advanced prediction of failures and allows the team to undertake timely corrective actions and decisions ahead of time. The aim of this paper is to present a smart monitoring and diagnostics system as an expert system that can alert an operator before equipment failures to prevent material and environmental damages. The main novelty and contribution of this paper is a flexible architecture of the predictive maintenance system, based on software patterns - flexible solutions to general problems. The presented conceptual model enables the integration of an expert knowledge of anticipated failures and the matrix-profile technique based anomaly detection. The results so far are encouraging.
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Nowosielski, Adam. "Two-Letters-Key Keyboard for Predictive Touchless Typing with Head Movements." In Computer Analysis of Images and Patterns, 68–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64689-3_6.

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Pourbafrani, Mahsa, Shreya Kar, Sebastian Kaiser, and Wil M. P. van der Aalst. "Remaining Time Prediction for Processes with Inter-case Dynamics." In Lecture Notes in Business Information Processing, 140–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98581-3_11.

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AbstractProcess mining techniques use event data to describe business processes, where the provided insights are used for predicting processes’ future states (Predictive Process Monitoring). Remaining Time Prediction of process instances is an important task in the field of Predictive Process Monitoring (PPM). Existing approaches have two key limitations in developing Remaining Time Prediction Models (RTM): (1) The features used for predictions lack process context, and the created models are black-boxes. (2) The process instances are considered to be in isolation, despite the fact that process states, e.g., the number of running instances, influence the remaining time of a single process instance. Recent approaches improve the quality of RTMs by utilizing process context related to batching-at-end inter-case dynamics in the process, e.g., using the time to batching as a feature. We propose an approach that decreases the previous approaches’ reliance on user knowledge for discovering fine-grained process behavior. Furthermore, we enrich our RTMs with the extracted features for multiple performance patterns (caused by inter-case dynamics), which increases the interpretability of models. We assess our proposed remaining time prediction method using two real-world event logs. Incorporating the created inter-case features into RTMs results in more accurate and interpretable predictions.
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Leibovitz, Rotem, Jhonathan Osin, Lior Wolf, Guy Gurevitch, and Talma Hendler. "fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits." In Lecture Notes in Computer Science, 282–94. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16431-6_27.

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Conference papers on the topic "Predictive Patterns"

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Ibrahim, Ronny K., Eliathamby Ambikairajah, Branko G. Celler, and Nigel H. Lovell. "Linear predictive modelling of gait patterns." In ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/icassp.2009.4959611.

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Athineos, Marios, Hynek Hermansky, and Daniel P. W. Ellis. "LP-TRAP: linear predictive temporal patterns." In Interspeech 2004. ISCA: ISCA, 2004. http://dx.doi.org/10.21437/interspeech.2004-344.

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Ortu, Marco, Tracy Hall, Michele Marchesi, Roberto Tonelli, David Bowes, and Giuseppe Destefanis. "Mining Communication Patterns in Software Development." In PROMISE'18: The 14th International Conference on Predictive Models and Data Analytics in Software Engineering. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3273934.3273943.

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Dey, Tapajit, Yuxing Ma, and Audris Mockus. "Patterns of Effort Contribution and Demand and User Classification based on Participation Patterns in NPM Ecosystem." In PROMISE'19: The Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3345629.3345634.

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Roor, Roman, Michael Karg, Andy Liao, Wenhui Lei, and Alexandra Kirsch. "Predictive ridesharing based on personal mobility patterns." In 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2017. http://dx.doi.org/10.1109/ivs.2017.7995895.

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Batal, Iyad, and Milos Hauskrecht. "Constructing classification features using minimal predictive patterns." In the 19th ACM international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1871437.1871549.

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Chitu, Claudia, Mokhloss I. Khadem, and Valentin Sgarciu. "Predictive modeling of occupancy patterns in smart buildings." In 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2017. http://dx.doi.org/10.1109/idaacs.2017.8095167.

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Park, Eunjung, Christos Kartsaklis, and John Cavazos. "HERCULES: Strong Patterns towards More Intelligent Predictive Modeling." In 2014 43nd International Conference on Parallel Processing (ICPP). IEEE, 2014. http://dx.doi.org/10.1109/icpp.2014.26.

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Krah, Jens Onno, Tobias Schmidt, and Joachim Holtz. "Predictive Current Control with Synchronous Optimal Pulse Patterns." In 2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE). IEEE, 2019. http://dx.doi.org/10.1109/sgre46976.2019.9021105.

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Zhang, Wenjing, and Xin Feng. "Predictive temporal patterns detection in multivariate dynamic data system." In 2012 10th World Congress on Intelligent Control and Automation (WCICA 2012). IEEE, 2012. http://dx.doi.org/10.1109/wcica.2012.6357988.

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Reports on the topic "Predictive Patterns"

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Shaw, J., D. R. Sharpe, J. Harris, D. Lemkow, and D. Pehleman. Digital landform patterns for glaciated regions of Canada - a predictive model of flowlines based on topographic and LANDSAT 7 data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2010. http://dx.doi.org/10.4095/286248.

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Brodie, Katherine, Ian Conery, Nicholas Cohn, Nicholas Spore, and Margaret Palmsten. Spatial variability of coastal foredune evolution, part A : timescales of months to years. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41322.

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Coastal foredunes are topographically high features that can reduce vulnerability to storm-related flooding hazards. While the dominant aeolian, hydrodynamic, and ecological processes leading to dune growth and erosion are fairly well-understood, predictive capabilities of spatial variations in dune evolution on management and engineering timescales (days to years) remain relatively poor. In this work, monthly high-resolution terrestrial lidar scans were used to quantify topographic and vegetation changes over a 2.5 year period along a micro-tidal intermediate beach and dune. Three-dimensional topographic changes to the coastal landscape were used to investigate the relative importance of environmental, ecological, and morphological factors in controlling spatial and temporal variability in foredune growth patterns at two 50 m alongshore stretches of coast. Despite being separated by only 700 m in the alongshore, the two sites evolved differently over the study period. The northern dune retreated landward and lost volume, whereas the southern dune prograded and vertically accreted. The largest differences in dune response between the two sections of dunes occurred during the fall storm season, when each of the systems’ geomorphic and ecological properties modulated dune growth patterns. These findings highlight the complex eco-morphodynamic feedback controlling dune dynamics across a range of spatial scales.
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Jaroszewicz, Thomas, Elizabeth Bleszynski, Marek Bleszynski, and Vladimir Rokhlin. Advanced Antenna Pattern Prediction Software. Fort Belvoir, VA: Defense Technical Information Center, May 2006. http://dx.doi.org/10.21236/ada452136.

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Peterson, P. F., and I. K. Paik. MODFLOW 2.0: A program for predicting moderator flow patterns. Office of Scientific and Technical Information (OSTI), July 1991. http://dx.doi.org/10.2172/10158938.

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Jai, Tun-Min (Catherine). Predicting Consumers' Apparel Purchase Decisions from Brain Activity Patterns. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-377.

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Peterson, P. F., and I. K. Paik. MODFLOW 2. 0: A program for predicting moderator flow patterns. Office of Scientific and Technical Information (OSTI), July 1991. http://dx.doi.org/10.2172/5112906.

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Apiyo, Eric, Zita Ekeocha, Stephen Robert Byrn, and Kari L. Clase. Improving Pharmacovigilliance Quality Management System in the Pharmacy and Poisions Board of Kenya. Purdue University, December 2021. http://dx.doi.org/10.5703/1288284317444.

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The purpose of this study was to explore ways of improving the pharmacovigilance quality system employed by the Pharmacy and Poisons Board of Kenya. The Pharmacy and Poisons Board of Kenya employs a hybrid system of pharmacovigilance that utilizes an online system of reporting pharmacovigilance incidences and a physical system, where a yellow book is physically filled by the healthcare worker and sent to the Pharmacy and Poisons Board for onward processing. This system, even though it has been relatively effective compared to other systems employed in Africa, has one major flaw. It is a slow and delayed system that captures the data much later after the fact and the agency will always be behind the curve in controlling the adverse incidents and events. This means that the incidences might continue to arise or go out of control. This project attempts to develop a system that would be more proactive in the collection of pharmacovigilance data and more predictive of pharmacovigilance incidences. The pharmacovigilance system should have the capacity to detect and analyze subtle changes in reporting frequencies and in patterns of clinical symptoms and signs that are reported as suspected adverse drug reactions. The method involved carrying out a thorough literature review of the latest trends in pharmacovigilance employed by different regulatory agencies across the world, especially the more stringent regulatory authorities. A review of the system employed by the Pharmacy and Poisons Board of Kenya was also done. Pharmacovigilance data, both primary and secondary, were collected and reviewed. Media reports on adverse drug reactions and poor-quality medicines over the period were also collected and reviewed. An appropriate predictive pharmacovigilance tool was also researched and identified. It was found that the Pharmacy and Poisons Board had a robust system of collecting historical pharmacovigilance data both from the healthcare workers and the general public. However, a more responsive data collection and evaluation system is proposed that will help the agency achieve its pharmacovigilance objectives. On analysis of the data it was found that just above half of all the product complaints, about 55%, involved poor quality medicines; 15% poor performance, 13% presentation, 8% adverse drug reactions, 7% market authorization, 2% expired drugs and 1% adulteration complaints. A regulatory pharmacovigilance prioritization tool was identified, employing a risk impact analysis was proposed for regulatory action.
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Wideman, Jr., Robert F., Nicholas B. Anthony, Avigdor Cahaner, Alan Shlosberg, Michel Bellaiche, and William B. Roush. Integrated Approach to Evaluating Inherited Predictors of Resistance to Pulmonary Hypertension Syndrome (Ascites) in Fast Growing Broiler Chickens. United States Department of Agriculture, December 2000. http://dx.doi.org/10.32747/2000.7575287.bard.

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Background PHS (pulmonary hypertension syndrome, ascites syndrome) is a serious cause of loss in the broiler industry, and is a prime example of an undesirable side effect of successful genetic development that may be deleteriously manifested by factors in the environment of growing broilers. Basically, continuous and pinpointed selection for rapid growth in broilers has led to higher oxygen demand and consequently to more frequent manifestation of an inherent potential cardiopulmonary incapability to sufficiently oxygenate the arterial blood. The multifaceted causes and modifiers of PHS make research into finding solutions to the syndrome a complex and multi threaded challenge. This research used several directions to better understand the development of PHS and to probe possible means of achieving a goal of monitoring and increasing resistance to the syndrome. Research Objectives (1) To evaluate the growth dynamics of individuals within breeding stocks and their correlation with individual susceptibility or resistance to PHS; (2) To compile data on diagnostic indices found in this work to be predictive for PHS, during exposure to experimental protocols known to trigger PHS; (3) To conduct detailed physiological evaluations of cardiopulmonary function in broilers; (4) To compile data on growth dynamics and other diagnostic indices in existing lines selected for susceptibility or resistance to PHS; (5) To integrate growth dynamics and other diagnostic data within appropriate statistical procedures to provide geneticists with predictive indices that characterize resistance or susceptibility to PHS. Revisions In the first year, the US team acquired the costly Peckode weigh platform / individual bird I.D. system that was to provide the continuous (several times each day), automated weighing of birds, for a comprehensive monitoring of growth dynamics. However, data generated were found to be inaccurate and irreproducible, so making its use implausible. Henceforth, weighing was manual, this highly labor intensive work precluding some of the original objectives of using such a strategy of growth dynamics in selection procedures involving thousands of birds. Major conclusions, solutions, achievements 1. Healthy broilers were found to have greater oscillations in growth velocity and acceleration than PHS susceptible birds. This proved the scientific validity of our original hypothesis that such differences occur. 2. Growth rate in the first week is higher in PHS-susceptible than in PHS-resistant chicks. Artificial neural network accurately distinguished differences between the two groups based on growth patterns in this period. 3. In the US, the unilateral pulmonary occlusion technique was used in collaboration with a major broiler breeding company to create a commercial broiler line that is highly resistant to PHS induced by fast growth and low ambient temperatures. 4. In Israel, lines were obtained by genetic selection on PHS mortality after cold exposure in a dam-line population comprising of 85 sire families. The wide range of PHS incidence per family (0-50%), high heritability (about 0.6), and the results in cold challenged progeny, suggested a highly effective and relatively easy means for selection for PHS resistance 5. The best minimally-invasive diagnostic indices for prediction of PHS resistance were found to be oximetry, hematocrit values, heart rate and electrocardiographic (ECG) lead II waves. Some differences in results were found between the US and Israeli teams, probably reflecting genetic differences in the broiler strains used in the two countries. For instance the US team found the S wave amplitude to predict PHS susceptibility well, whereas the Israeli team found the P wave amplitude to be a better valid predictor. 6. Comprehensive physiological studies further increased knowledge on the development of PHS cardiopulmonary characteristics of pre-ascitic birds, pulmonary arterial wedge pressures, hypotension/kidney response, pulmonary hemodynamic responses to vasoactive mediators were all examined in depth. Implications, scientific and agricultural Substantial progress has been made in understanding the genetic and environmental factors involved in PHS, and their interaction. The two teams each successfully developed different selection programs, by surgical means and by divergent selection under cold challenge. Monitoring of the progress and success of the programs was done be using the in-depth estimations that this research engendered on the reliability and value of non-invasive predictive parameters. These findings helped corroborate the validity of practical means to improve PHT resistance by research-based programs of selection.
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Peterson, P. F., and I. K. Paik. Code requirements document: MODFLOW 2.1: A program for predicting moderator flow patterns. Office of Scientific and Technical Information (OSTI), March 1992. http://dx.doi.org/10.2172/10169804.

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McKenzie, Donald, David L. Peterson, and Ernesto Alvarado. Predicting the effect of fire on large-scale vegetation patterns in North America. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1996. http://dx.doi.org/10.2737/pnw-rp-489.

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