Logic Filter Research Articles

Determining the Type and Starting Time of Land Cover and Land Use Change in Southern Ghana Based on Discrete Analysis of Dense Landsat Image Time Series

Rural to urban migration and relatively high fertility rates have influenced rapid land cover and land use change (LCLUC) in southern Ghana, which warrants more frequent monitoring. We develop and test approaches for semiautomatically and more frequently identifying the type and date of LCLUC from time series of Landsat ETM+ imagery from 2000 to 2014. Clouds, cloud shadows, and scan line corrector-off create missing data in $\text{ETM}+$ images. Forty-one dates of $\text{ETM}+$ images that partially contain missing data were utilized. The general approach is to conduct a per-pixel supervised classification on each image of a Landsat time series after masking missing data. Spatial, temporal, and logical filters are applied to correct for misclassification and missing data. Each image is classified into three general classes: 1) Built; 2) Natural Vegetation; 3) and Agriculture, with expansion of Built being our main focus. Reference data for Change-to-Built were independently selected from all available high-spatial resolution satellite images (e.g., Quickbird, GeoEye, Worldview, and Google Earth imagery), and the type and beginning time of LCLUC was recorded. Results show that the temporal-filtered product identified both the location and the start of Change-to-Built more precisely and accurately than the nonfiltered and other filtered products. Based on reference data, 40% of the Change-to-Built samples were correctly identified without filtering; whereas, when a temporal filter was applied, 80% were correctly identified with low amounts of false positive Change-to-Built pixels. The temporal-filtered product has the highest temporal precision and accuracy ( $\text{mean time difference} = 2.1 \text{years}$ ) in identifying the start of Change-to-Built.

A Methodology for Investigating Public Opinion Using Multilevel Text Analysis

Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions. Keywords—Big data, social network analysis, text mining, topic modeling.

Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments

Abstract. The ability of a fuzzy logic classifier to dynamically identify non-meteorological radar echoes is demonstrated using data from the National Centre for Atmospheric Science dual polarisation, Doppler, X-band mobile radar. Dynamic filtering of radar echoes is required due to the variable presence of spurious targets, which can include insects, ground clutter and background noise. The fuzzy logic classifier described here uses novel multi-vertex membership functions which allow a range of distributions to be incorporated into the final decision. These membership functions are derived using empirical observations, from a subset of the available radar data. The classifier incorporates a threshold of certainty (25 % of the total possible membership score) into the final fractional defuzzification to improve the reliability of the results. It is shown that the addition of linear texture fields, specifically the texture of the cross-correlation coefficient, differential phase shift and differential reflectivity, to the classifier along with standard dual polarisation radar moments enhances the ability of the fuzzy classifier to identify multiple features. Examples from the Convective Precipitation Experiment (COPE) show the ability of the filter to identify insects (18 August 2013) and ground clutter in the presence of precipitation (17 August 2013). Medium-duration rainfall accumulations across the whole of the COPE campaign show the benefit of applying the filter prior to making quantitative precipitation estimates. A second deployment at a second field site (Burn Airfield, 6 October 2014) shows the applicability of the method to multiple locations, with small echo features, including power lines and cooling towers, being successfully identified by the classifier without modification of the membership functions from the previous deployment. The fuzzy logic filter described can also be run in near real time, with a delay of less than 1 min, allowing its use on future field campaigns.

텍스트 분석을 활용한 과학기술이슈 여론 분석 방법론

Recently, many users frequently share their opinions on diverse issues using various social media. Therefore, many governments have attempted to establish or improve national policies according to the public opinions captured from the various social media. In this paper, we indicate several limitations of traditional approaches for analyzing public opinions about science and technology and provide an alternative methodology to overcome the limitations. First of all, we distinguish science and technology analysis phase and social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we apply a start list and a stop list successively to acquire clarified and interesting results. Finally, to identify most appropriate documents fitting to a given subject, we develop a new concept of logical filter that consists of not only mere keywords but also a logical relationship among keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discovering core issues and public opinions from 1,700,886 documents comprising SNS, blog, news, and discussion.

Practical Modeling: Making the Invisible Visible

EDITOR'S SUMMARYA fundamental part of information architecture is translating rough ideas through language to a set of organized relationships, understandable to all stakeholders. Modeling information helps visualize the problem to be addressed en route to finding a solution. The process may be complex, iterative and time consuming but necessary to transition from a vague idea to a final implementation. Modeling takes place throughout a project to facilitate analysis of the problem being addressed. It helps clarify relationships and ideas without moving too quickly to specifics, like bubble diagrams of spatial relationships that evolve in phases into detailed architectural drawings. Modeling captures assumptions, even if unstated and invisible, and it can take multiple forms as it progresses to support clear navigation, logical filters and effective discovery.

Develop a multi-detection security system using multi-sensor fusion algorithms

The paper develops the multi-detection system using multi-level surveillance structure. The system contains active detection modules, passive detection modules, a supervised computer, an image system and an intelligent home. The passive detection modules contain wire/wireless detection modules and appliance control modules, and decide the event to be true or not using fusion algorithms, and transmit detection signals to the supervised computer via wire/wireless interface. Mobile robots are active detection modules and carry various sensors to search dangerous events. Each mobile robot transmits the real-time event signal to the supervised computer and the other mobile robots via wireless RF interface. The image system detects fire source using Otsu algorithm. The system integrates wire/wireless passive detection modules, mobile robots and image system to detect fire source using weighted average method. If the fire event occurs, the supervised computer calculates the dangerous grade using logical filter method according to the signals of detection modules in the first step, and transmits the position of the fire event to the other mobile robots. The assigned mobile robots move to the event location for double check autonomously, and transmit the detection results to the supervised computer. The supervised computer gives the final decision according to the feedback signals in the second step. Finally, we present some experimental scenarios using passive detection modules, active detection modules and image system for the fire detection in the intelligent home.

Digital processing methods of images and signals in electromagnetic infiltration process

Abstract The article contains information about the capabilities of electromagnetic infiltration process in case of occurrence of strong interfering signals. As a methods supporting infiltration process used method of digital processing of signals and images in the form of histogram transformations, global and local thresholding of signal amplitudes and logical filters. The material presented in the article shows that risk can arise if the uncontrolled use of the computer. Risks that could decide our safety and security of our data. obtained images. Manipulation of histograms, threshold amplitudes of the emission signal correlated with the classified signals or logical filters highlight the weakness of the security used at the source. The presence of strong interfering signals such as vertical and horizontal synchronization signals blocking measurement receivers, do not prevent the reproduction of classified information. Opportunities of the electromagnetic infiltration in situations of weak compromising emissions occurs are presented in the article.

An object-based analysis filtering algorithm for airborne laser scanning

Ground filtering is a key process to derive digital terrain models from airborne laser scanning data. Although many methods have been developed to tackle the filtering problem, it has not been fully solved so far. Current algorithms mainly focus on neighbourhood-based or directional filtering approaches. A new object-based analysis (OBA) method is proposed in this article. First, a grid index algorithm accelerates access to unorganized cloud points. Then, a segmentation algorithm is deployed based on the index, and objects are obtained. A filtering logic that utilizes the objects' characteristics is designed. Following this, the performance of the method is comprehensively tested using publicly available International Society for Photogrammetry and Remote Sensing (ISPRS) test data sets for nine urban and six rural regions, and the results are compared to those of eight other algorithms. The OBA method implemented in this article reveals good results without scene-wise optimization of the parameters, and it ranks third or fourth in most of the cases.

Control synthesis based on logical constraints for safe manufacturing systems

Abstract This paper presents an original approach of safe control synthesis of manufacturing systems. This approach is based on the use of a logic filter (placed at the end of PLC (Programmable Logic Controller)) robust to control errors, and formally validated using a model checker. The proposed approach, which separates the functional control part from the safety control part, is simple to implement and ensures that the designed controller is safe. The methodology is based on the use of safety constraints coming from the filter in order to get the most permissive safe controller. This controller is then constrained by functional constraints. The approach is illustrated by using an example of sorting boxes simulated using the ITS PLC software from the Real Games company ( www.realgames.pt ). The control algorithm is presented and allows to result in a safe control, may be simpler than a conventional approach based on a specification in GRAFCET (IEC 60848), that does not distinguish the functional aspect from the safety aspect. This approach involves a new way to see the control of manufacturing systems and presents interesting perspectives like the management of several operating modes.

Safe control synthesis based on Boolean constraints for manufacturing systems

This paper presents an original approach of safe control synthesis of manufacturing systems. This is an extension of the work that CReSTIC has led for several years on the definition and design of a logic filter (placed into a Programmable Logic Controller (PLC)) robust to control errors, and formally verified using a model checker. The proposed approach, which separates the functional control part from the safety control part, is simple to implement and ensures that the designed controller is safe. The methodology is based on the use of safety constraints coming from the filter in order to get the most permissive safe controller. This controller is then constrained by functional constraints. The approach is illustrated by using an example of sorting boxes simulated using the ITS PLC software from the Real Games company (www.realgames.pt). The control algorithm is presented and allows to result in a safe control, may be simpler than a conventional approach based on a specification in GRAFCET (IEC 60848), that does not distinguish the functional aspect from the safety aspect. This approach presents interesting perspectives like the management of several operating modes.

Multisensor fusion-based gas detection module

This article develops a gas detection module for the intelligent home. The module uses eight gas sensors to detect the environment of the home and building. The gas sensors of the module have an NH3 sensor, an air pollution sensor, an alcohol sensor, an HS sensor, a smoke sensor, a CO sensor, an LPG sensor, and a natural gas sensor, and can classify more than eight types of gas using multisensor fusion algorithms. In the logical filter method, either AND or OR filters can be implemented in the gas detection module. Then we can calculate the system's reliability using the AND and OR filters, and classify the type of gas in the environment. The controller of the gas detection module is a HOLTEK microchip. The module can communicate with the supervised computer via a wire interface or a wireless RF interface, and can caution the user via a voice module. Finally, we present some experimental results to measure unknown gases using the gas detection module on the security system of an intelligent building and home.

Invariants with new indexing functions: Application to welding panel recognition

Many lines in a typical cluttered image incur a size explosion when invariants from every combination of the extracted lines are calculated. To solve this problem, we propose a new method of reducing the search space by introducing not only a line convex hull (LCH) but also an indexing logic filter (ILF). The LCH arranges five lines in a unique order and classifies a set of five lines into topological types. The ILF produces an integer indexing key from the acquired LCHs. The LCH and ILF are incorporated into a hierarchical database so that the model features can be retrieved efficiently. We achieved satisfactory results for synthetic welding panels used in shipbuilding.

Stability Conditions of Fuzzy Filter Type III

A digital fuzzy logic filter of type III interacts with a real model signal reference to obtain the best answer in the sense of minimum mean square error of the output. The key part of the filter is a fuzzy mechanism that adaptively selects and emits answer according to the changes of the external reference signal. Based on input signal level, this fuzzy filter selects the best parameter values from a set of membership in the knowledge base (KB), and the filter weights are updated according to the reference signal in a natural form. With this fuzzy structure the filter reduces error. The simulation result shows the stability of the filter. The states of the filtering process require that all of its answers are bounded by the error criteria probabilistically.

Reconstruction with criterion from labeled markers: new approach based on the morphological watershed

The goal of image segmentation is to partition an input image into a set of regions. In mathematical morphology, the recon- struction of images from markers has proven to be useful in morpho- logical filtering and image segmentation. The utilization of a criterion in the problem of the image reconstruction from an image marker has been partially treated elsewhere. We further investigate this idea and extend it to the problem of image reconstruction from labeled markers by proposing a new method based on the transforma- tion as an alternative in image segmentation. The image gradient is considered as a topographic relief that is flooded (similarly as in a nor- mal watershed). However, a criterion is added in this reconstruction process that enables the flexibility to separate structures of interest. Following the flooding analogy on topographic reliefs, this flooding process is limited to certain zones to control the recovering process of structures shapes. Experimental results are provided. A compar- ison with a viscous watershed is performed to show the differences between them. The technique is applied mainly in the biomedical do- main, although the technique can generally be applied to other areas.

NCCN Chemotherapy Order Templates: Enhancing patient safety through standardization

e17537 Background: NCCN Chemotherapy Order Templates (COT), which delineate antineoplastics and associated supportive care agents, monitoring and safety parameters, and instructions for self-administered agents, were launched in 2008 to complement the NCCN Clinical Practice Guidelines in Oncology and NCCN Drugs and Biologics Compendium for nine cancers. Through COT, NCCN sought to enhance patient safety by reducing medication errors, anticipating and managing adverse events, and standardizing care. NCCN developed and distributed a survey to evaluate the reception, use, and impact of COT on oncology practice. Methods: The survey included multiple-choice questions with filtering logic. Questions included 5-point Likert scale. The survey was emailed on December 18, 2008 to a convenience sample of 10,183 registered users of NCCN.org who had clicked at least once to the COT; 110 (1%) survey emails were undeliverable. 734 (7%) responded by 1/5/09 and 588 (6%) completed the survey (80% completion rate). 28 (<1%) recipients opted out of participating. Results: 476 (64%) respondents were providers, including MDs (47%), mid-level (8%) and nurses (10%); 11% were pharmacists. Of the 734 respondents, 465 (63%) had used COT. Among the 465 users, the median number COT accessed was 2 (range 0 - 9) with physicians accessing more than other providers (p = 0.002). Breast cancer COT were accessed most (68%). COT were used as a reference (52%) and for setting up chemotherapy orders (42%). 292 users (63%) agreed that COT impacted patient safety; with MDs more likely to agree (p = 0.001) compared to other providers. Of these, 89% responded that COT made chemotherapy ordering safer. 271 users (58%) agreed that using NCCN COT in practice impacted the ordering of supportive care agents. Among providers, MDs were more likely to agree (p = 0.002). Of those who agreed, 86% responded that COT made it more likely that appropriate supportive care orders were included. Conclusions: Adding NCCN Chemotherapy Order Templates to the core NCCN content was done to make the NCCN Clinical Practice Guidelines in Oncology more accessible to providers. Survey results indicate that COT users feel that template use improves the safety of chemotherapy and supportive care agents. Throughout 2009, NCCN will continue to develop COT to cover most cancers. [Table: see text]

The Eukaryotic Linear Motif Resource (ELM): Regulatory Sites in Proteins

AbstractLinear motifs are short and evolutionarily variable sequence patterns associated with particular functions often involving post-translational modifications, such as phosphorylation, acetylation, glycosylation, targeting signals for cellular compartments, protein cleavage sites and protein–protein interaction.Experimentally they are often neglected because their short length (4-10 residues long), and the fact that they often reside in disordered regions in proteins makes them difficult to detect. For a similar reason, using the sole regular expression to detect linear motifs matches in sequences has almost no predictive power because they are both statistically insignificant and prone to massive over-prediction.The Eukaryotic Linear Motif resource (ELM - "http://elm.eu.org":http://elm.eu.org) is a bioinformatics facility for investigating candidate short functional motifs in eukaryotic proteins. The ELM database to date has collected more than 140 motifs and their regular expressions patterns as well as information about their instances of occurrence, distribution, crystal structure, publications, etc.In order to reduce the over-prediction inherent to pattern matching against protein sequences and to discriminate true from false positive motif matches, context-based rules and logical filters are applied. The current version includes cell compartment, phylogeny, globular domain clash filters and the more recent structural filter based on known three-dimensional information that relies on structural information, such as residue solvent accessibility and secondary structure features. This implies that a candidate motif can be excluded from further consideration if the protein resides in the wrong cellular compartment or the motif is buried in the core of a globular domain. By considering additional types of context information, we expect that prediction of functional sites by ELM can be considerably improved. In cases where the user cannot provide relevant context information, we consider providing predictions of contextual information in order to improve the ELM performance. For example, since the ELM motif database has been annotated with biological process GO terms, the system could be prepared for addition of a new context filter using biological process.

Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion

This paper focuses on recently advanced fuzzy models and the application of type-2 fuzzy sets in video deinterlacing. The final goal of the proposed deinterlacing algorithm is to exactly determine an unknown pixel value while preserving the edges and details of the image. To begin, we will discuss some artefacts of spatial, temporal, and spatio-temporal domain deinterlacing methods. In order to address the aforementioned issues, we adopted type-2 fuzzy sets concepts to design a weight evaluating approach. In the proposed method, the upper and lower fuzzy membership functions of the type-2 fuzzy logic filters are derived from the type-1 (or primary) fuzzy membership function. The weights from upper and lower membership functions are considered to be multiplied with the candidate deinterlaced pixels. Experimental results proved that the performance of the proposed method was superior, both objectively and subjectively to other different conventional deinterlacing methods. Moreover, the proposed method preserved the smoothness of the original image edges and produced a high-quality progressive image.

Real-time fuzzy digital filters (RTFDF) properties for siso systems

This paper describes real-time fuzzy digital filter (RTFDF) concepts considering a description of fuzzy logic and adaptive digital filter concepts with real-time properties: the basic characteristic operation of this kind of filters is known as operation regions, knowing it as linguistic natural descriptions.

Fault Detection and Isolation Applied to a Ship Propulsion Benchmark

This paper describes a fault detection and isolation (FDI) scheme performed on the benchmark problem of a ship propulsion system. The model used for the ship propulsion system is nonlinear, for which two types of additive sensor faults, an additive incipient fault, and a multiplicative parametric fault are simulated. The estimation of the fault severity is accomplished by using an adaptive two-stage extended Kalman filter. A set of statistical detection variables is formed from the residuals of the bias and measurement estimates of the filter. These variables are then used in a threshold based hypothesis test to declare the occurrence of a fault and through a binary logic filter to identify the fault type. The simulation results showed that the developed fault detection and isolation scheme fulfilled some of the benchmark requirements reasonably well in the face of some prescribed perturbations in the model and disturbances of external signals.

Mapping piping plover (Charadrius melodus melodus) habitat in coastal areas using airborne lidar data

Coastal estuaries and beach habitat are some of the most important and productive ecosystems in Atlantic Canada. These sensitive areas are crucial for hundreds of land and marine species. Mapping and monitoring coastal habitat is important for the protection of species such as the endangered piping plover (Charadrius melodus melodus). Light detection and ranging (lidar) elevation and intensity data have been used together to successfully classify land-cover types. This study explores the use of elevation, texture, slope, and intensity to classify coastal habitat. Lidar data were collected over a barrier beach and estuary on the South Shore of Nova Scotia. Ground validation and training sites were collected using a real-time kinematic global positioning system. Unsupervised, supervised, and logical filter classifications were compared for separability of various beach and intertidal habitats. Coastal land classes similar in elevation, texture, and slope, such as mudflats, sand beaches, and salt marshes, relied heavily on intensity data for separation. Tidal saturation of these areas produced similar intensity returns, resulting in poor separation between classes. Logical filters applied to the lidar data improved the classification of coastal habitat compared to standard unsupervised and supervised classifications. Additional logical filters were used to isolate important nesting and feeding habitat for piping plover. Results of this study suggest that lidar can effectively be used for classifying coastal habitat if tidal and seasonal factors are taken into consideration.