982 resultados para Classification Rules


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2000 Mathematics Subject Classification: 26A33 (main), 44A40, 44A35, 33E30, 45J05, 45D05

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his article presents some of the results of the Ph.D. thesis Class Association Rule Mining Using MultiDimensional Numbered Information Spaces by Iliya Mitov (Institute of Mathematics and Informatics, BAS), successfully defended at Hasselt University, Faculty of Science on 15 November 2011 in Belgium

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Красимир Манев, Нели Манева, Хараламби Хараламбиев - Подходът с използване на бизнес правила (БП) беше въведен в края на миналия век, за да се улесни специфицирането на фирмен софтуер и да може той да задоволи по-добре нуждите на съответния бизнес. Днес повечето от целите на подхода са постигнати. Но усилията, в научно-изследователски и практически аспект, за постигане на „’формална основа за обратно извличане на БП от съществуващи системи “продължават. В статията е представен подход за извличане на БП от програмен код, базиран на методи за статичен анализ на кода. Посочени са някои предимства и недостатъци на такъв подход.

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Az egyes nemzetek számviteli szabályozásának vizsgálatánál az adott ország sajátosságaiból eredően részben eltérő szabályozások alakultak ki. Az induktív megközelítésű vizsgálatok jellemzően a szabályozási kérdések széles körét fogják át, de csak néhány tényező mentén közelítve. A cash flow-kimutatások témakörénél a legtöbbször csak azt nézték, hogy van-e előírás a kimutatás elkészítésére, de a részletekkel már kevésbé foglalkoztak. Ebből adódóan e területen viszonylag kis különbséget mutattak ki ezek a felmérések. A szerző kutatása szerint a nemzeti cash flow-kimutatások szabályozásának részleteiben eltérések tapasztalhatók, és ezek alapján a nemzetek klaszterelemzéssel hierarchikusan csoportokba rendezhetők. _____ Research has found that as a result of their particularities, different countries have established partly different accounting frameworks. Studies with inductive approaches typically encompass a wide range of regulatory issues, but based on a limited number of factors only. In the case of Statements of Cash Flows, most studies have so far only examined the existence of rules governing the presentation of the statement, without an in-depth analysis of the details. Therefore, these studies only found relatively minor differences in this field. The author’s research shows that many differences exist in the details of national Cash Flow Statement regulations, which makes it possible to classify the countries in groups using the method of hierarchical clustering.

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This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach “hybrid”, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both “top-down” structured knowledge and “bottom-up” data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 — i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.

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Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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The Subaxial Injury Classification (SLIC) system and severity score has been developed to help surgeons in the decision-making process of treatment of subaxial cervical spine injuries. A detailed description of all potential scored injures of the SLIC is lacking. We performed a systematic review in the PubMed database from 2007 to 2014 to describe the relationship between the scored injuries in the SLIC and their eventual treatment according to the system score. Patients with an SLIC of 1-3 points (conservative treatment) are neurologically intact with the spinous process, laminar or small facet fractures. Patients with compression and burst fractures who are neurologically intact are also treated nonsurgically. Patients with an SLIC of 4 points may have an incomplete spinal cord injury such as a central cord syndrome, compression injuries with incomplete neurologic deficits and burst fractures with complete neurologic deficits. SLIC of 5-10 points includes distraction and rotational injuries, traumatic disc herniation in the setting of a neurological deficit and burst fractures with an incomplete neurologic deficit. The SLIC injury severity score can help surgeons guide fracture treatment. Knowledge of the potential scored injures and their relationships with the SLIC are of paramount importance for spine surgeons who treated subaxial cervical spine injuries.

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to assess the construct validity and reliability of the Pediatric Patient Classification Instrument. correlation study developed at a teaching hospital. The classification involved 227 patients, using the pediatric patient classification instrument. The construct validity was assessed through the factor analysis approach and reliability through internal consistency. the Exploratory Factor Analysis identified three constructs with 67.5% of variance explanation and, in the reliability assessment, the following Cronbach's alpha coefficients were found: 0.92 for the instrument as a whole; 0.88 for the Patient domain; 0.81 for the Family domain; 0.44 for the Therapeutic procedures domain. the instrument evidenced its construct validity and reliability, and these analyses indicate the feasibility of the instrument. The validation of the Pediatric Patient Classification Instrument still represents a challenge, due to its relevance for a closer look at pediatric nursing care and management. Further research should be considered to explore its dimensionality and content validity.

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Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

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To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.

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Improve the content validity of the instrument for classification of pediatric patients and evaluate its construct validity. A descriptive exploratory study in the measurement of the content validity index, and correlational design for construct validation through exploratory factor analysis. The content validity index for indicators was 0.99 and it was 0.97 for graded situations. Three domains were extracted in the construct validation, namely: patient, family and therapeutic procedures, with 74.97% of explained variance. The instrument showed evidences of content and construct validity. The validation of the instrument occurred under the approach of family-centered care, and allowed incorporating some essential needs of childhood such as playing, interaction and affection in the content of the instrument.

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To evaluate the distribution of women according to the Robson 10-group classification system (RTGCS) and the occurrence of severe maternal morbidity (SMM) by mode of delivery at a tertiary referral hospital. A retrospective cross-sectional study was conducted of all women admitted to the Women's Hospital at the University of Campinas (Campinas, Brazil) for delivery between January 2009 and July 2013. Women were grouped according to RTGCS. Mode of delivery and SMM (defined as need for admission to the intensive care unit) were assessed. Among 12 771 women, 5957 (46.6%) delivered by cesarean. Overall, 3594 (28.1%) women were in group 1 (nulliparous, single pregnancy, cephalic, term, spontaneous labor), 2328 (18.2%) in group 5 (≥1 previous cesarean, single pregnancy, cephalic, term), and 2112 (16.5%) in group 3 (multiparous excluding previous cesarean, single pregnancy, cephalic, term, spontaneous labor). Group 5 contributed the most cesarean deliveries (1626 [27.3%]), followed by group 2 (nulliparous, single pregnancy, cephalic, term, induced labor or cesarean before labor; 1049 [17.6%]). SMM was more common among women undergoing cesarean delivery than among those delivering vaginally in groups 1-5. The RTGCS allowed the identification of groups with the highest frequency of cesarean delivery and an assessment of SMM. This should be considered in related health policies.

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Didanosine-loaded chitosan microspheres were developed applying a surface-response methodology and using a modified Maximum Likelihood Classification. The operational conditions were optimized with the aim of maintaining the active form of didanosine (ddI), which is sensitive to acid pH, and to develop a modified and mucoadhesive formulation. The loading of the drug within the chitosan microspheres was carried out by ionotropic gelation technique with sodium tripolyphosphate (TPP) as cross-linking agent and magnesium hydroxide (Mg(OH)2) to assure the stability of ddI. The optimization conditions were set using a surface-response methodology and applying the Maximum Likelihood Classification, where the initial chitosan concentration, TPP and ddI concentration were set as the independent variables. The maximum ddI-loaded in microspheres (i.e. 1433mg of ddI/g chitosan), was obtained with 2% (w/v) chitosan and 10% TPP. The microspheres depicted an average diameter of 11.42μm and ddI was gradually released during 2h in simulated enteric fluid.