822 resultados para discriminant analysis and cluster analysis


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It is well established that accent recognition can be as accurate as up to 95% when the signals are noise-free, using feature extraction techniques such as mel-frequency cepstral coefficients and binary classifiers such as discriminant analysis, support vector machine and k-nearest neighbors. In this paper, we demonstrate that the predictive performance can be reduced by as much as 15% when the signals are noisy. Specifically, in this paper we perturb the signals with different levels of white noise, and as the noise become stronger, the out-of-sample predictive performance deteriorates from 95% to 80%, although the in-sample prediction gives overly-optimistic results. ACM Computing Classification System (1998): C.3, C.5.1, H.1.2, H.2.4., G.3.

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Background: Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO/WHO Codex alimentarius guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.Results: A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three z-descriptors (z1, z2 and z3) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), naïve Bayes (NB) and k nearest neighbours (kNN). The best performing model was derived by kNN at k = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at http://www.pharmfac.net/allertop. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.Conclusions: AllerTOP is the first alignment-free server for in silico prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin. © 2013 Dimitrov et al.; licensee BioMed Central Ltd.

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Small and Medium Enterprises (SMEs) play an important part in the economy of any country. Initially, a flat management hierarchy, quick response to market changes and cost competitiveness were seen as the competitive characteristics of an SME. Recently, in developed economies, technological capabilities (TCs) management- managing existing and developing or assimilating new technological capabilities for continuous process and product innovations, has become important for both large organisations and SMEs to achieve sustained competitiveness. Therefore, various technological innovation capability (TIC) models have been developed at firm level to assess firms‘ innovation capability level. These models output help policy makers and firm managers to devise policies for deepening a firm‘s technical knowledge generation, acquisition and exploitation capabilities for sustained technological competitive edge. However, in developing countries TCs management is more of TCs upgrading: acquisitions of TCs from abroad, and then assimilating, innovating and exploiting them. Most of the TIC models for developing countries delineate the level of TIC required as firms move from the acquisition to innovative level. However, these models do not provide tools for assessing the existing level of TIC of a firm and various factors affecting TIC, to help practical interventions for TCs upgrading of firms for improved or new processes and products. Recently, the Government of Pakistan (GOP) has realised the importance of TCs upgrading in SMEs-especially export-oriented, for their sustained competitiveness. The GOP has launched various initiatives with local and foreign assistance to identify ways and means of upgrading local SMEs capabilities. This research targets this gap and developed a TICs assessment model for identifying the existing level of TIC of manufacturing SMEs existing in clusters in Sialkot, Pakistan. SME executives in three different export-oriented clusters at Sialkot were interviewed to analyse technological capabilities development initiatives (CDIs) taken by them to develop and upgrade their firms‘ TCs. Data analysed at CDI, firm, cluster and cross-cluster level first helped classify interviewed firms as leader, follower and reactor, with leader firms claiming to introduce mostly new CDIs to their cluster. Second, the data analysis displayed that mostly interviewed leader firms exhibited ‗learning by interacting‘ and ‗learning by training‘ capabilities for expertise acquisition from customers and international consultants. However, these leader firms did not show much evidence of learning by using, reverse engineering and R&D capabilities, which according to the extant literature are necessary for upgrading existing TIC level and thus TCs of firm for better value-added processes and products. The research results are supported by extant literature on Sialkot clusters. Thus, in sum, a TIC assessment model was developed in this research which qualitatively identified interviewed firms‘ TIC levels, the factors affecting them, and is validated by existing literature on interviewed Sialkot clusters. Further, the research gives policy level recommendations for TIC and thus TCs upgrading at firm and cluster level for targeting better value-added markets.

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The article attempts to answer the question whether or not the latest bankruptcy prediction techniques are more reliable than traditional mathematical–statistical ones in Hungary. Simulation experiments carried out on the database of the first Hungarian bankruptcy prediction model clearly prove that bankruptcy models built using artificial neural networks have higher classification accuracy than models created in the 1990s based on discriminant analysis and logistic regression analysis. The article presents the main results, analyses the reasons for the differences and presents constructive proposals concerning the further development of Hungarian bankruptcy prediction.

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This study examined the association of theoretically guided and empirically identified psychosocial variables on the co-occurrence of risky sexual behavior with alcohol consumption among university students. The study utilized event analysis to determine whether risky sex occurred during the same event in which alcohol was consumed. Relevant conceptualizations included alcohol disinhibition, self-efficacy, and social network theories. Predictor variables included negative condom attitudes, general risk taking, drinking motives, mistrust, social group membership, and gender. Factor analysis was employed to identify dimensions of drinking motives. Measured risky sex behaviors were (a) sex without a condom, (b) sex with people not known very well, (c) sex with injecting drug users (IDUs), (d) sex with people without knowing whether they had a STD, and (e) sex with using drugs. A purposive sample was used and included 222 male and female students recruited from a major urban university. Chi-square analysis was used to determine whether participants were more likely to engage in risky sex behavior in different alcohol use contexts. These contexts were only when drinking, only when not drinking, and when drinking or not. The chi-square findings did not support the hypothesis that university students who use alcohol with sex will engage in riskier sex. These results added to the literature by extending other similar findings to a university student sample. For each of the observed risky sex behaviors, discriminant analysis methodology was used to determine whether the predictor variables would differentiate the drinking contexts, or whether the behavior occurred. Results from discriminant analyses indicated that sex with people not known very well was the only behavior for which there were significant discriminant functions. Gender and enhancement drinking motives were important constructs in the classification model. Limitations of the study and implications for future research, social work practice and policy are discussed. ^

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An increasing number of students are selecting for-profit universities to pursue their education (Snyder, Tan & Hoffman, 2006). Despite this trend, little empirical research attention has focused on these institutions, and the literature that exists has been classified as rudimentary in nature (Tierney & Hentschke, 2007). The purpose of this study was to investigate the factors that differentiated students who persisted beyond the first session at a for-profit university. A mixed methods research design consisting of three strands was utilized. Utilizing the College Student Inventory, student’s self-reported perceptions of what their college experience would be like was collected during strand 1. The second strand of the study utilized a survey design focusing on the beliefs that guided participants’ decisions to attend college. Discriminant analysis was utilized to determine what factors differentiated students who persisted from those who did not. A purposeful sample and semi-structured interview guide was used during the third strand. Data from this strand were analyzed thematically. Students’ self-reported dropout proneness, predicted academic difficulty, attitudes toward educators, sense of financial security, verbal confidence, gender and number of hours worked while enrolled in school differentiated students who persisted in their studies from those who dropped out. Several themes emerged from the interview data collected. Participants noted that financial concerns, how they would balance the demands of college with the demands of their lives, and a lack of knowledge about how colleges operate were barriers to persistence faced by students. College staff and faculty support were reported to be the most significant supports reported by those interviewed. Implications for future research studies and practice are included in this study.

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This study examined the association of theoretically guided and empirically identified psychosocial variables on the co-occurrence of risky sexual behavior with alcohol consumption among university students. The study utilized event analysis to determine whether risky sex occurred during the same event in which alcohol was consumed. Relevant conceptualizations included alcohol disinhibition, self-efficacy, and social network theories. Predictor variables included negative condom attitudes, general risk taking, drinking motives, mistrust, social group membership, and gender. Factor analysis was employed to identify dimensions of drinking motives. Measured risky sex behaviors were (a) sex without a condom, (b) sex with people not known very well, (c) sex with injecting drug users (IDUs), (d) sex with people without knowing whether they had a STD, and (e) sex with using drugs. A purposive sample was used and included 222 male and female students recruited from a major urban university. Chi-square analysis was used to determine whether participants were more likely to engage in risky sex behavior in different alcohol use contexts. These contexts were only when drinking, only when not drinking, and when drinking or not. The chi-square findings did not support the hypothesis that university students who use alcohol with sex will engage in riskier sex. These results added to the literature by extending other similar findings to a university student sample. For each of the observed risky sex behaviors, discriminant analysis methodology was used to determine whether the predictor variables would differentiate the drinking contexts, or whether the behavior occurred. Results from discriminant analyses indicated that sex with people not known very well was the only behavior for which there were significant discriminant functions. Gender and enhancement drinking motives were important constructs in the classification model. Limitations of the study and implications for future research, social work practice and policy are discussed.

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A certain type of bacterial inclusion, known as a bacterial microcompartment, was recently identified and imaged through cryo-electron tomography. A reconstructed 3D object from single-axis limited angle tilt-series cryo-electron tomography contains missing regions and this problem is known as the missing wedge problem. Due to missing regions on the reconstructed images, analyzing their 3D structures is a challenging problem. The existing methods overcome this problem by aligning and averaging several similar shaped objects. These schemes work well if the objects are symmetric and several objects with almost similar shapes and sizes are available. Since the bacterial inclusions studied here are not symmetric, are deformed, and show a wide range of shapes and sizes, the existing approaches are not appropriate. This research develops new statistical methods for analyzing geometric properties, such as volume, symmetry, aspect ratio, polyhedral structures etc., of these bacterial inclusions in presence of missing data. These methods work with deformed and non-symmetric varied shaped objects and do not necessitate multiple objects for handling the missing wedge problem. The developed methods and contributions include: (a) an improved method for manual image segmentation, (b) a new approach to 'complete' the segmented and reconstructed incomplete 3D images, (c) a polyhedral structural distance model to predict the polyhedral shapes of these microstructures, (d) a new shape descriptor for polyhedral shapes, named as polyhedron profile statistic, and (e) the Bayes classifier, linear discriminant analysis and support vector machine based classifiers for supervised incomplete polyhedral shape classification. Finally, the predicted 3D shapes for these bacterial microstructures belong to the Johnson solids family, and these shapes along with their other geometric properties are important for better understanding of their chemical and biological characteristics.

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Which 'actor' takes the management accountant role as an extravert business partner? Does a relation between the personal trait Extraversion and fulfilling a management accountant role as a business partner exist? Open Universiteit Nederland End thesis MSc Management, Accounting & Finance Support 1: Prof. dr. A.C.N. van de Ven RA Support 2: dr. P.C.M. Claes Examinator: dr. P. Kamminga Date of approval: September 3, 2014 student: P.R. van der Wal (studentnumber 839104017 email petervanderwal2003@yahoo.com The main question of this research is: Does a relation between the personal trait Extraversion and fulfilling a management accountant role as a business partner exist? This research is based on the dataset obtained by the controller survey 2013, executed in commission of the 'Open Universiteit' (Bork & van der Wal, 2014). From the literature review it is clear: among other management accountant roles we need business partners. And there is a relation between the personal trait Extraversion and fulfilling the role as business partner. At the same time a lack of necessary personal traits for this role has been noticed, among which is Extraversion. The factor- and cluster analyses reported by Bork & van der Wal (2014) resulted in the identification of two types of management accountant roles. In this extended research TYPE II is identified as a business partner because (s)he practices activity-combinations which are related to strategy, analyzing, supporting management in decision making, advisory, change-agency and representing the organization. 36% of the population of Dutch management accountants with a master degree (or similar) meet with the role of the business partner. Although the fulfillment of the role (TYPE II) is not purely business partnering. E.g. reporting and scorekeeping are still activities executed by TYPE II and it is not clear to what extent. Apart from that, role TYPE I executes change management and risk-management activities, which are (according to the definition) activities that belong to the business partner. The role as business partner is practiced but not that optimal as defined in theory. The logistic regression analyses on the survey-data show that Extraversion among three other triggers is significant for the prediction of the fulfillment of the management accountant role (Bork & van der Wal, 2014). A more extravert personal trait predicts a preference for TYPE II, which relates to the business partner. This 'in depth research' concentrated on the relation between the Big Five personal traits and the six activity-combinations (factors) instead of on the two clusters (I and II). The statistic analyses confirm the predicting influence of Extraversion on the business partner role. Although, except for one factor, no extra significance has been found in this additional research. The essential question can be confirmed positively: the management accountant role business partner exists in practice, some management accountants are more extravert then others, and there is a positive relation between extraversion and fulfilling the business partner role. Some formulated research limitations are related to the statistical weakness of some prediction outcomes and to interpretation differences that might occur. Further research can e.g. concentrate on the other personal traits and the significance for role-differentiation in education programs. The management accountant survey 2013 Management accountant roles in 2013 in the Netherlands Open Universiteit Nederland End thesis MSc Management, Accounting & Finance Support 1: Prof. dr. A.C.N. van de Ven RA Support 2: dr. P.C.M. Claes Examinator: dr. P. Kamminga Date of approval: September 3, 2014 student: P.R. van der Wal and H.J. Bork studentnumber: 839104017 and 838532340) email: petervanderwal2003@yahoo.com and hjbork@hotmail.com This paper describes the conceptual model and results of the 'management accountants survey 2013'. The survey is part of a longitudinal survey, earlier executed in 2004, 2007 and 2010 under responsibility of the 'Open Universiteit Nederland'. Secondly the dataset of this survey will be used by us to do our own analyses on the predicting value of the triggers 'personality factor: extraversion' and 'lever of control: interactive controls' on the management accounting role that comes close to a role defined as 'Business Partner'. Scientific research shows that there are different management accounting roles, and that these roles change and that preferences exist for certain roles (Verstegen B. , Loo, Mol, Slagter, & Geerkens, 2007). The main question that will be answered in this paper is which coherent combinations of activities are being executed by management accountants in 2013 in the Netherlands by master-graduates? And secondly which triggers of management accountants' activities predict to which cluster a management accountant belongs? The conceptual model of this research has been developed in 2004 (Verstegen B. , Loo, Mol, Slagter, & Geerkens, 2007). For this research the same 37 activities as in the former researches are included (appendix 1). In the trigger-set (appendix 1) some adaptations have been made for reasons of restricting the length of the survey and to pinpoint on particular research goals (e.g. personality and levers of control). The coherent combinations of activities were found by a factor-analysis and the groups of controllers by a cluster analysis. A regression analysis shows which trigger-items are most significant. The survey has been sent to 2.353 students that finished a controller-study on a Dutch University. There was a 9% (211) response with a completely filled survey. 137 of which indicated to work in a controller-function at the moment. These controllers have been included in the results. The factor-analysis results in six different coherent combinations of activities (factors). Shortly these factors are: advising top management on strategic level with result-effecting information (1), organizing internal reporting (2) organizing and representing the organization on external reporting (3), advising and managing changes by shortcomings in processes and control systems (4), maintaining and managing administrative organization- , information- and control systems (5) and organizing/executing risk management and internal audit (6). Factors 4, 5 and 6 are clustered in cluster TYPE I (125 controllers) and factors 1, 2 and 3 in cluster TYPE II (69 controllers). TYPE II can be associated with the management accountant role 'Business Partner', although the accountant keeps partly active in a scorekeeper role. The four most significant triggers for predicting being a TYPE II controller are 'Executing a risk-management task in order to meet compliance standards' (1), extraversion (2), company size in terms of fte (3) and gender (4).

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Abstract Honey is a high value food commodity with recognized nutraceutical properties. A primary driver of the value of honey is its floral origin. The feasibility of applying multivariate data analysis to various chemical parameters for the discrimination of honeys was explored. This approach was applied to four authentic honeys with different floral origins (rata, kamahi, clover and manuka) obtained from producers in New Zealand. Results from elemental profiling, stable isotope analysis, metabolomics (UPLC-QToF MS), and NIR, FT-IR, and Raman spectroscopic fingerprinting were analyzed. Orthogonal partial least square discriminant analysis (OPLS-DA) was used to determine which technique or combination of techniques provided the best classification and prediction abilities. Good prediction values were achieved using metabolite data (for all four honeys, Q2 = 0.52; for manuka and clover, Q2 = 0.76) and the trace element/isotopic data (for manuka and clover, Q2 = 0.65), while the other chemical parameters showed promise when combined (for manuka and clover, Q2 = 0.43).

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Diazotrophs in the mangrove rhizosphere play a major role in providing new nitrogen to the mangrove ecosystem and their composition and activity are strongly influenced by anthropogenic activity and ecological conditions. In this study, the diversity of the diazotroph communities in the rhizosphere sediment of five tropical mangrove sites with different levels of pollution along the north and south coastline of Singapore were studied by pyrosequencing of the nifH gene. Bioinformatics analysis revealed that in all the studied locations, the diazotroph communities comprised mainly of members of the diazotrophic cluster I and cluster III. The detected cluster III diazotrophs, which were composed entirely of sulfate-reducing bacteria, were more abundant in the less polluted locations. The metabolic capacities of these diazotrophs indicate the potential for bioremediation and resiliency of the ecosystem to anthropogenic impact. In heavily polluted locations, the diazotrophic community structures were markedly different and the diversity of species was significantly reduced when compared with those in a pristine location. This, together with the increased abundance of Marinobacterium, which is a bioindicator of pollution, suggests that anthropogenic activity has a negative impact on the genetic diversity of diazotrophs in the mangrove rhizosphere.

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Background: It is important to assess the clinical competence of nursing students to gauge their educational needs. Competence can be measured by self-assessment tools; however, Anema and McCoy (2010) contend that currently available measures should be further psychometrically tested.
Aim: To test the psychometric properties of Nursing Competencies Questionnaire (NCQ) and Self-Efficacy in Clinical Performance (SECP) clinical competence scales.
Method: A non-randomly selected sample of n=248 2nd year nursing students completed NCQ, SECP and demographic questionnaires (June and September 2013). Mokken Scaling Analysis (MSA) was used to investigate structural validity and scale properties; convergent and discriminant validity and reliability were also tested for each scale.
Results: MSA analysis identified that the NCQ is a unidimensional scale with strong scale scalability coefficients Hs =0.581; but limited item rankability HT =0.367. The SECP scale MSA suggested that the scale could be potentially split into two unidimensional scales (SECP28 and SECP7), each with good/reasonable scalablity psychometric properties as summed scales but negligible/very limited scale rankability (SECP28: Hs = 0.55, HT=0.211; SECP7: Hs = 0.61, HT=0.049). Analysis of between cohort differences and NCQ/SECP scores produced evidence of discriminant and convergent validity; good internal reliability was also found: NCQ α = 0.93, SECP28 α = 0.96 and SECP7 α=0.89.

Discussion: In line with previous research further evidence of the NCQ’s reliability and validity was demonstrated. However, as the SECP findings are new and the sample small with reference to Straat and colleagues (2014), the SECP results should be interpreted with caution and verified on a second sample.
Conclusions: Measurement of perceived self-competence could start early in a nursing programme to support students’ development of clinical competence. Further testing of the SECP scale with larger nursing student samples from different programme years is indicated.

References:
Anema, M., G and McCoy, JK. (2010) Competency-Based Nursing Education: Guide to Achieving Outstanding Learner Outcomes. New York: Springer.
Straat, JH., van der Ark, LA and Sijtsma, K. (2014) Minimum Sample Size Requirements for Mokken Scale Analysis Educational and Psychological Measurement 74 (5), 809-822.

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This study examines the complex hotel buyer decision process in front of the tourism distribution channels. Its objective is to describe the influence level of the tourism marketing intermediaries, mainly the travel agents and tour operators, over the hotel decision process by the buyer-tourist. The data collection process was done trough a survey with three hundred brazilian tourists hosted in nineteen hotels of Natal, capital of Rio Grande do Norte, Brazil. The data analysis was done using some multivariate statistic techniques as correlation analysis, multiple regression analysis, factor analysis and multiple discriminant analysis. The research characterizes the hotel services consumers profile and his trip, and identifying the distribution channels used by them. Furthermore, the research verifies the intermediaries influence exercised over hotel buyer decision process, looking for identify causality relations between the influence level and the buyer profile. Verifies that information about hotels available on internet reduces the probability that this influence can be practiced; however it was possible identifying those consumers considers this information complementary and non-substitutes than the information from intermediaries. The characteristics of the data do not allow indentifying the factors that constraint the intermediaries influence neither identifying discriminant functions of the specific distribution channel choice by consumers. The study concludes that consumers don t agree in have been influenced by intermediaries or don t know if they have, still considering important to consult them and internet doesn t substitute their function as information source

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The principal purpose of this research was to investigate discriminant factors of survival and failure of micro and small businesses, and the impacts of these factors in the public politics for entrepreneurship in the State of Rio Grande do Norte. The data were ceded by SEBRAE/RN and the Commercial Committee of the Rio Grande do Norte State and it included the businesses that were registered in 2000, 2001 and 2002. According to the theoretical framework 3 groups of factors were defined Business Financial Structure, Entrepreneurial Preparation and Entrepreneurial Behavior , and the factors were studied in order to determine whether they are discriminant or not of the survival and business failure. A quantitative research was applied and advanced statistical techniques were used multivariate data analysis , beginning with the factorial analysis and after using the discriminant analysis. As a result, canonical discriminant functions were found and they partially explained the survival and business failure in terms of the factors and groups of factors. The analysis also permitted the evaluation of the public politics for entrepreneurship and it was verified, according to the view of the entrepreneurs, that these politics were weakly effective to avoid business failure. Some changes in the referred politics were suggested based on the most significant factors found.

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The Behavioral Finance develop as it is perceived anomalies in these markets efficient. This fields of study can be grouped into three major groups: heuristic bias, tying the shape and inefficient markets. The present study focuses on issues concerning the heuristics of representativeness and anchoring. This study aimed to identify the then under-reaction and over-reaction, as well as the existence of symmetry in the active first and second line of the Brazilian stock market. For this, it will be use the Fuzzy Logic and the indicators that classify groups studied from the Discriminant Analysis. The highest present, indicator in the period studied, was the Liabilities / Equity, demonstrating the importance of the moment to discriminate the assets to be considered "winners" and "losers." Note that in the MLCX biases over-reaction is concentrated in the period of financial crisis, and in the remaining periods of statistically significant biases, are obtained by sub-reactions. The latter would be in times of moderate levels of uncertainty. In the Small Caps the behavioral responses in 2005 and 2007 occur in reverse to those observed in the Mid-Large Cap. Now in times of crisis would have a marked conservatism while near the end of trading on the Bovespa speaker, accompanied by an increase of negotiations, there is an overreaction by investors. The other heuristics in SMLL occurred at the end of the period studied, this being a under-reaction and the other a over-reaction and the second occurring in a period of financial-economic more positive than the first. As regards the under / over-reactivity in both types, there is detected a predominance of either, which probably be different in the context in MLCX without crisis. For the period in which such phenomena occur in a statistically significant to note that, in most cases, such phenomena occur during the periods for MLCX while in SMLL not only biases are less present as there is no concentration of these at any time . Given the above, it is believed that while detecting the presence of bias behavior at certain times, these do not tend to appear to a specific type or heuristics and while there were some indications of a seasonal pattern in Mid- Large Caps, the same behavior does not seem to be repeated in Small Caps. The tests would then suggest that momentary failures in the Efficient Market Hypothesis when tested in semistrong form as stated by Behavioral Finance. This result confirms the theory by stating that not only rationality, but also human irrationality, is limited because it would act rationally in many circumstances