Change-Point Detection in Business Cycles using Machine Learning Algorithms

Turning points in business cycles are defined as the onset of a recession or an expansion which are quite difficult to be predicted. In this thesis, we approach the problem of turning (change) point detection as the viewpoint of binary classification task. Due to the small ratio of changes to total data (as the number of recessions is relatively low), we face heavily class-imbalance challenge in this problem. We explore a wide variety of machine learning-based solutions for this problem: from base classifier to the multi-step classifier ensemble algorithm as well as a feature selection step. We examined the proposed classification methods on Canadian large dataset. Among different examined methods, the hybrid ensemble method including data sampling followed by a feature selection and multi-step ensemble can predict the Covid19 recession’s changepoints precisely with all the time series available one month ago. Some robustness checks such as the effect of window size on the model performance are also provided. Moreover, excluding the financial crisis from the training set, the method 8 is still able to predict the changepoints in the case of financial crisis precisely, however, in the case of the Covid-19 recession, they were detected one-period late, suggesting importance of financial crisis’ data in detecting Covid-19 change points

Learning Representations from Persian Handwriting for Offline Signature Verification, a Deep Transfer Learning Approach

Offline Signature Verification (OSV) is a challenging pattern recognition task, especially when it is expected to generalize well on the skilled forgeries that are not available during the training. Its challenges also include small training sample and large intra-class variations. Considering the limitations, we suggest a novel transfer learning approach from Persian handwriting domain to multi-language OSV domain. We train two Residual CNNs on the source domain separately based on two different tasks of word classification and writer identification. Since identifying a person signature resembles identifying ones handwriting, it seems perfectly convenient to use handwriting for the feature learning phase. The learned representation on the more varied and plentiful handwriting dataset can compensate for the lack of training data in the original task, i.e. OSV, without sacrificing the generalizability. Our proposed OSV system includes two steps: learning representation and verification of the input signature. For the first step, the signature images are fed into the trained Residual CNNs. The output representations are then used to train SVMs for the verification. We test our OSV system on three different signature datasets, including MCYT (a Spanish signature dataset), UTSig (a Persian one) and GPDS-Synthetic (an artificial dataset). On UT-SIG, we achieved 9.80% Equal Error Rate (EER) which showed substantial improvement over the best EER in the literature, 17.45%. Our proposed method surpassed state-of-the-arts by 6% on GPDS-Synthetic, achieving 6.81%. On MCYT, EER of 3.98% was obtained which is comparable to the best previously reported results

Arabų piliečių politinės nuostatos Šiaurės Afrikos valstybėse

Theories of social capital, government performance, Islamic values, and globalization are among the most important tools that can be used to help explain individuals’ political attitudes. The present research attempts to address the effects of the abovementioned factors on the political attitude of Arab citizens using the Arab Barometer Wave IV data. The results showed that only 23.2% of citizens disagreed with a democratic political system, while 70.3% and 60.1% expressed their opposition to authoritarian and Shari’ah-based systems. Results of the final model of research indicated that memberships in social associations, on the one hand, increased the tendency of individuals to support authoritarian and law-based political systems and, on the other hand, did not have any significant effect on the tendency toward supporting a democratic political system. It was concluded that improving economic performance not only affected the promotion of the Shari’ah-based political system, but that Political Performance also reduced the inclinations toward Shari’ah and authoritarianism. Furthermore, Political Performance increased the tendency of individuals to favor a democratic system. In addition, although individuals’ support for a Shari’ah-based political system had increased, Islamic values did not act as a barrier that would keep individuals away from favoring a democratic political system. Among the variables of globalization, the expansion of communication reduced people’s tendencies toward Shari’ah and authoritative political systems, along with a positive effect on strengthening support for democratic systems. Ultimately, Westernization only affected the shrinking support of some Shari’ah-based political systems. Socialinio kapitalo, vyriausybės veiklos, islamo vertybių ir globalizacijos teorijos yra vienos iš svarbiausių priemonių, kurios gali būti naudojamos paaiškinti asmenų politinėms pažiūroms. Šis tyrimas, remiantis Arabų barometro „Wave IV“ duomenimis, bando išsiaiškinti minėtų veiksnių poveikį arabų piliečių politinėms nuostatoms. Rezultatai parodė, kad tik 23,2 proc. piliečių nesutinka su demokratine politine sistema, o atitinkamai 70,3 proc. ir 60,1 proc. apklaustųjų išreiškė nepritarimą autoritarinėms ir šariatu paremtoms sistemoms. Galutinio tyrimo modelio rezultatai parodė, kad narystė socialinėse asociacijose, viena vertus, padidina individų polinkį palaikyti autoritarines ir šariato įstatymais pagrįstas politines sistemas, tačiau, kita vertus, neturėjo reikšmingos įtakos polinkiui remti demokratines politines sistemas. Buvo padaryta išvada, kad geresni ekonominiai rodikliai turi įtakos šariatu pagrįstos politinės sistemos rėmimui, o geresni vyriausybių efektyvumo rodikliai sumažina paramą šariatui ir autoritarizmui. Be to, geresni vyriausybių efektyvumo rodikliai padidino asmenų polinkį palankiai vertinti demokratinę sistemą. Taip pat, nors asmenų paramą šariatu paremtai politinei sistemai didina pritarimas islamo vertybėms, šis kintamasis nebuvo kliūtis, kuri mažintų asmenų palankumą demokratinei politinei sistemai. Tarp globalizacijos kintamųjų komunikacijos plėtra sumažino žmonių pritarimą šariatu paremtoms ir autoritarinėms politinėms sistemoms, taip pat turėjo teigiamą poveikį stipresnei paramai demokratinėms sistemoms. Galiausiai vakarietiškumas lėmė tik mažesnę paramą kai kurioms šariatu paremtoms politinėms sistemoms

Factors related to Helping Behavior in Guilan Welfare Organization

Introduction: The aim of this study was to identify the factors affecting the reduction of citizens' helping behavior with the welfare organization. Method: This study was conducted by descriptive method and ex-post facto design.  Data were collected from 408 citizens whose age was 20 years and older, and they all were from Guilan province. Samples were selected using multistage cluster sampling method. Measurement tools were: Adult Trust Scale; Multidimensional Perceived Social Support Scale; Norm of Reciprocity Scale; Social Network Index; Social Responsibility Questionnaire; Sense of Empathy Questionnaire; Revised Citizen Participation in Decision Making Questionnaire; Organizational Transparency Questionnaire; Awareness of Cooperation Methods and Level of Cooperation Questionnaire. Findings: Significant differences between individuals with poor, moderate, and high helping in terms of social trust; social support; social networks and ties; norm of reciprocity; norm of social responsibility; sense of empathy; belief in not involving citizens in the decisions of the welfare organization; citizens' awareness of cooperation methods; belief in the lack of transparency in the performance of the welfare organization; and altruistic behavior was observed. Discussion: Inadequacies in social variables act as risk factors for reducing cooperation with the welfare organization. Therefore, it is necessary to take intervention measures to strengthen psychosocial variables in order to improve the level of cooperation of citizens

Active Transfer Learning for Persian Offline Signature Verification

Offline Signature Verification (OSV) remains a challenging pattern recognition task, especially in the presence of skilled forgeries that are not available during the training. This challenge is aggravated when there are small labeled training data available but with large intra-personal variations. In this study, we address this issue by employing an active learning approach, which selects the most informative instances to label and therefore reduces the human labeling effort significantly. Our proposed OSV includes three steps: feature learning, active learning, and final verification. We benefit from transfer learning using a pre-trained CNN for feature learning. We also propose SVM-based active learning for each user to separate his genuine signatures from the random forgeries. We finally used the SVMs to verify the authenticity of the questioned signature. We examined our proposed active transfer learning method on UTSig: A Persian offline signature dataset. We achieved near 13% improvement compared to the random selection of instances. Our results also showed 1% improvement over the state-of-the-art method in which a fully supervised setting with five more labeled instances per user was used

COMPARISON BETWEEN PID CONTROLLERS FOR GRYPHON ROBOT OPTIMIZED WITH NEURO- FUZZY SYSTEM AND THREE INTELLIGENT OPTIMIZATION ALGORITHMS

ABSTRACT In this paper three intelligent evolutionary optimization approaches to design PID controller for

Epistemology of the New Social Movements in the International System and Middle East

From 2010 onwards, the international system has observed public protests providing the situation for entering a new level of political and social evolutions around the world and the region. The transition from collective action based on class to action based on notions of identity, transition from unilateralism in action to interactive model and relationship-based and transition from economic aims in the form of collective action to symbolic cultural and political aims have been the main elements of evolution of social movement in the recent years. The current article is a response to the reason of incidence of such evolution and why the pluralism and increased access of people to political procedures, development of information and communication technologies, and highlighting the role of civil society, non-governmental organizations and expansion of role of new middle class have resulted in such evolution. Discussions made by authors such as Alberto Melucci regarding the interactive and identity-based action, could be appropriate theoretical frameworks for surveying the process of transition from conventional social movement to new social movement (NSM). From the point of research condition, the current article is a descriptive-analytical survey and from the point of aim it is an applied survey. DOI: 10.5901/mjss.2015.v6n5s1p31