فهرست مطالب

  • Volume:1 Issue: 2, 2020
  • تاریخ انتشار: 1398/12/21
  • تعداد عناوین: 8
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  • Neda Nazarboland*, Narges Abedivzadeh, Saeed Ghanbari Pages 1-11

    Executive dysfunction is common symptom among patients with attention deficit hyperactivity disorder (ADHD) and/ or Mathematical Learning disability (MLD). Current research evidences indicate that anxiety can lead to numerous cognitive deficits. Therefore, through comparing executive functioning in children with ADHD/MLD, who have high and low levels of anxiety, the present study examined the probable role of anxiety in intensifying their problems in executive functions, especially verbal and visuospatial working memory. In a retrospective quasi-experimental study, 8-12 years old children, who were diagnosed for ADHD and MLD comorbidity were selected using purposive convenience sampling (n=85). They completed the multidimensional anxiety scale for children. Then, due to their scores on this scale, 20 children with high anxiety (1.5 standard deviations and more above the mean) and 20 children with low anxiety (1.5 standard deviations and more below the mean) were selected and placed in two groups. Then, executive functions assessment tasks, including Tower of London test, Wechsler Memory Scale (WMS), and the Benton’s Visual Retention Test, were carried out. Collected data were analyzed using independent t test. Findings showed that anxiety can be considered as an intensifying factor in executive functioning of children with ADHD and MLD. Therefore, executive functions can be improved by balancing the levels of anxiety and preventing further impairment of executive function in these children.

    Keywords: Attention deficit hyperactivity disorder, Executive functions, Mathematical learning disability, Verbalworking memory, Visuospatial working memory
  • Nasrin Sadat Mirshafiee*, Forough Jafari Pages 12-21
    Introduction

    Self-compassion helps adolescents to accept themselves unconditionally and Future Time Perspective (FTP) can make them motivated to do their meaningful tasks in the future.

    Method

    Method was semi experimental method (pre-test –post-test research) with control group. The statistical population of the study consisted of 6,232 male students (14-16 years of age) at the 13th district of Tehran (Iran), the sample size was 30 people who were selected by available sampling method and randomly assigned to experimental and control groups. Two questionnaires include self-compassion of Neff (2003) and FTP of Brothers, Chui& Diehl (2014) these will be administered three times, a pre-test, a post-test and a follow-up test. Group counseling held in twelve sessions for experimental group for three months, the collected data from pretest, posttest and follow up were analyzed by SPSS software with the help of factorial mixed design with repeated measure.

    Result

    The results show the effectiveness of strength-based group counseling on self-compassion (self-kindness, common humanity, mindfulness and over-identification) and FTP (opportunities, limitations and ambiguities) after three months of group counseling.

    Conclusion

    Finding signature strengths (five highest strengths) through analyzing life’s experiences helps students to be aware of what they can do well, to learn how they can make decisions about their future, based on character strengths and to accept their limitations without self-censure.

    Keywords: future time perspective, self- compassion, strength-based group counseling
  • A. Javadian*, E. Sorouri Pages 22-26

    In this study, considering the importance of treatment of addiction as an illness, we have analyzed a model of harvesting of facilities for the rehabilitation and treatment as a new application of game theory. According to the results of this research, it is possible to avoid a waste of money, energy, and facilities with a better management of allocating facilities and we can treat more addicts.

    Keywords: Game theory, Dynamic systems, Harvest function, Statistical mechanics
  • Mohsen Sha’bani, Reza Khosrowabadi, Javad Salehi* Pages 27-38

    False memory is normally examined by the Deese-Roediger-McDermott (DRM) paradigm and it has shown an indirect association with gender stereotypes. In this study, gender effect on the false memory formation along with influence of emotional words stimuli were examined. 60 subjects (30 female) were recruited and they were exposed to 4 lists of 12 words in a DRM paradigm. Effects of gender stereotypes were examined using 2 lists of gender categorized words. In addition, emotional effect of the stimuli was also investigated by 2 lists of negatively-valanced or neutral lures (eg. blood or chair). Subsequently, false memory rates in the male and female participants were statistically compared using a mixed ANOVA model. The results showed a significant differential effect of gender on the false memory formation as well as negative and neutral word stimuli.

    Keywords: False memory, Deese-Roediger-McDermott paradigm, gender stereotypes
  • Arman Rezayati Charan, Shahriar Gharibzadeh* Pages 39-41

    The relation between objective reality and subjective perception is a controversial issue. In modern cognitive science many of well-known scientists believe that evolution prefers veridical perception systems which constitute representations which are similar to external reality, but in a recent theory which entitled as “interface theory of perception” D.D. Hoffman and his colleagues remark evolution prefers interfacial perceptual system which reflects the objective reality in a manner that there is no congruency between the perception and perceived object. It seems this theory neglects the environmental dramatic changes but we think this parameter can change the situation and bring and significant evolutionary advantage for veridical species.

    Keywords: Interface theory of perception, Veridical perception, relation of subjectivity, objectivity
  • Shima Nofallah, Fatemeh Bakouie*, Amirhossein Memari, Shahriar Gharibzadeh Pages 42-56

    Studies have shown that individuals with Autism Spectrum Disorder (ASD) tend to gaze aversion during social interaction. It also has been observed that autistic people have significant problems in performing social tasks, including face recognition. Researches emphasize the role of face gaze, especially visual communication in social interaction and learning. In this paper, we propose an Artificial Neural Network (ANN) to model the ASD’s deficiency in face recognition. We used Olivetti Research Laboratory (ORL) face database and chose pictures which fitted our desires. The ANN was trained and tested in three trial experiments; in the experiment 1 (exp. 1), we used pictures with up-masked faces (the upper half of the faces had been blurred) in order to model ASD’s face recognition problem, in the experiment 2 (exp. 2), pictures with normal pictures was used for simulation normal individuals’ face recognition; and in the experiment 3 (exp. 3), we used pictures with down-masked faces as a test group. Testing results show 20.00% error in the exp. 1, 4.44% error in the exp. 2, and 10.00% error in the exp. 3. Based on these results, the proposed network emphasizes the face recognition problem in ASD as a result of eye contact aversion.

    Keywords: Autism, Face Recognition, Eye Contact, Artificial Neural Network
  • Ommolbanin Moghimi Kandelous*, Norassadat Moosavi, Mahya Sam Daliri, Keivan Navi Pages 57-70

    In this article, we try to model the effect of the changes of the threshold voltage of two positive inputs to negative ones using nanotechnology-based on Quantum Dot Cellular automata (QCA). In order to do so, the voter of a Majority cell has been modified resulting in amplifying the negative effect of the upper and the lower cells. Besides this Brain-inspired approach can be used to design a very fast Majority function with two negative inputs based on QCA.

    Keywords: Neural Network, Bio-inspired nanostructure design, Nanotechnology, QCA, Powerconsumption, Majority Gate
  • A.H. Hadian Rasanan*, S. Meghdadi Zanjani, M. Akhavan, Jamal Amani Rad Pages 71-78

    In recent decades, autism spectrum disorder (ASD) has displyed an incremental prevalence rate. Due to unavailability of a definite cure, the early diagnosis of the disorder is of high significance. There are evidences suggesting the dimcriminatable differences between resting state networks of people who suffer from the disorder and healthy individuals. This distinguishability allows for utilization of fMRI imaging to perform as a good instrument for identification autism spectrum disorder. In this paper, a tensor decomposition method for diagnosis of autism form fMRI images is presented. The selected dataset for testing the performance of the proposed algorithm is ABIDE1. All site of the ABIDE1 are used for training the algorithm which is a challenging problem in fMRI data analyzing. Our proposed method successfully achieves the classification performance of about 60% for all site analysis.

    Keywords: Autism spectrum disorder, Tensor decomposition, ABIDE