Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance rate.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

The purpose of this study was to compare the effect of different types of second stimulus (simple, discrimination, choice) at different time intervals on the first stimulus reaction time in the psychological refractory period paradigm. Thirty-six female students, aged 18–24 (mean=21) years, were randomly assigned to three experimental groups of 12 each: simple, discrimination and choice. For each group, there were five measurement phases based on the time interval between two stimuli (50, 100, 200, 400, and 1000 ms).Data was analyzed with repeated measures and mixed factorial analysis of variance including factors of time intervals and groups. Results showed that in the first stimulus reaction time, the main effect of group (F2,33=15.40, P=0.001), the main effect of different time interval (F3,93=16.79, P=0.001), and the interaction between group and time interval (F5,93=2.42, P=0.03) was significant. In the second stimuli reaction time, the main effect of group (F2,33=12.04, P=0.001) was significant; the main effect of different time interval (F3,100=2.57, P=0.05) and the interaction between group and time interval (F3,100=1.63, P=0.05) was not significant. Findings showed that the second stimulus type and the interval between two stimuli significantly affect the second stimulus reaction time delay as well as the first stimulus reaction time.

Background: Time perception is considered as an important subject in cognitive psychology, which is essential for our understanding regarding brain mechanisms underlying human cognition and disabilities. Deficits in time perception have been found in people with both attention-deficit/hyperactivity disorder (ADHD), dyslexia, Parkinson’ s and Alzheimer’ s disease. The present study aimed at developing and evaluating the Time Perception Software with a sample including 152 Iranian students. Methods: The computerized time perception task was designed based on time estimation, reproduction, production and time comparison method. In order to verify the reliability of the task, 30 students which were participated in the test sample repeated the test after one month. The content and construct validity were used in order to examine the validity of the task. The construct validity of the time perception task was verified by analyzing the confirmatory factor analysis using the Amos 24 software. Results: In the modified model, the comparison factor was eliminated (CFI=0. 965). The highest correlation was observed in the time estimation of 11 seconds with a correlation coefficient which was equal to 0. 935 (P=0. 001), while the lowest correlation coefficient was observed in the time production of 17 seconds with the correlation coefficient which was equal to 0. 679 (P=0. 001). The internal consistency of the task indicated that the time perception task had a near-optimal validity and its reliability was at the optimal level with the Cronbach’ s alpha which was equal to 0. 67. Conclusion: In order to conclude, The Time Perception Software appeared to be reliable and valid for assessing and measuring time perception in the Iranian students. This software can be used in future research investigations.

Introduction: Time perception is one of the most controversial issues in the field of cognitive science. One of the first models for time perception in the brain is the internal clock model, according to which a part of the brain acts as the constructor of time pulses and another part as the counter of these pulses. Yet, nother part is responsible for storing this time in memory. According to previous studies, delta and beta waves seem to play a role in the overestimation and underestimation of individuals, although the role of these waves in the perception of long- term time frames has not been studied.Method: Participants in the test were 33 healthy subjects and according to the way of estimating time, they were placed in two groups of overestimation and underestimation. Time estimation was investigated during a mindfulness task. Functional brain activity was investigated using electroencephalography during rest and task. Spectral analysis was performed in the standard bands at 19 electrodes. Statistical analysis was carried out for five electrodes of C3, C4, Fz, Cz, Pz. The statistical comparison of five C3, C4, Fz, Cz, Pz electrodes showed a meaningful difference between the two groups in the absolute power of the beta frequency band (25-30 Hz) on each of the five electrodes.Results: The results show significant differences of high beta (25-30 Hz) absolute power at all investigated electrodes.Conclusion: The results can be argued in the context of internal clock model and scalar timing theory. In the range of long term duration, the results confirm internal clock model as a valid model for explaining time estimation.

This study aimed to investigate the relationship between listening assessment task types, time on task, and the use of listening strategy by Iranian EFL learners. For this purpose, a group of 44 Iranian EFL students (Males and Females, 14 to 25 years old) selected through convenience sampling from an English language institute in Sanandaj participated in this study. Then, they were randomly assigned into four experimental groups. In one group, note-taking was considered the listening assessment task, while in the second group oral reproduction was specified as the assessment task for assessing listening comprehension. After that, each group was further subdivided randomly into a shorter time-on-task group (20 minutes) and a longer time-on-task group (40 minutes). Next, all groups completed Vandergrift, Goh, Mareschal, and Tafaghodtari’s (2006) Meta-cognitive Awareness Listening Strategy Questionnaire. A two-way ANOVA was run to examine the effects of both listening assessment task type and time on task on listening strategy use among the four groups. The results revealed that the students in the oral reproduction task with high time on task group significantly showed higher preferences for choosing Planning-Evaluation, Mental Translation, and Problem-Solving strategies and those in the note-taking with low time on task group preferred the Directed-Attention strategy, while those in the note-taking with high time on task group preferred Person-Knowledge strategy.

Aim: The aim of this study was to investigate the interactive effect of working memory and task duration on time perception. Methods: The research method was quasi-experimental. The population of this research was school students, university students and personnel of organizations of Kerman city in 2018 and among them, 300 persons were selected by available sampling method. The time reproduction task of Shahabifar and Movahedinia (2016) was used for obtaining data. Data were analyzed by paired samples t-test and two factor analysis of variance with repeated measures. Findings: The results showed that the main effect of working memory and task duration and interactive effect of these variables on time perception was significant (p<0. 01). Working memory and increase of the task duration affect time perception respectively in the form of decreasing and increasing the amount of time reproduction error. Conclusion: Time perception decays significantly with increasing length of time intervals and working memory load.