ali ghaffari

Neurodevelopmental disorders manifest as a range of conditions during development, impacting the brain's function, structure, and growth. 
resulting in cognitive deficits and challenges in adaptation for children. This study examines how problem-solving skills contribute to learning disabilities in children with attention deficit hyperactivity disorder, distinguishing between boys and girls and considering the mediating influence of social cognition.
The current study employed a descriptive-correlational approach with a cross-sectional research design, utilizing structural equation modeling (SEM) and multi-group analysis techniques. The study aimed to explore male and female students with attention deficit hyperactivity disorder (ADHD) in Tehran from July to October 2023. A sample of 134 adolescents was selected using purposive sampling. The research tools included the Problem-Solving Inventory (PSI), Colorado Learning Difficulties Questionnaire (CLDQ), and Student Social Cognition Questionnaire (SHAD). The researchers performed descriptive statistics analysis with SPSS version 27 and utilized SmartPLS version 4 for path analysis and Multi-Group Analysis (MGA). The study considered a significance level of 0.05.
According to the research findings, Problem-solving skills had a significant negative impact on Learning Difficulties, with girls being affected more than boys. The difference between the two genders was statistically significant (p = 0.029). Further analysis revealed that Social cognition only acted as a mediator in reducing Learning Difficulties in girls. 
Based on the results of this study, it appears essential to focus on problem-solving skills to decrease learning disabilities and enhance social cognition in students diagnosed with attention deficit hyperactivity disorder.

To quickly detect sudden cardiac death (SCD), it is decisive to gather suitable information and enhance the accuracy of the diagnosis algorithms. Consequently, in the present study, the heart rate variability (HRV) signal of subjects who experience sudden cardiac death (SCD) is studied. We looked at people's heart signals for one hour before something happens to see if there are any noticeable changes. The patients' HRV signals are segregated into 5-minute parts in the suggested approach. Each section is divided into four shorter signals. Thereupon, the energy and instant amplitude of each sub-signal are examined. The information flows between signal strengths and measuring the complexity of energy sub-signals are checked. A significant change from its former section is identified. A support vector machine classifier benefits from detecting individuals exposed to SCD by considering significant changes as indicators of the SCD process. It can anticipate SCD 15 minutes before it happens. Not restricted to any special subclass of cardiac diseases, this technique has priority. To evaluate the specificity of the algorithm, it has been used not only with patients having SCD but also with individuals who are healthy, as well as those with coronary artery disease (CAD) and congestive heart failure (CHF), analyzing their HRV signals. The specificity values for normal, CHF, and CAD patients are 100%, 93.3%, and 95.6%, respectively, in the results.

The turn-around task is one of the challenging maneuvers in automated driving which requires intricate decision making, planning and control, concomitantly. During automatic turn-around maneuver, the path curvature is too large which makes the constraints of the system severely restrain the path tracking performance. This paper highlights the path planning and control design for single and multi-point turn of autonomous vehicles. The preliminaries of the turn-around task including environment, vehicle modeling, and equipment are described. Then, a predictive approach is proposed for planning and control of the vehicle. In this approach, by taking the observation of the road and vehicle conditions into account and considering the actuator constraints in cost function, a decision is made regarding the minimum number of steering to execute turn-around. The constraints are imposed on the speed, steering angle, and their rates. Moreover, the collision avoidance with road boundaries is developed based on the GJK algorithm. According to the simulation results, the proposed system adopts the minimum number of appropriate steering commands while incorporating the constraints of the actuators and avoiding collisions. The findings demonstrate the good performance of the proposed approach in both path design and tracking for single- and multi-point turns.

We introduce the notions of $\mathcal{T}_{M}$-amenability and $\phi$-$\mathcal{T}_{M}$-amenability. Then, we characterize $\phi$-$\mathcal{T}_{M}$-amenability  in terms of $WAP$-diagonals and $\phi$-invariant means. Some concrete cases are also discussed.

Increasing population and urbanization have been caused many problems such as: increased traffic in cities, travel time, cost, fuel consumption, air pollution and so on. In the mentioned situation, some methods are needed to increase the safety and efficiency of the transportation system. In this regard, one of the programs that can be implemented to improve transportation is the use of Autonomous Vehicles. These vehicles have attracted the attention of researchers and industries, so that many transportation experts are currently working on this field. This system can act as the basis for economic growth and countries development. In the present study, the roles of AVs in transportation system have been discussed. The main structure of this project is neural network as one of the machine learning methods. The task of this section is to learn the system and make decisions based on the current condition.  Accordingly, the combinations of Dense and Convolutional neural networks and Udacity simulator have been used. It showed that the simulator can help to speed up the process and implementation of AVs. The results indicated that there is high similarity between human driving cars and AVs which are implemented by the Udacity simulator.

Let A and B be Banach algebras with preduals A∗ and B∗ respectively, and Θ : B → A be an algebraic homomorphism. In this paper, we derive some specific results concerning the characterizations of module Connes amenability of certain Banach algebras. Indeed, we investigate and give necessary and sufficient conditions for module Connes amenability of projective tensor product Ab⊗B. Moreover, we characterize the module (ψ, θ)- Connes amenability of Θ-Lau product A×Θ B, which ψ and θ are homomorphisms in A∗ and B∗, respectively.

For a locally compact group $G$, $L^1(G)$ is its group algebra and $L^\infty(G)$ is the dual of $L^1(G)$. We consider on $L^\infty(G)$ the $\tau$-topology, i.e. the weak topology under all right multipliers induced by measures in $L^1(G)$. For such an arbitrary $G$ the $\tau$-topology is not weaker than the weak$^*$-topology and not stronger than the norm topology on $L^\infty(G)$. Among the other results we mention that except for discrete $G$ the $\tau$-topology is always different from the norm-topology. The properties of $\tau$ are then studied further and we pay attention to the $\tau$-almost periodic elements of $L^\infty(G)$.

A great deal of research has been carried out on the classification of residential units and various classifications have been presented. The purpose of this article was to investigate the role of vertical and horizontal density in urban housing typology in order to improve human health and the active living environment of citizens. Therefore, in this article, the typology of housing was discussed from the perspective of horizontal and vertical density in urban housing architecture, and based on the results obtained, factors affecting health were discussed. The assumptions of this research were based on the impact of residential density on flexibility and changeability, the type of environmental arrangement, the number of unconnected houses on the residents' perception of their place of residence. The current research was applied and descriptive non-experimental in terms of its nature and method. Cochran's formula was used for sampling and 385 questionnaires were collected. Sample selection was random and included engineers and architectural specialists at the engineering system organization of Tehran province with at least 15 years of related activity and work experience. Data collection method was through the use of a questionnaire as well as library study by referring to available documents in scientific and authoritative articles. The validity of the questionnaire was obtained by formulating the questions based on the theoretical foundations of the research and with the comments and approval of the above-selected engineers and architectural experts. In order to confirm the reliability of the questionnaire, Cronbach's alpha coefficient was used and values ​​above 0.7 were considered acceptable. The mean test was calculated on the main and specific hypotheses in SPSS22 software and at a confidence level of 0.95. The results demonstrated that all research hypotheses were confirmed. As a result of this research, effective factors in human health and living environment were identified and recommendations were made for using all factors.

The current study uses heart rate variability (HRV) signal processing to investigate changes in the multifractal dimension in congestive heart failure (CHF) patients and predict sudden cardiac death (SCD). In this regard, HRV signals are first extracted, and their four sub-signals are determined using the Local Characteristic Decomposition (LCD) method. In the next step, using the Teager Energy method, the instant amplitudes of each sub-signal obtained in the previous step are calculated; thus, new signals are generated based on these instant amplitudes. Employing multifractal detrended fluctuation analysis (MF-DFA), the modified fractal dimensions of each new signal are then obtained. With the t-test method, appropriate features are selected and input into the support vector machine (SVM) classifier. By detecting subtle changes in HRV signals, this method can detect SCD in CHF patients.  The results indicate that the proposed algorithm can distinguish the signals of SCD subjects with an accuracy of 84.76% 26 minutes before the event. In addition, after passing each 5-minute interval, the proposed method can update and determine how much time is left before SCD occurs

The coordinated control of autonomous electric vehicles with in-wheel motors is classified as over-actuated control problems requiring a precise control allocation strategy. This paper addresses the trajectory tracking problem of autonomous electric vehicles equipped with four independent in-wheel motors and active front steering. Unlike other available methods presenting optimization formulation to handle the redundancy, in this paper, the constraints have been applied directly using the kinematic relations of each wheel. Four separate sliding mode controllers are designed in such a way that they ensure the convergence of tracking errors, in addition to incorporating the parametric and modeling uncertainties. The lateral controller is also designed to determine the front steering angles to eliminate lateral tracking errors. To appraise the performance of the proposed control strategy, a co-simulation is carried out in MATLAB/Simulink and Carsim software. The results show that the proposed control strategy has enabled the vehicle to follow the reference path and has converged the errors of longitudinal and lateral positions, velocity, heading angle, and yaw rate. Furthermore, the proposed control system shows promising results in the presence of uncertainties including the mass and moment of inertia, friction coefficient, and the wind disturbances.

The behavior of self-driving cars is categorized into different strategic, tactical and operational levels in a hierarchical structure. In this research, a study at the local planning level aims to design an automatic turning system and Focus on path and maneuver planning (single and multi-point). The turn around maneuver as a common scenario in the required conditions, includes one or more forward and backward movements, in which the vehicle must be in the proper position in the opposite lane of the road and with a heading angle of 180 degrees. Moreover, the condition of collision avoidance is considered during the maneuver. For this purpose, the four-wheeled model of the vehicle with the relevant geometry is described; Next, on the basis of the deduced minimum permissible road width, a decision is made according to the objective of the minimum number of commands. Then the path design is presented using the proposed geometrical method with circle arcs for each initial position and orientation and generalized to the backward turning. The proposed method has advantages such as low computational cost and can be used for different situations of the initial states of the vehicle. The result of the turning simulation with sample vehicle data and continuous evaluation of the most feasible maneuver confirms the efficiency of the chosen planning approach. In a case study for the Samand car, while proper planning was done, a distance reduction of about 11% for the road with a width of 12 meters is observed compared to the path planned by one of the references.

One of the main goals of the resilient discourse in the recent urban design literature has been creating resilient places. Urban resilience is defined by the URFs (urban resilience features) for operation and realization in various fields. Due to continuous urban developments, there is a need to revise URFs with a place-based approach. URFs addressed in literature are so diverse that placing them into one single general list creates many contradictions and ambiguities. To reduce or eliminate inconsistencies in the definition of URFs and the qualitative performance of each URF in delivering urban resilience, this paper justifies the key factors for ordering and classifying URFs. In this study, a systematic review of the literature on urban resilience was performed in five stages using the Scopus databases within the 1973-February 2020 period. Then, 16 URFs, using three guidelines based on the corresponding evaluation of place and resilience, were identified and classified into three groups: (1) the intrinsic (internal) characteristics of the constituent components of a resilient system, (2) the behavioral proxies (proactive/reactive) of a resilient system and (3) the resilience-reinforcing attributes of a system in relation to the external environment. This study can shed light on the proper definition of urban resilience and its operational URFs.

In this paper we develop the notions of Connes amenability for certain product of Banach algebras. We give necessary and sufficient conditions for the existence of an invariant mean on the predual of $\Theta$-Lau product  $\mathcal{A}\times_{\Theta}\mathcal{B}$, module extension Banach algebra $\mathcal{A}\oplus\mathcal{X}$ and projective tensor product $\mathcal{A} \widehat{{\otimes}} \mathcal{B}$, where $\mathcal{A}$ and $\mathcal{B}$ are dual Banach algebras  with preduals $\mathcal{A}_*$ and $\mathcal{B}_*$ respectively and $\mathcal{X}$ is a normal Banach $\mathcal{A}$-bimodule with predual $\mathcal{X}_*$.

The primary purpose of each autonomous exit parking system is to facilitate the process of exiting the vehicle, emphasizing the comfort and safety of driving in the absence of almost any human effort. In this paper, the problem of exit parking for autonomous vehicles is addressed. A nonlinear kinematic model is presented based on the geometric relationship of the vehicle velocities, and a linear time-varying discrete-time model of the vehicle is obtained for utilizing the optimal control strategy. The proposed path planning algorithm is based on the minimization of a geometric cost function. This algorithm works for ample space exit parking in Single-Maneuver and tight spaces in Multi-Maneuver exit parking. Finally, an optimal discrete-time linear quadratic control approach is hired to minimize a quadratic cost function. To evaluate the performance of the proposed algorithm, the control system is simulated by MATLAB/Simulink software. The results show that the optimal control strategy is well able to design and follow the desired path in each of the exit parking maneuvers.

Although ECG signals contain rich enough information about the heart function, neither the clinical cardiologists nor researchers and engineers with their developed algorithms can illustrate all of this hidden information without some ECG pre-processing attempts. The standard 12- lead ECG signals represent the magnitudes of the heart's electrical activity at any instant in a cardiac cycle. Still, the direction of these signals is not clearly shown in ECG leads. On the other hand, in VCG, we have both the magnitude and direction of the heart's electrical signal, but the time is hidden. In this paper, a new approach has been proposed that, without requiring complicated calculations, represents and visualizes the magnitude and direction of the heart's electrical activity as a function of time. Unlike the normal 2-dimensional ECG for several leads, in this new 3-dimensional proposed ECG(Time Vector Electrocardiogram), any two arbitrary frontal leads are shown versus time. The resulting curve is independent of the selected leads; thus, only a single 3-dimensional curve is obtained, which contains and illustrates more information about the heart function. Some applications of the proposed method are presented in this paper by using the ECG data for patients from the G12EC database. If this new approach is welcomed by cardiologists and field experts, we believe that it would greatly assist them in diagnosing heart behavior and its possible abnormalities more clearly and much faster.

Due to the high fatalities of head-on accidents, the design of intelligent systems to prevent such severe collisions is essential. In this study, path planning for head-on collision avoidance with a deviated vehicle from the opposite lane has been investigated. The main approach is based on a model predictive controller with 2 seconds of prediction horizon and a linearized prediction model with low errors near the operational conditions. A conservative method is used for lateral motion prediction of the deviated vehicle and based on that, the collision avoidance constraints of the model predictive planner are simply modeled by a new approach. Moreover, a novel method to choose the proper swerve direction of evasive maneuver is proposed. This method is based on keeping the ego vehicle away from dangerous directions and has different criteria for far and close encounters. The final algorithm is capable to control the steering of the prediction model with a constrained lateral acceleration and calculates safe and maneuverable paths for the aforementioned scenario. Four simulations are conducted to validate the algorithm in far and close encountering, and critical conditions of choosing swerve direction. Results show the robustness of the path planner, even to sudden deviations at close distances and with high lateral accelerations.

The concept of resilience has been considered in academia in the last decade. Given that cities are always exposed to constant and sudden dangers, urban resilience is a new path and strategy for urban development. Urban form resilience is a subset of the urban resilience discourse, and although research and articles on urban form resilience and how to evaluate it have been written over the past decade, it is still in the conceptual and exploratory stages. This article tries to make a comparative comparison between urban form resilience assessment tools by explaining the different dimensions of the resilient place assessment toolbox, which is derived from the spatial resilience framework. In this context, urban morphology is defined as the spatial and physical manifestation of human activities resulting from the complex interactions of various social, economic and environmental factors that affect the city's response to natural and man-made hazards. Urban fabrics that do not have the capacity of resilient place are at risk of deterioration of environmental qualities in the process of urban development and extensive changes, and the quality of viability and vitality of these areas declines in the long run. In this regard, the three dimensions of fabric and structure, place and image, environment and behavior as the main dimensions are justified by comparison with other frameworks and toolboxes. By measuring the resilience of urban forms, especially in emerging contexts, this tool can enable urban planners, designers, and policymakers to intervene more effectively against change and risk.

Generalizing the notion of Connes amenability for LM(A, P, m, n), we study Φ- Connes amenability of LM(A, P, m, n) that Φ is a character on LM(A, P, m, n). Among the other things, we study when Φ- Connes amenability of LM(A, P, m, n) is equivalent to φ- Connes amenability of A where φ is the unique character on A associated to Φ. We apply this results to semigroup algebras.

The Internet of everything that is often known as The Internet of Things (IoT), is the next generation internet network that is created by intelligent objects with software and sensors, where machines can communicate with various machines and humans. The IoT industry does not have one clear set of security standards for developers and manufactures to build in consistent security. The data collected and stored with these devices such as name, age, health data, location and more can aid cyber-attack activity. The first step to face these threats is to classify it and determine the risk of attacks and threats according to different classes of layers. The present study discusses about various IoT attacks happening, classify them, its countermeasures and finding the most prominent attacks in IoT in different layers.

Let $H$ be a hypergroup with left Haar measure and let $L^1(H)$ be the complex Lebesgue space associated with it. Let $L^\infty(H)$ be the set of all locally measurable functions that are bounded except on a locally null set, modulo functions that are zero locally a.e. Let $\mu\in M(H)$. We want to find out when $\mu F\in L^\infty(H)^*$ implies that $F\in L^1(H)$. Some necessary and sufficient conditions is found for a measure $\mu$ for which if $\mu F\in L^1(H)$ for every $F\in L^\infty(H)^*$, then $F\in L^1(H)$.

In this paper, an algorithm is presented for a swarm motion stability based on Lagrange equations. Having virtual energy sources, the mentioned algorithm is designed and applying energy values to Lagrange equations the swarm members move toward the desired target point. Moreover, the presented stability algorithm has been generalized to prevent collision between members of the swarm as well as avoid collision with obstacles and two repulsive operators have been designed to guaranty the safety of the swarm members along the path. Arriving of all members at the target point, an aggregation switch is designed for members’ aggregation. Prioritizing on experimental works, this feature enables the swarm members move more freely and cover a greater area along the path. It is also possible to define and arrange virtual obstacles in any desired layouts (e.g., narrow corridor) in order to achieve different goals such as avoiding an area, guiding the swarm in the desired direction, etc. the presented algorithm is suitable for identification, navigation, search and rescue, protection, etc. Using MATLAB software this algorithm is simulated and validated for the movement of swarm robots in both two- and three-dimensional spaces covering different conditions. The simulation results demonstrate the capabilities and efficiency of the presented algorithm for application in swarm motion.

 In response to a wide range of challenges and problems arising from social and economic change, spatial resilience as a late theory of urban resilience is being developed and conceptualized in both theoretical and practical areas. However, the conceptual implications of spatial resilience, especially in the field of urban design, have not been clearly explainedyet and its implications in other fields have been used sparsely in the field of urban design.

Spatial resilience in many respects represents a new-multidimensional discourse approach to place-based urban resilience, where the urban system produces and reproduces adaptability and variability vis-a-vis change. This paper seeks to develop a general framework to create a resilient place based on the relationship between spatial resilience and urban design. Moreover, it aims to determine the conceptual framework for the urban spatiality of resilience.

This study examines the spatial resilience literature based on the conceptual framework of the RPA. This study performed a systematic review of spatial resilience literature in four stages by searching the term “spatial resilience” in the Scopus database from 1973 to May 2020. Finally, 14 articles were selected for content analysis.

Spatial resilience implies the place-based and local aspects of the urban system and its integration with higher scales. Intra- and inter-scale interactions and trade-offs transformability and adaptability, innovation and creativity, co-evolution, and place identity are the five influential features of spatial resilience.Beyond traditional resilience with an engineering approach, spatial resilience emphasizes the integration of resilience policies with other policies and programs that affect the nature of places and how they operate.

Temporal point of view examines time in the narrative and the three ‎main aspects of order, duration and frequency are discussed in it, which ‎should be examined in the whole text and not in one sentence. This article ‎descriptively and analytically examines the temporal point of view in the ‎story of Abraham 7 as the ancestor of the monotheistic religions and Lot 7 ‎as his cousin and that the story is intertwined in the two holy books of the ‎Holy Quran and the Old Testament. The results show that the general ‎ideology that dominates both of these books has a direct effect on their ‎temporal point of view. The order in the story of the Old Testament is ‎more prominent than the Holy Quran and the time of recitation is more in ‎harmony with the time of narration in the Holy Quran than the Old ‎Testament. Also, the frequency is repetitive in the Holy Quran whereas in ‎the Old Testament it is often singular. These cases originate from the ‎ideology of the Quran, which is directional and educational, while the ‎Old Testament is historical, and tries to express it in general‏.‏

The distributed structure of cloud computing makes it an attractive target for potential cyberattacks by intruders. In this paper, using the anomaly detection approach, a method for embedding an intrusion detection system for cloud computing is presented. Therefore, by studying how to check the parameters and the combined role of the parameters in the detection of penetration in the cloud, a method for detecting suspicious behavior in the cloud is provided. The most logical way to detect an intrusion is to use supervised methods to learn the parameters of normal customer behavior. Therefore, the detection of biased behavior in the form of suspicious behavior was implemented and discussed, investigated, and compared with an initial simulation in the form of identifying abnormal behavior in different behavioral areas by the neural network. In this article, the basis of abnormality detection in different aspects is to examine the behavior of users and use the capabilities of reproducing inputs in RNN neural networks. In these networks, during the training of the network, the weights are adjusted in such a way that they can minimize the average square of the error so that the network can produce common repeating patterns well. Therefore, after training, these networks cannot reproduce well the input patterns that are actually significantly different from the training samples. Hence, these networks are able to identify anomalies in the tested sets. Accordingly, RNN networks are used here to model normal behavior. The simulation results show that the proposed method, which is based on the recurrent neural network, can improve the false positive, false negative, and detection accuracy compared to the classification method. In this article, the detection of biased behavior in the form of suspicious behavior was implemented and discussed, investigated, and compared with an initial simulation in the form of identifying abnormal behavior in different behavioral fields. The simulation results show that the proposed method, which is based on the iterative neural network, can improve the false positive, false negative, and detection accuracy compared to the classification method.

Lane Change at high speeds is a strategic maneuver to avoid the collision. In this situation, The time of an accident possibility is mainly less than two seconds. therefore, finding the proper trajectory and control of the vehicle is crucial at the lowest cost. In this paper, based on a skilled driver’s performance in a similar situation, a proper path and corresponding appropriate control system was designed aiming at vehicle stability preserving and collision avoidance. To this purpose, possible paths were simulated and identified using the vehicle's seven degrees of freedom model and applying the driver’s behavior. A neural network system was trained; then, the trajectory was chosen. A hybrid controller was hired for the vehicle navigation, consisting of the driver's performance pattern with a covering neural network and two proportional derivative controllers. The Novelties of this method are the simultaneous design of a stable path while maintaining geometric constraints and the low computational burden of the path planning and control system. The results show that the highest neural network error is about 11%. Also, the control system has been able to steer the vehicle and follow the trajectory with 40cm maximum lateral displacement error in the speed and road friction different conditions.