learning capability
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2022 ◽  
Vol 24 (2) ◽  
pp. 0-0

In last decade, there has been a growing awareness in E-Learning which is the most recent type of distance education, and becomes a highly significant model of educational technology. Today e-Learning studies indicate that there is an increasing use of this educational scheme for students, trainers and instructors which improve the learning capability of the students and trainee by depending on student-centered learning (SCL) scheme rather than using the traditional teacher or trainer centered teaching mechanism.However, students’ awareness for the advantage of using e-Learning has not been significantly investigated, especially in Iraq. The aim of this article is to inspect students’ awareness of the using of e-Learning at the Dohuk Polytechnic University. Participants involved in this study were 100 students studying the C++ programming language course during 2015-2016 and 2017-2018 academic years and 210 students studying computer application course during 2018-2019.


2022 ◽  
Vol 24 (2) ◽  
pp. 1-11
Author(s):  
Abdulraheem Jamil Ahmed ◽  
Falah Hasan Mohammed ◽  
Naji Abdullah Majedkan

In last decade, there has been a growing awareness in E-Learning which is the most recent type of distance education, and becomes a highly significant model of educational technology. Today e-Learning studies indicate that there is an increasing use of this educational scheme for students, trainers and instructors which improve the learning capability of the students and trainee by depending on student-centered learning (SCL) scheme rather than using the traditional teacher or trainer centered teaching mechanism.However, students’ awareness for the advantage of using e-Learning has not been significantly investigated, especially in Iraq. The aim of this article is to inspect students’ awareness of the using of e-Learning at the Dohuk Polytechnic University. Participants involved in this study were 100 students studying the C++ programming language course during 2015-2016 and 2017-2018 academic years and 210 students studying computer application course during 2018-2019.


2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Lizhe Zhang ◽  
Juan He

In the digitized era, life has become simpler with the increased information technology. The Education Department in the whole world is facing a tremendous revolution with the development. The traditional classroom study is converted to a modernized and digitized classroom with visualization. This modernization has increased the learning capability of the students with an increase in student and teacher interaction. From this teaching and learning process, most colleges and universities have improved performance in preparing course materials, effective teaching, and independent learning among the students in the theoretical courses. Ideological and political education (IPE) is a theoretical subject that is taught and understood at higher education institutions, such as colleges and universities. A hybrid hierarchical K -means clustering for optimizing clustering with unsupervised machine learning is proposed to analyze the student performance and concluded that the proposed algorithm shows improved performance than the K -means algorithm.


Author(s):  
Mohit Kumar Gautam ◽  
Sanjay Kumar ◽  
Shaibal Mukherjee

Abstract Here, we report a fabrication of Y2O3-based memristive crossbar array along with an analytical model to evaluate the performance of such memristive array system to understand the forgetting and retention behavior in the neuromorphic computation. The developed analytical model is able to simulate the highly-dense memristive crossbar array based neural network of biological synapses. These biological synapses control the communication efficiency between neurons and can implement the learning capability of the neurons. During electrical stimulation of the memristive devices, the memory transition is exhibited along with the number of applied voltage pulses which is analogous to the real human brain functionality. Further, to obtain the forgetting and retention behavior of the memristive devices, a modified window function equation is proposed by incorporating two novel internal state variables in the form of forgetting rate and retention. The obtained results confirm that the effect of variation in electrical stimuli on forgetting and retention as similar to the biological brain. Therefore, the developed analytical memristive model further can be utilized in the memristive system to develop real-world applications in neuromorphic domains.


2022 ◽  
pp. 327-348
Author(s):  
José G. Vargas-Hernández

The purpose of this study is to analyze the strategic organizational learning approach to dynamic resilient capabilities. A scoping review of the theoretical and empirical literature on organizational dynamic resilience capability reveals gaps to be addressed to improve the conceptualization. Under the assumption of some attributes and properties, it is viable to study the organizational resilience learning process leading to the analysis of the organizational resilience strategies. Resilience is addressed through turnaround and dynamic capabilities. Organizational resilience is critical to possessing dynamic capabilities attracting new resources, design strategies, and learning to overcome rigidity and regain stability.


Author(s):  
Hao Ji ◽  
Yan Jin

Abstract Self-organizing systems (SOS) are developed to perform complex tasks in unforeseen situations with adaptability. Predefining rules for self-organizing agents can be challenging, especially in tasks with high complexity and changing environments. Our previous work has introduced a multiagent reinforcement learning (RL) model as a design approach to solving the rule generation problem of SOS. A deep multiagent RL algorithm was devised to train agents to acquire the task and self-organizing knowledge. However, the simulation was based on one specific task environment. Sensitivity of SOS to reward functions and systematic evaluation of SOS designed with multiagent RL remain an issue. In this paper, we introduced a rotation reward function to regulate agent behaviors during training and tested different weights of such reward on SOS performance in two case studies: box-pushing and T-shape assembly. Additionally, we proposed three metrics to evaluate the SOS: learning stability, quality of learned knowledge, and scalability. Results show that depending on the type of tasks; designers may choose appropriate weights of rotation reward to obtain the full potential of agents’ learning capability. Good learning stability and quality of knowledge can be achieved with an optimal range of team sizes. Scaling up to larger team sizes has better performance than scaling downwards.


Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ye Tian ◽  
Yang Zhao ◽  
Shengping Liu ◽  
Qiang Li ◽  
Wei Wang ◽  
...  

Abstract Photonic computation has garnered huge attention due to its great potential to accelerate artificial neural network tasks at much higher clock rate to digital electronic alternatives. Especially, reconfigurable photonic processor consisting of Mach–Zehnder interferometer (MZI) mesh is promising for photonic matrix multiplier. It is desired to implement high-radix MZI mesh to boost the computation capability. Conventionally, three cascaded MZI meshes (two universal N × N unitary MZI mesh and one diagonal MZI mesh) are needed to express N × N weight matrix with O(N 2) MZIs requirements, which limits scalability seriously. Here, we propose a photonic matrix architecture using the real-part of one nonuniversal N × N unitary MZI mesh to represent the real-value matrix. In the applications like photonic neural network, it probable reduces the required MZIs to O(Nlog2 N) level while pay low cost on learning capability loss. Experimentally, we implement a 4 × 4 photonic neural chip and benchmark its performance in convolutional neural network for handwriting recognition task. Low learning-capability-loss is observed in our 4 × 4 chip compared to its counterpart based on conventional architecture using O(N 2) MZIs. While regarding the optical loss, chip size, power consumption, encoding error, our architecture exhibits all-round superiority.


2021 ◽  
Vol 12 (4) ◽  
pp. 18-41
Author(s):  
Murat Çemberci ◽  
Mustafa Emre Civelek ◽  
Yonca Gürol ◽  
Perlin Naz Cömert

Learning, which is the main key of innovation, is an indispensable element for companies to gain sustainable competitive advantage. Although not being adequately studied in management literature, network learning capability, a type of organizational learning ability, is a determining factor in the innovation process. Likewise, open-mindedness is a component that accelerates the creation of knowledge in the organization as well as encouraging the organization to be open towards new opportunities and to value different opinions. In this study, a model including these variables was designed and the mediator role of network learning in the relationship between open-mindedness and innovation performance was explored. It is suggested that open-mindedness has a positive effect on innovation performance and that network learning capability possesses a mediator role in this relationship. The data were collected through surveys answered by the middle and senior managers of Turkey’s leading companies. As a result, it is pointed out that there is a positive and significant relationship between open-mindedness and innovation performance, and that network learning has a mediator effect on this relationship. This study adds value to the management literature by highlighting the momentousness of network learning capability in the innovation process as well as offering several avenues of future studies and implications for different stakeholders.


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