• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.249-261
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• 2022

Globally, COVID-19 has significantly impacted many different organizations and people. From the banks' perspective, this pandemic has affected banks' corporate and retail customers. Also, banks had to adjust to distributed workforce model. This paper analyses the lessons learned from the COVID-19 pandemic, which can be effectively used to rebuild banks' Operational Risk Management capabilities. The present study used the survey research methodology, which includes structured questionnaires completed by senior banking professionals to analyze the learnings from COVID-19 and understand the distributed workforce model and remote working effectiveness. Findings: The Pandemic accelerated the pace of digital transformation. The lockdown imposed due to the pandemic led to employees working remotely, which has been effective because of enhanced digital capabilities. However, enhanced monitoring is required to prevent data-related issues, and action needs to be taken to address challenges faced in having a remote distributed workforce model, like negative impact on on-the-job learning, data-related risks, and employee wellbeing. COVID-19 is an unprecedented event that could not have been predicted in any scenario analysis. This crisis has highlighted various systemic drawbacks that need to be addressed. Banks can apply the lesson learned from this Pandemic to become more robust in the future.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.661-668
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• 2022

Various lean design and construction methods such as target value design, pull planning, value stream mapping have successfully transformed the commercial building construction industry into achieving improved productivity, higher design and construction quality, and meeting the target values of construction projects. Considering the significant advantages of lean, the accelerated dissemination and adoption of lean methods and tools for construction is highly desirable. Currently, the lean design and construction body of knowledge is imparted primarily through publications and conferences. However, one of the most effective ways to impart this soft knowledge is through getting students and trainees involved in hands-on participatory games, which can quickly help them truly understand the concept and apply it to real-world problems. The COVID-19 Pandemic has raised an urgent need of developing virtual games that can be played simultaneously from various locations over the Internet, but these virtual games should be as effective as in-person games. This research develops an online 3D simulation game for Target Value Design that is as effective as in-person games or possibly better in terms of knowledge capture and retention and enjoyable environment and experience. The virtual game is tested on volunteers using feedback from pre-and post- simulation surveys to evaluate its efficacy.

• Journal of Distribution Science
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• v.22 no.6
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• pp.83-93
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• 2024

Purpose: The present study is developed with the aim of mapping the trends in scientific production related to the implementation of artificial intelligence systems for agro-food supply chains. Research design, data and methodology: The methodological approach of the research shows a descriptive documentary process based on bibliometric techniques for mapping the main indicators of the area of knowledge through the establishment of a search equation in Scopus. Results: The research results show a total of 633 documents published between 2019 and 2023, with a great annual growth rate of 61.68%; In addition to a notable participation of countries such as India, China, the United Kingdom and the United States in the generation of new knowledge related to artificial intelligence applied to food distribution systems. Conclusions: It is concluded that the rise of new artificial intelligence technologies has shown extremely important results in the development of industries worldwide, with increasingly accelerated steps; which certainly translates into the creation of spaces and incentives in the production of research aimed at understanding these dynamics and in turn to propose new alternatives and proposals for the reduction of the large technological gaps that are present within the agro-food sector.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

• Journal of Gifted/Talented Education
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• v.11 no.3
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• pp.1-21
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• 2001

In general, curriculum is a product of the process of a political decision-making among a variety of peoples who have different perspectives on learners, knowledge, and society as a whole. And also, it is being affected by larger social and political contexts. As curriculum has become more a centerpiece of program activity for the gifted, the field has more emphasized the importance of viable curriculum models. The purpose of this article is to reflect current status of curriculum development for the gifted, explain the commonness and differences of several perspectives on gifted education programs, and lastly, share some experiences to deliberate about several critical issues of which any activity of program development for the gifted should consider. According to Eisner & Valiance (1974), there are five conceptions of curriculum which have shaped the thinking of many educators of what a view of curriculum for the gifted might be ; curriculum as the development of cognitive process, curriculum as technology, curriculum as personal relevance, curriculum as social construction, curriculum as academic rationalism. Although educators have a freedom to choose among these various curriculum orientations, the most effective curricular incorporate or balance all of them to some extent. After reviewing those perspectives on curriculum and several difficulties which are currently confronted at the site of curriculum development, this article have tried to identify the major curriculum efforts of the gifted education field. It focuses on the issues of developing programs for gifted and talented students, rather than on specific program models. As a result, it suggested seven critical issues or value conflicts which should be considered in the process of program development for the gifted: the balance of domain-general abilities of the gifted and domain-specific abilities, mutual consideration of accelerated learning and enrichment learning, separate organization of contents versus integrated organization, the balance of cognitive domain of human development and affective domain, official curriculum versus non-official education experience, individual-oriented learning situation versus group-oriented teaming, and expert-centered approach versus practitioner-centered approach to curriculum development.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.517-522
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• 2001

The appearance of web technology has accelerated a role of the development of the multimedia technology, the computer communication technology and the multimedia application contents. And serveral researches of WBI (Web-based Instruction) system have combined the technology of the digital library and LOD. Recently WBI (Web-based Instruction) model which is based on web has been proposed in the part of the new activity model of teaching-learning. And the demand of the customized coursewares which is required from the learners is increased, the needs of the efficient and automated education agents in the web-based instruction are recognized. But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose "Design of Multi-agent System for Course Scheduling of Learner-oriented using Weakness Analysis Algorithm". First proposed system monitors learner's behaviors constantly, evaluates them, and calculates his accomplishment. From this accomplishment the multi-agent schedules the suitable course for the learner. And the learner achieves a active and complete learning from the repeated and suitable course.le course.

• The KIPS Transactions:PartC
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• v.12C no.1 s.97
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• pp.45-52
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• 2005

A damage scale of information property has been increasing rapidly by various illegal actions of information systems, which result from dysfunction of a knowledge society. Reinforcement in criminal investigation requests of network security has accelerated research and development of Intrusion Detection Systems(IDSs), which report intrusion-detection about these illegal actions. Due to limited designs of early IDSs, it is hard for the IDSs to cope with tricks to go around IDS as well as false-positive and false-negative trials in various network environments. In this paper, we showed that this kind of problems can be solved by using a Virtual Protocol Stack(VPS) that possesses automatic learning ability through an optimum-adaptive mobile code. Therefore, the enhanced IDS adapts dynamically to various network environments in consideration of monitored and self-learned network status. Moreover, it is shown that Insertion/Evasion attacks can be actively detected. Finally, we discussed that this method can be expanded to an intrusion detection technique that possesses adaptability in the various mixed network environments.

• KIEAE Journal
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• v.15 no.2
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• pp.27-35
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• 2015

Purpose: Healthcare is on the whole a personal and critical service that consumer's use, whereas hospitalization is as a rule painful, because nature nurtures and Sun Light Luminosity for healthcare settings is considered healing. The performance and design of climate responsive buildings such as AKU requires a detailed study of attributes of climate both at micro as well as macro level. The therapeutic value of contact with nature through window view, greenery and landscape is calculated there. Method: A two prong strategy is been devised for this article, at micro level three typical morphologies are analysed by creating same environment of neighboring building on sun shading chart, radiation and temperature range. Since the analysis of local climate helps to determine the design strategies for hospital Healing Environment which is suitable for Karachi climate; in order to track the macro climatic behaviour, a considerable analysis of psychometrics chart for AKU Karachi are designed on Climate Consultant (CC) and analysed by Machine Learning. Climate Consultant proposes different design strategies suitable for Karachi. And on the other hand time wise illumination sources for clinical area which are then measured on psychrometric chart- according to singular space: multi patient admission, secondly: acute ambulatory ward, and tertiary: multi windowed space according to the mushrabiyah and sky light pattern. Result: Our findings support the hypothesis that windowed wall is 75-80% more healing wall; an accelerated evidence was found for healing at macro level if the form of the hospital is designed according to the climatologically preferences, whereas at micro level: the light resource becomes the staff attentiveness determinant. In Conclusion evidence was provided that the actual form of luminosity results consequently in satisfaction while light entering from several set of windows and other sources might be valued if design according to the healing environment. The data added on the sun shading chart to calculate rays entraining into space in patient room equal to 124416.21 Watts/ meter $m^2$ is calculated as precise healing rate-and is confirmed by questionnaire from patients belonging from each clinical stage having different illnesses.

• Archives of Plastic Surgery
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• v.40 no.4
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• pp.312-319
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• 2013

Over the past decade, driven by advances in educational theory and pressures for efficiency in the clinical environment, there has been a shift in surgical education and training towards enhanced simulation training. Microsurgery is a technical skill with a steep competency learning curve on which the clinical outcome greatly depends. This paper investigates the evidence for educational and training interventions of traditional microsurgical skills courses in order to establish the best evidence practice in education and training and curriculum design. A systematic review of MEDLINE, EMBASE, and PubMed databases was performed to identify randomized control trials looking at educational and training interventions that objectively improved microsurgical skill acquisition, and these were critically appraised using the BestBETs group methodology. The databases search yielded 1,148, 1,460, and 2,277 citations respectively. These were then further limited to randomized controlled trials from which abstract reviews reduced the number to 5 relevant randomised controlled clinical trials. The best evidence supported a laboratory based low fidelity model microsurgical skills curriculum. There was strong evidence that technical skills acquired on low fidelity models transfers to improved performance on higher fidelity human cadaver models and that self directed practice leads to improved technical performance. Although there is significant paucity in the literature to support current microsurgical education and training practices, simulated training on low fidelity models in microsurgery is an effective intervention that leads to acquisition of transferable skills and improved technical performance. Further research to identify educational interventions associated with accelerated skill acquisition is required.