Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents
Issue:
Volume 9, Issue 4, August 2020
Pages:
24-34
Received:
11 September 2020
Accepted:
24 September 2020
Published:
29 September 2020
Abstract: At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified agents with strong artificial intelligence based on communicative-associative logic by recurring development of professional skills, increasing visual, sound, subject, spatial and temporal sensitivity. For this purpose several diversifiable agents that try to get the same conclusion will give a more accurate result, so several diversifiable agents are combined into an ensemble. Then, based on the criteria of utility and preference, the final result is obtained based on the conclusions of diversifying agents. This approach increases accuracy. Bagging and Boosting techniques are used to form ensembles. Bagging is a combination of independent diversifiable agents by averaging patterns (weighted average, majority vote, or normal average). Boosting is the construction of ensembles of diversifiable agents consistently. The idea here is that the next agent will consider the errors of the previous agent. Due to the fact that diversifiable agents take into account errors committed by previous agents, it takes less time to get to a real response. The combination of Bagging and Boosting decision-making methods allows the development of intelligent artificial intelligence by ensembles of diversified agents. Cognitive virtual smart artificial intelligence becomes smarter through the accumulated professional experience of high-tech skills, competencies and knowledge, having increased visual, sound, subject, spatial and temporal sensitivity. Many researchers believe that the information technology industry is on the verge of a transition to smart universal artificial intelligence. The information technology industry is trying to find the boundaries of smart artificial intelligence. Standardization of strong artificial intelligence and the use of ensembles of intelligent compatible diversified agents will help to find boundaries in which smart artificial intelligence will benefit humanity and not harm.
Abstract: At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified age...
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Prediction of Leaves Using Convolutional Neural Network
Abhishek Agarwal,
Rohini Venkat
Issue:
Volume 9, Issue 4, August 2020
Pages:
35-38
Received:
24 February 2020
Accepted:
17 March 2020
Published:
27 October 2020
Abstract: Plants have a significant role in every corner, let it be for humans, animals, and the environment. They play a significant role in saving each other lives by providing each one with the necessities. For saving these plants, humans should be able to identify the plants in order to give proper treatment to the plants. The species of the plants can be easily identified by the venation of the leaves. This paper focuses on the Convolution Neural Networks (CNN) classification methodology, which helps to classify the leaves accurately. The work uses leaf images of apple, grape and tomatoes from the plant village dataset for getting the features and further classification of the leaves. The prediction of the leaves will be done by using the deep learning techniques in which the input layer will be the features extracted using the proposed algorithm. The proposed algorithm is based on Local Binary Pattern (LBP), which is a simple yet very efficient method to identify the pixels of the image by threshold in the neighborhood of each pixel and consider the result as a binary number. The proposed algorithm is efficient for its computational simplicity, which makes it possible to analyze images in challenging real-time settings in the field of image processing and computer vision.
Abstract: Plants have a significant role in every corner, let it be for humans, animals, and the environment. They play a significant role in saving each other lives by providing each one with the necessities. For saving these plants, humans should be able to identify the plants in order to give proper treatment to the plants. The species of the plants can b...
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Clinical Instructors’ Perceptions About the Characteristics of an Effective Clinical Instructor and Clinical Training Policies in Gaza Strip
Mahmoud Elkhateeb,
Hamza Abdeljawad
Issue:
Volume 9, Issue 4, August 2020
Pages:
39-43
Received:
23 May 2020
Accepted:
15 June 2020
Published:
27 October 2020
Abstract: The overall aim of this study is to assess the clinical instructors’ perceptions about the characteristics of an effective clinical instructor and clinical training policies at the colleges that run bachelor of nursing programs in Gaza Strip. A descriptive-analytical cross-sectional study was used. The research participants were selected through quota sampling. The sample size included 182 clinical instructors from five colleges and universities. Self-administered questionnaires were distributed. Cronbach's alpha was calculated for the questionnaire by more than 0.7. Data were analyzed by using Statistical Package for Social Sciences (SPSS) version 23. The findings showed that the male clinical instructors represented 64% of the respondents while the female 36%. The data indicated with regard to the qualifications of clinical instructors found that most of them had just a bachelor's degree (81.3%) and the remaining had a master's degree (18.7%). According to the results, the highest characteristic was “Professional Competence / Knowledge” with weighted mean 93.73%, followed by “Communication” with weighted mean 89.07% and “Support the professional growth of students” in 3rd rank with weighted mean 87.87%. While the most effective clinical training policies as perceived by clinical instructors were “The role of clinical training department in monitoring of instructors' performance with students is clear” with weighted mean 91.07%, “The clinical instructor evaluates students in a fair and objective manner” with weighted mean 90.67%, and “Selection of training site is relevant to achieve the clinical course objectives” with weighted mean 90.40%. The study concluded that clinical nursing teaching is in need to improve its quality for both, the clinical instructors and policies.
Abstract: The overall aim of this study is to assess the clinical instructors’ perceptions about the characteristics of an effective clinical instructor and clinical training policies at the colleges that run bachelor of nursing programs in Gaza Strip. A descriptive-analytical cross-sectional study was used. The research participants were selected through qu...
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