The Global Conference on Technology and Information Management (GCTIM) 2020 served as a platform for global community of individuals passionate about technology and information management, facilitating the exchange of ideas and insights across borders. The conference successfully brought together 85 researchers, students, and scientists from diverse backgrounds featuring an array of paper and poster presentations along with keynote speeches and other engaging talks.
Conference Date: 15 February 2020
Conference Venue: UBC Robson Square, Vancouver, Canada
The conference received a high number of submissions from around the world, reflecting the global interest and relevance of the event. These submissions were subjected to a rigorous and fair double-blind peer review process. The reviewers provided constructive feedback and recommendations based on the quality, originality, relevance, and clarity of the submissions. The accepted submissions showcased the best and most recent research and practice in computer science and its applications.
This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Paper 1: A Quantitative Model for Replacement of Medical Equipment Based on Technical and Environmental Factors
Abstract: Medical equipment operation state is a valid reflection of health care organizations performance, where such equipment’s highly contribute to the quality of healthcare services on several levels in which quality improvement has become an intrinsic part of the discourse and activities of health care services. In healthcare organizations, clinical and biomedical engineering departments play an essential role in maintaining the safety and efficiency of such equipment’s. One of the most challenging topics when it comes to such sophisticated equipment’s is the lifespan of a medical equipment where many factors will impact such characteristic of a medical equipment through its life cycle. So far, many attempts have been made in order to address this issue where most of the approaches are kind of arbitrary approaches and one of the criticisms of existing approaches trying to estimate and understand the lifetime of a medical equipment lies under the enquiry of what are the environmental factors that can play into such a critical characteristic of a medical equipment. In an attempt to address this short coming the purpose of our study rises where in addition to the standard technical factors taken into consideration through the decision making process by a clinical engineer in case of medical equipment failure, the dimension of environmental factors shall be added. The investigations, researches and studies applied for the purpose of supporting the decision making process by a clinical engineers and assessing the lifespan of healthcare equipment’s in the Lebanese society was highly dependent on the identification of technical criteria’s that impacts the lifespan of a medical equipment where the affecting environmental factors didn’t receive the proper attention. The objective of our study is based on the need of introducing a new well-designed plan for evaluating medical equipment’s depending on two dimensions. According to this approach, the equipment’s that should be replaced or repaired will be classified based on a systematic method taking into account two essential criteria’s, the standard identified technical criteria and the added environmental criteria.
Authors: Ghadeer El-Sheikh1, Samer Shalhoob2
Paper 2: Data-Mining Accuracy Boost Technique for Software Deformity Prophecy Datasets Model
Abstract: Data Mining is characterized as data mining or an endeavor to extricate significant and valuable data on a huge database. Data mining investigation can be utilized to settle on business choices that would improve cost, income and operational productivity of human services industry while keeping up elevated levels of patient consideration. In machine learning area, Software Deformity Prophecy datasets model is actuated on the arrangement of preparing information which capacities dependent on a lot of rules to separate among defected and non-defected datasets model. In this manner, the capacity of these Software Deformity Prophecy datasets model to classify a module is fundamentally a component of the nature of preparing dataset. In order to boost the accuracy of classification model for Software Deformity Prophecy datasets model, the most proper methods in each progression of preprocessing is Discretization. A data preprocessing technique called Discretization we have used in our research for software deformity prophecy datasets model. This is our classification accuracy boost technique for our software deformity prophecy datasets model. For observation and analysis, we have used multiple classifiers for getting the boost accuracy with the help of discretization preprocess method. All experiments analysis clearly showed that all classifiers cannot be perfect for the accuracy and efficiency in software deformity prophecy datasets models. In case of correctly classified instances where we easily can judge the improvement of every classifiers that decision stump, hoeffding tree and lmt, their effciency and accuracy is not very good but increased as compare to use these without discretization way. The position of stacking is quite bad and not good to use in these experiments because their efficiency and accuracy have not increased but seems to be worst in all case.
Authors: Maaz Rasheed Malik1, Liu Yining2, Salahuddin Shaikh3
Paper 3: A New Horizon of Data Communication through Quantum Entanglement
Abstract: By the blessing of our existing data communication system, we can communicate or share our information with each other in every nook and corner of the world within some few seconds but there are some limitations in our traditional data communication system. Every day we are trying to overcome these limitations and improve our systems for better performance. Among them some problems may not be resolvable, for the reason of very basic or root dependencies of physics. In this paper, we have clarified some main drawbacks in our traditional communication system and provided a conceptual model to overcome these issues by using mystic Quantum Entanglement theorem rather than classical or modern physics phenomenon. In the end, we introduced a possible Quantum circuit diagram and Quantum network architecture for end-to-end data communication. It is predicted that through this hypothetical model data can be transmitted faster than light and it will be 100% real time between any distances without any kinds of traditional communication medium that are being used to date.
Authors: S.M. Rashadul Islam1, Md. Manirul Islam2, Umme Salsabil3
Paper 4: Improved Face Recognition based on Hidden Markov Model
Abstract: In this paper, a new face recognition technique based on Hidden Markov Model (HMM), Pre-processing, and feature extraction (K-means and the Sobel operator) is proposed. Two main contributions are presented; the first contribution in the pre-processing were image’s edges are normalized to enhance the HMM models to be non-sensitive to different edges. The second contribution is a new technique to extract the image's features by splitting the image into non-uniform height depending on the distribution of the foreground pixels. The foreground pixels are extracting by using the vertical sliding windows. The proposed technique is faster with a higher accuracy with respect to other techniques which are investigated for comparison. Moreover, it shows the capability of recognizing the normal face (center part) as well as face boundary.
Authors: Sameh Magdy1, Mohamed Ibrahim2
Paper 5: An IoT Based Water-Logging Detection System: A Case Study of Dhaka
Abstract: With a large number of populations, many problems are rising rapidly in Dhaka, the capital city of Bangladesh. Water-logging is one of the major issues among them. Heavy rainfall, lack of awareness and poor maintenance causes bad sewerage system in the city. As a result, water is overflowed on the roads and sometimes it gets mixed with the drinking water. To overcome this problem, this paper realizes the potential of using Internet of Things to combat water-logging in drainage pipes which are used to move wastes as well as rainwater away from the city. The proposed system will continuously monitor real time water level, water flow and gas level inside the drainage pipe. Moreover, all the monitoring data will be stored in the central database for graphical representation and further analysis. In addition to that if any emergency arises in the drainage system, an alert will be sent directly to the nearest maintenance office.
Authors: Md. Manirul Islam1, Md. Sadad Mahamud2, Umme Salsabil3, A A M Mazharul Amin4, Samiul Haque Suman5
Paper 6: Adoption of Cloud Based E-learning in Lebanon: Examining the Mediating Role of Attitude
Abstract: Cloud computing (CC) has created a paradigm shift in using technology. Prior literature focused on the adoption of this technology among business organization while studies that are related to educational institutions are few. The aim of this study is to investigate the factors that affect the cloud based e-learning (CBEL) adoption among students in Lebanon. Based on the literature, it is proposed that performance expectancy (PE), effort expectancy (EE), social influence (SI), and user satisfaction affect the behavioural intention (BI). BI is expected to affect the adoption of CBEL. In addition, attitude is proposed to mediate the effect of PE, EE, SI and user satisfaction on BI. The population of this study is four universities in Lebanon. Stratified sampling technique was used to collect the data using a questionnaire. A total of 422 students participated in this study. Data was analyzed using Smart Partial Least Square (PLS). The findings indicated that the user satisfaction is the most important predictors of BI followed by PE, SI, and EE. BI affected use behaviour significantly. Attitude mediated the effects of SI and user satisfaction on BI. Decision makers are recommended to focus on user satisfaction and increase the benefits of CBEL.
Authors: Mohammad kayali1, Nurhizam Safie2, Muriati Mukhtar3
Paper 7: Real Time Systems in Computer Vision and Recognition of Images
Abstract: The importance of micro-expression is that micro-expressions occur in a meaningless way, that is, they occur in a forced, disobedient way, thus revealing human emotions. These statements can be useful for criminal investigations, airport security, forensic science, and especially for psychological expertise. The article describes the development of models and algorithms for systematic analysis of digital camera data in real time.
Authors: Islomjon Mirzakbarov1