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Section: csiReview of Pedagogical Principles of Cyber Security Exercises
Modern digitalized cyber domains are extremely complex ensemble. Cyber attacks or incidents against system may affect capricious effects for another system or even for physical devices. For understanding and training to encounter those effects requires an effective and complex simulation capability. Cyber Security Exercises are an effective expedient for training and learning measures and operations…
Read MoreAdvances in Optimisation Algorithms and Techniques for Deep Learning
In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…
Read MoreContextual Word Representation and Deep Neural Networks-based Method for Arabic Question Classification
Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…
Read MoreShape Optimization of Planar Inductors for RF Circuits using a Metaheuristic Technique based on Evolutionary Approach
In this article, we concentrate on the use of a metaheuristic technique based on an Evolutionary Algorithm (EA) for determining the optimal geometrical parameters of spiral inductors for RF circuits. For this purpose, we have opted for an optimization procedure through an enhanced Differential Evolution (DE) algorithm. The proposed tool allows the design of optimized…
Read MoreISR Data Processing in Military Operations
This paper provides an overview of Intelligence, Surveillance, and Reconnaissance (ISR) data with respect on NATO standards and recommendations; further presents methods, tools, and experiences in ISR data processing in military operations. The steps of the Intelligence cycle and disciplines Business Intelligence (BI), Data Warehousing, Data Mining, and Big Data are presented in the introduction.…
Read MoreAssessing Heutagogical Elements in Learning of Engineering Education: Instrument Validation
Practically level of design element (i.e., explore, sharing, connect) is an essential of heutagogical approach. The self-determined learning process can be at ease with the implementation of these elements, and the critical step is reliability to measure teaching and learning feedback. Although various instruments were proposed in the literature to assess heutagogy elements, the specific…
Read MoreFour-Dimensional Sparse Data Structures for Representing Text Data
This paper focuses on a string encoding algorithm, which produces sparse distributed representations of text data. A characteristic feature of the algorithm described here, is that it works without tokenizing the text and can avoid other data preparation steps, such as stemming and lemmatization. The text can be of arbitrary size, whether it is a…
Read MoreQuantitative Approach in Enhancing Decision Making Through Big Data as An Advanced Technology
The technology of Big Data got the capability to process large amounts of data, manage them effectively and make retrieval whenever it is required. Decision making in any organisation is a challenging task since decisions need to be made based on the accessibility of data and its status, this becomes more challenging especially in large…
Read MoreFast Stream Cipher based Chaos Neural Network for Data Security in CAN Bus
Vehicle systems are controlled by embedded electronic devices called electronic control units (ECUs). These ECUs are connected together with network protocols. The Controller Area Network (CAN) protocol is widely implemented due to its high fault tolerance. However, the CAN is a serial broadcast bus, and it has no protection against security threats. In this paper,…
Read MoreFine Tuning the Performance of Parallel Codes
We propose a multilevel method to speed highly optimized parallel codes whose runtime increases faster than their workload. This method requires the ability to solve large in- stances by decomposing them into smaller instances. Using a simple parallel computing model, we derive a mathematical model that predicts whether or not our method can im- prove…
Read MoreMentoring Model in an Active Learning Culture for Undergraduate Projects
Senior projects allow students to move the learning process from basic knowledge to an interdisciplinary approach. The purpose of this research is (1) to analysis attitude and perception, which is a collaboration between teachers and students to develop a model for clustering of appropriate advisors and advisee who cooperate in senior project, and (2) to…
Read MoreEthics as a Motivation Indicator in Second Language Vocational Digital Teaching
The non-selective second language course at vocational colleges and universities makes teachers strive at fostering students’ motivation to learn by choosing from a variety of enhancing factors. Teacher’s personality and skills if they comply with pedagogical ethics are considered to be inspiring for students to learn. The aim of this piloting study was to collect…
Read MoreAn Explanatory Review on Cybersecurity Capability Maturity Models
Cybersecurity is growing exponentially day by day in both the public and private sectors. This growth also comes with a new and dynamic cyber-threats risk that causes both sectors’ performance to halt. These sectors must update their cybersecurity measures and must understand the capability and maturity of their organization’s cybersecurity preparedness. Cybersecurity maturity models are…
Read MoreA Review on Cross-Layer Design Approach in WSN by Different Techniques
Wireless Sensor Networks (WSN) include a large number of sensor nodes that are connected to each other with the limitations in energy sources, battery life, memory, mobility and computational capacity. Since the traditional layered architecture was appropriate only for the wired network. It works within a strict boundary that leads to more energy usage as…
Read MoreClustering of Mindset towards Self-Regulated Learning of Undergraduate Students at the University of Phayao
The effects of Covid-19 severely affected the Thai higher education model. Therefore, there are three significant objectives in this research: (1) to cluster the mindsets and attitudes toward self-regulated learning styles of undergraduate students at the University of Phayao. (2) to construct a predictive model for recommending an appropriate student learning clusters. (3) to evaluate…
Read MoreCorrelation-Based Incremental Learning Network for Gas Sensors Drift Compensation Classification
A gas sensor array is used for gas analysis to aid in an inspection. The signals from the sensor array are fed into machine learning models for learning and classification. These signals are characterized by time series fluctuating according to the environment or drift. When an unseen pattern is entered, the classification may be incorrect,…
Read MoreMachine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read MoreCustomer Satisfaction Recognition Based on Facial Expression and Machine Learning Techniques
Nowadays, Customer satisfaction is important for businesses and organizations. Manual methods exist, namely surveys and distributing questionnaires to customers. However, marketers and businesses are looking for quick ways to get effective and efficient feedback results for their potential customers. In this paper, we propose a new method for facial emotion detection to recognize customer’s satisfaction…
Read MoreApplication of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition
The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD,…
Read MoreDecision Making System for Improving Firewall Rule Anomaly Based on Evidence and Behavior
Firewalls are controlled by rules which often incur anomalies. The anomalies are considered serious problems that administrators do not desire to happen over their firewalls because they cause more vulnerabilities and decrease the overall performance of the firewall. Resolving anomaly rules that have already occurred on the firewall is difficult and mainly depends on the…
Read MoreThe Sound of Trust: Towards Modelling Computational Trust using Voice-only Cues at Zero-Acquaintance
Trust is essential in many interdependent human relationships. Trustworthiness is measured via the effectiveness of the relationships involving human perception. The decision to trust others is often made quickly (even at zero acquaintance). Previous research has shown the significance of voice in perceived trustworthiness. However, the listeners’ characteristics were not considered. A system has yet…
Read MoreThe Role of KM in Enhancing AI Algorithms and Systems
Knowledge Management processes present a vital role in improving AI systems and algorithms. Many studies and reviews were carried out to examine the relationship between KM processes and AI systems. However, studies were focusing on specific methods and the impact on some AI algorithms, neglecting the role of other KM processes and how it may…
Read MoreSurvey Analysis: Enhancing the Security of Vectorization by Using word2vec and CryptDB
Vectorization is extracting data from strings through Natural Language Processing by using different approaches; one of the best approaches used in vectorization is word2vec. To make the vectorized data secure, we must apply a security method, which will be CryptDB. The paper is analyzing the survey, which is created to interview security engineers through the…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreDynamic Decision-Making Process in the Opportunistic Spectrum Access
We investigate in this paper many problems related to the decision-making process in the Cognitive Radio (CR), where a Secondary User (SU) tries to maximize its opportunities by finding the most vacant channel. Recently, Multi-Armed Bandit (MAB) problems attracted the attention to help a single SU, in the context of CR, makes an optimal decision…
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