Advances in Science, Technology and Engineering Systems

Article history: Received: 08 December, 2020 Accepted: 27 March, 2021 Online: 20 May, 2021 The TAM is a model that is widely used to understand IT adoption and usage process accordingly and the reason for its popularity is that the model clarifies variances like behavioral intention (BI) relevant to IT appropriation and use over a broad range of settings. The model's main factors for system use is perceived usefulness (PU) and perceived ease of use (PEOU). Likewise, the T-O-E framework is a popular framework for three stimuli that influence organizational adoption namely technology, organization, and environment. Much literature has dealt with the use of TAM and T-O-E frameworks together with their derivatives without looking at the shortfall of these models. This paper reviewed one hundred and seventeen papers that used or reviewed TAM or TOE models. The contribution of this paper is the address of the usefulness, limitations, and criticism of the two models and also how the TAM and the T-O-E frameworks can be integrated into a hybrid model using a generic framework. In conclusion these models can be used separately or as a hybrid depending on the situation at hand. In future it important to harmonize the so many factors of the models that have been suggested and used in literature.

Julies David Bryan

Tranos Zuva

Advances in Science Technology and Engineering Systems Journal

A Review on TAM and TOE Framework Progression and How These Models Integrate

TAM与TOE框架进展综述及其整合方式

South African Drainage and Stormwater Systems in urban roads has been of great concern, more so with recent flash floods in Gauteng and KwaZulu Natal Province in South Africa.Pervious concrete can be used to mitigate these challenges for urban roads.Pervious concrete is a concrete that contains no fines or only a small amount is added for binding.It consists of single sized rounded aggregates between 9.5mm to 12.5mm and bonded by cement and water at points of contact to create a high porosity system that drains water.The research focused on developing different structural pervious concrete mixes, with varying (a) aggregate sizes (7mm, 9.5mm and 19mm) (b) including (river fine aggregates, rubber flakes, fly ash and steel reinforced fiber) and combinations thereof.Results indicated that strong pervious concrete mixes can be developed using a combination of 9.5mm aggregate, river fine aggregates and fly ash, with a recorded maximum yield of 25MPa, and an accompanying Voids Content of 16%.Furthermore, against this performance, it was found that final compressive yield strength of 25MPa falls shy of the 35MPa COTO standard specifications for road and bridge works for south African road authorities (2020 edition).The derived pervious concrete mix was found to satisfy Class 4b Minor Collector Arterial in urban zones, with capacity to withstand up to 10 000 Average Daily Traffic

Pontsho Penelope Mokgatla

Ramadhan Wanjala Salim

Julius Ndambuki

Enhancing Compressive Strength of Pervious Concrete for Use as Pavement Layer in Urban Roads Aper

增强透水混凝土用于城市道路路面层的抗压强度研究

The literature shows a growing interest in taking into account human and organizational factors (HOFs) to achieve safe and successful human performance by reducing the risk of errors.In this sense, the concept of maturity models aims to help companies in the integration of these factors by assessing the current level of maturity and define future areas for improvement.The HOFs maturity model shown in this article is based on the five main factors that can impact human performance and safety positively.The measurement methodology consists in applying the Fuzzy Analytic Hierarchy Process (FAHP) method to calculate the weighting of the elements of the model since they do not have the same importance.Next, the Fuzzy Comprehensive Evaluation Method (FCEM) is used to determine the maturity level in terms of HOFs among the five proposed by performing an assessment of the sub-factors using a questionnaire.The purpose of using fuzzy logic is to deal with vagueness and uncertainty of the human reasoning .The proposed model and methodologies are implemented to bring out the current situation of a Moroccan mining organization and identify the elements that require more effort to reach the next level of maturity.

Yousra Karim

Abdelghani Cherkaoui

Fuzzy Analytical Hierarchy Process and Fuzzy Comprehensive Evaluation Method Applied to Assess and Improve Human and Organizational Factors Maturity in Mining Industry

模糊层次分析法与模糊综合评价法在矿业中评估和提升人因与组织因素成熟度中的应用

Koji Oda

Toshiyasu Kato

Yasushi Kambayashi

Evaluation of a Classroom Support System for Programming Education Using Tangible Materials

使用实物材料评估编程教育课堂支持系统

The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability.Network anomaly detection is crucial for ensuring the security of information resources.Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in the dataset.Conventional machine learning approaches need more efficiency in addressing these issues.Deep learning has demonstrated greater effectiveness in identifying network anomalies.Specifically, a recurrent neural network model is created to recognize the serial data patterns for prediction.We optimized the hybrid model, the convolutional neural network combined with Bidirectional Long-Short Term Memory (BLSTM), to examine optimizers (Adam, Nadam, Adamax, RMSprop, SGD, Adagrad, Ftrl), number of epochs, size of the batch, learning rate, and the Neural Network (NN) architecture.Examining these hyperparameters yielded the highest accuracy in anomaly detection, reaching 98.27% for the binary class NSL-KDD and 99.87% for the binary class UNSW-NB15.Furthermore, recognizing the inherent class imbalance in network-based anomaly detection datasets, we explore the sampling techniques to address this issue and improve the model's overall performance.The data imbalance problem for the multiclass network anomaly detection dataset is addressed by using the sampling technique during the data preprocessing, where the random over-sampling methods combined with the CNN-based BLSTM model outperformed by producing the highest performance metrics, i.e., detection accuracy for multiclass NSL-KDD and multiclass UNSW-NB15 of 99.83% and 99.99% respectively.Evaluation of performance, considering accuracy and F1-score, indicated that the proposed CNN BLSTM hybrid network-based anomaly detection outperformed other existing methods for network traffic anomaly detection.Hence, this research contributes valuable insights into selecting hyperparameters of deep learning techniques for anomaly detection in imbalanced network datasets, providing practical guidance on choosing appropriate hyperparameters and sampling strategies to enhance model robustness in realworld scenarios.

Toya Acharya

Annamalai Annamalai

Mohamed F Chouikha

Enhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data

利用CNN-双向LSTM混合模型和采样策略增强不平衡网络流量数据的网络异常检测

Maikel Leon

Hanna DeSimone

Advancements in Explainable Artificial Intelligence for Enhanced Trans- parency and Interpretability across Business Applications

企业应用中可解释人工智能的进展：提升透明度和可解释性

Diego Costa

Gabriel Matos

Anderson Lins

Leon Barroso

Carlos Aguiar

Erick Bezerra

Web Application Interface Data Collector for Issue Reporting

问题报告的Web应用程序接口数据收集器

Wai Yie Leong Yie Leong

Yuan Zhi Leong

Wai San Leong

Energy Management Policy and Strategies in ASEAN

东盟能源管理政策与战略

Shuvo Kumar Paul

Mircea Nicolescu

Monica Nicolescu

Integrating Speech and Gesture for Generating Reliable Robotic Task Configuration

整合语音与手势生成可靠的机器人任务配置

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基本数据	创刊年份: 2016，原创研究文献占比: ，自引率:， Gold OA占比:

Advances in Science, Technology and Engineering Systems

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A Review on TAM and TOE Framework Progression and How These Models Integrate

Enhancing Compressive Strength of Pervious Concrete for Use as Pavement Layer in Urban Roads Aper

Fuzzy Analytical Hierarchy Process and Fuzzy Comprehensive Evaluation Method Applied to Assess and Improve Human and Organizational Factors Maturity in Mining Industry

Evaluation of a Classroom Support System for Programming Education Using Tangible Materials

Enhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data

Evaluation of a Classroom Support System for Programming Education Using Tangible Materials

Advancements in Explainable Artificial Intelligence for Enhanced Trans- parency and Interpretability across Business Applications

Web Application Interface Data Collector for Issue Reporting

Energy Management Policy and Strategies in ASEAN

Integrating Speech and Gesture for Generating Reliable Robotic Task Configuration