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1. Enhanced Colon Cancer Segmentation and Image Synthesis Through Advanced Generative Adversarial Networks Based-Sine Cosine Algorithm

Author

Alawi Alqushaibi, Mohd Hilmi Hasan, Said Jadid Abdulkadir, Kamaluddeen Usman Danyaro, Mohammed Gamal Ragab, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, and Hitham Alhussian

Subjects
Generative adversarial networks, medical applications, medical imaging, sine cosine optimization, GAN convergence, metaheuristic, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Colorectal cancer (CRC) is a prevalent and life-threatening malignancy, demanding early diagnosis and effective treatment for improved patient outcomes. Accurate segmentation of colon cancer in medical images is a challenging task due to the complexity of its morphology and limited annotated data availability. This paper presents an efficient approach for colon cancer segmentation and image synthesis, combining an Attention U-Net and Pix2Pix Generative Adversarial Network (Pix2Pix-GAN) guided by Sine Cosine Algorithm (SCA) for hyperparameter tuning within the GAN framework. The utilization of SCA plays a pivotal role in optimizing the delicate balance between generator and discriminator dynamics, resulting in enhanced convergence and stability. Our method achieved state-of-the-art results with a mean Dice score of 0.9514, mean Intersection over Union of 0.9123, F beta score of 0.9636, and similarity index of 0.9430 outperforming existing methods. Moreover, the Mean Absolute Error reached a minimal value of 0.01583. This proposed approach shows promise in enhancing the accuracy and robustness of colon cancer diagnosis and treatment which could lead to better diagnosis and treatment of colon cancer.

Published
2024
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2. Sentiment Analysis in Low-Resource Settings: A Comprehensive Review of Approaches, Languages, and Data Sources

Author

Yusuf Aliyu, Aliza Sarlan, Kamaluddeen Usman Danyaro, Abdullahi Sani B. A. Rahman, and Mujaheed Abdullahi

Subjects
Word-embedding, transfer learning, transformer, machine translation, low-resource, sentiment analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The field of low-resource sentiment analysis has seen significant developments in recent years. This research review SLR evaluates the approaches and data sources utilized in low-resource sentiment analysis by deep learning. The primary aim is to discover suitable approaches for future sentiment analysis in low-resource. Our studies explore various languages, models, and data sources expressing a desire to create effective approaches. Our emphasis lies in the critical evaluation of the approaches and the datasets utilized, to identify areas where further research is needed. Our analysis study adds to the existing body of literature reviews, encompassing multilingual low-resource sentiment analysis research spanning from 2018 to 2023. The findings indicate that the transfer learning approach is the most frequently used, followed by word embedding learning and machine translation systems. Additionally, the study shows that social media is the most used platform for data collection, followed by product reviews, movies, and hotels. There has been a significant surge in the adoption of pre-trained transformers, indicating a growing interest in exploring the potential of these models for low-resource languages within the natural language processing (NLP) community. This trend is largely attributed to the novel nature of these models and their feature of being non-labour intensive. However, the scarcity of annotated datasets for such languages remains a major hurdle. finally, these research findings are relevant and informative for any researcher working in the field of low-resource multilingual sentiment analysis. The study introduces a conceptual framework for performing sentiment analysis in low-resource. The study provides a valuable resource for future researchers.

Published
2024
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3. Optimized Multi-Level Multi-Type Ensemble (OMME) Forecasting Model for Univariate Time Series

Author

Mehak Usmani, Zulfiqar Ali Memon, Kamaluddeen Usman Danyaro, and Rizwan Qureshi

Subjects
ARIMA, deep learning, energy, ensemble methods, exponential smoothing, forecasting, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Energy is of paramount importance for the world, and it is a fundamental driver of economic growth and development. Industries, businesses, and households rely on energy for even a small task. Due to its high demand, a significant portion of the global population still lacks access to reliable and affordable energy sources. Many industries and sectors continue to waste significant amounts of energy through inefficiencies. While energy is essential, the production and consumption of energy can have significant environmental consequences. Predicting power usage can help to significantly improve energy efficiency, reduce costs, enhance grid reliability, and minimize the environmental impact of energy consumption. In this work, a novel model named, the Optimized Multi-level Multi-type Ensemble (OMME) Forecasting Model is presented to estimate the power consumption. The proposed model was applied to the data set of total power consumption recorded in Austria at each hour after the pre-processing. The model applied bootstrapping at level 1 and a hybrid ensemble at level 2. Both ensemble methods utilized different algorithms for time series forecasting including ARIMA, Exponential smoothing, LSTM, GRU, and MLP. The parameters were tuned using Bayesian and Tabu search optimization. Different experiments were conducted for day and night usage separately. The proposed model was able to estimate the power usage with an error of 22%. This work also learned the most suitable technique for power consumption time series. GRU performed very well in different experiments and gave the forecast with 12% error. Distribution graphs of the OMME prediction further validate the integrity of the results.

Published
2024
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4. Review on Approaches of Federated Modeling in Anomaly-Based Intrusion Detection for IoT Devices

Author

Umar Audi Isma'ila, Kamaluddeen Usman Danyaro, Aminu Aminu Muazu, and Umar Danjuma Maiwada

Subjects
Federated learning modeling, IoT devices, anomaly-based intrusion detection, aggregation function, non-IDD data, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

The novelty of Federated Learning (FL) has emerged as a promising alternative to centralized machine learning systems in the context of anomaly-based intrusion detection systems (AIDS) deployed on Internet of Things (IoT) devices. Unlike traditional centralized models, FL allows on-device model training and updates, reducing privacy concerns and issues such as single points of failure and high false alarm rates (FAR). This approach, termed ‘Fed-AIDS,’ offers a more secure and efficient solution. However, the development of Fed-AIDS models faces challenges related to limited training data and the diverse nature of IoT datasets. Additionally, FL’s decentralized nature introduces weight divergence issues arising from non-Independently and Identically Distributed (non-IID) clients. To address these challenges and optimize Fed-AIDS modeling, interdisciplinary research efforts are vital. The primary objective of this study is to conduct an up-to-date review by adopting a Systematic Literature Review (SLR) approach to analyze existing studies of Fed-AIDS modeling procedures for IoT devices. Data from the published studies were retrieved from Scopus database, which covered major publishers such as IEEE, Elsevier and others. Specifically, our review conducted from the following Fed-AIDS perspectives: workflow and tools, training dataset, complexities of non-IID data in Fed-AIDS models, classification tasks, aggregation tasks, and model validation metrics. Based on the research findings, the study highlights a series of challenges and proposes potential solutions to stand in future research in Fed-AIDS modeling, aiming to advance the field of IoT device security.

Published
2024
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5. Digital Predistortion Based Experimental Evaluation of Optimized Recurrent Neural Network for 5G Analog Radio Over Fiber Links

Author

Muhammad Usman Hadi, Kamaluddeen Usman Danyaro, Alawi AlQushaibi, Rizwan Qureshi, and Tanvir Alam

Subjects
Digital predistortion, fiber nonlinearity, radio over fiber, error vector magnitude, recurrent neural network, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

In the context of Enhanced Remote Area Communications (ERAC), Radio over Fiber (RoF) technology plays a crucial role in extending reliable connectivity to underserved and remote areas. This paper explores the significance of fifth-generation (5G) Digital Predistortion (DPD) role in mitigating non-linearities in Radio over Fiber (RoF) systems for enhancing communication capabilities in remote regions. The seamless integration of RoF and 5G technologies requires robust linearization techniques to ensure high-quality signal transmission. In this paper, we propose and exhibit the effectiveness of a machine learning (ML)-based DPD method for linearizing next-generation Analog Radio over Fiber (A-RoF) links within the 5G landscape. The study investigates the use of an optimized recurrent neural network (ORNN) based DPD experimentally on a multiband 5G new radio (NR) A-RoF system while maintaining low complexity. The ORNN model is evaluated using flexible-waveform signals at 2.14 GHz and 5G NR signals at 10 GHz transmitted over a 10 km fiber length. The proposed ORNN-based machine learning approach is optimized and is compared with conventional generalized memory polynomial (GMP) model and canonical piecewise linearization (CPWL) methods in terms of Adjacent Channel Power Ratio (ACPR), Error Vector Magnitude (EVM), and in terms of computation complexity including, storage, time and memory consumption. The findings demonstrate that the proposed ORNN model reduces EVM to below 2% as compared to 12% for non-compensated cases while ACPR is reduced by 18 dBc, meeting 3GPP limits.

Published
2024
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6. Challenges of Maturity Models in Public-Private Partnerships (PPPs) in the Post-COVID-19 Era

Author

Yusuf Umar Datti, Noor Amila Wan Abdullah Zawawi, Abdullahi Ahmed Umar, Muslich Hartadi Sutanto, and Kamaluddeen Usman Danyaro

Subjects
maturity models, public-private partnership, descriptive model, prescriptive model, covid-19, Industrial engineering. Management engineering, T55.4-60.8
Abstract

Maturity models (MMs) have witnessed exponential increase due to their successful application in several domains. However, there is an absence of review that guides researchers in developing, applying and validating Public-Private Partnership maturity models (PPPMMs). This study examines PPPMMs, provides guidance on the topic and highlights gaps in the literature. A literature search on selected electronic databases was conducted, and the study adopted the widely accepted Preferred Reporting Items for Systematic Review and Meta-analysis statement (PRISMA). The study identified a total of four thousand six hundred and eighteen (4,618) studies, and twenty-one studies (21Nr) were rigorously selected. The results revealed PPPMMs as an emerging area of research with a low number – 21 publications since its deployment for about two (2) decades. Similarly, the findings unveiled a lack of uniformity in conceptualising the terms, dimensions used, and methodology adopted. This finding is attributed mainly to the limited use of the theoretical lens, which considerably weakens the model’s theoretical foundation and limits its potential to guide improvement. Additionally, there are more efforts in developing MMs than applying and validating them. Furthermore, there is an unbalanced focus on descriptive models over prescriptive and comparative models, which inhibit the model’s potential to guide improvement. Future work should provide a solid ground to the field using a theoretical lens and focus on prescriptive models with a strong emphasis on application and validation. This research is the first of its kind that synthesises and brings together available PPPMMs literature into one place. It also contributes to the body of knowledge by highlighting areas of research that require immediate attention to enhance the much-needed success of PPP in the post-COVID-19 era.

Published
2022

7. Optimizing the Energy Efficiency in 5G Security Systems for Intrusion Detection with an Emphasis on DDOS Assaults

Author

Umar Danjuma Maiwada, Kamaluddeen Usman Danyaro, Aliza Bt Sarlan, Aminu Aminu Muazu, and Abubakar Rufai Garba

Subjects
5G, security, intrusion detection systems, energy efficiency, NETSIM, DDoS, Engineering machinery, tools, and implements, TA213-215
Abstract

In response to the rising demand for new and existing use cases of energy efficiency, the telecoms sector is going through a dramatic shift toward 5G technology. High data speeds, extensive coverage provided by dense base station deployment, higher capacity, improved Quality of Service (QoS), and extremely low latency are required for 5G wireless networks. New deployment methods, networking architectures, processing technologies, and storage solutions must be created to satisfy the anticipated service requirements of 5G technologies. These developments further increase the need to secure the security of 5G systems and their functionality as well as energy efficiency problems. Indeed, 5G system security is the target of intense efforts by developers and academics in this industry. Significant security concerns for 5G networks have been identified with extensive research. Attackers can make use of vulnerabilities like traffic and the flow base by introducing malicious code and performing other nefarious deeds to take advantage of the system. On 5G networks, attack techniques such as model node map (MNmap), power depletion assaults, and Man-in-the-Middle (MiTM) assaults can be effectively used. However, this study analyses 5G technology’s current energy efficiency problems. We recommend an unusual intrusion detection system (IDS) that makes use of Traffic Volume methods. Considering this investigation, we propose an enhancing training process by including statistical analysis on Distributed Denial-of-Service (DDoS) threats, which is how prior research recommended using OMNET and NS-3 on IDS for optimization. Additionally, the methodology for incorporating the suggested intrusion detection systems within a typical 5G architecture is presented by our research using NETSIM. The paper also offers a planned system’s correction method, providing a useful implementation after completing analysis.

Published
2023
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8. Seismic Microzonation Map for a Fixed-Jacket Platform in the Malay Basin

Author

Mohamad Mazlina, M. S. Liew, Kamaluddeen Usman Danyaro, Azlan Adnan, and Nor Hayati Ab Hamid

Subjects
seismicity, seismic microzonation, microzonation map, ground response analysis, offshore facilities in the Malay Basin, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

The existence of soft soil in offshore areas may lead to the amplification of vibration received from offshore facilities, especially from the existing fixed-jacket platforms, which were designed without provision to seismicity, as in Malaysian water. Therefore, this study was designed to develop a seismic microzonation map and a soil amplification factor map according to soil type; we propose horizontal response spectra and site coefficient values (Ca and Cv) for the Malay Basin. A one-dimensional nonlinear analysis of layered soil (NERA) was used in the ground response analysis for six selected seismic events under five return periods of 100, 200, 500, 1000, and 2500 years. Soil amplification factors for soil types D and E showed a decreasing trend from 100 years to 2500 years. Two designed horizontal response spectra are proposed (for soil type D and E) under average and envelope conditions; a comparison with ISO showed that the proposed spectra were higher, especially for soil type E. To summarize, the seismicity effect should be included in the development of offshore industries as findings indicated that soil amplification occurred in soil types D and E at the Malay Basin.

Published
2022
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9. Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review

Author

Kamaluddeen Usman Danyaro, Haizatul Hafizah Hussain, Mujaheed Abdullahi, M. S. Liew, Lim Eu Shawn, and Mustapha Yusuf Abubakar

Subjects
data interoperability, Metocean, oil and gas, artificial intelligence, machine learning, automation, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

The current oil industry is moving towards digitalization, which is a good opportunity that will bring value to all its stakeholders. The digitalization of oil and gas discovery, which are production-based industries, is driven by enabling technologies which include machine learning (ML) and big data analytics. However, the existing Metocean system generates data manually using sensors such as the wave buoy, anemometer, and acoustic doppler current profiler (ADCP). Additionally, these data which appear in ASCII format to the Metocean system are also manual and silos. This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. A comprehensive review of several research studies, which explore the needs of ML in oil and gas industries by investigating the in-depth integration of Metocean data interoperability for intelligent operations and automation using an ML-based approach, is presented. A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. The study reveals that ML is one of the crucial and key enabling tools that the oil and gas industries are now focused on for implementing digital transformation, which allows the industry to automate, enhance production, and have less human capacity. Lastly, user recommendations for potential future investigations are offered.

Published
2022
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10. Deterioration of Electrical Load Forecasting Models in a Smart Grid Environment

Author

Abdul Azeem, Idris Ismail, Syed Muslim Jameel, Fakhizan Romlie, Kamaluddeen Usman Danyaro, and Saurabh Shukla

Subjects
energy management, adaptive models, generation modalities, load forecasting, machine learning, model deterioration, Chemical technology, TP1-1185
Abstract

Smart Grid (S.G.) is a digitally enabled power grid with an automatic capability to control electricity and information between utility and consumer. S.G. data streams are heterogenous and possess a dynamic environment, whereas the existing machine learning methods are static and stand obsolete in such environments. Since these models cannot handle variations posed by S.G. and utilities with different generation modalities (D.G.M.), a model with adaptive features must comply with the requirements and fulfill the demand for new data, features, and modality. In this study, we considered two open sources and one real-world dataset and observed the behavior of ARIMA, ANN, and LSTM concerning changes in input parameters. It was found that no model observed the change in input parameters until it was manually introduced. It was observed that considered models experienced performance degradation and deterioration from 5 to 15% in terms of accuracy relating to parameter change. Therefore, to improve the model accuracy and adapt the parametric variations, which are dynamic in nature and evident in S.G. and D.G.M. environments. The study has proposed a novel adaptive framework to overcome the existing limitations in electrical load forecasting models.

Published
2022
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11. Ground Motion Prediction Equations for Malaysia Due to Subduction Zone Earthquakes in Sumatran Region

Author

M. S. Liew, Kamaluddeen Usman Danyaro, Mazlina Mohamad, Lim Eu Shawn, and Aziz Aulov

Subjects
Ground motion prediction equation, earthquakes in Malaysia, earthquakes in the sumatran region, seismic hazard, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

There has been numerous seismic hazard studies so far that includes Malaysian territories. However, there is a need to assess how reliable those studies are. Two main potential contributors to error have been identified: 1) seismic hazard analysis method and 2) ground motion prediction equation (GMPE). The amount of variation in predicting erroneous GMPE is huge. Thus, this paper concentrates on generating new GMPEs due to subduction specified for Malaysia and validated against developed GMPE. Empirical method for GMPE generation was utilized using recorded ground motion data acquired from the Malaysian Meteorological Department. The earthquakes were grouped according to the source, and only source types in the Sumatran subduction area were used due to the availability of enough data to identify a pattern. Three GMPEs were generated for three different source types, namely, shallow subduction earthquake, deep subduction earthquake, and backarc earthquake sources. Sumatran strike slip fault is considered within backarc seismicity. They were compared with the models proposed by Petersen (modified from Young), Atkinson and Boore, and Megawati. The comparison results showed that the proposed models are far superior at predicting the earthquakes in the Sumatran region, with percentage difference between estimates and the recorded values being the lowest. Therefore, the equations should be used in further seismic hazard analyses. Thus, this paper becomes a part of the recent initiatives in Malaysia to assess the hazards posed by earthquakes.

Published
2017
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12. A Comprehensive Guide to Different Fracturing Technologies: A Review

Author

M. S. Liew, Kamaluddeen Usman Danyaro, and Noor Amila Wan Abdullah Zawawi

Subjects
guide to different fracturing technologies, shale gas extraction technologies, different hydraulic fracturing, natural gas extraction technologies, Technology
Abstract

Hydraulic fracturing has made the production of gas more economical. Shale gas possesses the potential to arise as a main natural gas source worldwide. It has been assessed that the top 42 countries, including the U.S., are predicted to own 7299 trillion cubic feet (tcf) of technically recoverable shale gas resources. The main goal of this paper is to serve as a guide of different shale gas extraction methods. The significance of these methods and possible pros and cons are determined. Each technique was explained with the support of literature review. Specifically, this paper revealed that some fracking methods such as pulsed arc electrohydraulic discharges (PAED), plasma stimulation and fracturing technology (PSF), thermal (cryogenic) fracturing, enhanced bacterial methanogenesis, and heating of rock mass are at the concept stage for conventional and other unconventional resources. Thus, these found to be significant for stimulating natural gas wells, which provides very good production results. This paper also discovered that fracking remains the recommended technique used by the oil and gas industries.

Published
2020
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13. Investigation of Fibers Reinforced Engineered Cementitious Composites Properties Using Quartz Powder

Author

M. S. Liew, Muhammad Aswin, Kamaluddeen Usman Danyaro, Bashar S. Mohammed, and A. M. Al-Yacouby

Subjects
quartz powder, fresh properties, engineered cementitious composites, fibers reinforced engineered cementitious composites, PVA fiber, steel fiber, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Engineering (General). Civil engineering (General), TA1-2040, Microscopy, QH201-278.5, Descriptive and experimental mechanics, QC120-168.85
Abstract

In relation to the use of retrofit materials on damaged constructions, application on earthquake-resistant buildings, and for the strengthening and rehabilitation on weakened regions, there is a need for a more superior material than concrete. Application sites include beam-column joints, corbels, link-slabs, deep beams, support regions and dapped-end areas. Fiber reinforced engineered cementitious composites (FR-ECC) can address this issue, because FR-ECC is one of the composite materials that has high strength, ductility and durability. In order to develop FR-ECC, this study was done to investigate the effect of adding quartz powder on the compressive strength capacity and properties of FR-ECC through the use of polyvinyl alcohol (PVA) and steel fibers. The volume fraction of fiber was set to 0%–2%. To support the friendly environment, FR-ECC uses by-product materials such as fly ash and silica fume, with a cement content less than 600 kg/m3. In terms of the experimental investigation on FR-ECC, this work conducted the fresh property tests showing that PVA fibers have quite an influence on ECC workability, due to their hydrophilic behavior. By adjusting the superplasticizer (SP) content, the consistency and high workability of the ECC mixes have been achieved and maintained. The test results indicated that the PVA and steel fibers-based ECC mixes can be classified as self-compacting composites and high early compressive strength composites. Significantly, addition of quartz powder into the ECC mixes increased the compressive strength ratio of the ECC samples up to 1.0747. Furthermore, the steel fiber-based ECC samples exhibited greater compressive strength than the PVA fibers-based ECC samples with the strength ratio of 1.1760. Due to effect of the pozzolanic reaction, the fibers dispersion and orientation in the fresh ECC mixes, so that the cementitious matrices provided the high strength on the FR-ECC samples. During the compression loading, the bulging effect always occurred before the failures of the fibers-based ECC samples. No spalling occurred at the time of rupture and the collapse occurred slowly. Thus, FR-ECC has provided unique characteristics, which will reduce the high cost of maintenance.

Published
2020
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24. Physics-Based Structural Health Monitoring Digital Twin for Seismically Vulnerable Fixed Offshore Structures

Author

Edward Kawos @ Bartholomew, Eu Shawn Lim, Iraj Toloue, Mohd Shahir Liew, Kamaluddeen Usman Danyaro, Kar Mun Chan, and Seng Wah Ling

Abstract

An Autonomous Structural Health Monitoring (SHM) System for Fixed Offshore Structures is a tool used to monitor the state or the health of a structure in terms of its integrity and strength in an automated manner. An SHM system framework comprises of software and hardware integration equipped with IoT capability to collect raw data, online data transmittal to onshore, a back-end engine to process data into useful engineering information and display the monitoring results through engineering parameters and digital twinning, which emulates the real condition of the structure offshore. The prominent monitoring method for a structure's strength is through global monitoring, using structural modal properties as the measuring parameter to indentify a certain structure's global integrity, specifically using its natural frequency. This paper aims to layout the framework of an autonomous SHM system for global monitoring which is implemented onto a seismically vulnerable fixed offshore structure.

Published
2022

25. An Investigation on the Influence of Structural Damage on Eigenvalue Characteristics and Reserve Strength Ratio of Onshore Lattice Steel Structures

Author

Wan Farra Ayesha Binti Wan Muhaimin, Mohd Shahir Liew, Noor Amila Binti Wan Abdullah Zawawi, Lim Eu Shawn, Anas Khaled Al Sheikh, Siddique Mohd Yatim Bin Salim, and Kamaluddeen Usman Danyaro

Abstract

In the study of structural strength, the reserve strength ratio provides a measure of the ultimate strength capacity of a structure. Under actual site conditions, the reserve strength ratio may vary from its design values with loss of stiffness and changes in structural integrity. Changes in the vibrational response of a structure due to loss of stiffness is observed as a form of structural health monitoring (SHM). The aim of this study is to investigate the relationship and sensitivity of the reserve strength ratio of a structure to changes in natural frequency due to damage occurrences as a measure of global structural integrity. The reduction of stiffness is simulated by the sequential removal of members according loading path within the model. To obtain the values used for comparison, a non-linear pushover analysis and eigenvalue analysis is utilized to obtain the Reserve Strength Ratio (RSR) and eigenvalue for intact as well as simulated progressive damage conditions. The pattern recognized from the analysis performed indicated that as the reserve strength ratio (RSR) is reduced with reduction of stiffness by the removal of primary and secondary members, the eigenvalues for each respective model showing similar reductions.

Published
2022

26. A Literature Review on Site Suitability and Structural Hydrodynamic Viability for Artificial Reefs Purposes

Author

Anas Khaled Alsheikh, Noor Amila Wan Zawawi, Mohd Shahir Liew, Lim Eu Shawn, Iraj Toloue, Kamaluddeen Usman Danyaro, and Nurshazlyn Mohd Aszemi

Abstract

In Malaysia, over 400 oil and gas platforms are in operation. In every life cycle of a platform, it undergoes decommissioning. The most used method is by relocating the asset to an onshore fabrication facility. The alternative to onshore decommissioning is by reefing structures in-situ or ex-situ basis. to achieve the environmental assurance of a successful decommissioning by reefing, two domains of parameters were overviewed. the study involved hydrodynamic simulation of platforms. The first domain is in relations to the site to determine its suitability against hosting marine life and thriving coral formulation (Site Suitability). the other domain is in relations to the structure's physical and hydrodynamic properties (structural viability). Site suitability is governed by water depth and current velocity. Structural viability is governed by two sub-domains, one is where dimensions and complexity of the structure are assessed using dimensionality analysis. And the other is its hydrodynamic properties (Vortex Shedding Frequency, Pressure, Wake Region indices).

Published
2022

28. Study of Mechanical Behavior of Free Standing Drilling Riser Under Extreme Weather Conditions

Author

Kamaluddeen Usman Danyaro, Hong Yaw Yong, Mohd Shahir Liew, Mark Ovinis, and Eu Shawn Lim

Subjects
Health (social science), General Computer Science, General Mathematics, General Engineering, 020101 civil engineering, 02 engineering and technology, 01 natural sciences, 010305 fluids & plasmas, 0201 civil engineering, Education, Extreme weather, General Energy, 0103 physical sciences, Environmental science, Drilling riser, General Environmental Science, Marine engineering
Published
2018

29. Effects of Quartz Powder on the Compressive Strength of High Performance Engineered Cementitious Composites

Author

Sani Haruna, A. M. Al-Yacouby, Bashar S. Mohammed, Mohd Shahir Liew, and Kamaluddeen Usman Danyaro

Subjects
Compressive strength, Materials science, Cementitious composite, Composite material, Quartz
Abstract

This study presents an experimental investigation on the effect of quartz powder on the compressive strength of high performance engineered cementitious composites (HP-ECC). Four different HP-ECC mixtures were considered ECC mixture with PVA fibres and zero quartz powder, ECC made with PVA fibres and quartz powder, ECC made with steel fibres and zero quartz powder, ECC made with steel fibres and quartz powder respectively. Different percentages of steel and PVA fibres were investigated at 0 to 2%. The compressive strength of HP-ECC was examined for 1, 7, 14, and 28 days. Based on the experimental results, it was found that the inclusion of quartz powder leads to enhancement in the compressive strength. Compressive strength of more than 100 MPa was obtained for both ECC made with quartz powder. On the other hand, the fibres type has a negligible effect on the performance of HP-ECC.

Published
2021

30. Analysis of Spread Moored FPSO-Tanker Side-by-Side System with Offloading Operability

Author

Kamaluddeen Usman Danyaro, A. M. Al-Yacouby, Mohd Shahir Liew, Ruly Irawan, and N. L. Azizan

Subjects
Azimuth, Metocean, Operability, Computer science, Significant wave height, Mooring, Wind engineering, Dynamic load testing, Swell, Marine engineering
Abstract

Dynamic load acting on the side-by-side mooring system is one of the important factors to estimate the offloading operability of the FPSO. In this paper, a numerical mooring analysis for the side-by-side moored FPSO-tanker system is investigated. Floating Structure analysis is divided into two parts. The first is to calculate the hydrodynamic coefficient, and the second part is calculating the system responses in the time-domain analysis. The prediction of FPSO-Tanker responses is necessary during offloading. This research presents the possibility of the use of Artificial Neural Networks model for the prediction of the responses of FPSO-Tanker system with spread-mooring configuration. The ANN model considering various metocean data such as azimuth angles, significant wave height, wind load, swell, hawser and the mooring configurations. The results of this study indicated that the ANN model shows an accurate prediction of the FPSO-tanker response that are required for the design of side-by-side vessels during offloading.

Published
2021

31. A Comprehensive Guide to Different Fracturing Technologies: A Review

Author

Noor Amila Wan Abdullah Zawawi, Kamaluddeen Usman Danyaro, and Mohd Shahir Liew

Subjects
Control and Optimization, Shale gas, 020209 energy, Energy Engineering and Power Technology, 02 engineering and technology, 010501 environmental sciences, 01 natural sciences, different hydraulic fracturing, lcsh:Technology, Hydraulic fracturing, Natural gas, shale gas extraction technologies, natural gas extraction technologies, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Rock mass classification, Engineering (miscellaneous), 0105 earth and related environmental sciences, Petroleum engineering, Renewable Energy, Sustainability and the Environment, business.industry, lcsh:T, Fossil fuel, guide to different fracturing technologies, Unconventional oil, Environmental science, Extraction methods, business, Energy (miscellaneous)
Abstract

Hydraulic fracturing has made the production of gas more economical. Shale gas possesses the potential to arise as a main natural gas source worldwide. It has been assessed that the top 42 countries, including the U.S., are predicted to own 7299 trillion cubic feet (tcf) of technically recoverable shale gas resources. The main goal of this paper is to serve as a guide of different shale gas extraction methods. The significance of these methods and possible pros and cons are determined. Each technique was explained with the support of literature review. Specifically, this paper revealed that some fracking methods such as pulsed arc electrohydraulic discharges (PAED), plasma stimulation and fracturing technology (PSF), thermal (cryogenic) fracturing, enhanced bacterial methanogenesis, and heating of rock mass are at the concept stage for conventional and other unconventional resources. Thus, these found to be significant for stimulating natural gas wells, which provides very good production results. This paper also discovered that fracking remains the recommended technique used by the oil and gas industries.

Published
2020

32. Investigation of Fibers Reinforced Engineered Cementitious Composites Properties Using Quartz Powder

Author

Mohd Shahir Liew, Bashar S. Mohammed, Kamaluddeen Usman Danyaro, Muhammad Aswin, and A. M. Al-Yacouby

Subjects
engineered cementitious composites, Materials science, Silica fume, 0211 other engineering and technologies, PVA fiber, 02 engineering and technology, lcsh:Technology, Article, fibers reinforced engineered cementitious composites, 021105 building & construction, General Materials Science, quartz powder, Fiber, Composite material, Ductility, lcsh:Microscopy, lcsh:QC120-168.85, lcsh:QH201-278.5, lcsh:T, Superplasticizer, 021001 nanoscience & nanotechnology, Compression (physics), Compressive strength, lcsh:TA1-2040, steel fiber, Pozzolanic reaction, lcsh:Descriptive and experimental mechanics, Cementitious, lcsh:Electrical engineering. Electronics. Nuclear engineering, fresh properties, 0210 nano-technology, lcsh:Engineering (General). Civil engineering (General), lcsh:TK1-9971
Abstract

In relation to the use of retrofit materials on damaged constructions, application on earthquake-resistant buildings, and for the strengthening and rehabilitation on weakened regions, there is a need for a more superior material than concrete. Application sites include beam-column joints, corbels, link-slabs, deep beams, support regions and dapped-end areas. Fiber reinforced engineered cementitious composites (FR-ECC) can address this issue, because FR-ECC is one of the composite materials that has high strength, ductility and durability. In order to develop FR-ECC, this study was done to investigate the effect of adding quartz powder on the compressive strength capacity and properties of FR-ECC through the use of polyvinyl alcohol (PVA) and steel fibers. The volume fraction of fiber was set to 0%–2%. To support the friendly environment, FR-ECC uses by-product materials such as fly ash and silica fume, with a cement content less than 600 kg/m3. In terms of the experimental investigation on FR-ECC, this work conducted the fresh property tests showing that PVA fibers have quite an influence on ECC workability, due to their hydrophilic behavior. By adjusting the superplasticizer (SP) content, the consistency and high workability of the ECC mixes have been achieved and maintained. The test results indicated that the PVA and steel fibers-based ECC mixes can be classified as self-compacting composites and high early compressive strength composites. Significantly, addition of quartz powder into the ECC mixes increased the compressive strength ratio of the ECC samples up to 1.0747. Furthermore, the steel fiber-based ECC samples exhibited greater compressive strength than the PVA fibers-based ECC samples with the strength ratio of 1.1760. Due to effect of the pozzolanic reaction, the fibers dispersion and orientation in the fresh ECC mixes, so that the cementitious matrices provided the high strength on the FR-ECC samples. During the compression loading, the bulging effect always occurred before the failures of the fibers-based ECC samples. No spalling occurred at the time of rupture and the collapse occurred slowly. Thus, FR-ECC has provided unique characteristics, which will reduce the high cost of maintenance.

Published
2020

34. Hydrodynamic Study of Free Standing Drilling Riser Under Hurricane Conditions

Author

Hong Yaw Yong, Mohd Shahir Liew, Kamaluddeen Usman Danyaro, Eu Shawn Lim, and Mark Ovinis

Subjects
Saffir–Simpson scale, Wind wave, Mode (statistics), Submarine pipeline, Drilling riser, Significant wave height, Offshore drilling, Geology, Swell, Marine engineering
Abstract

Offshore structures are susceptible to damages due to hurricane. The main subject of this research, free standing drilling riser (FSDR), is an innovation to the drilling riser that enables rapid disconnection prior to hurricane conditions. This allows the offshore drilling rig and operator to move away from hurricane path prior to hurricane landing. Yet, currently, the emergency disconnection decision of FSDR is decided by a rig manager. Past incidents have shown that human error can cause catastrophic damage. Studies on FSDR operations under hurricane condition are scarcely available. The most relevant studies, free standing riser (FSR) behaves differently. With the increase in hurricane intensity over the past 50 years, this increases the risk in FSDR operations. In this work, the hydrodynamic response of FSDR under hurricane conditions was investigated. Four simulation studies were conducted in Orcaflex finite element modeling (FEM) software. These studies were conducted to determine the effect of emergency disconnection location, the optimum emergency disconnection location, the effect of various Saffir Simpson maximum significant wave height and hurricane generated swell on the hydrodynamic response of FSDR. Hurricane generated wave spectrum was used to replicate hurricane conditions. The simulation study shows that the lateral displacement of FSDR decreases in a 3rd order polynomial function with the emergency disconnection location, LD = −6e−6d3 + 0.0024d2 − 0.3348d + 19.179. In addition, the optimum emergency disconnection location along drilling riser line is at 87.50% of the original water depth. The lateral displacement of FSDR increases exponentially with Saffir Simpson scale storm intensity, y = 1.7537e0.0386x. Lastly, the stronger the swell component of hurricane generated swell, the higher the hydrodynamic responses. Wind wave component of hurricane generated swell did not influence FSDR as the riser was in the free standing mode. The limitation of this research is the findings are applicable for this simulation setup only. Further validations are required with experimental setup and various types of offshore structure.

Published
2020

36. Ground Motion Prediction Equations for Malaysia Due to Subduction Zone Earthquakes in Sumatran Region

Author

Aziz Aulov, Mohd Shahir Liew, Mazlina Mohamad, Kamaluddeen Usman Danyaro, and Lim Eu Shawn

Subjects
Ground motion, 010504 meteorology & atmospheric sciences, General Computer Science, Subduction, General Engineering, Comparison results, earthquakes in Malaysia, seismic hazard, Induced seismicity, earthquakes in the sumatran region, 010502 geochemistry & geophysics, Strike-slip tectonics, 01 natural sciences, Seismic hazard, Surface wave, Ground motion prediction equation, General Materials Science, lcsh:Electrical engineering. Electronics. Nuclear engineering, Electrical and Electronic Engineering, lcsh:TK1-9971, Geology, Seismology, Analysis method, 0105 earth and related environmental sciences
Abstract

There has been numerous seismic hazard studies so far that includes Malaysian territories. However, there is a need to assess how reliable those studies are. Two main potential contributors to error have been identified: 1) seismic hazard analysis method and 2) ground motion prediction equation (GMPE). The amount of variation in predicting erroneous GMPE is huge. Thus, this paper concentrates on generating new GMPEs due to subduction specified for Malaysia and validated against developed GMPE. Empirical method for GMPE generation was utilized using recorded ground motion data acquired from the Malaysian Meteorological Department. The earthquakes were grouped according to the source, and only source types in the Sumatran subduction area were used due to the availability of enough data to identify a pattern. Three GMPEs were generated for three different source types, namely, shallow subduction earthquake, deep subduction earthquake, and backarc earthquake sources. Sumatran strike slip fault is considered within backarc seismicity. They were compared with the models proposed by Petersen (modified from Young), Atkinson and Boore, and Megawati. The comparison results showed that the proposed models are far superior at predicting the earthquakes in the Sumatran region, with percentage difference between estimates and the recorded values being the lowest. Therefore, the equations should be used in further seismic hazard analyses. Thus, this paper becomes a part of the recent initiatives in Malaysia to assess the hazards posed by earthquakes.

Published
2017

37. Hydrodynamic forces on tubular cylinders fitted with sacrificial anodes – numerical analysis

Author

M. H. Talhah, Kamaluddeen Usman Danyaro, A. M. Al-Yacouby, and Mohd Shahir Liew

Subjects
Physics::Fluid Dynamics, Materials science, Galvanic anode, Hydrodynamic forces, Numerical analysis, Mechanics
Abstract

In offshore engineering, the design of effective marine platforms compatible with the offshore environmental condition is a challenging task, especially accurate estimation of hydrodynamic coefficients that affect the viscous forces. Practically, the well-known Morison’s equation is often adopted by designers to calculate wave loads on slender structures, where the values of drag and inertia coefficients are selected as constant values based on the design code of practice’s recommendations. However, the mass and drag coefficients must be determined empirically based on specific met-ocean data for the operation location. Thus, the objective of this study is to evaluate the Hydrodynamic Forces on Circular Cylinders fitted with sacrificial anodes using empirical methods, and validate the results using Computational Fluid Dynamic (CFD). It is found that the major parameters that affect the drag and inertia coefficients are the water depth, wave heights, wave frequencies, the pipe diameters, and the presence of anode fittings.

Published
2021

38. A Structured Review on the Improvement of GBI-RNC

Author

Sayang Syazanna Raf'ee, Noor Amila Wan Abdullah Zawawi, Mohd Shahir Liew, and Kamaluddeen Usman Danyaro

Subjects
lcsh:TA1-2040, Business, lcsh:Engineering (General). Civil engineering (General)
Abstract

This paper presents the reviews of studies with regards to the development of Green Building Index- Residential New Construction (GBI-RNC). GBI-RNC is considered since the development of Residential Construction is expected to increase every year since Malaysia is considered as a developing country. The Carbon Emission of Residential Construction is evident thus one of the ways to control and commit to Carbon Emission reduction is by promoting Sustainable Development. Even though GBI-RNC has been introduced to the industry since 2009, participation increased just slightly by the year and to reach a rating more than ‘Certified’ are low. Furthermore, a national green rating system is proposed by JKR, to assist with all residential government projects. Therefore, this paper shall present the suggested modifications that should be made to GBI-RNC to improve its elements and gain more influence to maintain as the most used green rating system for residential construction.

Published
2018

39. A Proposed Methodology for Integrating Oil and Gas Data Using Semantic Big Data Technology

Author

Kamaluddeen Usman Danyaro and Mohd Shahir Liew

Subjects
Engineering, business.industry, Data management, Fossil fuel, Big data, computer.software_genre, Data science, Data sharing, Data exchange, Information system, business, Semantic Web, computer, Data integration
Abstract

The paradigm change in web structure has turned the world of information systems and data sharing to be a huge and diverse storage. As many oil and gas companies vie for attention due to the downturn, more data management is needed. Therefore, oil and gas industries are hungry to share their information for competitive advantage. The challenge is the redundancy or/and unorganized information present in large amounts of data. This paper proposed a methodology for the development of semantic big data for oil and gas data exchange that facilitates data integration. It provides a framework that will be used for accessing the oil and gas data; and integrate the oil and gas unstructured, semi-structured and structured data for better accessibility to users.

Published
2017

40. Thermal Insulation of Residential Construction through the Study of Temperature Difference of Bricks

Author

Mohd Shahir Liew, Sayang Syazanna Raf'ee, Kamaluddeen Usman Danyaro, and Noor Amila Wan Abdullah Zawawi

Subjects
Brick, Hot weather, lcsh:TA1-2040, Thermocouple, Thermal insulation, business.industry, Data logger, Temperature difference, Masonry, lcsh:Engineering (General). Civil engineering (General), business, Civil engineering, Interlocking
Abstract

This study seeks to measure the temperature difference of 3 types of interlocking bricks and 2 types of conventional bricks, all which are available in Malaysian market. The study aims to assist Malaysia’s residential construction dilemma in masonry. This is done by constructing 5 models using different types of bricks with the same dimensions, finishes and placed in the same area. Six points were taken to measure the temperature differences. The equipment used are 6 Thermocouples and HOBO UX120-014M data logger. Intervals of 15 minutes were recorded with duration of four months in Tronoh, Perak. Results show the best performed brick is IB2, even though IB1 and Clay bricks depict significant temperature differences. Comparing the temperature differences of IB1 and Clay brick, IB1 provide a better performance in a hot weather due to its higher thermal conductivity.

Published
2018

41. Web Intelligence

Author

Kamaluddeen Usman Danyaro, Mohd Shahir Liew, and Jafreezal Jaafar

Subjects
Web standards, medicine.medical_specialty, business.industry, Computer science, Social Semantic Web, World Wide Web, Web mining, medicine, Semantic Web Stack, Web intelligence, business, Web modeling, Semantic Web, Data Web
Abstract

This chapter discusses about the veracity of data. The veracity issue is the challenge of imprecision in big data due to influx of data from diverse sources. To overcome this problem, this chapter proposes a fuzzy knowledge-based framework that will enhance the accessibility of Web data and solve the inconsistency in data model. D2RQ, protégé, and fuzzy Web Ontology Language applications were used for configuration and performance. The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. The result shows that the D2RQ is more scalable with respect to performance comparison. Finally, the conclusion and future lines of the research were provided.

Published
2015

42. MetOcean data to linked data

Author

Jafreezal Jaafar, Mohd Shahir Liew, and Kamaluddeen Usman Danyaro

Subjects
Metocean, Information retrieval, Computer science, Server, InformationSystems_DATABASEMANAGEMENT, Graph (abstract data type), SPARQL, computer.file_format, Linked data, RDF, computer, Semantic Web, Data modeling
Abstract

This paper describes the Linked Data initiative in meteorological environment. MetOcean data are meteorological and oceanographic datasets that provide information to meteorological industries, petroleum industries as well as research institutes. The MetOcean has a myriad of data and scattered along the globe which lack Linked Data or Semantic Web capabilities. Linked Data is a concept of publishing interoperable data globally. As a way of integrating MetOcean data, this work used D2R server, a server that manages data sources and translates it to Web data. Therefore, the paper elucidates the process of developing Linked Data in Meteorological sector. Also, the results were queried using SPARQL endpoint as a graph. This approach was analyzed using F-measure which reveals the system is sufficient for querying and accessing the data as a graph.

Published
2014

43. Modeling RDF Data for MetOcean Information Systems

Author

Jafreezal Jaafar and Kamaluddeen Usman Danyaro

Subjects
Information retrieval, General Computer Science, Database, Computer science, RDF Schema, computer.file_format, Linked data, computer.software_genre, RDF/XML, Simple Knowledge Organization System, Semantic analytics, SPARQL, RDF, computer, RDF query language, computer.programming_language
Abstract

This paper suggests a Resource Description Framework (RDF) model for effective handling of distributed data relating to the Semantic Web. RDF is a data model that integrates aptly structured data. The World Wide Web is facing great challenges in data retrieval as a result of increase and request of knowledge from different sources. This brings the issue of information overload. Therefore, in minimizing this challenge, the paper presents the process of modeling RDF knowledge base which is the essential step of Semantic Web development. As a state-of-the-art research, a meteorological and oceanographic dataset has been used to provide the basic concepts of RDF serialization. The result accessed through the developed SPARQL endpoint. Thus, it implies that the approach is sufficient for querying as well as data representation of distributed data.

Published
2014

44. An RDF model for meteorological and oceanographic information systems

Author

Jafreezal Jaafar, Mohd Shahir Liew, and Kamaluddeen Usman Danyaro

Subjects
Information retrieval, Computer science, RDF Schema, Linked data, computer.file_format, computer.software_genre, Data model, Simple Knowledge Organization System, SPARQL, Data mining, RDF, computer, Data Web, RDF query language, computer.programming_language
Abstract

This paper suggests an RDF Model for effective management of distributed data on the Semantic Web. Resource Description Framework (RDF) is a data model that unifies aptly structured data. The Web is facing great challenge in data retrieval due to the increase and request of information from different sources. This brings the problem of information overload. In minimizing this problem, we provide a knowledge model for structuring data which is the first step of building Semantic Web. In particular, to elucidate the model, Meteorological and Oceanographic (MetOcean) data have been used. We present the result using SPARQL query method. Thus, the finding shows that the model is ideal for querying and data representation of distributed data.

Published
2012

45. A proposed methodology for Semantic Web implementation

Author

Jafreezal Jaafar, Mohd Shahir Liew, and Kamaluddeen Usman Danyaro

Subjects
Information retrieval, Computer science, business.industry, Interoperability, Semantic interoperability, Ontology (information science), computer.software_genre, Social Semantic Web, Semantic integration, Semantic Web Stack, business, computer, Semantic Web, Data integration
Abstract

Semantic Web provides precise, timely, searchable and well-define information across different sources of data. However, there is need of solving the problem of interoperability due to everyday increase of data from different sources. Whereby, the resourceful information or data integration between human and machines are needed. Thus, more precisely, this paper addresses an ultimate problem of integrating and utilizing the accurate data on information systems. The proposed methodology of this paper includes: (1) grounded theory that focuses on particular interaction between human and machines, (2) developing the analysis; the research introduces the Software Development Life Cycle (SDLC) approach, from the development to implementation stages, (3) sources of data; for state-of-the-art research, we propose to use MetOcean (Meteorological and Oceanographic) data, and (4) Research instrument which is to set our research into practice where we will build Semantic Web application using Franz AllegroGraph and use SIMILE (Semantic Interoperability of Metadata and Information in Unlike Environments). Finally, we provide the Ontology model of the for the state-of-the-art research in meteorological and Oceanographic domain.

Published
2011

46. Tractability method for ontology development of Semantic Web

Author

Kamaluddeen Usman Danyaro, Jafreezal Jaafar, and Mohd Shahir Liew

Subjects
Ontology Inference Layer, Information retrieval, Description logic, Knowledge representation and reasoning, computer.internet_protocol, Computer science, Ontology-based data integration, Upper ontology, Conjunctive query, Ontology (information science), computer, OWL-S
Abstract

Ontology is an explicit representation of a particular domain of interest. This paper focuses on the inherent problem of intractability (data complexity) due to data capturing for heterogeneous sources. We proposed to follow the tradition of knowledge representation and reasoning processes to develop a Semantic Web. Building query systems is the ultimate goal for this study. Conjunctive queries were adopted over ontology methods to address the data complexity. The Conjunctive queries are the form of queries in first-order logic that deal with conjunction (Λ) and existential quantification (∃) in database atomic formulae. State of the art meteorological and oceanographic domain provides the motivation for this work. We found that the querying method facilitates the tractability in reasoning and logical systems.

Published
2011

47. An evaluation of the usage of Web 2.0 among tertiary level students in Malaysia

Author

Rod Allan A. de Lara, Kamaluddeen Usman Danyaro, Alan G. Downe, and Jafreezal Jaafar

Subjects
Higher education, Web 2.0, Computer science, business.industry, media_common.quotation_subject, Information technology, World Wide Web, Misconduct, Feeling, ComputingMilieux_COMPUTERSANDEDUCATION, Cognitive development, Mathematics education, The Internet, business, Self-determination theory, media_common
Abstract

Web 2.0 is increasingly becoming a familiar pedagogical tool in higher education, facilitating the process of teaching and learning. But this advancement in information technology has further provoked the problems like plagiarism and other academic misconduct. This paper evaluates the patterns of use and behavior of tertiary level students towards the use of Web 2.0 as an alternative and supplemental eLearning Portal. A total of 92 students' data were collected and analyzed according to [1] 'Self-Determination Theory' (SDT). It was found that students use social websites for chatting, gamming and sharing files. Facebook, YouTube and Wikipedia are ranked as the most popular websites used by college students. It also reveals that students have an inherent desire of expressing ideas and opinion online openly and independently. This sense of freedom makes students feel more competent, autonomous or participative and find learning to be less tedious. Therefore, this report, recommends educators to adopt strategies for acknowledging students' feelings and activities online to reinforce positive behavior effective learning. Finally, we discussed the implications of Web 2.0 on education.

Published
2010

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