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- ItemA decision support model for demolition waste management(Universiti Teknologi Malaysia, 2018) Rakshanifar, MansoorehDemolition waste management is the process of managing, collecting, handling and disposing of waste in demolition projects. Significant effects on resource preservation, environment, and public health, and safety are the main concerns associated with demolition waste. Hence, lack of a sound decision making system for demolition waste management can negatively affect construction and demolition industry. Therefore, this study aimed to develop an integrated tool in order to assist decision making for demolition waste management. To achieve this target, overall review on the whole life cycle of demolition waste was conducted. In depth literature review and reliable interviews with experts have led to generation of a complete description of factors affecting waste management during demolition projects. Critical factors of demolition waste management were identified by considering risk assessment approach integrated with the Delphi method analysis. Next, critical factors affecting demolition waste management and different waste paths were assessed based on a consensus opinion from the experts’ panel. Analysis of the important data from the experts meeting session was conducted by using Analytic Network Process (ANP) Benefit, Opportunity, Cost and Risk (BOCR) model. ANP BOCR and Rating model have been used to rank the critical factors and demolition waste paths. To evaluate the developed model, the research used three case studies which were The Garden Premium Parking, Masjid AsySakirin and Putra Bus Station. The functionality of the model was evaluated by four evaluators. Conclusively, the result confirmed that the model satisfied 74.5% of the expectations. The developed model namely referred as Demolition Waste Management Model (DWMM) will enable the decision makers in a demolition project to systematically and semi-quantitatively identify, analyze and evaluate waste management factors. DWMM acts as information source that can be used by demolition contractors to identify and evaluate demolition waste related factors to be incorporated into the project design.
- ItemA millimeter wave reflectarray antenna with tilted side patch elements for fifth generation communication systems(Universiti Teknologi Malaysia, 2019) Dahri, Muhammad HashimA flat surface reflectarray antenna is becoming an impending competitor for fifth generation (5G) communications among the generally known conventional antenna systems. Its narrow bandwidth and high loss performance lead to restrict its gain and effciency at millimeter wave frequencies. Additionally, high design sensitivity is also an issue at millimeter waves that can trigger the problem of imperfect fabrications. Therefore, a simple design of reflectarray patch element is required with wide reflection phase range to achieve wideband and high gain performance. Effciency of reflectarray antenna is also needed to be formulated properly to acquire polarization diversity. In this work, a new reflectarray patch element with a tilted side is recommended for a wideband dual resonance operation within 24 GHz to 28 GHz frequency range. Dual resonance of the tilted side patch element offers a reflection phase range of more than 600' and a reflection loss of 1.6 dB with a novel design. Simulated results of the patch element have been verified by the scattering parameter measurements using a waveguide simulator. Additionally, a mathematical relationship has been formulated to predict the effciency of the reflectarray antenna based on its aperture shape and feed distance. It has been found that, a circular aperture reflectarray attains 21.46% higher effciency than its equivalent square aperture reflectarray of the same feed distance. Consequently, a circular aperture reflectarray consisting of 332 variable size tilted side patch elements has been designed and tested at 26 GHz with various possible configurations. The high cross polarization issue due to the asymmetric design of the tilted side patch element has been tackled by mirroring the orientations of the elements on the surface of reflectarray. Moreover, circular ring slots with variable radius have been embedded in reflectarray ground plane for gain improvement. Experimental results show that, the slotted ground reflectarray antenna offers a 3.5 dB higher gain with 22.9% higher effciency and 3% wider bandwidth than a full grounded reflectarray antenna. A maximum of 26.1 dB gain with 41.3% effciency and 11.5% (3 GHz) bandwidth has been acquired with the slotted ground reflectarray antenna. The tilted side patch reflectarray has offered dual linear polarization when its elements are mirrored to each other and dual circular polarization when its elements are not mirrored to each other. Its main beam has been numerically steered up to +20' by a progressive phase shift of 80'. The acquired parameters of the tilted side patch reflectarray antenna fit within the requirements of the 5G communication systems.
- ItemA model of argument quality for information adoption in e-commerce review platform(Universiti Teknologi Malaysia, 2020) Che Lah, Nur SyadhilaThe viral nature the content of the Web has transformed the landscape of e-Commerce review platforms to be in a state of constant growth. Similarly, the prominent features of these platforms have been recognized to be among the dominant factors in shaping online consumer behavior. Nonetheless, in this regard, if the review platform returns too many reviews, and the reviews are presented in non-relevant manner, in which this may be cumbersome and time-consuming for consumers. Therefore, identifying credible reviews that contain valuable information has becomes increasingly important for online businesses. The main research question to be addressed in this study is to determine on how can a model be developed to improve the argument quality perceptions in the adoption of online reviews across e-Commerce review platform. Subsequently, the main objective to be achieved is to develop a model of argument quality for review‘s adoption in the e-Commerce review platform. The potential effects of consumer relevance judgment from information retrieval perspective have been considered, which include perceived informative and affective relevance in developing the research model by using Elaboration Likelihood Model (ELM). A quantitative research method has been applied to test and validate the propose research model. The response data from 238 valid respondents was analyzed using the Partial Least Square Structural Modelling (PLS-SEM) technique. The findings from the results indicate that content novelty, content topicality, content similarity, content tangibility and content sentimentality could positively influence the perception of argument quality which lead to information adoption behavior. Finally, the importance of information relevancy was also highlighted in this study, which reveals some appropriate features that can be utilized by e-Commerce practitioners to better refine their information search criteria in the online review platforms.
- ItemA structure of waqf land declaration and registration system in Malaysia(Universiti Teknologi Malaysia, 2017) Ghazali, Noor AzimahUnder Islamic Law, waqf is special and differs from other properties and ownership because of the element of perpetuity, inalienability and irrevocability as soon as the waqif makes a declaration. Under Islamic law, the land or any property declared by individuals to become waqf is considered binding and valid as soon as the donor applies the five pillars (rukn) of waqf declaration, which are sighah, waqif, mauwquf, mawquf alaihi and nazir. However, under the Malaysian Land Law, waqf properties need to be registered at the Land Office to ensure the State Islamic Religious Council (SIRC) has indefeasible ownership under National Land Code (NLC), 1965. Even though, there exists a registration system of waqf land under the Malaysia Legal System, the system is lengthy, rather disorganized and can cause the declaration of a waqif to be defeasible and not binding, hence this risks the loss of the waqf land. This research has examined the existing structure for waqf land declaration and registration in order to improve its system within the scope of the Malaysian Legal System while being compliant to the Islamic Law. The research methodology adopted is the Content Analyses through System Theory Approach and semi-structured interviews with identified experts. The collected data were analyzed qualitatively. From the findings the researcher has identified that the declaration of waqif is defeasible and not binding because the waqf land is not free from encumbrances within the existing structure of waqf land declaration and registration system. Therefore, the research has developed a New Improved Structure of Waqf Land Declaration and Registration in Malaysia suggesting the declaration of waqif shall be valid, binding and indefeasible in future. In conclusion, the new proposed structure shall make the process of waqf land declaration and registration easier, faster, and more efficient hence; secure the waqf property from risk to be lost
- ItemA three-step strategy for generalization of three-dimensional buildings modelled in city geographic markup language(Universiti Teknologi Malaysia, 2013) Baig, Siddique UllahFor a better visual impression, three-dimensional (3D) information systems and landscape architectures need photo-realistic visualization of detailed 3D datasets. But easy accessibility with efficient rendering becomes difficult due to the detailed data associated with 3D objects. Therefore, different applications demand different levels of detail (LoD). A single generalization method cannot be applied to remove or preserve different pieces of building information on a certain LoD. Additionally, different generalization strategies produce different results for generalized models. Therefore, the aim of this thesis is to contribute the state-of-the-art in 3D generalization methodologies. This thesis proposes a 3D generalization framework based on a three-step (projection, generalization and reconstruction) strategy to generate less-detailed and more abstract representation of buildings modelled in the City Geography Markup Language (CityGML). The proposed strategy focuses specifically on simplification and aggregation of building footprints based on point-reduction, edge-removal and small circle strategies. Furthermore, vertex reduction method for simplification of complex shapes of building footprints is one of the contributions to the scientific field of 3D Geographic Information System (GIS). Experiments and results of the thesis show that 3D generalization based on the CityGML generalization specifications can avoid removal of important features of a building and fulfill the demands of task specific applications. Furthermore, mostly, data reduction is directly proportional to the length of edges as threshold value. However, the data volume of the generalized models is 10.5% for 4 meters and 30.62% for 6 meters threshold values. About 37.65% of data is reduced after generalization at LoD1 CityGML model as compared to 30.18% at LoD2. Furthermore, 3.31% boundary of building footprints of Putrajaya at 5 meters threshold value is observed as eliminated despite removing 52% smaller edges. The authenticity of generalized models is evaluated based on a comparison of similarity between original and generalized boundaries of building footprints. The proposed generalization strategy could be extended to generalize a group of buildings and maintain topological relationship among generalized LoDs
- ItemAdaptive anomaly based fraud detection model for handling concept drift in short-term profile(Universiti Teknologi Malaysia, 2018) Alabdeen, Aisha Abdallah ZainFraud is a cybercrime where the purpose is to take money by illegal means. Fraud results in significant losses to organizations, companies and government agencies. Detecting fraud accurately will have an impact on reducing such loss, for instance by using anomaly detection, which relies on behavioural modelling methods. The anomaly based Fraud Detection System (FDS) model aims to detect and recognize fraudulent activities or anomalies as they enter a system and report them accordingly. Many anomaly based FDSs have been proposed in the literature. However, current anomaly based FDS models have low accuracy, high false alarms and delayed detection due to the drifted behaviour over time (concept drift issue), developing behavioural patterns of customers, hidden indicators, and the large dimensionality. The main purpose of this research is to design and develop an adaptive anomaly FDS model based on concept drift detection technique using shortterm aggregation profile to improve fraud detection accuracy and support early fraud detection. To achieve this purpose, two main phases are involved: the first phase is the data pre-processing phase and the second phase is the fraud and concept drift detection phase. The data pre-processing phase contains two stages; firstly, deriving features and profile building and; secondly, the feature selection stage. The first stage in the pre-processing phase is to support early detection by using a combination of derived features and features derived from literature. A rank-search feature selection stage is a hybrid approach which consists of two steps; Support Vector Machines Recursive Feature Elimination (SVM-RFE) Rank method and Greedy Stepwise (GS) Search method. A feature selection stage is used to improve fraud detection accuracy by selecting optimum features of user behaviour. In the second phase of the proposed adaptive FDS model, the fraud and drift detection phase, an effective online streaming approach based on an incremental classifier is adopted to accuratelydiscriminate fraudulent from normal data. In the concept drift detection phase, the trigger based approach is used for adaptive learning, and an adaptive training window is used to manage training data. The Statistical Process Control (SPC) technique is used as a drift detector to identify the sudden and gradual drift in the users’ behaviour. The Call Details Records (CDR) dataset containing Subscriber Identity Module (SIM) Box fraud is used to test and evaluate the proposed model. The proposed adaptive Incremental Learning Strategy and Concept Drift Detection Technique (FDS-ILS-CDDT) model integrated with the rank-search feature selection approach improves the detection accuracy of the SIM Box fraud containing the concept drifts. The average detection accuracy on a daily basis for DATA-CP (continuous pattern) saw an increase from 91.16%, 88.08% and 90.81% to 91.40% for FDS-SLS, FDS-PLS and FDS-ILS models respectively. The same growth occurred for DATA-CDP (continuous and discrete pattern), from 84.55%, 83.81% and 85.11% to 89.34% for FDS-SLS, FDS-PLS and FDS-ILS models respectively. Furthermore, FDS-ILS-CDDT obtained the best performance for false negative rate and false positive rate compared with other FDS models. The features are reduced to two and eleven of the most relevant and influential features for DATA-CP and DATA-CDP respectively.
- ItemAdaptive model for web engineering methods to develop multi web applications in agile environment(Universiti Teknologi Malaysia, 2019) Said, Karzan WakilModel Driven Web Engineering (MDWE) is an application of a model driven paradigm in the domain of web software development. MDWE is helpful because technologies and platforms of web applications constantly evolve into Web Engineering Methods (WEMs). The evolution of web applications has consequently introduced new features and challenges, therefore existing WEMs need to be improved. These WEMs have failed to develop modern web applications’ features. Furthermore, no single WEM is capable of covering the whole lifecycle phases. These issues decrease the usability. In addition, the Interaction Flow Modeling Language (IFML) as a recent method has also not been able to address them. This thesis developed a new WEM, Useable Adaptive Agile IFML (UAA-IFML) to solve these issues in several steps. In this research, mixed methods used were qualitative and quantitative methodologies. In the first step, a new adaptive model was defined for supporting the features of multi-web applications. The new model was developed via an adaptive model into the IFML metamodels known as Adaptive IFML (AIFML). In the second step, IFML was enriched through MockupDD for covering lifecycle, known as Agile IFML (A-IFML). This is because MockupDD provides an agile environment, hence agile lifecycle can solve the lifecycle issue. In the third step, a new adaptive model and agile process were combined as Adaptive Agile IFML (AAIFML). This integration increased the usability of the IFML method. In presenting the usability of AA-IFML, experimentation of the framework was extended to evaluate the usability of WEMs. Besides, feedbacks on the usability of AA-IFML were obtained from developers around the world using three instruments, namely performing tasks, answering questionnaires, and interviewing experts. Analysis on the feedback indicated a 20% improvement usability of the AA-IFML compared with current IFML. The findings have shown that the UAA-IFML is beneficial for developers, as they would only need to use one method to design modern web application features in the whole lifecycle phases.
- ItemAgile development in cloud computing for eliciting non-functional requirements(Universiti Teknologi Malaysia, 2019) Younas, MuhammadAgile is a popular and growing software development methodology. In the agile methodology, requirements are refined based on collaborations with customers and team members. However, the agile process faces a lack of visibility across the development and delivery processes, has complex and disjointed development processes and lacks communication agility between disconnected owners, development teams, and users. Furthermore, Non-Functional Requirements (NFR) are ignored due to the nature of agile development that lacks knowledge of the user and developer about NFR. In addition, extraction of the NFR is difficult and this difficulty is increased because the agile methodology promotes change in requirement at any stage of the development. Cloud computing services have helped solve some of the issues in the agile process. However, to address the issues in agile development, this research developed a framework for Agile Development in Cloud Computing (ADCC) that uses the facilitation of cloud computing to solve the abovementioned issues. An Automated NFR eXtraction (ANFRX) method was developed to extract NFR from the software requirement documents and interview notes wrote during requirement gathering. The ANFRX method exploited the semantic knowledge of words in the requirement to classify and extract the NFR. Furthermore, an NFR Elicitation (NFRElicit) approach was developed to help users and development teams in elicitation of NFR in cloud computing. NFRElicit approach used components such as an organization’s projects history, ANFRX method, software quality standards, and templates. The ADCC framework was evaluated by conducting a case study and industrial survey. The results of the case study showed that the use of ADCC framework facilitated the agile development process. In addition, the industrial survey results revealed that the ADCC framework had a positive significant impact on communication, development infrastructure provision, scalability, transparency and requirement engineering activities in agile development. The ANFRX method was evaluated by applying it on PROMISE-NFR dataset. ANFRX method improved 40% and 26% in terms of f-measure from the Cleland and Slankas studies, respectively. The NFRElicit approach was applied to eProcurement dataset and evaluated in terms of more “Successful”, less “Partial Success” and “Failure” to identify NFR in requirement sentences. The NFRElicit approach improved 11.36% and 2.27% in terms of increase in “Successful” NFR, decrease of 5.68% and 1.14% in terms of “Partial success” and decrease of 5.68% and 1.13% in terms of “Failure” from the Non-functional requirement, Elicitation, Reasoning and Validation (NERV) and Capturing, Eliciting and Predicting (CEP) methodologies, respectively. The findings have shown the process was able to elicit and extract NFR for agile development in cloud computing.
- ItemAn adoption model of cloud enterprise resources planning for Malaysian small and medium enterprises(Universiti Teknologi Malaysia, 2019) Salum, KhamisThe Cloud Enterprise Resource Planning (ERP) system offers promising benefits for the development of Small and Medium Enterprises (SMEs). It helps to address many of the challenges faced by SMEs and significantly promotes them in terms of business operations and use of resource. Despite its benefits, the research on cloud ERP adoption among SMEs in developing countries has not been fully explored, leading to a low rate of cloud ERP adoption among SMEs. Furthermore, the factors which influence SMEs to adopt the cloud ERP system are still unclear. In an attempt to tackle the aforementioned situation, this research investigated the influencing factors that have determined and enhanced cloud ERP adoption rates. To identify factors and develop the model used in this research, the researcher conducted a Systematic Literature Review (SLR). The model was proposed based on three integrated Information System (IS) predominant theories, namely, Technology- Organization-Environment (TOE) framework and Fit-Viability Model (FVM) with extension of Diffusion of Innovation (DOI) theory to scrutinize the influential factors leading towards Cloud ERP Adoption. Thirteen hypotheses were developed to test and validate the model based on the decision to adopt cloud ERP. A positivism paradigm with quantitative approach was applied to conduct this research. Purposive sampling technique and a survey method were applied and data were collected from SMEs who have already adopted cloud ERP that provided 174 usable responses. The analysis was conducted by using Structural Equation Modeling (SEM) technique through Partial Least Squares (SmartPLS 3.2.7) software to determine the significant relationships of the independent factors to Cloud ERP Adoption. The results showed that Task- Technology Fit, Task Interdependence, Relative Advantage, Compatibility, System Trust, Security, Top Management Support, Employee Cloud ERP Knowledge, Cost Saving, and Competitive Pressure were significantly related to Cloud ERP Adoption. On the other hand, Security was found to have no relationship (p > 0.05) with Task- Technology Fit. Similarly, Government Support and Vendor Support were found to have no relationship (p > 0.05) with Cloud ERP Adoption. In line with this, the research model can be explained as 65.2% of variance from all the independent variables. This implies that the model has substantial predictive power to explain cloud ERP adoption. Finally, this model can be used to guide cloud ERP ecosystems to enhance their knowledge so as to successfully evaluate and adopt the cloud ERP system.
- ItemAn effective attack scenario construction model based on two-tier feature selection and coarse grain cleaning(Universiti Teknologi Malaysia, 2018) Mohammed Alhaj, Tagwa AhmedAttack Scenario Construction (ASC) via Alert Correlation (AC) is important to reveal the strategy of attack in terms of steps and stages that need to be launched to make the attack successful. Previous works on AC used two approaches which are Structural-based Alert Correlation (SAC) that clusters the alerts features to reveal a list of attack steps, and Casual-based Alert Correlation (CAC) which classifies the alerts based on the cause-effect relationship. However, major limitations of previous works have been found to have false and incomplete correlations due to inaccurate attack step identification based on different set of features, infiltration of raw alerts and failure to identify the sequence of attack stages. Therefore, an ASC model was developed to select significant features and to discover the complete correlations. Firstly, this research designed a two-tier feature selection using Information Gain (IG) for optimal accuracy on attack steps identification. Secondly, preserving the alerts using coarse grain cleaning for accurate attack stages identification was carried out. Finally, an effective attack scenario model to discover a complete relationship among alerts by identifying and mapping the related alerts was constructed. The model was successfully experimented using two types of datasets which are DARPA2000 and ISCX2012. The Completeness and Soundness of the model were measured to evaluate the overall correlation effectiveness. The existing works achieved 76% average completeness in comparison to the proposed model which achieved 100% completeness resulting in a 24% improvement. With regard to soundness measurement, the existing work scored 83.055% soundness while the proposed model soundness reached 100%, which has a 16.9% improvement. The findings has shown that this research is significant to Security Analyst (SA) for designing responsive and preventive mechanisms which are effective and reliable in protecting and securing computer networks.
- ItemAn ensemble-based anomaly-behavioural crypto-ransomware pre-encryption detection model(Universiti Teknologi Malaysia, 2019) Al-Rimy, Bander Ali SalehCrypto-ransomware is a malware that leverages cryptography to encrypt files for extortion purposes. Even after neutralizing such attacks, the targeted files remain encrypted. This irreversible effect on the target is what distinguishes crypto-ransomware attacks from traditional malware. Thus, it is imperative to detect such attacks during pre-encryption phase. However, existing crypto-ransomware early detection solutions are not effective due to inaccurate definition of the pre-encryption phase boundaries, insufficient data at that phase and the misuse-based approach that the solutions employ, which is not suitable to detect new (zero-day) attacks. Consequently, those solutions suffer from low detection accuracy and high false alarms. Therefore, this research addressed these issues and developed an Ensemble-Based Anomaly-Behavioural Pre-encryption Detection Model (EABDM) to overcome data insufficiency and improve detection accuracy of known and novel crypto-ransomware attacks. In this research, three phases were used in the development of EABDM. In the first phase, a Dynamic Pre-encryption Boundary Definition and Features Extraction (DPBD-FE) scheme was developed by incorporating Rocchio feedback and vector space model to build a pre-encryption boundary vector. Then, an improved term frequency-inverse document frequency technique was utilized to extract the features from runtime data generated during the pre-encryption phase of crypto-ransomware attacks’ lifecycle. In the second phase, a Maximum of Minimum-Based Enhanced Mutual Information Feature Selection (MM-EMIFS) technique was used to select the informative features set, and prevent overfitting caused by high dimensional data. The MM-EMIFS utilized the developed Redundancy Coefficient Gradual Upweighting (RCGU) technique to overcome data insufficiency during pre-encryption phase and improve feature’s significance estimation. In the final phase, an improved technique called incremental bagging (iBagging) built incremental data subsets for anomaly and behavioural-based detection ensembles. The enhanced semi-random subspace selection (ESRS) technique was then utilized to build noise-free and diverse subspaces for each of these incremental data subsets. Based on the subspaces, the base classifiers were trained for each ensemble. Both ensembles employed the majority voting to combine the decisions of the base classifiers. After that, the decision of the anomaly ensemble was combined into behavioural ensemble, which gave the final decision. The experimental evaluation showed that, DPBD-FE scheme reduced the ratio of crypto-ransomware samples whose pre-encryption boundaries were missed from 18% to 8% as compared to existing works. Additionally, the features selected by MM-EMIFS technique improved the detection accuracy from 89% to 96% as compared to existing techniques. Likewise, on average, the EABDM model increased detection accuracy from 85% to 97.88% and reduced the false positive alarms from 12% to 1% in comparison to existing early detection models. These results demonstrated the ability of the EABDM to improve the detection accuracy of crypto-ransomware attacks early and before the encryption takes place to protect files from being held to ransom.
- ItemAn improved image steganography scheme based on distinction grade value and secret message encryption(Universiti Teknologi Malaysia, 2020) Taha, Mustafa SabahSteganography is an emerging and greatly demanding technique for secure information communication over the internet using a secret cover object. It can be used for a wide range of applications such as safe circulation of secret data in intelligence, industry, health care, habitat, online voting, mobile banking and military. Commonly, digital images are used as covers for the steganography owing to their redundancy in the representation, making them hidden to the intruders, hackers, adversaries, unauthorized users. Still, any steganography system launched over the Internet can be cracked upon recognizing the stego cover. Thus, the undetectability that involves data imperceptibility or concealment and security is the significant trait of any steganography system. Presently, the design and development of an effective image steganography system are facing several challenges including low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel's bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme was assessed experimentally to determine the imperceptibility, security, robustness and capacity. The standard USC-SIPI images dataset were used as the benchmarking for the performance evaluation and comparison of the proposed scheme with the previous works. The resistance of the proposed scheme was tested against the statistical, F2 , Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of higher imperceptibility and security by the proposed DGV scheme while a higher capacity compared to previous works. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues.
- ItemAn instrument to measure students’ readiness for embedded system design course(Universiti Teknologi Malaysia, 2019) Ridwan Saeed, Intisar IbrahimEmbedded Systems Design has emerged as one of the fastest growing areas in the world. In this regard, higher education institutions acknowledge the significance for offering Embedded Systems Design course to fulfil the needs of skilled human resources in the field. Unfortunately, being a highly difficult and specialized course, it requires students to have sufficient body of knowledge courses in both theory and practice. To address this issue, this study proposed an instrument to measure students’ readiness for Embedded Systems Design course. The study was conducted using a sequential exploratory mixed method design. First, a survey instrument named MeSRESD which consisted of 10 scales and 89 items was developed. MeSRESD assessed students’ cognitive, affective, and psychomotor skills through holistic assessment by taking into account the domains of technical skills, critical thinking skills, communication skills, team working skills, entrepreneurship skills, lifelong learning skills, level of interest, attitude, and prior experience. Content validity of MeSRESD was verified using content validity index (CVI) and content validity ratio (CVR). All MeSRESD scales showed CVI and CVR ranging from 0.92 to 1.00 and from 0.88 to 1.00 respectively, establishing an excellent content validity. A pilot study on 40 students was performed to assess the Cronbach’s alpha scale reliability. The results obtained were from 0.73 to 0.92 using Statistical Package for Social Sciences (SPSS 23.0) and from 0.70 to 0.99 using WINSTEPS 3.92.1, indicating an excellent internal consistency reliability. MeSRESD construct validity was established using Rasch Analysis and WINSTEPS 3.92.1. The results showed that all scales fitted the Rasch measurement model with acceptable fit index from 0.6 to 1.4 and demonstrated excellent consistency, with a reliability index from 0.97 to 0.99 for items and from 0.70 to 0.88 for persons. The unidimensionality of each MeSRESD scales was evaluated using principal component analysis. Based on these results, we concluded that the survey instrument was valid and reliable. MeSRESD was administered in nine universities in Malaysia, Sudan, and Saudi Arabia. A total of 415 questionnaires with a response rate of 97.4% were analysed. Based on the literature review, the readiness threshold of 3.40 was selected. However, the students’ mean scores of MeSRESD scales were from 2.47 to 2.89, which were lower than the threshold. In light of these results, the study revealed strong evidence that students lack prior knowledge and had poor understanding of Embedded Systems Design course. They possessed poor proficiency in critical thinking, communication, team working, entrepreneurship, and lifelong learning skills. In addition, they had low level of interest, lack of prior experience and had negative attitude towards learning Embedded Systems Design course. Therefore, there is a need for universities to address this issue and take remedial action to improve the chance of academic success for the students not only in Embedded Systems Design course, but also in other related courses.
- ItemAn organizational attraction model of university entrepreneurship centre for web content(Universiti Teknologi Malaysia, 2020) Minouei, AminUniversity Entrepreneurship Centres (UEC) portray their organizational identity to potential students through their website in order to attract them to enroll in their entrepreneurship educational programs. Thus, UECs need to identify the influence of each organizational identity factors as their website content in creating the ideal attitudes in students as to attract them to their programs. The objectives of this study are, firstly, to identify the importance of UECs website content that leads to organizational attraction. Secondly, to propose an organizational attraction model for the university entrepreneurship centre web content to reflect on the influence of identified website content factors on the UEC’s organizational attraction. And thirdly, to evaluate the influence of identified website content factors on UEC’s organizational attraction. This research applied a quantitative method approach following a positivistic paradigm. Several models of organizational identity, image and attractiveness were employed and a research model was then developed based on a comprehensive literature review. A questionnaire was designed to enable the survey to be included as part of the data collection method. With 445 returned questionnaires in hand, the collected data were analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique. The results showed that the organizational attractiveness of UEC was affected by students’ attitude toward UEC as an organization, which itself was affected by UEC’s website design (WD), UEC’s identity (UECI) Perception, and Students attitude toward website (SATW). The results of this study showed that Industry Interaction (II), Producing Highly Qualified Graduates (PHQG), Team Working (TW), and Risk Taking (RT) are empirically proven to be the effective factors on Students Attitude Toward UEC as an Organization (SATO). Meanwhile, Innovativeness (INNO), Attracting Entrepreneurial Faculty (AEF), and Consultation (CONS) are empirically proven to be the effective factors on SATW which indirectly affect the SATO. Finally, the effectiveness of Proactiveness (PA) on SATW and SATO was not proven to be effective. These findings can be of pioneers in the field of UECs online attractiveness, and they contribute to the Organizational Impression Management. The proposed model in this study can be used by universities’ corporate office managers and web designers to enhance their UEC’s organizational attraction in the World Wide Web.
- ItemAplikasi teknik remote sensing bagi terbitan maklumat hasilan air di Semenanjung Malaysia(Universiti Teknologi Malaysia, 2014-03) Ali, Mohamad IdrisSatellite remote sensing techniques have found wide applications in hydrology including water-yield determination. This however requires the localization to area-of-interest that are influenced by the local climate and biophysical factors. This study focussed to develop a method for determining the water-yield information through full satellite-based data for Peninsular Malaysia from the public domain sources, for a period of 10 years (July 2000 - June 2010). The specific objectives were to investigate on: (i) derivation of information on monthly rainfall from Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) satellite data; (ii) derivation of monthly Actual- Evapotranspiration (AET) from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite with Normalized Differential Vegetation Index (NDVI) data product; (iii) derivation of water yield from fully satellite-based information using water balance analysis; and (iv) water yield variation, with respect to changes of corresponding land cover and land use. Results, indicated good correlation between monthly rainfall TMPA with the corresponding rain gauge records (r2=0.71: p<0.001, n=1337) with accuracy (RMSE) of +83 mm (n=2308). The TMPAcalibrated annual averaged rainfall for the entire study area is 2357mm, which is - 5.3% compared with independent studies undertaken by an international consultant appointed by the government. The bio-physical parameters based on MODIS used NDVI as an indicator of AET to represent the land use, reported good match-up (r2=0.55: p<0.001, n=1664) with accuracy (RMSE) of +15 mm (n=864). The NDVIcalibrated annual averaged AET throughout the study area was determined at 1153mm, which is -9.9% compared with the same independent research report. Annual averaged water-yield for the entire study area is 1204mm, with -0.5% and 1.6% variations when compared to the two independent studies, the same independent research report and, Drainage and Irrigation Department respectively. But at state level, the estimated rainfall, AET and water-yield varies with larger magnitudes. Analysis at selected basin level, the annual water-yield is determined at 1393mm, in access of 9.5% compared to the independent studies water flowrate, with a standard deviation of 22%. The regression analysis between water-yield and land use cover changes, clearly indicated strong relationship (r2=0:51, p<0.0001; n=151), and independent accuracy (RMSE) of 8.3% (n=154). The main findings in this study, especially the devised techniques indeed have contributed significantly as an alternative method for the determination of water-yield in Peninsular Malaysia based on fully satellite-driven data. The devised method could be accustomized to other areas through localised calibration approach thus, could serve as a guideline for the relevant authorities to have accurate and comprehensive water-yield information
- ItemAutomation of integrated system on MyCREST and life cycle costing(Universiti Teknologi Malaysia, 2019) Khan, Jam ShahzaibThe global building construction activities is responsible for 30-40% of global energy consumption thus with this contributes around 30% of greenhouse gas emissions. The holistic approach by green buildings recon can reduce 30-50% of energy usage, 35% of CO2 emissions, 70% of waste generation and 40% of water usage. However, the decline in financial markets and economic turmoil has meltdown interest of investors towards green-certified buildings due to higher cost implications and needed bigger capital. Additionally, Green Building Rating Tools (GBRT) do not provide Life Cycle Cost (LCC) analysis, where at the same time is a lack of available decision making support tool for GBRT integrated with LCC. This research developed an integrated web-based system which has applied GBRT, computer programming, and LCC analysis. This study has used Malaysia Carbon Reduction and Environment Sustainability Tool (MyCREST) for the integration with LCC. The study identified criteria, sub-criteria and super sub-criteria of MyCREST and with elements of LCC that combine to develop an integrated framework, thus later was transformed into an automated analogue computerised programming system using architectural programming flow system. Twenty-five sets of matrix form of MyCREST and LLC have been developed for the confirmation of professional in the field of GBRT and LCC. Two levels of Focus Group Discussions (FGD) were conducted amongst Qualified Professionals QP?s of GBRT. The quantitative data were analysed using (SPSS V.17) software that achieved frequency analysis, factor score analysis, weightage factor analysis and developed the cost control weightage distribution. The results output led to the development of cumulative control weightage of LCC. The cumulative cost control weightage indicates management cost 35%; development cost 20%; operation cost 14%; construction & installation cost 11%; maintenance cost 10%; replacement cost 6%; and contingencies cost 4%. The achieved cumulative control weightage is later were formulated into automated analogue computerised programming whereby this web-based innovation is named MyCREST-LCC. This MyCREST-LCC tool provides easy, efficient and effectively integrated programming that also offers to forecast of lifetime cost occurrence in green buildings. In conclusion, this innovative new approach of integrated automated web-based MyCREST-LCC assists construction stakeholders in the construction industry for providing a better, easy and quick way of decision making. The outcome adds value to green building project development, thus mapping the future cost that incurs in any proposal of green building development either locally or international wide.
- ItemBehavioural intention model of facebook usage for weight loss among young women in Sudan(Universiti Teknologi Malaysia, 2022) Abdelguiom Mohme, Ghada AhmedObesity among young Sudanese women has a negative influence on the healthcare system as it raises the expense of medical care and increases the risk of maternal and reproductive health issues. Prior studies on the use of technology to overcome obesity focused mostly on the technological perspective and ignored the health beliefs factors. This study aims to propose and validate the behavioural intention model for using Facebook (FB) for weight loss among young women in Sudan by integrating the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB) (C-HBM-TPB). A quantitative research approach was adopted, specifically the survey method. Using purposive sampling, 250 respondents entailing young women who attend fitness and gym centres in Khartoum state (Sudan) were selected. Data analysis was performed using SmartPLS Version 3 based on Structural Equation Modelling (SEM). The empirical results revealed that significant factors that influence behavioural intention to use FB for weight loss among the young women in Sudan were as follows: Perceived Susceptibility, Perceived Severity, Perceived Threat, Attitude, Subjective Norm, and Perceived Behavioural Control. In addition, the findings showed that perceived threat had a positive mediation role in the link between perceived susceptibility, perceived severity, and behavioural intention to use FB for weight reduction among young Sudanese women. In this context, the Level of Income was also explored as a moderator variable in the link between Attitude, Subjective Norm, Perceived Behavioural Control, and Behavioural Intention. The findings show that the Level of Income has a positive moderator influence on the association between Attitude and Perceived Behavioural Control and Behavioural Intention. However it has no moderator role in the relationship between Subjective Norm and Behavioural Intention. This study adds to the body of knowledge, particularly in the information systems (IS) domain, by presenting a comprehensive and integrated model capable of explaining 74% of the variance. In addition, according to the results of the Importance- Performance Matrix Analysis (IPMA), Perceived Susceptibility is the most important factor influencing the Behavioural Intention to use FB for weight loss, followed by Perceived Severity, Perceived Threat and Subjective Norm. The integrated C-HBMTPB model can assist creators of FB groups for weight loss in identifying the most important elements impacting the use of FB for weight loss.
- ItemBig Data acquired by Internet of Things-enabled Industrial Multichannel Wireless Sensors Networks for Active Monitoring and Control in the Smart Grid Industry 4.0.(Mendeley Data, 2021-03-09) Butt, Rizwan Aslam; Fizza, Ghulam; Ngadi, Md Asri; Muhammad Faheem; Waqar, Muhammad Waqar; Gungor, Vehbi Cagri• The data provided in this paper provides can be used for efficient monitoring and control of the power generation and distribution processes in the smart grid. • The data provided in this paper can be used for the integration of distributed power generation sources into the power transmission and distribution systems within realistic network scenarios. • It can also support reliable and dynamic data capacity requirements of different types of advanced cyber-physical systems equipped with sensors and devices to operate them optimally, either manual or automatic controls, and provide information about their operations to the utilities. • In case of faults, the designed scheme intelligently monitoring and identifies the faulty systems located in a remote position and notifies the user in real-time, so that appropriate actions can be taken to supply steady electricity to the customers.
- ItemBig data framework for quantity surveying firms in Malaysia(Universiti Teknologi Malaysia, 2020) Maaz, Zafira NadiaBig data emerges as a technology that improves decision making capability, optimizing productivity, and capable of generating a financial return in organizations across industries. Like many others, the benefit of big data is imminent, prompting construction organizations to redesign the conventional construction processes, thus stimulating change to the construction practices. While big data does improve productivity, any construction organizations which aspire to leverage its benefit will require a refreshed mindset and a new set of capabilities. Recognizing the importance of big data to the future of construction in Malaysia, there has been a strong push by the construction authorities for big data initiatives across organizations given the Construction Industry Transformation Programme (CITP) 2016-2020. Though the initiatives from CITP 2016-2020 managed to introduce big data to the construction organizations, there appear to be a fraction of construction organizations in Malaysia that are lagging behind the others to embrace big data. A clear case is Malaysian quantity surveying (QS) firms, where a limited big data adoption strategy was observed, creating a knowledge gap that hinders the Malaysian QS firm's capability to move forward with big data. Against this background, this research aims to develop a big data conceptual framework as a basis to support Malaysian QS firm's strategic big data adoption. The research outlines four objectives which include identifying big data potentials for QS, identifying attributes supporting QS firm's big data success, developing a conceptual big data framework for QS firms in Malaysia, and validating the big data framework for QS firms to support their strategic big data adoption. Adopting the TOE framework and the 5G innovation model as theoretical underpinnings, the research adopted Charmaz's grounded theory approach where sixteen QS with known experience in handling big data were contacted and interviewed. Data analysis revealed nine big data potentials for QS which are optimized data access, national cost data establishment, cost control data-driven decision making, project management data-driven decision making, development management data-driven decision making, work synchronization, data commercialization, diversifying professional services and strategic policy establishment. Likewise, seven big data attributes supporting the QS firm's big data success were identified which are data, people, technology, financial investment, strategic alignment, power, and collaboration. The conceptual framework demonstrates QS strategic big data adoption sequentially follows 'creating big data', 'big data buy-in', and 'revolutionizing through big data' phases. Each phase detailed specific big data potentials that the Malaysian QS firms can achieve, subject to the firm's resources and facilities availability. Framework validation was administered with the research participants and big data experts using a questionnaire survey to establish conformity. It was concluded that big data is a universal technology for the QS firms but, requires a unique set of big data attributes appraised from the peculiarities of its context of adoption. This research contributes by identifying big data potentials and attributes supporting big data success for QS firms. Further, it provides insights for policymakers, regulators, and authority bodies to strategically maximize their capabilities in advancing Malaysia's big data agenda.
- ItemBuilding information modeling adoption model for architecture,engineering and construction industry in Malaysia(Universiti Teknologi Malaysia, 2022) Faisal Shehzad, Hafiz MuhammadBuilding Information Modeling (BIM) is a modelling technology and an associated set of processes to produce, communicate, analyze, and use information models for the construction project life cycle. The BIM application developers provide a suite of BIM software that facilitates project delivery from early-stage design through to construction. The construction industry in Malaysia suffers productivity deficiency due to a lack of modern technologies such as BIM. The Malaysian construction sector is now implementing level one BIM (3D modelling with Revit and Sketch up), whereas the rest of the world is aiming towards level four or higher (4D Scheduling, 5D Costing, 6D Sustainability, and 7D Maintenance & Operation). In Malaysia, BIM adoption has been relatively unexplored, especially in Architecture, Engineering and Construction (AEC) organizations. Meanwhile, the lack of a theoretical framework is recognized as the central gap, as there are limited studies that used technology acceptance theories. Moreover, the influence of organizational, environmental, and interoperability factors on BIM adoption got limited attention in existing studies. Therefore, the purpose of this research was to empirically examine the factors that influence BIM adoption in the Malaysian AEC industry. A quantitative approach was adopted with data collection from AEC decision-makers. The survey instrument was distributed to 1,200 AEC organizations, with 552 responses obtained. After the data screening process, 279 valid answers for further analysis of the data were utilized. The proposed model's theoretical foundations were based on technology, organization, environment framework, Diffusion of Innovation theory, and European Interoperability framework. The model was tested and validated using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS software. The findings indicated that relative advantage, top management support, government support, organizational readiness, and regulation support were the drivers of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, and organizational interoperability were barriers to BIM adoption. Finally, this study provides implications of the essential technological, organizational, environmental, and interoperability factors that AEC stakeholders can address to enhance BIM adoption in Malaysia.