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The perception of rural community on Libya 2020 vision in improving livelihood in Tripoli, Libya
No full textAs part of efforts to promote sustainable peace in Libya and prevent the country’s relapse into conflict, Libya Vision 2020 was established. However, rural community in Libya still faced an issue in rural development such as adequate economic and social infrastructure, high cost of agriculture, political crisis, public health, sanitation problems and others. Therefore, this study was conducted with the aim of examining the perception of rural community on Libya vision 2020 in improving livelihood in Tripoli, Libya. The methodology undertaken in this study was based on a quantitative approach to evaluate the impacts of strategy in Libya vision 2020 on rural community livelihood in Libya. The selected study area is Tripoli, Libya bordered by towns that are included in Libya Vision 2020. Based on random sampling, 128 respondents were selected from Tripoli to participate in household survey. The trust in Libya Vision 2020 were used in this research comprise Economic Development (5 indicators) and human development (7 indicators). The data were analysed using frequency-based measurement. Implementation response for Libya vision 2020 receive positive response which is most of the response cross the 80 per cent. For determine action Libya vision 2020 improving livelihood, there is 92.5 per cent of respondents are indifferent, while 7 per cent is opposed to the re-establishment of national identity by such procedures and acts. It necessitates a community-level mechanism, with 80.4 per cent of respondents indicating a favourable reaction. In comparison, 13.3 per cent indicate neutrality for any system due to a lack of prior experience and action at such a level. The recommendations on the unsuccessful Libya vision 2020 is include key areas of peace, security, and economic development to linked with the progress and implementation of Libya’s vision 2020
Text detergent: The systematic combination of text pre-processing techniques for social media sentiment analysis
No full textDuring catastrophes such as natural or man-made disasters, social media services have evolved into a crucial tool utilised by communities to disseminate information. Because a vast number of social media data is being used for many applications, including sentiment analysis, sentiment analysis has become a very useful and demanding problem. Social media data cannot be applied directly because it is raw and unstructured or semi-structured data. Consequently, text pre-processing becomes one of the most important tasks because the process is strongly constrained by its dependable workflow. This reason creates a complex pattern in pre-processing workflows. For this purpose, different text pre-processing techniques have been used on Twitter, Facebook, and YouTube datasets to study the impact of different pre-processing techniques on the accuracy of machine learning algorithms. This paper applied different text pre-processing techniques in a specific sequence based on significance testing. This study examines their influence on sentiment classification accuracy using a machine learning classifier, Support Vector Machines (SVM). Results proved that applying all 14 techniques systematically can achieve up to 82.57% of the accuracy of the SVM classifier with unigram representations. By using Text Detergent, the YouTube dataset achieve the highest accuracy compared to Facebook and Twitter datasets. This will potentially improve the quality of the text and leads to better feature extraction, which in turn helps the sentiment analyst produce a better classifier
Validating mobile forensic metamodel using tracing method
No full textMobile Forensic (MF) is a branch of digital forensic used to collect and analyze mobile device crimes. Several forensic models and frameworks have been proposed in the literature for the MF domain to identify, acquire, and investigate MF crimes. However, these models are redundant and developed for specific purposes. Therefore, the authors developed a metamodel to solve the redundancy and heterogeneity of the MF domain called Mobile Forensic Metamodel (MFM). However, the MFM has not been evaluated from the modeling perspective to evaluate the effectiveness of the MFM in terms of instantiation solution models for the MF domain. Thus, this paper aims to evaluate the effectiveness of the MFM using a tracing method. The tracing method is a common way of validating metamodels through reasonable reliability on the domain application of the metamodel to assess the logical consistency of metamodels against domain models. For this purpose, two real scenarios were selected to confirm the capabilities of developed MFM in instantiate solution models for problems in hands. From real scenarios, the developed MFM was found to be scalable, logical, complete, interoperable, coherent, and useful for the MFM domain
Validating mobile forensic metamodel using tracing method
No full textMobile Forensic (MF) is a branch of digital forensic used to collect and analyze mobile device crimes. Several forensic models and frameworks have been proposed in the literature for the MF domain to identify, acquire, and investigate MF crimes. However, these models are redundant and developed for specific purposes. Therefore, the authors developed a metamodel to solve the redundancy and heterogeneity of the MF domain called Mobile Forensic Metamodel (MFM). However, the MFM has not been evaluated from the modeling perspective to evaluate the effectiveness of the MFM in terms of instantiation solution models for the MF domain. Thus, this paper aims to evaluate the effectiveness of the MFM using a tracing method. The tracing method is a common way of validating metamodels through reasonable reliability on the domain application of the metamodel to assess the logical consistency of metamodels against domain models. For this purpose, two real scenarios were selected to confirm the capabilities of developed MFM in instantiate solution models for problems in hands. From real scenarios, the developed MFM was found to be scalable, logical, complete, interoperable, coherent, and useful for the MFM domain
Importance of community participation for placemaking
No full textThe research aimed to outline the importance of community participation in a placemaking process. Placemaking is implying human attachment to places that are appealing and fit for their intended uses. Placemaking stresses the importance of community participation and decision-making, this type of engagement builds an important link and attachment between the people and the area where they reside. Despite the understand of the need of public participation, many placemaking process still use a top-down or expert-driven decision making in the process. The research has noted that the public participation in an urban planning and decision making in general can maximize the satisfaction with planning outcomes, project lifespan and possibilities for increasing civic engagement and interest. Some of the researchers also highlighted to the planners to actively involve the local community to recognise the people’s right to the city from the beginning. In order to support the research statements, 3 case studies were carried out in the Kuala Lumpur and Penang Island context. The selected case studies were made with comparison with different initiative party and community engagement process. The case study comparison outlined the importance of community engagement during the placemaking process. Placemaking project that had engaged with the local community has resulted to be more sustainable in the long run
Keperluan pembangunan hotel dalam menampung aktiviti pelancongan
No full textPembangunan sesebuah negara dapat dilihat dari situasi ekonomi semasa. Pergerakan ekonomi yang aktif akan menjana pendapatan sesebuah negara. Sektor ekonomi memainkan peranan atau fungsi masing-masing yang mana ianya saling melengkapi dalam pembangunan sesebuah negara. Antara sektor yang paling menjadi aktiviti pilihan yang mampu menggerakkan ekonomi setempat ialah industri pelancongan. Daerah Besut, Terengganu dilihat antara kawasan yang aktif menerima pelancong. Daerah Besut mempunyai gerbang pelancongan yang unik dan dinamik mampu mencorak kepelbagaian aktiviti pelancongan dan menggamit ramai pengunjung tempatan dan pelancong antarabangsa. Pusat-pusat peranginan pantai di Daerah Besut, Terengganu mempunyai tahap kemudahsampaian yang tinggi dan kemudahan infrastruktur yang baik seiring dengan kemajuan sektor pelancongan negara. Kelestarian aktiviti pelancongan perlu selari dengan pembangunan sektor ekonomi dan pembangunan harta tanah di daerah ini. Pembangunan penginapan yang sedia ada lebih menjurus kepada hotel bajet dan berbentuk chalet. Oleh yang demikian, kajian ini bertujuan untuk mengenal pasti penawaran hotel sediada adakah mencukupi untuk menampung industri pelancongan, mengenal pasti keperluan pembangunan hotel yang mempunyai penarafan bintang sebagai mercu tanda dan ciri-ciri pembangunan hotel. Skop kajian ini adalah melihat keperluan pembangunan hotel di Daerah Besut, Terengganu. Kajian ini menggunakan kaedah kualitatif dimana data dikumpulkan melalui kaedah temubual dan dianalisis menggunakan kaedah analisis kandungan (content analysis). Responden bagi kajian ini adalah wakil pihak pengurusan Majlis Daerah, Pentadbir Tanah, Jabatan Pelancongan Negeri dan Pihak Swasta. Kajian ini penting dalam membantu untuk dijadikan sebagai garis panduan asas dalam usaha untuk meningkatkan dan memperkasakan pembangunan harta tanah dalam industri perhotelan di negeri Terengganu amnya dan Daerah Besut amnya. Kajian ini dijangkakan mampu membantu pihak yang berkaitan dalam menarik minat pelabur dalam mewujudkan industri perhotelan yang bertaraf bintang bagi memangkin dan menjana ekonomi penduduk di daerah ini seiring dengan sektor ekonomi utama yang sedia ada iaitu pertanian, perikanan, perdagangan dan perkhidmatan
GIS based suitability analysis for siting petrol filling stations in Zaria Local Government, Kaduna State Nigeria
No full textThis study analyzed and assessed the Suitable site and distribution of petrol filling stations in Zaria Local Government based on the development standards set by Department of Petroleum Resource (DPR). The research used field surveys, GPS, remote sensing, and geographic information system (GIS) tools to locate and map the existing petrol filling station stations. The study located and mapped 56 petrol stations in the area. All analyses and mapping were carried out using ArcGIS 10.7 after the field data were processed in an Excel spreadsheet. A Multi Criteria Decision Analysis was performed in the research using weighted overlay tools. The distribution of the stations was calculated using the nearest neighbor method. The analysis clearly showed that the distribution of the petrol filling stations in the study area are clustered. The distances between petrol filling stations, the location of filling stations on the highway and the distances between filling stations to the nearest features were determined using the same technique. According to the survey, the listed petrol stations were all spread out along the highway on both sides. Additionally, it showed that only 3 of 56 gas stations met all of the development guidelines. The results of this study have also demonstrated the value of geospatial tools for managing and monitoring development in the built environment. Building ability to use the technology should be prioritized by relevant governmental agencies example Department of Petroleum Resource (DPR). In order to prevent haphazardly siting of petrol filling stations in the area, the study recommended regular monitoring by the Department of Petroleum Resource (DPR) to assure complete compliance with the rules. Lastly, there should be proper planning in order to handle future road expansions
Understanding wearable device adoption: Review on adoption factors and directions for further research in smart healthcare
No full textThis paper analyses prior literature that identify adoption model for smart wearable healthcare devices. This assessment aims to contribute and identify factors that enable users to adopt wearable devices in the Internet of Things (IoT) based healthcare to monitor blood glucose measuring. This study has set off in quest of research in IoT smart healthcare focusing on blood glucose monitoring based on previous studies on wearable devices for smart healthcare. The key aim of this paper is to provide a summary of published articles and to find the current factors leading to the adoption of wearable devices for smart healthcare. The authors guided a systematic review of wearable devices in smart healthcare to explore the factors of adopting smart healthcare devices. 55 studies were analyzed where 21 studies directly address wearable devices, adoption models, and also IoT systems. Most of the studies covered a few factors, namely Interpersonal Influence, Self-efficiency, Individual Innovativeness, Attitude toward wearable devices, Self-interest, Perceived Expensiveness, and Perceived Usefulness in a wearable fitness tracker or monitoring. Findings show that the effect of trustworthiness has a very extensive potential to be explored to improve the model prediction to measure the adoption of IoT wearable devices in smart healthcare as well as blood glucose monitoring
Relevance judgment of argument quality and online review adoption during information search in e-commerce review platform
No full textThe landscape of e-Commerce review platforms can be assumed to be in a state of constant growth due to the viral nature of web content. Furthermore, the leading features of these platform has been acclaimed to be among the influential factors in shaping the behavior of online consumer. Even so, in this regard, if the platform presents too many reviews in non-relevant manner, this may be time-consuming and cumbersome to be understand. Hence, awareness on identifying valuable content of online reviews during information searching process has become important part for online businesses. This study purposely aims to develop a model to understand consumer adoption of online reviews based on dynamics relevance judgment of argument quality in e-Commerce review platform. Elaboration Likelihood Model (ELM) is used in developing the research model to find the potential effects of consumer relevance judgment from information retrieval perspective, which include perceived informative and affective relevance. A quantitative research method has been applied to test and validate the proposed research model. Total of 238 valid respondents has been analyzed using the Partial Least Square Structural Modelling (PLS-SEM) technique. From the research findings, the study found that, content novelty, content topicality, content similarity, content tangibility and content sentimentality could positively influence perception of argument quality which led to information adoption behavior. To be concluded, 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 online review platforms
Relevance judgment of argument quality and online review adoption during information search in e-commerce review platform
No full textThe landscape of e-Commerce review platforms can be assumed to be in a state of constant growth due to the viral nature of web content. Furthermore, the leading features of these platform has been acclaimed to be among the influential factors in shaping the behavior of online consumer. Even so, in this regard, if the platform presents too many reviews in non-relevant manner, this may be time-consuming and cumbersome to be understand. Hence, awareness on identifying valuable content of online reviews during information searching process has become important part for online businesses. This study purposely aims to develop a model to understand consumer adoption of online reviews based on dynamics relevance judgment of argument quality in e-Commerce review platform. Elaboration Likelihood Model (ELM) is used in developing the research model to find the potential effects of consumer relevance judgment from information retrieval perspective, which include perceived informative and affective relevance. A quantitative research method has been applied to test and validate the proposed research model. Total of 238 valid respondents has been analyzed using the Partial Least Square Structural Modelling (PLS-SEM) technique. From the research findings, the study found that, content novelty, content topicality, content similarity, content tangibility and content sentimentality could positively influence perception of argument quality which led to information adoption behavior. To be concluded, 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 online review platforms