Developing a Mobile Application via Bluetooth Wireless Technology for Enhancing Communication

This paper presents Mobile application via Bluetooth wireless technology (MAvBT) that enhance the student portal in universities by connecting students' mobile phone devices to a server application that benefit from the devices Bluetooth technology and the storage abilities. MAvBT enables students to retrieve their information with minimum time and anywhere ranging from 100m up to 1Km and it facilitate the communication with instructors outside the office hours. This system consists of computer application (Server Application) installed on a Bluetooth enabled computer, Mobile application (client application) installed on studentsâ?? mobile phone devices, and a website that enable the instructors to edit their materials or enable the demonstrator to get some important reports. Experimental results show that the proposed system is faster, effortless, and cheaper

Semantic Partitioning and Machine Learning in Sentiment Analysis

This paper investigates sentiment analysis in Arabic tweets that have the presence of Jordanian dialect. A new dataset was collected during the coronavirus disease (COVID-19) pandemic. We demonstrate two models: the Traditional Arabic Language (TAL) model and the Semantic Partitioning Arabic Language (SPAL) model to envisage the polarity of the collected tweets by invoking several, well-known classifiers. The extraction and allocation of numerous Arabic features, such as lexical features, writing style features, grammatical features, and emotional features, have been used to analyze and classify the collected tweets semantically. The partitioning concept was performed on the original dataset by utilizing the hidden semantic meaning between tweets in the SPAL model before invoking various classifiers. The experimentation reveals that the overall performance of the SPAL model competes over and better than the performance of the TAL model due to imposing the genuine idea of semantic partitioning on the collected dataset

Reactive Traffic Congestion Control by Using a Hierarchical Graph

Traffic management is one of the major factors in growth strategy formulation in urban centers across the globe. The increasing population and, therefore, the increase in the number of vehicles on roads in urban centers cause congested traffic patterns. These patterns typically emerge on intersections in busy city roads at various times during the day, especially during peak hours. A direct consequence of congestion is the increase in commute time and pollution. This paper presents a hierarchical graph-based congestion control (HGCC) method. Congestion values are set and evaluated as a two-level hierarchical graph. The least congestion path algorithm (LCP)is integrated with the HGCC to compute the optimal route between source and destination. The experimental results for a Manhattan-like grid network, together with the paired-sample t-test, show that the proposed method is efficient in achieving good congestion-avoiding routes

Reactive Traffic Congestion Control by Using a Hierarchical Graph

Traffic management is one of the major factors in growth strategy formulation in urban centers across the globe. The increasing population and, therefore, the increase in the number of vehicles on roads in urban centers cause congested traffic patterns. These patterns typically emerge on intersections in busy city roads at various times during the day, especially during peak hours. A direct consequence of congestion is the increase in commute time and pollution. This paper presents a hierarchical graph-based congestion control (HGCC) method. Congestion values are set and evaluated as a two-level hierarchical graph. The least congestion path algorithm (LCP)is integrated with the HGCC to compute the optimal route between source and destination. The experimental results for a Manhattan-like grid network, together with the paired-sample t-test, show that the proposed method is efficient in achieving good congestion-avoiding routes

Public values regarding an urban mangrove wetland in the United Arab Emirates

Mangrove wetlands are facing an existential threat from rapid socio-economic development. In this study, public environmental values regarding mangrove wetlands in the Ras Al Khaimah (RAK) city in the United Arab Emirates were assessed, considering gender, age, education, income, length of residency in RAK, knowledge of RAK mangrove and awareness of sustainability. A population sample of 427 respondents were face-to-face interviewed. Results suggest that mangrove value orientations are highly associated with length of residency in RAK and awareness of sustainability at significance levels of 0.003 and 0.005, respectively. Value orientations are less associated with age, knowledge of RAK mangrove and education at significance levels of 0.023, 0.039 and 0.095, respectively, being largely independent of gender and income. The majority of the respondents support the preservation of the mangroves even at the expense of economic development. This indicates the need to draft policies and regulations to safeguard the mangroves

MaDiH (مديح): Mapping Digital Cultural Heritage in Jordan

MaDiH (مديح): Mapping Digital Cultural Heritage in Jordan, is a collaborative project between King’s Digital Lab (KDL), the Hashemite University, the Council for British Research in the Levant (CBRL), the Department of Antiquities of Jordan, the Jordanian Open Source Association, and the Endangered Archaeology in the Middle East and North Africa (EAMENA) project. It is scheduled to run for two years, from February 2019 to February 2021. The project will contribute to the long-term sustainable development of Jordan’s digital cultural heritage, identifying key systems, datasets, standards, and policies, and aligning them to government digital infrastructure capabilities and strategies. Defining a robust technical and operational architecture for digital cultural heritage will assist the Department of Antiquities in their planning processes, help product development teams develop their systems, facilitate the aggregation of valuable datasets held in disparate repositories, and ensure data generated from research activity is properly stored and widely accessible