A Comparison Between Inter-Asterisk eXchange Protocol and Jingle Protocol: Session Time

Over the last few years, many multimedia conferencing and Voice over Internet Protocol (VoIP) applications have been developed due to the use of signaling protocols in providing video, audio and text chatting services between at least two participants. This paper compares between two widely common signaling protocols: InterAsterisk eXchange Protocol (IAX) and the extension of the eXtensible Messaging and Presence Protocol (Jingle) in terms of delay time during call setup, call teardown, and media sessions

Kuwait’s readiness for the knowledge-based economy: an exploratory study

The small city-state of Kuwait has undergone marked change over the last century. However, despite the significant transformations within its political economy, Kuwait’s socioeconomic needs require attention. This is essential, considering Kuwait’s current attempt to transform into a knowledge-based economy (KBE), a central component of Kuwait’s Vision 2035 and at the top of the country’s policy agenda. Kuwait’s attempt to diversify its resources requires significant reform in KBE’s four main pillars: effective investment in education, constructing robust and innovative tertiary sector capabilities, modernising the information technology infrastructure, and having an economic environment that is conducive to maximum development. And while Kuwait increasingly invests in ICT infrastructure and a welcoming economic environment, education and innovation seem to lag. This research aims to address the increased demand for academically based explorations of Kuwait’s attempts to transfer to a knowledge-based economy and present a comprehensive analysis of Kuwait’s Vision 2035, with emphasis on how the country aims to develop its education and innovation pillars to aid diversification efforts. By involving the relevant participants (e.g., government ministries and higher education institutions), this research seeks to inform policy debates by proposing actionable policies targeting education and innovation and, thus, defines concrete steps to strengthen the KBE in Kuwait

Feasibility of seismic monitoring methods for Australian CO2 storage projects

I study the detectability of CO2 plumes by seismic methods for three Australian Carbon Capture and Storage projects. I quantify the ability of CO2 plume detection for different acquisition designs applicable to the projects. I evaluate both pre- and post-stack seismic imaging methods. Any detectability study depends on a realistic model of noise. For both of the imaging methods I design a different approach to model the time-lapse noise needed to evaluate the detectability

Effect of Aging Process in Different Solutions on Kenaf Fibre Structure and Its Interfacial Adhesion in Epoxy Composites

Interfacial adhesion of kenaf fibres in epoxy composites was investigated using single fibre pull-out test. Several aged kenaf fibres were tested in this work. Two types of kenaf fibres were used in the work, those treated with 6% NaOH and those untreated kenaf fibres. Kenaf fibres were aged in engine oil, water, salt water, and diesel. The pull-out tests were performed using microtensile tests. The tests were performed at 1 mm/min loading rate. Scanning electron microscopy was used to observe the damage on the fibres and the effect of the treatment. The general results revealed that aging of the fibres reduced their strength and interfacial adhesion. Salt water showed the least effect on the strength of the fibres. At most cases, the breakage in the fibres is the main failure. In other words, there is no remarkable effect of aging on the interfacial adhesion since the most impact was on the structure of the fibres

The Protective Properties of the Strawberry (Fragaria ananassa) against Carbon Tetrachloride-Induced Hepatotoxicity in Rats Mediated by Anti-Apoptotic and Upregulation of Antioxidant Genes Expression Effects

The strawberry (Fragaria ananassa) has been extensively used to treat a wide range of ailments in many cultures. The present study was aimed at evaluating the hepatoprotective effect of strawberry juice on experimentally induced liver injury in rats. To this end, rats were introperitoneally injected with carbon tetrachloride (CCl4) with or without strawberry juice supplementation for 12 weeks and the hepatoprotective effect of strawberry was assessed by measuring serum liver enzyme markers, hepatic tissue redox status and apoptotic markers with various techniques including biochemistry, ELISA, quantitative PCR assays and histochemistry. The hepatoprotective effect of the strawberry was evident by preventing CCl4-induced increase in liver enzymes levels. Determination of oxidative balance showed that strawberry treatment significantly blunted CCl4-induced increase in oxidative stress markers and decrease in enzymatic and non-enzymatic molecules in hepatic tissue. Furthermore, strawberry supplementation enhanced the anti-apoptotic protein, Bcl-2, and restrained the pro-apoptotic proteins Bax and caspase-3 with a marked reduction in collagen areas in hepatic tissue. These findings demonstrated that strawberry (Fragaria ananassa) juice possessed antioxidant, anti-apoptotic and anti-fibrotic properties, probably mediated by the presence of polyphenols and flavonoids compounds

The development of Saudi Arabian Entrepreneurship and Knowledge society

The current knowledge society has become a major factor in the distinction between countries, as many of them have sought to focus on knowledge and information; considering it the main resource. This study aims to identify the subject of the entrepreneurship's development in Saudi Arabia and contributes to the attainment of the knowledge society. We used the analytical descriptive approach and the questionnaire tool. The study population was represented by the Ministry of Economy and Planning officials in Saudi Arabia. Furthermore, the study’s sample consisted of 80 subjects, among which 60 were valid for analysis. We found that the impact on Saudi Arabia entrepreneurship, project participation and execution are reliant on support and encouragement of the concept itself while the level of education significantly influences the likelihood of project success.

Machine Learning Empowered Resource Allocation for NOMA Enabled IoT Networks

The Internet of things (IoT) is one of the main use cases of ultra massive machine type communications (umMTC), which aims to connect large-scale short packet sensors or devices in sixth-generation (6G) systems. This rapid increase in connected devices requires efficient utilization of limited spectrum resources. To this end, non-orthogonal multiple access (NOMA) is considered a promising solution due to its potential for massive connectivity over the same time/frequency resource block (RB). The IoT users’ have the characteristics of different features such as sporadic transmission, high battery life cycle, minimum data rate requirements, and different QoS requirements. Therefore, keeping in view these characteristics, it is necessary for IoT networks with NOMA to allocate resources more appropriately and efficiently. Moreover, due to the absence of 1) learning capabilities, 2) scalability, 3) low complexity, and 4) long-term resource optimization, conventional optimization approaches are not suitable for IoT networks with time-varying communication channels and dynamic network access. This thesis provides machine learning (ML) based resource allocation methods to optimize the long-term resources for IoT users according to their characteristics and dynamic environment. First, we design a tractable framework based on model-free reinforcement learning (RL) for downlink NOMA IoT networks to allocate resources dynamically. More specifically, we use actor critic deep reinforcement learning (ACDRL) to improve the sum rate of IoT users. This model can optimize the resource allocation for different users in a dynamic and multi-cell scenario. The state space in the proposed framework is based on the three-dimensional association among multiple IoT users, multiple base stations (BSs), and multiple sub-channels. In order to find the optimal resources solution for the maximization of sum rate problem in network and explore the dynamic environment better, this work utilizes the instantaneous data rate as a reward. The proposed ACDRL algorithm is scalable and handles different network loads. The proposed ACDRL-D and ACDRL-C algorithms outperform DRL and RL in terms of convergence speed and data rate by 23.5\% and 30.3\%, respectively. Additionally, the proposed scheme provides better sum rate as compare to orthogonal multiple access (OMA). Second, similar to sum rate maximization problem, energy efficiency (EE) is a key problem, especially for applications where battery replacement is costly or difficult to replace. For example, the sensors with different QoS requirements are deployed in radioactive areas, hidden in walls, and in pressurized pipes. Therefore, for such scenarios, energy cooperation schemes are required. To maximize the EE of different IoT users, i.e., grant-free (GF) and grant-based (GB) in the network with uplink NOMA, we propose an RL based semi-centralized optimization framework. In particular, this work applied proximal policy optimization (PPO) algorithm for GB users and to optimize the EE for GF users, a multi-agent deep Q-network where used with the aid of a relay node. Numerical results demonstrate that the suggested algorithm increases the EE of GB users compared to random and fixed power allocations methods. Moreover, results shows superiority in the EE of GF users over the benchmark scheme (convex optimization). Furthermore, we show that the increase in the number of GB users has a strong correlation with the EE of both types of users. Third, we develop an efficient model-free backscatter communication (BAC) approach with simultaneously downlink and uplink NOMA system to jointly optimize the transmit power of downlink IoT users and the reflection coefficient of uplink backscatter devices using a reinforcement learning algorithm, namely, soft actor critic (SAC). With the advantage of entropy regularization, the SAC agent learns to explore and exploit the dynamic BAC-NOMA network efficiently. Numerical results unveil the superiority of the proposed algorithm over the conventional optimization approach in terms of the average sum rate of uplink backscatter devices. We show that the network with multiple downlink users obtained a higher reward for a large number of iterations. Moreover, the proposed algorithm outperforms the benchmark scheme and BAC with OMA in terms of sum rate, self-interference coefficients, noise levels, QoS requirements, and cell radii

Opportunities of Conserving Energy on an Existing Institutional Building: Case Study

The building considered in this case study is a two-story facility with total floor area of 3588 square meter; it is mainly educational facility (classrooms, laboratories, and workshops) as well as staff offices. The building is cooled by an air-cooled reciprocating chillers which is operating round the clock. A preliminary energy audit technique was conducted to evaluate the building energy performance and identify opportunities of saving energy. In addition to the walk-through technique also mini-data loggers were installed in each zone to monitor dry-bulb temperatures, relative humidity, and light intensity over the year 2008. Specific ANSI/ASHRAE/IESNA Standard 100-2006 Energy Conservation in Existing Building measures were implemented in the building. The recorded data showed large deviation of dry-bulb temperatures from comfort range in many zones. The building simulated using DesignBuilder simulation program controlling the indoor temperature and using the set-back temperature schedules. These two parameters showed an opportunity of saving energy of the existing building by 35%, and 15% respectively. Finally, a cost analysis of implementing Building Management System (BMS) was analyzed; the result showed a pay-back period of less than six months was obtained