Effect of Vacuum Intrusion Compaction on the Mechanical Properties of Mortar

The Vacuum Intrusion Compaction Method (VICM) can be defined as a mortar or cement based material compaction method which applies the principle of air pressure in extracting air bubbles trapped in mortar in order to achieve the objective of compaction. This alternative compaction method is able to prevent segregation from happening in mortar and other cement based materials. It also provides better control over the orientation of the elements inside the mortar. Laboratory tests on the physical and mechanical properties of mortars were conducted to study bulk density, porosity, compressive strength, and flexural strength in the early stages of strength development of different mortars. Through such testing, the effectiveness of the vacuum intrusion method on the effect of compaction could be observed. The outcome of this research shows that the VICM is capable of compacting mortar and extracting macro pores, thereby providing a relatively similar compressive strength and flexural strength to that of the standard compaction method. However, it is not efficient in extracting micro pores, therefore, leading to high porosity of the mortar specimens. As a conclusion, the vibration compaction method is still considered a good compaction method when compared to VICM

Evaluation of Shugor, Dubasi and Watish subtypes of Sudan Desert sheep at the El-Huda National Sheep Research Station, Gezira Province, Sudan

Presents results obtained from a trial conducted at El-Huda National Sheep Research Station, Sudan, Shugor, Dubasi and Watish subtypes of Sudan Desert sheep to compare productivity, reproductivity and animal performance, with particular reference to lambing, lambing intervals, body weight, growth rates and mortality rates, incl. recommendations for further investigations

Small businesses as vehicles for job creation in North-West Nigeria

Small businesses are considered as engine of economic growth, contributing to employment generation, wealth creation, and poverty alleviation and food security in both developed and developing countries. Nigeria is facing many socio-economic problems and it is believed that by supporting small business development, as propellers of new ideas and more effective users of resources, often driven by individual creativity and innovation, Nigeria would be able to address some of its economic and social challenges, such as unemployment and economic diversification. Using secondary literature, this paper examines the role small businesses can play in the creation of jobs in North-West Nigeria to overcome issues of unemployment, which is the most devastating economic challenge facing the region. Most studies in this area have focused on Nigeria as a whole and only a few studies provide a regional focus, hence, this study will contribute to knowledge by filling this gap by concentrating on North-West Nigeria. It is hoped that with the present administration’s determination to improve the economy, small businesses would be used as vehicles for diversification of the economy away from crude oil to create jobs that would lead to a reduction in the country's high unemployment level

Smart System for Prediction of Accurate Surface Electromyography Signals Using an Artificial Neural Network

Bioelectric signals are used to measure electrical potential, but there are different types of signals. The electromyography (EMG) is a type of bioelectric signal used to monitor and recode the electrical activity of the muscles. The current work aims to model and reproduce surface EMG (SEMG) signals using an artificial neural network. Such research can aid studies into life enhancement for those suffering from damage or disease affecting their nervous system. The SEMG signal is collected from the surface above the bicep muscle through dynamic (concentric and eccentric) contraction with various loads. In this paper, we use time domain features to analyze the relationship between the amplitude of SEMG signals and the load. We extract some features (e.g., mean absolute value, root mean square, variance and standard deviation) from the collected SEMG signals to estimate the bicep’ muscle force for the various loads. Further, we use the R-squared value to depict the correlation between the SEMG amplitude and the muscle loads by linear fitting. The best performance the ANN model with 60 hidden neurons for three loads used (3 kg, 5 kg and 7 kg) has given a mean square error of 1.145, 1.3659 and 1.4238, respectively. The R-squared observed are 0.9993, 0.99999 and 0.99999 for predicting (reproduction step) of smooth SEMG signals

Turning Natural Fiber Reinforced Cement Composite as Innovative Alternative Sustainable Construction Material: A Review Paper

In recent years, a great deal of interest in concrete leads to the most frequently used sustainable construction material. Using of natural fiber as fiber reinforcement effectively improved strength, ductility and durability requirements of high performance cement composites. Regretly, natural fibers are dumped as agricultural waste (e.g. coconut, bamboo, wood or chips, bast fiber, leaf fiber, seed and fruit fibers, etc), so can be easily available low cost. The applications of natural fiber for sustainable construction material design can be done as filler or masonry composites, reinforcement, thermal conductivity, cementations/binder, etc. Previous and current researchers focusing the natural fiber to improve the properties of lightweight composites still required a lot of investigations to make it improved. However, the present work consists of the availability of natural fiber waste substance, sustainable construction materials are evaluated for their physico-mechanical properties of sustainable construction materials, method of production and environmental impact of several materials. No doubt, the application of natural fiber provides a solution to conservation of natural resource and energy

Attitudes Of Jordanian Students Toward Managers' Leadership Styles And Their Relationship To The National Culture

This study explores the attitudes of a group of university students about managers' leadership styles and the cultural characteristics of the Jordanian society. The amount of research on the topic of leadership styles in Jordan is rare, particularly when associated with national culture. The outcomes demonstrated that the surveyed students were more disposed to portray the proposed leadership styles of managers as Team management style followed by Country Club style. On the other hand, when these students were asked to describe their national culture, they described it in a way similar to the Arab Group culture presented by Hofstede. Furthermore, the surveyed students gave power distance then muscularity the first confirmation. No significant relation observed between students' attitudes of leadership styles and characteristics of the Jordanian culture. Reasons for this outcome together with a few recommendations are incorporated into this study.

Stability Analysis and Control of a Microgrid against Circulating Power between Parallel Inverters

In grid-connected mode, the grid normally absorbs all the power generated by each inverter in a microgrid. Droop control-based microgrid power management employs the frequency as a wireless communication to determine the power outage. However, in the cases of grid loss, each inverter should receive, from a supervisory controller, new settings of the output power suitable to the microgrid load. Because of the supervisory controllers are slower than the droop control loops, this might produce unstable dynamics caused by the excess generated power circulating between the inverters if the microgrid load is low. This case degrades the microgrid stability leading the DC link voltage of each inverter to rise to trip point. In this paper, a PD voltage control loop is proposed to stabilize the system and minimize the circulating power so providing more time for the supervisory control to respond without tripping any inverter. A detailed small signal model is developed and stability analysis is performed to tune the controller’s gain. Matlab/Simulink results validate the performance of the proposed controller

Path Planning and Cyber-Physical System Integration in Unmanned Aerial Vehicles for Wireless Communication

Unmanned Aerial Vehicles (UAVs) have become indispensable in a variety of fields, including surveillance, emergency response, packet delivery, and data collection for the Internet of Things (IoT). These systems are also critical in enhancing connectivity within cellular networks. This dissertation focuses on improving UAV operational efficiency and security by advancing trajectory optimization techniques, enhancing trajectory design through antenna radiation patterns, and increasing resilience against cyber-physical attacks, particularly GPS sensor faults. The first part of the study addresses UAV trajectory optimization in wireless communications, highlighting the significance of trajectory planning in improving the efficiency and reliability of UAV operations. Effective trajectory planning ensures optimal energy usage and maximized coverage areas, crucial for maintaining robust communication links with ground base stations (GBS). This optimization is vital for enhancing both the performance and safety of UAV operations in complex environments. Building on trajectory optimization, the second part of the research explores the impact of antenna radiation patterns on UAV trajectory design. The study develops an Enhanced Artificial Potential Field (Enhanced-APF) algorithm that integrates the 3D radiation patterns of antennas equipped on UAVs. This integration is essential for facilitating effective collision avoidance and smoother navigation paths, thereby optimizing UAV performance in scenarios involving multiple UAVs and ensuring safer operations across various applications. The final part of the dissertation introduces a novel algorithm, the Resilient Cyber-Attack Artificial Potential Field (RCA-APF), designed to enhance the resilience of UAV path planning against permanent GPS faults within a cyber-physical system (CPS) framework. This algorithm employs a three-stage process: detecting GPS faults due to the attack, estimating UAV location using Received Signal Strength (RSS) trilateration, and adjusting the UAV\u27s path planning accordingly. The effectiveness of this approach is validated through rigorous experimental and simulation testing, demonstrating its capability to substantially improve the robustness of UAV operations against cyber-physical threats. Overall, this research provides comprehensive strategies for improving UAV trajectory planning and resilience, offering significant advancements in the safe and efficient deployment of UAVs. By integrating advanced cyber-security measures with strategic communications engineering, the dissertation contributes to the development of more reliable and effective UAV systems, paving the way for their expanded use in increasingly complex scenarios