7264 research outputs found
Sort by
HYDROTHERMAL SYNTHESIS OF TITANIA NANORODS FOR EFFICIENT PHOTOELECTROCHEMICAL WATER SPLITTING
No full textPhotoelectrochemical water splitting using semiconductors such as titanium dioxide has been a highly investigated topic for several decades. Many factors can affect the photoelectrochemical activity of these materials including their phase, combination with other materials, and surface area. In this work, we optimize the synthesis procedure of titanium dioxide nanorods thin films. The morphology of these materials was investigated using SEM, and based on XRD patterns it was concluded that samples contain mixed phase rutile and anatase titania. Photoelectrochemical measurements showed that hydrothermally synthesized pristine titanium dioxide thin films can show very high and stable photocurrent densities of up to 300 μA/cm2 under AM1.5 simulated solar light. This observation opens new possibilities for designing highly efficient photoelectrochemical devices by combining TiO2 in these thin films with other semiconductors and metal nanoparticles to further enhance the activity
OPTIMIZATION OF RF AND MICROWAVE FILTERS USING ML TECHNIQUES
No full textDesigning high-performance microwave and millimeter-wave filters presents a significant challenge due to the sensitivity of filter characteristics to variations in geometric dimensions and electrical sizes. Typically, filter design involves optimizing design variables, starting from initial values. However, if these initial values are too far from the optimal solution, optimization often fails to yield satisfactory results. To address this issue, this project analyzes current methods used in the optimization of microwave and millimeter-wave filters
APPLICATION OF MACHINE LEARNING TO THE PREDICTION OF WAVE VELOCITY IN A GIVEN MINE GROUND CONDITION
No full textThis thesis explores the use of machine learning (ML) to predict wave velocities in mining environments, aiming to improve mining safety by reducing seismic risks like rockbursts. It challenges traditional, less accurate methods with an innovative approach that combines laboratory models and ML algorithms for more precise predictions. The study constructs physical models to replicate mine conditions and generate data for training ML models, from simple linear regression to complex deep neural networks. In a comprehensive analysis of predictive modeling techniques for seismic wave velocities, it was discovered that Linear Regression and Gradient Boosting outperformed, with an R-square value of 0.83, showcasing a balanced reduction in bias and variance. In contrast, the K-Nearest Neighbors (KNN) method's lower effectiveness implied that its proximity-based assumptions might be less relevant in seismic contexts, while the Deep Neural Network (DNN) model notably struggled, evidenced by a negative R-squared value of -0.81, wich is not possibble because Rsquare ranges between 0 and 1. It indicates substantial overfitting likely due to the complexity of the model and limited data. Among the models evaluated, Linear Regression emerged as the most fitting, owing to its simplicity, interpretability, and high accuracy, effectively avoiding overfitting and proving reliable for predicting seismic wave velocities. The findings advocate for future acquisition of more extensive datasets to potentially enhance the performance of complex models like the DNN, but within the current dataset's constraints, Linear Regression is identified as the superior predictive model for this purpose. Study firmly establishes ML's role in advancing seismic risk assessment in mining, opening avenues for future research in integrating ML with seismic data analysis
ANALYSIS OF FLOW AND MIXING CHARACTERISTICS OF NON-SPHERICAL PARTICLE MIXTURES IN A ROTATING DRUM
No full textThis study investigates the flow and mixing characteristics of powder mixtures that incorporate non-spherical particles using both experimental and DEM simulation methods. Investigated particulate materials include Aluminum Oxide (Al2O3), Aluminum-Alloy (AlSi10Mg), and two composite materials: one composed of 90% AlSi10Mg and 10% Al2O3, and the other composed of 95% AlSi10Mg and 5% Al2O3. A rotary drum apparatus is used experimentally with different rotational speeds (5, 10, 15, 20, and 30 rpm) to study powder behavior. High-speed videography records the dynamic angle of repose and flow patterns. The results demonstrate a clear correlation between rotation speed and dynamic angle of repose, suggesting that disturbance of the particles increases with higher speeds. Our findings reveal that optimal rotation speeds significantly enhance mixing performance along with best optimized values for achieving a DAOR and promoting mixing efficiency. Three flow regimes, rolling, cascading, and cataracting, are distinguished in the drum due to the effects of rotation speed and particle interactions. Analysis of the segregation index suggests increased rotation speeds enhance mixing efficiency, leading to less particle segregation in composite mixtures. The mixture's composition significantly impacts mixing behavior, as a higher ceramic concentration enhances mixing efficiency. It is critical to regulate rotation speed and particle composition in mixing processes to ensure uniform mixes. This study provides valuable insights into the behavior of powder and the effectiveness of mixing in rotary drums. The work improves comprehension of the parameters affecting powder flow by combining experimental data with DEM models
PROCESS TRACING THE IMPLEMENTATION GAP OF ENVIRONMENTAL INFORMATION DISCLOSURE, CASE OF TANZANIA
No full textThis study examines in detail the causes of the implementation gap of Environmental Information Disclosure (EID) strategies as a means of implementing environmental policies, tracing back to the country's adoption and implementation of these strategies. The research seeks to answer two questions RQ1. How does the environmental information disclosure policy’s content impact its implementation? And RQ2. How does the context of the environmental information disclosure policy Impact its implementation? The policy system's content and context shed light on the causes of the gap in implementing these strategies in environmental governance.
The principal objective is to test causal mechanisms behind the low reporting of environmental information, creating a policy implementation gap. Using explicit Bayesian process tracing, I tested three mutually exclusive hypotheses: (1) hierarchical governance, HHG, (2) closed political systems, HPS and (3) limited civil engagement, HCE. The analysis drew inferences on the key contextual factors that facilitate implementing EID as a tool for environmental governance within the mining industry.
The study's findings, which traced the implementation gap of EID in Tanzania, support the HHG hypothesis. The study revealed that not all stakeholders (government, firms and community) were aware of the adoption of EID, and even now, it is not well recognised. The interviewees acknowledged that the implementation of EID is still poorly understood and practised in the community. Additionally, initiatives such as TEITI have yet to incorporate the consolidation of environmental data in their reports.
The study's theoretical insight lies in updating the understanding of the political context of EID implementation. A collaborative environment fosters EID's outcome considering that voluntary disclosure was found to have an interacting role in the implementation of legislation, serving as a mechanism for ensuring compliance in business practices which has a higher impact on EID outcome. By examining reporting mechanisms, this study contributes to the ongoing policy dialogues on promoting transparency and inspires further research and policy development in resource governance. The study offers practical implications for improved EID, at its current state there are well-established methods of identifying environmental risks. However, the research recommends to improve information reliability and information dissemination to communities. Similarly, communities are encouraged to act upon information
ANALYSIS AND COMPARISON OF APPROXIMATE K-NEAREST NEIGHBOR ALGORITHMS
No full textThis study presents a comprehensive comparison of Approximate k-Nearest Neighbor
(AKNN) methods across multiple datasets, including image, text, and behavioral
datasets. The performance of various AKNN algorithms is evaluated in terms of build
time, search time, total time, and recall metrics for different datasets. Key findings
reveal that tree-based AKNN methods exhibit vulnerability to changes in dataset
contents, while graph-based algorithms demonstrate superior performance in certain
scenarios. Furthermore, algorithm-specific nuances, such as computational efficiency
and recall rates, are discussed across diverse datasets. Insights from this study provide
valuable guidance for selecting suitable AKNN methods based on specific application
requirements and dataset characteristics. Furthermore, potential directions for future
research, including scalability improvements, algorithmic enhancements, and domain-
specific applications are identified to further advance the field of AKNN algorithms
MULTI-LEO SATELLITE NETWORKS FOR INTEGRATED ACCESS AND BACKHAUL
No full textLow Earth Orbit (LEO) Satellites have emerged as a promising solution to extend the coverage area of terrestrial networks, particularly in scenarios where ground users are located in remote or inaccessible areas. As such, forming a network over ground users with LEO satellites becomes essential to ensure reliable connectivity at desired data rates. This thesis focuses on investigating a LEO network for integrated access and backhaul (IAB) within fifth-generation (5G) systems, where LEO satellites serve as IAB nodes connecting to other IAB nodes for backhaul transmissions while acting as base stations (BSs) for ground users. LEO satellites offer rapid, low-latency connectivity, which is crucial for time-sensitive applications like remote surgery or autonomous vehicles where even slight delays could have significant repercussions. Positioned in a high altitude from the Earth’s surface, LEO satellites can achieve remarkably low latency levels, making them comparable to terrestrial networks in terms of responsiveness. Furthermore, the enhanced bandwidth capabilities afforded by LEO satellites position 5G networks optimally to handle the escalating data traffic and increasing number of connected devices effectively. In this work, A model is proposed for wireless multi-hop transmission in LEO satellite networks with integrated access and backhaul (IAB). This model supports ground users that can’t communicate directly with ground base stations (gNBs). The traffic
flows for uplink and downlink transmissions are characterized using the channel capacity of both local access and backhaul links. LEO-Satellites serve as relay nodes facilitating the link between ground users and gNBs. Additionally, as LEO-Satellites form an interconnected network, they not only communicate with ground users but also engage in data exchange with neighboring LEO-Satellites. Consequently, in the IAB framework, LEO-Satellites transform into IAB nodes, while gNBs act as IAB donors. Within this model, a path is defined by a series of connected LEO-Satellites, and each LEO-Satellite is tasked to deliver data between users and gNBs for uplink and downlink transmissions along the designated path. The proposed model is evaluated by analyzing end-to-end packet transmission delay and propagation delay. Analytical formulas for transmission delay in both the access and backhaul networks are derived, and extensive simulations are conducted to examine the system’s sensitivity to vari-
ous parameters, providing insights into its performance under different scenarios. Furthermore, analytical expressions for outage probabilities are derived for both the backhaul link, consisting of inter-LEO satellite communication, and access networks connecting LEO satellites with ground users. The channel link in the access network is assumed to follow a Nakagami fading channel, while the backhaul network is primarily influenced by large-scale fading. Through
numerical simulations, the impact of transmission rate and LEO-Sat transmit power on the system’s outage probability is analyzed, revealing trade-offs between data rate and reliability. To efficiently allocate transmit power to LEOs and support the specified data rates of ground users, an optimization problem is formulated and solved to minimize the total transmit power of LEO
IMPROVING CONTROL SYSTEMS OF THE MAN- UFACTURING MACHINERY IN THE GRANITE MINES OF KAZAKHSTAN
No full textThis study investigates modernizing control
systems in Kazakhstan’s granite mining indus-
try, addressing outdated technology from the
Soviet era. It focuses on three core aspects:
modern electrical components, PLC and HMI
integration, and the role of VFDs. Through
analysis and implementation, the research aims
to automate processes, enhance safety, and
boost operational efficiency. Benefiting the
mining industry, economy, and academia, the
project employs a comprehensive methodology
involving data collection and phased imple-
mentation. Anticipated outcomes include im-
proved safety standards, operational efficiency,
and economic impact via the application of
contemporary automation technology
DESIGN OF A 20-STORY "PACIFIC TOWER" HIGH-RISE RESIDENTIAL BUILDING IN LOS ANGELES, CALIFORNIA, USA
No full textThis paper proposes designing and constructing a 20-story residential building at 1201
South Grand Avenue in Los Angeles, California, in a densely populated commercial district. The growing population in Los Angeles has spurred a demand for innovative residential construction solutions, prompting a comprehensive approach that considers architectural, structural, material, and geotechnical factors.
The proposed building has 19 residential floors and 1 commercial floor with a gross area
of 1138. 3 . All of the architectural, structural, and geotechnical design procedures were done in accordance with IBC, ASCE, LA Building Code guidelines. The site is located in a
seismically active region, which was taken into consideration during the design of foundation and structural members. The geotechnical design included site response analysis to investigate soil behavior under strong earthquake ground motions. Additionally, detailed foundation design and retaining wall design was provided. Lastly, project costs, risks, and schedules were estimated and the project deadline to put into operation is set to 2026
MODIFICATION OF NANOMATERIALS WITH INTENSE PULSED ION BEAMS FOR PHOTOCATALYTIC APPLICATIONS
No full textThe world energy problem has been facing harsh challenges in the last few decades due to the increase in energy consumption of the growing world population and decreasing reserves of traditional carbon-based energy resources. Photoelectrochemistry (PEC) based solar water splitting is one of the potential paths for transforming renewable solar energy into green hydrogen fuel to meet energy expectations. In PEC water splitting, hydrogen is generated using semiconductor materials that can absorb sunlight and decompose water molecules into hydrogen and oxygen gases. Fabrication of highly effective, stable, and economically viable semiconductor photoelectrode materials, to increase their performance, and enhancing their photocatalytic activity has been proved to be a vital task for PEC solar water decomposition.
Among all the suitable materials, WO3 has been reputed as a promising photoelectrode in the last decade due to the many criteria that it fits. The main current problems in WO3, based PEC water splitting systems are their low solar to hydrogen efficiencies and poor photocatalytic properties. Developing and applying new methods of surface modifications and engineering are favorable strategies to enhance photocatalytic properties of WO3.
This thesis work is devoted to the study of surface modification of WO3 photoelectrodes with intense pulsed ion beam (IPIB) irradiation for photocatalytic properties enhancement and studying the effect of IPIB irradiation on solid state dewetting shape formation of plasmonic Ag nanoparticles (NPs). The thesis also reports strategies of combining plasmonic nanoparticles and downshifting photoluminescent NPs with WO3.
IPIB irradiation is a method for modification of surfaces of materials with few hundreds keV energetic ions that penetrate deep into 1-2 micrometers.
The outcomes of experiments show that surface engineering of WO3 photoelectrode with IPIB can enhance its photocatalytic properties and promote charge-carrier characteristics. The IPIB also gives opportunity to study shape formations of silver NPs and results exhibit huge influence of super-fast annealing on sphericity of the silver NPs. Simultaneous use of plasmonic NPs and fluorescent materials also proven to be effective method of photoactivity enhancement of WO3 thin films