256 research outputs found
Lane Line Detection and Object Scene Segmentation Using Otsu Thresholding and the Fast Hough Transform for Intelligent Vehicles in Complex Road Conditions
No full textAn Otsu-threshold- and Canny-edge-detection-based fast Hough transform (FHT) approach to lane detection was proposed to improve the accuracy of lane detection for autonomous vehicle driving. During the last two decades, autonomous vehicles have become very popular, and it is constructive to avoid traffic accidents due to human mistakes. The new generation needs automatic vehicle intelligence. One of the essential functions of a cutting-edge automobile system is lane detection. This study recommended the idea of lane detection through improved (extended) Canny edge detection using a fast Hough transform. The Gaussian blur filter was used to smooth out the image and reduce noise, which could help to improve the edge detection accuracy. An edge detection operator known as the Sobel operator calculated the gradient of the image intensity to identify edges in an image using a convolutional kernel. These techniques were applied in the initial lane detection module to enhance the characteristics of the road lanes, making it easier to detect them in the image. The Hough transform was then used to identify the routes based on the mathematical relationship between the lanes and the vehicle. It did this by converting the image into a polar coordinate system and looking for lines within a specific range of contrasting points. This allowed the algorithm to distinguish between the lanes and other features in the image. After this, the Hough transform was used for lane detection, making it possible to distinguish between left and right lane marking detection extraction; the region of interest (ROI) must be extracted for traditional approaches to work effectively and easily. The proposed methodology was tested on several image sequences. The least-squares fitting in this region was then used to track the lane. The proposed system demonstrated high lane detection in experiments, demonstrating that the identification method performed well regarding reasoning speed and identification accuracy, which considered both accuracy and real-time processing and could satisfy the requirements of lane recognition for lightweight automatic driving systems
A global meta-analysis of greenhouse gases emission and crop yield under no-tillage as compared to conventional tillage
No full textNo-tillage (NT) practice is extensively adopted with aims to improve soil physical conditions, carbon (C) sequestration and to alleviate greenhouse gases (GHGs) emissions without compromising crop yield. However, the influences of NT on GHGs emissions and crop yields remains inconsistent. A global meta-analysis was performed by using fifty peer-reviewed publications to assess the effectiveness of soil physicochemical properties, nitrogen (N) fertilization, type and duration of crop, water management and climatic zones on GHGs emissions and crop yields under NT compared to conventional tillage (CT) practices. The outcome reveals that compared to CT, NT increased CO2, N2O, and CH4 emissions by 7.1, 12.0, and 20.8%, respectively. In contrast, NT caused up to 7.6% decline in global warming potential as compared to CT. However, absence of difference in crop yield was observed both under NT and CT practices. Increasing N fertilization rates under NT improved crop yield and GHGs emission up to 23 and 58%, respectively, compared to CT. Further, NT practices caused an increase of 16.1% CO2 and 14.7% N2O emission in the rainfed areas and up to 54.0% CH4 emission under irrigated areas as compared to CT practices. This meta-analysis study provides a scientific basis for evaluating the effects of NT on GHGs emissions and crop yields, and also provides basic information to mitigate the GHGs emissions that are associated with NT practice
Quantum Dot Cellular Automata Check Node Implementation for LDPC Decoders
No full textThe quantum dot Cellular Automata (QCA) is an emerging nanotechnology that has gained significant research interest in recent years. Extremely small feature sizes, ultralow power consumption, and high clock frequency make QCA a potentially attractive solution for implementing computing architectures at the nanoscale. To be considered as a suitable CMOS substitute, the QCA technology must be able to implement complex real-time applications with affordable complexity. Low density parity check (LDPC) decoding is one of such applications. The core of LDPC decoding lies in the check node (CN) processing element which executes actual decoding algorithm and contributes toward overall performance and complexity of the LDPC decoder. This study presents a novel QCA architecture for partial parallel, layered LDPC check node. The CN executes Normalized Min Sum decoding algorithm and is flexible to support CN degree dc up to 20. The CN is constructed using a VHDL behavioral model of QCA elementary circuits which provides a hierarchical bottom up approach to evaluate the logical behavior, area, and power dissipation of the whole design. Performance evaluations are reported for the two main implementations of QCA i.e. molecular and magneti
Memory Study in The Danish Girl (2000) by David Ebershoff Through Voyant Text Mining Tools: A Digital Humanities (DH) Study: 1. Muhammad Awais 2. Adeel Khalid
No full textIn this digital era, the world has revolutionised its ways of extracting knowledge patterns based on diverse and large texts using a digital humanities (DH) approach and a range of digital text mining tools available to deconstruct and visualise literary texts. This paper attempts to explore the characters of the novel, ‘The Danish Girl’ by David Ebershoff, through the study of their individual or collective memories through Voyant, a text-mining digital tool for textual analysis. Analysis revealed knowledge patterns on memory in the text through the Voyant text mining tool, which recognizes repeating words and phrases and provides insights into the author\u27s language choices and how they relate to memory studies. It provided textual analysis and allowed data visualisation, collocations, and quantitative and qualitative analysis of the text. The study unveils the summary tool features of the overall corpus, cirrus, unique words, dense words, themes, and phrase tools using a digital humanities approach to text mining, underscoring the significance of digital tools in advancing our understanding of literature and memory
Investigation of Precursor Nanoparticles and Soot using Point-wise Time-resolved Laser-Induced Emission
No full textThis thesis provides improved insight into the formation and growth of combustion formed nanoparticles. The effects of two pollutant control methods (oxygen-enhancement and carbon dioxide dilution) on the formation and destruction of carbonaceous nanoparticles are studied. This thesis focuses on two classes of the carbonaceous nanoparticles: precursor nanoparticles and soot particles. Precursor nanoparticles have size range of 1-10 nm, ability to absorb in the ultraviolet, and fluoresce. Soot particles have size range of 10-100 nm, ability to absorb in broadband, and incandesce.
A laser in the ultraviolet range (266 nm) was used for laser-induced fluorescence (LIF) measurements to detect and characterize incipient soot. In general, 266 nm laser pulse can excite gas-phase polyaromatic hydrocarbons (PAHs) as well. However, the diagnostics setup was tuned to reduce the contributions from gas-phase species. This arrangement was confirmed by analyzing the fluorescence decays. An infrared range (1064 nm) laser was used to probe soot. Scattering was also used to characterize aromatization, which involves the transformation of aliphatic to the aromatic structure.
The sequence and timing of the lasers were adjusted to avoid interference between the lasers. First, 266 nm laser was fired to excite precursor nanoparticles. Then there was a delay of 900 ns, after which 1064 nm laser was fired to excite soot particle. As the lifetime of LIF signals is very short, 900 ns delay was enough to avoid any interference from 266 nm laser on the signal generated by 1064 nm laser. These measurements tracked the temporal decays of the signals, which were captured on four photomultiplier tubes (PMTs) and stored in an oscilloscope. The spectral positions of the PMTs were carefully chosen to characterize the critical behaviours of the excited particles.
The transformation from smaller aromatic to larger aromatic species was inferred from red-shifting in the fluorescence spectrum, scattering, and increasing decay times while moving downstream the burner. Temperature is essential in the characterization of precursor nanoparticles, and the estimation of soot primary size. A pneumatic-powered rapid insertion mechanism was designed and installed, which drove a thermocouple in and out of the flames quickly, enabling the thermocouple bead to read temperature before significant soot built upon the bead.
This thesis characterized precursor nanoparticles in terms of concentration, structural growth, and aromatization. Moreover, the volume fraction and primary particle diameter of soot were also quantified.
Oxygen enhancement not only increased the concentration of precursors, but also streamlined the transformation of precursors to soot. Growth of precursors is found to be a function of temperature rather than oxygen. A common intermediate stage during the transformation from precursors to soot is observed. Carbon dioxide enhancement did not affect the concentration of precursors, however, the transformation of precursors to soot was greatly reduced. Soot suppressing effects of carbon dioxide were observed in oxygen-depleted, atmospheric, and oxygen-enriched environments. Regardless of flame composition, a set of matching characteristics was achieved by precursors just before they converted into soot
Indirect determination of partial depolymerization reactions in dialdehyde celluloses (DAC) by gel permeation chromatography of their oxime derivatives
No full textFunding Information: This work was a part of the Academy of Finland's Flagship Programme under Projects No. 318890 and 318891 (Competence Center for Materials Bioeconomy, FinnCERES). The support by the Austrian Biorefinery Center Tulln (ABCT-II) is gratefully acknowledged. The authors thank Muhammad Awais for help in the visualization of the results. Publisher Copyright: © 2023, The Author(s).Owing to a supposed quantitative transformation, oximation of dialdehyde cellulose (DAC) with hydroxylamine hydrochloride is commonly employed in chemical DAC analysis, e.g., for the determination of the degree of oxidation (DO) by titration or elemental analysis. In this study, this modification was utilized for the indirect determination of molecular weight distributions (MWD) by gel permeation chromatography (GPC). The presumably quantitative conversion of aldehyde groups in DAC to the corresponding oxime also breaks up the intermolecular and intramolecular hemiacetal crosslinks, which were associated with solubility issues in the DMAc/LiCl solvent system in previous studies. The limits of the procedure and the material's stability during oximation were investigated. For samples with a DO up to approximately 9% a good applicability was observed, before at higher DO values residual crosslinks led to solubility problems. The oximation/GPC protocol was used to examine the development of the MWD in the early stages of DAC formation under different reaction conditions. The time-dependent partial depolymerization of the polymer backbone was observed. Furthermore, the stability of DAC towards different pH conditions ranging from strongly acidic to strongly alkaline was tested. The depolymerization of DAC in alkaline media occurred with concomitant degradation of aldehyde moieties. In turn, DAC proved to be remarkably stable in acidic and neutral solutions up to a pH of 7.Peer reviewe
Symmetry-Enhanced Fuzzy Logic Analysis in Parallel and Cross-Road Scenarios: Optimizing Direction and Distance Weights for Map Matching
No full textThis study addresses the challenges of setting segmentation points in the membership function and determining appropriate weights for different types of information within a fuzzy logic algorithm for map matching. We use linear fitting to derive an empirical formula for setting segmentation points for the information membership function. Furthermore, we evaluate the effects of various weights for direction and distance information in parallel and cross-road scenarios. The research identified the optimal distance that achieves the highest matching accuracy and provided insights into how the weights of connection, direction, and distance information affect this accuracy. The simulations confirmed the critical importance of precise segmentation point settings and weight determinations in enhancing the accuracy of fuzzy logic algorithms for map matching. The results underscore the potency of our tailored parameter-setting strategy and contribute to knowledge of symmetry, offering practical insights for implementing fuzzy logic in map matching with a particular emphasis on the principle of symmetry in algorithm design and information processing
An Entrapped woman of Poscoloniality: Journeying through Displacement to individuality in Shamsi’s Burnt Shadows
No full textThe present study is aimed to trace out the diasporic representation in Shamsie’s Burnt Shadows with reference to postcolonial displacement. For thematic analysis of the novel the model of acculturation proposed by J.W Berry (2005) has been adopted. The findings of the study reveal that all the characters of the novel are the victim of failure of acculturation. Hiroko, Raza and Sajjad Ashraf are the worst victims of psychological distress, cultural shocks and social marginalization due to their consistent displacement. Diaspora which is considered as a source of potential experiences and adjustment has failed in this novel to cater any such potential and benefits to the characters of the novel. Shamsie demands the development of a Pakistani society with unified national ideology
Response of foliar-applied nutrient solution with and without soil-applied fertilizers on growth and yield of mung bean
No full textThe Role of Leadership Styles in Enhancing Sports Performance Among Male High School Athletes
No full textThis study aimed to investigate the impact of various leadership styles on the school-level sports performance of male students. Understanding how leadership affects student-athletes is crucial, as it can significantly influence their motivation, personal growth, and overall performance in sports. To conduct this research, a survey questionnaire adapted from the Leadership Sports Scale (LSS) was employed within a descriptive correlational design. The sample consisted of 150 male students actively participating in school sports, allowing for a robust analysis of their experiences. Statistical methods, including Pearson\u27s correlation coefficient, descriptive statistics, and multiple regression analysis, were utilized to assess the relationship between different leadership styles specifically autocratic, democratic, and laissez-faire and sports performance, which served as the dependent variable. The results revealed that each leadership style exhibited a significant positive correlation with the performance of male student-athletes, highlighting the importance of effective leadership in sports. These findings suggest that the leadership style adopted by coaches at the school level plays a crucial role in determining their teams\u27 overall effectiveness and success in competitions
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