373 research outputs found
Data for: Size at Sexual Maturity of Waved Whelk (Buccinum undatum) on the Eastern Scotian Shelf
No full textThe files contain the raw data sheets and the figures which have been used in the research. Additional data sheets, including the processed ones can be provided. Only the EXCEL has been used in the production of figures so there are no resource files (e.g. photoshop etc). Please contact Author for more detail, if other data files are required
Seismic Data Analysis and Earthquake Prediction with IoT Sensors and SmartGRU Model
No full textTectonic plate movement causes a slow accumulation of stress in the Earth’s lithosphere, especially around plate borders, leading to earthquakes. An earthquake occurs when this stress overcomes friction along a fault or exceeds the strength of the surrounding rock. Accurate earthquake prediction remains challenging due to the complexity of seismic data and the limitations of traditional methods. This creates a pressing need for models capable of real-time analysis and high prediction accuracy. The Internet of Things (IoT) provides a novel method for detecting earthquakes using a variety of sensors to collect vital seismic data, such as latitude, longitude, depth, magnitude, and time. IoT controllers and centralized systems process and analyze this data to enable efficient monitoring and forecasting. Furthermore, with the help of a machine learning model named Bidirectional Gated Recurrent Unit (Bi-GRU), which integrates sophisticated data fusion and advanced machine learning techniques. Our proposed study model, SmartGRU, demonstrates how to improve earthquake prediction systems by combining IoT sensors with a Bi-GRU machine learning model that incorporates an emerging approach
Seismic Data Analysis and Earthquake Prediction with IoT Sensors and SmartGRU Model
No full textTectonic plate movement causes a slow accumulation of stress in the Earth’s lithosphere, especially around plate borders, leading to earthquakes. An earthquake occurs when this stress overcomes friction along a fault or exceeds the strength of the surrounding rock. Accurate earthquake prediction remains challenging due to the complexity of seismic data and the limitations of traditional methods. This creates a pressing need for models capable of real-time analysis and high prediction accuracy. The Internet of Things (IoT) provides a novel method for detecting earthquakes using a variety of sensors to collect vital seismic data, such as latitude, longitude, depth, magnitude, and time. IoT controllers and centralized systems process and analyze this data to enable efficient monitoring and forecasting. Furthermore, with the help of a machine learning model named Bidirectional Gated Recurrent Unit (Bi-GRU), which integrates sophisticated data fusion and advanced machine learning techniques. Our proposed study model, SmartGRU, demonstrates how to improve earthquake prediction systems by combining IoT sensors with a Bi-GRU machine learning model that incorporates an emerging approach
Facile synthesis, characterization and optical studies on electrically conductive polypyrrole coated titanium dioxide nanocomposite photo-catalyst for water purification
No full textDevelopment of an Audio Assessment Module: For Sound Engineering of Aircraft Designs
No full textA first step in designing aircraft with optimal sound is the development of a module that is able to assess noise in a sophisticated way, which is the exact goal of this research. In this research the Audio Assessment Module (AAM) is completed with the addition of tonality, roughness and fluctuation strength. The AAM is now able to assess sound in terms of five sound quality metrics, specifically loudness, tonality, roughness, sharpness and fluctuation strength, but also in terms of conventional metrics such as EPNL. The five sound quality metrics can be combined to form a psychoacoustic annoyance value PAmod. The AAM is applied to a variety of sound recordings, including 255 measured aircraft flyover measurements of 26 different types of aircraft, in an attempt to find relations between design variables and the five sound quality metrics. The only significant correlations observed are those of the wingspan, wing loading and engine diameter with loudness. High values for roughness are observed for helicopter sounds due to the buzzing sound produced by the helicopter rotor, indicating that roughness is an important metric for propeller aircraft or aircraft with open-rotor engines. Listening tests, with the aim of learning whether the psychoacoustic annoyance value is a better annoyance predictor than EPNL, were conducted in which twenty subjects participated. From the listening tests it was found that the metrics did not outperform each other in terms of annoyance assessment. However, some deficiencies of the PAmod metric came to light during the listening tests. For a valid comparison of two sounds in terms of PAmod the duration of the sounds has to be the same, since the values "exceeded 5% of the time" are used in the calculation of PAmod. It was also found that the loudness contribution to PAmod might be too high. More research into PAmod can potentially improve correlations with subjective evaluations. The ultimate aim of an audio assessment module is to use it for sound engineering of aircraft designs. The sound quality metrics are capable of capturing the different characteristics of sound in a more comprehensive manner than for example EPNL. Differences in sound for current aircraft or future concepts such as aircraft powered with open-rotor engines can be captured by the individual metrics. This can then be used for sound engineering of aircraft designs in which the design is modified in such a way to arrive at a sound which is as close as feasible to the target sound. In this way, it is possible to design aircraft which sound inherently more acceptable and reduce the annoyance caused to residents by aircraft noise.Aerospace Engineerin
Asymmetric Impacts of Environmental Policy, Financial, and Trade Globalization on Ecological Footprints: Insights from G9 Industrial Nations
No full textThis study investigates the effects of financial globalization, trade globalization, and information and communication technology on the ecological footprint in G9 industrial economies (China, the United States, Japan, Germany, India, South Korea, Italy, France, and the United Kingdom) from 2000Q1 to 2018Q4. A distinctive Method of Moments Quantile Regression (MMQR) model was employed to analyze these relationships, and the Bootstrap Quantile Regression (BSQR) model was used to validate the results. The findings reveal that financial globalization (FG), environmental tax (ETAX), and institutional quality (IQ) contribute to environmentally sustainable development by reducing the ecological footprint (ECOFP). In contrast, trade globalization, information and communication technology (ICT), and gross domestic product (GDP) have a significant positive impact on the ecological footprint, leading to increased environmental degradation. The BSQR results corroborate these findings, confirming the roles of financial globalization, institutional quality, environmental tax, trade globalization, information and communication technology, and gross domestic product in shaping the ecological footprint. Based on these results, policymakers in G9 industrial nations should promote financial globalization as a tool to reduce the ecological footprint by encouraging green financing and environmentally sustainable investments. For trade globalization, stricter environmental regulations and sustainable trade practices are essential to mitigate its adverse environmental effects. Also, efforts to minimize the ecological impact of information and communication technology should focus on integrating renewable energy into ICT infrastructure and advancing green technology innovations
Convergence of Data Mining and Process Management for Operational Inteligence
No full textABSTRACT Convergence of data mining and process management is ideal -but still limited. Data mining techniques helps in actionable knowledge discovery but lack for context awareness whereas process management systems support context awareness but lack for operational intelligence. To make process management systems operational intelligent, data mining techniques can be integrated within them in removing different inefficiencies. This paper presents an example of such a convergence in resolving one of the inefficiency relating to its resource management specifically to its static agent assignment strategies. To highlight the potentials of this convergence, an exemplary use case from textile industry is presented and discussed in depth along with experiments and experiences from textile industry
INSUFFICIENCY AND EXCESES OF CHOLECALCIFEROL (VITAMIN D3) CAUSES ADVERSE EFFECT ON HEALTH
No full textFirst author: Shakeel Ahmed
(Hazara University Department of Biochemistry)
Second author: Anhum Aslam
(Hazara University Department of Biochemistry
Research Fundamentals: Study Design, Population, and Sample Size
No full textThis is the second article of a three-part series that continues the discussion on the fundamentals of writing research protocols for quantitative, clinical research studies. In this editorial, the author discusses some considerations for including information in a research protocol on the study design and approach of a research study. This series provides a guide for undergraduate researchers interested in publishing their protocol in the Undergraduate Research in Natural and Clinical Sciences and Technology (URNCST) Journal.</jats:p
Synthesis and characterization of CuO/WO3 nanocomposite using hybrid method: Simple precipitation and pulsed laser ablation in liquids technique
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