Dan Barfod la Cour: Pioneer of Geomagnetism and International Scientific Cooperation | Book Publisher International

 

Dan Barfod la Cour (1876–1942) was a distinguished scientist, instrument constructor, and international coordinator in geomagnetism and meteorology. He was the son of Poul la Cour, a Danish physicist who served as deputy director of the Danish Meteorological Institute (MI, now DMI) and later as professor at Askov Folk University. Dan la Cour matriculated from Lyceum in 1895, completed his military service in 1896–97, and worked as a science assistant at the University of Copenhagen from 1897–99. He obtained his M.Sc. degree from Copenhagen University in 1902 and became assistant professor at the Technical University in 1908. Dan la Cour participated in DMI aurora expeditions to Iceland and Finland during 1899–1901 and was employed at DMI in 1900. He became head of the DMI weather department in 1903, head of the department of geomagnetism in 1920, and served as director of DMI from 1923 until his death in 1942.

 

Dan la Cour was a brilliant instrument builder who constructed precision instruments for geomagnetic measurements, including the Copenhagen Variometer, the Godhavn Balance and BMZ vertical intensity variometers, and the QHM quartz horizontal magnetometer. These instruments were manufactured in Copenhagen and supplied to magnetic observatories worldwide during 1930–50. In 1925, he established a magnetic observatory in Godhavn, the first in Greenland, and initiated magnetic observations from Thule and Julianehaab, Greenland, during the Polar Year 1932–33.

 

Dan la Cour served the international scientific community as President of the Polar Year Commission from 1929, as Secretary of the International Association of Terrestrial Magnetism and Electricity from 1933 to1936, and as President of the International Union of Geodesy and Geophysics from 1936 to 1942.

 

 

Author(s) Details

Peter Stauning
Danish Meteorological Institute, Copenhagen, Denmark

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-93-88417-19-8

Harnessing Crowdsourcing and Machine Learning for Mobile Services Performance Analysis | Chapter 8 | Advances and Challenges in Science and Technology Vol. 2

 Data accumulation from user terminals or specialized group devices is necessary for crowdsourcing the evaluation of quality of knowledge (QoE) on mobile networks. With this method, mobile operators and professors may more affordably address large-scale issues, embellish resource distribution, and supply networks. Based on this strategy, we present here a vocabulary of dataset generation though movable signals measurements, and also a inclusive study utilizing crowdsourced data from consumer terminals to analyze the QoE of common Internet services, such as on-demand program streaming, netting browsing, and file downloading. The dataset, comprising over 220,000 calculations collected from two different dealer terminals and various maneuverability test modes, was obtained from a bigger French mobile driver in the Ile-de-France region over a six-month ending in 2021. Various models from the literature are then achieved to estimate the QoE in terms of consumer Mean Opinion Score (MOS), utilizing features at two together the radio and use levels. Furthermore, a detailed analysis of the calm dataset is conducted to identify the root causes of weak performance, disclosing that radio provisioning issues are not the singular factor donating to anomalies. Lastly, the chapter survey the prediction accuracy of HD broadcast streaming duties, considering factors to a degree launch occasion, bitrate, and MOS, based solely on material indicators. The analysis surrounds both ordinary readable form and encrypted traffic within different maneuverability modes, providing valuable acumens into QoE optimization in mobile networks.

Author(s) Details:

Lamine Amour,
ESME Engineering School / ESME Research Lab, France.

Abdulhalim Dandoush,
ESME Engineering School / ESME Research Lab, France and University of Doha for Science and Technology (UDST), Qatar and Laboratoire de Traitement et Transport de l’Information (L2TI) institution of Sorbonne University, France.

Please see the link here: https://stm.bookpi.org/ACST-V2/article/view/11931

Methodology of Data Collection in Information System (IS)| Chapter 7 | Current Overview on Science and Technology Research Vol. 9

This phase aims to give and explain the components of research methods in information order (IS), and compare between approximate approach and quantitative approach, in addition to justification for use of the record of what happened in information arrangement (IS). Research methodology in a research study is thought-out as an important detail, and therefore deciding the method of research methods is very important step. The qualitative approach design provides reasons to explore the phenomenon, belief building and catching everyday history through data group and analysis. Research methodology is valuable to establishing the makeup of research, such as policy, approach, research philosophy, and elements of the methodology. The main countenance that distinguish the exploratory study from other arrangements are the possibility of ruling the experimental variable or the cause to attain the hypothesis. The aim of research design is to specify a clear picture of the construction of the research as well as the designs used, in the way that data group, research questions, and data beginnings. The research design allows the researcher to outline all essential methods and forms for the research, such as project belief and research methodology.

Author(s) Details:

Mohamed Al Kilani,
Kharkov National University of Radio Electronics, Kharkov, Ukraine.

Volodymyr Kobziev,
Kharkov National University of Radio Electronics, Kharkov, Ukraine.

Please see the link here: https://stm.bookpi.org/COSTR-V9/article/view/8764

Autonomous Monitoring and Quality Control in Cyclic Manufacturing Process | Chapter 7 | New Ideas Concerning Science and Technology Vol. 2

 Injection moulding is commonly used in production processes for the production of plastic parts with a broad lot size, so continual improvements in the performance of product quality are important for maintaining a competitive advantage in the injection moulding industry. The presence of any difference impacts productivity for the whole lot. Conventionally, the consistency of the moulded product depends on the machine operator's expertise and understanding, since we can not monitor the process in between. The operator tries various settings, as suggested by the manufacturer, to achieve the optimum efficiency. For the optimization of the injection moulding process, various offline optimization techniques such as ANN, GA, Iterative system, and simulations are in use. But still, consistency errors occur due to variation during the moulding cycles. The data for operating process parameters can be reciprocated by modern injection moulding equipment, and external control methodologies can also be applied to the system. The work discussed focuses on the implementation of smart technology for real-time monitoring and control of the process of injection moulding. To make the process of moulding smart. To track the process inside the mould, cavity sensors, including pressure and temperature sensors, are used. Data generation, acquisition, collection, analysis, and failure detection are part of smart monitoring. In order to compensate for the variance of the moulding condition in the mould cavity so that the quality consistency is always satisfied, an AI-based autonomous control strategy is later determined. To derive the control strategy, process parameters and their interrelationship with quality defects have been studied and used. After its implementation, the whole process is expected to be smart and autonomous. To validate the established system for an automotive product, real industry scenarios and processing data were used. An automotive product, i.e. card door trim, is the research object chosen for this research. A comparative analysis shows that the number of scrap parts can be decreased effectively by 20 percent. This work is done with the mindset of constantly bringing the goods to the highest level, and in many respects it will definitely benefit the moulding and automotive industry.

Author(s) Details

Saurabh Kumar
School of Mechanical & Automotive Engineering, University of Ulsan, Ulsan 680-749, Korea.

Hong Seok Park
School of Mechanical & Automotive Engineering, University of Ulsan, Ulsan 680-749, Korea.

Prof. Dr. Chang Myung Lee
School of Mechanical & Automotive Engineering, University of Ulsan, Ulsan 680-749, Korea.

View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/320