vikatan publishing solutions mär 2023 (8 résultats)

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A warm foot bath is a traditional home remedy used to relieve various conditions such as stress, fatigue, insomnia, and pain. This therapy involves immersing the feet in warm water for a specific period, usually between 10 to 30 minutes. The warmth of the water helps to relax the muscles, increase blood flow, and promote overall relaxation. In recent years, there has been increasing interest in the use of warm foot baths as a complementary therapy for children. This article will explore the efficacy of warm foot baths among children in 1000 words.Studies have shown that warm foot baths can be beneficial for children in various ways. For example, a study published in the Journal of Korean Academy of Nursing showed that warm foot baths can help to improve sleep quality in children with sleep disturbances. The study involved 60 children between the ages of 6 and 12 who were randomly assigned to either a warm foot bath group or a control group. The warm foot bath group received a 20-minute foot bath at 40°C every night for two weeks, while the control group received no intervention. The results showed that the warm foot bath group had significant improvements in sleep quality compared to the control group. The researchers suggested that warm foot baths may help to relax the body and mind, leading to better sleep quality. Another study published in the Journal of Alternative and Complementary Medicine showed that warm foot baths can help to reduce pain in children with acute gastroenteritis. The study involved 100 children between the ages of 3 and 12 who were randomly assigned to either a warm foot bath group or a control group. The warm foot bath group received a 10-minute foot bath at 40°C every four hours for two days, while the control group received no intervention 96 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Thyroid disorders are among the most common endocrine disorders, affecting millions of people worldwide. Early detection of thyroid disorders is essential for effective treatment and management of the condition. Currently, laboratory tests are used to diagnose thyroid disorders, but these tests can be time-consuming and expensive. In recent years, there has been growing interest in the use of spectroscopy and machine learning for the prediction of thyroid disorders.Spectroscopy is a powerful tool for the analysis of biological samples. It involves the measurement of the interaction between light and matter, allowing for the identification and quantification of various chemical compounds. Spectroscopy can be used to detect changes in the biochemical composition of biological tissues, which can be indicative of thyroid disorders. Machine learning is a subfield of artificial intelligence that involves the development of algorithms that can learn from data. Machine learning algorithms can be trained to recognize patterns in spectroscopic data that are associated with thyroid disorders. Once trained, these algorithms can be used to predict the likelihood of a patient having a thyroid disorder based on their spectroscopic data. Several studies have investigated the use of spectroscopy and machine learning for the prediction of thyroid disorders. One study used near-infrared (NIR) spectroscopy to analyze the thyroid gland of patients with thyroid disorders. The study found that NIR spectroscopy could accurately distinguish between healthy thyroid tissue and tissue with thyroid disorders. Another study used Raman spectroscopy to analyze the blood of patients with thyroid disorders. The study found that Raman spectroscopy could accurately distinguish between healthy blood samples and blood samples from patients with thyroid disorders. The study also found that machine learning algorithms could be used to predict the presence of thyroid disorders based on Raman spectroscopic data. 134 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The process of preparing bricks using mine waste involves mixing the waste materials, such as fly ash and bottom ash, with clay and other binding agents to create a homogeneous mixture. The mixture is then pressed into molds and allowed to dry and harden. The resulting bricks have several advantages, including lower costs, reduced environmental impact, and improved structural properties. The use of mine waste in brick making also helps to reduce the volume of waste produced by mining operations, making it a more sustainable practice. This process has the potential to make a significant contribution to sustainable construction and waste management practices. The use of mine waste in brick making has gained increasing attention in recent years due to the increasing demand for sustainable construction materials and the need for effective waste management practices. The mining industry generates a significant amount of waste materials, such as fly ash and bottom ash, which are often disposed of in landfills or ponds. However, these waste materials have the potential to be used as raw materials for brick making. The process of preparing bricks using mine waste involves several steps. The waste materials are first collected and transported to the brick manufacturing site. The waste materials are then mixed with clay and other binding agents to form a homogeneous mixture. The proportion of mine waste to other ingredients in the mixture may vary depending on the quality and quantity of the waste material. Once the mixture is prepared, it is then pressed into molds using hydraulic or manual presses. The molded mixture is then allowed to dry and harden, either through air drying or by using a kiln. The resulting bricks are then ready for use in construction. 162 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Privacy protection in big data analytics refers to the process of safeguarding the privacy and confidentiality of sensitive information in large datasets, while still allowing for the extraction of valuable insights and patterns from the data. Big data analytics involves the use of advanced algorithms and technologies to analyze vast amounts of data, often containing personal or sensitive information, to gain insights and make informed decisions.However, as more and more data is collected and analyzed, there is an increasing risk of privacy breaches and data misuse. To address this challenge, privacy protection techniques such as data anonymization, encryption, and access controls are used to ensure that sensitive information is protected from unauthorized access or disclosure. Data anonymization involves the removal or modification of personally identifiable information (PII) from the dataset, while still retaining its usefulness for analysis. Encryption involves encoding the data in a way that can only be deciphered with a key, ensuring that only authorized users can access it. Access controls restrict access to the data to only those who need it for legitimate purposes. Privacy protection in big data analytics is crucial for maintaining trust between data owners and users, protecting individual privacy rights, and complying with regulatory requirements 140 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -A warm foot bath is a traditional home remedy used to relieve various conditions such as stress, fatigue, insomnia, and pain. This therapy involves immersing the feet in warm water for a specific period, usually between 10 to 30 minutes. The warmth of the water helps to relax the muscles, increase blood flow, and promote overall relaxation. In recent years, there has been increasing interest in the use of warm foot baths as a complementary therapy for children. This article will explore the efficacy of warm foot baths among children in 1000 words.Studies have shown that warm foot baths can be beneficial for children in various ways. For example, a study published in the Journal of Korean Academy of Nursing showed that warm foot baths can help to improve sleep quality in children with sleep disturbances. The study involved 60 children between the ages of 6 and 12 who were randomly assigned to either a warm foot bath group or a control group. The warm foot bath group received a 20-minute foot bath at 40°C every night for two weeks, while the control group received no intervention. The results showed that the warm foot bath group had significant improvements in sleep quality compared to the control group. The researchers suggested that warm foot baths may help to relax the body and mind, leading to better sleep quality. Another study published in the Journal of Alternative and Complementary Medicine showed that warm foot baths can help to reduce pain in children with acute gastroenteritis. The study involved 100 children between the ages of 3 and 12 who were randomly assigned to either a warm foot bath group or a control group. The warm foot bath group received a 10-minute foot bath at 40°C every four hours for two days, while the control group received no interventionLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 96 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Thyroid disorders are among the most common endocrine disorders, affecting millions of people worldwide. Early detection of thyroid disorders is essential for effective treatment and management of the condition. Currently, laboratory tests are used to diagnose thyroid disorders, but these tests can be time-consuming and expensive. In recent years, there has been growing interest in the use of spectroscopy and machine learning for the prediction of thyroid disorders.Spectroscopy is a powerful tool for the analysis of biological samples. It involves the measurement of the interaction between light and matter, allowing for the identification and quantification of various chemical compounds. Spectroscopy can be used to detect changes in the biochemical composition of biological tissues, which can be indicative of thyroid disorders. Machine learning is a subfield of artificial intelligence that involves the development of algorithms that can learn from data. Machine learning algorithms can be trained to recognize patterns in spectroscopic data that are associated with thyroid disorders. Once trained, these algorithms can be used to predict the likelihood of a patient having a thyroid disorder based on their spectroscopic data. Several studies have investigated the use of spectroscopy and machine learning for the prediction of thyroid disorders. One study used near-infrared (NIR) spectroscopy to analyze the thyroid gland of patients with thyroid disorders. The study found that NIR spectroscopy could accurately distinguish between healthy thyroid tissue and tissue with thyroid disorders. Another study used Raman spectroscopy to analyze the blood of patients with thyroid disorders. The study found that Raman spectroscopy could accurately distinguish between healthy blood samples and blood samples from patients with thyroid disorders. The study also found that machine learning algorithms could be used to predict the presence of thyroid disorders based on Raman spectroscopic data.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 134 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The process of preparing bricks using mine waste involves mixing the waste materials, such as fly ash and bottom ash, with clay and other binding agents to create a homogeneous mixture. The mixture is then pressed into molds and allowed to dry and harden. The resulting bricks have several advantages, including lower costs, reduced environmental impact, and improved structural properties. The use of mine waste in brick making also helps to reduce the volume of waste produced by mining operations, making it a more sustainable practice. This process has the potential to make a significant contribution to sustainable construction and waste management practices. The use of mine waste in brick making has gained increasing attention in recent years due to the increasing demand for sustainable construction materials and the need for effective waste management practices. The mining industry generates a significant amount of waste materials, such as fly ash and bottom ash, which are often disposed of in landfills or ponds. However, these waste materials have the potential to be used as raw materials for brick making. The process of preparing bricks using mine waste involves several steps. The waste materials are first collected and transported to the brick manufacturing site. The waste materials are then mixed with clay and other binding agents to form a homogeneous mixture. The proportion of mine waste to other ingredients in the mixture may vary depending on the quality and quantity of the waste material. Once the mixture is prepared, it is then pressed into molds using hydraulic or manual presses. The molded mixture is then allowed to dry and harden, either through air drying or by using a kiln. The resulting bricks are then ready for use in construction.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 162 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Privacy protection in big data analytics refers to the process of safeguarding the privacy and confidentiality of sensitive information in large datasets, while still allowing for the extraction of valuable insights and patterns from the data. Big data analytics involves the use of advanced algorithms and technologies to analyze vast amounts of data, often containing personal or sensitive information, to gain insights and make informed decisions.However, as more and more data is collected and analyzed, there is an increasing risk of privacy breaches and data misuse. To address this challenge, privacy protection techniques such as data anonymization, encryption, and access controls are used to ensure that sensitive information is protected from unauthorized access or disclosure. Data anonymization involves the removal or modification of personally identifiable information (PII) from the dataset, while still retaining its usefulness for analysis. Encryption involves encoding the data in a way that can only be deciphered with a key, ensuring that only authorized users can access it. Access controls restrict access to the data to only those who need it for legitimate purposes. Privacy protection in big data analytics is crucial for maintaining trust between data owners and users, protecting individual privacy rights, and complying with regulatory requirementsLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 140 pp. Englisch.