The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien

Water, an essential element for life, is becoming increasingly contaminated due to the continuing discharge of hazardous substances into our water sources. Pharmaceuticals, industrial chemicals, dyes, colorants, heavy metals, and pesticides are examples of some of the organic and inorganic substances that persistently contaminate water systems and traditional wastewater treatment systems are not designed to remove dissolved organic constituents, which is why their entry into the environment is so ubiquitous. Common pharmaceuticals such as aspirin, amoxicillin, ciprofloxacin, paracetamol, and ibuprofen, are amongst the most substantial contributors to water pollution The efficient and eco-friendly management of pharmaceutical pollutants pres

In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

We observed strong nonlinear absorption in the CdS nanoparticles of dimension in the range 50-100 nm when irradiant with femtosecond pulsed laser at 800 nm and 120 GW/cm 2 irradiance intensity. The repetition rate and average power were 250 kHz and

The No Mobile Phone Phobia or Nomophobia notion is referred to the psychological condition once humans have a fear of being disconnected from mobile phone connectivity. Hence, it is considered as a recent age phobia that emerged nowadays as a consequence of high engagement between people, mobile data, and communication inventions, especially the smart phones. This review is based on earlier observations and current debate such as commonly used techniques that modeling and analyzing this phenomenon like statistical studies. All that in order to possess preferable comprehension concerning human reactions to the speedy technological ubiquitous. Accordingly, humans ought to restrict their utilization of mobile phones instead of prohibit

Transdermal drug delivery has made an important contribution to medical practice but has yet to fully achieve its potential as an alternative to oral delivery and hypodermic injections. Transdermal therapeutic systems have been designed to provide controlled continuous delivery of drugs through the skin to the systemic circulation. A transdermal patch is an adhesive patch that has a coating of drug; the patch is placed on the skin to deliver particular amount of drug into the systemic circulation over a period of time. The transdermal drug delivery systems (TDDS) review articles provide information regarding the transdermal drug delivery systems and its evaluation process as a ready reference for the research scientist who is involved

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua

With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar