Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and operational robustness. Further research is needed to reach the full potential of THz technology in achieving sustainable agriculture. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
The goal of the research is to develop a sustainable rating system for roadway projects in Iraq for all of the life cycle stages of the projects which are (planning, design, construction and operation and maintenance). This paper investigates the criteria and its weightings of the suggested roadway rating system depending on sustainable planning activities. The methodology started in suggesting a group of sustainable criteria for planning stage and then suggesting weights from (1-5) points for each one of it. After that data were collected by using a closed questionnaire directed to the roadway experts group in order to verify the criteria weightings based on the relative importance of the roadway related impacts
... Show MoreWith the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MoreIn this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement. The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.
In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
... Show MoreThis study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44º 53ʹ 26.16 '- 45º 07 ʹ 28.03ʺ and 34º 04ʹ 24.75ʺ ــ 34º 19ʹ 12.74ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km2 for October and the lowest surface area 140.202 km2 for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on ban
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