Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

One of the most important elements of achieving food security is livestock, which is an essential element in the agricultural sector, and is one of the state support sectors. Animal production (sheep) ranked an important position in this sector due to the economic advantages that are available when rearing. Moreover, the success and development of sheep breeding depend on several factors, including financial return and achieving profitability. The study aims to identify the phenomenon size of random slaughter as a problem, which spread in Baghdad and its causes and the factors that influencing its development. As well as, the possibility of applying the idea of a​​mobile slaughterhouse to reduce this phenomen

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

The study has used Geographic Information Systems (GIS) data and Arc GIS software, to produce a new map. This map contains a spatial database of the newly constructed buildings, in the area of water resources engineering college, and using the above tool for updating contains the college in any time, also the map and browse all buildings individually or in clustered, for example, browsing geometric data,  statistical data and the plans of drawings, and make any necessary changes to these sectors immediately, or in the future, like the expansion of the study halls by constructed a new floor, or add supplements, prepare any electrical to any building, and  anything else.  The paper also, updates the old Google Earth image, f

The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

     In this research, the geotechnical properties of soil for modern residential complexes in the city of Tikrit-Iraq were determined using six samples represented by three residential complexes (Bety, Yarmouk and Jawhara) and that these complexes built on gypsum soils suffer in the future from several engineering problems that appear in the form of cracks, inclination or subsidence in The buildings or the collapse of the facilities, the dilution of the roads and the breaking of the water and sewage networks due to the melting of the gypsum in the soil. One of the most important objectives for the research is that the residential complexes for the research area in Tikrit are not older than some years. With the urban expansion that a