Construction is a hazardous industry with a high number of injuries. Prior research found that many industry injuries can be prevented by implementing an effective safety plan if prepared and maintained by qualified safety personnel. However, there are no specific guidelines on how to select qualified construction safety personnel and what criteria should be used to select an individual for a safety position in the United States (US) construction industry. To fill this gap in knowledge, the study goal was to identify the desired qualifications of safety personnel in the US construction industry. To achieve the study goal, the Delphi technique was used as the main methodology for determining the desired qualifications for constructio

Current numerical research was devoted to investigating the effect of castellated steel beams without and with strengthening. The composite concrete asymmetrical double hot rolled steel channels bolted back to back to obtain a built-up I-shape form are used in this study. The top half part of the steel is smaller than the bottom half part, and the two parts were connected by bolting and welding. The ABAQUS/2019 program employed the same length and conditions of loading for four models: The first model is the reference without castellated and strengthening; the second model was castellated without strengthened; the third model was castellated and strengthened with reactive powder concrete encased in the

The present paper describes a static model of malware detection and employs a tri-class prevention policy that operates on the EMBER 2024 Win64 partition. A LightGBM classifier trained on 1,040,000 samples and 804 static PE features achieves AUC-ROC = 0.9979, precision = 98.7%, recall = 97.4%, and F1 = 0.9805 on the temporally-split 240,000-sample test set. An innovative Tri-class Threshold Scheme (BLOCK/SUSPICIOUS/ALLOW) obtained by constrained F2-score optimisation on a separate validation set obtains 97.9% malware detection with 98.1% benign pass rate. Efficient model scoring is verified by mean per-sample model inference latency of 2.30 ms (P99: 2.70 ms) measured on pre-extracted EMBER features, future work is characterized by a complet

In this study, the volatile compounds found in lemon trees infested and uninfested with Planococcus citri (Risso) (Hemiptera: Pseudococcidae) were investigated. In addition, the interest of the predator Cryptolaemus montrouzieri (Coleoptera: Coccinellidae) and the parasitoid Leptomastix dactylopii (Hymenoptera: Encyrtidae) in lemon trees infested and uninfested with P. citri and some volatile compounds was investigated. According to the results obtained, most of the volatile compounds obtained from mealybug-infested lemon trees showed changes compared to healthy lemon trees. Since volatile compounds play an important role in attracting pests and natural enemies, linalyl acetate was selected as the compound showing the highest amount of chan

Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study