Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

English

Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

This research aims at studying and analyzing the creative research thinking of the educational staffs in private universities and colleges, and also the role of incentives, in its materialistic and moral sides in the development of such thinking and the pack of restraints which cause decline in interest level of the scientificresearch, and its weak role in the development of universities in Iraq, despite the interest of the Ministry of Higher Education and Scientific Research in Iraq in scientific research as part ofits academic and humanitarian targets.Based on study and analysis, and the using if some of statistical methods such as the Alpha Chronobaghcoefficient and the (T. Test)(F. Test),the research reached a number of conclusions.

Objectives: The study aims at:
1- Measuring the level of lead in workers’ saliva and blood in the factory.
2- Studying the correlation between the saliva lead level and the infection that caused by microorganisms, isolation and
identification.
3-Studying the influence of high blood lead level on the total white blood cells.
Methodology: This study has been conducted for the period from March 15th, 2010 to May, 20th
, 2010. A total of (60)
saliva and blood samples were collected from workers in batteries industry factory in Baghdad and another (20) samples
were collected as a control group. Lead level had been measured in blood and saliva samples, then microorganisms were
isolated the from the saliva samples.

The research aims to measure the impact of envy on job stress because the topic of envy represents a negative emotion that exists at all organizational levels, which may cause stress in the work environment.

The Research problem is represented by the lack of perception of most of the faculty staff on the negative effects of envy on their well-being in the Technical College of Management - Baghdad, and what is the impact level of envy on their job stress.

To achieve this, the scale of envy was based on two dimensions (being envied, Envying others), While the job stress scale was based on seven dimensions (workload, conflict role, Family factors, work environment, work relationships

Authentic materials are the most important tools that the teacher could use in class in order to make teaching go smoothly and effectively in transmitting the necessary knowledge to all students. This research has investigated experimentally the effect of using authentic materials in teaching English as a foreign Language, because a number of studies point out that the use of authentic materials is regarded a useful means to motivate learners, arouse their interest and expose them to the real language they will face in real life situations.

It is hypothesis that there is no statistical significance difference between the experimental group who taught English as a foreign language by using the authentic materials with those