In this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Machine scheduling problems (MSP) are     considered as one of the most important classes of combinatorial optimization problems. In this paper, the problem of job scheduling on a single machine is studied to minimize the multiobjective and multiobjective objective function. This objective function is: total completion time, total lead time and maximum tardiness time, respectively, which are formulated as  are formulated. In this study, a mathematical model is created to solve the research problem. This problem can be divided into several sub-problems and simple algorithms have been found to find the solutions to these sub-problems and compare them with efficient solutions. For this problem, some rules that provide efficient solutio

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

In this study, active knife and fixed knife of single-row disc silage machine has three different clearance C1, C2 and C3 (1, 3 and 5 mm) and it is tried in three different working speed V1, V2 and V3 (1.8, 2.5 and 3.7 km / h) and PTO speed (540 min-1) and machine's fuel consumption (l/h), average power consumption (kW), field energy consumption (kW/da), product energy consumption (kW/t), field working capacity (da/h), product working capacity (t/h) and Chopping size distribution characteristics of the fragmented material were determined. It has been found that knife-counter knife clearances smaller than 3 mm (1 mm) and larger (5 mm) have a negative effect on machine performance in general. In terms of fuel and power consumptions, the m

Objective: The aims of research to identify sample of websites of Arabian medical periodicals and exam applying to
standards for publishing on the internet.
Methodology: A survey method is applied about nine medical periodicals websites and data are collected through
forms include five international standards to assessing websites.
Results: of data collected, the following findings are obtained:
1. Through examining website addresses, unsuitability was found in using Universal Resources Locater, because six of
periodicals use com. in URL. While, all of them not relevance commercial but scientific aim.
2. To measure Credibility Standard by adopting numbers values, the results found, four of periodicals obtained (level

The study aimed to know the degree of availability of integrated preparation criteria in the Arabic Teacher training Program in Syrian universities from the viewpoint of university students of the Educational qualification diploma, and the degree of availability of these standards in the outputs of the preparation program. To achieve the Goals of the study, a list of integrated preparation criteria was prepare comprising (110) indicators, distributed to (11) criteria. The list was applied to a randomly chosen sample of (45) educational qualification diploma students. The results of the study showed that the Standards for integrated preparation are provided in a medium degree overall in the program for preparing teachers of Arabic languag

Deconstruction theory is a theory that appeared After construction theory, and it tends, through some key principles, to reach the purposive and the main meaning of the text by the means of different perspectives. In other words, deconstruction is a critical literary theory and a contemporary philosophical approach that work together to reach exact concept of the text, and this is achieved through reading and analyzing the text. Therefore, deconstruction has specified some principles so as to reach the exact meaning of the text through these different principles.

پێشەكی:

تیۆری هەڵوەشاندنەوە تیۆرێكە پاش بوونیادگەری سەریهەڵداوە و دەیەوێت لەڕ

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi