With 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

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes del

تواجه الوحدات الاقتصادية في العراق منافسة قوية بسبب مشكلات خاصة بإرتفاع الاسعار وارتفاع تكاليف الانتاج وضعف الاهتمام بدراسة السوق وغيرها من المشاكل ، فضلاً عن استخدام نظام التكاليف التقليدي الذي لا يوفر معلومات ملائمة لقرارات التسعير الامر الذي يتطلب دراسة وتحليل تلك المشكلات ومعالجتها بالاعتماد على تقنيات حديثة بما يمكنها من المنافسة ولهذا جاء هذا البحث والذي يعتبر من المداخل الحديثة لتخفيض التكاليف وم

This research is an attempt to study and evaluate the maintenance function at Factory 7 - The State General Company for Leather Industries, and to design a computerized preventive maintenance system to design and to analyze preventive  maintenance.  To accomplish the objectives of this research, data were gathered and analyzed according to the reliability engineering criteria for the period 2/1– 30/6/2005, then a preventive maintenance plan was designed for each machine of the sample study using the computerized system designed in this research. A Monte Carlo Simulation methodology was used for the purpose of evaluating the performance of the preventive maintenance plan of each machine for one year. The simulation res

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.