This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

The foreguts of a total of 515 fish of Chondrostoma regium (Heckel, 1843) (locally: Bala’aot Malloky) were studied. These fish were collected from Tigris River at Salah Al-Deen Province (between Al-Hagag & Yathrib) for 20 months between March and October of the next year. Detritus, plant in origin materials (19.6%, 23.0% & 24.9%); green and blue green algae, mostly Cladophora, Cosmarium and Merismpedia sp. (17.1%, 12.9% & 12.2%) and diatoms, mostly Diatoma, Chanathes, Amphora and Cyulbella sp. (16.9%, 8.8% & 8.2%) were the main food categories taken by these fishes according to occurrence (O%), volumetric methods (V%) and ranking index (R%). Debris (not part of the diet) took 45.3% of the studied fish foreguts by volume. Detritus was also

In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data

The research aims to find a contemporary model in analyzing the reasons behind the delay of the investment plan projects suffered by the North Oil Company. This model is able to understand the environment surrounding the implementation of projects in the light of the changes facing the company at the present time, which in turn requires the need to identify the most important strengths and weaknesses Internal and external opportunities and threats using the SWOT matrix and identify the appropriate strategic alternative based on clear policy, strategies and programs to address weaknesses and look to the future prospects as the company can be stronger and more flexible environmental changes surrounding the reality of implementation