The continuous growth in technology and technological devices has led to the development of machines to help ease various human-related activities. For instance, irrespective of the importance of information on the Steam platform, buyers or players still get little information related to the application. This is not encouraging despite the importance of information in this current globalization era. Therefore, it is necessary to develop an attractive and interactive application that allows users to ask questions and get answers, such as a chatbot, which can be implemented on Discord social media. Artificial Intelligence is a technique that allows machines to think and be able to make their own decisions. This research showed that the dis

This study aimed to evaluate the sustainable efficiency and calculate the sustainable value, opportunity cost and revenue to cost of potato production farms in Baghdad Governorate. Data were collected from a random sample of 102 spring potato producers in Baghdad governorate for the year 2022, the value-added function was estimated using three levels: economic (seeds and space), and social (education level), while environmental represented by (residual and volatile of nitrogen). Effective resources were calculated to extract the sustainability value- SV appeared on an average of 18023.15 thousand Iraqi dinars. Positive relationship with residual nitrogen and productivity, and Inverse relationship to the amount of volatile nitrogen.

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

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu