The knowledge of the quantity of total solar radiation on horizontal and inclined surfaces is very important in the calculations of heating and cooling loads in architecture and in the design of certain solar energy applications such as photovoltaic and solar collectors. This paper estimates the total solar radiation on inclined surfaces in Baghdad (Lat. 33⁰ 21' N      44⁰ 14' long and 34m above MSL).  A good model was used to estimate hourly total solar radiation on the inclined surface with different elevations (15⁰, 30⁰, 45⁰, 60⁰, 75⁰, 90⁰) from a horizontal surface. The mean hourly, daily and monthl

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

     In this research, a type of gram negative bacteria was exposed to non-thermal plasma at a distance of (2 and 3 cm) from the plasma flow nozzle, with the use of an alternating power supply (5KHz), where exposure was made at two different voltages (4.9 and 8 kV). A negative gram of Pseudomonas aeruginosa bacteria was isolated and exposed to non-thermal plasma at different flow rates of argon gas whose value ranged from (1-5) liters/minute. The results showed that bacterial killing rate is directly proportional to distance while exposing the samples to non-thermal plasma, and the best factors by which a complete killing rate was obtained were at a distance of 2 cm with a voltage of 8 kV and a gas flow rate of 5 liters/min,

Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Background: Ganglions are the most common benign cystic swellings found around the wrist,they can be treated conservatively or by surgical excision,but the net results revieled no significant difference.Complete evacuation of the cysts followed by intracystic autologus blood instillation has given encouraging results.
Objective: To assess the efficacy and safety of aspiration of wrist ganglions and instillation of autologus blood inside the cysts.
Patients and Methods: Aprospective study was conducted on forty patients with wrist ganglions.20% of the patients underwent aspiration of the cysts alone,and the other 20 underwent aspiration of the cysts followed by autologus blood instillation, then an immobilization for seven to ten da

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