This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Biped robots have gained much attention for decades. A variety of researches has been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand the human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. Some challenges encountered in the design of biped robots are: (1) biped robots have unstable structures due to the passive joint located at the unilateral foot-ground contact. (2) They have different configuration when switching from walking phase to another. During the singlesupport phase, the robot is under-actuated, while turning into an over-actuated system during the double-support pha

Abstract

The economic and financial crises in the world economy series led to increased awareness of the importance of the internal control system, because it is one of the main pillars of any economic unit, as it works to verify the application of policies, regulations and laws and verification of asset protection from theft and embezzlement procedures, it is also working on trust accounting information imparted through the validation of accounting information, analyze and detect the misleading.

The existence the internal control system a factor in many of the accounting practices that limit the ability of the administration to produce misleading financial reporting

The

In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

This research is concerned with a new type of ferrocement characterized by its lower density and enhanced thermal insulation. Lightweight ferrocement plates have many advantages, low weight, low cost, thermal insulation, environmental conservation. This work contain two group experimental : first different of layer ferrocement, second different of ratio aggregate to cement. The experiments were made to determined the optimum proportion of cement and lightweight aggregate (recycle thermestone ). A low W/C ratio of 0.4 was used with super plasticizer conforming to ASTM 494 Type G. The compressive strength of the mortar mixes is 20-25 MPa. The work also involved the determination of thermal properties .Thermal conductivity value of thi

The plant Conyza canadensis, which belongs to Asteraceae (Compositae) family and known as Canadian horseweed. It was used as traditional medicine in China, Pakistan, India, and Africa for the treatment of various diseases causing by bacteria, fungi, or viruses. The plant has antimicrobial, antioxidant, anticoagulant, anti-inflammatory, and anticancer pharmacological activity. This study provides the first phytochemical investigation of the plant in Iraq and is concerned with extraction, fractionation, isolation, and purification of some of the important phytochemicals detected in the plant-like phenolic acids, flavonoids, and alkaloids. Also, the literature survey has revealed that the plant has a substantial antimicrobial activity, so it w

A factorial experiment was conducted at the College of Education for Pure Sciences Ibn al Haitham/University of Baghdad for the 2023 growing season to study the effect of the biofertilizer represented by the mycorrhizae vaccine and the NPK Nano fertilizer on some indicators of vegetative and root growth, yield, and volatile oil production of the basil plant, Ocimum basilicum L., the experiment included two factors. The rst factor was mycorrhizae inoculum at 2 levels: 0 (no addition) and an addition of 25 g plant–1, as the seeds were inoculated upon planting. The second factor was spraying the plant’s shoots with NPK Nano fertilizer at four levels (0, 0.5, 1, 1.5) g l–1. The results showed a signicant eect of the treatment of inocula

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that