Been using a pv system program to determine the solar window for Baghdad city . the solar window for any location can be determine by deviating left and right from the geographical south as well as deviation according to the amount of tilt angle with the horizon for fixed panel so that will not change the average of solar radiation incident over the whole year and this lead to help in the process of installation of fixed solar panel without any effect on annual output .the range of solar window for Baghdad city between two angles ( -8 - +8 ) degrees left to right of the geographical south and tilt angle that allowed for the horizon range between angles (21- 30) degrees so that the amount of solar radiation that falling on the solar pan

The Video Assistant Referee (VAR) is a technology designed to review on- eld decisions through video footage in order to correct clear and critical refereeing errors. It enables the replay of key moments in slow motion to determine the correct naldecision,withcommunicationbetweenthevideoof cialsandtherefereeconductedviaheadset.Thesystem operates under the principle of "minimal interference, maximum bene t," intervening only in essential situations. This study aimedtoassessthecurrent implementationofVARintheIraqStarsFootballLeagueduringthe2023–2024season. To achieve this objective, the researchers employed a descriptive survey method involving a sample of 220 participants, including referees, coaches, players, assessors, academics, a

The current study deals with host-guest complex formation between cucurbit [7] urils as host and lansoprazole as guesti using PM3 (semi empirical molecules orbital calculations) also DFT calculations. In this complex, the formation of hydrogen bonding may be occurred through portal oxygen atoms(O2) of cucurbit [7] urils and amine groups (NH 2 )of the drug. The energies of HOMO and LUMO orbital’s have been computed for the host guest complex and its components. The result of the stabilization energy explained a complex formation.

A study carried out in quail’s field owned by the Department of Animal production/ Collage of Agriculture / Tikrit University. For the period 14/ 5/ 2016 to 4/ 6/ 2016 in order to study the effect of adding Curcuma longa - to the diet of quails - on some productive and physiological characteristics of the Japanese quail birds bred for meat production. Using (48) quail birds which are two weeks old provided by Department of Agricultural Research. The birds were divided randomly after weighing them into three treatments; four replicate treatments for (4 bird/ replicate). The treatments as follows: (T1) control group (fed diet without any supplement), second (T2) and third (T3) groups were fed diet supplemental 4.5 and 9g Curcuma powder /

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.