This paper proposes a new approach to model and analyze erect posture, based on a spherical inverted pendulum which is used to mimic the body posture. The pendulum oscillates in two directions, [Formula: see text] and [Formula: see text], from which the mathematical model was derived and two torque components in oscillation directions were introduced. They are estimated using stabilometric data acquired by a foot pressure mapping system. The model was quantitatively investigated using data from 19 participants, who were first were classified into three groups, according to the foot arch-index. Stabilometric data were then collected and fed into the model to estimate the torque’s components. The components were statistically proce

Abstract

     This research deals with Building A probabilistic Linear programming model  representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution .              &

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.

This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

Purpose:  To compare the central corneal thickness (CCT),minimum corneal thickness (MCT) and corneal power measured using theScheimpflug-Placido device and optical coherence tomography (OCT) in healthy eyes. Study Design:  Descriptive observational. Place and Duration of Study:  Al-Kindy college of medicine/university of Baghdad, from June 2021 to April 2022. Methods:  A total of 200 eyes of 200 individuals were enrolled in this study. CCT and MCT measurements were carried out using spectral-domain optical coherence tomography (Optovue) and a Scheimpflug-Placido topographer (Sirius).The agreement between the two approaches was assessed using Bland-Altman analysis in this study. Results:  Mean age was 28.54 ± 6.6 years, me

Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the