Meloxicam is a non-steroidal anti-inflammatory drug. It is practically insoluble in water. It is associated with gastrointestinal side effects at high doses on long  term treatment. The aim of this investigation to formulate and evaluate gellified nanoemulsion of meloxicam as a topical dosage form to enhance meloxicam therapeutic activity and reduce systemic side effect.

The pseudo ternary phase diagrams were made, including  the oil mixture which is composed of almond oil and peppermint oil at a ratio (1:2), variable surfactant mixture (S mix) which are tween 80 and ethanol at ratios of (1:1, 2:1, 3:1, and 4:1) and double distilled water. Slow dripping of double distilled water to the combination  of the oil mixtu

Objective: To determine the effectiveness of the Nursing Management Education Program upon the Nurse
Managers' Knowledge about planning in Nursing Management at Baghdad City Hospitals.
Methodology: A Quasi-experimental study in which a purposive "non-probability" sample of (50) Nurse
Managers was selected from Baghdad City Hospitals. These Managers were divided into two equal groups of
(25) Nurse Managers for each (study and control ones). A questionnaire was developed as a tool for data
collection. A pilot study was carried out to test the reliability of the questionnaire for the period from April 2nd to
June 20th 2007. The pre-post test approach was applied to the study and control groups as mean for the quasiexperime

Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

A growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. Recently, a tremendous number of studies have been conducted in the field of speech enhancement. This study aims to map the field of speech enhancement by conducting a systematic literature review to provide comprehensive details of recently proposed SEAs. This systematic review aims to highlight research trends in SEAs and direct researchers to the most important topics published between 2015 and 2024. It attempts to address seven key research questions related to this topic. Moreover, it covers articles available

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

The present study aimed to examine the concordance between FISH/CISH techniques for assessment of amplification of her2neu gene in Iraqi breast carcinoma patients. Seventy four (74) Iraqi breast cancer patients were involved at the study from the Histopathology Department at the Central Public Health Laboratory in Bagdad, Iraq. Amplification of HER2neu was detected in (33.8%) by fluorescence in situ hybridization and (13.51%) showed high amplification by chromogenic in situ hybridization and (32.43%) showed low amplification. The results of chromogenic in situ hybridization were significantly correlated with the results of two-color fluorescence in situ hybridization with the same tumors. In addition, the study involved the correlation betw