Background: Coronavirus pandemic (COVID-19) has enormously affected various healthcare services including the one of community pharmacy. The ramifications of these effects on Iraqi community pharmacies and the measures they have taken to tackle the spread of COVID-19  is yet to be explored. In this cross sectional survey, infection control measures by community pharmacies in Sulaimani city/Iraq has been investigated.        

Methods: Community pharmacists were randomly allocated  to participate in a cross-sectional survey via visiting their pharmacies and filling up the questionnaire form.

Results and discussion:

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

     Feature selection, a method of dimensionality reduction, is nothing but collecting a range of appropriate feature subsets from the total number of features. In this paper, a point by point explanation review about the feature selection in this segment preferred affairs and its appraisal techniques are discussed. I will initiate my conversation with a straightforward approach so that we consider taking care of features and preferred issues depending upon meta-heuristic strategy. These techniques help in obtaining the best highlight subsets. Thereafter, this paper discusses some system models that drive naturally from the environment are discussed and calculations are performed so that we can take care of the prefe

With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

Steganography is the art of concealing security data in media, such as pictures, audio, video, text, and protocols. The objective of this paper is hiding a secret message in a colour image to prevent an attacker from accessing the message. This is important because more people use the Internet all the time and network connections are spread around the world. The hidden secret message uses two general algorithms that are embedded and extracted. This paper proposes a new algorithm to conceal a secret message in a colour image in LSB. This algorithm includes three phases: 1) dividing the colour image into a number of blocks, 2) concealing the secret message, and 3) transmitting the stego-image from the sender in a multiplexer network and re

Background and objective: Viral Hepatitis Type B&C is serious public health challenge throughout the world.Hepatitis B and C viruses still remain to be the major causes of chronic hepatitis.It is estimated that around 350-400 million people in the world are chronic carriers of HBV, which represents approximately 7% of the total populationwhereas infection with HCV is found in approximately 3% of the world population, which represents 160 million people. Hepatitis B infection has a wide range of seroprevalence in the Mediterranean countries ranging from intermediate (=>2% ) to high prevalence ( =>7%). World Health Organization estimated a prevalence rate for HCV infection of about 4.6% in Eastern Mediterranean in 1999. During the eightieths

Background: Data on SARS-CoV-2 from developing countries is not entirely accurate, demanding incorporating digital epidemiology data on the pandemic.

Objectives: To reconcile non-Bayesian models and artificial intelligence connected with digital and classical (non-digital) epidemiological data on SARS-CoV-2 pandemic in Iraq.

Results: Baghdad and Sulaymaniyah represented statistical outliers in connection with daily cases and recoveries, and daily deaths, respectively. Multivariate tests and neural networks detected a predictor effect of deaths, recoveries, and daily cases on web searches concerning two search terms, "كورونا" and "Coronavirus" (Pillai's Trace val