English has for long been one of the most widely used media of communication globally, especially in the Malaysian universities. It has been termed as a Lingua Franca because it is shared with other languages which are considered first languages by different speakers. For this reason, English as a Lingua Franca (ELF) has attracted a number of researchers to investigate its variety via other languages in various communities. The objective of this paper is therefore to establish the strategies which are employing by the international students at the National University of Malaysia/ UniversitiKebangsaan Malaysia (UKM) as an example of one of the Malaysian universities; when they e

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Background: Concha bullosa is an anatomical variation which defined by pneumatizaton of middle turbinate that occurred with an incidence of (5 to 25%) in the normal population.It has the potential to cause crowding and obstruction of the middle meatus and nasal cavity. There are many surgical techniques which utilized for its management. Study goal: Is to compare the formation of adhesion between endoscopic partial lateral middle turbinectomy and middle turbinate trimming in cases of concha bullosa. Patients and methods: A prospectivecomparative clinical trial was performed in the ENT department at Al-Shahid Ghazi AL Hariri Hospital in Medical City over the period from September 2016 to August 2017. Fifty nine (59) patients {24 males

The aim of this study was to assess the effectiveness of listening to music or Quran in reducing cancer patients’ anxiety before chemotherapy administration. Reducing anxiety in people with cancer, prior to chemotherapy administration, is a crucial goal in nursing care.

Background: Acne is a common disorder experienced by adolescents and persists into adulthood in approximately 12%–14% of cases with psychological and social implications of high gravity. Fractional resurfacing employs a unique mechanism of action that repairs a fraction of skin at a time. The untreated healthy skin remains intact and actually aids the repair process, promoting rapid healing with only a day or two of downtime. Aims: This study, was designed to evaluate the safety and effectiveness of fractional photothermolysis (fractionated Er: YAG laser 2940nm) in treating atrophic acne scars. Methods: 7 females and 3 males with moderate to severe atrophic acne scarring were enrolled in this study that attained private clinic for Derm

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f