The COVID-19 outbreak from the SARS-CoV-2 virus has shocking us with its fast transmission and deadly complication. Due to that, the movement restriction has been enforced to contain this pandemic. Recently, there is an increasing pressure to restart and resurrect social and economic sectors, and to allow people to get back to work. This must be well planned before the movement restriction is lifted. Because of that, this paper aims to review and make recommendations on the new normal for our daily activities and works. Firstly, the social and economic sectors must be opening in phases by emphasizing safety and health than an economic recovery. In the meantime, the WHO recommendations on social distancing and personal hygiene must be adapted and become a new normal. Because of that, the government and local authorities should develop a soft landing approach based on the WHO recommendations. Next, the community must be engaged and empowered to do their parts in preventing the spread of COVID-19. From the new normal recommendations, the people can continue their daily routines, and at the same time can reduce COVID-19 transmission. However, medical possibilities are not considered while compiling these new normals and procedures. The population must adapt and embrace the new normal to control, reduce and prevent the spreading of COVID-19, as it could be with us for a long time.

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Over recent years, iris recognition has been an explosive growth of interest in human identification due to its high accuracy. Iris recognition is a biometric system that uses iris to verify and identify human identity. Iris has pattern that is rich with textures and can be compared among humans. There are many methods can be used in iris recognition. The methods based on the integro-differential operator and Hough transform are the most widely used in iris recognition. Unfortunately, both methods require more time to execute and has less accurate recognition accuracy due to the eyelid occlusion. In order to solve these problems, the Chan-Vese active contour is modified to reduce the execution time and to increase the recognition accuracy of iris recognition. Then, this method is compared with the integro-differential operator method. The iris images from CASIA-v4 database are used for the experiments. According to the results, the proposed method recorded 0.91 s for execution time which was 61.28 % faster than the integro-differential operator method. The proposed method also achieved 0.9831 for area under curve (AUC) which was 2.66 % higher recognition accuracy than the integro-differential operator method. To conclude, the modified Chan-Vese active contour was able to improve the performance of iris recognition compared to the integro-differential operator method.

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Iris recognition used the iris features to verify and identify the identity of human. The iris has many advantages such as stability over time, easy to use and high recognition accuracy. However, the poor quality of iris images can degrade the recognition accuracy of iris recognition system. The recognition accuracy of this system is depended on the iris pattern quality captured during the iris acquisition. The iris pattern quality can degrade due to the blurry image. Blurry image happened due to the movement during image acquisition and poor camera resolution. Due to that, a deblurring method based on the Wiener filter was proposed to improve the quality of iris pattern. This work is significant since the proposed method can enhance the quality of iris pattern in the blurry image. Based to the results, the proposed method improved the quality of iris pattern in the blurry image. Moreover, it recorded the fastest execution time to improve the quality of iris pattern compared to the other methods.