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CrossRef Open Access 2017
Of Pyramids and Dictators: Memory, Work and the Significance of Communist Heritage in Post-Socialist Albania

Francesco Iacono, Klejd L. Këlliçi

The communist regime that governed Albania between 1944 and 1991 has left considerable architectural remains. These however, are rapidly dissapearing, as a result of recent development. This paper explores the perception of the monumental heritage of the socialist regime in current day Albania. In our view, concepts of “unwanted” or “difficult” heritage used in the past to make sense of the heritage of socialist dictatorships, are not able to fully account for the specificities of the Albanian case as aspects other than trauma and pain need to be considered.The perception of the heritage from Albania’s communist past is investigated both through a theoretical discussion, which addresses the relationship between “unwanted heritage” and phenomena of nostalgia for certain aspects of life during communism, as well as through a questionnaire targeted at a sample of the population of the capital city Tirana. As far as this last aspect is concerned, our focus has been on the most iconic communist monument in Tirana, the Pyramid, the former museum dedicated to the dictator Enver Hoxha.In the last part of the paper, we try to make sense of the trends that emerged through the analysis of quantitative data, addressing the role of work and related forms of memory in forging the relationship between Albanians and the material remains of their recent past.

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CrossRef 2019
Detection of Diabetes using Biosensors

Department Of Computer Science And Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Ap, India., B. Venkateswarulu*, Nandita. Y et al.

Diabetes is the widespread disease in the world. During the last few decades there is a huge increase in the number of diabetic patients. Biosensor is a device which is used to detect diabetes. It converts biological reading into electrical pursuing that helps the patients to predict their diabetic levels. It consists of a biological recognition element and a chemical sensor. They are high-technology tracking tools that measures sugar levels in a quick, highly sensible fashion. We mainly focus on the glucose-oxidase biosensor which uses machine learning techniques and regression methods. Detection of diabetes can be done in many forms like with a radiofrequency biosensor chip, optical fiber biosensor, micro-fluidic biosensor. Optical biosensor is placed in contact lens to detect glucose levels within the tears and give the accurate prediction. There were some early versions of glucose-sensing devices. There are different existing techniques for the detection. But the preferred method is using the continuous glucose observing system. This method offers a good control of diabetes by using real time data. However, there are few provokes identified with the accomplishment of precise and dependable glucose observing. Further consistency and improvements in the development of biosensors to meet their goals are required.

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