Distortion Level Analysis of a 2D Median Filter with a Weighted Central Element

Abstract:The sharing of knowledge worldwide using hypermedia facilities and fast communication protocols (i.e., Mosaic and World Wide Web) provides a growth capacity with tremendous versatility and efficacy. The example of ExPASy, a molecular biology server developed at the University Hospital of Geneva, is striking. ExPASy provides hypermedia facilities to browse through several up-to-date biological and medical databases around the world and to link information from protein maps to genome information and diseases. Its extensive access is open through World Wide Web. Its concept could be extended to patient data including texts, laboratory data, relevant literature findings, sounds, images and movies. A new hypermedia culture is spreading very rapidly where the international fast transmission of documents is the central element. It is part of the emerging new “information society”.

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Gene Expression Level Analysis

10.32388/eeuvoc ◽

2020 ◽

Author(s):

Keyword(s):

Gene Expression ◽

Gene Expression Level ◽

Expression Level ◽

Level Analysis

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Economic models of Environment monitoring under imperfect information and high Costs

Voprosy Ekonomiki ◽

10.32609/0042-8736-2014-4-99-122 ◽

2014 ◽

pp. 99-122

Author(s):

M. Levin ◽

K. Matrosova

Keyword(s):

Environmental Monitoring ◽

Environmental Regulation ◽

Environmental Economics ◽

Imperfect Information ◽

Central Element ◽

Economic Models ◽

Environment Monitoring ◽

Nature Protection ◽

Protection Measures ◽

Effective System

The paper considers monitoring of environmental change as the central element of environmental regulation. Monitoring, as each kind of principalagent relations, easily gives rise to corruptive behavior. In the paper we analyze economic models of environmental monitoring with high costs, incomplete information and corruption. These models should be the elements of environmental economics and are needed to create an effective system of nature protection measures.

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İstanbul İlçelerinin Nüfus Değişimi ve Kütük Bilgilerinin Analizi

GÖÇ DERGİSİ ◽

10.33182/gd.v6i1.635 ◽

2019 ◽

Vol 6 (1) ◽

pp. 37-72

Author(s):

Ulaş Sunata ◽

Dila Ergül

Keyword(s):

Population Growth ◽

Population Growth Rate ◽

Population Change ◽

Urban Migration ◽

Specific Population ◽

Related Factors ◽

Internal Migrant ◽

Level Analysis ◽

Study District ◽

Demographic Features

39 ilçesiyle Türkiye’nin en büyük nüfusuna sahip ili İstanbul aynı zamanda Türkiye’nin en çok iç göç alan şehridir. Özellikle kırdan kente göç bağlamında sosyo-ekonomik ve demografik özellikleriyle birçok araştırmaya konu olmuştur. Fakat İstanbul yerleşik nüfusunun Türkiye’nin diğer şehirlerine kayıtlı olma yoğunluğu da önemlidir. Bu çalışmanın amacı 2012 ve 2017 yıllarındaki nüfus değişimini göz önünde bulundurarak İstanbul ilçelerinin ayrıntılı nüfus yoğunluğu ve büyüme analizini yapmak, ilgili faktörleri değerlendirmek, hemşehri ağlarını okumak adına yerleşik nüfus kütük bilgileri bakımından inceleyerek elde edilen örüntüler doğrultusunda ilçe tipolojileri oluşturmaktır. Çalışmanın birinci bölümünde ilgili beş yıllık nüfus değişimlerine göre İstanbul ilçe nüfusları analiz edilmiştir. Ardından her bir ilçe için nüfusa kayıtlı olunan kente göre nüfus büyüme hızlarına bakılarak ilçelerin ağırlıklı olarak barındırdığı hemşehri ağları belirlenmiştir. İkinci bölümde ise ilçeler nüfus değişim özelliklerine göre belirli kategorilere ayrılmış ve bu kategoriler doğrultusunda ilçe tipolojileri oluşturulmuştur..ABSTRACT IN ENGLISHA District Level Analysis of Istanbul’s Population Change (2012-2017)Istanbul having the largest population of Turkey with its 39 districts is the most internal-migrant-receiving city in Turkey. Particularly in the context of rural-to-urban migration, Istanbul has been became a subject of various researches with its socio-economic and demographic features. However, the density of Istanbul’s settled population who registered other cities of Turkey is important. The main aim of this study is to analyse population growth of all districts considering the population change between 2012 and 2017, to evaluate the related factors and to develop a district typology by using the data of settled population according to their family registration in the name of reading the current countryman networks. In the first section of the study, district populations of Istanbul are examined regarding the related five-year change. Afterwards, most repeated countryman networks of all Istanbul’s districts are specified regarding the population growth rate of the registered cities. In the latter section of the study, districts were divided into categories regarding the specific population change features which help to create district typology.

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