Legal and Regulatory Framework for the Agriculture Sector in Uganda

Author(s):  
Emmanuel Kasimbazi
2020 ◽  
pp. 587-611 ◽  
Author(s):  
Elena Viganò ◽  
Federico Gori ◽  
Antonella Amicucci

The central role of quality agri-food production in the promotion of a given territory is actually widely recognized by both the economic and marketing literature and the stakeholders involved in the enhancement process of rural systems. On this basis, this work analyzes one of the finest Italian agri-food products: the truffle. This work tries to point out the main problems characterizing the current regulatory framework, the trade and the production of the Italian truffle sector, emphasizing their causes, consequences and possible solutions.


2019 ◽  
Vol 6 (2) ◽  
pp. 173-190
Author(s):  
Fethiye Tilbe

Bu makale, göçmen dövizi  akımlarında “düzensizlik” olarak ifade ettiğimiz, Türkiye’ye resmi kanallar dışında gönderilen enformel  göçmen dövizlerini, Birleşik Krallık’ta (özellikle Londra’da) yaşayan Türkiye kökenli göçmenler açısından incelemektedir. Her göçmen grubu, gerek ev sahibi ülkedeki düzenleyici çerçeve ve sosyo-ekonomik koşullar, gerek göçmen topluluğunun sosyo-kültürel değerleri tarafından belirlenen biçimde, farklı göçmen dövizi transfer biçimlerine eğilim sergilemektedir. Dolayısıyla farklı ülkelerdeki aynı kökenden göçmen toplulukları, ev sahibi ülkedeki dinamikler nedeniyle göçmen dövizlerinin formel ya da enformel (düzenli ya da düzensiz) gönderiminde farklılaşabilirken, aynı ülkedeki farklı ülke kökenli göçmen grupları da pek çok örüntünün etkisiyle farklı eğilim gösterebilmektedir. Nitel araştırma tasarımı kapsamında 27 göçmen ve 7 anahtar statüdeki katılımcıyla gerçekleştirilen yüz yüze görüşmelere dayalı olan bu çalışma, Birleşik Krallık’tan Türkiye’ye göçmen dövizi gönderimindeki düzensizlik olgusunu, her iki ülkenin sosyal, ekonomik ve kültürel dinamikleriyle ilişkilendirerek incelemeyi ve nedenlerini ortaya çıkarmayı amaç edinmektedir. Elde edilen sonuçlar, göçmenlik statüsü, gönderilen para miktar ve sıklığı ile geleneksel ilişki ağlarına olan güvenin yanında, Birleşik Krallık’taki sosyal yardım ve çalışma biçimine ilişkinin düzenleyici çerçevenin ve göçmenlerin sosyo-ekonomik durumlarının Türkiye’ye enformel göçmen dövizi gönderiminde temel belirleyici olduğunu ortaya koymaktadır.ABSTRACT IN ENGLISHA Qualitative Examination of Determinants of Remittances Sending Behaviour Among Immigrants from Turkey in the UKThis article examines the causes of irregularity in remittances flows from the United Kingdom (UK) to Turkey, from the perspective of migrants from Turkey living in the UK. Each group of migrants prefers different types of remittance sending methods, as determined by the regulatory framework and socio-economic conditions in the host country and the socio-cultural values of the migrant community. Therefore, migrant communities of the same origin in different countries may differ in using formal or informal sending methods of remittances due to the dynamics in the host country. Similarly, migrant groups of different nationalities in the same country may show different tendencies due to the influence of many patterns. Similarly, migrant groups of different nationalities in the same country may show different tendencies due to the influence of many patterns. This study aims to examine the phenomenon of irregularities in sending remittances by associating with the social, economic and cultural dynamics of both countries. For this purpose, face-to-face in-depth interviews were conducted with 27 immigrants and 7 key status participants by using qualitative research method. The obtained results reveal that the regulatory framework relating to social assistance and labour market in the UK, immigration status, the frequency and the amount of money sent and confidence in traditional relationship networks is the main determinants of informal money transfers to Turkey.


Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


Author(s):  
Sujata Mulik

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 


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