GRAZING STUDIES FOR GRASSLAND SHEEP SYSTEMS AT THE HILL FARMING RESEARCH ORGANISATION, U.K.

1984 ◽  
pp. 184-189
Author(s):  
J. Hodgson ◽  
T.J. Maxwell
Keyword(s):  
Perennial Ryegrass ◽  
Management Objectives ◽  
Research Organisation ◽  
Hill Farming ◽  
The Uk ◽  
The Hill

Studies in the UK on continuously stocked swards dominated by perennial ryegrass show that both net herbage production and lamb output per hectare are maximised when herbage mass is maintained at 1200-I 500 kg OM/ha (3-5 cm surface height) during the main season of growth. The use of this information to define sward management objectives is outlined, and the incorporation of these objectives into the spring and summer phases of a grassland sheep enterprise is illustrated

scholarly journals Detection of duplicate and non-face images in the eRecruitment applications using machine learning techniques

2021 ◽  
Vol 10 (2) ◽  
pp. 114
Author(s):  
Manjunath K. E. ◽  
Yogeen S. Honnavar ◽  
Rakesh Pritmani ◽  
Sethuraman K.
Keyword(s):  
Machine Learning ◽  
Detection Algorithm ◽  
Similarity Score ◽  
Machine Learning Techniques ◽  
Human Face ◽  
Face Images ◽  
Research Organisation ◽  
Learning Techniques ◽  
Satellite Centre ◽  
Recruitment Activities

The objective of this work is to develop methodologies to detect, and report the noncompliant images with respect to indian space research organisation (ISRO) recruitment requirements. The recruitment software hosted at U. R. rao satellite centre (URSC) is responsible for handling recruitment activities of ISRO. Large number of online applications are received for each post advertised. In many cases, it is observed that the candidates are uploading either wrong or non-compliant images of the required documents. By non-compliant images, we mean images which do not have faces or there is not enough clarity in the faces present in the images uploaded. In this work, we attempt to address two specific problems namely: 1) To recognise image uploaded to recruitment portal contains a human face or not. This is addressed using a face detection algorithm. 2) To check whether images uploaded by two or more applications are same or not. This is achieved by using machine learning (ML) algorithms to generate similarity score between two images, and then identify the duplicate images. Screening of valid applications becomes very challenging as the verification of such images using a manual process is very time consuming and requires large human efforts. Hence, we propose novel ML techniques to determine duplicate and non-face images in the applications received by the recruitment portal.

INNOVATION COLLABORATIONS IN LOW-TO-MEDIUM TECH SMEs: THE ROLE OF THE FIRM’S INNOVATION ORIENTATION AND USE OF EXTERNAL INFORMATION

2019 ◽  
Vol 23 (02) ◽  
pp. 1950011 ◽  
Author(s):  
OUAFA SAKKA ◽  
JOSÉE ST-PIERRE ◽  
MOUJIB BAHRI
Keyword(s):  
Management Control ◽  
Manufacturing Industries ◽  
External Information ◽  
Marketing Innovation ◽  
Research Organisation ◽  
Research Organisations ◽  
Medium Enterprises ◽  
Successful Innovation ◽  
The Relationship

This study articulates and tests the direct and indirect relationships between the company’s innovation orientation (IO), its collection and dissemination (C&D) of external information among the organisational members, and the level of success of its innovation collaborations involving customers, suppliers, and research organisations. Our conceptual framework is developed based on an integration of the literatures on organisational capabilities, marketing, innovation, and management control. We empirically test these relationships on a sample of 117 small-to-medium enterprises (SME) operating in Low-to-Medium-Tech (LMT) manufacturing industries. Partial Least Squares (PLS) results reveal that the relationship between the firm’s IO and the success of its customer collaborations is partially mediated by the C&D of external information. We also find that the relationship between the firm’s IO and the success of supplier collaborations is direct, and that the C&D of external information has no effect on the success of such collaborations. Finally the relationship between IO, C&D of external information and the success of research organisation collaborations is found to be indirect. Overall, these findings suggest that developing successful innovation collaborations in LMT sectors requires that SME managers start by building an internal culture that promotes innovation, learning and openness to the external environment.

CSIRO and land research in Papua New Guinea 1950–2000: part 2: post-Independence

2019 ◽  
Vol 30 (2) ◽  
pp. 100
Author(s):  
Gael Keig ◽  
Robin L. Hide ◽  
Susan M. Cuddy ◽  
Heinz Buettikofer ◽  
Jennifer A. Bellamy ◽  
...  
Keyword(s):  
Papua New Guinea ◽  
Collaborative Research ◽  
National Level ◽  
Historical Review ◽  
New Guinea ◽  
Research Projects ◽  
Resource Information ◽  
Research Organisation ◽  
Scientific Disciplines ◽  
Computer Based

Following Papua New Guinea (PNG) Independence in 1975, the new administration approached Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO) directly concerning the need to address issues related to food security and village-based agriculture. A subsequent series of collaborative research projects between CSIRO and PNG government departments built upon the existing survey information to provide PNG with one of the earliest national-level, computer-based resource information systems, with widespread applications, particularly in agriculture, forestry, environmental management and planning. Part 1 of this historical review discussed the evolution, conduct and outcomes of the CSIRO integrated surveys over the period 1950–75, while Part 2 describes the subsequent research projects that arose from the surveys and concluded in 2000. In addition, the legacy of CSIRO involvement in land research in PNG is examined in relation to advances made both within individual scientific disciplines and in other relevant technological fields, and to operational challenges and structural change within the organisation.

Estimated halothane gene frequency in eight British pig breeding companies

1986 ◽  
Vol 1986 ◽  
pp. 25-25
Author(s):  
O.I. Southwood ◽  
M.K. Curran ◽  
S.P. Simpson ◽  
A.J. Webb
Keyword(s):  
Gene Frequency ◽  
Animal Breeding ◽  
Large White ◽  
Lean Growth ◽  
Research Organisation ◽  
Breeding Research ◽  
Foundation Stock ◽  
Joint Experiment ◽  
Wye College

Eight breeding companies contributed foundation stock for a joint experiment on lean growth at the Animal Breeding Research Organisation (ABRO) and Wye College. All animals were test-mated to halothane positive (HP) reactors and incidences of HP reaction among progeny were used to estimate the frequency of the halothane gene (n) in the original herds. Estimated incidences of HP were compared with those observed in an earlier 1979 survey.260 British Landrace (LR) were test-mated to HP (expected nn) LR at Wye, and 186 Large White (LW), including 18 boars standing at national AI centres, were test-mated to HP LR, Pietrain-Hampshire or LR x (LW x Norwegian Landrace) at ABRO.Offspring were given a 4-minute halothane test at an average age of 50 days in LW and 76 days in LR. Numbers tested and incidences of reaction are shown in Table 1. Herds are coded ‘A’ to ‘I’ for anonymity. Purebred LR in herds A, C, D, E, H and I were halothane testec in advance and only halothane negatives (HN) were supplied for test-mating.

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