scholarly journals Study on the Integration of Collaborative Innovation and Professional Qualities of Cultivation System for Computer Engineer Application-Type Graduates

2017 ◽  
Vol 07 (02) ◽  
pp. 100-106
Author(s):  
继国 禹
Keyword(s):  
Cultivation System ◽  
Collaborative Innovation ◽  
Engineer Application

Organic Farming System for Producing Healthy Rice Oleh

2018 ◽  
Vol 9 (04) ◽  
pp. 20213-20217
Author(s):  
Dr. Ir. Ni.Gst.Ag.Gde Eka Martiningsih ◽  
Dr.Ir. I Putu Sujana, MS
Keyword(s):  
Elementary Education ◽  
Dry Weight ◽  
Farming System ◽  
Rice Cultivation ◽  
Cultivation System ◽  
Organic Rice ◽  
Organic Cultivation ◽  
A Value ◽  
Cultivation Technology ◽  
Organic Farming System

Introduction of organic rice-based rice cultivation technology package through demplot is done in Subak Sungi 1 using ciherang variety. The number of farmers participating in demonstration plots in organic cultivation of paddy-based rice cultivation were 5 people, with age of farmers aged greater than 55 years occupying the highest percentage (45.45%), with elementary education level (72.75%), followed by high school education (18.25%), and junior high (9%). The average farmland area is 34.63 acres, with self-owned status (55,94%), status as penyakap 41,18% and rent status 2,88%. The farmers' response to the organic rice-based rice planting assessment is quite high, as evidenced by the evaluation that 100% of farmers participating in demonstration plots know and understand about organic rice system cultivation, and they agree to develop this cultivation system in the future. Demplot research results can increase the yield components and weight of dry grain harvest per hectare. Organic rice-based rice cultivation technology EVAGRO able to increase production of dry grain harvest significantly with a value of 6.8 tons / ha. There is a tendency of dry weight value of ciherang varieties of 6.8 tons / ha giving highest but not significantly different with PGPR organic based technology.

Double Line Clustering based Colour Image Segmentation Technique for Plant Disease Detection

2019 ◽  
Vol 15 (8) ◽  
pp. 769-776
Author(s):  
Kalaivani Subramani ◽  
Shantharajah Periyasamy ◽  
Padma Theagarajan
Keyword(s):  
Pattern Matching ◽  
Error Rate ◽  
Median Filter ◽  
Identification System ◽  
Double Line ◽  
Cultivation System ◽  
Matching Algorithm ◽  
Non Local ◽  
Mining Methods ◽  
Blight Disease

Background: Agriculture is one of the most essential industry that fullfills people’s need and also plays an important role in economic evolution of the nation. However, there is a gap between the agriculture sector and the technological industry and the agriculture plants are mostly affected by diseases, such as the bacterial, fungus and viral diseases that lead to loss in crop yield. The affected parts of the plants need to be identified at the beginning stage to eliminate the huge loss in productivity. Methods: In the present scenario, crop cultivation system depend on the farmers experience and the man power, but it consumes more time and increases error rate. To overcome this issue, the proposed system introduces the Double Line Clustering technique based disease identification system using the image processing and data mining methods. The introduced method analyze the Anthracnose, blight disease in grapes, tomato and cucumber. The leaf images are captured and the noise has been removed by non-local median filter and the segmentation is done by double line clustering method. The segmented part compared with diseased leaf using pattern matching algorithm. Methods: In the present scenario, crop cultivation system depend on the farmers experience and the man power, but it consumes more time and increases error rate. To overcome this issue, the proposed system introduces the Double Line Clustering technique based disease identification system using the image processing and data mining methods. The introduced method analyze the Anthracnose, blight disease in grapes, tomato and cucumber. The leaf images are captured and the noise has been removed by non-local median filter and the segmentation is done by double line clustering method. The segmented part compared with diseased leaf using pattern matching algorithm. Conclusion: The result of the clustering algorithm achieved high accuracy, sensitivity, and specificity. The feature extraction is applied after the clustering process which produces minimum error rate.

Collaborating for Innovation

2019 ◽  
pp. 586-609
Author(s):  
Peter G. Klein ◽  
Mark D. Packard ◽  
Karen Schnatterly
Keyword(s):  
Organizational Structure ◽  
Organizational Design ◽  
Resource Constraints ◽  
Spillover Effects ◽  
Employee Motivation ◽  
Corporate Entrepreneurship ◽  
Marketplace Of Ideas ◽  
Collaborative Innovation ◽  
Barriers To Collaboration ◽  
Innovation Outcomes

This chapter looks inside the firm at how organizational design affects collaboration in pursuit of corporate entrepreneurship or “intrapreneurship.” It shows how the intrafirm “marketplace” of ideas, employees, and resources can be strategically configured to encourage or inhibit collaborative innovation. The chapter focuses on the key structural dimensions of autonomy, sponsorship, and incentives. Complementarities between these dimensions create spillover effects that produce unique innovation outcomes by mitigating barriers to collaboration such as knowledge problems, resource constraints, and employee motivation. Illustrating configurations of these dimensions with company examples, the chapter shows how organizational design affects intrapreneurship and offers suggestions on how firms might strategically align their organizational structure with their intrapreneurial strategy.

scholarly journals Collaborative innovation in healthcare: a case study of hospitals as innovation platforms

2020 ◽  
Vol 11 (1) ◽  
pp. 24
Author(s):  
Pauliina Hyrkäs ◽  
Lotta Haukipuro ◽  
Satu Väinämö ◽  
Marika Iivari ◽  
Anna Sachinopoulou ◽  
...  
Keyword(s):  
Collaborative Innovation
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