Less intra-row weeds – experiences with a punch planter and a cycloid hoe based on GPS

Experiences with a punch planter and an intelligent rotary tine weeder are summarized. The objectives were to investigate (1) to what extent punch planting and pre-emergence flame weeding can reduce intra-row weed emergence in direct sown crops like onion, carrot and sugar beet, (2) to what extent an intelligent intra-row weeder, a cycloid hoe based on RTK-GPS technology, can control intra-row weeds without damaging the crop in direct sown crops, (3) and to what extent there exists synergy between punch planting with pre-emergence flame weeding and mechanical intra-row weeding

BUFFER STOCK MODEL FOR STABILIZING PRICE WITH CONSIDERING THE EXPECTATION STAKEHOLDERS IN THE STAPLE-FOOD DISTRIBUTION SYSTEM

The extremely different supplies between the harvest season and the planting season are one of serious problem in the staple-food distribution system. In free-market mechanism, this extreme difference will trigger price-volatility and shortage of staple-food. This situation causes opportunity-losses for the stakeholders (producer, consumer, agent and government) in the staple-food distribution system. The government has got incurred losses because the government cannot achieve food-security for the households. The government has several price stabilization policies; one of them is market intervention policy by using buffer stock schemes to stabilize price and to reduce losses for the stakeholders. The objective of this research is to determine the buffer stock schemes required for market-intervention program. In the previous researches, the buffer stock models have been developed separately based on optimization and econometrics methods. Optimizations methods have been used to determine the level of availability with schemes consist of time and quantity of buffer stock. Econometrics methods have been used to determine the equilibrium price by using the selling-price and the amount of buffer stock. In this research, the integration of optimization model (multi-objectives programming) and econometrics model are used to develop a buffer stock model with the decision variables that consist of quantity, time, and price. Key Words: Buffer Stock Model, Market-Intervention, Price-Stabilizatio

Prevention and control of weeds, pests and diseases

Weed control still requires major investments of money and labour in organic arable farming and field vegetable cultivation. For this reason, current research is focused to a large extent on the development of weed control strategies. These incorporate prevention as well as mechanical methods, and cover a range of approaches. From inexpensive techniques to very innovative technologies. Research into pests and diseases primarily focuses on improving systems and preventing infestation. However, even with maximum prevention measures some pests and diseases still cause unacceptable damage. For these residual problems control measures are being develope

Design of Smart Agricultural Monitoring and Management System

One of the important contents of China’s agricultural construction is vegetable planting, and most of the vegetable planting technology is relatively backward. The commonly used greenhouse planting technology is simply using special mechanical planting management methods, which cannot realize real-time monitoring of crop growth. In order to optimize the crop growth environment and improve the yield, a smart agricultural monitoring and management system based on PLC and MCGS configuration technology is designed. The system combines PLC technology, configuration technology and sensor technology to complete the overall structure design of the control system, and separately explains the hardware design, software design and operation and debugging of the system. The experimental results show that the system can remotely monitor and control the growing environment of crops, such as soil moisture, gas temperature and humidity, light intensity and other parameters, and the operation and maintenance are convenient, which provides a reference method for the intelligent development of agriculture

Planting and harvesting innovation - an analysis of Samsung Electronics

This study explores how firms manage the entire life cycle of innovation projects based on the framework of harvesting and planting innovation. While harvesting innovation seeks new products in the expectation of financial performance in the short term, planting innovation pursues creating value over a long time period. Without proper management of the process of planting and harvesting innovation, firms with limited resources may not be successful in launching innovative new products to seize a momentum in high tech industries. To examine this issue, the case of Samsung Electronics (SE), now an electronics giant originated from a former developing country, is analyzed. SE has shown to effectively utilize co-innovation to maintain numerous planting and harvesting innovation projects. Both researchers and practitioners would be interested in learning about how SE shared risks of innovation investment with external partners at the early stage of innovation cycles

Partnerships for Scaling Climate-Smart Agriculture (P4S) Phase II: 2019 annual report

First annual report of P4

EviPlant: An efficient digital forensic challenge creation, manipulation and distribution solution

Education and training in digital forensics requires a variety of suitable challenge corpora containing realistic features including regular wear-and-tear, background noise, and the actual digital traces to be discovered during investigation. Typically, the creation of these challenges requires overly arduous effort on the part of the educator to ensure their viability. Once created, the challenge image needs to be stored and distributed to a class for practical training. This storage and distribution step requires significant time and resources and may not even be possible in an online/distance learning scenario due to the data sizes involved. As part of this paper, we introduce a more capable methodology and system as an alternative to current approaches. EviPlant is a system designed for the efficient creation, manipulation, storage and distribution of challenges for digital forensics education and training. The system relies on the initial distribution of base disk images, i.e., images containing solely base operating systems. In order to create challenges for students, educators can boot the base system, emulate the desired activity and perform a "diffing" of resultant image and the base image. This diffing process extracts the modified artefacts and associated metadata and stores them in an "evidence package". Evidence packages can be created for different personae, different wear-and-tear, different emulated crimes, etc., and multiple evidence packages can be distributed to students and integrated into the base images. A number of additional applications in digital forensic challenge creation for tool testing and validation, proficiency testing, and malware analysis are also discussed as a result of using EviPlant.Comment: Digital Forensic Research Workshop Europe 201

Aerospace Medicine and Biology: a Continuing Bibliography with Indexes (Supplement 328)

This bibliography lists 104 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Soft set theory based decision support system for mining electronic government dataset

Electronic government (e-gov) is applied to support performance and create more efficient and effective public services. Grouping data in soft-set theory can be considered as a decision-making technique for determining the maturity level of e-government use. So far, the uncertainty of the data obtained through the questionnaire has not been maximally used as an appropriate reference for the government in determining the direction of future e-gov development policy. This study presents the maximum attribute relative (MAR) based on soft set theory to classify attribute options. The results show that facilitation conditions (FC) are the highest variable in influencing people to use e-government, followed by performance expectancy (PE) and system quality (SQ). The results provide useful information for decision makers to make policies about their citizens and potentially provide recommendations on how to design and develop e-government systems in improving public services