Research on Agricultural Products Logistics Operational Pattern Based on Advanced IT Technology

Agriculture is the founding principle for a country which has great significance with national interest and people's livelihood. Some logistics links are stumble on information dissemination and high cost which are also the key factors that restrict agriculture logistics development. Based on the comprehensively summarizing of logistics theories both at home and abroad, the paper analyzes the current condition of logistics and finds the problems, such as the low level of information sharing, cumbersome process, expensive cost, low efficiency and less sensitive reaction to market. Through the investigation of Third-Part Logistics (TPL), the paper proposes the agriculture service model with Advanced IT tech upon TPL. In the end, through analysis and evaluation on the model, the paper concludes its advantages, like perfect service functions, strategic alliance with customers, altogether shedding risks, big profit margins, and high level information sharing.

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OPTIMIZATION OF DISPERSANT APPLICATION, ESPECIALLY BY SHIP

International Oil Spill Conference Proceedings ◽

10.7901/2169-3358-1989-1-337 ◽

1989 ◽

Vol 1989 (1) ◽

pp. 337-342

Author(s):

François Merlin ◽

Christian Bocard ◽

Gilles Castaing

Keyword(s):

Flow Rate ◽

Laboratory Tests ◽

State Of The Art ◽

Sea Surface ◽

Key Factors ◽

Treatment Procedure ◽

Low Efficiency ◽

High Level ◽

Meso Scale ◽

Oil Thickness

ABSTRACT A lot of information has been made available for 10 years on the use of dispersants through offshore and meso-scale trials. A state-of-the-art review shows that among the key factors that have been identified, the contact between dispersant and oil is of utmost importance. A better knowledge of this parameter should be taken into account in defining operational procedures, especially when applying dispersants by ship, which is considered to be complementary to aerial spraying. Upon request of the French Navy, a series of meso-scale trials was carried out off Brittany in June 1987, according to the methodology previously used in 1984. Three dispersants were sprayed from a boat. It was concluded that a high level of energy at the sea surface mitigates discrepancies in dispersants’ efficiencies as measured in laboratory tests. Better results were obtained in the case of relatively thick oil slicks. The low efficiency that was measured when treating downwind was attributed to the already-observed herding effect. These complementary results reinforce the actions that have been recently developed to optimize dispersant application by ship:Shipboard equipment for neat dispersant spraying is described. Its main feature is an original nozzle assembly that allows the dispersant to be applied effectively onto the oil at a flow rate that can be widely and very quickly changed according to the estimated oil thickness.An operational treatment procedure is discussed, showing how to map, mark out, prospect and treat oil slicks according to the slick shape, estimated oil thickness, and wind direction.

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Data Reduction in the String Space for Efficient kNN Classification Through Space Partitioning

Applied Sciences ◽

10.3390/app10103356 ◽

2020 ◽

Vol 10 (10) ◽

pp. 3356 ◽

Cited By ~ 1

Author(s):

Jose J. Valero-Mas ◽

Francisco J. Castellanos

Keyword(s):

Data Reduction ◽

Structural Data ◽

Data Representation ◽

Space Partitioning ◽

Classification Rate ◽

Symbolic Data ◽

Knn Classifier ◽

Initial Dataset ◽

Low Efficiency ◽

High Level

Within the Pattern Recognition field, two representations are generally considered for encoding the data: statistical codifications, which describe elements as feature vectors, and structural representations, which encode elements as high-level symbolic data structures such as strings, trees or graphs. While the vast majority of classifiers are capable of addressing statistical spaces, only some particular methods are suitable for structural representations. The kNN classifier constitutes one of the scarce examples of algorithms capable of tackling both statistical and structural spaces. This method is based on the computation of the dissimilarity between all the samples of the set, which is the main reason for its high versatility, but in turn, for its low efficiency as well. Prototype Generation is one of the possibilities for palliating this issue. These mechanisms generate a reduced version of the initial dataset by performing data transformation and aggregation processes on the initial collection. Nevertheless, these generation processes are quite dependent on the data representation considered, being not generally well defined for structural data. In this work we present the adaptation of the generation-based reduction algorithm Reduction through Homogeneous Clusters to the case of string data. This algorithm performs the reduction by partitioning the space into class-homogeneous clusters for then generating a representative prototype as the median value of each group. Thus, the main issue to tackle is the retrieval of the median element of a set of strings. Our comprehensive experimentation comparatively assesses the performance of this algorithm in both the statistical and the string-based spaces. Results prove the relevance of our approach by showing a competitive compromise between classification rate and data reduction.

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Inference of Mood State Indices by Using a Multimodal High-Level Information Fusion Technique

IEEE Access ◽

10.1109/access.2021.3073733 ◽

2021 ◽

pp. 1-1

Author(s):

Chih-Hua Tai ◽

Kuo-Hsuan Chung ◽

Ya-Wen Teng ◽

Feng-Ming Shu ◽

Yue-Shan Chang

Keyword(s):

Information Fusion ◽

Mood State ◽

Fusion Technique ◽

Level Information ◽

Information Fusion Technique ◽

High Level

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Re-constructing high-level information for language-specific binary re-optimization

Proceedings of the 2016 International Symposium on Code Generation and Optimization - CGO 2016 ◽

10.1145/2854038.2854057 ◽

2016 ◽

Cited By ~ 1

Author(s):

Toshihiko Koju ◽

Reid Copeland ◽

Motohiro Kawahito ◽

Moriyoshi Ohara

Keyword(s):

Level Information ◽

High Level

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On priority development of knowledge economy

Economic Revival of Russia ◽

10.37930/1990-9780-2021-1-67-15-22 ◽

2021 ◽

pp. 15-22

Author(s):

A.G. Aganbegyan ◽

Keyword(s):

Mortality Rate ◽

Knowledge Economy ◽

Federal Budget ◽

The Public ◽

National Economic ◽

Working Age ◽

Low Efficiency ◽

Child Mortality Rate ◽

Main Component ◽

High Level

A.G. Aganbegyan considers the knowledge economy as the main component of human capital. He analyzes certain areas of the knowledge economy (R&D, healthcare and education) by comparing relevant results demonstrated by Russian regions with similar indices reported for other countries. The article points out positive and negative aspects, e.g. high level and quality of education v. low efficiency of its application; lower cancer mortality rate and particularly child mortality rate v. high mortality from cardiovascular disease among working-age population, etc. Major causes of negative phenomena include insufficient funding of the public sector and inefficient administration. In order to remedy the situation, the author recommends the development of a new federal budget, transition to national economic planning and adjustment of national projects.

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Development of decree 1072 of 2015, as a regulatory factor of practices in the construction field for the prevention of workplace accidents with MHF Construark SAS, carried out during the year 2020 in Bogotá

Ingeniería solidaria ◽

10.16925/2357-6014.2021.02.11 ◽

2021 ◽

Vol 17 (2) ◽

pp. 1-27

Author(s):

Daniel Tabares

Keyword(s):

Regulatory Factor ◽

Key Factors ◽

Improvement Strategy ◽

Implementation Processes ◽

Workplace Accidents ◽

Determining Factors ◽

Administrative Area ◽

Implementation Level ◽

High Level

Introduction: This article "Development of the decree 1072 of 2015, as a regulatory factor of practices in the construction field for the prevention of workplace accidents in MHF Construark SAS" company was executed during 2020 in Bogotá. Background: There has been recurring practices in the construction sector that generate difficulties in the implementation of the SGSST, which may be the main cause of this insufficient implementation, which can lead to workplace accidents and occupational diseases. Objective: The objective of the investigation is to establish the level of compliance in the implementation of the SGSST, in order to identify determining factors that negatively affect such a process. Methods: This research has designed a study with mainly, a qualitative approach. Interviews were conducted with company representatives from the administrative area in charge of implementing the SGSST. Results: The MHF Company has achieved an implementation level of 85%. It is at a high level. Conclusion: This project contributes to the research in terms of the study of SGSST in particular, from a perspective that inquiries factors related to the role of key factors such as senior management and construction personnel. Originality: A small business of the construction field is investigated, setting up human factors in the SGSST implementation processes and the improvement strategy Limitations: information gathering on site was affected due to the circumstances generated by the COVID-19 emergency due to the fact the construction field was forced to suspend work as consequence of the pandemic

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