Soil carbon sequestration of organic crop and livestock systems and potential for accreditation by carbon markets

During a two-day RTOACC workshop hosted by the Research Institute of Organic Agriculture (FiBL), participants discussed the potential for organic agriculture in carbon markets and the need to develop strategies for the role of organic agriculture in climate policy. To move in this direction requires quantifying and raising recognition of the mitigation potential of organic agriculture. Thus the participants also looked at available data and began a process of identifying data gaps. In doing so, they presented the related ongoing work of their organizations and drew conclusions for the further orientation and actions of the RTOACC. The following synthesizes the discussions, reports and outcomes of the workshop

Application of Data Mining Technique in Stock Market : An Analysis

Stock market prediction with data mining technique is one of the most important issues to be investigated and it is one of the fascinating issues of stock market research over the past decade. Many attempts have been made to predict stock market data using statistical and traditional methods, but these methods are no longer adequate for analyzing this huge amount of data. Data mining is one of most important powerful information technology tool in today’s competitive business world, it is able to uncover hidden patterns and predict future trends and behavior in stock market. This paper also highlights the application of association rule in stock market and their future movement direction

Occupational Accidents and need for worker safety in manufacturing and high Risk Industries – An Explorative Study with solutions

Abstract: OAs (Occupational accidents) have been responsible for fatalities and injuries in both industrialised and developing nations. Due to weak documentation and notification systems, where developing countries in particular lack reliable information on OAs, there are no worldwide standards for information on OAs. Baseline OSMs (occupational safety measures) statistics are still used in workplaces for improving worker safety notwithstanding the underreporting of accident data. 2.78 million Workers every year are estimated to pass away from OAs and other associated conditions, while another 374 million have non-fatal OAs, according to estimates from the ILO (International Labour Organization). Additionally, because manufacturing sectors are dealing with greater OAs, it is necessary to confirm links between safety performances in order to maximise productivity.   Purpose: The purpose of this research was to explore the effects of workplace safety s of assembly workers in manufacturing facilities.   Theoretical framework: According to studies, industries can enhance their safety cultures by focusing on five key areas: management commitment, communication, safety priority, supportive environment, and involvement. These areas in turn improve employee and equipment performance, as well as safety performance as measured by safety performance reports.    Design/methodology/approach: The suggested workplace safety for this job was tested in assembly sites and put into practise. While secondary data was gathered from material found in publications, books, journals, and the internet, primary data came through questionnaires provided to management and personnel. The safety cultures of firms that did not participate in any lean events during the same time period were compared to control groups.   Validity: To gauge Security Environment in the assembling enterprises in Tamilnadu, a changed rendition of the poll utilized by Corridor (2013) was utilized. This survey was chosen in light of the fact that at first, the instrument utilized by Corridor (2013) filled in as a kind of perspective. The said instrument contained 27 things. The main limit of the first estimating instrument is that the association's whose working environment wellbeing is estimated utilizing the instrument should have a comparative workplace and hierarchical construction as the steel processes that were utilized to approve the first instrument. This need was met by the associations picked for the ongoing review. Inward consistency was utilized to pass judgment on the nature of the estimating instrument, as exhorted by Cooper et al (1998)   Findings:  P values less than 0.05 were found for the four individual dimension scores—Management Commitment, Priority of Safety, Involvement, and Work Environment—and the overall score, indicating that the proposed framework improved workplace safety-related metrics after adoption. The improvement in the mean total scores for both groups shows that the suggested framework can increase workplace safety. Additionally, rotation times were shortened by 16.6%, space was used up by 22.2%, and stocks were cut by 25% throughout testing. Due to these enhancements, the overall level of workplace safety was greatly raised along with favourable changes in these four dimensions.    Practical and social implications: However, it seems important to draw attention to the ongoing effects of the accident phenomenon on social and health systems, as well as how the development of the economic system has brought about some risk factors that can be addressed through different work practises, increased organisational well-being, and a widespread introduction of corporate welfare tools, in addition to increased controls. The introduction of hazardous work instruments and the absence of controls in particular industries are only two factors contributing to the accident statistics; high workloads are also a frequent factor, the lengthening of workdays and a "culture of performance" and productivity that, even if they do not result in an accident, raise risk margins and, thus, exacerbate the state of "work-related stress." The suggested methodology provides businesses with verified tools and specialised resources that may be applied by businesses using a sustainable and integrated approach. The recommended technique is broken down into steps that engage both workers and prevention experts. The danger of work-related stress is taken into consideration while evaluating the recognised allowances, which merely reflect the most obvious and emerging facet of a much larger issue

Using Text Mining to Predicate Exchange Rates with Sentiment Indicators

Recent innovations in text mining facilitate the use of novel data for sentiment analysis related to financial markets, and promise new approaches to the field of behavioral finance. Traditionally, text mining has allowed a near-real time analysis of available news feeds. The recent dissemination of web 2.0 has seen a drastic increase of user participation, providing comments on websites, social networks and blogs, creating a novel source of rich and personal sentiment data potentially of value to behavioral finance. This study explores the efficacy of using novel sentiment indicators from Market Psych, which analyses social media in addition to newsfeeds to quantify various levels of individual’s emotions, as a predictor for financial time series returns of the Australian Dollar (AUD)-US Dollar (USD) exchange rate. As one of the first studies evaluating both news and social media sentiment indicators as explanatory variables for linear and nonlinear regression algorithms, our study aims to make an original contribution to behavioral finance, combining technical and behavioral aspects of model building. An empirical out-of-sample evaluation with multiple input structures compares Multivariate Linear Regression models (MLR) with multilayer perceptron (MLP) neural networks for descriptive modelling. The results indicate that sentiment indicators are explanatory for market movements of exchange rate returns, with nonlinear MLPs showing superior accuracy over linear regression models with a directional out-of-sample accuracy of 60.26% using cross validation

How Mood Affects The Stock Market: Empirical Evidence From Chinese Microblog

With the advent of the Web2.0 era, social media can achieve the rapid transmission of information and reduce the information asymmetry. In our study, we selected social media of Sina Weibo because of its wide use in China. Through text mining technology, this paper we extracted total 22504 tweets related to real estate industry. We succeeded in classify microblog accounts and two clusters of social media users are selected: individual investors and official media. Based on two dimensions of attention and emotion, this paper discusses the influence of different users on the stock market. Interestingly, the empirical results show that (1) there is an inverse U-shaped curve between attention and stock return for both official media and investor which support the over-attention underperformance hypothesis. (2) We also find that both daily sentiment of official media and investor are positively correlated to stock return. Our study contributes to a better understanding of emotion and stock market, particularly based on Chinese microblog

Organic agriculture and climate change mitigation - A report of the Round Table on Organic Agriculture and Climate Change

Summary and next steps Participants of the workshop were able to draw from their discussions and from the input of guest speakers and synthesize a set of conclusions that can be used to guide future activities concerning LCAs and other activities that seek to identify and quantify the potential contributions of organic agriculture to climate change mitigation. - LCA is the best tool for measuring GHG emissions related to agricultural products. - There is a risk of oversimplification when focusing on climate change as a single environmental impact category. - Farm production and transport (at least for plant products) are important hotspots for agricultural products. - Studies have shown no remarkable difference in GHG emissions between organic and conventional but, traditionally, soil carbon changes have not been included – which can have a major impact, especially for plant products. - The challenges of LCA of organic products – accounting for carbon sequestration and interactions in farming systems, including the environmental costs of manure – need to be addressed. - Attempts should be made to secure a consistent LCA methodology for agricultural products, including organic products

Tutoring Students with Adaptive Strategies

Adaptive learning is a crucial part in intelligent tutoring systems. It provides students with appropriate tutoring interventions, based on students’ characteristics, status, and other related features, in order to optimize their learning outcomes. It is required to determine students’ knowledge level or learning progress, based on which it then uses proper techniques to choose the optimal interventions. In this dissertation work, I focus on these aspects related to the process in adaptive learning: student modeling, k-armed bandits, and contextual bandits. Student modeling. The main objective of student modeling is to develop cognitive models of students, including modeling content skills and knowledge about learning. In this work, we investigate the effect of prerequisite skill in predicting students’ knowledge in post skills, and we make use of the prerequisite performance in different student models. As a result, this makes them superior to traditional models. K-armed bandits. We apply k-armed bandit algorithms to personalize interventions for students, to optimize their learning outcomes. Due to the lack of diverse interventions and small difference of intervention effectiveness in educational experiments, we also propose a simple selection strategy, and compare it with several k-armed bandit algorithms. Contextual bandits. In contextual bandit problem, additional side information, also called context, can be used to determine which action to select. First, we construct a feature evaluation mechanism, which determines which feature to be combined with bandits. Second, we propose a new decision tree algorithm, which is capable of detecting aptitude treatment effect for students. Third, with combined bandits with the decision tree, we apply the contextual bandits to make personalization in two different types of data, simulated data and real experimental data

A model for innovation leadership in South African companies

The problem: Ideally, the underpinning principles and processes that innovation leaders practise in South African companies are well-established. In reality, however, the extent to which principles and processes are known and adapted to innovation leadership in the South African means and social context was found to be limited. Without this locally developed understanding, the processes and underpinning principles for leading innovation remains a “black box”, perpetuating innovation leaders’ struggle to advocate and execute innovation initiatives. The method: Guided by the means and social context concepts identified by previous academic studies, this research questioned how successful innovation leaders in existing South African companies use the means of technology, market requirements and external resources. How these above means were integrated through processes of learning by experimentation from within their company’s social context. How from within the company’s social context the innovation leaders organised and planned innovation activities, selected and managed innovation team members, and maintained a positive working relationship between ongoing operations and innovation activities. These concepts informed the development of a conceptual framework and questions that were used to gather primary data during semi-structured interviews with South African innovation leaders using a multiple case study method. For this purpose, successfully commercialised innovations were identified, and the innovation leaders directly involved in these projects were interviewed to gather the primary data. The findings: The research explains how South African innovation leaders were able to integrate their means and social contexts, cognitive abilities and supportive behaviour of their company to successfully develop innovation projects. The resulting model for innovation leadership in South Africa modified the existing First World model by describing and expanding the underpinning principles and internal/external learning processes that innovation leaders used to successfully commercialise innovations in the South African emerging socio-economic context. Key terms: Innovation leader, innovation leadership model, innovation execution principles, organisational structure for innovation, planning for innovation, innovation team, innovation experiments, positive relationship between ongoing operations and innovation initiatives, internal and external processes for innovation, corporate entrepreneurship, technology, market requirements and external resource networks.Business ManagementD.B.L