The Political Economy of Pro-Poor Livestock Policymaking in Vietnam

This paper presents a case study of how livestock policies are made and implemented in a national context, and how they can be improved to better serve the interests of the poor. Livestock is a sector with a great potential for growth compared to other sectors in agriculture. However, appropriate policies and institutions that allow the poor to tap this growth potential may not exist or may be inadequate. In some cases, existing policies may actually hinder the poor from doing so. The study used the key informant method supplemented with official documents, newspaper sources and recently published research on the livestock sector. Interviews helped reveal policymakers' concerns, whereas field trips allowed the researcher to talk to a few peasants and learn their perspectives from the bottom. Newspapers contained many lively stories of how well-intentioned policies went awry at the implementation stage, while published research analyzed various political, institutional and technical aspects of policymaking in the sector. The author concludes that despite economic reform policymaking and implementation is still hindered by a political ambivalence about rural development in general. This results in a restrictive land policy that inhibits the potential of rural producers while restricting the growth of off-farm employment opportunities that may benefit the poor. Despite official rhetoric that calls for increased assistance to the poor, policies lack effective mechanisms to realize their participation in productive activities. Four strategic entry points are recommended that can both improve the performance of the sector and the participation of the poor in productive activities. With sufficient resources to back up programs and efforts to identify political allies for the cause, it may be possible to make livestock policies better serve the interests of the poor.Vietnam, policymaking, livestock, rural development, poverty, Political Economy,

The Political Economy of Avian Influenza Response and Control in Vietnam

As a country suffering from large-scale AI outbreaks and receiving considerable international support, Vietnam provides a crucial case not to be missed in any analysis of the global AI crisis. Vietnam is also interesting because of two paradoxes in her response to AI. Despite being poor, Vietnam selected the most expensive approach (comprehensive vaccination) to disease control. Despite substantial foreign aid and praise lavished on Vietnam, and despite a tough strategy, Vietnam has not performed better than neighbouring countries in keeping the epidemic from coming back. Based on interviews of various stakeholders and newspaper sources since 2003, this paper analyses the timeline of major events, key narratives driving the debate, and the main actor networks in the policy process. I found Vietnam’s AI policy process was characterised by top down/technical perspectives supported by the central government and foreign donors. These narratives reinforced the political interests of a national/international elite. This powerful nexus pushed a particular approach that involved mass culling and comprehensive vaccination, and projected a narrative of success to the nation and the world. The main lesson from Vietnam is the need to bring accountability back to aid collaboration. Vietnam’s case suggests that many mistakes such as excessive culling and wasteful vaccination could have been avoided had accountability been given a higher priority by donors.ESR

Modelling the effect of individual differences in punishment sensitivity on behaviour in a public goods game

Previous research on social dilemmas demonstrated that various forms of punishment for free-riding can increase contribution levels in public goods games. The way individual group members react to the possibility of punishment can be also affected by individual differences in punishment sensitivity. Therefore, depending individual differences in punishment sensitivity of group members, different levels of punishment can be more or less effective to prevent free riding behaviour. This paper uses agent-based modelling to model the effect of punishment sensitivity on contribution levels in a public goods game. The paper then examines the correlation between punishment sensitivity and variability of free riding behaviour under different punishment conditions

AUTOMATIC PAPER SLICEFORM DESIGN FROM 3D SOLID MODELS

Master'sMASTER OF SCIENC

A software engineering approach for agent-based modelling and simulation of public goods games

In Agent-based Modelling and Simulation (ABMS), a system is modelled as a collection of agents, which are autonomous decision-making units with diverse characteristics. The interaction of the individual behaviours of the agents results in the global behaviour of the system. Because ABMS offers a methodology to create an artificial society in which actors with their behaviour can be designed and results of their interaction can be observed, it has gained attention in social sciences such as Economics, Ecology, Social Psychology, and Sociology. In Economics, ABMS has been used to model many strategic situations. One of the popular strategic situations is the Public Goods Game (PGG). In the PGG, participants secretly choose how many of their private money units to put into a public pot. Social scientists can conduct laboratory experiments of PGGs to study human behaviours in strategic situations. Research findings from these laboratory studies have inspired studies using computational agents and vice versa. However, there is a lack of guidelines regarding the detailed development process and the modelling of agent behaviour for agent-based models of PGGs. We believe that this has contributed to ABMS of PGG not having been used to its full potential. This thesis aims to leverage the potential of ABMS of PGG, focusing on the development methodology of ABMS and the modelling of agent behaviour. We construct a development framework with incorporated software engineering techniques, then tailored it to ABMS of PGG. The framework uses the Unified Modelling Language (UML) as a standard specification language, and includes a simulation development lifecycle, a step-by-step development guideline, and a short guide for modelling agent behaviour with statecharts. It utilizes software engineering methods to provide a structured approach to identify agent interactions, and design simulation architecture and agent behaviour. The framework is named ABOOMS (Agent-Based Object-Oriented Modelling and Simulation). After applying the ABOOMS framework to three case studies, the framework demonstrates flexibility in development with two different modelling principles (Keep-It-Simple-Stupid vs. Keep-It-Descriptive-Stupid), capability in supporting complex psychological mechanisms, and ability to model dynamic behaviours in both discrete and continuous time. Additionally, the thesis developed an agent-based model of a PGG in a continuous-time setting. To the best of our knowledge such agent-based models do not exist. During the development, a new social preference, Generous Conditional Cooperators, was introduced to better explain the behavioural dynamics in continuous-time PGG. Experimentation with the agent-based model generated dynamics that are not presented in discrete-time setting. Thus, it is important to study both discrete and continuous time PGG, with laboratory experiment and ABMS. Our new framework allows to do the latter in a structured way. With the ABOOMS framework, economists can develop PGG simulation models in a structured way and communicate them with a formal model specification. The thesis also showed that there is a need for further investigation on behaviours in continuous-time PGG. For future works, the framework can be tested with variations of PGG or other related strategic interactions

CROWD-2-CLOUD – Remote Sensing Land Cover Verification With Crowd-Sourcing Data

Nowadays, advanced remote sensing technologies provide huge amount of Earth Observation (EO) data timely. Growing quickly in terms of size and structure, EO data require a new way of handling and processing as it is considered big data. Cloud-computing platform proved to be a reliable and scalable platform that suits various user demands in remote sensing data processing. To verify the ambiguity of information derived solely from remote sensing, ground data is vital. The only way to keep pace with big remote sensing data is to exploit the crowdsourced data, which has been recently proposed elsewhere. In this study, we developed a prototype of an integrated location based service on top of cloud computing platform to detect land cover features and engage the crowd of volunteers during training and verification process. Relying on open-source tools, the proposed system provides location-based data collection and satellite image classification. The prototype was tested over the rapid on-going landscape surrounding the University of Nottingham, Malaysia campus. More advanced functions will be developed and a full system will be deployed and tested in further study

Dynamic agent-based bi-objective robustness for tardiness and energy in a dynamic flexible job shop

Nowadays, manufacturing systems are shifting rapidly with the significant change in technology, business, and industry to become more complex and involved in more difficult issues, customised products, variant services and products, unavailable machines, and rush jobs. In the current practices, there are limited models or approaches that are dealing with these complexities. Most of the scheduling models in literature are proposed as centralised approaches. Researchers recently started to pay attention to reduce energy consumption in manufacturing due to the rising cost and the environmental impact. The energy consumption factor has been lately introduced into scheduling research among other traditional objectives such as time, cost and quality. Although reducing energy in manufacturing systems is very important, few researchers have considered energy consumption factor into scheduling in dynamic flexible manufacturing systems. This paper proposes an agent-based dynamic bio-objective robustness for energy and time in a job shop. Two types of agent are introduced which are machine agent and product agent. A new decision making and negotiation model for multi-agent systems is developed. Two types of dynamic unexpected events in the shop floor are introduced: dynamic job arrival and machines breakdown. A case study is provided in order to verify the result

LOẠI BỎ XANH METYLEN BẰNG PHƯƠNG PHÁP ĐIỆN DI LẮNG ĐỌNG KẾT HỢP VỚI VẬT LIỆU MnO2/GO

Graphene oxide (GO) was synthesized with the improved Hummer method and chemically modified with manganese dioxide (MnO2) to obtain an MnO2/GO composite. The properties of the composite material were evaluated via infrared spectroscopy, UV-Vis spectroscopy, scanning electron microscopy combined with energy-dispersive X-ray spectroscopy, and image mapping. The parameters studied in the method of electrophoretic deposition (EPD) are pH, electrolysis potential, electrolysis time, sodium chloride concentration, and the mass of the composite. Under suitable experimental conditions, the EPD method provides a rate of colour removal and chemical oxygen demand (COD) of methylene at 99.64 and 85.85%. This result shows the potential of the EPD method coupled with MnO2/GO composite to remove organic pigments in the aqueous medium.Vật liệu graphen oxit (GO) được tổng hợp bằng phương pháp Hummer cải tiến và biến tính với mangan đioxit (MnO2) bằng phương pháp hóa học để thu được vật liệu tổ hợp MnO2/GO. Một số tính chất đặc trưng của vật liệu tổ hợp được đánh giá bằng phổ hồng ngoại, phổ UV-Vis, hiển vi điện tử quét kết hợp với quang phổ tán xạ năng lượng tia X và ảnh mapping. Các thông số trong phương pháp điện di lắng đọng (EPD) như pH, thế điện phân, thời gian điện phân, nồng độ clorua natri và khối lượng vật liệu tổ hợp đã được nghiên cứu. Vật liệu MnO2/GO có khả năng loại màu và nhu cầu oxy hóa học của xanh metylen với hiệu suất 99,64 và 85,85% với phương pháp EPD. Kết quả cho thấy tiềm năng của của phương pháp EPD kết hợp với vật liệu MnO2/GO để loại bỏ chất màu hữu cơ trong môi trường nước

Lax Compliance of Goodwill Impairment Accounting in the Early Year after IFRS Implementation

After some decades of discussing in recognizing, measuring and reporting goodwill in the financial reports, Hong Kong finally has promulgated HKAS 36 - Impairment of Assets, for the convergence of IFRS including IAS 36. This is absolutely applicable to all transactions of business combinations beginning on or after 1st January, 2005. The adoption of HKAS 36 has resulted in significant changes and more complexity in terms of techniques and in the nature of disclosures relating to goodwill and its impairment to the reporting first-time adopters. The traditional method by adopting “capitalize and amortize” has been replaced by impairment testing regime based on subjective assumptions. Therefore, it is more likely to have inconsistent compliance by the first-time adopters in their transition period under the new reporting approach. Thus, this study has the purpose of examining the compliance levels under a variety of provisions of HKAS 36. By using the data of annual reports of Hong Kong listed firms, first-time adopters, the research found the material levels of non-compliance and substantial changes in the quality of note-form disclosures bearing on impairment testing process. Further study on post transition period is identified and discussed. Keywords: Goodwill, Impairment, Financial Reporting Standard, Hong Kon