Current issues in aquaculture: lessons from Malaysia

Aquaculture in Malaysia has become a top 15 of global producers with 521,000 tonnes of total aquaculture production. As a world producer, it is crucial to learn the foundation and current challenges encountered by the sector. This paper address six major issues and challenges of the aquaculture sector in Malaysia specifically issues of fish stock depletion, climate changes, current diseases, media influences in the sector, non-compliance feeding practiced and poor interaction between stakeholders. The methodology involves searching the divergent trusted database and related information using a most popular search engine that covers selected journals including resources from fisheries authorities: Department of Fisheries Malaysia, Food, and Agriculture Organization of The United Nation and WorldFish Center. A combination of this findings, newest technology application will be suggested as accurate and timely information on managing aquaculture systems

Knowledge Integration to Overcome Ontological Heterogeneity: Challenges from Financial Information Systems

The shift towards global networking brings with it many opportunities and challenges. In this paper, we discuss key technologies in achieving global semantic interoperability among heterogeneous information systems, including both traditional and web data sources. In particular, we focus on the importance of this capability and technologies we have designed to overcome ontological heterogeneity, a common type of disparity in financial information systems. Our approach to representing and reasoning with ontological heterogeneities in data sources is an extension of the Context Interchange (COIN) framework, a mediator-based approach for achieving semantic interoperability among heterogeneous sources and receivers. We also analyze the issue of ontological heterogeneity in the context of source-selection, and offer a declarative solution that combines symbolic solvers and mixed integer programming techniques in a constraint logic-programming framework. Finally, we discuss how these techniques can be coupled with emerging Semantic Web related technologies and standards such as Web-Services, DAML+OIL, and RuleML, to offer scalable solutions for global semantic interoperability. We believe that the synergy of database integration and Semantic Web research can make significant contributions to the financial knowledge integration problem, which has implications in financial services, and many other e-business tasks.Singapore-MIT Alliance (SMA

A technology and policy analysis for global E-business

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2002.Includes bibliographical references (p. 49-51).We introduce an e-business analytical framework that focuses on transaction flows, including information, physical goods, and services. Within this framework, global e-business involves transaction flows that cross both organizational and national boundaries. Many challenging technology and policy issues arise from this trans-boundary characteristic of global e-business. These issues are analyzed using web aggregation as an example global e-business application. We start the analysis by introducing web aggregation services and their enabling technologies. Our survey of current status of web aggregation indicates that most services are still operated regionally despite their global presence. Although benefits of web aggregation have been realized in regions with extensive use of information aggregation, little is done at the global level. Our case study on worldwide price distribution of a nearly homogeneous consumer electronics product indicates great potential for global aggregation to bring information and efficiency to the global market. In addition to lack of global integration, we identified other deficiencies of web aggregation. Technological challenges and possible solutions to overcoming these deficiencies are discussed. However, having technological capability for trans-boundary information flow does not solve all problems in global aggregation. National policies often prohibit such flow into nations that have different policies, especially in database and privacy protection areas. We analyze these policy issues and propose future research on international policy harmonization.by Hongwei Zhu.S.M

Global Optimization: Software and Applications

Mathematical models are a gateway into both theoretical and experimental understand- ing. However, sometimes these models need certain parameters to be established in order to obtain the optimal behaviour or value. This is done by using an optimization method that obtains certain parameters for optimal behaviour, as described by an objective function that may be a minimum (or maximum) result. Global optimization is a branch of optimization that takes a model and determines the global minimum for a given domain. Global opti- mization can become extremely challenging when the domain yields multiple local minima. Moreover, the complexity of the mathematical model and the consequent lengths of calcu- lations tend to increase the amount of time required for the solver to find the solution. To address these challenges, two software packages were developed to aid a solver in optimizing a black box objective function. The first software package is called Computefarm, a distributed local-resource computing software package that parallelizes the iteration step of a solver by distributing objective function evaluations to idle computers. The second software package is an Optimization Database that is used to monitor the global optimization process by storing information on the objective function evaluation and any extra information on the objective function. The Optimization Database is also used to prevent data from being lost during a failure in the optimization process. In this thesis, both Computefarm and the Optimization Database are used in the context of two particular applications. The first application is quantum error correction gate design. Quantum computers cannot rely on software to correct errors because of the quantum me- chanical properties that allow non-deterministic behaviour in the quantum bit. This means the quantum bits can change states between (0, 1) at any point in time. There are various ways to stabilize the quantum bits; however, errors in the system of quantum bits and the sys- tem to measure the states can occur. Therefore, error correction gates are designed to correct for these different types of errors to ensure a high fidelity in the overall circuit. A simulation of a quantum error correction gate is used to determine the properties of components needed to correct for errors in the circuit of the qubit system. The gate designs for the three-qubit and four-qubit systems are obtained by solving a feasibility problem for the intrinsic fidelity ii(error-correction percentage) to be above the prescribed 99.99% threshold. The Optimization Database is used with the MATLAB ’s Global Search algorithm to obtain the results for the three-qubit and four-qubit systems. The approach used in this thesis yields a faster high- fidelity (≤ 99.99%) three-qubit gate time than obtained previously, and obtained a solution for a fast high-fidelity four-qubit gate time. The second application is Rational Design of Materials, in which global optimization is used to find stable crystal structures of chemical compositions. To predict crystal structures, the enthalpy that determines the stability of the structure is minimized. The Optimization Database is used to store information on the obtained structure that is later used for identification of the crystal structure and Compute- farm is used to speed up the global optimization process. Ten crystal structures for carbon and five crystal structures for silicon-dioxide are obtained by using Global Convergence Par- ticle Swarm Optimization. The stable structures, graphite (carbon) and cristobalite (silicon dioxide), are obtained by using Global Convergence Particle Swarm Optimization. Achieving these results allows for further research on the stable and meta-stable crystal structures to understand various properties like hardness and thermal conductivity

Potential applications of geospatial information systems for planning and managing aged care services in Australia

[Abstract]: This paper discusses the potential applications of Geospatial Information Technology (GITs) to assist in planning and managing aged care programs in Australia. Aged care is complex due to the numbers of participants at all levels of including planning of services, investing in capacity, funding, providing services, auditing, monitoring quality, and in accessing and using facilities and services. There is a vast array of data spread across the entities that are joined to aged care. The decision-making process for investment in capacity and service provision might be aided by technology including GIT. This is also expected to assist in managing and analysing the vast amount of demographic, geographic, socio-economic and behavioral data that might indicate current and future demand for services the aged and frail-aged population. Mapping spatio-temporal changes in near real time can assist in the successful planning and management of aged care programs. Accurate information on the location of aged care services centres and mapping the special needs of clients and their service needs may assist in monitoring access to services and assist in identifying areas where there are logistic challenges for accessing services to meet needs. GIT can also identifying migrations of aged people and of the cohorts of the population who are likely to be the next wave of clients for aged care services. GITs include remote sensing, geographic information systems (GIS) and global positioning systems (GPS) technologies, which can be used to develop a user friendly digital system for monitoring, evaluating and planning aged care and community care in Australia. Whilst remote sensing data can provide current spatiotemporal inventory of features such as locations of carer services, infrastructure, on a consistent and continuous coordinate system, a GIS can assist in storing, cross analysing, modeling and mapping of spatial data pertaining to the needs of the older people. GITs can assist in the development of a single one-stop digital database which will prove a better model for managing aged care in Australia. GIT will also be a component of technologies such as activity monitors to provide tracking functionality. This will assist in tracking dementia sufferers who may be prone to wandering and be exposed to risk

ART Neural Networks: Distributed Coding and ARTMAP Applications

ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial forecasting, machine tool monitoring, digital circuit design, chemical analysis, and robot vision. Supervised ART architectures, called ARTMAP systems, feature internal control mechanisms that create stable recognition categories of optimal size by maximizing code compression while minimizing predictive error in an on-line setting. Special-purpose requirements of various application domains have led to a number of ARTMAP variants, including fuzzy ARTMAP, ART-EMAP, Gaussian ARTMAP, and distributed ARTMAP. ARTMAP has been used for a variety of applications, including computer-assisted medical diagnosis. Medical databases present many of the challenges found in general information management settings where speed, efficiency, ease of use, and accuracy are at a premium. A direct goal of improved computer-assisted medicine is to help deliver quality emergency care in situations that may be less than ideal. Working with these problems has stimulated a number of ART architecture developments, including ARTMAP-IC [1]. This paper describes a recent collaborative effort, using a new cardiac care database for system development, has brought together medical statisticians and clinicians at the New England Medical Center with researchers developing expert systems and neural networks, in order to create a hybrid method for medical diagnosis. The paper also considers new neural network architectures, including distributed ART {dART), a real-time model of parallel distributed pattern learning that permits fast as well as slow adaptation, without catastrophic forgetting. Local synaptic computations in the dART model quantitatively match the paradoxical phenomenon of Markram-Tsodyks [2] redistribution of synaptic efficacy, as a consequence of global system hypotheses.Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

Impact of Traffic Sign Diversity on Autonomous Vehicles: A Literature Review

Traffic sign classification is indispensable for road traffic systems, including automated ones. There is a fundamental difference in the visual appearance of traffic signs from one country to another. Each dataset has its design standards and regulations based on shape, color, and information content, making implementing classification and recognition techniques more difficult. This paper aims to assess the influence of traffic sign diversity on autonomous vehicles (AVs) by reviewing several previous studies, comparing, summarizing their results, and focusing on classifying and detecting traffic sign datasets based on color, shape, and deep learning spaces using various methods and applications. Furthermore, it covers the main challenges facing road designers and planners considering changes to road safety infrastructure. It will be argued that compiling and standardizing a comprehensive global database of traffic signs is very difficult because it is costly and complex in application. However, it is still one of the possible solutions for the coming decades. Recommendations for future developments are also presented in this study

Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)