A mill design concept for reducing bagasse moisture

This paper describes the development and testing of a novel mill design to reduce the moisture content of bagasse. It takes advantage of gravity to separate juice from bagasse by pushing bagasse upwards while juice drains downwards under gravity. The potential of the design to reduce bagasse moisture content has not been adequately established. The prototype mill had limited power available that prevented typical delivery nip compactions from being achieved. Tests conducted did show a reduction in bagasse moisture but that moisture reduction is less than expected under ideal conditions. Work on the mill design has ceased, at least for the foreseeable future. The design does have potential to reduce bagasse moisture content but presents some engineering challenges to establish a reliable, low maintenance design alternative.

A research framework for assessing the effects of heat stress on construction workers

Hong Kong in summer (June - October) is hot and humid. Construction workers have to undertake physically demanding activities and often in confined spaces. They are vulnerable to heat stress in summer hence health and safety measures associated to heat stress measured by scientific and clinical parameters are urgently needed. This paper provides an initial report of a research project funded by the Research Grants Council (RGC) of the HKSAR. The aim of this study is to develop a set of indices measured by clinical and scientific methods to detect impending attacks of heat stress. These indices would be of tremendous value in better safeguarding workers’ health and safety by reducing the occurrences of heat stress on site. This paper firstly reports on the statistics of construction incidents arising from heat stress. Qualitative and quantitative research methods applied in conducting the research are discussed. It is believed that the construction industry and the government would benefit a lot as a result of this study.

Semantic service discovery in the service ecosystem

Electronic services are a leitmotif in ‘hot’ topics like Software as a Service, Service Oriented Architecture (SOA), Service oriented Computing, Cloud Computing, application markets and smart devices. We propose to consider these in what has been termed the Service Ecosystem (SES). The SES encompasses all levels of electronic services and their interaction, with human consumption and initiation on its periphery in much the same way the ‘Web’ describes a plethora of technologies that eventuate to connect information and expose it to humans. Presently, the SES is heterogeneous, fragmented and confined to semi-closed systems. A key issue hampering the emergence of an integrated SES is Service Discovery (SD). A SES will be dynamic with areas of structured and unstructured information within which service providers and ‘lay’ human consumers interact; until now the two are disjointed, e.g., SOA-enabled organisations, industries and domains are choreographed by domain experts or ‘hard-wired’ to smart device application markets and web applications. In a SES, services are accessible, comparable and exchangeable to human consumers closing the gap to the providers. This requires a new SD with which humans can discover services transparently and effectively without special knowledge or training. We propose two modes of discovery, directed search following an agenda and explorative search, which speculatively expands knowledge of an area of interest by means of categories. Inspired by conceptual space theory from cognitive science, we propose to implement the modes of discovery using concepts to map a lay consumer’s service need to terminologically sophisticated descriptions of services. To this end, we reframe SD as an information retrieval task on the information attached to services, such as, descriptions, reviews, documentation and web sites - the Service Information Shadow. The Semantic Space model transforms the shadow's unstructured semantic information into a geometric, concept-like representation. We introduce an improved and extended Semantic Space including categorization calling it the Semantic Service Discovery model. We evaluate our model with a highly relevant, service related corpus simulating a Service Information Shadow including manually constructed complex service agendas, as well as manual groupings of services. We compare our model against state-of-the-art information retrieval systems and clustering algorithms. By means of an extensive series of empirical evaluations, we establish optimal parameter settings for the semantic space model. The evaluations demonstrate the model’s effectiveness for SD in terms of retrieval precision over state-of-the-art information retrieval models (directed search) and the meaningful, automatic categorization of service related information, which shows potential to form the basis of a useful, cognitively motivated map of the SES for exploratory search.

An enhanced mill extraction model

An enhanced mill extraction model has been developed to calculate mill performance parameters and to predict the extraction performance of a milling unit. The model takes into account the fibre suspended in juice streams and calculates filling ratio, reabsorption factor, imbibition coefficient, and separation efficiency using more complete definitions than those used in previous extraction models. A mass balance model is used to determine the fibre, brix and moisture mass flows between milling units so that a complete milling train, including the return stream from the juice screen, is modelled. Model solutions are presented to determine the effect of different levels of fibre in juice and efficiency of fibre separation in the juice screen on brix extraction. The model provides more accurate results than earlier models leading to better understanding and improvement of the milling process.

A new approach to automatically producing schedules for cane railways

The scheduling of locomotive movements on cane railways has proven to be a very complex task. Various optimisation methods have been used over the years to try and produce an optimised schedule that eliminates or minimises bin supply delays to harvesters and the factory, while minimising the number of locomotives, locomotive shifts and cane bins, and also the cane age. This paper reports on a new attempt to develop an automatic scheduler using a mathematical model solved using mixed integer programming and constraint programming approaches and blocking parallel job shop scheduling fundamentals. The model solution has been explored using conventional constraint programming search techniques and found to produce a reasonable schedule for small-scale problems with up to nine harvesters. While more effort is required to complete the development of the full model with metaheuristic search techniques, the work completed to date gives confidence that the metaheuristic techniques will provide near optimal solutions in reasonable time.

The effect of mill orientation angle on bagasse moisture content

THIS PAPER DESCRIBES an experimental investigation to explore a concept designed to reduce the moisture content of bagasse. It takes advantage of gravity to separate juice from bagasse by feeding bagasse upwards into the nip of the mill while juice drains downwards under gravity. The investigation found that orienting the feed to a mill upwards does reduce bagasse moisture content and that the benefit is expected to be greater than two units of moisture. While an advantage was found in orienting the feed up to 50° above the horizontal, no extra benefit was found in increasing the angle higher (up to 60° was explored) and so a 50° orientation was identified as the preferred angle for this design concept.

Mixing and drying mud and ash at Tully Mill

Disposal of mud and ash, particularly in wet weather conditions, is a significant expense for mills. This paper reports on part of a process to pelletise mud and ash, aimed at making mud and ash more attractive to growers across entire mill districts. The full process and the re-constituting and centrifuging rotary vacuum filter mud part of the process were described in two papers to the 2011 conference. The component described in this paper involves aspects of mixing mud and ash with subsequent drying using boiler exit gas. The mud material needs to mix easily with boiler ash and the mixture has to feed easily into and be pneumatically conveyed by a flue gas dryer. The performance of a pilot flue gas dryer for drying mud and ash was evaluated. The mud and ash mixture was found to dry much faster than final bagasse, provided the mud and ash material was broken up into individual particles. A previously developed computer model of bagasse drying was updated to take into account the smaller particle size of the mud and ash mixture. This upgraded model predicted the performance of the pilot flue gas dryer well.

Ontology-based knowledge management for enterprise systems

Companies face the challenges of expanding their markets, improving products, services and processes, and exploiting intellectual capital in a dynamic network. Therefore, more companies are turning to an Enterprise System (ES). Knowledge management (KM) has also received considerable attention and is continuously gaining the interest of industry, enterprises, and academia. For ES, KM can provide support across the entire lifecycle, from selection and implementation to use. In addition, it is also recognised that an ontology is an appropriate methodology to accomplish a common consensus of communication, as well as to support a diversity of KM activities, such as knowledge repository, retrieval, sharing, and dissemination. This paper examines the role of ontology-based KM for ES (OKES) and investigates the possible integration of ontology-based KM and ES. The authors develop a taxonomy as a framework for understanding OKES research. In order to achieve the objective of this study, a systematic review of existing research was conducted. Based on a theoretical framework of the ES lifecycle, KM, KM for ES, ontology, and ontology-based KM, guided by the framework of study, a taxonomy for OKES is established.

Text mining in negative relevance feedback

It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

Report on INEX 2011

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2011 evaluation campaign, which consisted of a five active tracks: Books and Social Search, Data Centric, Question Answering, Relevance Feedback, and Snippet Retrieval. INEX 2011 saw a range of new tasks and tracks, such as Social Book Search, Faceted Search, Snippet Retrieval, and Tweet Contextualization.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Building prosperous knowledge cities : policies, plans and metrics

This unique book reveals the procedural aspects of knowledge-based urban planning, development and assessment. Concentrating on major knowledge city building processes, and providing state-of-the-art experiences and perspectives, this important compendium explores innovative models, approaches and lessons learnt from a number of key case studies across the world. Many cities worldwide, in order to brand themselves as knowledge cities, have undergone major transformations in the 21st century. This book provides a thorough understanding of these transformations and the key issues in building prosperous knowledge cities by focusing particularly on the policy-making, planning process and performance assessment aspects. The contributors reveal theoretical and conceptual foundations of knowledge cities and their development approach of knowledge-based urban development. They present best-practice examples from a number of key case studies across the globe. This important book provides readers with a thorough understanding of the key issues in planning and developing prosperous knowledge cities of the knowledge economy era, which will prove invaluable to national, state/regional and city governments’ planning and development departments. Academics, postgraduate and undergraduate students of regional and urban studies will also find this path-breaking book an intriguing read.