title: Development and design of binder systems for titanium metal injection molding: An overview

authors: Wen, Guian

subjects: titanium metal injection molding

abstract: Titanium metal injection molding (Ti-MIM) has been practiced since the late 1980s. Logically, the Ti-MIM practice follows the similar processes developed for the antecedent materials such as stainless steel and ceramics. Although Ti-MIM is a favorite research topic today, the issue of convincing the designers to use Ti injection-molded parts still exists. This is mainly because of the concern about contamination which seems unavoidable during the Ti-MIM process. Much information about the binder formulation, powder requirements, debinding, and sintering is available in the literature. There are several powder vendors and feedstock suppliers. However, most of the binders in the feedstock are proprietarily protected. The disclosed information on the binders used for formulating powder feedstock is very limited, which in turn discourages their adoption by engineering designers. This overview intends to discuss some of major binder systems for Ti-MIM available in the literature. It serves to provide a guideline for the Ti-MIM practitioners to choose a suitable powder feedstock.

text: Development and design of binder systems for titanium metal injection molding: An overview Titanium metal injection molding (Ti-MIM) has been practiced since the late 1980s. Logically, the Ti-MIM practice follows the similar processes developed for the antecedent materials such as stainless steel and ceramics. Although Ti-MIM is a favorite research topic today, the issue of convincing the designers to use Ti injection-molded parts still exists. This is mainly because of the concern about contamination which seems unavoidable during the Ti-MIM process. Much information about the binder formulation, powder requirements, debinding, and sintering is available in the literature. There are several powder vendors and feedstock suppliers. However, most of the binders in the feedstock are proprietarily protected. The disclosed information on the binders used for formulating powder feedstock is very limited, which in turn discourages their adoption by engineering designers. This overview intends to discuss some of major binder systems for Ti-MIM available in the literature. It serves to provide a guideline for the Ti-MIM practitioners to choose a suitable powder feedstock.

year: 2013

title: Propositionalisation of multi-instance data using random forests

authors: Frank, Eibe

subjects: Machine learning

abstract: Multi-instance learning is a generalisation of attribute-value learning where examples for learning consist of labeled bags (i.e. multi-sets) of instances. This learning setting is more computationally challenging than attribute-value learning and a natural fit for important application areas of machine learning such as classification of molecules and image classification. One approach to solve multi-instance learning problems is to apply propositionalisation, where bags of data are converted into vectors of attribute-value pairs so that a standard propositional (i.e. attribute-value) learning algorithm can be applied. This approach is attractive because of the large number of propositional learning algorithms that have been developed and can thus be applied to the propositionalised data. In this paper, we empirically investigate a variant of an existing propositionalisation method called TLC. TLC uses a single decision tree to obtain propositionalised data. Our variant applies a random forest instead and is motivated by the potential increase in robustness that this may yield. We present results on synthetic and real-world data from the above two application domains showing that it indeed yields increased classification accuracy when applying boosting and support vector machines to classify the propositionalised data.

text: Propositionalisation of multi-instance data using random forests Multi-instance learning is a generalisation of attribute-value learning where examples for learning consist of labeled bags (i.e. multi-sets) of instances. This learning setting is more computationally challenging than attribute-value learning and a natural fit for important application areas of machine learning such as classification of molecules and image classification. One approach to solve multi-instance learning problems is to apply propositionalisation, where bags of data are converted into vectors of attribute-value pairs so that a standard propositional (i.e. attribute-value) learning algorithm can be applied. This approach is attractive because of the large number of propositional learning algorithms that have been developed and can thus be applied to the propositionalised data. In this paper, we empirically investigate a variant of an existing propositionalisation method called TLC. TLC uses a single decision tree to obtain propositionalised data. Our variant applies a random forest instead and is motivated by the potential increase in robustness that this may yield. We present results on synthetic and real-world data from the above two application domains showing that it indeed yields increased classification accuracy when applying boosting and support vector machines to classify the propositionalised data.

year: 2013

title: Lifting barriers: Leadership, tactical, and strategic issues from, and for, indigenous community development

authors: Murthy, Vikram

subjects: indigenous communities

abstract: This paper uses learnings from a project with indigenous youth to engage with a recurring challenge in indigenous community organisation (ICO) development initiatives: The unwitting detraction from outcome efficacy by charismatic and influential indigenous leadership leading with an out-of-date repertoire. Using material from recent literature in the fields of non-profit management, new leadership, and social enterprise, the paper suggests guides to improved practice for meeting this challenge. It also sets out to effectiveness, will better underwrite sensitivity in entrepreneurial environments with complex cultural and social beliefs and practices. Such a repertoire will energise intraorganisational communal and consensual processes, which would resonate culturally with the ICO's normative behaviours and values, and would thus help the organisation marshall its collective will to frame futures that best capture their stakeholders' hopes and aspirations. Finally, it recommends that future research examine interfaces between these fields and the spiritual frameworks of indigenous world-views.

text: Lifting barriers: Leadership, tactical, and strategic issues from, and for, indigenous community development This paper uses learnings from a project with indigenous youth to engage with a recurring challenge in indigenous community organisation (ICO) development initiatives: The unwitting detraction from outcome efficacy by charismatic and influential indigenous leadership leading with an out-of-date repertoire. Using material from recent literature in the fields of non-profit management, new leadership, and social enterprise, the paper suggests guides to improved practice for meeting this challenge. It also sets out to effectiveness, will better underwrite sensitivity in entrepreneurial environments with complex cultural and social beliefs and practices. Such a repertoire will energise intraorganisational communal and consensual processes, which would resonate culturally with the ICO's normative behaviours and values, and would thus help the organisation marshall its collective will to frame futures that best capture their stakeholders' hopes and aspirations. Finally, it recommends that future research examine interfaces between these fields and the spiritual frameworks of indigenous world-views.

year: 2006