Environmental Issues and Recent Infrastructure
Development in the Mekong Delta: review, analysis and
recommendations with particular reference to largescale
water control projects and the development of
Takehiko ‘Riko’ Hashimoto.
Australian Mekong Resource Centre.
University of Sydney.
The Mekong River system supports one of the world’s largest and most diverse inland
fisheries. It includes a broad assortment of operations, ranging from solitary fishers to largescale
commercial enterprises. The catch contains a high proportion of fishes whose lifecycles
involve migrations between feeding and spawning grounds and dry season refuges.
The preservation of the river’s fisheries, therefore, partly depends on keeping the migration
routes these fish use free from obstructions and barriers that could critically disrupt their lifecycles.
The study of psychological processes in physical activity and health has grown
considerably in recent years. “Exercise psychologists” study the psychological antecedents
of physical activity and use their theoretical perspectives to inform the design and implementation
of interventions to change sedentary lifestyles. In addition, involvement in
physical activity can have important psychological benefits. Although we have known
this for a very long time, it is only relatively recently that a systematic approach has been
adopted to the accumulation of evidence.
Measured Progress is a not-for-profit organization
that designs and administers customized, largescale
student assessments. The Dover, New
Hampshire-based company develops assessments
that help states and school districts meet federal
mandates to evaluate the effectiveness of
classroom instruction through assessment, rather
than merely ranking students. Of course, the
primary goal for both Measured Progress and
its clients is improving teaching and learning
This paper proposes a novel framework called bilingual co-training for a largescale, accurate acquisition method for monolingual semantic knowledge. In this framework, we combine the independent processes of monolingual semanticknowledge acquisition for two languages using bilingual resources to boost performance. We apply this framework to largescale hyponymy-relation acquisition from Wikipedia.
In this paper, we present an unsupervised methodology for propagating lexical cooccurrence vectors into an ontology such as WordNet. We evaluate the framework on the task of automatically attaching new concepts into the ontology. Experimental results show 73.9% attachment accuracy in the first position and 81.3% accuracy in the top-5 positions. This framework could potentially serve as a foundation for ontologizing lexical-semantic resources and assist the development of other largescale and internally consistent collections of semantic information. ...
This paper describes Subcat-LMF, an ISOLMF compliant lexicon representation format featuring a uniform representation of subcategorization frames (SCFs) for the two languages English and German. Subcat-LMF is able to represent SCFs at a very ﬁne-grained level. We utilized SubcatLMF to standardize lexicons with largescale SCF information: the English VerbNet and two German lexicons, i.e., a subset of IMSlex and GermaNet verbs. To evaluate our LMF-model, we performed a crosslingual comparison of SCF coverage and overlap for the standardized versions of the English and German lexicons.
Put simply, public health has a bold mission:
“protecting health and saving lives—
millions at a time.”
In medical fields, clinicians treat diseases
or injuries, one patient at a time. But in
public health, we prevent disease and
injury. As researchers, practitioners and
educators, we work with communities and
populations. We identify causes of disease
and disability, and we implement largescale
For example, instead of treating a gun
wound, we identify causes of gun violence
and develop interventions.
The nature and amount of information needed for learning a natural language, and the underlying mechanisms involved in this process, are the subject of much debate: is it possible to learn a language from usage data only, or some sort of innate knowledge and/or bias is needed to boost the process? This is a topic of interest to (psycho)linguists who study human language acquisition, as well as computational linguists who develop the knowledge sources necessary for largescale natural language processing systems. ...
The ability to compress sentences while preserving their grammaticality and most of their meaning has recently received much attention. Our work views sentence compression as an optimisation problem. We develop an integer programming formulation and infer globally optimal compressions in the face of linguistically motivated constraints. We show that such a formulation allows for relatively simple and knowledge-lean compression models that do not require parallel corpora or largescale resources. The proposed approach yields results comparable and in some cases superior to state-of-the-art.
We describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the largescale acquisition of word-semantic information, e.g. the construction of domainindependent lexica. The backbone of the annotation are semantic roles in the frame semantics paradigm. We report experiences and evaluate the annotated data from the ﬁrst project stage. On this basis, we discuss the problems of vagueness and ambiguity in semantic annotation.