Using digital storytelling as a change agent for women’s participation in the Turkish public sphere

This thesis builds on the scholarship and practical know-how that have emerged from digital storytelling projects around the world with diverse groups of participants in a range of institutions. I have used the results of these projects to explore the opportunities Digital Storytelling workshop practice may hold for women’s participation in the public sphere in Turkey. Through theoretical discussion and practical experimentation, I examine the potential of Digital Storytelling workshop practice as a means to promote agency and self-expression in a feminist activist organisation, focusing in particular on whether Digital Storytelling can be used as a change agent – as a tool for challenging the idea of public sphere in ways that make it more inclusive of women’s participation. The thesis engages with feminist scholarship’s critiques of the public/private dichotomy, as well as the concept of gender, to seek connections with narrative identity in the light of the analysis of the Digital Storytelling workshops and the digital stories that were created in a feminist context. The study on which this thesis is based saw the introduction of Digital Storytelling to Turkey for the first time through workshops in Istanbul and Antakya, conducted in partnership with the feminist activist organisation Amargi Women’s Academy. Applying the principles of feminist post-structuralist discourse analysis as used by Judith Baxter (2003), I examine two sets of data collected in this project. First, I analyse the interactions during the Digital Storytelling workshops, where women from Amargi created their digital stories in a collaborative setting. This is done through participatory observation notes and in-depth interviews with the workshop participants and facilitators. Second, I seek to uncover the strategies that these women used to ‘speak back to power’ in their digital stories, reading these as texts. I conclude that women from the Amargi network used the workshops to create digital content in order to communicate their concerns about issues that can be classified as gender-specific matters. During this process, they also cooperated, established new connections, and at the end of the process even defined new ways of using, circulating and repurposing their digital stories for feminist activism in Turkey. My research thereby contributes equally to feminist discourse analysis, the study of new-media usage and uptake among non-professionals, and the study of media–public sphere interactions in a particular national setting: Turkey. My conclusion indicates that the process of production is as important as the product itself, and from that I am able to draw out some strategies for developing digitally equipped women’s activism in Turkey.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

A New DER coordination in LV network based on the concept of distributed control

Given the paradigm of smart grid as the promising backbone for future network, this paper uses this paradigm to propose a new coordination approach for LV network based on distributed control algorithm. This approach divides the LV network into hierarchical communities where each community is controlled by a control agent. Different level of communication has been proposed for this structure to control the network in different operation modes.

Evaluation in health outcomes research : linking theories, methodologies and practice in health promotion.

Health outcomes research has developed as a means of evaluating the effectiveness of health care interventions and as an approach to informing resource allocation. The use of a health outcomes approach in health promotion has made increasing demands on evaluation methodologies to demonstrate program effectiveness. However, criticism of the contribution of health promotion to outcomes research has made several assumptions about the use of qualitative methodologies and the content of program objectives largely derived from a biomedical approach. In contrast to the measurement of biomedical interventions in clinical health care, health promotion practice involves social phenomena, wide-reaching cultural, psychological, political and ideological problems and issues. The integration of methodologies of health promotion evaluation will inform further conceptualisation of the health outcomes approach with the differentiation of three types of outcomes: health development outcomes; social health outcomes; and biomedical health outcomes. It is concluded that this differentiation moves away from dualist concepts that advocate the replacement of goals and targets with regional and locally based approaches. Rather, the future direction for health promotion evaluation needs to employ a framework that elaborates multiple methodologies and approaches necessary for establishing what relationships exist between morbidity, mortality, health advancement and equity.

“Yarning” as a method for community-based health research with indigenous women : the indigenous women's wellness research program

This project explores yarning as a methodology for understanding health and wellness from an indigenous woman's perspective. Previous research exploring indigenous Australian women's perspectives have used traditional Western methodologies and have often been felt by the women themselves to be inappropriate and ineffective in gathering information and promoting discussion. This research arose from the indigenous women themselves, and resulted in the exploration of using yarning as a methodology. Yarning is a conversational process that involves the sharing of stories and the development of knowledge. It prioritizes indigenous ways of communicating, in that it is culturally prescribed, cooperative, and respectful. The authors identify different types of yarning that are relevant throughout their research, and explain two types of yarning—family yarning and cross-cultural yarning—which have not been previously identified in research literature. This project found that yarning as a research method is appropriate for community-based health research with indigenous Australian women. This may be an important finding for health professionals and researchers to consider when working and researching with indigenous women from other countries.

SERS based detection of barcoded gold nanoparticle assemblies from within animal tissue

We have explored the potential of deep Raman spectroscopy, specifically surface enhanced spatially offset Raman spectroscopy (SESORS), for non-invasive detection from within animal tissue, by employing SERS-barcoded nanoparticle (NP) assemblies as the diagnostic agent. This concept has been experimentally verified in a clinic-relevant backscattered Raman system with an excitation line of 785 nm under ex vivo conditions. We have shown that our SORS system, with a fixed offset of 2-3 mm, offered sensitive probing of injected QTH-barcoded NP assemblies through animal tissue containing both protein and lipid. In comparison to that of non-aggregated SERS-barcoded gold NPs, we have demonstrated that the tailored SERS-barcoded aggregated NP assemblies have significantly higher detection sensitivity. We report that these NP assemblies can be readily detected at depths of 7-8 mm from within animal proteinaceous tissue with high signal-to-noise (S/N) ratio. In addition they could also be detected from beneath 1-2 mm of animal tissue with high lipid content, which generally poses a challenge due to high absorption of lipids in the near-infrared region. We have also shown that the signal intensity and S/N ratio at a particular depth is a function of the SERS tag concentration used and that our SORS system has a QTH detection limit of 10-6 M. Higher detection depths may possibly be obtained with optimization of the NP assemblies, along with improvements in the instrumentation. Such NP assemblies offer prospects for in vivo, non-invasive detection of tumours along with scope for incorporation of drugs and their targeted and controlled release at tumour sites. These diagnostic agents combined with drug delivery systems could serve as a “theranostic agent”, an integration of diagnostics and therapeutics into a single platform.

Phase II trial of Oxaliplatin and 5-Fluorouracil/Leucovorin combination in epithelial ovarian carcinoma relapsing within 2 years of platinum-based therapy

Objective To evaluate the efficacy and toxicity of Oxaliplatin and 5-Fluorouracil (5-FU)/Leucovorin (LV) combination in ovarian cancer relapsing within 2 years of prior platinum-based chemotherapy in a phase II trial. Methods Eligible patients had at least one prior platinum-based chemotherapy regimen, elevated CA-125 ≥ 60 IU/l, radiological evidence of disease progression and adequate hepatic, renal and bone marrow function. Patients with raised CA-125 levels alone as marker of disease relapse were not eligible. Oxaliplatin (85 mg/m 2) was given on day 1, and 5-Fluorouracil (370 mg/m 2) and Leucovorin (30 mg) was given on days 1 and 8 of a 14-day cycle. Results Twenty-seven patients were enrolled. The median age was 57 years (range 42-74 years). The median platinum-free interval (PFI) was 5 months (range 0-17 months) with only 30% of patients being platinum sensitive (PFI > 6 months). Six patients (22%) had two prior regimens of chemotherapy. A total of 191 cycles were administered (median 7; range 2-12). All patients were evaluable for toxicity. The following grade 3/4 toxicities were noted: anemia 4%; neutropenia 15%; thrombocytopenia 11%; neurotoxicity 8%; lethargy 4%; diarrhea 4%; hypokalemia 11%; hypomagnesemia 11%. Among 27 enrolled patients, 20 patients were evaluable for response by WHO criteria and 25 patients were evaluable by Rustin's CA-125 criteria. The overall response rate (RR) by WHO criteria was 30% (95% CI: 15- 52) [three complete responses (CRs) and three partial responses (PRs)]. The CA-125 response rate was 56% (95% CI: 37-73). Significantly, a 25% (95% CI: 9-53) radiological and a 50% (95% CI: 28-72) CA-125 response rate were noted in platinum resistant patients (PFI < 6 months). The median response duration was 4 months (range 3-12) and the median overall survival was 10 months. Conclusion Oxaliplatin and 5-Fluorouracil/ Leucovorin combination has a good safety profile and is active in platinum-pretreated advanced epithelial ovarian cancer. © 2004 Elsevier Inc. All rights reserved.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.

"Candidatus Similichlamydia laticola", a novel Chlamydia-like agent of epitheliocystis in seven consecutive cohorts of farmed Australian barramundi, lates calcarifer (Bloch)

Six consecutively hatched cohorts and one cohort of pre-hatch eggs of farmed barramundi (Lates calcarifer) from south Australia were examined for Chlamydia-like organisms associated with epitheliocystis. To identify and characterise the bacteria, 59 gill samples and three pre-hatch egg samples were processed for histology, in situ hybridisation and 16S rRNA amplification, sequencing and comprehensive phylogenetic analysis. Cases of epitheliocystis were observed microscopically and characterised by membrane-enclosed basophilic cysts filled with a granular material that caused hypertrophy of the epithelial cells. In situ hybridisation with a Chlamydiales-specific probe lead to specific labelling of the epitheliocystis inclusions within the gill epithelium. Two distinct but closely related 16S rRNA chlamydial sequences were amplified from gill DNA across the seven cohorts, including from pre-hatch eggs. These genotype sequences were found to be novel, sharing 97.1 - 97.5% similarity to the next closest 16S rRNA sequence, Ca. Similichlamydia latridicola, from Australian striped trumpeter. Comprehensive phylogenetic analysis of these genotype sequences against representative members of the Chlamydiales order and against other epitheliocystis agents revealed these Chlamydia-like organisms to be novel and taxonomically placed them within the recently proposed genus Ca. Similichlamydia. Following Fredricks and Relman's molecular postulates and based on these observations, we propose the epitheliocystis agents of barramundi to be known as "Candidatus Similichlamydia laticola" (sp. nov.).

Molecular characterization of "Candidatus Parilichlamydia carangidicola," a novel Chlamydia-like epitheliocystis agent in yellowtail kingfish, Seriola lalandi (Valenciennes), and the proposal of a new family, "Candidatus Parilichlamydiaceae" fam. nov. (order Chlamydiales).

Three cohorts of farmed yellowtail kingfish (Seriola lalandi) from South Australia were examined for Chlamydia-like organisms associated with epitheliocystis. To characterize the bacteria, 38 gill samples were processed for histopathology, electron microscopy, and 16S rRNA amplification, sequencing, and phylogenetic analysis. Microscopically, the presence of membrane-enclosed cysts was observed within the gill lamellae. Also observed was hyperplasia of the epithelial cells with cytoplasmic vacuolization and fusion of the gill lamellae. Transmission electron microscopy revealed morphological features of the reticulate and intermediate bodies typical of members of the order Chlamydiales. A novel 1,393-bp 16S chlamydial rRNA sequence was amplified from gill DNA extracted from fish in all cohorts over a 3-year period that corresponded to the 16S rRNA sequence amplified directly from laser-dissected cysts. This sequence was only 87% similar to the reported "Candidatus Piscichlamydia salmonis" (AY462244) from Atlantic salmon and Arctic charr. Phylogenetic analysis of this sequence against 35 Chlamydia and Chlamydia-like bacteria revealed that this novel bacterium belongs to an undescribed family lineage in the order Chlamydiales. Based on these observations, we propose this bacterium of yellowtail kingfish be known as "Candidatus Parilichlamydia carangidicola" and that the new family be known as "Candidatus Parilichlamydiaceae."

Developing Co-operating Legal Knowledge Based Systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work supplements rule-based reasoning with case based reasoning and intelligent information retrieval. This research, specifies an approach to the case based retrieval problem which relies heavily on an extended object-oriented / rule-based system architecture that is supplemented with causal background information. Machine learning techniques and a distributed agent architecture are used to help simulate the reasoning process of lawyers. In this paper, we outline our implementation of the hybrid IKBALS II Rule Based Reasoning / Case Based Reasoning system. It makes extensive use of an automated case representation editor and background information.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.