Gender studies : Intersex by Catherine Harper

Intersex is the condition whereby an individual is born with biological features that are simultaneously perceived as male and female. Ranging from the ambiguous genitalia of the true 'hermaphrodite' to the 'mildly or internally intersexed', the condition may be as common as cleft palate. Like cleft palate, it is hidden and surgically altered, but for very different reasons. Intersex draws heavily on the personal testimony of intersexed individuals, their loved ones and medical carers. The impact of early sex-assignment surgery on an individual's later life is examined within the context of ethical and clinical questions. Harper challenges the conventional and radical 'treatment' of intersexuality through non-consensual infant sex-assignment surgery. In doing so, she exposes powerful myths, taboos and constructions of gender - the perfect phallus, a bi-polar model of gender and the infallibility of medical decisions. Handling sensitive material with care, this book deepens our understanding of a condition that has itself only been medically understood in recent years.

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.

Theory-based self-management programs for promoting recovery in community-dwelling stroke survivors : a systematic review

Background Post-stroke recovery is demanding. Increasing studies have examined the effectiveness of self-management programs for stroke survivors. However no systematic review has been conducted to summarize the effectiveness of theory-based stroke self-management programs. Objectives The aim is to present the best available research evidence about effectiveness of theory-based self-management programs on community-dwelling stroke survivors’ recovery. Inclusion criteria Types of participants All community-residing adults aged 18 years or above, and had a clinical diagnosis of stroke. Types of interventions Studies which examined effectiveness of a self-management program underpinned by a theoretical or conceptual framework for community-dwelling stroke survivors. Types of studies Randomized controlled trials. Types of outcomes Primary outcomes included health-related quality of life and self-management behaviors. Secondary outcomes included physical (activities of daily living), psychological (self-efficacy, depressive symptoms), and social outcomes (community reintegration, perceived social support). Search Strategy A three-step approach was adopted to identify all relevant published and unpublished studies in English or Chinese. Methodological quality The methodological quality of the included studies was assessed using the Joanna Briggs Institute critical appraisal checklist for experimental studies. Data Collection A standardized JBI data extraction form was used. There was no disagreement between the two reviewers on the data extraction results. Data Synthesis There were incomplete details about the number of participants and the results in two studies, which makes it impossible to perform meta-analysis. A narrative summary of the effectiveness of stroke self-management programs is presented. Results Three studies were included. The key issues of concern in methodological quality included insufficient information about random assignment, allocation concealment, reliability and validity of the measuring instruments, absence of intention-to-treat analysis, and small sample sizes. The three programs were designed based on the Stanford Chronic Disease Self-management program and were underpinned by the principles of self-efficacy. One study showed improvement in the intervention group in family and social roles three months after program completion, and work productivity at six months as measured by the Stroke Specific Quality of Life Scale (SSQOL). The intervention group also had an increased mean self-efficacy score in communicating with physicians six months after program completion. The mean changes from baseline in these variables were significantly different from the control group. No significant difference was found in time spent in aerobic exercise between the intervention and control groups at three and six months after program completion. Another study, using SSQOL, showed a significant interaction effect by treatment and time on family roles, fine motor tasks, self-care, and work productivity. However there was no significant interaction by treatment and time on self-efficacy. The third study showed improvement in quality of life, community participation, and depressive symptoms among the participants receiving the stroke self-management program, Stanford Chronic Disease Self-management program, or usual care six months after program completion. However, there was no significant difference between the groups. Conclusions There is inconclusive evidence about the effectiveness of theory-based stroke self-management programs on community-dwelling stroke survivors’ recovery. However the preliminary evidence suggests potential benefits in improving stroke survivors’ quality of life and self-efficacy.

Effects of wireless sensor network uncertainties on output-only modal-based damage identification

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

Structured feature extraction using association rules

As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.