Polarisasi “Liyan” dalam Meme Please Help Me: Contraceptive Pills

Contraceptives are considered to be the key to solving poverty problems by controlling women's reproductive systems. In campaigning for poverty solutions, women's bodies are presented in the Please Help Me: Contraceptive Pills meme through a representation system. Representation is closely related to the use of stereotypes which are subjective and prejudiced labeling. The first discussion is about how women's cultural identity is represented in the sign relation of a Please Help Me: Contraceptive Pills meme and what ideological practices that works behind the meme. This paper aims to analyze the representation system of women's cultural identity in a meme, Please Help Me: Contraceptive Pills. In addition, this paper seeks to show the pervasive discrimination through sign relations. This qualitative research uses the semiotic method in interpreting signs in memes. The results of this analysis state that the practice of the representation system has limited the flow of meaning so that in this meme there is an imbalanced represention of women's cultural identity and that the responsibility for procreation is only a woman's concerns. Keywords: discrimination, identity, meme, representation, the Other

Differential Privacy Trajectory Data Protection Algorithm Based on Polar Coordinate Transformation

Differential privacy technology has been widely used in the issue of trajectory data release. Improving the availability of data release under the premise of ensuring privacy and security is one of its basic research goals. At present, most trajectory data release methods use a rectangular coordinate system to represent location information. Research has shown that the availability of published data cannot be optimized through the rectangular coordinate system. In order to improve the effect of trajectory data release, this paper proposes a differential privacy trajectory data protection algorithm based on polar coordinates. First, the stay point detection method is used to find frequent stay points in the trajectory and the key location points related to personal privacy are detected by the type of location points. Then, this paper converts the rectangular coordinate system representation of the key position points to the polar coordinate system representation, and implement differential privacy trajectory data release by adding noise to the key position points represented by the polar coordinates. Experiments show that the algorithm proposed in this paper effectively improves the usability of trajectory data on real data sets.

Nature-based Solutions to Mitigate Environmental Challenges: A Systems Thinking Approach for Integrated Understanding of Human-Nature Interactions

<p>Urban areas increasingly face challenges associated with dynamic interactions between human and nature systems, such as global (land-, water-use and climate) changes and their related environmental consequences. These challenges can be addressed by sustainable management of coupled human-nature systems that are being stablished and progressed in urban areas. In this context, nature-based solutions (NbSs), as cost-effective actions, are used to protect, sustain, and restore natural or engineered ecosystems for potentially increasing their services delivery to humans. Being inspired and supported by nature systems, NbSs provide human well-being and biodiversity benefits and address coupled environmental-social-economic challenges. This study develops an integrated understanding of human-nature interactions, by investigating wetland functions and their values in Stockholm region, a European densely populated urban area. Wetlands integrate natural and anthropogenic processes and help cities adapt to changes by enhancing their resilience to environmental and social challenges. In this study, a participatory approach has been applied for combining local and scientific knowledge to address the following questions: (i) What are the underlying system dynamics and interactions between urbanization and wetland regulating ecosystem services as coupled human-nature systems? and (ii) How do these dynamics affect synergies and trade-offs in achieving Sustainable Development Goals (SDGs)? Therefore, relevant actors have been involved in thematic sector workshops and followed a systems thinking technique to co-create a causal loop diagram (CLD) as a conceptual system representation. The CLD highlights key components and drivers of the system, providing actor-specific perspectives of interactions and feedback structures within the system. Dynamic hypotheses on the effectiveness and roles of wetlands as NbSs in the study region have also been examined in a fuzzy cognitive map, developed as a semi-quantitative system representation. The results provide insights on wetland contributions to attaining SDGs in urban areas, as well as potential transition pathways toward sustainable development by identifying opportunities and barriers for the study region.</p>

Physical interpretation of hydrologic model complexity revisited

<p>It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We use algorithms to quantify model complexity in this context from Pande et al. (2014). We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for CAMEL data set (Addor et al., 2017) and quantify complexities of corresponding models. Relationships between hydrologic characteristics of CAMEL basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated.</p><p>Recently Pande and Moayeri (2018) introduced an index of basin complexity based on another, non-parameteric, model of least statistical complexity that is needed to reliably model daily streamflow of a basin. This method essentially interprets complexity in terms of difficulty in predicting historically similar stream flow events. Daily streamflow is modeled using k-nearest neighbor model of lagged streamflow. Such models are parameterised by the number of lags and radius of neighborhood that it uses to identify similar streamflow events from the past. These parameters need to be selected for each time step of prediction ’query’. We use 1) Tukey half-space data depth function to identify time steps corresponding to ’difficult’ queries and 2) then use Vapnik-Chervonenkis (VC) generalization theory, which trades off model performance with VC dimension (i.e. a measure of model complexity), to select parameters corresponding to k nearest neighbor model that is of appropriate complexity for modelling difficult queries. Average of selected model complexities corresponding to difficult queries are then related with the same hydrologic characteristics as above for CAMEL basins.</p><p>We find that complexities estimated on SAC-SMA model using the algorithm of Pande et al. (2014) are correlated with those estimated on knn model using VC generalization theory. Further, the relationships between the two complexities and hydrologic characteristics are also similar. This indicates that interpretation of complexity as a measure of instability in hydrological system representation is similar to the interpretation provided by VC generalization theory of difficulty in predicting historically similar stream flow events.  </p><p>Reference:</p><p>Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P. (2017) The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017.</p><p>Pande, S., Arkesteijn, L., Savenije, H. H. G., and Bastidas, L. A. (2014) Hydrological model parameter dimensionality is a weak measure of prediction uncertainty, Hydrol. Earth Syst. Sci. Discuss., 11, 2555–2582, https://doi.org/10.5194/hessd-11-2555-2014.</p><p>Pande, S., and Moayeri, M. (2018). Hydrological interpretation of a statistical measure of basin complexity. Water Resources Research, 54. https://doi.org/10.1029/2018WR022675</p>