Search results for: homeland

Authors: Murari Prasad

Abstract:

This paper is motivated by the implications of indentured migration depicted in Amitav Ghosh’s critically acclaimed novel, Sea of Poppies (2008). Ghosh’s perspective on the experiences of North Indian indentured labourers moving from their homeland to a distant and unknown location across the seas suggests a radical attitudinal change among the migrants on board the Ibis, a schooner chartered to carry the recruits from Calcutta to Mauritius in the late 1830s. The novel unfolds the life-altering trauma of the bonded servants, including their efforts to maintain a sense of self while negotiating significant social and cultural transformations during the voyage which leads to the breakdown of familiar life-worlds. Equally, the migrants are introduced to an alternative network of relationships to ensure their survival away from land. They relinquish their entrenched beliefs and prejudices and commit themselves to a new brotherhood formed by ‘ship siblings.’ With the official abolition of direct slavery in 1833, the supply of cheap labour to the sugar plantation in British colonies as far-flung as Mauritius and Fiji to East Africa and the Caribbean sharply declined. Around the same time, China’s attempt to prohibit the illegal importation of opium from British India into China threatened the lucrative opium trade. To run the ever-profitable plantation colonies with cheap labour, Indian peasants, wrenched from their village economies, were indentured to plantations as girmitiyas (vernacularized from ‘agreement’) by the colonial government using the ploy of an optional form of recruitment. After the British conquest of the Isle of France in 1810, Mauritius became Britain’s premier sugar colony bringing waves of Indian immigrants to the island. In the articulations of their subjectivities one notices how the recruits cope with the alienating drudgery of indenture, mitigate the hardships of the voyage and forge new ties with pragmatic acts of cultural syncretism in a forward-looking autonomous community of ‘ship-siblings’ following the fracture of traditional identities. This paper tests the hypothesis that Ghosh envisions a kind of futuristic/utopian political collectivity in a hierarchically rigid, racially segregated and identity-obsessed world. In order to ground the claim and frame the complex representations of alliance and love across the boundaries of caste, religion, gender and nation, the essential methodology here is a close textual analysis of the novel. This methodology will be geared to explicate the utopian futurity that the novel gestures towards by underlining new regulations of life during voyage and dissolution of multiple differences among the indentured migrants on board the Ibis.

Keywords: indenture, colonial, opium, sugar plantation

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Authors: Ani Kojoyan

Abstract:

The Syrian refugee crisis has been a matter of worldwide concern during the recent years. And though refugees’ problems are contextualized in terms of time and space, the refugee crisis still remains a global issue to discuss. Since the start of the conflict, Armenia has welcomed thousands of Syrian refugees too. Taking into consideration Armenia’s current socio-economic and geopolitical situation, the flow of refugees is a challenge both for the country and for refugees themselves. However, these people are not simply refugees from Syria, they are Syrian-Armenian refugees; people whose ancestors were survivals of the Armenian Genocide, perpetrated by the Ottoman Turks in 1915, people whose ancestors became refugees a century ago in Syria and now, ironically, a century later they follow their ancestors’ paths, turning into refugees themselves in their historical homeland, facing various difficulties, among them socio-economic, socio-ideological, and identity and gender issues, the latter being the main topic of discussion in the present paper. The situation presented above makes us discuss certain questions within this study: how do Syrian-Armenian refugees define themselves and their status? Which are their gender roles in the socio-economic context? How do social and economic challenges re-shape Syrian-Armenian women refugees’ identities? The study applies qualitative research methods of analysis, which includes semi-structured and in-depth interviews with 15 participants (18-25, 26-40 age groups), and two focus group works, involving 8 participants (18-35 age group) for each focus group activity. The activities were carried out in October 2016, Yerevan, Armenia. The study also includes Secondary Data Analysis. In addition, in order to centralize refugee women’s experiences and identity issues, the study adopts a qualitative lens from a feminist standpoint position. It is based on the assumption that human activity structures and limits understanding, and that the distorted comprehension of events or activities has emerged from the male-oriented dominant judgement which can be discovered through uncovering the understanding of the situation from women’s activity perspectives. The findings suggest that identity is dynamic, complex, over-changing and sensitive to time and space, gender and class. The process of re-shaping identity is even more complicated and multi-layered and is based on internal and external factors, conditioned by individual and collective needs and interests. Refugees are mostly considered as people who lost their identity in the past since they have no longer connection anywhere and try to find it in the present. In turn, female refugees, being a more vulnerable class, go through more complicated identity re-formulating discourse negotiations. They stand between the borders of the old and new, borders of lost and re-found selves, borders of creating and self-fashioning, between illusions and the challenging reality. Particularly, refugee women become more sensitive within the discourses of the private and the public domains: some of them try to create a ‘new-self’, creating their space in a new society, whereas others try to negotiate their affective/emotional labour within their own family domains.

Keywords: feminist standpoint position, gender, identity, refugee studies, Syrian-Armenian women refugees

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Authors: Zachary Blanks, Solomon Sonya

Abstract:

Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Men An Pan, Ho Hsiung Huang, Jui Chuan Lin, Tsui Hsun Wu, Hsing Yuan Yen

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Pingtung County, located in the southernmost region of Taiwan, has the largest number of pig farms in the country. In the past, livestock operators in Dongpian Village discharged their wastewater into the nearby water bodies, causing water pollution in the local rivers and polluting the air with the stench of the pig excrement. These resulted in many complaints from the local residents. In response to a long time fighting back of the community against the livestock farms due to the confrict, the County Government's Environmental Protection Bureau (PTEPB) examined potential wayouts in addition to heavy fines to the perpetrators. Through helping the livestock farms to upgrade their pollution prevention equipment, promoting the reuse of biogas residue and slurry from the pig excrement, and environmental education, the confrict was successfully resolved. The properly treated wastewater from the livestock farms has been freely provided to the neighboring farmlands via pipelines and tankers. Thus, extensive cultivation of bananas, papaya, red dragon fruit, Inca nut, and cocoa has resulted in 34% resource utilization of biogas residue as a fertilizer. This has encouraged farmers to reduce chemical fertilizers and use microbial materials like photosynthetic bacteria after banning herbicides while lowering the cost of wastewater treatment in livestock farms and alleviating environmental pollution simultaneously. That is, the livestock farms fully demonstrate the determination to fulfill their corporate social responsibility (CSR). Due to the success, Eight farms jointly established a social enterprise - "Dongpian Gemstone Village Co., Ltd." to promote organic farming through a "shared farm." The company appropriates 5% of its total revenue back to the community through caregiving services for the elderly and a fund for young local farmers. The community adopted the Satoyama Initiative in accordance with the Conference of the CBD COP10. Through the positive impact of environmental education, the community seeks to realize the coexistence between society and nature while maintaining and developing socio-economic activities (including agriculture) with respect for nature and building a harmonic relationship between humans and nature. By way of sustainable management of resources and ensuring biodiversity, the community is transforming into a socio-ecological production landscape. Apart from nature conservation and watercourse ecology, preserving local culture is also a key focus of the environmental education. To mitigate the impact of global warming and climate change, the community and the government have worked together to develop a disaster prevention and relief system, strive to establish a low-carbon emitting homeland, and become a model for resilient communities. By the power of environmental education, this community has turned its residents’ hearts and minds into concrete action, fulfilled social responsibility, and moved towards realizing the UN SDGs. Even though it is not the only community to integrate government agencies, research institutions, and NGOs for environmental education, it is a prime example of a low-carbon sustainable community that achieves more than 9 SDGs, including responsible consumption and production, climate change action, and diverse partnerships. The community is also leveraging environmental education to become a net-zero carbon community targeted by COP26.

Keywords: environmental education, biogas residue, biogas slurry, CSR, SDGs, climate change, net-zero carbon emissions

Procedia PDF Downloads 118