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"Since 1989, Jammu and Kashmir has been affected by conflict between the Indian state and a movement demanding independence. This book explores the effect of that conflict on the Hindu Pandit minority of the Kashmir Valley. The displacement of the Kashmir Pandits has been drastic with the majority having fled Kashmir within the first year of the conflict and relocating to Jammu and elsewhere. They are one of the most prominent internally displaced persons (IDPs) in the region. Kashmiri Pandits are historically associated with state bureaucracies from the precolonial to postcolonial regimes and having been prominent landowners in Kashmir. While Kashmiri nationalism declares independence from the Indian state, the Pandits are located in the union between India and Kashmir. This book attempts to explore their experiences by looking at their relationship to Kashmir and the place they have relocated to, where they have rebuilt their lives. Focusing on camp colonies and the lives of Pandits across the city, the book reveals a tension between the recovery of ordinary life after loss and the inability to feel truly settled and to finds ones place in the world. This book explores how they seek recognition as victims through engagements with political parties, organizations, and organs of the Indian welfare state. But this process is caught in a struggle between the uniqueness of victimhood and the universality of violence and suffering. Thus, this book attempts to understand experiences of dispossession among people who occupy a politically ambivalent location."

"Konsep hypergraph pertama kali dikembangkan oleh Claude Berge pada 1960 untuk menggeneralisasi definisi busur di graf, sehingga alih-alih hanya dapat menghubungkan dua buah simpul secara bersamaan, busur (atau hyperedge) pada hypergraph dapat menghubungkan berapa simpul pun. Pada graf sendiri, keberadaan suatu busur yang tidak selalu bersifat deterministik memberi ruang bagi teori probabilitas maupun teori uncertainty untuk membuat pemetaan φ : E → [0,1] dengan E adalah himpunan busur di suatu graf. Di antara teori probabilitas dan teori uncertainty sendiri terdapat perbedaan, seperti probabilitas memetakan beberapa kejadian yang saling bebas dalam operasi perkalian, sementara uncertainty dalam operasi minimum. Suatu graf yang busur-busurnya mengikuti teori probabilitas (disebut juga graf random) lebih dahulu diperkenalkan oleh Erdo ́s dan Renyi pada 1959. Kemudian Gao & Gao pada 2013 mengaplikasikan teori uncertainty pada graf (disebut juga graf uncertain). Liu, dengan mempertimbangkan bahwa randomness dan uncertainty kerap kali muncul bersamaan, mencetuskan konsep kombinasi teori probabilitas dengan teori uncertainty pada 2013. Teori kombinasi yang disebut teori chance ini berhasil diterapkan juga pada graf dan dikenal sebagai konsep graf uncertain random. Di antara banyak penerapan graf uncertain random, terdapat gagasan pencarian derajat kepercayaan atau indeks dari suatu graf dan salah satunya adalah indeks keterhubungan. Indeks keterhubungan sebagai derajat kepercayaan bahwa suatu graf terhubung dapat dicari menggunakan penghitungan terhadap ukuran chance dari masing-masing busur. Karena konsep graf uncertain random dapat dibatasi pada komponen uncertainty-nya saja, maka definisi indeks keterhubungan juga dapat dimodifikasi agar menjadi well-defined untuk graf uncertain. Sejauh ini kebanyakan penelitian teori uncertainty masih tertuju pada graf klasik dan belum ada penelitian terhadap indeks keterhubungan dari hypergraph meskipun hal ini sangat dibutuhkan sebagai aplikasi dari teori uncertainty. Oleh sebab itu, pada penelitian ini, digeneralisasi konsep indeks keterhubungan pada graf uncertain ke dalam uncertain hypergraph dan dicari sifat-sifatnya, baik yang dianalogikan dari graf uncertain maupun yang baru.

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The hypergraph concept was first developed by Claude Berge in 1960 to generalize the definition of an edge in a graph, so that instead of being only capable to simultaneously connect two vertices, the edge (or hyperedge) in hypergraph is capable to connect any number of vertices. In the graph itself, the existence of an edge that is not always deterministic gives room for probability theory as well as uncertainty theory to make a mapping φ : E → [0, 1] where E is the set of edges in a graph. There are differences between probability theory and the uncertainty theory, such as the way of handling the measure of several independent events which in probability is by multiplication operation, while in uncertainty is by minimum operation. A graph whose edges follow probability theory (also called random graph) was first introduced by Erdo ́s and Renyi in 1959. Then Gao & Gao in 2013 applied the uncertainty theory to a graph (also called uncertain graph). Liu, taking into account that randomness and uncertainty often appear together, coined the concept of combining probability theory with uncertainty theory in 2013. This combined theory called chance theory was also successfully implemented on graph and is known as the uncertain random graph concept. Among the many applications of uncertain random graph, there is the idea of finding the belief degree or the index of a graph and one of them is the connectivity index. Connectivity index as the belief degree that a graph is connected can be found by calculating the chance measure of each edge. Because the concept of an uncertain random graph can be restricted to its uncertainty components only, the definition of connectivity index can also be modified to become well-defined for an uncertain graph. So far, most research on uncertainty theory simply focused on classical graphs and there has been no research on the connectivity index of hypergraph, although this is really needed as an application of uncertainty theory. Therefore, in this study, it is generalized the concept of the connectivity index of an uncertain graph to an uncertain hypergraph, along with its properties, both the analogous one to the uncertain graph and the new one."