Closeness and Residual Closeness of Harary Graphs

Analysis of a network in terms of vulnerability is one of the most significant problems. Graph theory serves as a valuable tool for solving complex network problems, and there exist numerous graph-theoretic parameters to analyze the system's stability. Among these parameters, the closeness parameter stands out as one of the most commonly used vulnerability metric. Its definition has evolved over time to enhance ease of formulation and applicability to disconnected structures. Furthermore, based on the closeness parameter, residual closeness, which is a newer and more sensitive parameter compared to other existing parameters, has been introduced as a new graph vulnerability index by Dangalchev. In this study, the outcomes of the closeness and residual closeness parameters in Harary Graphs have been examined. Harary Graphs are well-known constructs that are distinguished by having $n$ vertices that are $k$-connected with the least possible number of edges.Comment: 21 pages preprin

Parameterized algorithms of fundamental NP-hard problems: a survey

Parameterized computation theory has developed rapidly over the last two decades. In theoretical computer science, it has attracted considerable attention for its theoretical value and significant guidance in many practical applications. We give an overview on parameterized algorithms for some fundamental NP-hard problems, including MaxSAT, Maximum Internal Spanning Trees, Maximum Internal Out-Branching, Planar (Connected) Dominating Set, Feedback Vertex Set, Hyperplane Cover, Vertex Cover, Packing and Matching problems. All of these problems have been widely applied in various areas, such as Internet of Things, Wireless Sensor Networks, Artificial Intelligence, Bioinformatics, Big Data, and so on. In this paper, we are focused on the algorithms’ main idea and algorithmic techniques, and omit the details of them

Visualized Algorithm Engineering on Two Graph Partitioning Problems

Concepts of graph theory are frequently used by computer scientists as abstractions when modeling a problem. Partitioning a graph (or a network) into smaller parts is one of the fundamental algorithmic operations that plays a key role in classifying and clustering. Since the early 1970s, graph partitioning rapidly expanded for applications in wide areas. It applies in both engineering applications, as well as research. Current technology generates massive data (“Big Data”) from business interactions and social exchanges, so high-performance algorithms of partitioning graphs are a critical need. This dissertation presents engineering models for two graph partitioning problems arising from completely different applications, computer networks and arithmetic. The design, analysis, implementation, optimization, and experimental evaluation of these models employ visualization in all aspects. Visualization indicates the performance of the implementation of each Algorithm Engineering work, and also helps to analyze and explore new algorithms to solve the problems. We term this research method as “Visualized Algorithm Engineering (VAE)” to emphasize the contribution of the visualizations in these works. The techniques discussed here apply to a broad area of problems: computer networks, social networks, arithmetic, computer graphics and software engineering. Common terminologies accepted across these disciplines have been used in this dissertation to guarantee practitioners from all fields can understand the concepts we introduce

Undergraduate Management Accounting Research in University of Tanjungpura: Past, Present and Future

This paper provides a review of 168 undergraduate theses submitted between the year 2002 and 2011 in management accounting topics. During this time, there is a changing interest of students in accounting research, especially in topic selection. To review the development of management accounting research in undergraduate level, this paper is structured according to the topics, theories and research methods used. The purposes of this review are to determine the main interest and map the past and current achievement of such research area in University of Tanjungpura. Based on the current trend and international hot debatable topics, the last section of this paper also gives a recommendation about the possible interesting topics for future research. Keywords: Management Accounting, Undergraduate Research, University of Tanjungpura, Research Directions and Bibliographic Stud

Algorithms for Computing Edge-Connected Subgraphs

This thesis concentrates on algorithms for finding all the maximal k-edge-connected components in a given graph G = (V, E) where V and E represent the set of vertices and the set of edges, respectively, which are further used to develop a scale reduction procedure for the maximum clique problem. The proposed scale-reduction approach is based on the observation that a subset C of k + 1 vertices is a clique if and only if one needs to remove at least k edges in order to disconnect the corresponding induced subgraph G[C] (that is, G[C] is k-edge-connected). Thus, any clique consisting of k + 1 or more vertices must be a subset of a single k-edge connected component of the graph. This motivates us to look for subgraphs with edge connectivity at least k in a given graph G, for an appropriately selected k value. We employ the method based on the concept of the auxiliary graph, previously proposed in the literature, for finding all maximal k-edge-connected subgraphs. This method processes the input graph G to construct a tree-like graphic structure A, which stores the information of the edge connectivity between each pair of vertices of the graph G. Moreover, this method could provide us the maximal k-edge-connected components for all possible k and it shares the same vertex set V with the graph G. With the information from the auxiliary graph, we implement the scale reduction procedure for the maximum clique problem on sparse graphs based on the k-edge-connected subgraphs with appropriately selected values of k. Furthermore, we performed computational experiments to evaluate the performance of the proposed scale reduction and compare it to the previously used k-core method. The comparison results present the advancement of the scale reduction with k-edge-connected subgraphs. Even though our scale reduction algorithm based has higher time complexity, it is still of interest and deserves further investigation

Undergraduate Management Accounting Research in University of Tanjungpura: Past, Present and Future

This paper provides a review of 168 undergraduate theses submitted between the year 2002 and 2011 in management accounting topics. During this time, there is a changing interest of students in accounting research, especially in topic selection. To review the development of management accounting research in undergraduate level, this paper is structured according to the topics, theories and research methods used. The purposes of this review are to determine the main interest and map the past and current achievement of such research area in University of Tanjungpura. Based on the current trend and international hot debatable topics, the last section of this paper also gives a recommendation about the possible interesting topics for future research

The Governance Grenade: Mass Privatization, State Capacity and Economic Development in Postcommunist and Reforming Communist Societies.

This article critiques neoliberal transition theory from a state-centered perspective. Neoliberal scholars have used cross-national regression analysis to argue that postcommunist economic failure is the result of inadequate adherence to neoliberal precepts. Sociologists, in turn, have relied on case study data to show that postcommunist economic failure is the outcome of too close adherence to neoliberal policy recommendations, which has led to an erosion of state effectiveness, and thus produced underdevelopment. The present paper advances a version of this statist theory based on a quantitative analysis of mass privatization programs in the postcommunist world. We argue that the neoliberal policy of rapid large-scale privatization creates severe supply and demand shocks for enterprises, thereby inducing firm failure. The resulting erosion of tax revenues leads to a fiscal crisis for the state, and severely weakens its capacity and bureaucratic character. This, in turn, reacts back on the enterprise sector, as the state can no longer support the institutions necessary for the effective functioning of a capitalist economy, thus resulting in de-modernization. In this paper, we test the predictions of neoliberal transition theory against those of our statist theory, using cross-national regression techniques. We find that the implementation of mass privatization programs negatively impacts measures of economic growth, state capacity and the security of property rights.