Incorporating Local Data and KL Membership Divergence into Hard C-Means Clustering for Fuzzy and Noise-Robust Data Segmentation

Hard C-means (HCM) and fuzzy C-means (FCM) algorithms are among the most popular ones for data clustering including image data. The HCM algorithm offers each data entity with a cluster membership of 0 or 1. This implies that the entity will be assigned to only one cluster. On the contrary, the FCM algorithm provides an entity with a membership value between 0 and 1, which means that the entity may belong to all clusters but with different membership values. The main disadvantage of both HCM and FCM algorithms is that they cluster an entity based on only its self-features and do not incorporate the influence of the entity’s neighborhoods, which makes clustering prone to additive noise. In this chapter, Kullback-Leibler (KL) membership divergence is incorporated into the HCM for image data clustering. This HCM-KL-based clustering algorithm provides twofold advantage. The first one is that it offers a fuzzification approach to the HCM clustering algorithm. The second one is that by incorporating a local spatial membership function into the HCM objective function, additive noise can be tolerated. Also spatial data is incorporated for more noise-robust clustering

An acoustic sensor transmitter for in situ assessment of water quality and fish behaviour during chemical treatment of a parasite-infected river system : tag design and practical use

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Family Complexity and Parents’ Migration:The Role of Repartnering and Distance to Non-Resident Children

Recent research suggests that the increasing complexity of family life could be a factor in declines in internal migration (long-distance moves within countries). As many separated parents continue to share childcare responsibilities or have visiting arrangements, their mobility is naturally constrained. However, the relationship between family complexity and individual migration behaviour has never been studied explicitly. We compare separated parents with parents in two-parent families in their likelihood of migrating within the Netherlands. We use detailed records of parents’ partnership status and children’s residential situation. An event-history analysis was performed using register-based population data (N = 442,412). We find that separated, single parents are more likely to migrate than those in two-parent families. The same is true for repartnered mothers, while repartnered fathers are about as likely to migrate as fathers in two-parent families. Separated parents’ migration behaviour depends on where their children live. Having non-resident children who live some distance away is associated with a much higher likelihood of migrating than having resident children or non-resident children who live nearby. Having both resident and non-resident children who live nearby—shared residence (i.e. joint physical custody) is likely common in this situation—is associated with a considerably lower likelihood of migrating than having resident children only. Based on our findings, one would expect family complexities stemming from parental separation to be associated with higher rather than lower levels of migration. However, potential future increases in the number of parents who share physical custody after separation might lead to lower migration levels

Assessing performance in health care: A mathematical programming approach for the re-design of primary health care networks

Mathematical models allow studying complex systems. In particular, optimal facility location models provide a sound framework to assess the performance of first-level of health care networks. In this work, a methodology founded on need/offer/demand quantification through a facility location-based mathematical model is proposed to assess the performance of existing networks of Primary Health Care Centers (PHCC) and assist in its re-design. The proposed re-design problem investigates the re-allocation of existing resources within the given infrastructure (existing PHCCs) to better satisfy the estimated health needs of the target population. This problem has not been widely addressed in the open literature despite its paramount importance in modern societies with fast demographic dynamics and constrained investment capacities. The model seeks to optimally assign the required type of service and the corresponding capacity to each PHCC (offer). The objective function to be maximized is the number of (needed) patients’ visits effectively covered by the network (demand). The following constraints are explicitly considered: i) geographic accessibility from need centers to PHCCs, ii) maximum delivery capacity of each service in each PHCC, and iii) total budget regarding fixed, variable, and relocation costs. The proposed methodology was applied to a medium-size city. Results show that the non-attended necessity can be reduced by introducing capacity modifications in the existing network. Moreover, different solutions are obtained if budgetary restrictions or minimum attention volume constraints are included. This reveals how model-based decision support tools can help health decision-makers assessing primary health care network performance.Fil: Elorza, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Moscoso, Nebel Silvana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

The Concept of Archipelagic State and the South China Sea

*洪农,中国南海研究院副研究教授。 **李建伟,中国南海研究院研究员。 ***陈平平,中国南海研究院助理研究员。电子邮箱:[email protected]。［文摘］中国如何设定南沙群岛的基线以及其所主张海域的法律地位将直接决定将要被包括进其主权权利的水域中的航行制度。因此,与领土争端直接有关的国家以及外部国家为确保其最大利益,希望中国这些实践符合《联合国海洋法公约》(以下简称“《公约》冶)。本文作者探讨《公约》第四部分中涉及的原则及其与大陆国家附属洋中群岛的关系,并据此建议群岛国实践的某些原则可以适用于南沙群岛,以平衡以下两种关系:一、沿岸国和该区域众多使用国的需要之间的关系;二、群岛国洋中群岛和大陆国家洋中群岛的权利之间的关系。［Abstract］How China will designate its baselines from the Spratlys ( Nansha Islands in Chinese) and define the legal status of its claimed maritime zones will directly determine the navigation regimes in the waters to be included in its sovereign rights.Therefore countries directly involved in the territorial disputes as well as external countries are interested in making sure such practice is in line with the United Nations Convention on the Law of the Sea (UNCLOS) to guarantee their maximum interests.The authors in this papere xplore the principles of PartIV of UNCLOS and their relations with oceanic archipelagos belonging to continental States.By doing so they suggest that certain principles practiced by archipelagic States could be applied in the Spratlys in order to balance two relations:first,the need of coastal States and that of many user States in this region and second,the rights of oceanic islands of archipelagic States and those of continental States.本文为2010年国家社科基金重大课题《南海地区 国家核心利益的维护策略研究》(项目编号:10zd&013)阶段性成果

Efficient product allocation strategy to enable network-wide risk mitigation

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 65-66).Amgen Inc. currently manufactures, formulates and fills substantially all of their global drug product units in a single primary facility ("Site 1A"). Concerned about the inherent risks posed by the geographic concentration of these activities, Amgen has decided to acquire a new international Risk Mitigation Site ("RMS"), expand existing bulk manufacturing infrastructure at Site 1A, and construct a new formulation and filling facility colocated with Site 1A ("Site IB"). Bringing both sites online in the near future will create a novel operational challenge for Amgen, as it will present a broad range of formulation/fill production allocation decisions that did not previously exist. If per-unit costs (production, logistics, etc.) were considered to be typically higher at either RMS or Site 1A/B, an unconstrained optimization model might suggest filling/finishing all product at whichever site has the lowest average cost. However, we assume that RMS should be able to ramp up to full capacity within 3 months of an adverse occurrence at Site 1A. This translates to a minimum product flow constraint through RMS, irrespective of per unit costs, that will keep the facility sufficiently staffed to prepare for a fast ramp-up. Furthermore, helping Amgen mitigate the risks of geographic concentration, RMS may typically produce only a portion of global demand for any product. Given this situation, this thesis develops a product allocation strategy that will: 1) minimize the financial cost of filling various quantities of drug product at the new facility, yet 2) maintain at RMS the expertise required begin manufacturing all drugs in a short period of time. A mixed-integer linear program ("MILP") was developed to capture variable costs of the formulation & fill process for each drug product ("DP") and market combination. The objective of this model is to minimize total supply chain costs subject to meeting market demand and maintaining a sufficient amount of product flow through the RMS facility. The analysis assumes that the decision to develop fill capacity at both RMS and Site lB is complete and that both facilities will be licensed to fill all products that currently run through Site 1A (i.e. capital investment decisions will not be analyzed in this study). The outcome of this study is a product allocation strategy that minimizes network costs as well as a tool that will enable Amgen to solve for minimal network costs under additional future scenarios.by Roy J. Lehman, III.S.M.M.B.A