A PAC-Theory of Clustering with Advice

In the absence of domain knowledge, clustering is usually an under-specified task. For any clustering application, one can choose among a variety of different clustering algorithms, along with different preprocessing techniques, that are likely to result in dramatically different answers. Any of these solutions, however, can be acceptable depending on the application, and therefore, it is critical to incorporate prior knowledge about the data and the intended semantics of clustering into the process of clustering model selection. One scenario that we study is when the user (i.e., the domain expert) provides a clustering of a (relatively small) random subset of the data set. The clustering algorithm then uses this kind of ``advice'' to come up with a data representation under which an application of a fixed clustering algorithm (e.g., k-means) results in a partition of the full data set that is aligned with the user's knowledge. We provide ``advice complexity'' of learning a representation in this paradigm. Another form of ``advice'' can be obtained by allowing the clustering algorithm to interact with a domain expert by asking same-cluster queries: ``Do these two instances belong to the same cluster?''. The goal of the clustering algorithm will then be finding a partition of the data set that is consistent with the domain expert's knowledge (yet using only a small number of queries). Aside from studying the ``advice complexity'' (i.e., query complexity) of learning in this model, we investigate the trade-offs between computational and advice complexities of learning, showing that using a little bit of advice can turn an otherwise computationally hard clustering problem into a tractable one. In the second part of this dissertation we study the problem of learning mixture models, where we are given an i.i.d. sample generated from an unknown target from a family of mixture distributions, and want to output a distribution that is close to the target in total variation distance. In particular, given a sample-efficient learner for a base class of distributions (e.g., Gaussians), we show how one can come up with a sample-efficient method for learning mixtures of the base class (e.g., mixtures of k Gaussians). As a byproduct of this analysis, we are able to prove tighter sample complexity bounds for learning various mixture models. We also investigate how having access to the same-cluster queries (i.e., whether two instances were generated from the same mixture component) can help reducing the computational burden of learning within this model. Finally, we take a further step and introduce a novel method for distribution learning via a form of compression. In particular, we ask whether one can compress a large-enough sample set generated from a target distribution (by picking only a few instances from it) in a way that allows recovery of (an approximation to) the target distribution. We prove that if this is the case for all members of a class of distributions, then there is a sample-efficient way of distribution learning with respect to this class. As an application of this novel notion, we settle the sample complexity of learning mixtures of k axis-aligned Gaussian distributions (within logarithmic factors)

Assessment of Flood Hazard using Analytic Hierarchy Process Method (AHP) in Mazandaran Province, Iran

One of the most important steps to prevent and deal with the destructive effects of floods is to identify areas with the highest flood potential in the watershed and its sub-basins. In this research, an attempt was made to determine the regions with the highest capacity of runoff and flood production in Mazandaran Province basin using the hierarchical analysis process (AHP) model. On this basis, six factors including heights, slope, land use, geology, flow accumulation, and rainfall were used. After calculating the final weight of each input factor using the hierarchical process model in ArcGIS (V. 10.5) software, a combination of input layers was used to construct a flooding map of the study area in five different categories including very high, high , Medium, low, and very little. Results showed that 38.79% of the Mazandaran Province, equivalent to the area of 9244.82 km2, has a high and very high flooding hazard. Moreover, almost half of this province, equivalent to the area of 12028.51 km2 has a moderate flooding hazard. The results reveal that flooding hazard at each hydrometric stations was in good agreement with the historical observations of floods, that most of them have the return periods of 50- and 100-year. It implies the high accuracy of the method and the weights assigned to each of the effective factors. This clarifies the usability of this research results for future preventive implementation

Designing an Updatable Long Term Health Insurance

In this paper, we considered the long-term health insurance as a sequence of annual health insurance policies. To improve the disadvantages of long-term health insurance, we specify the optimal contract including optimal insurance premiums and optimal insurance coverage for the healthcare costs using a negotiation model. We considered two case of known and unknown initial health state. The predictive model for healthcare costs was determined as a time series and state-contingent models. Since the health state changes over time, the insured tends not only to be insured against risk according to her health state, but also to be insured against reclassification of risk. The insurer also seeks a fair premium appropriate to the insured's risk. To achieve this, we determined the optimal contract based on the negotiation model, in which the negotiation parameter is calculated based on the Nash solution. The optimal premium is independent of health state so that the insured is safe against reclassification. However, the insurer coverage is state-contingent and protects the insurer from detriment. Moreover, due to the uncertainty in estimating the parameters of the prediction model, we specified the projection interval by using the bootstrap method for optimal insurance premiums in the coming years. Thus, the insured is aware of the premium intervals at the time of signing the contract with the insurer

Graph signature for self-reconfiguration planning of modules with symmetry

In our previous works we had developed a framework for self-reconfiguration planning based on graph signature and graph edit-distance. The graph signature is a fast isomorphism test between different configurations and the graph edit-distance is a similarity metric. But the algorithm is not suitable for modules with symmetry. In this paper we improve the algorithm in order to deal with symmetric modules. Also, we present a new heuristic function to guide the search strategy by penalizing the solutions with more number of actions. The simulation results show the new algorithm not only deals with symmetric modules successfully but also finds better solutions in a shorter time

Phenotype and Genotype Heterogeneity of PLA2G6-Associated Neurodegeneration in a Cohort of Pediatric and Adult Patients

BACKGROUND: Phospholipase-associated neurodegeneration (PLAN) caused by mutations in the PLA2G6 gene is a rare neurodegenerative disorder that presents with four sub-groups. Infantile neuroaxonal dystrophy (INAD) and PLA2G6-related dystonia-parkinsonism are the main two subtypes. In this cohort, we reviewed clinical, imaging, and genetic features of 25 adult and pediatric patients harboring variants in the PLA2G6. METHODS: An extensive review of the patients\u27 data was carried out. Infantile Neuroaxonal Dystrophy Rating Scale (INAD-RS) was used for evaluating the severity and progression of INAD patients. Whole-exome sequencing was used to determine the disease\u27s underlying etiology followed by co-segregation analysis using Sanger sequencing. In silico prediction analysis based on the ACMG recommendation was used to assess the pathogenicity of genetic variants. We aimed to survey a genotype-genotype correlation in PLA2G6 considering all reported disease-causing variants in addition to our patients using the HGMD database and the chi-square statistical approach. RESULTS: Eighteen cases of INAD and 7 cases of late-onset PLAN were enrolled. Among 18 patients with INAD, gross motor regression was the most common presenting symptom. Considering the INAD-RS total score, the mean rate of progression was 0.58 points per month of symptoms (Standard error 0.22, lower 95% - 1.10, and upper 95% - 0.15). Sixty percent of the maximum potential loss in the INAD-RS had occurred within 60 months of symptom onset in INAD patients. Among seven adult cases of PLAN, hypokinesia, tremor, ataxic gate, and cognitive impairment were the most frequent clinical features. Various brain imaging abnormalities were also observed in 26 imaging series of these patients with cerebellar atrophy being the most common finding in more than 50%. Twenty unique variants in 25 patients with PLAN were detected including nine novel variants. Altogether, 107 distinct disease-causing variants from 87 patient were analyzed to establish a genotype-phenotype correlation. The P value of the chi-square test did not indicate a significant relationship between age of disease onset and the distribution of reported variants on PLA2G6. CONCLUSION: PLAN presents with a wide spectrum of clinical symptoms from infancy to adulthood. PLAN should be considered in adult patients with parkinsonism or cognition decline. Based on the current knowledge, it is not possible to foresee the age of disease onset based on the identified genotype

Inequalities in Cultural Capital in Tehran

AbstractCultural turn in contemporary society has undoubtedly turned culture into a major arena for the production and representation of social gaps and inequalities. The interplay of inequalities in access to the capitals and urban life has rarely been a topic for systematic empirical studies in Iran. Relying on a large scale representative survey recently conducted in Tehran, this paper aims to reveal the unequal distribution of cultural capital in Tehran and also to reveal the mechanisms the residents employ both to produce and to display cultural capital. The findings while clarifying the prospects of inequalities in different dimensions of urban cultural capital, highlight the ways cultural capital both affects and is affected by urban [physical] spaces and urban life. This conclusion while uncovering some of the inadequacies related to current cultural capital literature, offers new concepts and spheres by which social inequalities can be conceived in the context of Iranian society

The Youths, Body and Fitness Culture

A recent interest in body issues on the part of academic and scientific circles should be seen as a reaction to the radical changes in relationship between body, economy, technology and society. The growth of nutrition, health and sport technologies along with the increasing importance of agency and consumerism, have turned body and embodiment into major themes in the contemporary society. Drawing on quantitative and qualitative data on young boys and girls having regular sport activity, the present paper aims to reveal the relationship and the feelings they have towards their body. The findings indicate that modernity has made the youths more sensitive towards controlling and disciplining their body. Similarly, the competing discourses in public sphere (including the masculine discourse) act as major references in forming, understanding, and representing the body. In addition to reproducing traditional norms and bodily behaviors, such young boys and girls having regular sport activity, the present paper aims to reveal the relationship and the feelings they have towards their body

Enhanced Finite Element Modeling Of The Thermo-Mechanical Responses Of Jointed PCC Pavements Under Environmental And Traffic Loads

Jointed plain concrete pavements (JPCP) are the most commonly used type of rigid pavement systems and the accurate modeling of their thermo-mechanical responses is of primary importance in a mechanistic-empirical pavement design procedure. In JPCP, the temperature gradient and resulting slab shape play a crucial role in the magnitude of stresses and deflections caused by the superimposed traffic loads. Temperature gradients through the slab depth can produce thermal curling in slabs and can also produce slab expansion and contraction, which leads to the generation of frictional tractions between slabs and foundation. The prediction of these frictional tractions is complicated by the curling of the slabs that causes some portions of the slabs to lose contact with the foundation. From the initial development of pavement analysis software in the early 1970\u27s, it was recognized that the finite element (FE) method was the most appropriate modeling tool, due to its potential ability to capture all the pavement response features. A series of software development efforts have culminated in the production of NYSLAB, a jointed pavement analysis tool that has the capability to predict the complete thermo-mechanical responses, due to the combined effect of environmental and vehicular loads. This Dissertation presents a series of studies conducted toward developing an improved FE-based model to be used in the source code of NYSLAB. A complete review of characteristics and mechanistic behavior of components of JPCP is provided. Detailed mathematical models of pavement slabs, load transfer devices and foundation layers developed in NYSLAB are presented. In addition, the implementation of interface elements used to model the contact between pavement layers is included. These elements have the ability to capture the separation and sliding between pavement layers, due to thermal loads, and calculate the frictional traction at their interface. Finally, a series of parametric studies was carried out to determine that the governing equations that were used to idealize the behavior of JPCP in NYSLAB have been accurately selected and implemented in the FE model. The results presented in these studies highlight the capabilities of NYSLAB in modeling and considering the most important factors that affect the prediction of the stresses and strains produced in concrete slabs

Youth and Academic and Educational Alienation

The empirical studies undertaken on academic culture in Iran suggest an inefficient academic acculturation and students alienation from the structure and process of a desired academic culture. A sense of powerlessness, normlessness, anomie, social isolation and in general strangement from the self, educational processes, unverrsity camp, academic staff members and also from other students is increasingly growing in the minds and feelings of a considerable number of higher education students in humanities and social sciences. Drawing on a mixed methodology, the following paper aims to reconstruct the phenomenology of academic and educational alienation based on students personal lived experience and narrativity. Apart from accounting for internal and external social factors affecting this experience, we have proposed a typology of the types of alienation experienced by different groups of students and the strategies they have adopted to counter it. Results suggest that alienation is directly affected by culture politics and involves different social, psychological, and economic consequences in their lives