scholarly journals A Privacy Protection Model for Patient Data With Multiple Sensitive Attributes

2010 ◽  
pp. 44-60
Author(s):  
Tamas S. Gal ◽  
Zhiyuan Chen ◽  
Aryya Gangopadhyay
Keyword(s):  
Privacy Protection ◽  
Practical Method ◽  
Patient Data ◽  
Experimental Results ◽  
Diagnosis And Treatment ◽  
Data Sets ◽  
New Model ◽  
Sensitive Attribute

The identity of patients must be protected when patient data is shared. The two most commonly used models to protect identity of patients are L-diversity and K-anonymity. However, existing work mainly considers data sets with a single sensitive attribute, while patient data often contain multiple sensitive attributes (e.g., diagnosis and treatment). This chapter shows that although the K-anonymity model can be trivially extended to multiple sensitive attributes, L-diversity model cannot. The reason is that achieving L-diversity for each individual sensitive attribute does not guarantee L-diversity over all sensitive attributes. The authors propose a new model that extends L-diversity and K-anonymity to multiple sensitive attributes and propose a practical method to implement this model. Experimental results demonstrate the effectiveness of this approach.

scholarly journals A Preference Model on Adaptive Affinity Propagation

2018 ◽  
Vol 8 (3) ◽  
pp. 1805 ◽  
Author(s):  
Rina Refianti ◽  
Achmad Benny Mutiara ◽  
Asep Juarna ◽  
Adang Suhendra
Keyword(s):  
Data Clustering ◽  
Message Passing ◽  
Clustering Algorithms ◽  
Experimental Results ◽  
Data Sets ◽  
Similarity Matrix ◽  
Preference Model ◽  
New Model ◽  
Data Points ◽  
Scanning Algorithm

In recent years, two new data clustering algorithms have been proposed. One of them isAffinity Propagation (AP). AP is a new data clustering technique that use iterative message passing and consider all data points as potential exemplars. Two important inputs of AP are a similarity matrix (SM) of the data and the parameter ”preference” p. Although the original AP algorithm has shown much success in data clustering, it still suffer from one limitation: it is not easy to determine the value of the parameter ”preference” p which can result an optimal clustering solution. To resolve this limitation, we propose a new model of the parameter ”preference” p, i.e. it is modeled based on the similarity distribution. Having the SM and p, Modified Adaptive AP (MAAP) procedure is running. MAAP procedure means that we omit the adaptive p-scanning algorithm as in original Adaptive-AP (AAP) procedure. Experimental results on random non-partition and partition data sets show that (i) the proposed algorithm, MAAP-DDP, is slower than original AP for random non-partition dataset, (ii) for random 4-partition dataset and real datasets the proposed algorithm has succeeded to identify clusters according to the number of dataset’s true labels with the execution times that are comparable with those original AP. Beside that the MAAP-DDP algorithm demonstrates more feasible and effective than original AAP procedure.

scholarly journals Authorship Attribution with Topic Models

2014 ◽  
Vol 40 (2) ◽  
pp. 269-310 ◽  
Author(s):  
Yanir Seroussi ◽  
Ingrid Zukerman ◽  
Fabian Bohnert
Keyword(s):  
State Of The Art ◽  
Topic Models ◽  
Experimental Results ◽  
Authorship Attribution ◽  
Data Sets ◽  
New Model ◽  
On Line ◽  
Art Performance

Authorship attribution deals with identifying the authors of anonymous texts. Traditionally, research in this field has focused on formal texts, such as essays and novels, but recently more attention has been given to texts generated by on-line users, such as e-mails and blogs. Authorship attribution of such on-line texts is a more challenging task than traditional authorship attribution, because such texts tend to be short, and the number of candidate authors is often larger than in traditional settings. We address this challenge by using topic models to obtain author representations. In addition to exploring novel ways of applying two popular topic models to this task, we test our new model that projects authors and documents to two disjoint topic spaces. Utilizing our model in authorship attribution yields state-of-the-art performance on several data sets, containing either formal texts written by a few authors or informal texts generated by tens to thousands of on-line users. We also present experimental results that demonstrate the applicability of topical author representations to two other problems: inferring the sentiment polarity of texts, and predicting the ratings that users would give to items such as movies.

scholarly journals Privacy Protection Method for Multiple Sensitive Attributes Based on Strong Rule

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Tong Yi ◽  
Minyong Shi
Keyword(s):  
Association Rules ◽  
Privacy Protection ◽  
Background Knowledge ◽  
Data Publishing ◽  
High Quality ◽  
New Model ◽  
Attack Model ◽  
Protection Method ◽  
Sensitive Attribute ◽  
Almost All

At present, most studies on data publishing only considered single sensitive attribute, and the works on multiple sensitive attributes are still few. And almost all the existing studies on multiple sensitive attributes had not taken the inherent relationship between sensitive attributes into account, so that adversary can use the background knowledge about this relationship to attack the privacy of users. This paper presents an attack model with the association rules between the sensitive attributes and, accordingly, presents a data publication for multiple sensitive attributes. Through proof and analysis, the new model can prevent adversary from using the background knowledge about association rules to attack privacy, and it is able to get high-quality released information. At last, this paper verifies the above conclusion with experiments.

A new medical Internet system in healthcare: innovation of Telegeriatrics and healthcare demands of older patients of different age groups (Preprint)

2020 ◽  
Author(s):  
Yu Gong ◽  
Jianyuan Zhou
Keyword(s):  
Cardiovascular Diseases ◽  
General Practitioners ◽  
Older Patients ◽  
Metabolic Diseases ◽  
Treatment Plan ◽  
Age Groups ◽  
The Elderly ◽  
Diagnosis And Treatment ◽  
World Health ◽  
New Model

BACKGROUND Healthcare for older patients is a worldwide challenge for public health system. A new medical Internet system in healthcare which is a new model of telegeriatrics system has been established. The key innovation is the new telegeriatrics system was conducted jointly by general practitioners in the Community Health Service Center and specialists in university teaching hospital. Unlike the typical telemedicine that has been practiced in other countries, the new model provides a solution for the key issues in telemedicine where a doctor is unable to conduct a direct physical examination and the associated potential diagnostic error. OBJECTIVE This study is to introduce the operation mechanism of the new Telegeriatrics system and analyze healthcare demands of older patients in different age groups applying the new Telegeriatrics system. METHODS 472 older patients (aged≥60) were enrolled and divided into the young older group (aged 60 to 74), the old older group (aged 75 to 89) and the very old group (aged≥90) according to the age stratification of World Health Organization. Proportion of the top 10 diseases of older patients of different age groups was analyzed. RESULTS The process of older patients’ diagnosis and treatment made by specialist and general practitioners formed a closed loop. It ensures the timeliness and effectiveness of diagnosis and treatment of older patients. The treatment effect can be observed by general practitioners and specialist can adjust the treatment plan in time. In this study, it was found that older patients in different age groups have different healthcare demands. Coronary heart disease and type 2 diabetes mellitus were found to be the main diseases of the older patients and the young older patients as well as the old older patients applying Telegeriatrics. CONCLUSIONS The new telegeriatrics system can provide convenient and efficient healthcare services for older patients and overcome the disadvantage of currently used models of telegeriatrics. Older patients in different age groups have different medical care demands. Cardiovascular diseases and metabolic diseases have become the main diseases of the elderly applying the new Telegeriatrics system. Healthcare policy makers should invest more medical resources to the prevention of cardiovascular diseases and metabolic diseases in the elderly.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

Application of a Viscoelastic Model for Polyester Mooring

2010 ◽  
Author(s):  
J. W. Kim ◽  
J. H. Kyoung ◽  
A. Sablok
Keyword(s):  
Material Properties ◽  
Viscoelastic Model ◽  
Practical Method ◽  
Time Dependent ◽  
Mooring Line ◽  
New Model ◽  
Global Performance ◽  
Excitation Period ◽  
Linear Viscoelastic ◽  
Floating Platforms

A new practical method to simulate time-dependent material properties of polyester mooring line is proposed. The time-dependent material properties of polyester rope are modeled with a standard linear solid (SLS) model, which is one of the simplest forms of a linear viscoelastic model. The viscoelastic model simulates most of the mechanical properties of polyester rope such as creep, strain-stress hysteresis and excitation period-dependent stiffness. The strain rate-stress relation of the SLS model has been re-formulated to a stretch-tension relation, which is more suitable for implementation into global performance and mooring analyses tools for floating platforms. The new model has been implemented to a time-domain global performance analysis software and applied to simulate motion of a spar platform with chain-polyester-chain mooring system. The new model provides accurate platform offset without any approximation on the mean environmental load and can simulate the transient effect due to the loss of a mooring line during storm conditions, which has not been possible to simulate using existing dual-stiffness models.

MondoA Drives B-ALL Malignancy through Enhanced Adaptation to Metabolic Stress

Blood ◽  
2021 ◽  
Author(s):  
Alexandra Sipol ◽  
Erik Hameister ◽  
Busheng Xue ◽  
Julia Hofstetter ◽  
Maxim Barenboim ◽  
...  
Keyword(s):  
Stress Responses ◽  
Lymphoblastic Leukemia ◽  
Metabolic Stress ◽  
Tca Cycle ◽  
Underlying Mechanism ◽  
Patient Data ◽  
Data Sets ◽  
Dependent Manner

Cancer cells are in most instances characterized by rapid proliferation and uncontrolled cell division. Hence, they must adapt to proliferation-induced metabolic stress through intrinsic or acquired anti-metabolic stress responses to maintain homeostasis and survival. One mechanism to achieve this is to reprogram gene expression in a metabolism-dependent manner. MondoA (also known as MLXIP), a member of the MYC interactome, has been described as an example of such a metabolic sensor. However, the role of MondoA in malignancy is not fully understood and the underlying mechanism in metabolic responses remains elusive. By assessing patient data sets we found that MondoA overexpression is associated with a worse survival in pediatric common acute lymphoblastic leukemia (B-ALL). Using CRISPR/Cas9 and RNA interference approaches, we observed that MondoA depletion reduces transformational capacity of B-ALL cells in vitro and dramatically inhibits malignant potential in an in vivo mouse model. Interestingly, reduced expression of MondoA in patient data sets correlated with enrichment in metabolic pathways. The loss of MondoA correlated with increased tricarboxylic acid (TCA) cycle activity. Mechanistically, MondoA senses metabolic stress in B-ALL cells by restricting oxidative phosphorylation through reduced PDH activity. Glutamine starvation conditions greatly enhance this effect and highlight the inability to mitigate metabolic stress upon loss of MondoA in B-ALL. Our findings give a novel insight into the function of MondoA in pediatric B-ALL and support the notion that MondoA inhibition in this entity offers a therapeutic opportunity and should be further explored.

scholarly journals Interactive coupling of regional atmosphere with biosphere in the new generation regional climate system model REMO-iMOVE

2014 ◽  
Vol 7 (3) ◽  
pp. 1093-1114 ◽  
Author(s):  
C. Wilhelm ◽  
D. Rechid ◽  
D. Jacob
Keyword(s):  
Land Surface ◽  
Regional Climate ◽  
Regional Model ◽  
Horizontal Resolution ◽  
Soil Conditions ◽  
Data Sets ◽  
Vegetation Phenology ◽  
Land Surface Scheme ◽  
New Model ◽  
Surface Scheme

Abstract. The main objective of this study is the coupling of the regional climate model REMO with a new land surface scheme including dynamic vegetation phenology, and the evaluation of the new model version called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. First, we focus on the documentation of the technical aspects of the new model constituents and the coupling mechanism. The representation of vegetation in iMOVE is based on plant functional types (PFTs). Their geographical distribution is prescribed to the model which can be derived from different land surface data sets. Here, the PFT distribution is derived from the GLOBCOVER 2000 data set which is available on 1 km × 1 km horizontal resolution. Plant physiological processes like photosynthesis, respiration and transpiration are incorporated into the model. The vegetation modules are fully coupled to atmosphere and soil. In this way, plant physiological activity is directly driven by atmospheric and soil conditions at the model time step (two minutes to some seconds). In turn, the vegetation processes and properties influence the exchange of substances, energy and momentum between land and atmosphere. With the new coupled regional model system, dynamic feedbacks between vegetation, soil and atmosphere are represented at regional to local scale. In the evaluation part, we compare simulation results of REMO-iMOVE and of the reference version REMO2009 to multiple observation data sets of temperature, precipitation, latent heat flux, leaf area index and net primary production, in order to investigate the sensitivity of the regional model to the new land surface scheme and to evaluate the performance of both model versions. Simulations for the regional model domain Europe on a horizontal resolution of 0.44° had been carried out for the time period 1995–2005, forced with ECMWF ERA-Interim reanalyses data as lateral boundary conditions. REMO-iMOVE is able to simulate the European climate with the same quality as the parent model REMO2009. Differences in near-surface climate parameters can be restricted to some regions and are mainly related to the new representation of vegetation phenology. The seasonal and interannual variations in growth and senescence of vegetation are captured by the model. The net primary productivity lies in the range of observed values for most European regions. This study reveals the need for implementing vertical soil water dynamics in order to differentiate the access of plants to water due to different rooting depths. This gets especially important if the model will be used in dynamic vegetation studies.

Mixture copulas and insurance applications

2018 ◽  
Vol 12 (2) ◽  
pp. 391-411
Author(s):  
Maissa Tamraz
Keyword(s):  
Joint Distribution ◽  
Stable Distribution ◽  
Random Variable ◽  
Fixed Time ◽  
Collective Model ◽  
Data Sets ◽  
New Model ◽  
Time Period ◽  
Insurance Data ◽  
Dependence Property

AbstractIn the classical collective model over a fixed time period of two insurance portfolios, we are interested, in this contribution, in the models that relate to the joint distributionFof the largest claim amounts observed in both insurance portfolios. Specifically, we consider the tractable model where the claim counting random variableNfollows a discrete-stable distribution with parameters (α,λ). We investigate the dependence property ofFwith respect to both parametersαandλ. Furthermore, we present several applications of the new model to concrete insurance data sets and assess the fit of our new model with respect to other models already considered in some recent contributions. We can see that our model performs well with respect to most data sets.

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