Framework for Identification and Prevention of Direct and Indirect Discrimination using Data mining

Extraction of useful and important information from huge collection of data is known as data mining. Negative social perception about data mining is also there, among which potential privacy invasion and potential discrimination are there. Discrimination involves unequally or unfairly treating people on the basis of their belongings to a specific group. Automated data collection and data mining techniques like classification rule mining have made easier to make automated decisions, like loan granting/denial, insurance premium computation, etc. If the training data sets are biased in what regards discriminatory (sensitive) attributes like age, gender, race, religion, etc., discriminatory decisions may ensue. For this reason, antidiscrimination techniques including discrimination discovery, identification and prevention have been introduced in data mining. Discrimination may of two types, either direct or indirect. Direct discrimination is the one where decisions are taken on basis of sensitive attributes. Indirect discrimination is the one where decisions are made based on non-sensitive attributes which are strongly correlated with biased sensitive ones. In this paper, we are dealing with discrimination prevention in data mining and propose new methods applicable for direct or indirect discrimination prevention individually or both at the same time. We discuss how to clean training data sets and transformed data sets in such a way that direct and/or indirect discriminatory decision rules are converted to legitimate (non-discriminatory) classification rules. We also propose new measures and metrics to analyse the utility of the proposed approaches and we compare these approaches

An Efficient Distributed Task Offloading Scheme for Vehicular Edge Computing Networks

With the recent advancement of vehicular ad-hoc networks (VANETs) or the internet of vehicles (IoVs), vehicles are getting more powerful and generating huge amount of traffic data, including computation-intensive and delay-sensitive applications in the vehicular edge computing (VEC) networks, which are difficult to be processed by an individual vehicular node. These resource-demanding tasks can be transferred to another vehicular node with idle computing resources for processing. Due to high mobility and limited resources of vehicular nodes, it is challenging to execute lengthy computation-intensive tasks until completion within the delay constraint. There is a need to provide an efficient task offloading strategies to support these applications. In this paper, an efficient distributed task offloading scheme is proposed to select nearby vehicles with idle computing resources, to process the tasks in parallel by considering some vital metrics, including link reliability, distance, available computing resources, and relative velocity. In order to complete the lengthy computation-intensive tasks in vehicular edge computing networks, a task is divided into several subtasks before offloading. The performance of the proposed scheme is evaluated in several VEC network conditions. Results show that the proposed computation task offloading scheme achieves better performance in latency, throughput, resource utilization and packet delivery ratio than the existing schemes

QoS-Aware Content Dissemination Based on Integrated Social and Physical Attributes Among Cellular and V2V Users

With the recent advancement in intelligent transportation systems (ITS), the vehicular network has become the major force in content dissemination, and it is essential to improve efficiency in content delivery and quality and service (QoS). The rapid growth in vehicular data traffic and limited resources in the vehicular network have created a bottleneck in content dissemination. In addition, the demand of high data rate, low latency and user's satisfaction on content make content dissemination more challenging. To address the above problem which involves vehicle to vehicle (V2V) peer discovery and resource allocation, we propose an efficient content dissemination scheme which integrates both social and physical attributes of the users. V2V users are paired to share content based on the similarity in their preferences and link reliability, while considering the QoS of vehicle to network (V2N) users in both uplink and downlink phases. Moreover, we present an improved matching algorithm for channel allocation, which maximizes the sum rate of V2V pairs weighted by the intensity of their social relationship. Simulation results demonstrate the performance of the proposed scheme in terms of weighted sum rate and user's satisfaction on content

Gender and Age Interact to Affect Early Outcome after Intracerebral Hemorrhage

BackgroundIntracerebral hemorrhage (ICH) is a common and devastating form of cerebrovascular disease. In ICH, gender differences in outcomes remain relatively understudied but have been examined in other neurological emergencies. Further, a potential effect of age and gender on outcomes after ICH has not been explored. This study was designed to test the hypothesis that age and gender interact to modify neurological outcomes after ICH.MethodsAdult patients admitted with spontaneous primary supratentorial ICH from July 2007 through April 2010 were assessed via retrospective analysis of an existing stroke database at Duke University. Univariate analysis of collected variables was used to compare gender and outcome. Unfavorable outcome was defined as discharge to hospice or death. Using multivariate regression, the combined effect of age and gender on outcome after ICH was analyzed. ResultsIn this study population, women were younger (61.1+14.5 versus 65.8+17.3 years, p=0.03) and more likely to have a history of substance abuse (35% versus 8.9%, p<0.0001) compared to men. Multivariable models demonstrated that advancing age had a greater effect on predicting discharge outcome in women compared to men (p=0.02). For younger patients, female sex was protective; however, at ages greater than 60 years, female sex was a risk factor for discharge to hospice or death.ConclusionWhile independently associated with discharge to hospice or death after ICH, the interaction effect between gender and age demonstrated significantly stronger correlation with early outcome after ICH in a single center cohort. Prospective study is required to verify these findings