Preserving individual privacy when publishing data is a problem that receiving increasing attention. According to the fc-anonymity principle, each release of must be such indistinguishable from at least k - 1 other individuals. In this paper we study anonymity preserving in moving objects databases. We propose novel concept k-anonymity based on co-localization exploits inherent uncertainty object's whereabouts. Due sampling and positioning systems (e.g., GPS) imprecision, trajectory object...

Despite efforts to explore how employees react corporate social responsibility (CSR), the research on this topic within hospitality industry has yet reach its mature stage. Anchored in exchange theory, present endeavours address critical gap by proposing that employees’ perceptions of CSR lead improved job performance. The study also hypothesizes perceived organizational support (POS) acts as a mediator. Additionally, role gender moderator been proposed. Results based data from 396 hotel...

Learning in a partially observable and nonstationary environment is still one of the challenging problems area multiagent (MA) learning. Reinforcement learning generic method that suits needs MA many aspects. This paper presents two new based domain independent coordination mechanisms for reinforcement learning; multiple agents do not require explicit communication among themselves to learn coordinated behavior. The first mechanism perceptual mechanism, where other are included state...

An important step in annotation of sequenced genomes is the identification transcription factor binding sites. More than a hundred different computational methods have been proposed, and it difficult to make an informed choice. Therefore, robust assessment motif discovery becomes important, both for validation existing tools promising directions future research. We use machine learning perspective analyze collections factors with known Algorithms are presented finding position weight...

This paper presents a privacy-preserving framework for the protection of sensitive positions in real time trajectories. We assume scenario which sensitivity user's is space-varying, and so depends on spatial context, while movement confined to road networks places. Typical users are non-anonymous members geo-social network who agree share their exact position whenever such does not fall within place, e.g. hospital. Suspending location sharing user inside place an appropriate solution because...

The process of discovering relevant patterns holding in a database was first indicated as threat to security by O'Leary in. Since then, many different approaches for knowledge hiding have emerged over the years, mainly context association rules and frequent item sets mining. Following real-world data application demands, this paper, we shift problem contexts where both extracted sequential structure. We define show its NP-hardness. Thus, devise heuristics polynomial sanitization algorithm....

Purpose This study aims to investigate the potential positive correlation between inclusive leadership and hotel frontline employees’ (FLEs) customer stewardship (CS) behavior, using conservation of resource theory as its foundation. It hypothesizes that role breadth self-efficacy (RBSE) acts a mediating factor in this relationship, with employee conscientiousness serving significant moderating variable. Design/methodology/approach A time-lagged survey design was used, spanning over three...

Computational discovery of regulatory elements is an important area bioinformatics research and more than a hundred motif methods have been published. Traditionally, most these addressed the problem single - discovering binding motifs for individual transcription factors. In higher organisms, however, factors usually act in combination with nearby bound to induce specific behaviours. Hence, recent focus has shifted from sets by multiple cooperating factors, so called composite or...

The process of discovering relevant patterns holding in a database, was first indicated as threat to database security by O' Leary [20]. Since then, many different approaches for knowledge hiding have emerged over the years, mainly context association rules and frequent itemsets mining. Following real-world data applications demands, this paper we shift, problem contexts where both arid extracted sequential structure. We provide statement, some theoretical issues including NP-hardness...

Abstract Background With the recent advances and availability of various high-throughput sequencing technologies, data on many molecular aspects, such as gene regulation, chromatin dynamics, three-dimensional organization DNA, are rapidly being generated in an increasing number laboratories. The variation biological context, increasingly dispersed mode generation, imply a need for precise, interoperable flexible representations genomic features through formats that easy to parse. A host...

Data science continues to evolve with each passing day and upgrades itself according the exponentially increasing amount of data. The progression provides convenience extract meaningful information from huge data various domains including individual, public health, micro-blogging sensors. ability process volume valuable sometimes scare people especially when individual sensitive is concerned. Many privacy-preserving techniques are developed overcome these fears. Over years, adapted meet...

Cluster validity investigates whether generated clusters are true or due to chance. This is usually done based on subsampling stability analysis. Related this problem estimating number of in a given dataset. There methods described the literature handle both purposes. In paper, we propose three for confidence clustering result. The first method validates result by employing supervised classifiers. dataset divided into training and test sets accuracy classifier evaluated set. computes...

Computational discovery of motifs in biomolecular sequences is an established field, with applications both the functional sites proteins and regulatory DNA. In recent years there has been increased attention towards composite motifs, typically occurring cis-regulatory regions genes. This paper describes Compo: a discrete approach to motif that supports richer modeling more realistic background model compared previous methods. Furthermore, multiple parameter threshold settings are tested...

This paper addresses the control formulation process for probabilistic boolean genetic networks. It is a major problem that has not been investigated enough yet. We argue monitoring stage necessary after providing guidance about evolution of state. For this purpose, we developed methods generating optimal policies each following five cases: finite control, infinite control-infinite monitoring, control-finite and repeated monitoring. Our initial proposal was based on using action cost...

Spatio-temporal traces left behind by moving individuals are increasingly available. On the one hand, mining this kind of data is expected to produce interesting behavioral knowledge enabling novel classes mobility applications; but on other due peculiar nature position data, it creates important privacy concerns. Thus, studying preserving methods for mov- ing object and challenging. In paper, we address problem hiding sensi- tive trajectory patterns from objects databases. The aim modify...

Knowledge hiding, hiding rules/patterns that are inferable from published data and attributed sensitive, is extensively studied in the literature context of frequent itemsets association rules mining transactional data. The research this thread focused mainly on developing sophisticated methods achieve less distortion quality. With work, we extend item-set to co-occurring itemset problem. Co-occurring those co-exist output mining. What different classical new sensitivity definition: an set...

Increasing popularity of Twitter in politics is subject to commercial and academic interest. To fully exploit the merits this platform, reaching target audience with desired political leanings critical. This paper extends research on inferring orientations users case 2017 Turkish constitutional referendum. After constructing a targeted dataset tweets, we explore several types potential features build accurate machine learning based predictive models. In our experiments, three-class support...

Packet-based mobile networks are increasingly carrying internet traffic mostly for data intensive-applications. Mobile usage, with 67% share worldwide, is very important users. Because of the explosive growth usage demand, speed analysis a essential way to characterize network quality and user experience service providers. Key Performance Indicators (KPIs), measured on segments by current sophisticated systems, may not correctly capture users' Quality Experience (QoE) due actual throughput...