No abstract

Personally identifiable information (PII) affects individual privacy because PII combinations may yield unique identifications in published data. User PII such as age, race, gender, and zip code contain private information that may assist an adversary in determining the user to whom such information relates. Each item of user PII reveals identity differently, and some types of PII are highly identity vulnerable. More vulnerable types of PII enable unique identification more easily, and their presence in published data increases privacy risks. Existing privacy models treat all types of PII equally from an identity revelation point of view, and they mainly focus on hiding user PII in a crowd of other users. Ignoring the identity vulnerability of each type of PII during anonymization is not an effective method of protecting user privacy in a fine-grained manner. This paper proposes a new anonymization scheme that considers the identity vulnerability of PII to effectively protect user privacy. Data generalization is performed adaptively based on the identity vulnerability of PII as well as diversity to anonymize data. This adaptive generalization effectively enables anonymous data, which protects user identity and private information disclosures while maximizing the utility of data for performing analyses and building classification models. Additionally, the proposed scheme has low computational overheads. The simulation results show the effectiveness of the scheme and verify the aforementioned claims.

This paper presents the flight path planning algorithm in a 3-dimensional environment with fixed obstacles for small unmanned aerial vehicles (SUAVs). The emergence of SUAVs for commercial uses with low-altitude flight necessitates efficient flight path planning concerning economical energy consumption. We propose the visibility roadmap based on the visibility graph approach to deal with this uprising problem. The objective is to approximate the collision-free and energy-efficient flight path of SUAVs for flight missions in a considerable time complexity. Stepwise, we describe the construction of the proposed pathfinding algorithm in a convex static obstacle environment. The theoretical analysis and simulation results prove the effectiveness of our method.

No abstract

Determination of an individual's hepatitis C virus (HCV) genotypes prior to antiviral therapy has become increasingly important for the clinical management and prognosis of HCV infection. Therefore, this study was conducted to investigate the prevalence of HCV genotypes in HCV infected patients of district Bannu in Khyber Pakhtunkhwa region of Pakistan. Serum samples of 117 seropositive patients were screened for HCV-RNA by using reverse transcriptase-nested polymerase chain reaction (RT-nested PCR) and then PCR positive samples were subjected to HCV genotyping. Out of 117 seropositive samples, 110 samples were found positive by PCR analysis. Genotype 3a was the most prevalent one detected in 38% of patients, followed by genotype 3b in 21% of patients, and then genotype 2a in 12% of patients. However 21% of HCV-PCR positive samples could not be genotyped by method used in this study. Genotype 3a was the most prevalent genotype in patients of all age groups and its prevalence was found high among patients with increasing age (>34 years). Moreover, genotypes 3a and 3b were found to be the most prevalent genotypes in patients with history of shaving by barbers, receiving multiple injections, and dental procedures. In conclusion there is need of further investigation of genotypes of HCV by using more sensitive assays and considering large sample size in district Bannu.

No abstract

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements.

A new tricyclic clerodane-type diterpene, nepetolide (1), has been isolated from Nepeta suavis along with three known compounds namely β -sitosterol, stigmasterol, and ursolic acid. The structure elucidation of the isolated compounds was based primarily on two-dimensional (2D)-NMR techniques including correlation spectroscopy (COSY), heteronuclear multiple quantum coherence (HMQC), and heteronuclear multiple bond correlation (HMBC) experiments.