Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game

The deployment of small cell networks is seen as a major feature of the next generation of wireless networks. In this paper, a novel approach for cell association in small cell networks is proposed. The proposed approach exploits new types of information extracted from the users' devices and environment to improve the way in which users are assigned to their serving base stations. Examples of such context information include the devices' screen size and the users' trajectory. The problem is formulated as a matching game with externalities and a new, distributed algorithm is proposed to solve this game. The proposed algorithm is shown to reach a stable matching whose properties are studied. Simulation results show that the proposed context-aware matching approach yields significant performance gains, in terms of the average utility per user, when compared with a classical max-SINR approach.Comment: 11 pages, 11 figures, Journal article in ICST Wireless Spectrum, 201

Antitumour Promoting Activity And Mode Of Action Of Methanolic Extracts Of Selected Malaysian Seaweeds And Oil Palm Fronds

Dietary and non dietary biophenols may potentially be chemoprotective against various cancers. This research aims to investigate the cancer preventive and tumoricidal properties of selected Malaysian seaweeds and oil palm leaves as a source of phenolic compounds. Initially, the anti-proliferation activities of, red (Eucheuma cottonii), green (Caulerpa lentillifera) and brown (Sargassum polycystum) seaweeds methanolic extract, against five important human cancer cell lines MCF-7, (human breast carcinoma cell line, estrogen positive) MDA-MB-231, (human breast carcinoma cell line, estrogen negative) HeLa, (human cervical adenocarcinoma cell line) HepG2, (human hepatocellular carcinoma cell line) HT-29, (human colon carcinoma) and normal Vero (African green monkey kidney cell line) were assessed. The MTT assays indicated that the 3 seaweeds extracts were cytotoxic against all these cancer cell lines in a dose-dependent manner,with Eucheuma cottonii having the greatest inhibition activity

A Novel Approach to Predict the Helpfulness of Online Reviews

Online reviews help consumers reduce uncertainty and risks faced in purchase decision making by providing information about products and services. However, the overwhelming amount of data continually being produced in online review platforms introduce a challenge for customers to read and judge the reviews. This research addresses the problem of misleading and overloaded information by developing a novel approach to predict the helpfulness of online reviews. The proposed approach in this study, first, clusters reviews using reviewer-related, and temporal factors. It then uses review-related factors to predict online review helpfulness in each cluster. Using a sample of Amazon.com reviews, the empirical findings offer strong support to the proposed approach and show its superior predictions of review helpfulness compared to earlier approaches. The outcomes of this study help customers in online shopping and assist online retailers in reducing information overload to improve their customers’ experience