Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks

In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.Comment: To appear in Journal of Computer and System Science

A Clustering-based Location Privacy Protection Scheme for Pervasive Computing

In pervasive computing environments, Location- Based Services (LBSs) are becoming increasingly important due to continuous advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBSs can jeopardize the location privacy of mobile users. Consequently, providing safeguards for location privacy of mobile users against being attacked is an important research issue. In this paper a new scheme for safeguarding location privacy is proposed. Our approach supports location K-anonymity for a wide range of mobile users with their own desired anonymity levels by clustering. The whole area of all users is divided into clusters recursively in order to get the Minimum Bounding Rectangle (MBR). The exact location information of a user is replaced by his MBR. Privacy analysis shows that our approach can achieve high resilience to location privacy threats and provide more privacy than users expect. Complexity analysis shows clusters can be adjusted in real time as mobile users join or leave. Moreover, the clustering algorithms possess strong robustness.Comment: The 3rd IEEE/ACM Int Conf on Cyber, Physical and Social Computing (CPSCom), IEEE, Hangzhou, China, December 18-20, 201

SVMTriP: A Method to Predict Antigenic Epitopes Using Support Vector Machine to Integrate Tri-Peptide Similarity and Propensity

Identifying protein surface regions preferentially recognizable by antibodies (antigenic epitopes) is at the heart of new immuno-diagnostic reagent discovery and vaccine design, and computational methods for antigenic epitope prediction provide crucial means to serve this purpose. Many linear B-cell epitope prediction methods were developed, such as BepiPred, ABCPred, AAP, BCPred, BayesB, BEOracle/BROracle, and BEST, towards this goal. However, effective immunological research demands more robust performance of the prediction method than what the current algorithms could provide. In this work, a new method to predict linear antigenic epitopes is developed; Support Vector Machine has been utilized by combining the Tri-peptide similarity and Propensity scores (SVMTriP). Applied to non-redundant B-cell linear epitopes extracted from IEDB, SVMTriP achieves a sensitivity of 80.1% and a precision of 55.2% with a five-fold cross-validation. The AUC value is 0.702. The combination of similarity and propensity of tri-peptide subsequences can improve the prediction performance for linear B-cell epitopes. Moreover, SVMTriP is capable of recognizing viral peptides from a human protein sequence background. A web server based on our method is constructed for public use. The server and all datasets used in the current study are available at http://sysbio.unl.edu/SVMTriP

VI-Band Follow-Up Observations of Ultra-Long-Period Cepheid Candidates in M31

The ultra-long period Cepheids (ULPCs) are classical Cepheids with pulsation periods exceeding $\approx 80$ days. The intrinsic brightness of ULPCs are ~1 to ~3 mag brighter than their shorter period counterparts. This makes them attractive in future distance scale work to derive distances beyond the limit set by the shorter period Cepheids. We have initiated a program to search for ULPCs in M31, using the single-band data taken from the Palomar Transient Factory, and identified eight possible candidates. In this work, we presented the VI-band follow-up observations of these eight candidates. Based on our VI-band light curves of these candidates and their locations in the color-magnitude diagram and the Period-Wesenheit diagram, we verify two candidates as being truly ULPCs. The six other candidates are most likely other kinds of long-period variables. With the two confirmed M31 ULPCs, we tested the applicability of ULPCs in distance scale work by deriving the distance modulus of M31. It was found to be $\mu_{M31,ULPC}=24.30\pm0.76$ mag. The large error in the derived distance modulus, together with the large intrinsic dispersion of the Period-Wesenheit (PW) relation and the small number of ULPCs in a given host galaxy, means that the question of the suitability of ULPCs as standard candles is still open. Further work is needed to enlarge the sample of calibrating ULPCs and reduce the intrinsic dispersion of the PW relation before re-considering ULPCs as suitable distance indicators.Comment: 13 pages, with 14 Figures and 4 Tables (one online table). AJ accepte

Correlation between Office Locations, Corporate Governance and Business Performance

The concept of “corporate governance” developed in an era marked by global economic liberalization, continuing enterprise expansion, and separation enterprise ownership and management trends. Good corporate governance is important to enhance corporate value and national competitiveness. “Locations” refer to spaces wherein human social activities are held. Office activities have become important economic human activities, and enterprise headquarters are the primary places where enterprises issue orders, carry out corporate control, and make decisions. Hence, they are vital to the overall operation of enterprises. Do the locations of enterprise headquarters influence corporate governance quality, and thus, the overall business performance of enterprises? This research analyzes Taiwan's listed and over-the-counter companies. As per empirical results: (1) Corporate business performance significantly correlates with corporate governance and office locations, with a significant difference between various areas, and (2) the quality of corporate governance of Taiwanese enterprises significantly correlates and varies with their office locations. Keywords: Corporate Governance, Business Performance, Location Theory JEL Classifications: G34, M10, R3