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

Leber's Hereditary Optic Neuropathy: A Case Report

Leber's hereditary optic neuropathy (LHON) is a maternally inherited mitochondrial disease that primarily affects the optic nerve, causing bilateral vision loss in juveniles and young adults. A 12-year-old boy had complained of blurred vision in both eyes for more than 1 year. His best-corrected visual acuity was 0.08 in the right eye and 0.1 in the left. Ophthalmologic examination showed bilateral optic disc hyperemia and margin blurring, peripapillary telangiectasis, and a relative afferent pupil defect in his right eye. Fluorescein angiography showed no stain or leakage around the optic disc in the late phase. Visual field analysis showed central scotoma in the left eye and a near-total defect in the right. Upon examination of the patient's mitochondrial DNA, a point mutation at nucleotide position 11778 was found, and the diagnosis of LHON was confirmed. Coenzyme Q10 was used to treat the patient

Obesity and Heart Diseases, a Worsened Epidemic in Recent Decades

Overweight and obesity are major risk factors for a number of chronic diseases, including diabetes, cardiovascular diseases and metabolic diseases. Obesity induces serious heart diseases such as hypertension, heart failure, and coronary disease by multiple mechanisms. The endothelial dysfunction and artherosclerosis induced by obesity lead to the result of coronary artery disease. In addition, obesity is a substantial public health crisis worldwide, and internationally, with the prevalence increasing rapidly in numerous industrialized nations. Worldwide, 39% of adults aged 18 years and over were overweight in 2014, and 13% were obese. The first choice of treatment is weight loss by life-style modification, such as diet and exercise. Medication and surgery are for moderate obese patients with comorbidity. How to find the appropriate method of weight losing is the most important issue

An XCS-Based Intelligent Searching Model for Cross-Organization Identity Management in Web Service

Internet services in distributive organization are normally built on an open network environment. In the environment internet service provisioning cannot be expected executing in a single close organization [1]. Identity management in cross-organization becomes an issue for handling Internet service and distributive business process. The “identity” in cross-organization web service is defined as global identity rather than private identity from client. Global identity searching table that registers all related service organization is the normal way we used to [2]. Through global identity searching table the target service organization can be looked up directly. For some business program, however, global identity is not necessary registered in specific service organization, e.g. IMSI (International Mobile Subscriber Identification) registration in NP (Number Portability) Service [3], for instance. In NP Service each IMSI can be re-assigned to different mobile service provider if the IMSI apply the re-assignment. In the example about IMSI in NP service mentioned above, if there is an internet service will be executed according to identity management with IMSI, then it will be a challenge to find the organization for available IMSI in very short response time. To dynamically re-assign a IMSI in different mobile service provider, the traditional global identity searching table will not be practical due to frequently changing the registration of IMSI in different service provider. To give an intelligent searching model for cross-organization global identity management is a better way than a static global identity searching table management in Web service. In this article the XCS (eXtended Classifier System) classifier system [4] will be proposed as the kernel system. With the characteristics in machine learning and rules management, the XCS-based intelligent searching model can help to predict where the web service can find the global identity in the open and cross-organization environment

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