Implementation of brute force algorithm for topology optimisation of wireless networks

The paper discusses the topology optimisation of wireless networks using a brute force algorithm. In order to reduce the computational complexity of the algorithm the multi-thread application has been implemented to conduct the optimisation procedure. The efficiency of the algorithm was verified using an example task where topology of a wireless network has been optimised under various criteria

Relationship of Cyclin D1 expression, Estrogen Receptor status and Histological grading in Invasive Duct Carcinoma of the breast

Invasive duct carcinoma of the breast is a clinically and biologically heterogeneous disease. Histological grading was done according to Modified Bloom and Richardson Grading in 40 cases of formalin fixed, paraffin embedded tissue sections of Invasive duct carcinoma (NST). Estrogen receptor (ER) status and Cyclin D1 expression were detected by standard immunohistochemistry. Cyclin D1 expression was detected in 43% (17 of 40) of cases, and was inversely associated (x2 test) with histological grade (p=0.01). ER immunoreactivity was found in 30% (12 of 40) of patients and was inversely associated with histological grade (p=0.021). Cyclin D1 immunoreactivity was positively associated with estrogen receptor expression (p=0.043). There was no significant correlation with clinical prognostic parameters of age, menopausal status, tumour size and clinical stage

Clinicopathologic characteristics of solid papillary carcinoma of the breast

Solid papillary carcinoma (SPC) of the breast is defined as a “distinctive form of papillary carcinoma characterized by closely apposed expansive, cellular nodules.” This uncommon tumor frequently demonstrates neuroendocrine differentiation. SPCs are staged as in situ tumors, except those that exhibit jagged borders within desmoplastic stroma, or if accompanied by conventional invasive carcinoma, which is separately graded and staged. In this study, we review the immunomorphologic characteristics of SPCs diagnosed at our institution, with a view toward elucidating points of distinction from other mammary carcinomas that manifest neuroendocrine differentiation. A total of 250 cases of in situ and invasive carcinomas with immunohistochemically documented neuroendocrine differentiation, spanning 12 years, were retrieved from the records of the Department of Pathology, Singapore General Hospital. Morphologic review identified 108 (43.2%) cases of SPC (in situ and/or invasive) among this group of tumors. Tumors with SPC components were significantly associated with estrogen receptor, progesterone receptor, and chromogranin A expression, spindled tumor morphology, and older patient age (above median age). In addition, invasive carcinomas with SPC components were more likely to be of smaller size (≤20 mm), low grade (grade 1), and to occur in older patients (above median age), compared with cases of invasive carcinoma lacking an SPC component. In situ SPCs were significantly associated with mucin production and demonstrated improved disease-free survival over cases of conventional ductal carcinoma in situ with neuroendocrine differentiation. Presence of an SPC pattern is associated with favorable clinicopathologic characteristics, with in situ SPCs demonstrating improved disease-free survival, emphasizing the importance of accurately diagnosing this uncommon tumor

Topology Optimisation of Wireless Sensor Networks

Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head

Topology Optimisation of Wireless Sensor Networks

Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head

The computational aspects of estimating the efficiency of wireless networks' topology

Wireless Network has become the critical part of the communication infrastructure in our environment. Nowadays, the using of mobile computing devices such as laptops and Wi-Fi enabled phones in the workplace is increasing. The design of wireless networks for enterprise environments remains a challenging task due to the problem of topological design. In this paper, we discuss the computational aspects of the task of calculation the various criteria of efficiency wireless networks' topology. These criteria determine the different characteristics of wireless networks - the access level of populations to network services, the level of the distributed signal and the level of signal accepted in the city. We use brute force algorithm for comparing the different criteria of efficiency the topology of wireless networks. The brute force algorithm has high computational complexity therefore in our experiments we use parallel computing to solve the problem. For illustration the results we use the task of optimization the Wireless network topology for fragment of Myanmar territory

Expression of FGFR1 is an independent prognostic factor in triple-negative breast cancer

10.1007/s10549-015-3371-xBreast Cancer Research and Treatment151199-11