Effect of aberrations and scatter on image resolution assessed by adaptive optics retinal section imaging

The effect of increased high-order wavefront aberrations on image resolution was investigated, and the performance of adaptive optics (AO) for correcting wavefront error in the presence of increased light scatter was assessed in a model eye. An AO section imaging system provided an oblique view of a model retina and incorporated a wavefront sensor and deformable mirror for measurement and compensation of wavefront aberrations. Image resolution was quantified by the width of a Lorentzian curve fitted to a laser line image. Wavefront aberrations were significantly reduced with AO, resulting in improvement of image resolution. In the model eye, image resolution was degraded with increased high-order wavefront aberrations (horizontal coma and spherical) and improved with AO correction of wavefront error in the presence of increased light scatter. The findings of the current study suggest that AO imaging systems can potentially improve image resolution in aging eyes with increased aberrations and scatter.     

Hemodialysis cost in Tehran,Iran

The purpose of this study was to assess the health service cost of hemodialysis (HD) delivered at hospitals in Iran as a developing country with a well‐defined program of renal replacement therapy. A cost analysis was performed from the viewpoint of the 2 hospitals, with 3 shifts and full chairs, on current practice for dialysis maintenance. Cost and patient data were collected in 2006 and from April 1 to May 31, 2007, respectively. A total of 22,464 HD sessions were performed and 247 patients were studied during the study period. The reference year for the value of USD for different mentioned costs was 2006. Health care sector costs associated with each HD session were estimated at US$78.87. Most of the total maintenance expenditure was made up of medical supplies (36.19%), with dialyzers as the major cost driver. Staff salaries represented 17% of the cost and fixed direct capital costs accounted for 21.4%. Of the family members, 32.4% accompanied their patients. The mean cost for transportation of patients and accompanied person was US$3.15 ± 2.83 and US$1.5 ± 0.29, respectively. These findings are important in the light of limited available resources coupled with the increasing prevalence of kidney failure. A major attempt should also be made to increase peritoneal dialysis coverage as in some centers we cannot keep all chairs full, especially in some vast areas. It is highly recommended to place initial focus on strategies and treatments that slow disease progression, to postpone renal replacement therapy to save resources.     

Limited contiguous processor allocation mechanism in the mesh-connected multiprocessors using compaction

In this paper, several efficient migration and allocation strategies have been compared on the mesh-based multiprocessor systems. The traditional non-preemptive submesh allocation strategies consist of two row boundary (TRB) and two column boundary (TCB). The existing migration mechanisms are online dynamic compaction-four corner (ODC-FC), limited top-down compaction (LTDC), TCB, and the combination of TCB and ODC-FC algorithms. Indeed, the new allocation method is presented in this paper. This mechanism has the benefits of two efficient traditional allocation algorithms. It is the combination of the TCB and TRB allocation methods. Also, in this process the impact of four key metrics on online mapping is considered. The parameters are average task execution time (ATET), average task system utilization (ATSU), average task waiting time (ATWT), and average task response time (ATRT). Using TCB and TRB mechanism with the migration strategies is shown that the new algorithm has better ATET, ATRT, ATWT, and ATSU. It has, respectively, 23.5494, 97.1216, 39.1291, and 4.142% improvements in comparison with the previous mechanisms.     

Scalable structure-free data fusion on wireless sensor networks

Recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and minimize the energy consumption. In this research, a distributed, dynamic fusion algorithm is introduced. Since the proposed method is dynamic, the number of neighbors sending data to a node is not known in advance. So in order to increase the chances of different data to meet, the node waiting time is calculated. By the end of waiting time, the node performs data fusion and sends the fused data to the best neighbor chosen by the proposed best neighbor algorithm. This procedure continues until data reaches the sink. The proposed algorithm, while being scalable and convergent, outperforms similar methods in terms of number of transmissions, traffic load and energy consumption.     

Adaptive Markov-based approach for dynamic virtual machine consolidation in cloud data centers with quality-of-service constraints

Dynamic virtual machine (VM) consolidation is one of the emerging technologies that has been considered for low-cost computing in cloud data centers. Quality-of-service (QoS) assurance is one of the challenging issues in the VM consolidation problem since it is directly affected by the increase of resource utilization due to the consolidations. In this paper, we take advantage of Markov chain models to propose a novel approach for VM consolidation that can be used to explicitly set a desired level of QoS constraint in a data center to ensure the QoS goals while improving system utilization. For this purpose, an energy-efficient and QoS-aware best fit decreasing algorithm for VM placement is proposed, which considers QoS objective when determining the location of a migrating VM. This algorithm employs an online transition matrix estimator method to deal with the nonstationary nature of real workload data. We also propose new policies for detecting overloaded and underloaded hosts. The performance of our proposed algorithms is evaluated through simulations. The results show that the proposed VM consolidation algorithms in this paper outperforms the benchmark algorithms in terms of energy consumption, service-level agreement violations, and other cost factors.     

A stochastic process-based server consolidation approach for dynamic workloads in cloud data centers

The Journal of Supercomputing - With the development of information technology, there is a need for computational works everywhere and every time. Thus, people should be able to carry out their...