Hellman’ s time-memory trade-off is a probabilistic method for inverting one-way functions, using pre-computed data. Hellman introduced this method in 1980 and obtained a lower bound for the success probability of his algorithm. After that, all further analyses of researchers are based on this lower bound. In this paper, we first studied the expected Coverage Rate (ECR) of the Hellman matrices, which are constructed by a single chain. We showed that the ECR of such matrices is maximum and equal to 0. 85. In this process, we find out that there exists a gap between the Hellman’ s lower bound and experimental Coverage Rate of a Hellman matrix. Specifically, this gap is larger, when considering the Hellman matrices constructed with one single chain. So, we are investigated to obtain an accuRate formula for the ECR of a Hellman matrix. Subsequently, we presented a new formula that estimate the ECR of a Hellman matrix more accuRately than the Hellman’ s lower bound. We showed that the given formula is closely match experimental data. In the last, we introduced a new method to construct matrices which have much more ECR than Hellman matrices. In fact, each matrix in this new method is constructed with one single chain, which is non-repeating trajectory from a random point. So, this approach result in a number of matrices that each one contains a chain with variable length. The main advantage of this method is that we have more probability of success than Hellman method, however online time and memory requirements are increased. We have also verified theory of this new method with experimental results.

Background: Epileptic patients (EP) should be free of seizure recurrence (SR). Universal Health Coverage (UHC) was implemented in 2005 in Iran, aiming to tackle obstacles in front of health services' utilization. This study was done in order to assess the SR Rate in EP after UHC implementation. Methods: This study was a prospective time series that was done in rural areas of Falavarjan district in Isfahan province in central Iran from March 2016 to March 2017. 245 patients who suffering from any type of epilepsy and whom epilepsy confirmed by a neurologist, registered. All epileptic patients monitored continuously every month through the study, and the signs or symptoms attributed to the suspected seizure were assessed and referred to a physician for additional assessment and consultation to improve treatment compliance. The patients' data about their demographic characteristics, type of epilepsy, any SR attack, and their risk factors were gathered from their self-files based on the checklists. Results: Despite treatment schedules that were carried out for all EPs, during one year follow up, however, 37 (15. 1%) patients displayed SR attacks. 19 (7. 75%) patients who suffered RS were male with the mean age of 40 ± 13. 5 years, without gender statistical difference (P=0. 810). In patients who had RS, the main causes of lacking adherence to their treatment were forgetting to take medicines in 10 (55. 6%), poverty in 3 (16. 7%), and lacking motivation in 2 (11. 1%) EPs. Conclusion: Following UHC implementation in the primary health delivery system, that neuropsychiatric health packages were integRated, the incidence Rate of SR attack in EPs was low.

Background and Aims: Metal-free and fiber-reinforced composite (FRC) restorations have drawn considerable attention and interest in recent years for restoring in the posterior area due to their improved esthetics. Fracture resistance is one of the most important mechanical properties of materials because of 500-600 N load of occlusion. The restorations should toleRate this load. The purpose of this in vitro study was to compare the fracture resistance of FRC with that of zirconia all-ceramic for posterior partial dentures.Materials and Methods: Forty extracted human intact teeth (20 first premolars and 20 first molars) selected for fabricating 10 pairs of fiber-reinforced composite and 10 pairs of zirconia all-ceramic bridges. After receiving standard tooth preparation, the teeth were mounted with 7.5 mm distance between each other. The bridges were made and cemented on the teeth. Then the restorations were stored in 37oC water for 30 days. The fracture resistance was measured using mechanical testing machine with cross-head speed of 1mm/min. Data were evaluated by Independent sample t test.Results: The mean fracture resistance in the ceramic group was 1329.41 N and for the F.R.C group was 1118.528 N with significant differences between them (P=0.034). The failure modes were mainly cohesive at pontic area for ceramic samples, but adhesive for FRC samples at pontic area.Conclusion: Both systems showed sufficient fracture resistance for using in posterior area.

In this paper, we present a bi-objective virtual-force local search particle swarm optimization (BVFPSO) algorithm to improve the placement of sensors in wireless sensor networks while it simultaneously increases the Coverage Rate and preserves the battery energy of the sensors. Mostly, sensor nodes in a wireless sensor network are first randomly deployed in the target area, and their deployment should be then modified such that some objective functions are obtained. In the proposed BVFPSO algorithm, PSO is used as the basic meta-heuristic algorithm and the virtual-force operator is used as the local search. As far as we know, this is the first time that a bi-objective PSO algorithm has been combined with a virtual force operator to improve the Coverage Rate of sensors while preserving their battery energy. The results of the simulations on some initial random deployments with the different numbers of sensors show that the BVFPSO algorithm by combining two objectives and using virtual-force local search is enabled to achieve a more efficient deployment in comparison to the competitive algorithms PSO, GA, FRED and VFA with providing simultaneously maximum Coverage Rate and the minimum energy consumption.

Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance Rate. In addition, to prevent requests from being rejected when the mobile user leaves the Coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance Rate.

Background: The current study is to evaluate cardiovascular effects of anesthetic medications and volatile anesthetics on cardiac stress using cardiac stress index (CSI) and Rate pressure product (RPP) and to determine which of them in useful in evaluating cardiac stress after comparing results obtained from each method.Materials and methods: 40 patients, 60-80 years old, who were all performed trans abdominal prostatectomy were studied. Patients were divided into two groups, half of patients were placed in group A and the other half in group B. The study was carried out as a blinded study. CSI was measured and evaluated in group A and RPP changes were studied in group B.Results: The mean CSI were 60.25±5.57, 63.05±5.54, 55.75±4.78 and 67.65±4.88 before anesthesia induction, after induction, before surgical incision and in recovery respectively. There was no meaningful difference.RPP mean in four above mentioned stages was 10.15±0.44, 9.9±0.69, 6.8±0.36 and 9.2±0.61 respectively. There was a meaningful difference between RPP in stages before anesthesia induction and before surgical incision (P<0.0001).Conclusion: Considering the obtained results from this study, it can be seen that even in noncardiac surgery, the stress level is high in patients in the stage before surgery. This figure was not clear in RPP index case and was not in accordance with CSI, which means CSI has been able to illustRate existing stress level better and efficiently.

Evaluating the cutting Rate (CR) of stones is important in the cost estimation and the planning of the stone processing plants. This research used regression models to estimate the stones’ CR based on their physico-mechanical characteristics. Stone processing factories in Mahallat City (Markazi province, Iran) were visited, and the CR of diamond circular saws was recorded on six different travertine stones. Next, the stone block samples were collected from the quarries for laboratory tests. Stones’ porosity (n), uniaxial compressive strength (UCS), and Schmidt hammer hardness (SH) were determined in the laboratory as their physico-mechanical characteristics. Correlation relationships of CR with physico-mechanical characteristics were evaluated using simple and multiple regression analyses, and estimator models were developed. Results showed that multiple regression models are more reliable than simple regression for estimating the stones’ CR. The validity of the developed multiple regression models was verified with the published data of one researcher. The findings indicated that these models are accuRate enough for estimating the CR of stones. Consequently, the multiple regression models provide practical advantages for estimating the CR and save time and cost during the planning and design of the stone processing factories.

Background: Due to a strong correlation between maternal mortality Rate (MMR) and developmental indicators, MMR is regarded as a development index in communities. One of the deficiencies in the MMR data registries is the under-reporting due to the rare incidence of maternal mortality in the target population and the diversity of information resources. Methods: This study used a three-source capture-recapture method to estimate the MMR. This method can be used to calculate the under-reporting of different data registries. The sample size included all maternal mortality cases registered between 2010 and 2014 in the National Maternal Survey System, National Organization for Civil Registration, and National Death Registration System. Population estimation models including log-linear models, sample Coverage approach (SCA), and the Akaike’ s information criterion (AIC) were employed by the capture-recapture method. Results: The MMR was estimated to be 22. 15, 21. 49, 19. 55, 19. 77, and 18. 97 per 100000 live births from 2010 to 2014, respectively. The Coverage Rate of the three sources of data was estimated at 73%, 83%, 82%, 80%, and 83% between 2010 and 2014, respectively. Conclusions: The results of the study indicate that the capture-recapture method using three sources of data can be utilized to estimate the MMR with higher validity than using only one data source.