Background: For various reasons, inguinal hernia repair under local anaesthesia is not well accepted to both patients and surgeons. The patients fear from pain and surgeons need full relaxation and co-operation to do successful hernia repairMethods: purpose of this study is to evaluate the effectiveness of local anaesthesia in inguinal hernia repair.prospective study was made from January 2011-0ctober 2013 , on a total of 50 patients with inguinal hernia operated on under local anaesthesia. Patients were selected primarily on the basis of their willingness to accept the procedure after the technique was described to them.Results: In this study 50 patient and 58 herniorrhaphies done for them during a period of about 34months were evaluated .A questionnaire was sent to each patient postoperatively to aid in evaluating the subjective reactionto the local anaesthesia. all patients were males ,age range between 31-83 year, median age 51 .types of inguinal hernia were sliding 1case ,pantaloon 5cases ,indirect 28cases ,direct 24 cases ,Rt. Side 27cases, Lt. side 15 cases ,bilateral hernia 8 cases .we give local anesthesia by 2 methodsConclusions: Local anesthesia is without question the safest available technique of anesthesia.Local anesthesia is an extension of the surgical procedure (indeed, often an integral part of that procedure), and as such its administration should be the concern of the surgeon
This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method
... Show MoreTaking into account the significance of food chains in the environment, it demonstrates the interdependence of all living things and has economic implications for people. Hunting cooperation, fear, and intraspecific competition are all included in a food chain model that has been developed and researched. The study tries to comprehend how these elements affect the behavior of species along the food chain. We first examined the suggested model's solution properties before calculating every potential equilibrium point and examining the stability and bifurcation nearby. We have identified the factors that guarantee the global stability of the positive equilibrium point using the geometric approach. Additionally, the circumstances that would gu
... Show MoreIn this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.
In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro
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