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Number of results: 4
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Abstract

The In the paper, we investigate two single processor problems, which deal with the process of negotiation between a producer and a customer about delivery time of final products. This process is modelled by a due interval, which is a generalization of well known classical due date and describes a time interval, in which a job should be finished. In this paper we consider two diffierent mathematical models of due intervals. In both considered problems we should find such a schedule of jobs and such a determination of due intervals to each job, that the generalized cost function is minimized. The cost function is the maximum of the following three weighted parts: the maximum tardiness, the maximum earliness and the maximum due interval size. For the first problem we proved several properties of its optimal solution and next we show the mirror image property for both of considered problems, which helps us to provide an optimal solution for the second problem.
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Abstract

The aim of this study was to establish reference values for 2D and M-mode measurements in Dachshunds. Basic echocardiographic data, including M-mode, 2D and spectral Doppler measurements, was collected, analyzed and compared between 41 healthy Dachshunds and 50 other healthy dogs of similar weight. Echocardiographic reference intervals were prepared for Dachshunds. Dachshunds had a smaller left ventricular diameter in diastole and systole and a thicker septum than other dog breeds. Male Dachshunds had larger diastolic and systolic left ventricular diameter than females. Reference intervals for 2D and M-mode measurements in healthy Dachshunds differ from other dogs of similar weight and should be used for this breed to assess chamber enlargement.
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Abstract

Reference intervals (RIs) are one of the essential elements in the procedure of disease diagnosis. This is especially true for feline species in which RI is less available than in canine species. RIs are affected by biological, geographical and instrumental factors, yet published RIs with incomplete background are popularly used. Inappropriate interpretations of RIs may affect classification of disease and subsequent treatment. In this study, we demonstrated the step-by-step establishment of feline RIs following the American Society for Veterinary Clinical Pathology (ASVCP) reference interval guideline. A total of 51 parameters were examined, including 20 hematology and 31 biochemistry parameters, and the results were compared to one local RI and two foreign RIs. Overall, about 29% (10/35) of tested parameters were different form local RIs and 60% (30/50) were different from the two foreign RIs, highlighting geographical variations. A higher upper reference limit (URL) in red blood cell count (RBC), hematocrit (Hct), Hemoglobin (Hgb), albumin, creatinine and lower URL in potassium and white blood cell count (WBC) were identified, which may impact the interpretation. In addition, statistical analysis of age and gender were factored separately and indicated that 10 parameters were significantly higher in the adult group. For the impact of gender, percentage of basophil and total iron-binding capacity (TIBC) were lower in female and male cats, respectively. In conclusion, we have demonstrated that it is desirable to establish in-house RIs or RIs of local sources. An age specific RI for the geriatric feline population is advisable for better diagnosis and monitoring the disease.
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Abstract

Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.
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