Automated Algorithms for Detecting and Classifying X-Ray Images of Spine Fractures

This paper emphasizes a faster digital processing time while presenting an accurate method for identifying spinefractures in X-ray pictures. The study focuses on efficiency by utilizing many methods that include picturesegmentation, feature reduction, and image classification. Two important elements are investigated to reducethe classification time: Using feature reduction software and leveraging the capabilities of sophisticated digitalprocessing hardware. The researchers use different algorithms for picture enhancement, including theWiener andKalman filters, and they look into two background correction techniques. The article presents a technique forextracting textural features and evaluates three picture segmentation algorithms and three fractured spine detectionalgorithms using transformdomain, PowerDensity Spectrum(PDS), andHigher-Order Statistics (HOS) for featureextraction.With an emphasis on reducing digital processing time, this all-encompassing method helps to create asimplified system for classifying fractured spine fractures. A feature reduction program code has been built toimprove the processing speed for picture classification. Overall, the proposed approach shows great potential forsignificantly reducing classification time in clinical settings where time is critical. In comparison to other transformdomains, the texture features’ discrete cosine transform (DCT) yielded an exceptional classification rate, and theprocess of extracting features from the transform domain took less time. More capable hardware can also result inquicker execution times for the feature extraction algorithms.

Algorithms for Pre-Compiling Programs by Parallel Compilers

The paper addresses the challenge of transmitting a big number offiles stored in a data center(DC),encrypting them by compilers,and sending them through a network at an acceptable time.Face to the big number offiles,only one compiler may not be sufficient to encrypt data in an acceptable time.In this paper,we consider the problem of several compilers and the objective is tofind an algorithm that can give an efficient schedule for the givenfiles to be compiled by the compilers.The main objective of the work is to minimize the gap in the total size of assignedfiles between compilers.This minimization ensures the fair distribution offiles to different compilers.This problem is considered to be a very hard problem.This paper presents two research axes.Thefirst axis is related to architecture.We propose a novel pre-compiler architecture in this context.The second axis is algorithmic development.We develop six algorithms to solve the problem,in this context.These algorithms are based on the dispatching rules method,decomposition method,and an iterative approach.These algorithms give approximate solutions for the studied problem.An experimental result is imple-mented to show the performance of algorithms.Several indicators are used to measure the performance of the proposed algorithms.In addition,five classes are proposed to test the algorithms with a total of 2350 instances.A comparison between the proposed algorithms is presented in different tables discussed to show the performance of each algorithm.The result showed that the best algorithm is the Iterative-mixed Smallest-Longest-Heuristic(ISL)with a percentage equal to 97.7%and an average running time equal to 0.148 s.All other algorithms did not exceed 22%as a percentage.The best algorithm excluding ISL is Iterative-mixed Longest-Smallest Heuristic(ILS)with a percentage equal to 21,4%and an average running time equal to 0.150 s.