Role of Plain Abdominal X-Ray in the Differential Diagnosis of Common Acute Abdominal Conditions in Children at Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State, Nigeria

Background: The plain abdominal x-ray is one of the commonly requested investigations in the children emergency room, paediatric surgical ward and neonatal wards. The short interval required to carry out this investigative procedure and obtain results makes it the first imaging modality used to unravel the different causes of acute abdominal conditions in children. The safety of abdominal x-ray in children makes it attractive for use in paediatric surgical practice as part of routine work-up for undifferentiated acute abdominal conditions and also to diagnose specific causes of acute abdomen in children. Setting: Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State. Objectives: Evaluation of the role of plain abdominal x-ray in diagnosing common acute abdominal conditions in children. Materials and method: Patients admitted to the children emergency room, paediatric surgical wards, children’s ward and neonatal ward who had plain abdominal x-ray as part of their diagnostic work-up were included in the study. They were studied prospectively between March 2011 and April 2021. Results: Three Hundred and Ninety-nine patients who had plain abdominal x-rays as part of their diagnostic work-up were studied. Males were 240 while females were 159, a male to female ratio of 1.5:1. The patients were aged between 1 day to 16 years. Differential diagnoses made with plain abdominal x-ray were intestinal obstruction in 298, perforated viscus 69 patients, intra-abdominal masses 13 patients and location of intra-abdominal foreign body 14. Intestinal obstruction cases in which plain abdominal x-ray played a role in their diagnosis and management included the following: intussusception 66, neonatal sepsis 60, malrotation 48, intestinal atresia 42, anorectal malformation 32, hirschsprung’s disease in 30 cases, pyloric stenosis 24, obstructed hernia 22, post-operative adhesions 16 and intestinal helminthiasis 12. Perforated viscus accounted for 69 indications. Out of these indications, perforated gut in intussusception 19, perforated typhoid ileitis was responsible in 13 cases, gut perforation in blunt abdominal trauma 8, perforation in strangulated hernia 11 cases, perforated gut in malrotation 7, ceacal perforation in hirschsprugs disease 6 and colonic perforation in necrotizing enterocolitis 5 cases. Conclusion: Plain abdominal x-ray remains a role to play in the differential diagnosis and management of common paediatric acute abdominal conditions.

Fault diagnosis for on-board equipment of train control system based on CNN and PSO-SVM hybrid model

Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.

Elementary Analysis on the Technological Features of an Engineering Equipment Facile Diagnosis System

From the point of systemic engineering, the general properties of an engineering equipment fault diagnosis system and the studying object of diagnosis engineering -were discussed. With the developing course of fault diagnosis technology, the relationship between facile diagnosis system and diagnosis engineering were also discussed. The basic structure and feature of a facile diagnosis system -were discussed, and the isomorphic of a facile diagnosis system and precise diagnosis system -was presented. The facile diagnosis requires the perfection of method , pertinence and apriority of knowledge, adaptability of the object being diagnosed and the approach to the aim of the diagnosis result, as -well as th? outstanding of main functions.

Design and Application of a Reconstruction System for Engineering Equipment Fault Diagnosis

It is difficult to develop the corresponding fault diagnosis system and the software reusability is bad because the engineering equipment types are so many and their performance is diverse. This paper discussed the solution to engineering equipment integrated fault diagnosis system based on component technology, put forward the sys- tem model and gave the system frame design process and working principle. The software was designed based on the three-layer hierarchy. It is easy to rease and maintain, and the operation of the software is simple. A kind of new theory and method to develop the engineering equipment fault diagnosis system for the future was provided.

A Fuzzy Mathematics Based Fault Auto-diagnosis System for Vacuum Resin Shot Dosing Equipment

On the basis of the analysis of faults and their causes of vacuum resin shot dosing equipment, the fuzzy model of fault diagnosis for the equipment is constructed, and the fuzzy relationship matrix, the symptom fuzzy vector, the fuzzy compound arithmetic operator, and the diagnosis principle of the model are determined. Then the fault auto-diagnosis system for the equipment is designed , and the functions for real-time monitoring its operation condition and for fault auto diagosis are realized. Finally, the experiments of fault auto-diagnosis are conducted in practical production and the veracity of the system is verified.

Computer-Aided Diagnosis for Tuberculosis Classification with Water Strider Optimization Algorithm

Computer-aided diagnosis(CAD)models exploit artificial intelligence(AI)for chest X-ray(CXR)examination to identify the presence of tuberculosis(TB)and can improve the feasibility and performance of CXR for TB screening and triage.At the same time,CXR interpretation is a time-consuming and subjective process.Furthermore,high resemblance among the radiological patterns of TB and other lung diseases can result in misdiagnosis.Therefore,computer-aided diagnosis(CAD)models using machine learning(ML)and deep learning(DL)can be designed for screening TB accurately.With this motivation,this article develops a Water Strider Optimization with Deep Transfer Learning Enabled Tuberculosis Classification(WSODTL-TBC)model on Chest X-rays(CXR).The presented WSODTL-TBC model aims to detect and classify TB on CXR images.Primarily,the WSODTL-TBC model undergoes image filtering techniques to discard the noise content and U-Net-based image segmentation.Besides,a pre-trained residual network with a two-dimensional convolutional neural network(2D-CNN)model is applied to extract feature vectors.In addition,the WSO algorithm with long short-term memory(LSTM)model was employed for identifying and classifying TB,where the WSO algorithm is applied as a hyperparameter optimizer of the LSTM methodology,showing the novelty of the work.The performance validation of the presented WSODTL-TBC model is carried out on the benchmark dataset,and the outcomes were investigated in many aspects.The experimental development pointed out the betterment of the WSODTL-TBC model over existing algorithms.

Comparing upper gastrointestinal X-ray and endoscopy for gastric cancer diagnosis in Korea

AIM:To compare the cost and accuracy of upper gastrointestinal(GI)X-ray and upper endoscopy for diagnosis of gastric cancer using data from the 2002-2004 Korean National Cancer Screening Program(NCSP). METHODS:The study population included 1 503 646 participants in the 2002-2004 stomach cancer screening program who underwent upper GI X-ray or endoscopy.The accuracy of screening was defined as the probability of detecting gastric cancer.We calculated the probability by merging data from the NCSP and the Korea Central Cancer Registry.We estimated the direct costs of the medical examination and the tests for up- per GI X-ray,upper endoscopy,and biopsy. RESULTS:The probability of detecting gastric cancervia upper endoscopy was 2.9-fold higher than via upper GI X-ray.The unit costs of screening using upper GI X-ray and upper endoscopy were$32.67 and$34.89, respectively.In 2008,the estimated cost of identifying one case of gastric cancer was$53094.64 using upper GI X-ray and$16 900.43 using upper endoscopy.The cost to detect one case of gastric cancer was the same for upper GI X-ray and upper endoscopy at a cost ratio of 1:3.7. CONCLUSION:Upper endoscopy is slightly more costly to perform,but the cost to detect one case of gastric cancer is lower.

Screening and early diagnosis of osteoporosis through X-ray and ultrasound based techniques

Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinicallyavailable diagnostic methods are mainly based on the use of either X-rays or ultrasound(US). All X-ray based methods provide a measure of bone mineral density(BMD), but it has been demonstrated that other structural aspects of the bone are important in determining fracture risk, such as mechanical features and elastic properties, which cannot be assessed using densitometric techniques. Among the most commonly used techniques, dual X-ray absorptiometry(DXA) is considered the current 'gold standard' for osteoporosis diagnosis and fracture risk prediction. Unfortunately, as other X-ray based techniques, DXA has specific limitations(e.g., use of ionizing radiation, large size of the equipment, high costs, limited availability) that hinder its application for population screenings and primary care diagnosis. This has resulted in an increasing interest in developing reliable pre-screening tools for osteoporosis such as quantitative ultrasound(QUS) scanners, which do not involve ionizing radiation exposure and represent a cheaper solution exploiting portable and widely available devices. Furthermore, the usefulness of QUS techniques in fracture risk prediction has been proven and, with the last developments, they are also becoming a more and more reliable approach for assessing bone quality. However, the US assessment of osteoporosis is currently used only as a pre-screening tool, requiring a subsequent diagnosis confirmation by means of a DXA evaluation. Here we illustrate the state of art in the early diagnosis of this 'silent disease' and show up recent advances for its prevention and improved management through early diagnosis.

A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.

Exploratory Application of X-ray Photography in the Diagnosis of Poultry Fatty Liver

[Objectives]This study was conducted to explore the application value of X ray in the diagnosis of poultry fatty liver.[Methods]Serum biochemical tests were performed on laying hens with suspected fatty liver.The X-ray liver images of the left lateral position were observed.And the liver traits were observed by anatomy.[Results]The increase in liver space occupying lesion observed by X-ray photography was consistent with the increase in liver volume observed by anatomy.The biochemical test showed slight liver function abnormalities.[Conclusions]X-ray examination can be used for the auxiliary diagnosis of poultry fatty liver.

Application of Transfer Learningin Mechanical Equipment Intelligent Diagnosis:Literature Review

Accelerating the process of intelligent manufacturing and the demand for new industrial productivity,the operating conditions of machinery and equipment have become ever more severe.As an important link to ensure the stable operation of the production process,the condition monitoring and fault diagnosis of equipment have become equally important.The fault diagnosis of equipment in actual production is often challenged by variable working conditions,large differences in data distribution,and lack of labeled samples,etc.Traditional fault diagnosis methods are often difficult to achieve ideal results in these complex environments.Transfer learning(TL)as an emerging technology can effectively utilize existing knowledge and data to improve the diagnostic performance.Firstly,this paper analyzes the trend of mechanical equipment fault diagnosis and explains the basic concept of TL.Then TL based on parameters,TL based on features,TL based on instances and domain adaptive(DA)methods are summarized and analyzed in terms of existing TL methods.Finally,the problems faced in the current TL research are summarized and the future development trend is pointed out.This review aims to help researchers in related fields understand the latest progress of TL and promote the application and development of TL in mechanical equipment diagnosis.

X-ray DIAGNOSIS OF EXTRASKELETAL (SOFT TISSUE) CHONDROSARCOMA (A REPORT OF 8 CASES)

Eight cases of surgically and pathologically verified extraskeletal (soft tissue) chondrosarcoma were analyzed with regard to clinical and X-ray features. The cardinal clinical aspects of this series are: presence of a local soft tissue mass; gradual enlargement of the mass accompanied by increasing pain. The X-ray signs were summarized as follows: formation of a soft tissue mass; various forms of calcifications concentrated in the central area of the tumor; in some instances, presence of a saucer-like defect on the cortical surface of neighbouring bone and periosteal proliferation with mound-like new bone on both sides as well as bending deformity of the affected bone. The incidence and sites of predilection, the main X-ray findings, radiological diagnosis and differential diagnosis of the tumor were discussed. The Roentgen features of synovial chondrosarcoma of the knee joint were especially analyzed.

X-ray DIAGNOSIS OF JUXTACORTICAL CHONDROSARCOMA (A REPORT OF 16 CASES)

The clinical and radiologic features of 16 cases of surgically and pathologically proved juxtacortical chondrosarcoma were analyzed. The main radiograp-hic findings include: (1) A saucerlike or scalloped defect confined to the outer surface of cortex dut to tumor erosion; (2) Localized cortical proliferation and sclerosis; (3) Soft tissue mass and various forms of calcification within the tumor; but without a bony or calcified shell around the tumor mass and (4) sunray and/or laminated periosteal reaction. The origin of this tumor, its histopathology and classification were discussed. A preliminary investigation on the radiated periosteal reaction and its pathological basis was performed.

CHARACTERISTICS AND THEIR CORRECT SELECTION IN THE FAULTS DIAGNOSIS OF HYDRAULIC

The condition characteristics of hydraulic systems reflect running condition for the hydraulic equipment directly. It is the key for condition monitoring and early fault diagnosis to select characteristics reasonably. In this paper, the types, properties of characteristics in hydraulic equipment are analysed, and some considerations in their selection are presented.

Fault diagnosis and analysis of main sea water pump based on vibration monitoring in offshore oil field

The main sea water pump is the key equipment for the floating production storage and offloading （FPSO）. Affected by some factors such as hull deformation, sea water corrosion, rigid base and pipeline stress, the vibration value of main sea water pump in the horizontal direction is abnormally high and malfunctions usually happen. Therefore, it is essential to make fault diagnosis of main sea water pump, By conventional off-line monitoring and vibration amplitude spectrum analysis, the fault cycle is found and the alarm value and stop value of equipment are set, which is helpful to equipment maintenance and accident prevention.

Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical field.Among lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and damage.When an infected person coughs or sneezes,tiny droplets can bring pathogens to others through inhaling.Tuberculosis mainly damages the lungs,but it also affects any part of the body.Moreover,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more important.In our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray images.We proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set types.We also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning models.Our experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image datasets.After training,all models were verified on a pure Vietnamese X-rays set.The results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and accuracy.In the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.

Average Incremental Correlation Analysis Model and Its Application in Fault Diagnosis

The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isotonicity and interference factors independence,and it will not lead to changes of the sequence order relation because of the data transformation.Therefore,the new model keeps good stability.Finally,the incremental average correlation model is applied to failure model analysis of equipment,and an ideal diagnostic effect is obtained.

Value of CT scan in the diagnosis of primary large bowel lymphoma

Objective: To study the CT imaging of primary large bowel lymphoma and evaluate the value of CT scan. Methods: CT reports of 8 patients with proven primary large bowel lymphoma were retrospectively reviewed. Plain CT scans were done on all patients, enhanced CT scans simultaneously with 5-10 mm section thickness, and 5-10 mm table increments in 6 cases. Results: Primary involved sites were on the cecum (n=3), the ascending colon (n=2), and the rectum (n=1). The tumor was found in multiple areas of the large bowel in 2 cases. CT appearance fell into 3 typical patterns in our study. The first was focal mass type in 2 cases, with one combined with intussusception and retroperitoneal adenopathy; the second was segmental annular involvement type in 3 cases, with one of them combined with mesenteric adenopathy; the last was diffuse involvement type in 2 cases. Multiple nodules were seen in the rectum in 1 case. Conclusion: CT was found to be accurate in detecting the primary sites and complications of lymphoma, and evaluating invasion of adjacent structures; Focal mass type, segmental annular involvement type and diffuse involvement type are the main patterns of CT features in the primary large bowel lymphoma; The features revealed by CT scan are suggestive of primary large bowel lymphoma in some cases.

An Improved Biometric Fuzzy Signature with Timestamp of Blockchain Technology for Electrical Equipment Maintenance

The power infrastructure of the power system is massive in size and dispersed throughout the system.Therefore,how to protect the information security in the operation and maintenance of power equipment is a difficult problem.This paper proposes an improved time-stamped blockchain technology biometric fuzzy feature for electrical equipment maintenance.Compared with previous blockchain transactions,the time-stamped fuzzy biometric signature proposed in this paper overcomes the difficulty that the key is easy to be stolen by hackers and can protect the security of information during operation and maintenance.Finally,the effectiveness of the proposed method is verified by experiments.

A Protocol for Digitalized Collection of Traditional Chinese Medicine(TCM)Pulse Information Using Bionic Pulse Diagnosis Equipment

Pulse diagnosis equipment used in Traditional Chinese Medicine(TCM)has long been developed for collecting pulse information and in TCM research.However,it is still difficult to implement pulse taking automatically or efficiently in clinical practice.Here,we present a digital protocol for TCM pulse information collection based on bionic pulse diagnosis equipment,which ensures high efficiency,reliability and data integrity of pulse diagnosis information.A four-degree-of-freedom pulse taking platform together with a wrist bracket can satisfy the spatial positioning and angle requirements for individually adaptive pulse acquisition.Three-dimensional reconstruction of a wrist surface and an image localization model are combined to provide coordinates of the acquisition position and detection direction automatically.Three series elastic joints can not only simulate the TCM pulse taking method that“Three fingers in a straight line,the middle finger determining the‘Guan’location and finger pulp pressing on the radial artery,”but also simultaneously carry out the force-controlled multi-gradient pressing process.In terms of pulse information integrity,this proposed protocol can generate rich pulse information,including basic individual information,pulse localization distribution,multi-gradient dynamic pulse force time series,and objective pulse parameters,which can help establish the fundamental data sets that are required as the pulse phenotype for subsequent comprehensive analysis of pulse diagnosis.The implementation of this scheme is beneficial to promote the standardization of the digitalized collection of pulse information,the effectiveness of detecting abnormal health status,and the promotion of the fundamental and clinical research of TCM,such as TCM pulse phenomics.