Manual Testing Method Research Articles

Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.

Deep learning is a transformative force in the medical field and it has made significant progress as a pivotal alternative to conventional manual testing methods. Detection of Tubercle Bacilli in sputum samples is faced with the problems of complex backgrounds, tiny and numerous objects, and human observation over a long time not only causes eye fatigue, but also greatly increases the error rate of subjective judgement. To solve these problems, we optimize YOLOv8s model and propose a new detection algorithm, Lite-YOLOv8. Firstly, the Lite-C2f module is used to ensure accuracy by significantly reducing the number of parameters. Secondly, a lightweight down-sampling module is introduced to reduce the common feature information loss. Finally, the NWD loss is utilized to mitigate the impact of small object positional bias on the IoU. On the public Tubercle Bacilli datasets, the mean average precision of 86.3% was achieved, with an improvement of 2.2%, 1.5%, and 2.8% over the baseline model (YOLOv8s) in terms of mAP0.5, precision, and recall, respectively. In addition, the parameters reduced from 11.2 to 5.1 M, and the number of GFLOPs from 28.8 to 13.8. Our model is not only more lightweight, but also more accurate, thus it can be easily deployed on computing-poor medical devices to provide greater convenience to doctors.

Myofascial release in the treatment of lumbar pain in pregnant women

The prevalence of back pain in pregnant women is quite high nowadays. A special place is given to myofascial pain. They progress with the course of pregnancy and can lead to a decrease in a woman’s quality of life. However, the issues of back pain treatment, including the selection of methods and doctors training, still remain unresolved. The aim of our work was to identify the effect of manual therapy (in particular, myofascial release) on the dynamics of pain syndrome in pregnant women with low back pain. Material and methods. The study involved 90 patients of the MIRT Medical Center (Krasnoyarsk) with myofascial lumbosacral pain syndrome at different gestation phases. We used myofascial release techniques and training device to retrained their muscular system. We evaluated the effectiveness of treatment by using a visual analog scale of pain, test with two scales (patented model) and manual muscle testing methods. Results and discussion. The average pain score was 5 points before treatment and 0.6 points after treatment. Pain completely disappeared in most patients after treatment. The maximum decrease in pain score showed women in the third trimester. The pathological difference in the load on the limbs after treatment was 17 times less than before treatment, for all trimesters in general. In the first trimester it was not detected at all. The study revealed correlation between the pain syndrome and positive sacroiliac ligament compression test. Conclusions. We have developed a general scheme for examination and treatment of back pain in pregnant using patented technologies and myofascial release technics. It has proven to be effective in reducing lower back pain at different gestation phases. Tension in the sacroiliac ligaments should be investigated in the future and taken into account for back pain treatment of pregnant women, as well as at pregnancy planning stage.

Overall Scheme Design of Fault Diagnosis for Complex Electronic Systems

Traditional manual testing methods are no longer able to meet the maintenance needs of modern shipboard fire control system board-level circuits. Therefore, the development of intelligent and universal automatic test systems has become an important issue for shipboard fire control system fault detection. This article analyzes the performance and functional requirements of the automatic test system, develops the automatic test system based on PXI bus instruments, and designs an overall solution with signal time-frequency analysis capabilities that can carry out intelligent fault diagnosis for a variety of board-level circuits. On this basis, the design of hardware circuit and software solution is completed. The automatic test system was analyzed on hardware indicators and software functions. On the hardware side, the hardware resource selection was completed based on the hardware indicator requirements. On the software side, the overall software architecture design and the design of each functional module were completed based on the system software functional requirements. Finally, the composition and functions of each module of the system software and the overall operation process are introduced.

Design of Fault Diagnosis Method Based on Circuit Frequency Domain Characteristics Fault Dictionary Method

In recent years, with the rapid development of integrated circuits and the widespread application of smart chips, the internal structure of complex electronic systems have become increasingly complex, which greatly increases the difficulty of board-level circuit testing and fault diagnosis of complex electronic systems. At present, traditional manual testing methods are no longer able to meet the maintenance requirements of modern complex electronic system board-level circuit. Therefore, the development of intelligent and universal automatic testing systems has become an important issue in fault detection of complex electronic systems. Based on the testing requirements of the automatic test system(ATS), this paper designs the corresponding overall scheme, software scheme and hardware circuit, and studies the fault diagnosis and test of board-level circuit of complex electronic system, and proposes to apply the traditional Bode diagram to the engineering practice of ATS. Fault detection is realized by utilizing the frequency domain characteristics of the object under test.

DBTL bioengineering cycle for part characterization and refactoring

The Design-Build-Test-Learn (DBTL) cycle is a crucial framework in Synthetic Biology for the development and optimization of biological systems. However, the manual nature of the cycle poses limitations in terms of time and labor. This paper focuses on the application of automation techniques to the DBTL cycle, specifically in the testing and characterization of standard bioparts, which are essential components of genetic circuits. By automating the testing process, throughput, reliability, and reproducibility can be significantly improved. This paper discusses the challenges associated with manual testing methods and explores various automation strategies and technologies that can address these challenges. High-throughput screening methods, laboratory robotics, and data analysis algorithms are key elements in the automation process. As a case study, we utilize the automated DBTL cycle to refactor a biosensor, aiming to enhance its performance. Integrating automation in the DBTL cycle offers numerous advantages, including increased efficiency, standardization, and quality control of bioparts. It also enables the exploration of larger design spaces and rapid prototyping of complex genetic systems. Here, we show the advantages of using the DBTL cycle to refactor a biosensor that presents improved performance and can be readily used in more complex circuits.

Relationship Between Gestational Diabetes Mellitus and Postpartum Diastasis Recti Abdominis in Women in the First Year Postdelivery.

Postpartum diastasis recti abdominis (DRA) influences women's appearance and health. Gestational diabetes mellitus (GDM) can affect the structure of the rectus abdominis muscles. However, the relationship between GDM and postpartum DRA is unknown. The objective of this study was to investigate the relationship between GDM and postpartum DRA. This retrospective cohort study included 241 women in the first year postdelivery. Women with GDM were matched with those without GDM using propensity score matching. They underwent an oral glucose tolerance test during pregnancy and a random blood glucose test before delivery. At follow-up, DRA was diagnosed by palpation, and interrectus distance was measured using ultrasound to evaluate the severity of DRA. The strength of the rectus abdominis was evaluated using the manual muscle testing method. Among the 241 participants, 174 (72.2%) had postpartum DRA, and 46 women with GDM were matched with 46 women without GDM on the basis of propensity scores. Women with GDM had higher odds of experiencing postpartum DRA (adjusted odds ratio = 4.792; 95% CI = 1.672 to 13.736) and larger interrectus distance values at the upper part of the rectus abdominis than those without GDM. There was a weak and positive correlation between the fasting oral glucose tolerance test level and the interrectus distance values (0.267 ≤ r ≤ 0.367). GDM was associated with postpartum DRA in women in the first year of delivery. Women with GDM had larger interrectus distance values at the upper part of the rectus abdominis than those without GDM. The fasting oral glucose tolerance test level showed a positive and weak correlation with the severity of postpartum DRA. Women with GDM have higher odds of experiencing postpartum DRA than those without GDM. The upper part of the rectus abdominis deserves increased focus during and after rehabilitation. Controlling the fasting oral glucose tolerance test level may help reduce the severity of postpartum DRA.

Advances in Machine Learning and Hyperspectral Imaging in the Food Supply Chain

Food quality and safety are the essential hot issues of social concern. In recent years, there has been a growing demand for real-time food information, and non-destructive testing is gradually replacing traditional manual sensory testing and chemical analysis methods with lagging and destructive effects and has strong potential for application in the food supply chain. With the maturity and development of computer science and spectroscopic techniques, machine learning and hyperspectral imaging (HSI) have been widely demonstrated as efficient detection techniques that can be applied to rapidly evaluate sensory characteristics and quality attributes of food products nondestructively and efficiently. This paper first briefly described the basic concepts of hyperspectral imaging and machine learning, including the imaging process of HSI, the type of algorithms contained in machine learning, and the data processing flow. Secondly, this paper provided an objective and comprehensive overview of the current applications of machine learning and HSI in the food supply chain for sorting, packaging, transportation, storage, and sales, based on the state-of-art literature from 2017 to 2022. Finally, the potential of the technology is further discussed to provide optimized ideas for practical application.

Penerapan Normalisasi Data Dalam Mengelompokkan Data Mahasiswa Dengan Menggunakan Metode K-Means Untuk Menentukan Prioritas Bantuan Uang Kuliah Tunggal

At Budi Darma University there are obstacles in providing UKT rocks where it is profitable and less targeted for students who get it. This happened because those who deserved this assistance were students who had difficulty in costs, therefore we needed a way by grouping student data based on their social level. In determining the students who deserve to get the rock, they can use the data of students who are undergoing their studies at Budi Darma University. By digging up information based on student data. So that the data can be used first, the data normalization is carried out in order to obtain more accurate data. Where student data can be grouped correctly, data normalization must be carried out. One of the normalization methods that are often used in normalizing data is the decimal scaling method which is a data transformation method with normalization to equalize the range of values ​​on each attribute with a certain scale by moving the decimal value from data in the desired direction After the data is normalized, the next process is to explore student data information by applying data mining. The application of data mining is carried out to obtain information in the form of student data groups that are used as a priority in obtaining UKT assistance. The method used in classifying student data is using the K-Means algorithm. The manual testing method is that there are 3 clusters where the number of clusters 0 cluster 1 and cluster 3 is the same as testing data mining applications, namely rapidminer so that those who deserve to be prioritized get tuition assistance based on the sample, namely cluster / grouping 0 which consists of 22 people. This study aims to see the effect of applying data normalization in the K-Means method to classify student data which is used as a recommendation in the selection of UKT assistance.

Validation and Cultural Adaptation of the Serbian Version of the Pediatric Outcome Data Collection Instrument (PODCI) in Children with Obstetrical Brachial Plexus Lesion.

Background and objectives: Pediatric Outcome Data Collection Instrument (PODCI) is among the most described scales developed to evaluate the physical status of children and adolescents with various musculoskeletal disorders. We aimed to translate PODCI from English to Serbian, culturally adopt items and domains, evaluate the temporal stability, internal consistency and the test–retest reliability of PODCISR in children with obstetrical brachial plexus lesion (OBPL), and finally, to test the construct validity of PODCISR against muscular manual test (MMT) Materials and Methods: The study included 48 eligible participants aged between 2 and 10 years with OBPL. The MMT was used to test the construct validity. Results: There were no significant differences (p > 0.05) between test and retest for all PODCISR domains. Correlations for all tested domains with MMT were statistically significant except for biceps muscle and domains II and IV. Cronbach’s alpha value of the Global Functioning Scale was good and equaled 0.838 for test and 0.832 for retest session. Cronbach’s α was more than 0.600 for all PODCISR domains except for Domain II and for Domain IV. The observed Test–Retest ICC for all PODCISR domains scores ranged from 0.899 to 0.996. Conclusion: The Serbian version of PODCI (PODCISR) was successfully translated and transculturally adopted. It has satisfactory temporal stability, construct validity and test–retest reliability as well as relevant internal consistency.

Data Detection Device for Turret Motion Image Using Photoelectric Tracking Control System and Its Performance Analysis

The photoelectric tracking control system is a system composed of photoelectric signal detection, signal processing, servo control system and mechanical structure, which plays a crucial role in the field of target tracking. The turret needs to be tested when it leaves the factory, including high-low direction, horizontal direction, aiming speed and other indicators. Moreover, there are large errors in the manual testing methods such as recorder and recording pen, so the photoelectric tracking device is used for the detection of the turret system. First, the hardware of the photoelectric tracking system is designed, including the main control circuit, peripheral expansion module circuit, intelligent power drive circuit and a detection circuit. The system is connected to the camera. The optical signal sent by the system will hit the fixed target. The upper computer will track the trajectory of the light in real-time and then track the trajectory of the turret to obtain the coordinates of the optical signal and the offset angular velocity of the turret. First, color conversion is conducted on the image data collected by photoelectric tracking through the weighted average method. The complete motion path of the turret is obtained through an image denoising algorithm to obtain the motion speed of the turret. In the test, the photoelectric tracking system is first connected to the motor, and enters a stable state when the motor rotor is 80 ms. The rotor speed is faster. When the rotor speed decreases, the system’s current ripple is large, and then decreases rapidly. After the control system is installed in the turret, its display can be driven by FPGA programming. The VGA display of influence time is set, the editing program is downloaded to the FPGA development board, and the gray image of the turret motion track can be seen through the VGA display.

PREVALENCE OF LOWER CROSSED SYNDROME IN ADULT MALES WITH SEDENTARY LIFESTYLE

Background: Sedentary lifestyle is dened as performing less than 25-30 minutes of physical activity per day. Sedentary lifestyle may cause Lower-crossed syndrome (LCS) as, in sitting posture the hip and back muscles do zero work and the entire work is done by the chair sitting upon. Objective: To check the tightness and weakness of the lower body muscles and there by determine the cause for alteration in low back posture. Method: 100 Subjects with sedentary lifestyle were selected. Weakness of abdominals, gluteus maximum, gluteus medius and gluteus minimus was checked by manual muscle testing method. Tightness of iliopoas, hamstrings, and erector spinae muscles was checked using Thomas test, 90- 90 straight leg test & muscle length respectively. Erector spinae &TFL tightness was seen more in age group of 31-35 yrs which wasResults: (57.38% & 14.28 %) respectively. All the gluteal muscles (minimus, medius, maximus) showed grade 4 weakness in all the age groups. Conclusion: Tightness & weakness was found in some of the muscle groups followed LCS pattern in all the age groups.

An Online Fully-Automatic High Precision Monitoring System of Steam Dryness Based on Spectral Absorption Characteristics

Steam dryness detection is crucial in the field of oil exploitation. A steam dryness too high will be dangerous, whereas a low steam dryness too low will affect the efficiency of extraction. Therefore, real-time, high-precision detection of steam dryness is essential. The methods for detecting steam dryness include chemical, thermodynamic, radiometric, and microwave. The manual test method possesses the best detection accuracy. However, the real-time performance is not good, and the detection process is cumbersome. This article uses a silver nitrate solution to titrate chloride ions and combine them with the change in the absorbance of the solution to determine the endpoint of the titration. This article reported that the automatic chloride ion concentration measurement was a rep and that the detection of chloride ion concentration was 15 mg l−1. The detection linearity reached 0.992. Therefore, our titration endpoint judgment method has better anti-interference.

A Hemolysis Image Detection Method Based on GAN-CNN-ELM.

Since manual hemolysis test methods are given priority with practical experience and its cost is high, the characteristics of hemolysis images are studied. A hemolysis image detection method based on generative adversarial networks (GANs) and convolutional neural networks (CNNs) with extreme learning machine (ELM) is proposed. First, the image enhancement and data enhancement are performed on a sample set, and GAN is used to expand the sample data volume. Second, CNN is used to extract the feature vectors of the processed images and label eigenvectors with one-hot encoding. Third, the feature matrix is input to the map in the ELM network to minimize the error and obtain the optimal weight by training. Finally, the image to be detected is input to the trained model, and the image with the greatest probability is selected as the final category. Through model comparison experiments, the results show that the hemolysis image detection method based on the GAN-CNN-ELM model is better than GAN-CNN, GAN-ELM, GAN-ELM-L1, GAN-SVM, GAN-CNN-SVM, and CNN-ELM in accuracy and speed, and the accuracy rate is 98.91%.

The relationship between the exercise capacity and somatotype components, body composition, and quadriceps strength in individuals with coronary artery disease

Goal: The purpose of this cross-sectional study was to explore a possible relationship between exercise capacity and somatotype components, body composition, and quadriceps strength in individuals with coroner artery disease (CAD) Material and Methods: A convenient sample size of 60 participants between the ages of 45 and 60 years (mean age 56.6 ±4.7; 12 females [mean age 57.7±3.01], 48 males [mean age;56.3±5.1] was established from patients referred to the Department of the Cardiopulmonary Rehabilitation. The exercise was assessed using graded symptom-limited exercise testing while Participants' body composition was detected via Bioelectrical impedance analysis (BIA) technique by using TANITA SC-330 (TANITA, Tokyo, Japan). Finally, quadriceps femoris muscles testing was conducted with Dr Robert W. Lovett’s manual muscle testing method. Results: In the whole sample, exercise capacity was found to be negatively and weakly correlated with the endomorph component (r = - 0.39), whereas a slight and positive correlation was observed between the ectomorph component and exercise capacity (r = 0.28). However, the correlations revealed between exercise capacity and somatotype components differentiated with gender-based analysis. A moderate and weak correlation was found out between exercise capacity and fat mass (FM) in the whole group and the male individuals (r1=-0.45 and r2=-0.34), respectively; in contrast, there was not a meaningful correlation between the same variables in the female individuals(r=-0.002). Exercise capacity had slight and negative relationships with free-fat mass variable (FFM) in both gender (r1 = -0.28 and r2=-0.29), while small to moderate relationship with fat-mass variable (FM) in the male gender (r1=-0.34). Body composition elements, including FM, FFM and BMI, together explained a % 24 of variance in exercise capacity, while somatotype components together explained a % 16 of variance in the exercise capacity. Finally, quadriceps femoris strength was found to be the best predictor of exercise capacity of a patient with CAD (R2=0.44 or % 44) Conclusion: Our results suggest that exercise capacity in individuals with CAD is directly associated with somatotype components, anthropometry/body composition elements, and quadriceps strength.

Research and Application of Remote Control Test Method of Amplifier Indicators

As we all know, there are many test indicators for amplifiers, including saturated output power, 1dB compressed output power (P-1), harmonic suppression, etc. The saturated output power and 1dB compressed output power are tested step by step, and the harmonic suppression needs to traverse every frequency point to calculate the results, which require testers to pay more time and effort. When there are batches of power amplifiers to be tested, manual testing methods are unrealistic. In order to simplify the test steps, reduce the input of testers, and speed up the test progress, this article introduces a test method about instrument remote control, based on GPIB and C# after the study and research for the GPIB bus of the GPIB instrument. This method calls the VISA library to drive the GPIB card to communicate with the test instrument by SCPI programmable instrument standard commands and the respective remote control commands of each instrument to perform mixed programming with C#. Finally, we can complete the measurement, display and get the data by controlling the GPIB instruments on the PC side.

Spasticity syndrome in cerebral pathology: evaluation and clinical models

Knowing the frequency of spasticity patterns in different muscles allows correcting the botulinum neurotoxin (BoNT) administration schemes and creating spasticity models that could predict the drug consumption and treatment cost.Objective: to develop clinical spasticity models based on the frequencies of the spastic syndrome in the muscles of the extremities in post-stroke patients to optimize BoNT administration.Patients and methods. We examined 129 patients of both sexes aged 61.2±8.0 years with post-stroke spasticity (mean time after the stroke – 4.6±2.2). Twenty-seven muscles were tested for spasticity: shoulder girdle (n=3), upper (n=9) and lower (n=15) extremities. We used the original manual testing methods (MTM) of spasticity and the Tardieu scale (TS).Results and discussion. We observed the following frequencies of spasticity in the arm muscles: pectoralis major, brachioradialis, pronator teres, fl. carpi radialis, fl. digitorum profundus et superfacialis, fl. pollicis long. – over 70%, subscapularis – 61%, brachialis – 56.6%, biceps brachii – 35.8%. Frequencies of spasticity in the leg muscles were: semitendinosus, semimembranosus, fl. digitorum long. – 37.5%, gracilis – 21.4%, cap. med. gastrocnemius – 48%, tibialis post. – 39.2%, soleus – 19.6%, fl. halluces long. – 23%. There was no spasticity in the hip adductors; low spasticity incidence was seen in fl. digitorum brev. et fl. halluces brev. (<10%), tibialis ant., rectus femoris (<5%); biceps femoris, teres major, fl. carpi ulnaris, and cap. lat. gastrocnemius (<2%). Based on the frequency of identified spastic patterns, we created four models of patients with arm spasticity and five models – with leg spasticity with the calculation of the necessary doses of BoNT.Conclusion. We propose several spasticity models, which allow calculating the treatment costs, considering the frequency of involvement of specific muscles in spasticity evaluation, and tracking the rehabilitation follow-up of the patient's transition from one clinical model to another.

Automated Event-Triggered GUI Testing and Bug Reproduction for Non-Android Applications

Today’s mobile gadgets are seamlessly incorporating innovative features demanded by the users. Most often, the applications contain bugs or functionality issues reported by the customers. The developers are responsible for reproducing such reported bugs, which are written in natural languages. Reproducing bugs from bug reports make the bug resolution inefficient. Nowadays, various methods are adopted to reproduce crash reports for android applications. But bug reproduction for non-android applications is still a challenging task. This paper proposes a novel approach that is capable of doing bug reproduction from bug reports to help the developers to solve the functionality issues of non-android applications in an automated manner. This approach uses a UI tester called the GUI engine, which is an excel sheet. The use cases which are to be tested can be filled in the GUI engine. All the use cases are to be filled based on a particular syntax. For that purpose, the developer can make use of a set of yaml files containing all the GUI information for all the screens of the application under test. The use cases are executed in the GUI engine and conclusions are made based on the test result. The GUI engine displays two colors green and red showing the working and failing of GUI components of the application under test. So that the developer can easily identify the failing components and take actions accordingly. The test has been done with more than 1000 test cases for one region and the result shows that almost all GUI components work for this method except for animation. It has tested for software developed for US, Europe, and German regions. Also, the proposed method is found to be much faster and efficient than the existing as well as manual testing methods.

The Assessment of Muscle Strength in Fracture Patients with Manual Muscle Testing: Narrative Literature Review

Decreased muscle strength in fracture patients can be caused by postoperative immobilization, thus requiring early immobilization to accelerate the fracture healing process. The principle of early immobilization is the same as the assessment of muscle strength, namely flexion, extension, and rotation to determine muscle strength in fracture patients. To determine the decrease in muscle strength with the Manual Muscle Testing (MMT) method in fractured and non-fractured patients. Narrative literature review was chosen in this research design. Literature search through seven databases with keywords using boolean operators and found 6533 articles. The selection process is based on several criteria: the publication year 2015-2020, full-text access, National (SINTA) / International (Scimagojr) indexed articles, in English or Indonesian, so that 11 articles were reviewed in this study. MMT is a reliable measurement tool, does not require additional tools to assess muscle strength and is universal (can assess muscle strength in fractures and non-fractures). MMT examination needs to be performed on fracture patients to determine muscle strength to accelerate the muscle recovery process.

Automated Driving License Evaluation

The paper is regarding the automating of driver’s license testing system and updating the results to the person through website and conjointly through registered email. Usually, while driving test the person who requested for license have to be compelled to show his driving skills ahead of the authorities. The person need to operate the vehicle according to several rules. If he fails, he/she are knocked out and have to appear for the driving test next time. The Officials observe mistakes of the applicant physically. The proposed solution for the automation of existing manual test method permits the elimination of intervention of humans and improves the accuracy of driving test thereby going paperless, with Driving Skill Evaluation System. In the proposed system, we have a tendency of taking data from sensor as inputs from hardware simulator and stores into the database. In this system, the person participating in the test are obsereved by sensors. Therefore weather the person is qualified or not is informed to the applicant as well as the authorities. Gradual increase in number of road hazards are due to less practice in driving and illegal driving license given to the unskilled drivers by taking bribe. To beat this drawback, automated driving license test will be advantageous. This solution is introduced for ensuring the quality in approving in license to enhance safety.

Erratum for Khan et al., "Evaluation of the Performance of Manual Antimicrobial Susceptibility Testing Methods and Disk Breakpoints for Stenotrophomonas maltophilia".

Volume 65, no. 5, e02631-20, 2021, https://doi.org/10.1128/AAC.02631-20. We found several typographical errors in our recently published article. The overarching conclusions for the paper remain the same, but some of the data should be changed numerically, as described herein.