Quality Assurance Procedures Research Articles

Negotiating quality in open youth work: Balancing standardisation and individualised support

Formal quality assurance procedures in social service organisations are usually closely linked to issues of efficiency and effectiveness. However, there are often doubts as to whether such procedures can also be used profitably for the development of educational practice. In particular, tensions arise between the need for standardisation and comparability of output data on the one hand, and the often low-threshold and individualised support of young people on the other. Drawing on an empirical study in the field of youth work, the article addresses this problem of conflicting quality expectations in state-funded social and educational institutions. Based on expert interviews with youth work practitioners and drawing on neo-institutionalist theoretical concepts, it analyses which strategies and practices are used in open youth work to deal effectively with such contradictory quality expectations. Using a typology of different processing methods, the results show that an important aspect of professional quality action can be seen in the empowering behaviour of professionals and their context-specific interpretation and transformation of external requirements.

Optimization of Tumor Dissection Procedures Leads to Measurable Improvement in the Quality of Molecular Testing

Molecular tests have an inherent limit of detection (LOD) and, therefore, require samples with sufficiently high percentages of neoplastic cells. Many laboratories use tissue dissection; however, optimal procedures for dissection and quality assurance measures have not been established. In this study, several modifications to tissue dissection procedures and workflow were introduced over 4 years. Each modification resulted in a significant improvement in one or more quality assurance measures. The review of materials following dissection resulted in a 90% reduction in KRAS mutations below the stated LOD (P=0.004). Mutation allele frequencies correlated best with estimated tumor percentages for pathologists with more experience in this process. The direct marking of unstained slides, use of a stereomicroscope, validation of extraction from diagnostic slides, and use of a robust, targeted next-generation sequencing platform all resulted in reduction of quantity not sufficient specimens from 20% to 25% to nearly 0%, without a significant increase in test failures or mutations below the LOD. These data indicate that post-dissection review of unstained slides and monitoring quantity not sufficient rate, test failure rate, and mutation allele frequencies are important tumor dissection quality assurance measures that should be considered by laboratories performing tissue dissections. The amendments to tissue dissection procedures enacted during this study resulted in a measurable improvement in the quality and reliability of this process based on these metrics.

Production and Characterization of Rice Flour as Reference Material for Chemical Analysis

Proper application of reference materials (RMs) is one of the key components of the quality assurance procedure used to validate analytical methods and ensure that test data is traceable to a fundamental standard. This study was conducted to develop rice flour as an RM. Locally available commercial rice (Oryza sativa) was sampled from a locally available supermarket, ground, mixed with zinc fortificant, pulverized, and homogenized. Homogeneity of the RM was established following ISO Guide 35:2017. The RM property values for proximate and minerals were obtained through an interlaboratory comparison collaborated by 20 local testing laboratories. Continuous analysis of selected measurands by a credible subcontractor was conducted periodically to monitor its stability. The property values of the spiked rice flour RM, expressed as mean ± expanded uncertainty, were as follows: moisture (9.67 ± 0.87 g/ 100 g), protein (7.06 ± 0.46 g/ 100 g), ash (0.37 ± 0.08 g/ 100 g), potassium (64.03 ± 8.09 mg/ 100 g), and zinc (6.40 ± 1.57 mg/ 100 g). The mean was obtained by ANOVA of the laboratories’ result, whereas the expanded uncertainty was derived from the standard uncertainty associated with heterogeneity, short-term and long-term stability, and characterization of the property value of the RM. Spiked rice flour RM was successfully developed for use by testing laboratories as internal QCTM and for method validation purposes. It is highly recommended that the DOST- FNRI strengthen more its qualification in providing quality yet affordable RMs, following international guidelines.

Quantitation of micro and nanoplastics in human blood by pyrolysis-gas chromatography–mass spectrometry

The limited available data on human internal exposure poses a significant challenge in assessing the risks associated with micro and nanoplastics (MNPs) to human health. A contributing factor to this challenge is the scarcity of sensitive analytical methods to quantify the mass concentration of plastic polymers in human blood. In this study we present an improved and validated method for quantitatively analysing polyethylene (PE), polyethylene terephthalate (PET), poly(vinyl chloride) (PVC), poly(methyl methacrylate) (PMMA), polypropylene, and polystyrene in human whole blood samples. We introduce and apply stringent quality assurance and quality control procedures, including the validation of the method using quality control samples and continuous monitoring of batch analyses to ensure data reliability. Expanding upon prior pioneering work by Leslie et al. (2022), we optimised the pyrolysis-gas chromatography–mass spectrometry (Py-GC-MS) conditions to enhance method sensitivity and selectivity. Recovery experiments demonstrated a high level of accuracy and precision, with values ranging from 68 to 109% for quality control samples. Applying this method to whole blood samples (n = 68), we identified plastic polymers in 64 samples, with PE as the predominant polymer, followed by PVC, PET, and PMMA. In 17 blood samples, polymer concentrations were found to exceed the limit of quantitation, with a mean of 1070 ng/mL for the summed polymer concentrations, ranging between 170 and 2490 ng/mL. The mean of the sum of polymers across all blood samples (n = 68) was 268 ng/mL. These findings underscore the pressing need for further research aimed at comprehensive MNP quantification in human matrices, considering the potential health implications.

Алгоритм моніторингу та перегляду освітніх програм у системі внутрішнього забезпечення якості

The article presents an algorithm for monitoring and periodic review of study programs in the university system for quality assurance in higher education. It is proved that the responsibility for quality assurance in higher education is delegated to the institutional level, where the learning process is directly planned, organized and implemented. The procedures and order of monitoring, periodic review and updating of study programs at five organizational levels of the internal quality assurance system (IQAS) are characterized. It was determined that information about stakeholders' satisfaction of the quality of training and their recommendations for further improvement of study programs is collected at the first level of the IQAS. The second level of IQAS (department) is responsible for monitoring the study programs and periodic review based on changes in the legislative framework, taking into account the best pedagogical education of Ukrainian and foreign universities, the results of stakeholder surveys, etc. Responsible persons of the third level of IQAS (faculty) control the deadlines, the process of preparation and completion of procedures for external quality assurance in higher education, periodic review of study programs, curricula, programs of subjects for their compliance with higher education standards, urgent requirements of the labor market, educational needs and the interests of students. At the fourth level of the IQAS, structural units monitor the content of study programs for compliance with the Licensing Requirements for Educational Activities, the regulatory framework of higher education of Ukraine, and the current regulatory university documents. The fifth level of the IQAS is responsible for monitoring compliance with the requirements of the internal quality assurance system, including the academic integrity system at all organizational levels. It is summarized that compliance with the procedure for monitoring and periodic review of study programs will allow the university to achieve strategic goal of providing high-quality educational services to students based on sustainable cooperation with stakeholders.

A comprehensive pre-clinical treatment quality assurance program using unique spot patterns for proton pencil beam scanning FLASH radiotherapy.

Quality assurance (QA) for ultra-high dose rate (UHDR) irradiation is a crucial aspect in the emerging field of FLASH radiotherapy (FLASH-RT). This innovative treatment approach delivers radiation at UHDR, demanding careful adoption of QA protocols and procedures. A comprehensive understanding of beam properties and dosimetry consistency is vital to ensure the safe and effective delivery of FLASH-RT. To develop a comprehensive pre-treatment QA program for cyclotron-based proton pencil beam scanning (PBS) FLASH-RT. Establish appropriate tolerances for QA items based on this study's outcomes and TG-224 recommendations. A 250 MeV proton spot pattern was designed and implemented using UHDR with a 215nA nozzle beam current. The QA pattern that covers a central uniform field area, various spot spacings, spot delivery modes and scanning directions, and enabling the assessment of absolute, relative and temporal dosimetry QA parameters. A strip ionization chamber array (SICA) and an Advanced Markus chamber were utilized in conjunction with a 2cm polyethylene slab and a range (R80) verification wedge. The data have been monitored for over 3 months. The relative dosimetries were compliant with TG-224. The variations of temporal dosimetry for scanning speed, spot dwell time, and spot transition time were within±1mm/ms,±0.2 ms, and±0.2 ms, respectively. While the beam-to-beam absolute output on the same day reached up to 2.14%, the day-to-day variation was as high as 9.69%. High correlation between the absolute dose and dose rate fluctuations were identified. The dose rate of the central 5×5 cm2 field exhibited variations within 5% of the baseline value (155Gy/s) during an experimental session. A comprehensive QA program for FLASH-RT was developed and effectively assesses the performance of a UHDR delivery system. Establishing tolerances to unify standards and offering direction for future advancements in the evolving FLASH-RT field.

HARNESSING ARTIFICIAL INTELLIGENCE FOR REAL-TIME QUALITY ASSURANCE IN MEDICAL DEVICE MANUFACTURING

The production process for medical devices must precisely follow quality assurance (QA) procedures to comply with the sector's stringent regulatory requirements. Although conventional QA procedures are generally effective, they can be time-consuming and resource-intensive, which can lead to problems and increased costs. With its unprecedented potential for increased productivity, accuracy, and scalability, Artificial Intelligence (AI) has revolutionized quality assurance (QA) approaches across industries since its inception. In this study, we look at how artificial intelligence (AI) could improve medical device quality assurance procedures. Artificial intelligence (AI) methods such as computer vision, machine learning, and natural language processing can automate and optimize critical QA operations, allowing manufacturers to expedite production workflows, while improving product quality. Systems powered by artificial intelligence can sift through mountains of data in search of irregularities, defects, and faults, and they can do it in real-time. This lessens the likelihood of non-compliance problems and enables proactive response. Furthermore, QA systems driven by AI offer the ability to learn and adapt, which allows them to continuously improve performance by analyzing input and meeting evolving regulatory requirements.

Retinopathy of prematurity in Germany over 13 years: incidences, treatment preferences and effects of national guideline changes

ObjectiveRetinopathy of prematurity (ROP) is a leading yet avoidable cause of childhood blindness. Screening for ROP is highly effective in preventing blindness secondary to ROP. We provide epidemiological data on...

An integrated system for measuring 3D dose distributions of carbon-ion pencil beams in regular QA practice

The accurate measurement of three-dimensional (3D) dose distribution of carbon-ion pencil beams in water is crucial for regular quality assurance (QA) practice. Although ionization chambers scanned in a water tank is conventionally used for this purpose, these measuring methods are time-consuming and labor-intensive. In addition, the beam of Heavy Ion Medical Machine (HIMM) changes continuously in each extracted duration, these methods cannot obtain the accurate 3D dose distribution. To solve these problems, an integrated system (PBDOSE) is conceived and established, which employs multi-strip ionization chambers (MSICs) to measure 2D lateral profile dose distributions. The lateral profile dose distribution in the context of various depths is measured by a mobile MSIC and normalized by the measurement of a reference MSIC to reduce the effect of beam instability. On this basis, a 3D dose distribution is created by stacking those profiles in depth direction. By conducting a single depth scan within 3 min at HIMM, information such as the 3D dose distribution, lateral contour images, the Bragg curve, beam spot size, beam position, incident direction, and energy of the beam can be obtained. The Bragg curve acquired from PBDOSE with statistical uncertainties of 1.5% was almost identical to those measured by a commercial water phantom. Besides that, the lateral profiles revealed a remarkable agreement with Gafchromic EBT3 film measurements within differences less than 0.1 mm. PBDOSE shows great prospects in the accurate and efficient measurement of 3D dose distribution for carbon-ion therapy, and the clinical application of this system will improve the efficiency of regular QA procedures to a great extent.

Quality assurance of an established online adaptive radiotherapy program: patch and software upgrade.

The ability to dynamically adjust target contours, derived Boolean structures, and ultimately, the optimized fluence is the end goal of online adaptive radiotherapy (ART). The purpose of this work is to describe the necessary tests to perform after a software patch installation and/or upgrade for an established online ART program. A patch upgrade on a low-field MR Linac system was evaluated for post-software upgrade quality assurance (QA) with current infrastructure of ART workflow on (1) the treatment planning system (TPS) during the initial planning stage and (2) the treatment delivery system (TDS), which is a TPS integrated into the delivery console for online ART planning. Online ART QA procedures recommended for post-software upgrade include: (1) user interface (UI) configuration; (2) TPS beam model consistency; (3) segmentation consistency; (4) dose calculation consistency; (5) optimizer robustness consistency; (6) CT density table consistency; and (7) end-to-end absolute ART dose and predicted dose measured including interruption testing. Differences of calculated doses were evaluated through DVH and/or 3D gamma comparisons. The measured dose was assessed using an MR-compatible A26 ionization chamber in a motion phantom. Segmentation differences were assessed through absolute volume and visual inspection. (1) No UI configuration discrepancies were observed. (2) Dose differences on TPS pre-/post-software upgrade were within 1% for DVH metrics. (3) Differences in segmentation when observed were small in general, with the largest change noted for small-volume regions of interest (ROIs) due to partial volume impact. (4) Agreement between TPS and TDS calculated doses was 99.9% using a 2%/2-mm gamma criteria. (5) Comparison between TPS and online ART plans for a given patient plan showed agreement within 2% for targets and 0.6 cc for organs at risk. (6) Relative electron densities demonstrated comparable agreement between TPS and TDS. (7) ART absolute and predicted measured end-to-end doses were within 1% of calculated TDS. An online ART QA program for post-software upgrade has been developed and implemented on an MR Linac system. Testing mechanics and their respective baselines may vary across institutions, but all necessary components for a post-software upgrade QA have been outlined and detailed. These outlined tests were demonstrated feasible for a low-field MR Linac system; however, the scope of this work may be applied and adapted more broadly to other online ART platforms.

Rapid reviews methods series: guidance on rapid qualitative evidence synthesis

This paper forms part of a series of methodological guidance from the Cochrane Rapid Reviews Methods Group and addresses rapid qualitative evidence syntheses (QESs), which use modified systematic, transparent and...

Spread-out Bragg peak measurements using a compact quality assurance range calorimeter at the Clatterbridge cancer centre

Objective. The superior dose conformity provided by proton therapy relative to conventional x-ray radiotherapy necessitates more rigorous quality assurance (QA) procedures to ensure optimal patient safety. Practically however, time-constraints prevent comprehensive measurements to be made of the proton range in water: a key parameter in ensuring accurate treatment delivery. Approach. A novel scintillator-based device for fast, accurate water-equivalent proton range QA measurements for ocular proton therapy is presented. Experiments were conducted using a compact detector prototype, the quality assurance range calorimeter (QuARC), at the Clatterbridge cancer centre (CCC) in Wirral, UK for the measurement of pristine and spread-out Bragg peaks (SOBPs). The QuARC uses a series of 14 optically-isolated 100 × 100 × 2.85 mm polystyrene scintillator sheets, read out by a series of photodiodes. The detector system is housed in a custom 3D-printed enclosure mounted directly to the nozzle and a numerical model was used to fit measured depth-light curves and correct for scintillator light quenching. Main results. Measurements of the pristine 60 MeV proton Bragg curve found the QuARC able to measure proton ranges accurate to 0.2 mm and reduced QA measurement times from several minutes down to a few seconds. A new framework of the quenching model was deployed to successfully fit depth-light curves of SOBPs with similar range accuracy. Significance. The speed, range accuracy and simplicity of the QuARC make the device a promising candidate for ocular proton range QA. Further work to investigate the performance of SOBP fitting at higher energies/greater depths is warranted.

Characterization of positional accuracy of MLC using an ionization chamber array

PurposeThe purpose of this study is to characterize the positional accuracy of the multileaf collimator (MLC) using an ionization chamber array and develop an MLC quality assurance (QA) method. MethodsHalf of the volume for each ionization chamber located at the lower layer of the device was occluded by a specific leaf using the half-beam block (HBB) method, and the corresponding ionization chamber response was used as a baseline for the subsequent MLC QA study. The sensitivity of the method was assessed by introducing known leaf positional errors, varying from 0.5 to 2.5 mm in 0.5 mm increments in the positive and negative directions, into the baseline. The relative outputs of the detectors were linearly corrected according to the leaf position error recorded. The relationship between detector response variation relative to the baseline and the introduced leaf error was determined by function. The usefulness of the MLC QA technique developed in this study was verified weekly over 5 months. ResultsDuring the development of the algorithm, the maximum leaf absolute random position error was 0.3 mm. A strong linear relationship was observed between the relative output of the detector and the MLC positional error introduced, and the slope and coefficient of determination were −0.05159 and 0.99928, respectively. The mean MLC positional accuracy across all leaves for the error field and HBB baseline field over the 5-month assessment was 0.0649 ± 0.1340 mm and 0.0002± 0.0835 mm, respectively. ConclusionsThe automated MLC QA procedure we proposed has proven to be effective and robust, and satisfies the American Association of Physicists in Medicine (AAPM) Task Group Report 198 guideline criteria of ± 1 mm.

An open flame and smoke detection dataset for deep learning in remote sensing based fire detection

ABSTRACT The early warning of fires is pivotal for preventing substantial economic losses and ecological damage. However, the enhancement of fire model generalization performance still faces challenges due to limitations in existing fire datasets, such as image quantity and heterogeneity. Taking the advantage of rapid advancements in remote sensing technology and artificial intelligence, we introduce the Flame And Smoke Detection Dataset (FASDD), a pioneering collection comprising over 120,000 heterogeneous images covering various fire scenarios, aiming to promote the evolution of fire detection models. FASDD serves as a challenging benchmark for object detection tasks and features three sub-datasets: FASDD_CV, FASDD_UAV, and FASDD_RS. These sub-datasets comprise cross-domain images from ground-based, airborne, and spaceborne sensors, respectively. Extensive experiments using advanced Swin Transformer models demonstrate satisfactory fire detection performance, with mAP scores of 84.9%, 89.7%, and 74.0% on the respective sub-datasets. Notably, the application case in wildfire localization highlights the proficiency of FASDD_RS models for monitoring and tracking forest fires. Trained on FASDD_RS, FASDD_UAV, and FASDD_CV, deep learning models can be individually deployed on edge devices including satellites, drones, and terrestrial sensors, thus empowering collaborative fire warning within the space-air-ground integrated observation network. Additionally, a standardized procedure for data preparation, data procedure, and quality assurance is established, providing off-the-shelf annotations with four common configurations to facilitate machine learning model training. FASDD stands as a pivotal benchmark, providing valuable resources for training and evaluating deep learning fire detection models, especially Large Vision Models (LVM). It holds the potential to accelerate research progress in urban firefighting or forest fire detection, providing vital security measures for early fire warning and emergency response tasks.

Roles and Regulations for Conducting a Surveys Research in Social Studies

The quality of a survey is of prime importance for accurate, reliable and valid results, Survey teams should implement systematic quality assurance procedures to prevent unacceptable practices and to minimize errors in data collection This paper provides a checklist of good practice in the conduct and reporting of survey research, many researchers seek to publish work that uses questionnaires and surveys. Complexities in the use of surveys and questionnaires and the legal and ethical principles that frame their use are often overlooked, resulting in disappointment for authors who seem unaware of the responsibilities editors and reviewers have in relation to these data collection instruments. meaning a standard at which the results will be regarded as credible. Survey research is sometimes regarded as an easy research approach. However as with any other research approach and method, it is easy to conduct a survey of poor quality rather than one of high quality and real value, its purpose is to assist the novice researcher to produce survey work to a high standard, meaning a standard at which the results will be regarded as credible, and how to calculate sample size and how to select sample. It is not intended to provide a manual of how to conduct a survey, but rather to identify common pitfalls and oversights to be avoided by researchers if their work is to be valid and credible.

Abstract PO4-25-12: Improving HER2 Low Scoring Consistency and Accuracy: Insights from the Australian HER2 Low Concordance Study for Invasive Breast Cancer

Abstract Introduction: The Destiny Breast-04 Trial (DB-04) demonstrated the survival benefits of Trastuzumab Deruxtecan (T-DXd) for women with metastatic HER2 Low breast cancer, characterised by 1+ or 2+ IHC staining without amplification. While the DB-04 study applied the standard 2018 ASCO CAP IHC scoring criteria, in clinical practice, distinguishing HER2 0 from 1+ cancers is challenging as i) HER2 Low is not a biologically distinct subset of breast cancer, ii) there are no reference standards for HER2 Low cancers, iii) second-tier test, like ISH, are not applicable, and iv) there are no known controls for cases that have 0 or 1+ HER2 scores. For two decades this distinction was clinically immaterial, but now differentiating between HER2 0 and 1+ has now become crucial for determining patient eligibility for T-DXd therapy. Concerns regarding the subjectivity, imprecision and poor concordance between pathologists in scoring IHC in HER2 Low cancers raise the potential for misalignments in patient treatment. Ensuring pathologists have access to focused training for interpreting IHC scores at the low end of the HER2 expression spectrum, quality assurance procedures and reference sets are essential steps to help pathologists assess HER2 Low breast cancers more accurately and consistently. Design: In this study, a group of 9 experienced breast pathologists compiled a deidentified set of 60 breast cancer core biopsies from 3 laboratories. The Ventana 4B5 HER2 assay had been used for evaluation and the local laboratories had scored the samples as HER2 0 or 1+. We teased out the ASCO CAP 2018 criteria and used our collective expertise of reporting HER2 IHC for many years to specify HER2 Low-focused scoring conventions, including some potential pitfalls. Subsequently, using these conventions, each pathologist reviewed digitized whole slide images of the IHC slides and scored HER2 expression for each case. At a consensus workshop, the cases were jointly reviewed to establish consensus scores and determine the percentage of HER2-expressing tumor cells in each case. We then evaluated the concordance between individual pathologists' HER2 scores and the consensus opinion and ascertained reasons for discordance. Results: Among the cases discussed during the consensus conference, 43 out of 60 (71.7%) were classified as HER2 Low, with 40 cases designated as 1+ and three as 2+ (known to be not amplified). The consensus score matched the majority opinion of the pathologists' independent scores in 93.3% (56 out of 60) of the cases. Utilizing the HER2 Low-focused IHC scoring conventions, 7 out of 17 (41.2%) cases locally reported as HER2 0 were reclassified as HER2 Low. Conversely, among the 32 cases with local scores of 1+, 7 (21.8%) were reclassified as ultralow or null. When compared to the consensus score, individual pathologists' scores demonstrated concordance levels ranging from 71.7% to 91.7%, with a mean concordance rate of 81.3%. Cases with less than 20% of tumor cells expressing HER2 had lower inter observer concordance. This reference set of cases with expert consensus HER2 scores obtained through our study will be invaluable for peer training and the development of external quality assurance programs for HER2 Low cancers, including the quality assurance program of the Royal College of Pathologists of Australasia. Conclusion: This study revealed that when breast pathologists were provided explicit instructions on scoring pitfalls and HER2 Low-focused scoring conventions, their HER2 scores were concordant with expert consensus scores in 71.7% to 91.7% of cases. Discordant cases primarily involved cases with less than 20% of tumor cells expressing HER2. Utilising such an approach, peer training and quality assurance procedures will improve the accuracy and consistency of HER2 IHC assessment for better patient care. Reassessing older cases using HER2 Low focused scoring conventions may result in revisions of HER2 scores from HER2 Low to zero, and vice versa. Table. Individual pathologists' concordance with the consensus HER2 IHC score Applying our HER2 Low-focused IHC scoring conventions in a set of 60 core biopsies of invasive breast cancer with low or 0 HER2 protein expression. Citation Format: Gelareh Farshid, Beena Kumar, Nirmala Pathmanathan, Hema Mahajan, Ben Dessauvagie, Jane Armes, Cameron Snell, Amardeep Gilhotra. Improving HER2 Low Scoring Consistency and Accuracy: Insights from the Australian HER2 Low Concordance Study for Invasive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-25-12.

Ensuring Accuracy: Critical Validation Techniques in Geochemical Analysis for Sustainable Geothermal Energy Development

Geochemical analysis is a critical tool in geothermal exploration, providing valuable insights into reservoir characteristics. However, obtaining accurate and reliable geochemical data requires rigorous validation techniques. This review examines key factors affecting the accuracy of geochemical data and discusses best practices for ensuring quality. Proper sampling methods, including selection of representative locations, use of appropriate equipment, and adherence to robust protocols for sample collection, filtration, preservation, and storage, are essential for maintaining integrity. Analytical techniques must be carefully selected, with regular calibration and standardization of instruments using certified reference materials. Implementing comprehensive quality assurance and quality control procedures, such as analyzing blanks, duplicates, and spike samples, helps monitor precision and accuracy. Data interpretation should consider the complexities of the geological and hydrological settings, integrating multiple lines of evidence. By following established guidelines and continuously updating methods based on emerging technologies and inter-laboratory comparisons, geothermal teams can optimize the reliability of their geochemical data. Accurate and precise geochemical information, when combined with geological, geophysical, and hydrological data, enables informed decision-making and enhances the success of geothermal projects. As geothermal energy gains importance in the transition to sustainable resources, ensuring the accuracy of geochemical analysis will be crucial for effective exploration and development.

DEEP LEARNING FOR VISUAL RECOGNITION

The design and development of an advanced object detection system are presented in this work, which was guided by a thorough literature review and feasibility assessment. The literature review emphasises how object detection techniques have evolved, highlighting the shift from conventional techniques to deep learning approaches. Important developments are highlighted, such as feature pyramid networks, anchor-based localization, and region-based and single-stage detectors. Furthermore, offered are insights about assessment metrics, transfer learning, and data augmentation. A feasibility study assesses the suggested systems operational, technological, and financial viability and finds that it is highly feasible in each of these areas. The architecture of the system is modular and scalable, including backend services, data management, an object detection engine, and a user interface among its constituent parts. Specifications for both functional and non-functional needs are provided, which direct the development of the system. The development phases, resource allocation, development process, and quality assurance procedures are all outlined in the implementation plan. Through the integration of deep learning techniques, the suggested system seeks to achieve high-performance object identification capabilities that are appropriate for a variety of applications while being scalable, reliable, and user-friendly.

Institutional translation in Oman: An investigation of social, technical, and organisational factors

Translation outside the context of Language Service Providers (LSPs) represents a sizeable share of the translation market. However, this facet of the activity remains less visible and less open to monitoring. This study investigates translation as a situated practice in the context of Oman within institutions where the translation activity does not represent a primary purpose. Adopting a quantitative approach, the study employed an online survey to investigate indicators of the institutionalization of translation, such as resourcing, working conditions, distribution of work, interaction, workflows, and quality management policies. The findings show that translation activities within institutions in Oman are thriving. However, the study revealed that translation practices are subject to considerable variation and that, despite notable exceptions, translation is frequently affected by challenges related to inadequate staffing, resources, and quality assurance procedures. These practices are mainly ad hoc, providing little evidence that translation needs are treated as an integral part of the institution’s functioning. These findings align with observations in other contexts and underscore the need to recognise the significant role translation plays in the functioning of the institution and the need to effectively integrate translation activities within their institutional environments to enhance quality standards in this often-overlooked segment of the translation industry. More generally, the findings confirm the necessity for Translation Studies to appreciate the significance of institutional translation as a facet of translation as a situated activity.

Leveraging AI for Enhanced Quality Assurance in Medical Device Manufacturing

The medical device sector adheres to strict regulatory frameworks, requiring precise adherence to quality assurance (QA) processes during the production process. Conventional quality assurance (QA) approaches, although successful, sometimes require substantial time and resource allocations, resulting in possible obstacles and higher expenses. The emergence of Artificial Intelligence (AI) in recent years has completely transformed quality assurance (QA) methods in different sectors, providing unparalleled prospects for improved productivity, precision, and scalability. This research examines the possibility of using AI technologies to enhance quality assurance processes in the manufacturing of medical devices. Manufacturers may improve product quality and streamline production workflows by utilising AI techniques like machine learning, computer vision, and natural language processing to automate and optimize important QA procedures. Artificial intelligence systems can analyse large amounts of data to find abnormalities, uncover flaws, and anticipate any problems in real-time. This allows for proactive intervention and reduces the chances of non-compliance hazards. In addition, AI-powered QA systems provide adaptive learning capabilities, constantly enhancing performance through feedback and adapting to changing regulatory needs. The incorporation of artificial intelligence (AI) into current quality management systems enables smooth and efficient sharing of data and compatibility, promoting a comprehensive approach to quality control throughout the whole production process.