Search Results (144)

This study proposes a simple deep learning-based framework for image-level anti-personnel landmine detection in long-wave infrared imagery. To address challenges posed by the limited size of the available dataset and the small spatial size of anti-personnel landmines within images, we integrate two key techniques: transfer learning using pre-trained vision foundation models, and attention-based multiple instance learning to derive discriminative image features. We evaluate five pre-trained models, including ResNet, ConvNeXt, ViT, OpenCLIP, and InfMAE, in combination with attention-based multiple instance learning. Furthermore, to mitigate the reliance of trained models on irrelevant features such as artificial or natural structures in the background, we introduce an inpainting-based image augmentation method. Experimental results, conducted on a publicly available “legbreaker” anti-personnel landmine infrared dataset, demonstrate that the proposed framework achieves high precision and recall, validating its effectiveness for landmine detection in infrared imagery. Additional experiments are also performed on an aerial image dataset designed for detecting small-sized ship targets to further validate the effectiveness of the proposed approach. Full article

Operations management personnel emphasize the maintenance of workforce empowerment on the shop floor. This is made possible by implementing effective operations and human resource management practices. However, organizations are adept at controlling the workforce empowerment domain within operational scenarios. In the current industry revolution scenario, industry personnel often face failure due to a laggard mindset in the face of industry revolutions. There are higher possibilities of failure because of standardized operations controlling the shop floor. Organizations utilize well-established human resource concepts, including McClelland’s acquired needs theory, Herzberg’s two-factor theory, and Maslow’s hierarchy of needs, in order to enhance the workforce’s performance on the shop floor. Current SME individuals require fast-paced approaches for tracking the performance and idleness of a workforce in order to control them more efficiently in both flexible and transformational stages. The present study focuses on investigating the parameters and factors that contribute to workforce empowerment in an industrial revolution scenario. The present research is used to develop a framework utilizing operations and human resource management approaches in order to identify and address the issues responsible for deteriorating workforce contributions. The framework includes HRM and operations management practices, including Herzberg’s two-factor theory, Maslow’s theory, and lean and smart approaches. The developed framework contains four phases for achieving desired outcomes on the shop floor. The developed framework is validated by implementing it in a real-life electric vehicle manufacturing organization, where the human resources and operations team were exhausted and looking to resolve employee-related issues instantly and establish a sustainable work environment. The current industry is transforming from Industry 3.0 to Industry 4.0, and seeks future-ready innovations in operations, control, and monitoring of shop floor setups. The operations management and human resource management practices teams reviewed the results over the next three months after the implementation of the developed framework. The results revealed an improvement in workforce empowerment within the existing work environment, as evidenced by reductions in the number of absentees, resignations, transfer requests, and medical issues, by 30.35%, 94.44%, 95.65%, and 93.33%, respectively. A few studies have been conducted on workforce empowerment by controlling shop floor scenarios through modifications in operations and human resource management strategies. The results of this study can be used to fulfil manufacturers’ needs within confined constraints and provide guidelines for efficiently controlling workforce performance on the shop floor. Constraints refer to barriers that have been decided, including production time, working time, asset availability, resource availability, and organizational policy. The study proposes a decision-making plan for enhancing shop floor performance by providing suitable guidelines and an action plan, taking into account both workforce and operational performance. Full article

Semiconductor device fabrication is conducted through highly precise manufacturing processes. An essential component of the semiconductor package is the lead frame on which the silicon dies are assembled. Impurities such as oxides or organic matter on the surfaces have an impact on the process yield. Plasma cleaning is a vital process in semiconductor manufacturing, employed to enhance production yield through precise and efficient surface preparation essential for device fabrication. This paper explores the various facets of plasma cleaning, with a particular emphasis on its application in the cleaning of lead frames used in semiconductor packaging. To provide comprehensive context, this paper also reviews the critical role of plasma in advanced and emerging packaging technologies. This study investigates the fundamental physics governing plasma generation, the design of plasma systems, and the composition of the plasma medium. A central focus of this work is the comparative analysis of different plasma systems in terms of their effectiveness in removing organic contaminants and oxide residues from substrate surfaces. By utilizing reactive species generated within the plasma—such as oxygen radicals, hydrogen ions, and other chemically active constituents—these systems enable a non-contact, damage-free cleaning method that offers significant advantages over conventional wet chemical processes. Additionally, the role of non-reactive species, such as argon, in sputtering processes for surface preparation is examined. Sputtering is the ejection of individual atoms from a target surface due to momentum transfer from an energetic particle (usually an ion). Sputtering is therefore a physical process driven by momentum transfer. Energetic ions, such as argon (Ar⁺), are accelerated from the plasma to bombard a target surface. Upon impact, these ions transfer sufficient kinetic energy to atoms within the material’s lattice to overcome their surface binding energy, resulting in their physical ejection. This paper also provides a comparative assessment of various plasma sources, including direct current, dielectric barrier discharge, radio frequency, and microwave-based systems, evaluating their suitability and efficiency for lead frame cleaning applications. Furthermore, it addresses critical parameters affecting plasma cleaning performance, such as gas chemistry, power input, pressure regulation, and substrate handling techniques. The ultimate aim of this paper is to provide a concise yet comprehensive resource that equips technical personnel with the essential knowledge required to make informed decisions regarding plasma cleaning technologies and their implementation in semiconductor manufacturing. This paper provides various tables which provide the reader with comparative assessments of the various plasma sources and gases used. Scoring mechanisms are also introduced and utilized in this paper. The scores achieved by both the sources and the plasma gases are then summarized in this paper’s conclusions. Full article

This paper aims to propose a hybrid collaborative development model based on multi-dimensional behavioral information (HCDMB) to deal with systemic problems in modern software engineering, such as the low efficiency of cross-stage collaboration, the fragmentation of the intelligent tool chain, and the imperfect human–machine collaboration mechanism. This paper focuses on the stages of requirements analysis, software development, software testing and software operation and maintenance in the process of software development. By integrating the multi-dimensional characteristics of the development behavior track, collaboration interaction record and product application data in the process of project promotion, the mixture of experts (MoE) model is introduced to break through the rigid constraints of the traditional tool chain. Reinforcement learning combined with human feedback is used to optimize the MoE dynamic routing mechanism. At the same time, the few-shot context learning method is used to build different expert models, which further improve the reasoning efficiency and knowledge transfer ability of the system in different scenarios. The HCDMB model proposed in this paper can be viewed as an important breakthrough in the software engineering collaboration paradigm, so as to provide innovative solutions to the many problems faced by dynamic requirements and diverse scenarios based on artificial intelligence technology in the field of software engineering involving different project personnel. Full article

Introduction: Patients in intensive care units (ICUs) face factors that cause anxiety, fear, pain, depression, and adverse health behaviors. This qualitative study aims to determine patients’ experiences when transferred from the ICU to the ward. Methods: Thirteen individuals who were transferred from the ICU to the ward were included in this study. Interviews were conducted using a face-to-face method in the patient’s room. The interviews were recorded with a voice recorder with the consent of the patients. Codes, categories, and themes were created, and content analysis and descriptive analysis were carried out after the audio recordings were converted into text. Results: Patients reported receiving adequate physical and personal care in the ICU and were satisfied with its continuity. They felt safe due to the close attention of healthcare professionals and continuous treatment. Although they received psychological and social support from nurses, they were negatively affected by constant lights, patient noises, and nursing conversations. Patients experienced anxiety about not knowing the health status and time of day, about their relatives, their homes, and other critically ill patients in intensive care. Some patients reported fear of not being able to leave the intensive care unit, relapse, disability, or death. Patients reported pain due to the cold environment, lighting, probes, drains, and positioning. Patients suggested that healthcare personnel communicate better with them, have a clock they can see, reduce noise, and have caregivers of the same gender. They emphasized the need for moral support. Conclusions: Constant light in the intensive care unit, sounds from other patients, nurses talking among themselves, not being able to see their relatives, not knowing what time of day it is, and wondering caused anxiety in the patients. It was determined that patients experienced pain due to catheter, drain, aspiration procedures, cold environment, and position in bed. Notably, patients reported that they needed moral support and wanted to receive care from caregivers of the same gender. Full article

With the Republic of Türkiye signing the “Convention on Intangible Cultural Heritage” in 2006, awareness and sensitivity towards the safeguarding of cultural heritage has also begun to develop in the Turkish Republic of Northern Cyprus (TRNC), which has close relations with the Republic of Türkiye. However, the intangible cultural heritage convention could not be signed in the TRNC due to political reasons, and this has led to a lack of sufficient change and awareness about it on the island. Regrettably, the limited number of academic studies carried out in universities in this field has proven to be inadequate in terms of creating general public awareness about the subject. However, the knowledge and experience of both the community and individuals working in this field are crucial for the safeguarding and sustainability of cultural heritage elements. In this context, this study collected the knowledge and opinions of personnel affiliated with the TRNC Ministry of Culture on the subject of intangible cultural heritage (ICH), and it investigated whether the adequacy of the personnel’s knowledge and opinions around cultural heritage had a direct impact on its safeguarding and sustainability. This research used a type of mixed method called “Convergent Mixed-Methods Design”. The sample of this research consisted of 30 personnel working in different units affiliated with the Ministry of Culture in Northern Cyprus. This study included personnel working in different units and positions affiliated with the ministry. An interview form was used to obtain the data that formed the basis of this research. The interview form consisted of 10 structured and 3 semi-structured questions prepared by the researchers. Descriptive statistics were used in the analysis of the quantitative data, and content analysis was used in the analysis of the qualitative data. This study, which aimed to determine the knowledge and opinions of Ministry of Culture officials working in the TRNC regarding the safeguarding and transfer of intangible cultural heritage elements, revealed that the employees were not fully informed about the scope, objectives, and protection of ICH. Full article

Background/Objectives: The prevalence of obesity is high among children living with disability. The present study aimed to examine the perceptions of parents and caregivers of children living with disability regarding children’s energy balance related behaviors (EBRBs) and their determinants. Methods: Parents/caregivers of children living with disability (n = 45) from Thessaly, Crete and Attica Regions of Greece, participated in semi-structured interviews between November and December 2023. The interviews were recorded, transcribed and transferred to N-VIVO software. The results were analyzed according to the framework of the socio-ecological model, using deductive thematic analysis. Results: Parents/caregivers reported that eating habits of children living with disability and their physical activity levels were poorer compared to the general population. At an individual level, certain disabilities may affect children’s food preferences and parents’ ability to prepare healthy foods. At a familial level, financial difficulties may influence healthy eating, whereas some parents/caregivers act as children’s role models to encourage them to be physically active. Home food environments may also influence children’s eating patterns and peer influence on their EBRBs. At a community level, lack of trained personnel, available amenities/equipment and food education initiatives and the availability of unhealthy foods in school canteens were described as major barriers to healthy EBRBs. At an organizational level, lack of accessible/safe facilities, the marginalization/stigma that children living with disability may experience and lack of dietitians/nutritionists in health centers were named as the main factors influencing children’s EBRBs. Conclusions: The findings of this study highlight the importance of designing multi-sectoral policy interventions to promote healthy EBRBs and tackle obesity in children living with disability in Greece. Full article

Background: The emergency transport of thoraco-omphalopagus conjoined twins is a rare occurrence in the medical field of emergency medicine with no specific guidelines on which medical personnel can rely upon. We present to you the case of the transport of thoraco-omphalopagus conjoined twins. Methods: Important changes were made to the configuration of the aircraft as to provide adequate ventilation (one twin ventilated manually with an ABV while the other benefiting from mechanical ventilation) and hemodynamic stability. Results: The team successfully orchestrated the transfer with no complications arriving during the transfer with the twins benefiting from specialized care in the intended tertiary care center. Conclusions: Our paper highlights the importance for innovative approaches in adapting neonatal transport equipment, including ventilation and monitoring for two critically ill patients in a space designed for one, all that underscores the importance of tailored neonatal transport solutions. Full article

The Law on Credit Institutions 2010, amended and supplemented, was applied on 15 January 2018, causing many changes in senior personnel in Vietnamese banking. The period (2018–2014) had many changes. This was also a period of many business difficulties. Four commercial banks had to carry out mandatory transfers at the request of the State Bank to ensure the development of the Vietnamese banking system in 2024. Profitable investment channels of commercial banks sometimes generate income and, at other times, suffer losses. Managers often analyze and make investment decisions by observing developments recorded on graphs and estimating the future fluctuation trends of each profitable investment channel. However, no research has been conducted on how the simultaneous implementation of all information from investment channels affects the final profit results of commercial banks. This study investigates all banking activities, from trading to investing, to consider which investment channel has a stable impact on bank profits over a long period. The S-GMM estimation method is used, due to the consideration of endogenous variables in quarterly panel data of 27 Vietnamese commercial banks from the first quarter of 2018 to the third quarter of 2024. This study provides statistical evidence indicating that all investment channels of commercial banks contribute to increased profits, except for short-term securities trading channels and capital contributions to subsidiaries. This study also reveals that economic growth and systemic risk affect commercial bank profits. Several solutions are proposed for commercial banks to develop future profitable investment channels. Full article

Video cameras are one of the important elements in ensuring security in public areas. Videos inspected by expert personnel using traditional methods may have a high error rate and take a long time to complete. In this study, a new deep learning-based method is proposed for the detection of abandoned objects, such as bags, suitcases, and suitcases left unsupervised in public areas. Transfer learning-based keyframe detection was first performed to remove unnecessary and repetitive frames from the ABODA dataset. Then, human and object classes were detected using the weights of the YOLOv8l model, which has a fast and effective object detection feature. Abandoned object detection is achieved by tracking classes in consecutive frames with the DeepSORT algorithm and measuring the distance between them. In addition, the location information of the human and object classes in the frames was analyzed by a large language model supported by prompt engineering. Thus, an explanation output regarding the location, size, and estimation rate of the object and human classes was created for the authorities. It is observed that the proposed model produces promising results comparable to the state-of-the-art methods for suspicious object detection from videos with success metrics of 97.9% precision, 97.0% recall, and 97.4% f1-score. Full article

Transport by unmanned aerial systems (UASs) (e.g., drones) could save time and personnel. Our study aimed to assess the effect of drone transportation on the clinical laboratory results of biological samples by examining its impact on pre-analytical and analytical processes. We performed a cross-sectional study of healthy volunteers from Sha’ar Menashe Mental Health Center between July and November 2022. Blood and urine samples were transferred to the central laboratory at Hillel Yaffe Medical Center. Overall, 40 healthcare workers aged 21–67 years (57.5% females) with a mean age of 45.8 (SD = 11.3) years from Sha’ar Menashe Mental Health Center were recruited in the study. There were no significant differences between transportation modes in the complete blood count levels. We found a significant difference between the transportation modes for GGT (p = 0.01) and PT (p = 0.04), despite the very similar mean results of these tests. In Bland–Altman plots, GGT and PT samples fell within the 95% limits of agreement and were indicated as not clinically relevant; however, glucose and LDH did not meet the 95% acceptance criterion and showed a potential clinical effect. There was full agreement between the two types of transportation for urine glucose, nitrites, and urine cultures. UAS transport is an appropriate method for maintaining the quality of most routine clinical laboratory specimens, similar to the routine procedure of using a vehicle. For the 34 biochemistry, hematology, and coagulation assay parameters, only glucose and LDH did not meet the 95% acceptance criterion and showed a potential clinical effect. Full article

This research presents a scientifically grounded model designed to enhance the safety protocols for firefighting teams during fire intervention scenarios. The model estimates the maximum allowable exposure duration based on ambient temperature and radiant heat, employing data captured by thermal imaging cameras, which provide real-time measurements of infrared radiation emitted by fire-affected zones. Utilising the Stefan–Boltzmann law to quantify radiative heat transfer and Probit vulnerability analysis to assess thermal risk, critical temperature thresholds and corresponding exposure durations were determined. The results indicate that the maximum permissible ambient temperature for firefighting interventions is 263 °C, with a safe exposure duration of 26 s under these thermal conditions. This approach underscores the significance of ambient temperature as a pivotal parameter in risk assessment and intervention strategy development. Furthermore, the model’s applicability extends to other high-risk environments, including industrial operations, providing a robust and versatile framework for safety management. These findings contribute to advancing evidence-based protocols that mitigate injury risks, safeguard firefighting personnel, and optimise operational decision-making during emergencies. Full article

Moisture generation in the ventilation projects of deeply buried underground corridors affects the underground building environment and personnel health. In order to master the heat and humidity transfer law of underground corridors, this paper establishes a mathematical model by theoretical analysis, and the application of the theoretical model in engineering calculation is verified by a field test. It is found that the ventilation efficiency and heat and humidity transfer effect are related to corridor shape. The results show that under the same cross-sectional area, the average temperature drop and humidity of a rectangular corridor are 0.25% and 0.3% higher than that of an arch corridor, and 0.8% and 0.9% higher than that of a circular corridor. Under the condition of constant section circumference, the average temperature drop and humidity of a rectangular corridor are 0.51% and 0.62% higher than that of an arch corridor, and 1.37% and 1.58% higher than that of a circular corridor. When the equivalent diameter is the same, there is almost no difference in the heat and humidity transfer effect of the three shaped corridors. Full article

Autonomous Underwater Vehicles (AUVs) operate independently using onboard batteries and data storage, necessitating periodic recovery for battery recharging and data transfer. Traditional surface-based launch and recovery (L&R) operations pose significant risks to personnel and equipment, particularly in adverse weather conditions. Subsurface docking stations provide a safer alternative but often involve complex fixed installations and costly acoustic positioning systems. This work introduces a comprehensive docking solution featuring the following two key innovations: (1) a novel deployable docking station (DDS) designed for rapid deployment from vessels of opportunity, operating without active acoustic transmitters; and (2) an innovative sensor fusion approach that combines the AUV’s onboard forward-looking sonar and camera data. The DDS comprises a semi-submersible protective frame and a subsurface, heave-compensated docking component equipped with backlit visual markers, an electromagnetic (EM) beacon, and an EM lifting device. This adaptable design is suitable for temporary installations and in acoustically sensitive or covert operations. The positioning and guidance system employs a multi-sensor approach, integrating range and azimuth data from the sonar with elevation data from the vision camera to achieve precise 3D positioning and robust navigation in varying underwater conditions. This paper details the design considerations and integration of the AUV system and the docking station, highlighting their innovative features. The proposed method was validated through software-in-the-loop simulations, controlled seawater pool experiments, and preliminary open-sea trials, including several docking attempts. While further sea trials are planned, current results demonstrate the potential of this solution to enhance AUV operational capabilities in challenging underwater environments while reducing deployment complexity and operational costs. Full article

Monitoring the body condition of dairy cows is essential for ensuring their health and productivity, but traditional BCS methods—relying on visual or tactile assessments by skilled personnel—are subjective, labor-intensive, and impractical for large-scale farms. To overcome these limitations, we present BCS-YOLO, a lightweight and automated BCS framework built on YOLOv8, which enables consistent, accurate scoring under complex conditions with minimal computational resources. BCS-YOLO integrates the Star-EMA module and the Star Shared Lightweight Detection Head (SSLDH) to enhance the detection accuracy and reduce model complexity. The Star-EMA module employs multi-scale attention mechanisms that balance spatial and semantic features, optimizing feature representation for cow hindquarters in cluttered farm environments. SSLDH further simplifies the detection head, making BCS-YOLO viable for deployment in resource-limited scenarios. Additionally, channel-based knowledge distillation generates soft probability maps focusing on key body regions, facilitating effective knowledge transfer and enhancing performance. The results on a public cow image dataset show that BCS-YOLO reduces the model size by 33% and improves the mean average precision (mAP) by 9.4%. These advances make BCS-YOLO a robust, non-invasive tool for consistent and accurate BCS in large-scale farming, supporting sustainable livestock management, reducing labor costs, enhancing animal welfare, and boosting productivity. Full article