Search Results (38)

In the era of rapid technological progress, Robotic Process Automation (RPA) has emerged as a pivotal tool across professional domains. Organizations pursue automation to boost efficiency and productivity, control costs, and reduce errors. RPA software automates repetitive, rules-based tasks previously performed by employees, and its effectiveness depends on integration across the business–IT–people interface. We adopted a mixed-methods study combining a PRISMA-guided multivocal review of peer-reviewed and gray sources with semi-structured practitioner interviews to capture firsthand insights and diverse perspectives. Triangulation of these phases examines RPA governance, auditing, and policy. The study clarifies the relationship between business processes and IT and offers guidance that supports procedural standardization, regulatory compliance, employee engagement, role clarity, and effective change management—thereby increasing the likelihood of successful RPA initiatives while prudently mitigating associated risks. Full article

Advanced technologies, such as robotic process automation, blockchain, and machine learning, increase audit efficiency. Nonetheless, some Supreme Audit Institutions (SAIs) have not undergone digital transformation. This research aimed to develop a comprehensive framework for supreme audit institutions to adopt and integrate emerging technologies into their auditing processes using a hybrid theoretical approach based on the TAM (Technology Acceptance Model) and TOE (Technology–Organisation–Environment) models. The framework was informed by insights from nineteen highly experienced experts in the field from eight countries. Through a two-round Delphi questionnaire, the experts provided valuable input on the key factors, challenges, and strategies for successful technology adoption by public sector audit organisations. The findings of this research reveal that technology adoption in SAIs starts with solid management support led by the chief technology officer. They must evaluate the IT infrastructure and readiness for advanced technologies, considering the budget and funding. Integrating solutions like the SAI of Ghana’s Audit Management Information System can significantly enhance audit efficiency. Continuous staff training is essential to build a positive attitude toward new technologies, covering areas like data algorithm auditing and big data analysis. Assessing the complexity and compatibility of new technologies ensures ease of use and cost-effectiveness. Continuous support from technology providers and monitoring advancements will keep SAIs aligned with technological developments, enhancing their auditing capabilities. Full article

This paper introduces a configuration and integration model for mobile robots deployed in emergency and special operations scenarios. The proposed method is designed for implementation within the operational technology (OT) domain, enforcing security protocols that ensure both data encryption and network isolation. The primary objective is to establish a dedicated operational environment encompassing a command and control center where the robotic network server resides, alongside real-time data storage from network clients and remote control of field-deployed mobile robots. Building on this infrastructure, operational strategies are developed to enable an efficient robotic response in critical situations. By leveraging remote robotic networks, significant benefits are achieved in terms of personnel safety and mission efficiency, minimizing response time and reducing the risk of injury to human operators during hazardous interventions. Unlike generic IoT or IoRT systems, this work focuses on secure robotic integration within segmented OT infrastructures. The technologies employed create a synergistic system that ensures data integrity, encryption, and safe user interaction through a web-based interface. Additionally, the system includes mobile robots and a read-only application positioned within a demilitarized zone (DMZ), allowing for secure data monitoring without granting control access to the robotic network, thus enabling cyber-physical isolation and auditability. Full article

This umbrella review synthesizes international guidelines on the surgical management of rectal cancer to provide unified recommendations tailored to local healthcare organizations. This review emphasizes the importance of surgical centralization in high-volume centers, which maximizes outcomes, reduces morbidity, and increases survival rates. Minimally invasive approaches, such as laparoscopy and robotic surgery, are highlighted for their perioperative benefits, although careful patient selection and surgical expertise are required. Mechanical bowel preparation combined with oral antibiotics is recommended to effectively reduce complications, including surgical site infections and anastomotic leakage. Enhanced Recovery After Surgery protocols have been shown to significantly improve postoperative recovery and reduce hospital stay duration. Comprehensive perioperative care, including venous thromboembolism prophylaxis and infection control, is essential for optimal patient outcomes. This review underscores the need for structured training, certification, and regular audits for advanced techniques such as robotic surgery and transanal total mesorectal excision. Implementation of a national database is recommended to support ongoing improvements in rectal cancer surgery. This review centralizes evidence-based recommendations to guide surgical decision-making and harmonize the multidisciplinary care for patients with rectal cancer. Full article

This study presents a three-dimensional collective motion model that integrates auditory and visual sensing modalities, inspired by organisms like bats that rely on these senses for navigation. Most existing models of collective motion consider vision-based sensing, likely reflecting an inherent human bias towards visual perception. However, many organisms utilize multiple sensory modalities, and this study explores how the integration of these distinct sensory inputs influences group behavior. We investigate a generalized scenario of three-dimensional motion, an area not previously explored for combining sensory information. Through numerical simulations, we investigate the combined impact of auditory and visual sensing on group behavior, contrasting these effects with those observed when relying solely on vision or audition. The results demonstrate that composite sensing allows particles to interact with more neighbors, thereby gaining more information. This interaction allows the formation of a single, large, perfectly aligned group using a narrow sensing region, achievable by taking advantage of the mechanics of both auditory and visual sensing. Our findings demonstrate the importance of integrating multiple sensory modalities in shaping emergent group behavior, with potential applications in both biological studies and the development of robotic swarms. Full article

This paper proposes efficient implementations of robot audition systems, specifically focusing on deployments using HARK, an open-source software (OSS) platform designed for robot audition. Although robot audition systems are versatile and suitable for various scenarios, efficiently deploying them can be challenging due to their high computational demands and extensive processing times. For scenarios involving intensive high-dimensional data processing with large-scale microphone arrays, our generalizable GPU-based implementation significantly reduced processing time, enabling real-time Sound Source Localization (SSL) and Sound Source Separation (SSS) using a 60-channel microphone array across two distinct GPU platforms. Specifically, our implementation achieved speedups of 23.3× for SSL and 3.0× for SSS on a high-performance server equipped with an NVIDIA A100 80 GB GPU. Additionally, on the Jetson AGX Orin 32 GB, which represents embedded environments, it achieved speedups of 14.8× for SSL and 1.6× for SSS. For edge computing scenarios, we developed an adaptable FPGA-based implementation of HARK using High-Level Synthesis (HLS) on M-KUBOS, a Multi-Access Edge Computing (MEC) FPGA Multiprocessor System on a Chip (MPSoC) device. Utilizing an eight-channel microphone array, this implementation achieved a 1.2× speedup for SSL and a 1.1× speedup for SSS, along with a 1.1× improvement in overall energy efficiency. Full article

Robotic manipulators play a key role in modern industrial manufacturing processes. Monitoring their operational health is of paramount importance. In this paper, a novel anomaly detection framework named U-TFF is introduced for energy consumption auditing of robotic manipulators. It comprises a cascade of Time–Frequency Fusion (TFF) blocks to extract both time and frequency domain features from time series data. The block applies the Fast Fourier Transform to convert the input to the frequency domain, followed by two separate dense layers to process the resulting real and imaginary components, respectively. The frequency and time features are then combined to reconstruct the input. A U-shaped architecture is implemented to link corresponding TFF blocks of the encoder and decoder at the same level through skip connections. The semi-supervised model is trained using data exclusively from normal operations. Significant errors were generated during testing for anomalies with data distributions deviating from the training samples. Consequently, a threshold based on the magnitude of reconstruction errors was implemented to identify anomalies. Experimental validation was conducted using a custom dataset, including physical attacks as abnormal cases. The proposed framework achieved an accuracy and recall of approximately 0.93 and 0.83, respectively. A comparison with other benchmark models further verified its superior performance. Full article

With the rapid industrialization utilizing multi-rotor drones in recent years, an increase in urban flights is expected in the near future. This may potentially result in noise pollution due to the operation of drones. This study investigates the near- and far-field acoustic characteristics of low-noise propellers inspired by Gurney flaps. In addition, we examine the impact of these low-noise propellers on the sound source localization performance of drones equipped with a microphone array, which are expected to be used for rescuing people in disasters. Results from in-flight noise measurements indicate significant noise reduction mainly in frequency bands above 1 kHz in both the near- and far-field. An improvement in the success rate of sound source localization with low-noise propellers was also observed. However, the influence of the position of the microphone array with respect to the propellers is more pronounced than that of propeller shape manipulation, suggesting the importance of considering the positional relationships. Computational fluid dynamics analysis of the flow field around the propellers suggests potential mechanisms for noise reduction in the developed low-noise propellers. The results obtained in this study hold potential for contributing to the development of integrated drones aimed at reducing noise and improving sound source localization performance. Full article

Mobile service robots employ vision systems to discern objects in their workspaces for navigation or object detection. The lighting conditions of the surroundings affect a robot’s ability to discern and navigate in its work environment. Robot inclusivity principles can be used to determine the suitability of a site’s lighting condition for robot performance. This paper proposes a novel framework for autonomously auditing the Robot Inclusivity Index of indoor environments based on the lighting condition (RII-lux). The framework considers the factors of light intensity and the presence of glare to define the RII-Lux of a particular location in an environment. The auditing framework is implemented on a robot to autonomously generate a heatmap visually representing the variation in RII-Lux of an environment. The applicability of the proposed framework for generating true-to-life RII-Lux heatmaps has been validated through experimental results. Full article

Cloud manufacturing is an evolving networked framework that enables multiple manufacturers to collaborate in providing a range of services, including design, development, production, and post-sales support. The framework operates on an integrated platform encompassing a range of Industry 4.0 technologies, such as Industrial Internet of Things (IIoT) devices, cloud computing, Internet communication, big data analytics, artificial intelligence, and blockchains. The connectivity of industrial equipment and robots to the Internet opens cloud manufacturing to the massive attack risk of cybersecurity and cyber crime threats caused by external and internal attackers. The impacts can be severe because the physical infrastructure of industries is at stake. One potential method to deter such attacks involves utilizing blockchain and artificial intelligence to track the provenance of IIoT devices. This research explores a practical approach to achieve this by gathering provenance data associated with operational constraints defined in smart contracts and identifying deviations from these constraints through predictive auditing using artificial intelligence. A software architecture comprising IIoT communications to machine learning for comparing the latest data with predictive auditing outcomes and logging appropriate risks was designed, developed, and tested. The state changes in the smart ledger of smart contracts were linked with the risks so that the blockchain peers can detect high deviations and take actions in a timely manner. The research defined the constraints related to physical boundaries and weightlifting limits allocated to three forklifts and showcased the mechanisms of detecting risks of breaking these constraints with the help of artificial intelligence. It also demonstrated state change rejections by blockchains at medium and high-risk levels. This study followed software development in Java 8 using JDK 8, CORDA blockchain framework, and Weka package for random forest machine learning. As a result of this, the model, along with its design and implementation, has the potential to enhance efficiency and productivity, foster greater trust and transparency in the manufacturing process, boost risk management, strengthen cybersecurity, and advance sustainability efforts. Full article

This paper extends current research on Human–Robot Interaction (HRI) within Human–Computer Interaction (HCI), focusing on how future virtual agents and communication robots can support the temporal structures and routines within the home. We recruited representatives from 15 households with varied compositions, ranging from single inhabitants to full nest families. Drawing upon P.G. Wodehouse’s The Inimitable Jeeves as an inspiration, the methodology sought to imitate the relationship between a recruitment agency worker (researcher) and an employer (participant) seeking to hire a personal assistant (e.g., a virtual agent or communication robot device) for their home. A ‘household audit’ comprising a guided household tour and an architectural survey was conducted to ascertain the nuanced spatiotemporal routines within the home. The study analysed the responses of participants using the Labovian narrative schema, a traditional method in linguistics research. The findings were then examined through the lens of Reddy et al.’s temporal features of work to understand how domestic work unfolds within the home from a temporal perspective. We argue that the temporal concepts discussed by Reddy et al. provided valuable insights into the temporal dynamics of everyday activities and could inform the design of virtual agents and communication robotic devices to fulfil their roles as domesticated ‘personal assistants’. Full article

Mobile service robots often have to work in dynamic and cluttered environments. Multiple safety hazards exist for robots in such work environments, which visual sensors may not detect in time before collisions or robotic damage. An alternative hazard alert system using tactile methods is explored to pre-emptively convey surrounding spatial information to robots working in complex environments or under poor lighting conditions. The proposed method for robot-inclusive tactile paving is known as Passive Auto-Tactile Heuristic (PATH) tiles. These robot-inclusive tactile paving tiles are implemented in spatial infrastructure and are aimed to allow robots to pre-emptively recognize surrounding hazards even under poor lighting conditions and potentially provide improved hazard cues to visually impaired people. A corresponding Tactile Sensing Module (TSM) was used for the digital interpretation of the PATH tiles and was mounted onboard a mobile audit robot known as Meerkat. The experiment yielded a 71.6% improvement in pre-emptive hazard detection capabilities with the TSM using a customized Graph Neural Network (GNN) model. Full article

Background: The quality of care of patients receiving colorectal resections has conventionally relied on individual metrics. When discussing with patients what these outcomes mean, they often find them confusing or overwhelming. Textbook oncological outcome (TOO) is a composite measure that summarises all the ‘desirable’ or ‘ideal’ postoperative clinical and oncological outcomes from both a patient’s and doctor’s point of view. This study aims to evaluate the incidence of TOO in patients receiving robotic colorectal cancer surgery in five robotic colorectal units and understand the risk factors associated with failure to achieve a TOO in these patients. Methods: We present a retrospective, multicentric study with data from a prospectively collected database. All consecutive patients receiving robotic colorectal cancer resections from five centres between 2013 and 2022 were included. Patient characteristics and short-term clinical and oncological data were collected. A TOO was achieved when all components were realized—no conversion to open, no complication with a Clavien–Dindo (CD) ≥ 3, length of hospital stay ≤ 14, no 30-day readmission, no 30-day mortality, and R0 resection. The main outcome measure was a composite measure of “ideal” practice called textbook oncological outcomes. Results: A total of 501 patients submitted to robotic colorectal cancer resection were included. Of the 501 patients included, 388 (77.4%) achieved a TOO. Four patients were converted to open (0.8%); 55 (11%) had LOS > 14 days; 46 (9.2%) had a CD ≥ 3 complication; 30-day readmission rate was 6% (30); 30-day mortality was 0.2% (1); and 480 (95.8%) had an R0 resection. Abdominoperineal resection was a risk factor for not achieving a TOO. Conclusions: Robotic colorectal cancer surgery in robotic centres achieves a high TOO rate. Abdominoperineal resection is a risk factor for failure to achieve a TOO. This measure may be used in future audits and to inform patients clearly on success of treatment. Full article

Locating the sound source is one of the most important capabilities of robot audition. In recent years, single-source localization techniques have increasingly matured. However, localizing and tracking specific sound sources in multi-source scenarios, which is known as the cocktail party problem, is still unresolved. In order to address this challenge, in this paper, we propose a system for dynamically localizing and tracking sound sources based on audio–visual information that can be deployed on a mobile robot. Our system first locates specific targets using pre-registered voiceprint and face features. Subsequently, the robot moves to track the target while keeping away from other sound sources in the surroundings instructed by the motion module, which helps the robot gather clearer audio data of the target to perform downstream tasks better. Its effectiveness has been verified via extensive real-world experiments with a 20% improvement in the success rate of specific speaker localization and a 14% reduction in word error rate in speech recognition compared to its counterparts. Full article

Background: Despite increasingly advanced minimally invasive percutaneous ablation techniques, surgery remains the only evidence-based therapy in curative intent for larger (>3–4 cm) renal tumors. Although minimally invasive surgery using (robotic-assisted) laparoscopic or retroperitoneoscopic approaches has gained popularity, open nephrectomy (ON) is still performed in 25% of cases, especially in tumors with central localization (partial ON) or large tumors with/without cava thrombus (total ON). As postoperative pain is one of the drawbacks of ON, our study aims to assess recovery and post-operative pain management using continuous wound infiltration (CWI) compared to thoracic epidural analgesia (TEA). Methods: Since 2012, all patients undergoing ON at our tertiary cancer center at CHUV have been included in our prospective ERAS^® (enhanced recovery after surgery) registry that is centrally stored in ERAS^® Interactive Audit System (EIAS) secured server. This study represents an analysis of all patients operated on with partial or total ON at our center between 2012 and 2022. An additional analysis was performed for the estimations of the total cost of CWI and TEA, based on the diagnosis-related group method. Results: 92 patients were included and analyzed in this analysis (n = 64 (70%) with CWI; n = 28 (30%) with TEA). Adequate oral pain control was earlier achieved in the CWI group compared to the TEA group (median 3 vs. 4 days; p = 0.001), whereas immediate postoperative pain relief was better in the TEA group (p = 0.002). Consequently, opioid use was higher in the CWI group (p = 0.004). Still, reported nausea was lower in the CWI group (p = 0.002). Median time to bowel recovery was similar in both groups (p = 0.03). A shorter LOS (0.5 days) was observed in patients managed with CWI, although this was not statistically significant (p = 0.06). The use of CWI has reduced total hospital costs by nearly 40%. Conclusions: TEA has better results in terms of postoperative pain management compared to CWI following ON. However, CWI is better tolerated, and causes less nausea and earlier recovery, which leads to a shorter length of stay. Given its simplicity and cost-effectiveness, CWI should be encouraged for ON. Full article