Semi-automated Systems Research Articles

Field Evaluation of Targeted Shake-and-Catch Harvesting Technologies for Fresh Market Apple

HighlightsThree shaking methods and vibratory harvesting systems were evaluated and compared.Multi-year field evaluations were performed with up to six cultivars trained to formal architectures.The updated semi-automated system achieved the highest fruit removal efficiency and the best fruit quality.Abstract. Apple is the most economically important agricultural crop in Washington State. In 2018, Washington State produced ~3.3 billion kg of apple, accounting for approximately 63% of U.S. production. Fresh-market apple is currently harvested manually, requiring large numbers seasonal semi-skilled workers for a small harvest window. To overcome the increasing challenges of uncertain labor availability and raising labor costs, a promising mechanical harvesting system, using a targeted shake-and-catch approach, is under development at Washington State University. This study evaluated the system by analyzing its fruit harvest efficiency and fruit quality with three shaking methods, i.e., continuous non-linear, continuous linear, and intermittent linear shaking, on up to six apple cultivars trained to formal tree architectures. Results showed that intermittent linear shaking achieved 90% fruit removal efficiency for ‘Scifresh’ cultivar, while continuous linear shaking achieved only 63% removal efficiency for ‘Gala’. This study also compared three vibratory systems: a hand-held system, a hydraulically driven system, and a semi-automated hydraulic system. The semi-automated system achieved the highest fruit removal efficiency (90%), followed by the hand-held (87%) and hydraulic (84%) systems, mainly due to the different shaking methods employed. However, the differences were statistically insignificant. Fruit catching efficiency varied among the harvesting systems, with the hand-held system achieving the highest efficiency (97%), followed by the hydraulic (91%) and semi-automated (88%) systems. Among the three tested technologies, the prototype semi-automated system achieved the highest level of mechanization, as well as high fruit removal efficiency and the best fruit quality. Because the semi-automated system did not include an auto-positioning function, positioning its shaker head took about eight times longer (~103 s) than the actual shaking time (~13 s), which suggests that a fully automated system is desirable to further increase productivity. This study showed that the shake-and-catch approach has great potential for practical adoption in harvesting of fresh-market apple and therefore can have a positive economic impact on the U.S. apple industry. Keywords: Automation in apple production, Bulk mechanical harvest, Semi-automated system, Shaking method, Time efficiency.

Evaluation of the disinfectant concentration used on livestock facilities in Korea during dual outbreak of foot and mouth disease and high pathogenic avian influenza.

BackgroundA nationwide outbreak of foot-and-mouth disease (FMD) in South Korea caused massive economic losses in 2010. Since then, the Animal and Plant Quarantine Agency (QIA) has enhanced disinfection systems regarding livestock to prevent horizontal transmission of FMD and Avian influenza (AI). Although the amount of disinfectant used continues to increase, cases of FMD and AI have been occurring annually in Korea, except 2012 and 2013.ObjectivesThis study measured the concentration of the disinfectant to determine why it failed to remove the horizontal transmission despite increased disinfectant use.MethodsSurveys were conducted from February to May 2017, collecting 348 samples from disinfection systems. The samples were analyzed using the Standards of Animal Health Products analysis methods from QIA.ResultsTwenty-three facilities used inappropriate or non-approved disinfectants. Nearly all sampled livestock farms and facilities—93.9%—did not properly adjust the disinfectant concentration. The percentage using low concentrations, or where no effective substance was detected, was 46.9%. Furthermore, 13 samples from the official disinfection station did not use effective disinfectant, and—among 72 samples from the disinfection station—88.89% were considered inappropriate concentration, according to the foot-and-mouth disease virus guidelines; considering the AIV guideline, 73.61% were inappropriate concentrations. Inappropriate concentration samples on automatic (90.00%) and semi-automatic (90.90%) disinfection systems showed no significant difference from manual methods (88.24%). Despite this study being conducted during the crisis level, most disinfectants were used inappropriately.ConclusionsThis may partially explain why horizontal transmission of FMD and AI cannot be effectively prevented despite extensive disinfectant use.

Многоагентные системы полуавтоматического проектирования в машиностроении на базе механизма объект-функции

A methodology for creating semi-automatic design systems for engineering products using artificial intelligence technologies is proposed. The methodology is based on multi-agent methods for creating knowledge bases and is suitable for the development of design and control systems for digital intelligent industries. As a unified agent model, an objectfunction mechanism is proposed with a partition of attributes into a subset of the input and output attributes of the agent method. Object-function is considered as a unified module for creating multi-agent systems. Graphic and textual models of agent representation are proposed. It is shown that with this representation, the agent is equivalent to the production rule, which is a knowledge base module. The names of the variables of the knowledge module should be selected from a dictionary that can be compiled using various natural languages. The mechanisms of knowledge modules should ensure the implementation of all the functions that may be required in the formation of knowledge bases. It is shown that the mechanism of an object-function mechanism can be a system of agents. When using expert programming technology, the process of generating knowledge modules, translating them into object or executable modules in one of the traditional languages, and testing is performed as a single operation. After obtaining the necessary set of modules, a method is generated that uses a subset of the generated knowledge modules. The generated method can be used as a mechanism of the knowledge module, which allows the use of a hierarchy of rules. It is shown that a cooperative solution to complex problems is provided by a system of agents.

Complex of computer models for studying semi-automatic control systems of robot-manipulators

Complex of computer models for studying semi-automatic control systems of robot-manipulators

Spine Explorer: a deep learning based fully automated program for efficient and reliable quantifications of the vertebrae and discs on sagittal lumbar spine MR images

BACKGROUND CONTEXTAlthough quantitative measurements improve the assessment of disc degeneration, acquirement of quantitative measurements relies on manual segmentation on lumbar magnetic resonance images (MRIs), which may introduce subjective bias. To date, only a few semiautomatic systems have been developed to quantify important components on MRIs. PURPOSETo develop a deep learning based program (Spine Explorer) for automated segmentation and quantification of the vertebrae and intervertebral discs on lumbar spine MRIs. STUDY DESIGNCross-sectional study. PATIENT SAMPLEThe study was extended on the Hangzhou Lumbar Spine Study, a population-based study of mainland Chinese with focuses on lumbar degenerative changes. From this population-based database, 50 sets lumbar MRIs were randomly selected as training dataset, and another 50 as test dataset. OUTCOME MEASURESRegions of vertebrae and discs were manually segmented on T2W sagittal MRIs to train a convolutional neural network for automated segmentation. Intersection-over-union was calculated to evaluate segmentation performance. Computational definitions were proposed to acquire quantitative morphometric and signal measurements for lumbar vertebrae and discs. MRIs in the test dataset were automatically measured with Spine Explorer and manually with ImageJ. METHODSIntraclass correlation coefficient (ICC) were calculated to examine inter-software agreements. Correlations between disc measurements and Pfirrmann score as well as age were examined to assess measurement validity. RESULTSThe trained Spine Explorer automatically segments and measures a lumbar MRI in half a second, with mean Intersection-over-union of 94.7% and 92.6% for the vertebra and disc, respectively. For both vertebra and disc measurements acquired with Spine Explorer and ImageJ, the agreements were excellent (ICC=0.81~1.00). Disc measurements significantly correlated to Pfirrmann score, and greater age was associated with greater anterior disc bulging area (r=0.35~0.44) and fewer signal measurements (r=−0.62~−0.77) as automatically acquired with Spine Explorer. CONCLUSIONSSpine Explorer is an efficient, accurate, and reliable tool to acquire comprehensive quantitative measurements for lumbar vertebra and disc. Implication of such deep learning based program can facilitate clinical studies of the lumbar spine.

Irrigation systems of urban landscapes of the south of the European part of Russia: problems and perspective

The paper discusses the necessity to apply the innovative irrigation technology when creating artificial landscapes in the South of the European part of Russia. The artificial green areas of the Rostov agglomeration significantly differ from the traditional steppe plant associations. They are presented, as a rule, by tree plantings or grassy introduced species which are used to create the city microclimate and also for protection from the eastern winds. Unfortunately climatic conditions and increasing anthropogenic load don‘t provide the stable rooting and development of plants without additional moistening, despite the Chernozem high agronomic value. The process of the soil cover replanting of its central part and the phenologically old trees replacing is actively under way. This process should be accompanied by compliance with the requirements for enhanced, both in frequency and volume, irrigation of young trees. But the use of automatic and semi-automatic irrigation systems is associated with the absence of a regulatory framework for the design, installation, and further operation of irrigation systems under the conditions of the Russian Federation. This issue requires the solving with the direct participation of specialists from various fields, both theorists and construction practitioners, land reclamation specialists, soil scientists, landscape designers.

Predicting Quality of Overnight Glycaemic Control in Type 1 Diabetes Using Binary Classifiers.

In type 1 diabetes management, maintaining nocturnal blood glucose within target range can be challenging. Although semi-automatic systems to modulate insulin pump delivery, such as low-glucose insulin suspension and the artificial pancreas, are starting to become a reality, their elevated cost and performance below user expectations is hindering their adoption. Hence, a decision support system that helps people with type 1 diabetes, on multiple daily injections or insulin pump therapy, to avoid undesirable overnight blood glucose fluctuations (hyper- or hypoglycaemic) is an attractive alternative. In this paper, we introduce a novel data-driven approach to predict the quality of overnight glycaemic control in people with type 1 diabetes by analyzing commonly gathered data during the day-time period (continuous glucose monitoring data, meal intake and insulin boluses). The proposed approach is able to predict whether overnight blood glucose concentrations are going to remain within or outside the target range, and therefore allows the user to take the appropriate preventive action (snack or change in basal insulin). For this purpose, a number of popular established machine learning algorithms for binary classification were evaluated and compared on a publicly available clinical dataset (i.e., OhioT1DM). Although there is no clearly superior classification algorithm, this study indicates that, by using commonly gathered data in type 1 diabetes management, it is possible to predict the quality of overnight glycaemic control with reasonable accuracy (AUC-ROC = 0.7).

Meta-Analysis of the Sensitivity of Decision Support Systems in Diagnosing Diabetic Retinopathy.

Diabetic Retinopathy (DR) is one of the most common microvascular complications presenting by patients diagnosticated with diabetic diseases. Uncontrolled hyperglycemia may manifest as visual impairment and blindness. The early detection of DR is essential to minimize the risk and consequence of visual diminishing. The standard gold diagnoses tool relies on different imaging modalities and requires a judgment of expert photographers, which are not available in most of the primary care centers or remote location. In that scenario, an automate or semiautomated DR screening systems can contribute to improving the accuracy of the diagnostic. Thus, we performed a Systematic Review and Meta-Analysis to evaluate the Decision Support Systems (DSS) in diagnosing DR. The overall Diagnostic Odds Ratio was 73.15 (95%CI: 37.54-142.50), sensitivity was 97.70 (95%CI: 97.50-97.90) and specificity was 90.30 (95%CI: 90.00-90.60). Our results corroborate with the concept of usefulness of DSSs in early diagnosis, screening and preliminary evaluation of suspicious images of DR.

Targeted Adaptable Sample for Accurate and Efficient Quantile Estimation in Non-Stationary Data Streams

The need to detect outliers or otherwise unusual data, which can be formalized as the estimation a particular quantile of a distribution, is an important problem that frequently arises in a variety of applications of pattern recognition, computer vision and signal processing. For example, our work was most proximally motivated by the practical limitations and requirements of many semi-automatic surveillance analytics systems that detect abnormalities in closed-circuit television (CCTV) footage using statistical models of low-level motion features. In this paper, we specifically address the problem of estimating the running quantile of a data stream with non-stationary stochasticity when the absolute (rather than asymptotic) memory for storing observations is severely limited. We make several major contributions: (i) we derive an important theoretical result that shows that the change in the quantile of a stream is constrained regardless of the stochastic properties of data; (ii) we describe a set of high-level design goals for an effective estimation algorithm that emerge as a consequence of our theoretical findings; (iii) we introduce a novel algorithm that implements the aforementioned design goals by retaining a sample of data values in a manner adaptive to changes in the distribution of data and progressively narrowing down its focus in the periods of quasi-stationary stochasticity; and (iv) we present a comprehensive evaluation of the proposed algorithm and compare it with the existing methods in the literature on both synthetic datasets and three large “real-world” streams acquired in the course of operation of an existing commercial surveillance system. Our results and their detailed analysis convincingly and comprehensively demonstrate that the proposed method is highly successful and vastly outperforms the existing alternatives, especially when the target quantile is high-valued and the available buffer capacity severely limited.

Automation in the Mining Industry: Review of Technology, Systems, Human Factors, and Political Risk

In the opinion of these authors, technology alone can never give an organization an edge over competitors or provide an industry step change. However, history has shown that technology applied with correct logistics and strategy makes a significant difference. Never has the minerals industry faced such daunting challenges and been in such need of a step change. Application of autonomous systems has been steadily increasing in the minerals industry. Automation technology has changed the mining value chain from exploration to mineral processing and refining. The future state will only see additional in-roads of automation into more processes and the whole system design. To better understand the near-future potential of automation, it is useful to explore and review the current state of automation in minerals development. A review of the state of automation research is given. The review will consider three critical areas: automation technology, system’s engineering and management processes around automation, and the role of human factors engineering in automated and semi-automated systems. The review ends with a discussion on the social and political risks of automation in terms of shared value and sustainable development.

Interactive biomedical ontology matching.

Due to continuous evolution of biomedical data, biomedical ontologies are becoming larger and more complex, which leads to the existence of many overlapping information. To support semantic inter-operability between ontology-based biomedical systems, it is necessary to identify the correspondences between these information, which is commonly known as biomedical ontology matching. However, it is a challenge to match biomedical ontologies, which dues to: (1) biomedical ontologies often possess tens of thousands of entities, (2) biomedical terminologies are complex and ambiguous. To efficiently match biomedical ontologies, in this paper, an interactive biomedical ontology matching approach is proposed, which utilizes the Evolutionary Algorithm (EA) to implement the automatic matching process, and gets a user involved in the evolving process to improve the matching efficiency. In particular, we propose an Evolutionary Tabu Search (ETS) algorithm, which can improve EA’s performance by introducing the tabu search algorithm as a local search strategy into the evolving process. On this basis, we further make the ETS-based ontology matching technique cooperate with the user in a reasonable amount of time to efficiently create high quality alignments, and make use of EA’s survival of the fittest to eliminate the wrong correspondences brought by erroneous user validations. The experiment is conducted on the Anatomy track and Large Biomedic track that are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the experimental results show that our approach is able to efficiently exploit the user intervention to improve its non-interactive version, and the performance of our approach outperforms the state-of-the-art semi-automatic ontology matching systems.

Semi-automated quantification of cartilage volume in knee osteoarthritis: responsiveness and concurrent validity

Purpose: Cartilage change on Magnetic Resonance Imaging (MRI) is a potential surrogate endpoint in osteoarthritis (OA) research. Semi-quantitative scoring systems are based on qualitative and subjective assessments that require expensive and time-intensive radiology expertise; ordinal scores also have limited sensitivity to change. Quantitative measurement of cartilage that involves manual segmentation of cartilage is also time-intensive and costly. To overcome these limitations, semi-automated software systems have been developed to measure cartilage - providing a rapid, inexpensive, quantitative and objective method of evaluating disease status and progression. A novel and semi-automated Local-Area Cartilage Segmentation (LACS) software for knee OA has previously been demonstrated to be fast, responsive, and associated with radiographic and pain progression. However, LACS was initially developed to segment medial femur cartilage only. We aimed to update and extend LACS to the lateral femur, medial tibia, and lateral tibia - and evaluate responsiveness to change, as well as correlation with existing cartilage measurements using an established independent manual segmentation method from publicly available Osteoarthritis Initiative (OAI) data. Methods: 115 participants with symptomatic knee OA were selected from the OAI progression sub-cohort, defined by definite osteophytes and frequent knee symptoms. Cartilage volume in fixed weight-bearing areas was measured with LACS on unilateral knee MRIs at the baseline and 24 month visit, paired and blinded to image date, using the sagittal 3D double-echo steady-state (DESS) sequence (3 Tesla, 0.365mm x 0.365mm, 0.7mm slice thickness, repetition time 16.5 msec, echo time 4.7 msec). Briefly, a non-expert reader identified a set of consistent anatomical landmarks for each compartment on the femur and tibia, which were used to generate consistent cartilage measurement areas. Automated edge detection algorithms then outlined cartilage in regions defined by the landmarks (Figure). The expert reader corrected the cartilage margins in areas of misidentified cartilage margins when necessary. Change in cartilage volume was calculated between the baseline and the 24-month visit. Responsiveness was quantified by standardized response mean (SRM = mean (ΔVol)/SD (ΔVol)). Concurrent validity was evaluated by estimating the correlation between LACS volume measurements and Chondrometrics measurements of cartilage thickness based on manual segmentation in the four corresponding sub-regions. Results: Baseline Kellgren-Lawrence grade distribution was KL1 4.3%, KL2 32.2%, KL3 61.7%, and KL4 1.7% in knees of the 115 participants (53% females, mean (SD) age 62.6 (±8.8) years, mean (SD) and BMI 30.1 (±5.3) kg/m2). The Figure shows a rendered 3D-model of segmented cartilage, with red areas indicating selected regions of measurement. The SRM was -0.54 for the medial femoral region and lower in the other sub-regions (Table 1). Correlation with Chondrometrics measures of cartilage thickness ranged between 0.67 and 0.88 (Table 2). The expert reader time was under 5 minutes and total reader time less than 10 minutes total per compartment. Conclusions: We updated the semi-automated LACS software method for knee cartilage segmentation to not only include the medial femur, but also medial tibia, lateral tibia, and lateral femur. The automated steps increase efficiency compared to manual segmentation, and limit the need and cost of an expert reader. We found favorable SRMs for cartilage volume change over two years with default regions of interest. The flexible nature of this software enables further adjustment of sub-regions to potentially improve responsiveness. The software correlated well against established measurements of cartilage thickness based on manual segmentation. Although a comparison between thickness and volume is not ideal, the current results are encouraging. In summary, the updated LACS software represents a powerful tool for fast segmentation of knee cartilage in larger cohorts and could facilitate clinical evaluation of potential structure modifying OA interventions.

Evaluation of six commercial products for colistin susceptibility testing in Enterobacterales

ObjectivesThe recommended technique for colistin susceptibility testing by both EUCAST and CLSI is broth microdilution (BMD). However, many routine laboratories still use other methods such as gradient strips or semi-automated systems. The objective of this study was to compare six of the most widespread commercial products for colistin susceptibility testing in Europe with in-house prepared BMD. MethodsA collection of 325 carbapenemase-producing Enterobacterales was tested for colistin susceptibility with three semi-automated systems (Vitek 2, BD Phoenix, MicroScan WalkAway), one gradient-strip test (Etest®) and two commercial BMD products (MICRONAUT-S, TREK Sensititre). BMD, in-house prepared according to ISO standard 20776-1, served as reference. ResultsThe MICRONAUT-S BMD performed best with only one false-resistant (major error, ME) and four false-susceptible (very major error, VME) results while the TREK BMD performed poorer with 16 ME and seven VME. The semi-automated systems Vitek 2 and Phoenix performed poorly with 31 and 26 VME, respectively. The WalkAway semi-automated system showed 16 and 13 false results, depending on the inoculation method. The Etest® showed six ME and 10 VME. ConclusionsThis study shows that colistin susceptibility testing remains a challenging task for laboratories. It emphasizes the need for selecting the most reliable test method to advocate proper treatment and shows that critical evaluation and precautious usage of colistin susceptibility testing results is constantly required.

Mechanism for Diabetic Retinal Blood Vessel Profile Measurement and Analysis on Fundus Images

Diabetic Retinopathy (DR) occurs due to Type II diabetes. At the early stage, if it is identified one can save their vision. Later stage, retinal detachment leads to 100% vision loss. An automatic computer based system is needed for diagnosis. There are diverse tools and automatic and semi-automatic systems are available. But the system is not identifying and measuring the narrow blood vessels accurately, because of the noise and imaging problems. Also, while tracking the retinal vessel, the narrow vessels are equally taken into consideration as wider vessels. Thus the proposed segmentation and classification techniques extract the blood vessels and measure the profile features of fundus images obtained from dissimilar modalities significantly.

Advances in machine vision for flexible feeding of assembly parts

Human-robot collaboration can be used to share workload to form semi-automated production systems. Assembly operations are recognized with high potential to increase productivity by using the best skills of humans and robots in a combination. Components and parts to be assembled need to be structured and presented to the robot in a known location and orientation. The process of presenting parts to the robot for assembly tasks is referred to as parts feeding. Feeding system needs to be adaptable to dynamics of parts’ design, shape, location, and orientation to have flexibility in the production. The traditional automation methods for parts feeding are part-specific mechanical devices e.g. vibratory bowl feeders which are inflexible towards part variations. This comes as a hindrance in getting maximum advantage of the flexibility potential of human-robot collaboration in assembly. The recent years have seen advances in machine vision and has potential for feeding applications. This paper explores the developments in machine-vision for flexible feeding systems for human-robot assembly cells. A specification model is presented to develop a vision-guided flexible feeding system. Various vision-based feeding techniques are discussed and validated through an industrial case study. The results helped to compare the efficiency of each feeding technique for industrial application.

Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology.

Embryo assessment and selection is a critical step in an in vitro fertilization (IVF) procedure. Current embryo assessment approaches such as manual microscopy analysis done by embryologists or semi-automated time-lapse imaging systems are highly subjective, time-consuming, or expensive. Availability of cost-effective and easy-to-use hardware and software for embryo image data acquisition and analysis can significantly empower embryologists towards more efficient clinical decisions both in resource-limited and resource-rich settings. Here, we report the development of two inexpensive (<$100 and <$5) and automated imaging platforms that utilize advances in artificial intelligence (AI) for rapid, reliable, and accurate evaluations of embryo morphological qualities. Using a layered learning approach, we have shown that network models pre-trained with high quality embryo image data can be re-trained using data recorded on such low-cost, portable optical systems for embryo assessment and classification when relatively low-resolution image data are used. Using two test sets of 272 and 319 embryo images recorded on the reported stand-alone and smartphone optical systems, we were able to classify embryos based on their cell morphology with >90% accuracy.

Live reconstruction of global loads on a powerboat using local strain FBG measurements

Ships often operate under challenging conditions, considering that marine environment can cause failures of the structure related to overloads, fatigue, corrosion and erosion. As a consequence, advanced methods and procedures are under development for the evaluation of the on-site structural performance for both traditionally and newly designed ships. One of the main challenges in this field is the live monitoring of the loads acting on the ship hull; the load data processing can lead, through suited algorithms, to a real-time control of ship trim and, as a consequence, to the development of automatic or semi-automatic trim control systems. The presented procedure for load reconstruction requires a well-suited sensing network. In this kind of application, a high resolution, large sampling frequencies and low sensibility to possible noise factors such as moisture, electromagnetic fields or vibrations are required. These requirements lead to the choice of Fiber Bragg Grating sensors. In this paper, an experimental methodology is proposed to reconstruct the characteristics of loads acting on a fast ship, starting from a finite number of local strain data obtained with FBG sensors. Sensors positions have been defined considering the ship hull as a beam subjected to a set of standard loads acting on a fast ship and taking into account the maximum strain positions. The development of the FE model of the ship hull, obtained from a three-dimensional CAD of a real powerboat obtained with a 3D scan, allows the calculation of the strain field related to a set of standard loads applied on the ship. The above-mentioned data are used as input for a fast-computational algorithm, in which standard and actual strain fields - provided by a network of FBG sensors - are compared to reach the reconstruction of global loads acting on the structure. The algorithm has been effectively applied in sailing condition to the powerboat, detecting the acting loads on the hull in real time.

The Era of Artificial Intelligence in Malaysian Higher Education: Impact and Challenges in Tangible Mixed-Reality Learning System toward Self Exploration Education (SEE)

Artificial Intelligence (AI) is the creation of a smart machine that has human behaviour and response. AI in the education sector is able to interact, assist, and guide students through Self-Exploration Education (SEE) in Self Determined Learning (SDL) or Heutagogical technique, such as current, but semi-automatic learning systems. Malaysian higher education institutions are forced to adapt to such a radical change in order to stay competitive and fulfill their stakeholder needs. Everyone is born as a genius, with curiosity to explore the environment through experiments. This study examines the effect of SDL on SEE in Tangible Mixed-Reality Learning System until 2030. It does that under two different lenses: First, the effect on the value proposition and the business models of the SDL. Second, it identifies hurdles for the implementation and draws strategic implications for the SDL Tangible Mixed-Reality Learning System. However, in practice, SEE is still very much focused on spreading facts rather than encouraging personal exploration. Conducting exploration of learning in the classroom can be complicated for adult learning or andragogy and is limited by virtue, money and work infrastructure. But what if we can create a middle ground between learning and fiction, the world in which adults learn and explore in ways that may be impossible in real life but still true to the transfer of knowledge? The project is to craft an imaginative and accessible tool to help adults develop scientific minds and practices through self-exploration or Do-it-yourself DIY with a mixed reality learning system that empowers adults to know the invisible and investigate hard through exploration. By 2030 the likeliest scenario is that fully Self-Exploration is solely available for particularly high-value use cases, affecting the value proposition toward provision of education services, an increase of stakeholder and value-centric value propositions fostered by continuous interactions between the Heutagogical technique and the stakeholder.

Green Internet of Things Application of a Medical Massage Robot With System Interruption

Safe operation control systems are the most important aspect of medical device development apart from the machine's function itself. Due to the fact that machines are used on people, how people can protect themselves from intelligent/programmed automatic or semiautomatic operating systems is an unavoidable problem. The Massage Robot application is based on its medical potential, lightweight nature and underlying Internet of Things (IoT) device properties. Massage robots are currently going into development in clinical trials. Handheld system interruption equipment and the robot's physical characteristics can help people achieve harmless use. In this paper, we systematically test the safety of a massage robot in an entirely real-world setting. This paper focusses on safe control operations in order to keep exploring the most reasonable safe operating modes and interrupt modes for medical devices, as well as the security interrupt priority.

TRUS applications in anal and rectal diseases

Transrectal ultrasound (TRUS), sometimes named endoanal ultrasound, is performed with dedicated endoprobes and in the hands of an experienced user, can represent an indispensable tool in evaluation of anal fistulae and abscesses in the perianal and – rectal region plus staging of anal and rectal cancer. The spatial resolution of TRUS is unsurpassed, however, MRI or CT should be used to provide a complementary overview of the entire region. The anal canal constitutes the distal approximately 4 cm of the bowel system and represents the transition between mucosal lining in the rectum and squamous cell lining of the skin. The ultrasound appearance is dominated by the change in anatomy of the muscular layers of the wall which in this small segment is made up solely of the circular, concentric muscles representing the internal and external anal sphincter. The anal canal is divided into 3 levels relating to the sphincter muscles. In rectum 5 distinctive layers corresponding to the underlying anatomy can be identified with TRUS and correlated to disease. TRUS guided intervention by means of biopsy or drainage can be performed with a rigid US probe as well as with flexible echoendoscopes. The rigid US probe with an end-fire design is optimal for endo-rectal interventions and in most cases can visualize the entire rectum including perirectal structures. With use of a dedicated needle guide mounted on the probe this technique enables precise puncture of most rectal or perirectal target seen on TRUS. TRUS guided biopsy of rectal masses is an important supplement to the conventional endoscopic biopsy if the latter technique does not provide the final diagnosis. Indications are staging of rectal cancer or suspicions of local recurrence. In these cases, a TRUS guided biopsy of the rectal masse with a 1.2 mm needle (18 gauge automatic or semi-automatic biopsy systems) can provide a deep tissue sample that often results in a final histologic diagnosis. In addition, TRUS guided biopsy is an obvious technique to provide histologic or cytologic information about enlarged lymph nodes or other suspicious perirectal masses. TRUS guided drainage of perianal and deep pelvis abscesses or other fluid collections is a safe approach and effective treatment in cases where the transabdominal percutaneous access cannot be utilized because of overlying structures. This technique provides an alternative to other access routes such as transvaginal, transgluteal or transperineal technique Smaller abscesses can often be treated with needle aspiration followed by saline irrigation, whereas larger abscesses may require continuous drainage through a catheter, which can be inserted with Seldinger technique. A preprocedure CT examination of the lower abdomen is recommended to visualize the exact location and size of the abscess in order to optimize drainage strategy.