Unnecessary Interruptions Research Articles

Balancing enjoyment and learning in teaching software project management with game-based learning

Despite advancements in project management education, project failures remain common, often due to insufficient experience and skills. Games offer a valuable platform for teaching practical project management skills, allowing players to learn from mistakes without significant economic costs. However, many serious games in this field lack focus on engagement and motivation. The "Software Project Management Game" introduced in this article addresses these issues by incorporating motivational game design principles, drawing inspiration from entertainment games like Game Dev Tycoon and The Sims. The game ensures a smooth flow without unnecessary interruptions, putting players in control. Players progress through five projects of increasing complexity, gradually developing their skills and learning soft skills and task dependencies. This article details the design, implementation, and evaluation of the game, focusing on gameflow, intrinsic motivation, perceived learning, and usability. The results indicate that the game successfully balances enjoyment and learning, making it an effective tool for teaching core project management skills.

TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated Vehicles

Explanations in automated vehicles enhance passengers' understanding of vehicle decision-making, mitigating negative experiences by increasing their sense of control. These explanations help maintain situation awareness, even when passengers are not actively driving, and calibrate trust to match vehicle capabilities, enabling safe engagement in non-driving related tasks. While design studies emphasize timing as a crucial factor affecting trust, machine learning practices for explanation generation primarily focus on content rather than delivery timing. This discrepancy could lead to mistimed explanations, causing misunderstandings or unnecessary interruptions. This gap is partly due to alack of datasets capturing passengers' real-world demands and experiences with in-vehicle explanations. We introduce TimelyTale, an approach that records passengers' demands for explanations in automated vehicles. The dataset includes environmental, driving-related, and passenger-specific sensor data for context-aware explanations. Our machine learning analysis identifies proprioceptive and physiological data as key features for predicting passengers' explanation demands, suggesting their potential for generating timely, context-aware explanations. The TimelyTale dataset is available at https://doi.org/10.7910/DVN/CQ8UB0.

Effect of Residual Gastric Volume on Risk of Ventilator-Associated Pneumonia in Adults Receiving Mechanical Ventilation and Early Enteral Feeding

Abstract Background Early enteral nutrition is the standard of care in critically ill patients receiving invasive mechanical ventilation. However, numerous studies have shown that early enteral nutrition is frequently not used. The main reason for nonuse is gastrointestinal intolerance to enteral nutrition which has been ascribed to gastroparesis with increased gastric volume, gastroesophageal reflux, and regurgitation or vomiting carrying a risk of aspiration and ventilator-associated pneumonia. Aim of the Work To test the hypothesis that the risk of ventilator-associated pneumonia is not increased when residual gastric volume is not monitored compared with routine residual gastric volume monitoring in patients receiving invasive mechanical ventilation and early enteral nutrition. Furthermore residual gastric volume monitoring may be associated with decreased calorie delivery and therefore, with underfeeding and increased morbidity. Patients and Methods This is a Prospective cohort study that was conducted at Ain Shams University Hospitals& Rashid General hospital for 6 months on critically ill patients admitted to ICU with mechanical ventilation. Sample sizes of 215 in each group totaling 430 in the study achieve 80% power to detect a non-inferiority margin difference between the group proportions of -0.0800. The reference group proportion is 0.158. The treatment group proportion is assumed to be 0.078 under the null hypothesis of inferiority. Results There was no significant difference between groups regard BMI (is calculated as weight in kilograms divided by height in meters squared), SAPS II or SOFA regard sex distribution the majority were male in both groups with no significant difference and also DM and HTN distributed with no significant difference between groups. Considering cause of admission and risk factors distribution between studied groups, in our study there is no significant difference or association between the two groups and the majority admission causes of both groups were respiratory and cancer. No significant difference between groups regard hospital stay or ICU days but MV days were significantly shorter in intervention group. In our study, Ventilator-Associated Pneumonia was significantly associated with control group as 47.4% had pneumonia while only 11.2% in intervention group had it. In the present study, cumulative calories deficit was significantly lower in intervention group, Intolerance and Prokinetic TTT were significantly associated with control group. Conclusion The current study supports the hypothesis that a protocol of enteral nutrition management without residual gastric volume monitoring is not inferior to a similar protocol including residual gastric volume monitoring in terms of protection against VAP. Residual gastric volume monitoring leads to unnecessary interruptions of enteral nutrition delivery with subsequent inadequate feeding and should be removed from the standard care of critically ill patients receiving invasive mechanical ventilation and early enteral nutrition.

A survey of deep learning-driven architecture for predictive maintenance

Over the past decades, deep learning techniques have attracted increased attention from various research and industrial domains aligned with the development of Industry Internet-of-Things(IIoT). Specifically, with the advantage of data-driven methods, industrial organizations are seeking novel proactive strategies supported by analytic models to guarantee the quality of their production by observing degradation or predicting failure ahead of the occurrence of the component or asset. Predictive strategies are expected to promise the influence of unnecessary maintenance interruptions and mitigate the consequence of that, hence, extending the remaining useful life of products. This paper conducts a survey of the utilization of deep learning technologies on engineering applications where they provide satisfactory solutions with respect to specific data types or input signals. 106 primary papers are reviewed on deep learning–driven approaches which mainly explore five of the most popular architectures in the application of predictive maintenance. The main content of this paper summarizes the common advantages of each architecture and, accordingly, points out their limitations, as well as describes the application scopes of fully connected deep neural networks, convolutional neural networks, stacked autoencoders, deep belief networks, and deep recurrent neural networks. Based on the technique discussion for each of them, we intend to provide a comprehensive understanding and guidance of the appropriate usage of deep learning architectures to devise an effective predictive maintenance strategy for the scientific and industrial developers whose expertise lies in the prior domain knowledge of multi-source isomerization data. Moreover, the main content demonstrated the summarization of the decisive factor by which the incremental stages of the approaches were determined, fundamentally including the dataset specification, feature extraction, and the integration of deep learning approaches.

Pola Komunikasi Interpersonal Siswa SMAN Sidikalang Terhadap Kecanduan Bermain Game Mobile Legend

This research aims to determine the interpersonal communication patterns of SMAN 1 Sidikalang students regarding their addiction to playing Mobile Legends games. This research uses a qualitative descriptive method. This research is a field study. The data in this research comes from primary data obtained directly through direct findings in the research area such as the results of interviews and observations. This research data also comes from secondary data obtained through literature that relates to the research context such as journal articles and books. Data collection techniques in this research used semi-structured interviews and non-participant observation. Data analysis in this research was carried out by reducing, presenting, and then verifying the research data. The results of this research show that the interpersonal communication approach applied by teachers at SMA Negeri 1 Sidikalang is very focused on creating positive relationships with students. They listen attentively, show genuine interest, and avoid unnecessary interruptions. The body language they use supports a positive atmosphere, and simple language creates a comfortable environment. Teachers give praise to increase students' self-confidence and provide criticism wisely. They also demonstrate self-control and emotional maturity, helping students overcome gaming addiction problems. All of these approaches aim to create positive interpersonal relationships and provide important support in student development.

Automatic Signal and Gate System

Abstract: The "Automatic Signal and Gate System" project is a hardware setup aimed at improving safety on roads, particularly in hilly areas and railway crossings. By utilizing an Arduino UNO and an IR sensor module, the system focuses on signaling in challenging terrains, emphasizing the Automatic Rail Gate Signaling System to prevent rail crossing accidents. This project addresses the pressing issue of accidents and interruptions in rail tracks, which are prevalent in India, a densely populated country. Through the implementation of IR sensors, the system detects the presence of trains and transmits signals to the Arduino. The Arduino, in turn, controls the gate and signals using a servo motor, effectively enhancing safety measures at rail crossings. With a strong emphasis on this specific concept, the project aims to minimize rail crossing accidents and optimize the efficiency of rail gates and crossings. By concentrating efforts on this critical aspect, the system strives to mitigate accidents, reducing unnecessary interruptions in rail track operations and maximizing safety for commuters and railway personnel alike

SMARTCOPE: Smartphone Change Of Possession Evaluation for continuous authentication

The goal of continuous smartphone authentication is to detect when the adversary has gained possession of the user’s device post-login. This is achieved by triggering re-authentication at fixed, frequent intervals. However, these intervals do not take into account external information that might indicate that the impostor has gained physical access to the user’s device. Continuous smartphone authentication typically relies on behavioral cues, such as hand movement and touchscreen swipes, that can be collected without interrupting the user’s activity. Because these behavioral signals are characterized by relatively high error rates compared to physiological biometrics, their use at fixed intervals leads to unnecessary interruptions to the user’s activity in case of a false reject, and to not recognizing the impostor in case of a false accept.To address these issues, in this paper we introduce a novel framework called SMARTCOPE: Smartphone Change Of Possession Evaluation. In this work, SMARTCOPE leverages smartphone movement signals collected during user activity to determine when the smartphone is no longer in the hands of its owner. When this occurs, SMARTCOPE triggers re-authentication. By using these signals, we are able to reduce the total number of re-authentication points while simultaneously lowering re-authentication error rates. Our analysis shows that our technique can reduce equal error rates by over 40%, from 7.8% to 4.6% using movement and keystroke features. Further, we show that SMARTCOPE can be used to transform a static (login-time) authentication system, such as face recognition, to a continuous re-authentication system, with a significant increase in security and limited impact on usability.

Immunisation status during biologic therapy for hidradenitis suppurativa and psoriasis

AbstractBackgroundThe use of biologic agents has significantly improved the quality of life for patients with chronic skin diseases, and many other autoinflammatory diseases, over the past two decades. Due to the immunosuppressive nature of biologic agents, patients on these treatments are at increased risk of infection. Compulsory serological testing and vaccine optimisation before commencing biologic therapy is not common practice, potentially leaving some of these patients exposed to vaccine‐preventable disease.ObjectivesOur real‐world data aims to assess if the use of biologic agents in patients with hidradenitis suppurativa and psoriasis leads to an accelerated loss of immunity to diseases commonly vaccinated against.MethodsWe present 77 patients with psoriasis and hidradenitis who underwent serological testing before and after commencing biologic treatment. Statistical analysis, using the Z‐test for differences between two populations, was used to determine if a significant number of patients lost immunity after commencing biologic therapy for the treatment of their skin disease.ResultsA significant number of our patients lost immunity, especially to Hepatitis B (p < 0.001) and Diphtheria (p < 0.001), whilst being treated with a biologic agent.ConclusionsWhilst no control group was included in this real‐world study, our findings suggest that biologic agents may shorten the longevity of vaccine‐induced immunity and calls for future, larger‐scale, prospective studies. We recommend pre‐biologic serology testing and vaccine optimisation to reduce the risk of vaccine‐preventable illnesses and unnecessary treatment interruptions.

Antiretroviral stewardship in a tertiary academic hospital: The need for a clinical pharmacist.

South Africa has the highest prevalence of people living with HIV globally. Although antiretroviral therapy provides solutions, evidence of antiretroviral resistance emerged, requiring the application of antiretroviral-stewardship programmes to curb medication-related problems. Identify and describe antiretroviral-stewardship pharmacist interventions in an active antiretroviral-stewardship programme. HIV-positive adults admitted to medical wards at a tertiary academic hospital in South Africa. A descriptive quantitative study was performed, utilising an antiretroviral-stewardship assessment tool to determine antiretroviral-related recommendations in the treatment of HIV-positive adults. The study employed purposive sampling. Treatment charts were evaluated to identify antiretroviral-stewardship recommendations. The number of recommendations highlighted the need for a clinical pharmacist in an active antiretroviral-stewardship programme. Descriptive data analysis with Pearson correlations was employed to display the data. Medication-related problems were identified in 100% of study patients (n = 41), with an average of 2.46 interventions per patient. One-hundred-and-one medication-related problems were identified by using the antiretroviral-stewardship assessment tool. The identified problems included a lack of viral load testing (41, 100%), lack of CD4 count monitoring (15; 36.6%) and lack of prophylactic treatment against opportunistic infections (10; 24.4%). Medication-related problems included the presence of clinically significant drug-drug interactions and serious side effects, CD4 count decline despite being on antiretroviral therapy, unnecessary treatment interruptions including risk for IRIS, inappropriate antiretroviral therapy regimen, non-adherence and absence of treating tuberculosis as co-morbidity. Present study demonstrates the need of an active antiretroviral-stewardship programme's benefits. The possible role of the clinical pharmacist as active participant and leader in this programme is highlighted. Highlight the role of clinical pharmacists in antiretroviral stewardship.

089 Elucidating the pathomechanism of immune checkpoint inhibitors enhanced Stevens-Johnson syndrome/toxic epidermal necrolysis will prevent unnecessary immune checkpoint inhibitor interruptions

089 Elucidating the pathomechanism of immune checkpoint inhibitors enhanced Stevens-Johnson syndrome/toxic epidermal necrolysis will prevent unnecessary immune checkpoint inhibitor interruptions

A Decision-Making Tool for Port Operations Based on Downtime Risk and Met-Ocean Conditions including Infragravity Wave Forecast

Port downtime leads to economic losses and reductions in safety levels. This problem is generally assessed in terms of uni-variable thresholds, despite its multidimensional nature. The aim of the present study is to develop a downtime probability forecasting tool, based on real problems at the Outer Port of Punta Langosteira (Spain), and including infragravity wave prediction. The combination of measurements from three pressure sensors and a tide gauge, together with machine-learning techniques, made it possible to generate long wave prognostication at different frequencies. A fitting correlation of 0.95 and 0.9 and a root mean squared error (RMSE) of 0.022 m and 0.012 m were achieved for gravity and infragravity waves, respectively. A wave hindcast in the berthing areas, met-ocean forecast data, and information on 15 real operational problems between 2017 and 2022, were all used to build a classification model for downtime probability estimation. The proposed use of this tool addresses the problems that arise when two consecutive sea states have thresholds above 3.97%. This is the limit for guaranteeing the safety of port operations and has a cost of just 0.6 unnecessary interruptions of operations per year. The methodology is easily exportable to other facilities for an adequate assessment of downtime risks.

Identifying positive and negative use of non-technical skills by anesthesiologists in the clinical operating room: An exploratory descriptive study

BackgroundTeamwork is a critical competency in high-risk settings like the operating room (OR). While conventional approaches focus on describing and learning from negative performance, there may be value in learning from high-performing behaviour, particularly in specialties where serious safety events are relatively rare. This study aimed to explore both the positive and negative use of non-technical skills by anesthesia practitioners in the OR and situate them within the clinical OR context. MethodsThis study employed a prospective observational design. Following research ethics approval, a sample of surgical cases in a tertiary hospital were recorded using the OR Black Box®. Data related to surgical phase timing, non-technical skills, team factors, and environmental factors were identified by analysts according to a modified Systems Engineering Initiative for Patient Safety model. We performed descriptive statistics and qualitative description of these observations. ResultsWe observed 25 surgical cases capturing 242 instances of positive non-technical skills among anesthesiologists in the operating room and 9 instances of negative demonstrations. Situational awareness was most frequently (n = 160) observed, followed by communication and teamwork skills (n = 82), and were most often demonstrated in the context of potential environmental distractions (e.g., doors opening, unnecessary interruptions). The least common category of positive non-technical skills observed was leadership (n = 3). ConclusionsOur findings show anesthesiologists are doing a lot “right” and there may be many opportunities for learning from positive practice in the clinical setting. These findings can inform future work to better understand and standardize best practices for non-technical performance in anesthesia.

Crossing the line: The violating effects of illegitimate interruptions from work and the differential impact on work‐to‐family conflict by gender

SummaryDespite interruptions from work being increasingly common for many employees, their inherently disruptive nature induces strain on the work–life interface; yet, it remains unclear why the experienced strain is not universal. Drawing on role identity and Stress‐as‐Offense‐to‐Self theories, illegitimate interruptions from work (IIWs) are inappropriate, avoidable, unnecessary, or unreasonable interruptions that carry an added meaning of disrespect, thereby presenting a threat to the self and potentially inducing additional unnecessary strain. Differential value placed on professional and personal roles likely shapes attributions of illegitimacy. We collected event‐based data over 5 days from 182 employees (432 interruptions). Our multilevel moderated mediation model established IIW's indirect effect on work‐to‐family conflict (WFC) via boundary violation, above and beyond the negative effects of interruptions themselves. Thus, subjectively ascribed illegitimacy induces further but potentially unnecessary negative strain. Men were more likely to experience boundary violation in reaction to IIWs and subsequently reported more WFC as compared to women. Yet, although results suggest that IIWs may be a more salient immediate threat to men, it is possible that women's higher threshold for IIWs may present a more distal threat for gender parity. We offer guidance for developing strategies to reduce IIWs and mitigate their impact.

The Effects of Information Communication Technology on Administrative Efficiency of Tamale Technical University

The aim of the study was to assess the effect of Information Communication Technology (ICT) on administrative efficiency using the Tamale Technical University (TaTU) as a study area. A descriptive quantitative design was adopted. The total population was stratified into teaching and non-teaching and samples were drawn from each stratum by the method of purposive sampling and a total of 214 respondents were arrived and used for this study. Structured questionnaire was used in collecting data. The study found that TaTU has deployed ICT in administrative functions to some extent even though the ICT logistics are still not available in offices for the administrative functions. The deployment of ICT at the administrative functions improves efficiency and effectiveness. The study however revealed: the lack of human resource management software as well as antivirus software; the lack of proper maintenance; inadequate budget allocations; lack of in-service trainings; using different brands of ICT logistics; and unstable internet connections are the challenges bedeviling the ICT deployment in the University. Standardized brands of modern ICT facilities need to be provided together with reliable internet facilities at all times to avoid unnecessary interruptions which affect efficiency. The maintenance culture of the ICT logistics should also be improved and training of in-service personnel on the usage of the ICT facilities to help ensure their efficient utilization in the University.

Is monitoring of gastric residual volume for critically ill patients with enteral nutrition necessary? A meta-analysis and systematic review.

There are many controversies over the necessity of monitoring gastric residual volume in the nursing care of enteral nutrition. We aimed to conduct an updated meta-analysis to evaluate the effects of monitoring or not monitoring gastric residual volume on patients' outcomes and complications. We searched the Cochrane Library database to 15 April 2021 for randomized controlled trials (RCTs) on the effects of gastric residual volume and no gastric residual volume monitoring. Review Manager software was used for data analysis. A total of seven RCTs involving 1240 enteral nutritionpatients were included. Gastric residual volume monitoring was associated with reduced incidence of vomiting (OR2.33, 95% CI:1.68-3.24), whereas no gastric residual volume monitoring was associated with reduced incidence of unnecessary interruptions of enteral nutrition (OR0.38,95% CI:0.26-0.55). There were no significant differences on the incidence of abdominal distention (OR1.87, 95% CI:0.82-4.28), diarrhoea (OR1.03,95% CI:0.74-1.43), VAP (OR0.83, 95%CI:0.37-1.89), duration of mechanical ventilation (MD -0.06,95% CI:-1.22-1.10), length of ICU stay (MD -1.33, 95% CI:-3.58-0.91) and mortality (OR0.90,95% CI:0.61-1.34). Not monitoring gastric residual volume is associated with reduced unnecessary interruptions of enteral nutrition related to inadequate feeding and increased risk of vomiting.

Medication Interruptions and Subsequent Disease Flares During the COVID-19 Pandemic: A Longitudinal Online Study of Patients With Rheumatic Disease.

ObjectiveWe aimed to assess trends in anxiety and interruptions in disease‐modifying antirheumatic drug (DMARD) use among patients with rheumatic diseases during the COVID‐19 pandemic and to evaluate whether DMARD interruptions were associated with disease flares.MethodsArthritisPower, the Vasculitis Patient‐Powered Research Network, and other patient organizations invited members to join a 52‐week longitudinal study, with baseline surveys completed March 29 to June 30, 2020, with follow‐up through May 2021. Logistic regression incorporating generalized estimating equations evaluated associations between interruptions in DMARD use and self‐reported disease flares at the next survey, adjusting for demographic characteristics, medications, disease, and calendar time.ResultsAmong 2,424 patients completing a median of 5 follow‐up surveys, the mean age was 57 years, 87% were female, and the most common conditions were rheumatoid arthritis, vasculitis, and psoriatic arthritis. Average Patient‐Reported Outcomes Measurement Information System (PROMIS) anxiety T scores decreased from April 2020 (58.7) to May 2021 (53.7) (P < 0.001 for trend). Interruptions in DMARD use decreased from April (11.2%) to December 2020 (7.5%) (P < 0.001) but increased through May 2021 (14.0%) (P < 0.001). Interruptions in DMARD use were associated with a significant increase in severe flares (rated ≥6 of 10) at the next survey (12.9% versus 8.0% [odds ratio (OR) 1.71 (95% confidence interval [95% CI 1.23, 2.36]) although not any flare (OR 1.18 [95% CI 0.89, 1.58])].ConclusionAnxiety and interruptions in DMARD use initially decreased over time, but DMARD interruptions increased during 2021, possibly related to an increase in COVID‐19 cases or vaccine availability. Interruptions in DMARD use were associated with increased rates of severe disease flares, highlighting the importance of avoiding unnecessary DMARD interruptions.

MANAGE YOUR SUCCESS OF BUSINESS

The success of any business starts with how well you are able to manage yourself. Some useful tips for self management. Before you have even started your business, start developing a leadership vision. The responsibility for the growth you wish to achieve in your businesses, squarely lies on your shoulder. The benefit that is likely to accrue by implementing the decision and come out a winner. When you start a business, failure can be an important part of learning and growing. Unnecessary meetings, interruptions and inefficiency may sap you of your energy, leaving a little for the important aspects of business. Create an environment where people have the opportunity to increase their skills and are rewarded for doing so that. To be succeeding in business today, you have need of to be flexible and have good planning and organizational skills. Many people start a business thinking that they turn on their are computers or open the doors and start making money, One and only to find that making money in a business is much more difficult than they are thinking. You can continue away from this in your business ventures by taking your time and planning out all the necessary stepladder you need to achieve success. Anything type of business you want to start, using the following nine strategy can help you be successful in your project.

Real-Time Detection of Overloads on the Plasma-Facing Components of Wendelstein 7-X

Wendelstein 7-X (W7-X) is the leading experiment on the path of demonstrating that stellarators are a feasible concept for a future power plant. One of its major goals is to prove quasi-steady-state operation in a reactor-relevant parameter regime. The surveillance and protection of the water-cooled plasma-facing components (PFCs) against overheating is fundamental to guarantee a safe steady-state high-heat-flux operation. The system has to detect thermal events in real-time and timely interrupt operation if it detects a critical event. The fast reaction times required to prevent damage to the device make it imperative to automate fully the image analysis algorithms. During the past operational phases, W7-X was equipped with inertially cooled test divertor units and the system still required manual supervision. With the experience gained, we have designed a new real-time PFC protection system based on image processing techniques. It uses a precise registration of the entire field of view against the CAD model to determine the temperature limits and thermal properties of the different PFCs. Instead of reacting when the temperature limits are breached in certain regions of interest, the system predicts when an overload will occur based on a heat flux estimation, triggering the interlock system in advance to compensate for the system delay. To conclude, we present our research roadmap towards a feedback control system of thermal loads to prevent unnecessary plasma interruptions in long high-performance plasmas.

919. Rates of False-Positive Hepatitis B Surface Antigen Is Low in Cancer Patients

BackgroundAccurate interpretation of hepatitis B virus (HBV) laboratory testing is paramount in avoiding inaccurate diagnosis and incorrect management that could lead to unnecessary and overtreatment. This is particularly relevant in patients with cancer where universal testing is recommended in order to avoid HBV reactivation. Hepatitis B surface antigen testing (HBsAg) positivity indicates chronic or acute HBV infection. The rates and outcomes of a false-positive HBsAg have not been established for patients with cancer.MethodsThree hundred and ninety-seven patients with any type of cancer and positive HBsAg seen at MD Anderson Cancer Center from January 2016 – January 2021 were retrospectively reviewed in this study approved by the institutional review board. Cases of false-positive HBsAg were defined as those patients with a positive HBsAg but negative HBsAg quantitative, negative HBV core antibody (total Ig), and undetectable HBV DNA within 30 days of positive HBsAg testing. Serum samples from patients were tested for HBsAg using Vitros Enhanced Chemiluminescent Immunoassay (Ortho-Clinical Diagnostics, Raritan, NJ, USA). Data collection includes demographics, past medical history, underlying cancer and its stage, prior cancer treatment, risk factors for HBV, co-infections (hepatitis C, HIV), symptoms, liver function tests, anti-HBV treatment, and interruptions on cancer treatment.ResultsOut of 397 patients with a positive HBsAg, 33 were excluded as they did not meet the diagnostic criteria or have insufficient HBV data. Of them, 3 cases (0.8%) were identified as false positive HBsAg. All 3 patients were female, white, and had progressive malignancy (Table 1). No prior history of liver disease or liver function abnormalities were noted with these 3 patients. Initially, antiviral treatment was started on 1 patient which was discontinued shortly after confirmation of false-positive HBsAg. All 3 patients had additional workup and evaluation by an HBV specialist. In 2 patients, cancer treatment was canceled or delayed. ConclusionAlthough uncommon, cancer patients with false-positive HBsAg need further workup to avoid overtreatment and unnecessary interruptions in cancer careDisclosures Jessica P. Hwang, MD, MPH , Merck (Grant/Research Support)

Convolutional Neural Network and Long-Short Term Memory based for Identification and Classification of Power System Events

In this present era, power system delivery has to be reliable and sustainable. The growth of demands increasing the complexity of the power system operations. An interrupted power supply must not occur for any reason. Hence, the improvement of the controller and protection devices is mandatory. One of the unnecessary interruptions in the power system is a false trip due to the incorrect setting of the protection devices. Therefore, a method to classify the symptom of the power system based on the voltage, current, and frequency measurements is required. However, since there are a ton of maneuver options and fault types, the number of data becomes complex, enormous, and irregular. This is where deep learning takes place. This paper proposed the use of Convolutional Neural Networks (CNN) combined with Long-Short Term Memory (LSTM) to recognize the categorize the type of events in a medium voltage power distribution network. As CNN's models are great at decreasing frequency variation, LSTM is great for temporal modeling, we take benefit of CNN's and LSTM's complementarity in this study by integrating it into a unified architecture. The simulation results indicate that CNN and LSTM can recognize the symptoms in power system operation with accuracy up to 79 % with a total epoch 350.