Search results for: automated early warning score

Authors: Dustin Schöder

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The potential benefits of the utilization of highly automated and autonomous trucks in logistics operations are the subject of interest to the entire logistics industry. The benefits of the use of these new technologies were scientifically investigated and implemented in roadmaps. So far, reliable data and experiences from real life use cases are still limited. A German research consortium of both academics and industry developed a highly automated (SAE level 4) vehicle for yard operations at railports and container depots. After development and testing, a several month field test at the DUSS Terminal in Ulm-Dornstadt (Germany) and the nearby DB Intermodal Services Container Depot in Ulm-Dornstadt was conducted. The truck was piloted in a shuttle service between both sites. In a holistic automation approach, the vehicle was integrated into a digital communication platform so that the truck could move autonomously without a driver and his manual interactions with a wide variety of stakeholders. The main goal is to investigate the effects of highly automated trucks in the key processes of container loading, unloading and container relocation on holistic railport yard operation. The field test data were used to investigate changes in process efficiency of key processes of railport and container yard operations. Moreover, effects on the capacity utilization and potentials for smothering peak workloads were analyzed. The results state that process efficiency in the piloted use case was significantly higher. The reason for that could be found in the digitalized data exchange and automated dispatch. However, the field test has shown that the effect is greatly varying depending on the ratio of highly automated and manual trucks in the yard as well as on the congestion level in the loading area. Furthermore, the data confirmed that under the right conditions, the capacity utilization of highly automated trucks could be increased. In regard to the potential for smothering peak workloads, no significant findings could be made based on the limited requirements and regulations of railway operation in Germany. In addition, an empirical survey among railport managers, operational supervisors, innovation managers and strategists (n=15) within the logistics industry in Germany was conducted. The goal was to identify key characteristics of future railports and terminals as well as requirements that railports will have to meet in the future. Furthermore, the railport processes where automation and autonomization make the greatest impact, as well as hurdles and challenges in the introduction of new technologies, have been surveyed. Hence, further potential use cases of highly automated and autonomous applications could be identified, and expectations have been mapped. As a result, a highly detailed and practice-based roadmap towards a ‘terminal 4.0’ was developed.

Keywords: highly automated driving, autonomous driving, SAE level 4, railport operations, container depot, intermodal logistics, potentials of autonomization

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Authors: Kanak Parmanandani

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The present study aims to explore the impact of perceived parenthood styles in early nonage on attachment styles, and how it affects the emotional capacity of youthful grown-ups. Current studies suggest that there are 4 attachment styles. An existent gets attached to their significant other and important people, and understanding attachment styles helps to dissect a person’s nonage and duly understand an existent. Parenthood styles play a major part in children’s early development, and how they see the world and the people around them. A parent plays a huge part in the emotional development of a child. Both parents must be present to give their children a healthy terrain to grow up.

Keywords: parent styles, attachment styles, early development, parenting styles

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Authors: Sule Pallavi, Shah Priyank, Thavkar Amit, Rohira Poonam, Mehta Suyog

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Introduction: Minoxidil has been used topically for a long time to assist hair growth in the management of male androgenetic alopecia. The aim of this study was a comparative assessment of the irritation potential of three commercial formulations of minoxidil 2% topical solution in a human patch test. Methodology: The study was a non-randomized, double-blind, controlled, single-center study of 56 healthy adult Indian subjects. A 24-hour occlusive patch test was conducted with three formulations of minoxidil 2% topical solution. Products tested were aqueous-based minoxidil 2% (AnasureTM 2%, Sun Pharma, India – Brand A), alcohol-based minoxidil 2% (Brand B) and aqueous-based minoxidil 2% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate as a negative and positive control, respectively, were included. Patches were applied on the back, followed by removal after 24 hours. The Draize scale (0-4 points scale for erythema/dryness/wrinkles and for oedema) was used to evaluate and clinically score the skin reaction under constant artificial daylight 24 hours after the removal of the patches. The patch test was based on the principles outlined by Bureau of Indian Standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). A mean combined score up to 2.0/8.0 indicates that a product is “non-irritant,” and a score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and a score above 4.0/8.0 indicates “irritant”. In case of any skin reaction that was observed, a follow-up was planned after one week to confirm recovery. Results: The 56 subjects who participated in the study had a mean age of 28.7 years (28 males and 28 females). The combined mean score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.29± 0.53 (Brand B), 0.30 ± 0.46 (Brand C), 3.25 ± 0.77 (positive control) and 0.02 ± 0.13 (negative control). This mean score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.016) and that of Brand C (p=0.004). The mean erythema score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.27 ± 0.49 (Brand B), 0.30 ± 0.46 (Brand C), 2.5 ± 0.66 (positive control) and 0.02 ± 0.13 (negative control). The mean erythema score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.019) and that of Brand C (p=0.004). Reactions that were observed 24 hours after patch removal subsided in a week’s time. Conclusion: Based on the human patch test as per the BIS, IS 4011:2018, all the three topical formulations of minoxidil 2% were found to be non-irritant. Brand A of 2% minoxidil (Sun Pharma) was found to be the least irritant than Brand B and Brand C based on the combined mean score and mean erythema score.

Keywords: erythema, irritation, minoxidil, patch test

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Authors: Moses Balina, Archbald Bahizi

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Introduction: Early onset neonatal sepsis is a systemic infection in a newborn baby during the first week after birth and contributes to 50% of neonatal deaths each year. Risk factors for early onset neonatal sepsis, which can be maternal, health care provider, or health care facility associated, can be prevented with access to quality antenatal care. Objective: The objective of the study was to assess early onset neonatal sepsis and antenatal factors associated with Fort Portal Regional Referral Hospital. Methodology: A cross sectional study design was used. The study involved 60 respondents who were mothers of breastfeeding neonates being treated for early onset neonatal sepsis at Fort Portal Regional Referral Hospital neonatal intensive care unit. Simple random sampling was used to select study participants. Data were collected using questionnaires, entered in Stata 16, and analysed using logistic regression. Results: The prevalence of early onset neonatal sepsis at Fort Portal Regional Referral Hospital was 25%. Multivariate analysis revealed that institutional factors were the only antenatal factors found to be significantly associated with early onset neonatal sepsis at Fort Portal Regional Referral Hospital (p < 0.01). Bivariate analysis revealed that attending antenatal care at a health centre III or IV instead of a hospital (p = 0.011) and attending antenatal care in health care facilities with no laboratory investigations (p = 0.048) were risk factors for early onset neonatal sepsis in the newborn at Fort Portal Regional Referral Hospital. Conclusion: Antenatal factors were associated with early onset neonatal sepsis, and health care facility factors like lower level health centre and unavailability of quality laboratory investigations to pregnant women contributed to early onset neonatal sepsis in the newborn. Mentorships, equipping/stocking laboratories, and improving staffing levels were necessary to reduce early onset neonatal sepsis.

Keywords: antenatal factors, early onset neonatal sepsis, neonates 0-7 days, fort portal regional referral hospital

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Authors: Ali Ashtiani, Hamid Shirazi

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This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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Authors: Aqleem Fatimah

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The purpose of study was to find out the impact of teachers’ gender on students’ score achievement. Focusing on primary level’s teachers & students, a survey research was conducted by using convenient sampling technique. All the students of grade four (1500) and fifty-six teachers (equally divided by gender) from the 50 randomly selected coeducational schools from Lahore were taken as sample. The academic performance was operationalized using a t-test on standardized achievement tests of the students in language, science mathematics and social studies. In addition, all those gender based characteristics of teachers that count a lot in classroom interactions (taking Multi-grade classes, classroom strategies, feedback strategies and evaluation method) that influence students’ achievement were also analyzed by using a questionnaire and an observation schedule. The results of the study showed better academic achievement of students (girl &boy) of female teachers comparatively to the students of male teachers. Therefore, as the female teachers’ number lacks in Pakistan, the study suggests policy makers to seek guidelines to induct more specialized and professionally competent female teachers because their induction will prove highly beneficial for the betterment of students’ score achievement.

Keywords: gender, teacher, competency, score achievement

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Authors: Bekmurza H. Aitchanov, Sholpan K. Aitchanova, Olimzhon A. Baimuratov, Aitkul N. Aldibekova

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This work considers the automated control system (ACS) of milk quality during its magnetic field processing. For achieving high level of quality control methods were applied transformation of complex nonlinear systems in a linearized system with a less complex structure. Presented ACS is adjustable by seven parameters: mass fraction of fat, mass fraction of dry skim milk residues (DSMR), density, mass fraction of added water, temperature, mass fraction of protein, acidity.

Keywords: fluids magnetization, nuclear magnetic resonance, automated control system, dynamic pulse-frequency modulator, PFM, nonlinear systems, structural model

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Authors: Peter Sabev, Katalina Grigorova

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Test automation allows performing difficult and time consuming manual software testing tasks efficiently, quickly and repeatedly. However, development and maintenance of automated tests is expensive, so it needs a proper prioritization what to automate first. This paper describes a simple yet efficient approach for such prioritization of test cases based on the effort needed for both manual execution and software test automation. The suggested approach is very flexible because it allows working with a variety of assessment methods, and adding or removing new candidates at any time. The theoretical ideas presented in this article have been successfully applied in real world situations in several software companies by the authors and their colleagues including testing of real estate websites, cryptographic and authentication solutions, OSGi-based middleware framework that has been applied in various systems for smart homes, connected cars, production plants, sensors, home appliances, car head units and engine control units (ECU), vending machines, medical devices, industry equipment and other devices that either contain or are connected to an embedded service gateway.

Keywords: automated testing, manual testing, test automation, software testing, test prioritization

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Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

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Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Eun Jae Ko, In Young Sung, Eui Soo Joeng

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Cognitive impairment is commonly encountered problem in children with various clinical diseases, including Down syndrome, autism spectrum disorder, brain injury, and others. Cognitive impairment limits participation in education and society, and this further hinders development in cognition. However, young children with cognitive impairment tend not to respond well to traditional cognitive treatments, therefore alternative treatment choices are need. As a cognitive training program, touch screen technology can easily be applied to very young children by involving visual and auditory support. Injini was developed as tablet computer based cognitive rehabilitation program for young children or individuals with severe cognitive impairment, which targeted on cognitive ages of 18 to 36 months. The aim of this study was to evaluate the efficacy of a tablet computer based cognitive rehabilitation program (Injini) for children with cognitive impairment. 38 children between cognitive ages of 18 to 36 months confirmed by cognitive evaluations were recruited and randomly assigned to the intervention group (n=20) and the control group (n=18). The intervention group received tablet computer based cognitive rehabilitation program (Injini) for 30 minutes per session, twice a week, over a period of 12 weeks, in addition to the traditional rehabilitation program. The control group received traditional rehabilitation program only. Mental score of Bayley Scales of Infant Development II (BSID II), Pediatric Evaluation of Disability Inventory (PEDI), Laboratory Temperament Assessment Battery (Lab-TAB), Early Childhood Behavior Questionnaire (ECBQ), and Goal Attainment Scale (GAS) were evaluated before and after 12 weeks of therapeutic intervention. When comparing the baseline characteristics, there was no significant difference between the two groups in the measurements of cognitive function. After 12 weeks of treatment, both group showed improvements in all measurements. However, in comparison of improvements after treatment, the intervention group showed more improvements in the mental score of BSID II, social function domain of PEDI, observation domain of Lab-TAB, and GAS, as compared to the control group. Application of the tablet computer based cognitive rehabilitation program (Injini) would be beneficial for improvement of cognitive function in young children with cognitive impairment.

Keywords: cognitive therapy, computer-assisted therapy, early intervention, tablets

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Authors: Dovile Petkeviciute-Barysiene

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Legal technologies not only create new ways for accessing and providing legal services but also transform the role of legal practitioners. Both lawyers and users of legal services expect automated solutions to outperform people with objectivity and impartiality. Although fairness of the automated decisions is crucial, research on assessing various characteristics of automated processes related to the perceived fairness has only begun. One of the major obstacles to this research is the lack of comprehensive understanding of what legal actions are automated and could be meaningfully automated, and to what extent. Neither public nor legal practitioners oftentimes cannot envision technological input due to the lack of general without illustrative examples. The aim of this study is to map decision making stages and automation levels which are and/or could be achieved in legal actions related to pre-trial and trial processes. Major legal decisions and judgments are identified during the consultations with legal practitioners. The dual-process model of information processing is used to describe cognitive processes taking place while making legal decisions and judgments during pre-trial and trial action. Some of the existing legal technologies are incorporated into the analysis as well. Several published automation level taxonomies are considered because none of them fit well into the legal context, as they were all created for avionics, teleoperation, unmanned aerial vehicles, etc. From the information processing perspective, analysis of the legal decisions and judgments expose situations that are most sensitive to cognitive bias, among others, also help to identify areas that would benefit from the automation the most. Automation level analysis, in turn, provides a systematic approach to interaction and cooperation between humans and algorithms. Moreover, an integrated map of legal decisions and judgments, information processing characteristics, and automation levels all together provide some groundwork for the research of legal technology perceived fairness and acceptance. Acknowledgment: This project has received funding from European Social Fund (project No 09.3.3-LMT-K-712-19-0116) under grant agreement with the Research Council of Lithuania (LMTLT).

Keywords: automation levels, information processing, legal judgment and decision making, legal technology

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Authors: J. Al-Dmour, A. Sagahyroon, A. Al-Ali, S. Abusnana

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Radio Frequency Based Identification Systems have emerged as one of the possible valuable solutions that can be utilized in healthcare systems. Nowadays, RFID tags are available with built-in human vital signs sensors such as Body Temperature, Blood Pressure, Heart Rate, Blood Sugar level and Oxygen Saturation in Blood. This work proposes the design, implementation, and testing of an integrated mobile RFID-based health care system. The system consists of a wireless mobile vital signs data acquisition unit (RFID-DAQ) integrated with a fuzzy-logic–based software algorithm to monitor and assess patients conditions. The system is implemented and tested in ‘Rashid Center for Diabetes and Research’, Ajman, UAE. System testing results are compared with the Modified Early Warning System (MEWS) that is currently used in practice. We demonstrate that the proposed and implemented system exhibits an accuracy level that is comparable and sometimes better than the widely adopted MEWS system.

Keywords: healthcare, fuzzy logic, MEWS, RFID

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: Supalak Fakkhum, Wannita Pochanakul

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This research is qualitative research that aims to study the application of local wisdom in health care of early childhood at Ban Nam Chieo Community, Laem Ngop, Trat Province. The target is one folk medicine healer and 45 parents who have children or grandchildren aged between 0-5 years. The folk medicine healer was interviewed and observed during early childhood health care practice. Parents were interviewed. The results showed that local wisdom in health care of early childhood are as follows: 1. Local wisdom about early childhood diseases: It is believed that the disease was determined while the child was still in the womb, in the third month of pregnancy. When a child is born, they will have La, La-ong and Saang diseases, which are URI (upper respiratory infection) and DI (diarrhea) diseases. Supernatural aspect is also considered. 2. The treatment is chosen to match the symptoms of the disease. Caring for early childhood includes psychological therapy by rituals and spells. 3. For local wisdom concerning prevention and health promotion, parents normally bring their child to folk medicine healers for “throat paint” as an act of protection and health promotion. Folk healers often prescribe food according to belief and local wisdom.

Keywords: local wisdom, early childhood, folk medicine, healer

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Authors: H. J. Wattimanela, U. S. Passaribu, A. N. T. Puspito, S. W. Indratno

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Molluca Collision Zone is located at the junction of the Eurasian plate, Australian, Pacific, and the Philippines. Between the Sangihe arc, west of the collision zone, and to the east of Halmahera arc is active collision and convex toward the Molluca Sea. This research will analyze the behavior of earthquake occurrence in Molluca Collision Zone related to the distributions of an earthquake in each partition regions, determining the type of distribution of a occurrence earthquake of partition regions, and the mean occurrence of earthquakes each partition regions, and the correlation between the partitions region. We calculate number of earthquakes using partition method and its behavioral using conventional statistical methods. The data used is the data type of shallow earthquakes with magnitudes ≥ 4 SR for the period 1964-2013 in the Molluca Collision Zone. From the results, we can classify partitioned regions based on the correlation into two classes: strong and very strong. This classification can be used for early warning system in disaster management.

Keywords: molluca collision zone, partition regions, conventional statistical methods, earthquakes, classifications, disaster management

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Authors: Salima R. Rajwani, Tazeen Ali, Rubina Barolia, Yasmin Parpio, Nasreen Alwani, Salima B. Virani

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Introduction: Nurses and physicians have a critical role in initiating lifesaving interventions during cardiac arrest. It is important that timely delivery of high quality Cardio Pulmonary Resuscitation (CPR) with advanced resuscitation skills and management of cardiac arrhythmias is a key dimension of code during cardiac arrest. It will decrease the chances of patient survival if the healthcare professionals are unable to initiate CPR timely. Moreover, traditional training will not prepare physicians and nurses at a competent level and their knowledge level declines over a period of time. In this regard, simulation training has been proven to be effective in promoting resuscitation skills. Simulation teaching learning strategy improves knowledge level, and skills performance during resuscitation through experiential learning without compromising patient safety in real clinical situations. The purpose of the study is to evaluate the effectiveness of simulation training in Advanced Cardiac Life Support Courses by using the selfefficacy tool. Methods: The study design is a quantitative research design and non-randomized quasi-experimental study design. The study examined the effectiveness of simulation through self-efficacy in two instructional methods; one is Medium Fidelity Simulation (MFS) and second is Traditional Training Method (TTM). The sample size was 220. Data was compiled by using the SPSS tool. The standardized simulation based training increases self-efficacy, knowledge, and skills and improves the management of patients in actual resuscitation. Results: 153 students participated in study; CG: n = 77 and EG: n = 77. The comparison was done between arms in pre and post-test. (F value was 1.69, p value is <0.195 and df was 1). There was no significant difference between arms in the pre and post-test. The interaction between arms was observed and there was no significant difference in interaction between arms in the pre and post-test. (F value was 0.298, p value is <0.586 and df is 1. However, the results showed self-efficacy scores were significantly higher within experimental group in post-test in advanced cardiac life support resuscitation courses as compared to Traditional Training Method (TTM) and had overall (p <0.0001) and F value was 143.316 (mean score was 45.01 and SD was 9.29) verses pre-test result showed (mean score was 31.15 and SD was 12.76) as compared to TTM in post-test (mean score was 29.68 and SD was 14.12) verses pre-test result showed (mean score was 42.33 and SD was 11.39). Conclusion: The standardized simulation-based training was conducted in the safe learning environment in Advanced Cardiac Life Suport Courses and physicians and nurses benefited from self-confidence, early identification of life-threatening scenarios, early initiation of CPR, and provides high-quality CPR, timely administration of medication and defibrillation, appropriate airway management, rhythm analysis and interpretation, and Return of Spontaneous Circulation (ROSC), team dynamics, debriefing, and teaching and learning strategies that will improve the patient survival in actual resuscitation.

Keywords: advanced cardiac life support, cardio pulmonary resuscitation, return of spontaneous circulation, simulation

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Authors: Kh. Alaa, Sh. Sarah, J. Khowlah, S. Liyakathunsia

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Education has become very important nowadays and with the rapidly increasing number of student, taking the attendance manually is getting very difficult and time wasting. In order to solve this problem, an automated solution is required. An effective automated system can be implemented to manage student attendance in different ways. This research will discuss a unique class attendance system which integrates both Face Recognition and RFID technique. This system focuses on reducing the time spent on submitting of the lecture and the wastage of time on submitting and getting approval for the absence excuse and sick leaves. As a result, the suggested solution will enhance not only the time, also it will also be helpful in eliminating fake attendance.

Keywords: attendance system, face recognition, RFID, process model, cost, time

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Authors: Bindu S., Malavika Anakkathil Anil, Jayashree S. Bhat

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The dyadic interaction between the parent and child during story narration facilitates the emergence of early literacy skills. Early shared reading experiences positively predict better reading and language outcomes in children who experience rich communicative and effective interactions during shared book reading. However, research is yet to systematically explore mother’s perspective towards story narration and how employment may influence their perspectives. The study analysed the perspectives of employed and unemployed mothers of typically developing children between the age ranges of 2 to 5 years through a questionnaire which covered domains on story narration exposure and parental attitudes & beliefs. The results indicate no statistical difference between employed mothers (M=8.5, SD=3.4) and unemployed mothers (M=10.1, SD=1.06). Whereas, post-hoc comparisons using the scheffe test, revealed a significant difference in scores. An increasing score was obtained as the age of the child increased. This change could be attributed due to the integration of children in preschools which could have contributed to the change of perception towards story narration. Older children’s mother perceive story narration to be an important part of their curriculum, which could facilitate rich vocabulary and language output. Younger children’s parents are however not realising the significance of story narration and its impact on the emergent literacy skills. Parent-child interaction is a significant contributor to a healthy social and cultural development. The study emphasises on the need of mothers to engage in preliteracy based activities which contribute to better academic performance in later stages.

Keywords: early literacy skill, employment, language development, mother’s perspective, story narration

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Authors: J. H. Lee

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As the internet and smartphone use increases, the E-Commerce is constantly growing. Therefore, the parcel is increasing continuously every year. If the larger amount than the processing capacity of the current facilities is received, they do not process, and the delivery quality becomes low. In this paper, therefore, we analyze comparatively at the cost perspective between the case of building a new facility for the increasing parcel volumes and the case of reorganizing the current operating system. We propose the optimal discount policy per parcel by calculating the construction cost of new automated facility and manual facilities until the construction of the new automated facility, and discount price.

Keywords: system reorganization, load balancing, parcel sorting, discount policy

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Authors: Anne Tan, Kok-Sing Tang, Audrey Cooke

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Play has always been a prominent pedagogy in early childhood. However, there is growing evidence of success in students’ learning using explicit instruction, especially in literacy in the early years. There is also limited research using explicit instruction in early childhood mathematics, and play is usually prominently mentioned. This proposed research aims to investigate the possibilities and benefits of integrating guided play with explicit instruction in early childhood mathematics education. While play has traditionally been a prominent pedagogy in early childhood, there is growing evidence of success in student learning through explicit instruction, particularly in literacy. However, limited research exists on the integration of explicit instruction in early childhood mathematics, where play remains prominently mentioned. This study utilises a multiple case study methodology to gather data and provide immediate opportunities for curriculum improvement. The research will commence with semi-structured interviews to gain insights into educators' background knowledge. Highly structured observations will be conducted to record the frequency and manner in which guided play is integrated with specific elements of explicit instruction during mathematics teaching in early childhood. To enhance the observations, video recordings will be made using cameras with video settings and Microsoft Teams meeting recordings. In addition to interviews and observations, educators will maintain journals and use the Microsoft Teams platform for self-reflection on the integration of guided play and explicit instruction in their classroom practices and experiences. The study participants will include educators with early childhood degrees and students in years one and two. The primary goal of this research is to inform the benefits of integrating two high-impact pedagogies, guided play, and explicit instruction, for enhancing student learning outcomes in mathematics education. By exploring the integration of these pedagogical approaches, this study aims to contribute to the development of effective instructional strategies in early childhood mathematics education.

Keywords: early childhood, early childhood mathematics, early childhood numbers, guided play, play-based learning, explicit instruction

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Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

Abstract:

Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

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Authors: Yusra Pintaningrum, Ilma Fahira Basyir, Sony Hilal Wicaksono, Vito A. Damay

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Background: Coronary artery calcium (CAC) scores play an important role in improving prognostic accuracy and can be selectively used to guide the allocation of statin therapy for atherosclerotic cardiovascular disease outcomes and potentially associated with the occurrence of MACE (Major Adverse Cardiovascular Event) and MI (Myocardial Infarction). Objective: This systematic review and meta-analysis aim to analyze the findings of a study about CAC Score and statin treatment effect on MI and MACE risk. Methods: Search for published scientific articles using the PRISMA (Preferred Reporting, Items for Systematic Reviews and Meta-Analysis) method conducted on PubMed, Cochrane Library, and Medline databases published in the last 20 years on “coronary artery calcium” AND “statin” AND “cardiovascular disease” Further systematic review and meta-analysis using RevMan version 5.4 were performed based on the included published scientific articles. Results: Based on 11 studies included with a total of 1055 participants, we performed a meta-analysis and found that individuals with CAC score > 0 increased risk ratio of MI 8.48 (RR = 9.48: 95% CI: 6.22 – 14.45) times and MACE 2.48 (RR = 3.48: 95% CI: 2.98 – 4.05) times higher than CAC score 0 individual. Statin compared against non-statin treatment showed a statistically insignificant overall effect on the risk of MI (P = 0.81) and MACE (P = 0.89) in an individual with elevated CAC score 1 – 100 (P = 0.65) and > 100 (P = 0.11). Conclusions: This study found that an elevated CAC scores individual has a higher risk of MI and MACE than a non-elevated CAC score individual. There is no significant effect of statin compared against non-statin treatment to reduce MI and MACE in elevated CAC score individuals of 1 – 100 or > 100.

Keywords: coronary artery calcium, statin, cardiovascular disease, myocardial infarction, MACE

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Arne Hitzmann, Philipp Wentscher, Alexander Gabel, Reinhard Gerndt

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Autonomous mobile robots can be found in a wide field of applications. Their types range from household robots over workshop robots to autonomous cars and many more. All of them undergo a number of testing steps during development, production and maintenance. This paper describes an approach to improve testing of robot behavior. It was inspired by the RoboCup @work competition that itself reflects a robotics benchmark for industrial robotics. There, scaled down versions of mobile industrial robots have to navigate through a workshop-like environment or operation area and have to perform tasks of manipulating and transporting work pieces. This paper will introduce an approach of automated vision-based testing of the behavior of the so called youBot robot, which is the most widely used robot platform in the RoboCup @work competition. The proposed system allows automated testing of multiple tries of the robot to perform a specific missions and it allows for the flexibility of the robot, e.g. selecting different paths between two tasks within a mission. The approach is based on a multi-camera setup using, off the shelf cameras and optical markers. It has been applied for test-driven development (TDD) and maintenance-like verification of the robot behavior and performance.

Keywords: supervisory control, testing, markers, mono vision, automation

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon

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Authors: Sule Pallavi, Shah Priyank, Thavkar Amit, Mehta Suyog, Rohira Poonam

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Minoxidil is used topically to help hair growth in the treatment of male androgenetic alopecia. The objective of this study is to compare irritation potential of three conventional formulation of minoxidil 5% topical solution of in human patch test. The study was a single centre, double blind, non-randomized controlled study in 56 healthy adult Indian subjects. Occlusive patch test for 24 hours was performed with three formulation of minoxidil 5% topical solution. Products tested included aqueous based minoxidil 5% (AnasureTM 5%, Sun Pharma, India – Brand A), alcohol based minoxidil 5% (Brand B) and aqueous based minoxidil 5% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate were included as negative control and positive control respectively. Patches were applied and removed after 24hours. The skin reaction was assessed and clinically scored 24 hours after the removal of the patches under constant artificial daylight source using Draize scale (0-4 points scale for erythema/wrinkles/dryness and for oedema). A combined mean score up to 2.0/8.0 indicates a product is “non-irritant” and score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and score above 4.0/8.0 indicates “irritant”. Follow-up was scheduled after one week to confirm recovery for any reaction. The procedure of the patch test followed the principles outlined by Bureau of Indian standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). Fifty six subjects with mean age 30.9 years (27 males and 29 females) participated in the study. The combined mean score (± standard deviation) were: 0.13 ± 0.33 (Brand A), 0.39 ± 0.49 (Brand B), 0.22 ± 0.41 (Brand C), 2.91 ± 0.79 (Positive control) and 0.02 ± 0.13 (Negative control). The mean score of Brand A (Sun Pharma product) was significantly lower than Brand B (p=0.001) and was comparable with Brand C (p=0.21). The combined mean erythema score (± standard deviation) were: 0.09 ± 0.29 (Brand A), 0.27 ± 0.5 (Brand B), 0.18 ± 0.39 (Brand C), 2.02 ± 0.49 (Positive control) and 0.0 ± 0.0 (Negative control). The mean erythema score of Brand A was significantly lower than Brand B (p=0.01) and was comparable with Brand C (p=0.16). Any reaction observed at 24hours after patch removal subsided in a week. All the three topical formulation of minoxidil 5% were non-irritant. Brand A of 5% minoxidil (Sun Pharma) was found to be least irritant than Brand B and Brand C based on the combined mean score and mean erythema score in the human patch test as per the BIS, IS 4011;2018.

Keywords: erythema, irritation, minoxidil, patch test

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