Search results for: care networks

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

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Authors: Madhukar Kasarla, Sumit Fogla, Kiran Panuganti, Gaurav Jain, Abhijit Ramanujam, Astha Jain, Shashank Kraleti, Sharat Musham, Arun Chaudhury

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Patients have often chosen to travel for care — making pilgrimages to academic meccas and state-of-the-art hospitals for sophisticated surgery. This culture is still persistent in the landscape of US healthcare, with hundred thousand of visitors coming to the shores of United States to seek the high quality of medical care. One of the major challenges in this form of medical tourism has been the language barrier. Thus, an Iraqi patient, with immediate needs of communicating the healthcare needs to the treating team in the hospital, may face huge barrier in effective patient-doctor communication, delaying care and even at times reducing the quality. To circumvent these challenges, we are proposing the use of a state-of-the-art tool, Talk2All, which can translate nearly one hundred international languages (and even sign language) in real time. The tool is an easy to download app and highly user friendly. It builds on machine learning principles to decode different languages in real time. We suggest that the use of Talk2All will tremendously enhance communication in the hospital setting, effectively breaking the language barrier. We propose that vigorous incorporation of Talk2All shall overcome practical challenges in international medical and surgical tourism.

Keywords: language translation, communication, machine learning, medical tourism

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Yuri Melis, Mattia Resteghini, Emanuela Apicella, Eugenia Dozio, Leonardo Mendolicchio

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Aim: This retrospective study was created to analyze the psychometric, anthropometric and body composition values in patients at the beginning and the discharge of their of hospitalization in the residential care clinic for eating and feeding disorders (EFD’s). Method: The sample was composed by (N=59) patients with mean age N= 33,50, divided in subgroups: Anorexia Nervosa (AN) (N=28), Bulimia Nervosa (BN) (N=13) and Binge Eating Disorders (BED) (N=14) recruited from a residential care clinic for eating and feeding disorders. The psychometrics level was measured with self-report questionnaires: Eating Disorders Inventory-3 (EDI-3) The Body Uneasiness Test (BUT), Minnesota Multiphasic Personality Inventory (MMPI – 2). The anthropometric and nutritional values was collected by Body Impedance Assessment (B.I.A), Body mass index (B.M.I.). Measurements were made at the beginning and at the end of hospitalization, with an average time of recovery of about 8,6 months. Results: The all data analysis showed a statistical significance (p-value >0,05 | power size N=0,950) in variation from T0 (start of recovery) to T1 (end of recovery) in the clinical scales of MMPI-2, AN group (Hypocondria T0 64,14 – T1 56,39) (Depression T0 72,93 – T1 59,50) (Hysteria T0 61,29 – T1 56,17) (Psychopathic deviation T0 64,00 – T1 60,82) (Paranoia T0 63,82 – T1 56,14) (Psychasthenia T0 63,82 – T1 57,86) (Schizophrenia T0 64,68 – T1 60,43) (Obsessive T0 60,36 – T1 55,68); BN group (Hypocondria T0 64,08 – T1 47,54) (Depression T0 67,46 – T1 52,46) (Hysteria T0 60,62 – T1 47,84) (Psychopathic deviation T0 65,69 – T1 58,92) (Paranoia T0 67,46 – T1 55,23) (Psychasthenia T0 60,77 – T1 53,77) (Schizophrenia T0 64,68 – T1 60,43) (Obsessive T0 62,92 – T1 54,08); B.E.D groups (Hypocondria T0 59,43 – T1 53,14) (Depression T0 66,71 – T1 54,57) (Hysteria T0 59,86 – T1 53,82) (Psychopathic deviation T0 67,39 – T1 59,03) (Paranoia T0 58,57 – T1 53,21) (Psychasthenia T0 61,43 – T1 53,00) (Schizophrenia T0 62,29 – T1 56,36) (Obsessive T0 58,57 – T1 48,64). EDI-3 report mean value is higher than clinical cut-off at T0, in T1, there is a significant reduction of the general mean of value. The same result is present in the B.U.T. test in the difference between T0 to T1. B.M.I mean value in AN group is (T0 14,83 – T1 18,41) BN group (T0 20 – T1 21,33) BED group (T0 42,32 – T1 34,97) Phase Angle results: AN group (T0 4,78 – T1 5,64) BN (T0 6 – T1 6,53) BED group (T0 6 – T1 6,72). Discussion and conclusion: The evident presence that on the whole sample, we have an altered serious psychiatric and clinic conditions at the beginning of recovery. The interesting conclusions that we can draw from this analysis are that a multidisciplinary approach that includes the entire care of the subject: from the pharmacological treatment, analytical psychotherapy, Psychomotricity, nutritional rehabilitation, and rehabilitative, educational activities. Thus, this Multidisciplinary treatment allows subjects in our sample to be able to restore psychopathological and metabolic values to below the clinical cut-off.

Keywords: feeding and eating disorders, anorexia nervosa, care clinic treatment, multidisciplinary treatment

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Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).

Keywords: network security management, device organization, emergency response, cross-network

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: S. Karthikeyan, Naveen Bindra

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Introduction: To update ourselves and understand the concept of latest electronic formats available for Health care providers and how it could be used and developed as per standards. The idea is to correlate between the patients Manual Medical Records keeping and maintaining patients Electronic Information in a Health care setup in this world. Furthermore this stands with adapting to the right technology depending upon the organization and improve our quality and quantity of Healthcare providing skills. Objective: The concept and theory is to explain the terms of Electronic Medical Record (EMR), Electronic Health Record (EHR) and Personal Health Record (PHR) and selecting the best technical among the available Electronic sources and software before implementing. It is to guide and make sure the technology used by the end users without any doubts and difficulties. The idea is to evaluate is to admire the uses and barriers of EMR-EHR-PHR. Aim and Scope: The target is to achieve the health care providers like Physicians, Nurses, Therapists, Medical Bill reimbursements, Insurances and Government to assess the patient’s information on easy and systematic manner without diluting the confidentiality of patient’s information. Method: Health Information Technology can be implemented with the help of Organisations providing with legal guidelines and help to stand by the health care provider. The main objective is to select the correct embedded and affordable database management software and generating large-scale data. The parallel need is to know how the latest software available in the market. Conclusion: The question lies here is implementing the Electronic information system with healthcare providers and organisation. The clinicians are the main users of the technology and manage us to ‘go paperless’. The fact is that day today changing technologically is very sound and up to date. Basically the idea is to tell how to store the data electronically safe and secure. All three exemplifies the fact that an electronic format has its own benefit as well as barriers.

Keywords: medical records, digital records, health information, electronic record system

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Authors: Ade O. Oyewole, Sunday O. Okoh, Ruth O. Ishola, Adenike D. Odusote, Chima C. Igwe, Gloria N. Elemo, Anthony I. Okoh

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Azadirachta indica (Neem tree) also referred to as an all-purpose tree is used in a wide range of medical preparations in tropical and subtropical countries for prevention and management of various livestock, crops products and human diseases. In Nigeria however, the potentials of this plant have not been fully exploited thus it causes an environmental nuisance during the fruiting season. With a rise in the demand for herbal personal care products globally extracts from different parts of the neem plant were used as the bio-active ingredients in the formulation of personal care products. In this study, formulated neem soap, body cream, lotion, toothpaste and shampoo are analyzed to determine their antibacterial, antifungal, and toxicity properties. The efficacies of these products for management of infectious diseases, both oral and dermal, were also investigated in vitro. Oil from the neem seeds obtained using a mechanical press and acetone extracts of both the neem bark and leaves obtained by the maceration method were used in the formulation and production of the neem personal care products. The antimicrobial and toxicity properties of these products were investigated by agar diffusion, and haemolytic methods respectively. The five neem products (NPs) exhibited strong antibacterial activities against four multi–drug resistant pathogenic and three none pathogenic bacterial strains (Escherichia coli (180), Listeria ivanovii, Staphylococcus aureus, Enterobacter cloacae, Vibro spp., Streptococcus uberis, Mycobacterium smegmatis), except the neem lotion with insignificant activity against E. coli and S. aureus. The minimum inhibitory concentration (MIC) range was between 0.20-0.40 mg/ mL. The 5 NPs demonstrated moderate activity against three clinical dermatophytes isolates (Tinea corporis, Tinea capitis, and Tinea cruiz) as well as one fungal strain (Candida albican) with the MIC ranging between 0.30 - 0.50 mg/ mL and 0.550 mg/mL respectively. The soap and shampoo were the most active against test bacteria and fungi. The haemolytic analysis results on the 5 NPs indicated none toxicity at 0.50 mg/ mL in sheep red blood cells (SRBC).

Keywords: antimicrobial, Azadirachta indica, multi–drug resistant pathogenic bacteria, personal care products

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Authors: Hiranmoyee Das

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Aim. Due to late presentation and delayed diagnosis mortality rate of retinoblastoma is more than 50% in developing counties. So to facilitate the diagnosis, to decrease the disease and treatment burden and to increase the disease survival rate, an attempt was made for early diagnosis of Retinoblastoma by including fundus examination in routine immunization programs. Methods- A unique immunization card is followed in a tertiary health care center where examination of pupillary reflex is made mandatory in each visit of the child for routine immunization. In case of any abnormality, the child is referred to the ophthalmology department. Conclusion- Early detection is the key in the management of retinoblastoma. Every child is brought to the health care system at least five times before the age of 2 years for routine immunization. We should not miss this golden opportunity for early detection of retinoblastoma.

Keywords: retinoblastoma, immunization, unique, early

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Authors: Mary-Ellen Hooper, Anthony Paul O'Brien, Graeme Browne

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Background: It has been proposed that negative experiences in mental health nursing increase the risk of attrition for newly graduated nurses. The risk of nurse attrition is of particular concern with current nurse shortages worldwide continuing to rise. The purpose of this study was to identify and explore the qualitative experiences of new graduate nurses as they enter mental health services in their first year of clinical practice. Method: An ethnographic research design was utilized in order to explore the sub-cultural experiences of new graduate nurses. Which included 31 separate episodes of field observation (62 hours) and (n=24) semi-structured interviews. A total number of 26 new graduates and recently graduated nurses participated in this study – 14 new graduate nurses and 12 recently graduate nurses. Data collection was conducted across 6 separate Australian, NSW, mental health units from April until September 2017. Results: A major theme emerging from the research is the new graduate nurses experience of communication in their nursing role, particularly within the context of the multidisciplinary team, and the barriers to sharing information related to care. This presentation describes the thematic structure of the major theme 'communication' in the context of the everyday experience of the New Graduate mental health nurse's participation in their chosen nursing discipline. The participants described diminished communication as a negative experience affecting their envisioned notion of holistic care, which they had associated with the role of the mental health nurse. Conclusion: The relationship between nurses and members of the multidisciplinary team plays a key role in the communication of patient care, patient-centeredness and inter-professional collaboration, potentially affecting the role of the mental health nurse, satisfaction of new graduate nurses, and patient care.

Keywords: culture, mental health nursing, multidisciplinary team, new graduate nurse

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Authors: N. W. Paul, S. Michl

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In our globalized world we need to appreciate the fact that questions of health and justice need to be addressed on a global scale, too. The way in which diverse governmental and non-governmental initiatives are trying to answer the need for humanitarian medical aid has long since been a visible result of globalized responsibility. While the intention of humanitarian medical aids seems to be evident, the allocation of resources has become more and more an ethical and societal challenge. With a rising number and growing dimension of humanitarian catastrophes around the globe the search for ethically justifiable ways to decide who might benefit from limited resources has become a pressing question. Rooted in theories of justice (Rawls) and concepts of social welfare (Sen) we developed and implemented a model for an ethically sound distribution of a limited annual budget for humanitarian care in one of the largest medical universities of Germany. Based on our long lasting experience with civil casualties of war (Afghanistan) and civil war (Libya) as well as with under- and uninsured and/or stateless patients we are now facing the on-going refugee crisis as our most recent challenge in terms of global health and justice. Against this background, the paper strives to a) explain key issues of humanitarian medical aid in the 21st century, b) explore the problem of rationing from an ethical point of view, c) suggest a tool for the rational allocation of scarce resources in humanitarian medical aid, d) present actual cases of humanitarian care that have been managed with our toolbox, and e) discuss the international applicability of our model beyond local contexts.

Keywords: humanitarian care, medical ethics, allocation, rationing

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Yu-Chieh Chen, Kuei-Feng Shen, Chia-Ling Chao

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The purpose of this report was to present the nursing experience and case of an unexpected cerebellar hemorrhagic stroke with acute hydrocephalus patient after lumbar spine surgery. The patient had been suffering from an emergent external ventricular drainage and stayed in the Surgical Intensive Care Unit from July 8, 2016, to July 22, 2016. During the period of the case, the data were collected for attendance, evaluation, observation, interview, searching medical record, etc. An integral evaluation of the patient's physiological 'psychological' social and spiritual states was also noted. The author noticed the following major nursing problems including ineffective cerebral perfusion 'physical activity dysfunction' family resource preparation for disability. The author provided nursing care to maintain normal intracranial pressure, along with a well-therapeutic relationship and applied interdisciplinary medical/nursing team to draft an individualized and appropriate nursing plan for them to face the psychosocial impact of the patient disabilities. We also actively participated in the rehabilitation treatments to improve daily activity and confidence. This was deemed necessary to empower them to a more positive attitude in the future.

Keywords: family resourace preparation inability, hemorrhagic sroke, ineffective tissue cerebral perfusion, lumbar spine surgery

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Authors: Mehwish Sarfaraz Ahmad

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Background: There is a prevailing perception in Pakistan that private hospitals offer better services than government hospitals. Unfortunately, Pakistan faces challenges in providing efficient healthcare due to limited resources and management capabilities, resulting in demotivation among healthcare workers. Aim: The purpose of this study was to conduct a comprehensive assessment of the occupational health and well-being of healthcare workers in both public and private sector tertiary care hospitals in Lahore, Pakistan, to compare the well-being of healthcare professionals in these two sectors and investigate the influence of workplace culture and experiences on their overall health. Methods: A cross-sectional study was conducted using a validated International Questionnaire, and data from 440 participants was collected using a stratified random sampling technique from a diverse group of healthcare professionals from the public and private tertiary care hospitals in Lahore, Pakistan. The researcher conducted a comparative analysis using appropriate statistical tests, such as Anova, t-tests, chi-square tests, and regression analysis, to explore potential relationships between various factors. Results: The majority of respondents (70.2%) reported their health as "Good" or "Very good, a small percentage (8.2%) rated their health as "Poor," while 24.1% considered their health as "Fair". 39.6% reported being satisfied with their workplace culture, while a majority of 60.4% indicated being unsatisfied with their workplace culture. Results showed that workplace culture has a positive correlation with the overall health and well-being of healthcare professionals. The study found significant differences in health ratings, prevalence of chronic health conditions, workplace culture, and safety perceptions between healthcare professionals in public and private sector tertiary care hospitals. Conclusion: The study's findings emphasize the significance of promoting a positive workplace culture, ensuring workplace safety, and addressing chronic health conditions among healthcare workers.

Keywords: occupational health and well-being, workplace culture, frequency of fatigue, availabity of benefits

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Chiraz Ben Jabeur, Hassene Seddik

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In this paper, a full approach of modeling and control of a four-rotor unmanned air vehicle (UAV), known as quad-rotor aircraft, is presented. In fact, a PD and a PD optimized Neural Networks Approaches (PD-NN) are developed to be applied to control a quad-rotor. The goal of this work is to concept a smart self-tuning PD controller based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking the desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind added to the model on each axis. Thus, the quad-rotor is subject to three-dimensional unknown static/varying wind disturbances. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regard to decision-making facing disturbances. This technique offers some advantages over conventional control methods such as PD controller. Simulation results are obtained with the use of Matlab/Simulink environment and are founded on a comparative study between PD and PD-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, this controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient, facing turbulences in the form of wind disturbances.

Keywords: hostile environment, PD and PD-NN controllers, quad-rotor control, robustness against disturbance

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Authors: Pampita Chakraborty, Sukumar Mukherjee

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This study was done to determine the prevalence of nosocomial infections in the ICU and to identify the common microorganisms causing these infections and their antimicrobial sensitivity pattern. Nosocomial infection or hospital-acquired infection is a localized or a systemic condition resulting from an adverse reaction to the presence of infectious agents. Nosocomial infections are not present or incubating when the patient is admitted to hospital or other health care facility. They are caused by pathogens that easily spread through the body. Many hospitalized patients have compromised immune systems, so they are less able to fight off infections. These infections occur worldwide, both in the developed and developing the world. They are a significant burden to patients and public health. They are a major cause of death and increased morbidity in hospitalized patients, which is a matter of serious concern today. This study was done during the period of one year (2012-2013) in the ICU of the tertiary care hospital in eastern India. Prevalence of nosocomial infection was determined; site of infection and the pattern of microorganisms were identified along with the assessment of antibiotic susceptibility profile. Patients who developed an infection after 48 hours of admission to the ICU were included in the study. A total of 324 ICU patients were analyzed, of these 79 patients were found to have developed a nosocomial infection (24.3% prevalence). Urinary tract infection was found to be more predominant followed by respiratory tract infection and soft tissue infection. The most frequently isolated microorganism was E. coli, Pseudomonas aeruginosa, Klebsiella pneumoniae followed by other organisms respectively. Antibiotic susceptibility test of these isolates was done against commonly used antibiotics. Patients admitted to the ICU are especially susceptible to nosocomial infections. Despite adequate antimicrobial treatment, nosocomial ICU infections can significantly affect ICU stay and can cause an increase in patient’s morbidity and mortality. Adherence to infection protocol, proper monitoring and the judicious use of antibiotics are important in preventing such infections on a regular basis.

Keywords: antibiotic susceptibility, intensive care unit, nosocomial infection, nosocomial pathogen

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Authors: Natália Bruno Chaves, Richardes Caúla, Roosevelt do Vale, Daniela Toneti, Rafaela Carvalho, Renata Silva Lopes, Antônio Carlos Júnior, Adner Nobre, Viviane Santiago, Yara Alana Caldato, Estefania Rodriguez Urrego, André Buarque Lemos, Catarina Nucci Stetner, Marcos Mauro Barreto, Stefany Moreira Lima, Mara Cavalcante, Ticiane Ribeiro

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The Well Born (Nascer Bem – in Portuguese) Program was created in the Hapvida health network with the aim of improving access to safe and quality prenatal care for users. In addition to offering a line of prenatal care, the inclusion of obstetric nursing and the decentralization of childbirth, bring security that professionals did not indicate the route of delivery for professional convenience. The introduction of the nursing consultation came to reinforce the care to our users, strengthening their bond and reception. In 2021, the program maintained an average of 40% of normal births in the north, northeast and central-west regions of Brazil, an average above that observed in the rest of the country's private health systems, around 20%. In addition, the neonatal hospitalization rate of this population remained around 5.1%, a figure below the national average. With these data, the “Nascer Bem” program is affirmed as a safe and effective strategy for the promotion of safe normal birth.

Keywords: quality, safe, prenatal, obstetric nursing

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

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Authors: Marlene Rosa, Susana Lopes

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Board games have been used for different purposes in geriatric care, demonstrating good results for health in general. However, there is not a conceptual framework that can help professionals and researchers in this area to design intervention programs or to think about future studies in this area. The aim of this study was to provide a pilot collection of board games’ serious purposes in geriatric care, using a WHO framework for health and disability. Study cases were developed in seven geriatric residential institutions from the center region in Portugal that are included in AGILAB program. The AGILAB program is a serious game-based method to train and spread out the implementation of board games in geriatric care. Each institution provides 2-hours/week of experiences using TATI Hand Game for serious purposes and then fulfill questions about a study-case (player characteristics; explain changes in players health according to this game experience). Two independent researchers read the information and classified it according to the International Classification for Functioning and Disability (ICF) categories. Any discrepancy was solved in a consensus meeting. Results indicate an important variability in body functions and structures: specific mental functions (e.g., b140 Attention functions, b144 Memory functions), b156 Perceptual functions, b2 sensory functions and pain (e.g., b230 Hearing functions; b265 Touch function; b280 Sensation of pain), b7 neuromusculoskeletal and movement-related functions (e.g., b730 Muscle power functions; b760 Control of voluntary movement functions; b710 Mobility of joint functions). Less variability was found in activities and participation domains, such as purposeful sensory experiences (d110-d129) (e.g., d115 Listening), communication (d3), d710 basic interpersonal interactions, d920 recreation and leisure (d9200 Play; d9205 Socializing). Concluding, this framework designed from a brief gamed-based experience includes mental, perceptual, sensory, neuromusculoskeletal, and movement-related functions and participation in sensory, communication, and leisure domains. More studies, including different experiences and a high number of users, should be developed to provide a more comprehensive ICF framework for game-based experiences in geriatric care.

Keywords: board game, aging, framework, experience

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Authors: Mike Wei, Mario Cedillo, Jiahui Lin, Carol Lorraine Storey-Johnson, Carla Boutin-Foster

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Purpose: The extent to which health insurance enrollment succeeds under the Affordable Care Act (ACA) rests heavily on the ability to reach the uninsured and motivate them to enroll. We sought to identify perceptions about the ACA among uninsured patients at a free clinic in New York City. Background: The ACA holds tremendous promise for reducing the number of uninsured Americans. As of April 2014, nearly 8 million people had signed up for health insurance through the Health Insurance Marketplace. Despite this early success, future and continued enrollment rests heavily on the degree of public awareness. Reaching eligible individuals and increasing their awareness and understanding remains a fundamental challenge to realizing the full potential of the ACA. Reaching out to uninsured patients who are seeking care through safety net facilities such as free clinics may provide important avenues for reaching potential enrollees. This project focuses on the experience at the free clinic at Weill Cornell Medical College, the Weill Cornell Community Clinic (WCCC), and seeks to understand perceptions about the ACA among its patient population. Methods: This was a cross-sectional study of all patients who visited the free clinic at Weill Cornell Medical College, the Weill Cornell Community Clinic, from July 2013 to May 2014. Patients who provided informed consent at their visit and completed a semi-structured questionnaire were included (N=62). The questionnaire comprised of questions about demographic characteristics and open-ended questions about their knowledge and perception of the impact of the ACA. Descriptive statistics were used to characterize the population demographics. Qualitative coding techniques were used for open-ended items. Results: Approximately one third of patients surveyed never had health insurance. Of the remaining 65%, 20% lost their insurance within the past year. Only 55% had heard about the ACA, and only 10% knew about the Health Benefits Exchange. Of those who had heard about the ACA, sentiments were tinged with optimistic misperceptions, such as “it will be free health care for all.” While optimistic, most of the responses focused on the economic implications of the ACA. Conclusions: These findings reveal the immense amount of misconception and lack of understanding with regards to the ACA. As such, the study highlights the need to educate and address the concerns of those who remain skeptical or uncertain about the implications of the ACA.

Keywords: Affordable Care Act, demographics, free clinics, underserved.

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Authors: Neda Valizadeh, Mani Mofidi, Sama Haghighi, Ali Hashemaghaee, Soudabeh Shafiee Ardestani

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Background: There are many systems and parameters to evaluate trauma patients in the emergency department. Most of these evaluations are to distinguish patients with worse conditions so that the care systems have a better prediction of condition for a better care-giving. The purpose of this study is to determine the relationship between axillary body temperature and mortality in patients hospitalized in the intensive care unit (ICU) with multiple traumas and with other clinical and para-clinical factors. Methods: All patients between 16 and 75 years old with multiple traumas who were admitted into Emergency Department then hospitalized in the ICU were included in our study. An axillary temperature in the first and the second day of admission, Glasgow cola scale (GCS), systolic blood pressure, Serum glucose levels, and white blood cell counts of all patients at the admission day were recorded and their relationship with mortality were analyzed by SPSS software with suitable statistical tests. Results: Axillary body temperatures in the first and second day were statistically lower in expired traumatic patients (p=0.001 and p<0,001 respectively). Patients with lower GCS had a significantly lower first-day temperature and a significantly higher mortality. (p=0.006 and p=0.006 respectively). Furthermore, the first-day axillary temperature was significantly lower in patients with a lower first-day systolic blood pressure (p=0.014). Conclusion: Our results showed that lower axillary body temperature in the first day is associated with higher mortality, lower GCS, and lower systolic blood pressure. Thus, this could be used as a predictor of mortality in evaluation of traumatic patients in emergency settings.

Keywords: fever, trauma, mortality, emergency

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Authors: Hanefi Cinar, Musa Cibuk, Ismail Erturk, Fikri Aggun, Munip Geylani

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Mobile Wireless Sensor Networks (MWSNs) carry heterogeneous data traffic with different urgency and quality of service (QoS) requirements. There are a lot of studies made on energy efficiency, bandwidth, and communication methods in literature. But delay, high throughput, utility parameters are not well considered. Increasing demand for real-time data transfer makes these parameters more important. In this paper we design new MAC protocol which is delay constrained and targets for improving delay, utility, and throughput performance of the network and finding solutions on collision and interference problems. Protocol improving QoS requirements by using TDMA, FDM, and OFDMA hybrid communication methods with multi-channel communication.

Keywords: MWSN, delay, hybrid MAC, TDMA, FDM, OFDMA

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Authors: Lucia Mavudzi

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Socioeconomic and demographic factors influence male attendance of antenatal care (ANC) activities which are beneficial in improving maternal health and birth outcome. When a male, as the head of the family is expected to solely make decisions of how finances are managed, when and where health services are sought, it impacts on the woman’s health seeking behavior. Using the data from the Zimbabwe Demographic and Health Survey 2010-2011 this paper seeks to assess the prevalence of male ANC attendance in Zimbabwe and factors that influence male ANC attendance. We hypothesized that socioeconomic and demographic factors do not influence male ANC attendance. To achieve the objectives of this paper, descriptive analysis was used to describe the characteristics of men and the Binomial logistic modelling was used to assess the relationship between male ANC attendance and selected socioeconomic and demographic factors. Male ANC attendance was used as the dependent variable, and the independent variables are age, marital status, place of residence, wealth, education, religion and employment. A high percentage of males did not attend ANC with their pregnant partners. Religion, education, and place of residence were found to be significantly associated with male ANC attendance. There was no evidence to show that there was a difference in male ANC attendance by employment, marital status, and age. Findings from this paper are relevant to public health. They will be used to develop strategies and intervention programs to improve pregnant women’s attendance of ANC attendance by involving men in maternal health.

Keywords: antenatal care, male participation, maternal health, socio-economic and demographic factors

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Ge Zhan

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Mobile health (mHealth) concerns the use of mobile technologies to deliver health care and improve wellness. In this paper, we ask the question of what are the drivers of positive consumer attitude toward mHealth programs. Answers to this question are important to consumer health, but existing marketing and health care service literature does not provide sufficient empirical conclusions on the use of mobile technologies for consumer health. This study aims to fill the knowledge gap by investigating mHealth use and consumer attitude. A content analysis was conducted with sample mHealth programs and online consumer reviews in Hong Kong, UK, US, and India. The research findings will contribute to marketing and health services literature.

Keywords: mobile health, consumer attitude, content analysis, online marketing

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Authors: Cian O'Shea, Ross O'Halloran, Peter Haigh

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Wireless Sensor Networks (WSN) are Internet of Things (IoT) edge devices. They are becoming widely adopted in many industries, including health care, building energy management, and conditional monitoring. As the scale of WSN deployments increases, the cost and complexity of battery replacement and disposal become more significant and in time may become a barrier to adoption. Harvesting ambient energies provide a pathway to reducing dependence on batteries and in the future may lead to autonomously powered sensors. This work describes a simulation tool that enables the user to predict the battery life of a wireless sensor that utilizes energy harvesting to supplement the battery power. To create this simulator, all aspects of a typical WSN edge device were modelled including, sensors, transceiver, and microcontroller as well as the energy source components (batteries, solar cells, thermoelectric generators (TEG), supercapacitors and DC/DC converters). The tool allows the user to plug and play different pre characterized devices as well as add user-defined devices. The goal of this simulation tool is to predict the lifetime of a device and scope for extension using ambient energy sources.

Keywords: Wireless Sensor Network, IoT, edge device, simulation, solar cells, TEG, supercapacitor, energy harvesting

Procedia PDF Downloads 133