Search results for: TS patient selection

Authors: Ram Sharan Mehta

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The number of new cancer cases annually is estimated to rise from 10.9 million in 2002 to more than 16 million by 2020, if current trends continue. Much of this increase in absolute numbers derives from the ageing of populations worldwide. The objectives of this study were to find out the demographic characteristics of the admitted cancer patients in BPKIHS. It was hospital based descriptive cross-sectional study conducted reviewing all the records of admitted diagnosed cancer patients in BPKIHS from 15th October 2004 to 14th October 2012. Using total enumerative sampling technique all 1379 diagnosed cancer patients record were reviewed after obtaining the permission from concerned authorities. Using SPSS-15 software package data was analyzed. It was found that majority (71%) of cancer patients were of age more than 40 years and equal of both sexes. Most of the clients were form Sunsari (31.1%), Morang (16.6%) and Jhapa (17%) districts. The mean hospitalization day is 8.32 and very few patients (5.2%) were only cured. The numbers of cancer patients are markedly increases in BPKIHS, especially in advanced stage. It is mandatory to start the cancer information and education programme in eastern region of Nepal and proper management of cancer patients using chemotherapy, radiotherapy and surgery at BPKIHS for quality patient care.

Keywords: lung, cancer, patients, Nepal

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

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Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

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Authors: Siyuan Cai

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This paper takes community segregation during major infectious diseases as the background, based on the physiological needs and safety needs of citizens during home segregation, and based on the selection of convenient facilities and medical facilities as the main research objects. Based on the POI data of public facilities in Chongqing, the spatial distribution characteristics of the convenience and medical facilities in the 15-minute living circle centered on three neighborhoods in Shapingba, namely Shengwei Community, Anju Commmunity and Fengtian Garden Community, were explored by means of GIS spatial analysis. The results show that the spatial distribution of convenience and medical facilities in this area has significant clustering characteristics, with a point-like distribution pattern of "dense in the west and sparse in the east", and a grouped and multi-polar spatial structure. The spatial structure is multi-polar and has an obvious tendency to the intersections and residential areas with dense pedestrian flow. This study provides a preliminary exploration of the distribution of medical and convenience facilities within the 15-minute living circle of a segregated community, which makes up for the lack of spatial research in this area.

Keywords: ArcGIS, community segregation, convenient facilities; distribution pattern, medical facilities, POI, 15-minute community life circle

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Wei-Han Wang, Hsiang-Yu Yu, Mau-Sun Hua

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Theory of Mind (ToM) refers to the ability to infer another’s mental state. With appropriate ToM, one can behave well in social interactions. A growing body of evidence has demonstrated that patients with temporal lobe epilepsy (TLE) may have damaged ToM due to impact on regions of the underlying neural network of ToM. However, the question of whether there is cerebral laterality for ToM functions remains open. This study aimed to examine whether there is cerebral lateralization for ToM abilities in TLE patients. Sixty-seven adult TLE patients and 30 matched healthy controls (HC) were recruited. Patients were classified into right (RTLE), left (LTLE), and bilateral (BTLE) TLE groups on the basis of a consensus panel review of their seizure semiology, EEG findings, and brain imaging results. All participants completed an intellectual test and four tasks measuring basic and advanced ToM. The results showed that, on all ToM tasks; (1)each patient group performed worse than HC; (2)there were no significant differences between LTLE and RTLE groups; (3)the BTLE group performed the worst. It appears that the neural network responsible for ToM is distributed evenly between the cerebral hemispheres.

Keywords: cerebral lateralization, social cognition, temporal lobe epilepsy, theory of mind

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: Samantha Ramachandra, Avanthi Rupasinghe

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Demographic transition from lower to higher percentage of elderly population eventually coupled with epidemiological transition from communicable to non-communicable diseases (NCD). Higher percentage of NCD overload the health system as NCD survivors claims continuous health care. The demands are challenging to a resource constrained setting but reorganizing the system may find solutions. The study focused on the facilities available and their utilization at outpatient department (OPD) setting of the public hospitals of Sri Lanka for continuous medical care. This will help in identifying steps of reorganizing the system to provide better care with the maximum utilization of available facilities. The study was conducted as a situation analysis with secondary data at hospital planning units. Variable were identified according to the world health organization (WHO) recommendation on continuous health care for elders in “age-friendly primary health care toolkit”. Data were collected from secondary and tertiary care hospitals of Sri Lanka where most of the continuous care services are available. Out of 58 secondary and tertiary care hospitals, 16 were included in the study to represent each hospital categories. Average number of patient attending for episodic treatment at OPD and Clinical follow-up of chronic conditions shows vast disparity according to the category of the hospital ranging from 3750 – 800 per day at OPD and 1250 – 200 per clinic session. Average time spent per person at OPD session is low, range from 1.54 - 2.28 minutes, the time was increasing as the hospital category goes down. 93.7% hospitals had special arrangements for providing acute care on chronic conditions such as catheter, feeding tube and wound care. 25% hospitals had special clinics for elders, 81.2% hospitals had healthy lifestyle clinics (HLC), 75% hospitals had physical rehabilitation facilities and 68.8% hospitals had facilities for counselling. Elderly clinics and HLC were mostly available at lower grade hospitals where as rehabilitation and counselling facilities were mostly available at bigger hospitals. HLC are providing health education for both patients and their family members, refer patients for screening of complication but not provide medical examinations, investigations or treatments even though they operate in the hospital setting. Physical rehabilitation is basically offered for patients with rheumatological conditions but utilization of centers for injury rehabilitation and rehabilitation of survivors following major illness such as myocardial infarctions, stroke, cancer is not satisfactory (12.5%). Human Resource distribution within hospital shows vast disparity and there are 103 physiotherapists in the biggest hospital where only 36 physiotherapists available at the next level hospital. Counselling facilities also provided mainly for the patient with psychological conditions (100%) but they were not providing counselling for newly diagnosed patients with major illnesses (0%). According to results, most of the public-sector hospitals in Sri Lanka have basic facilities required in providing continuous care but the utilization of services need more focus. Hospital administration or the government need to have initial steps in proper utilization of them in improving continuous health care incorporating team approach of rehabilitation. The author wishes to acknowledge that this paper was made possible by the support and guidance given by the “Australia Awards Fellowships Program for Sri Lanka – 2017,” which was funded by the Department of Foreign Affairs and Trade, Australia, and co-hosted by Monash University, Australia and the Sri Lanka Institute of Development Administration.

Keywords: continuous care, outpatient department, non communicable diseases, rehabilitation

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Andrii Biloshchytskyi, Serik Omirbayev, Alexandr Neftissov, Sapar Toxanov, Svitlana Biloshchytska, Adil Faizullin

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Kazakhstan has adopted a carbon neutrality strategy until 2060. In accordance with this strategy, it is necessary to introduce various tools to maintain the environmental safety of the environment. The use of IoT, in combination with the characteristics and requirements of Kazakhstan's environmental legislation, makes it possible to develop a modern environmental monitoring system. The article proposes a solution for developing an example of an automated system for the continuous collection of data on the concentration of pollutants in the atmosphere based on an open architecture. The Audino-based device acts as a microcontroller. It should be noted that the transmission of measured values is carried out via an open wireless communication protocol. The architecture of the system, which was used to build a prototype based on sensors, an Arduino microcontroller, and a wireless data transmission module, is presented. The selection of elementary components may change depending on the requirements of the system; the introduction of new units is limited by the number of ports. The openness of solutions allows you to change the configuration depending on the conditions. The advantages of the solutions are openness, low cost, versatility and mobility. However, there is no comparison of the working processes of the proposed solution with traditional ones.

Keywords: environmental monitoring, greenhouse gases emissions, environmental pollution, Industry 4.0, IoT, microcontroller, automated monitoring system.

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Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

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Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

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Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

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In its simplest form, data quality can be defined as 'fitness for use' and it is a concept with multi-dimensions. Emergency Departments(ED) require information to treat patients and on the other hand it is the primary source of information regarding accidents, injuries, emergencies etc. Also, it is the starting point of various patient registries, databases and surveillance systems. This interventional study was carried out to improve data quality at the ED of the National Hospital of Sri Lanka (NHSL) by introducing an e health solution to improve data quality. The NHSL is the premier trauma care centre in Sri Lanka. The study consisted of three components. A research study was conducted to assess the quality of data in relation to selected five dimensions of data quality namely accuracy, completeness, timeliness, legibility and reliability. The intervention was to develop and deploy an electronic emergency department information system (eEDIS). Post assessment of the intervention confirmed that all five dimensions of data quality had improved. The most significant improvements are noticed in accuracy and timeliness dimensions.

Keywords: electronic health records, electronic emergency department information system, emergency department, data quality

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Authors: Z. Karakus, Z. Ozer

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Nurses are responsible for the care and treatment of individuals, as well as health maintenance and education. Medication administration is an important part of health promotion. The administration of a medicine is a common but important clinical procedure for nurses because of its complex structure. Therefore, medication errors are inevitable for nurses or nursing students. Medication errors can cause ineffective treatment, patient’s prolonged hospital stay, disablement, or death. Additionally, medication errors affect the global economy adversely by increasing health costs. Hence, preventing or decreasing of medication errors is a critical and essential issue in nursing. Nurse educators are in pursuit of new teaching methods to teach students significance of medication application. In the light of technological developments of this age, e-learning has started to be accepted as an important teaching method. E-learning is the use of electronic media and information and communication technologies in education. It has advantages such as flexibility of time and place, lower costs, faster delivery, and lower environmental impact. Students can make their own schedule and decide the learning method. This study is conducted to determine the impact of e-learning on medication administration of nursing students.

Keywords: e-learning, medication administration, nursing, nursing students

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Authors: Mohammad Muhebbullah Ibne Hoque, Zheng Jun, Wang Guoying

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Salinity stress is one of the most important abiotic factors contributing to crop growth and yield loss. Exploring the genetic basis is necessary to develop maize varieties with salinity tolerance. In order to discover the inherent basis for salinity tolerance traits in maize, 121 polymorphic SSR markers were used to analyze 163 F2 individuals derived from a single cross of inbred line B73 (a salt susceptible inbred line) and CZ-7 (a salt tolerant inbred line). A linkage map was constructed and the map covered 1195.2 cM of maize genome with an average distance of 9.88 cM between marker loci. Ten salt tolerance traits at seedling stage were evaluated for QTL analysis in maize seedlings. A total of 41 QTLs associated with seedling shoot and root traits were detected, with 16 and 25 QTLs under non-salinity and salinity condition, respectively. And only 4 major stable QTLs were detected in two environments. The detected QTLs were distributed on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, and chromosome 10. Phenotypic variability for the identified QTLs for all the traits was in the range from 6.27 to 21.97%. Fourteen QTLs with more than 10% contributions were observed. Our results and the markers associated with the major QTL detected in this study have the potential application for genetic improvement of salt tolerance in maize through marker-assisted selection.

Keywords: salt tolerance, seedling stage, root shoot traits, quantitative trait loci, simple sequence repeat, maize

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Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Peter Dzakah Fanam, Hong O. Nguyen, Stephen Cahoon

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The objective of this study is to explore the buying behavior of the freight forwarders and to evaluate how their buying decision affects the ocean container carriers’ market share. This study analysed the buying decisions of the freight forwarders and validated the process of stages that the freight forwarders’ pass through before choosing an ocean container carrier. Factor analysis was applied to data collected from 105 freight forwarding companies to unveil the influential factors the freight forwarders’ consider important when selecting an ocean container carrier. This study did not only analysed the buying behaviour of the freight forwarders but also unveiled the influential factors affecting the competitiveness of the ocean container carriers in their market share maximisation. Furthermore, the study have made a methodological contribution that helps in better understanding of the critical factors influencing the selection of the ocean container carriers from the freight forwarders’ perspective. The implications of the freight forwarders’ buying behaviour is important to the ocean container carriers because it have severe effect on the market share of the ocean container carriers and the percentage of customers they control within the liner shipping sector. The findings of this study will help the ocean container carriers to formulate relevant marketing strategies in attracting the freight forwarders in purchasing the liner shipping service.

Keywords: ocean carrier, freight forwarder, buying behaviour, influential factors

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Authors: Mohamed Amine El Hameur, Lyes Tarabet, Mahfoudh Cerdoun, Boubkr Zebiri, Giovanni Ferrara

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Due to the drastic environmental and energy regulations regarding the reduction of exhaust emissions and fuel consumption, added to the increasing demand for powerful performance, several automotive manufacturers are constantly obliged to redesign their existing products and/or develop novel powertrain techniques to respond to the aforementioned restrictions. In this aspect, an implemented approach is proposed in the present work to boost a 1.5 L, three-cylinder Diesel engine with a new turbocharger, based on 1D preliminary design codes, 3D design, and numerical assessment of a suitable radial turbine followed by an accurate selection procedure of an adequate centrifugal compressor. Furthermore, to investigate the effect of the turbine’s rotor position on the simulation convergence, stability, and calculation time; two combinations (rotor blade- volute) have been assessed. Consequently, significant results are obtained when comparing the original turbocharged engine and the new one at the engine’s full load and rated speed (@4500rpm) conditions. A maximum improvement in terms of brake-specific fuel consumption, thermal efficiency, total-to-static turbine efficiency, and total-to-total compressor efficiency equal 6.5% (corresponding to a decrease of 2.3 litre/hr in fuel consumption), 7%, 10.9%, and 19.9%, respectively.

Keywords: CFD investigation, engine boosting, turbine design, turbocharger, rotor blade positioning

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Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Fused deposition modeling (FDM) gains popularity in recent times, due to its capability to create prototype as well as functional end use product directly from CAD file. Parts fabricated using FDM process have mechanical properties comparable with those of injection-molded parts. However, performance of the FDM part is severally affected by the poor mechanical properties of the part due to nature of layered structure of printed part. Mechanical properties of the part can be improved by proper selection of process variables. In the present study, a comparative study between unidirectional and bidirectional raster angle has been carried out at a combination of different layer height and raster width. Unidirectional raster angle varied at five different levels, and bidirectional raster angle has been varied at three different levels. Fabrication of tensile specimen and tensile testing of specimen has been conducted according to ASTM D638 standard. From the results, it can be observed that higher tensile strength has been obtained at 0° raster angle followed by 45°/45° raster angle, while lower tensile strength has been obtained at 90° raster angle. Analysis of fractured surface revealed that failure takes place along with raster deposition direction for unidirectional and zigzag failure can be observed for bidirectional raster angle.

Keywords: additive manufacturing, fused deposition modeling, unidirectional, bidirectional, raster angle, tensile strength

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Authors: Riham Barbar

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This paper studies the dynamic effects of charitable giving in a Ramsey model à la Becker and Foias (1994), such that heterogeneity is reduced to two types of agents: rich and poor. It is assumed that rich show a great concern for poor and enjoy giving. The introduction of charitable giving in this paper is inspired from the notion of Zakat (borrowed from the Islamic Economics) and is defined according to the warm-glow of Andreoni (1990). In this framework, we prove the existence of a steady state where only the patient agent holds capital. Furthermore, we show that local indetermincay appears. While moderate values of charitable-giving elasticity makes the appearance of endogenous fluctuations due to self-fulfilling expectations more likely, high values of this elasticity stabilizes endogenous fluctuations, by narrowing down the range of parameter values compatible with local indeterminacy and may rule out expectations-driven fluctuations if it exceeds certain threshold. Finally, cycles of period two emerge. However, charitable-giving makes it less likely for these cycles to emerge.

Keywords: charitable giving, warm-glow, bifurcations, heterogeneous agents, indeterminacy, self-fulfilling expectations, endogenous fluctuations

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagi Allah Eltayeb, Mohamed E. Gar-elnabi, Mohamed Ahmed Ali

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To characterize coronary artery obstruction and related findings in ischemic heart patients using cardiac scintigraphy for the identification of myocardial ischemia, 146 patients were studied at basal conditions and also asked for fasting after night till the intravenous injection of the radiopharmaceutical. After the injection time about 15 to 20 minutes, the patient should eat a fatty meal and chocolate for the good excretion of the gall bladder, to evaluate the performance and regional wall motion of the left ventricle (LV). The results showed that the body mass index percentage in this sample was in range of 43.05 to 61.05. The number of patients who were catheter candidates were 56 with 43% and the patients that were not candidate to cathode were 74 patients with 57% of all patients. For the group of patients where type of ischemia was assessed, 29.5% of patients had reversible posterior and inferior wall, 15.1% of patients had fixed large from apex to base, 9.6% of patients had mild basal inferior wall, 4.8 % of patients had mild anterior wall, 6.2% of patients had antro-septal and 34.9% of patients had moderate ischemia.

Keywords: myocardial ischemia, myocardial scintigraphy, contrast ventriculography, coronary artery obstruction

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Authors: Hossein Alimohammadi, Mohsen Amirmojahedi, Mehrdad Rowhani

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Soil properties are used by geotechnical engineers to evaluate and analyze site conditions for designing purposes. Although basic soil classification tests are easy to perform and provide useful information to determine the properties of soils, it may take time to get the result and add some costs to the projects. Standard Penetration Test (SPT) provides an opportunity to evaluate soil parameters without performing laboratory tests. In addition to its simplicity and cheapness, the results become available immediately. This research provides a guideline on the application of the SPT test method, reliability of adapting the SPT test results in evaluating soil physical and mechanical properties such as Atterberg limits, shear strength, and compressive strength compressibility parameters. A total of 70 boreholes were investigated in this study by taking soil samples between depths of 1.2 to 15.25 meters. The project site was located in Morrow County, Ohio. A regression-based formula was proposed based on Tobit regression with a stepwise variable selection analysis conducted between SPT and other typical soil properties obtained from soil tests. The results of the research illustrated that the shear strength and physical properties of the soil affect the SPT number. The proposed correlation can help engineers to use SPT test results in their design with higher accuracy.

Keywords: standard penetration test, soil properties, soil classification, regression method

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

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Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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Authors: Zahra Abdolkarimi, Naser Zouri

Abstract:

Nowadays, there is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Additionally, robotics system recommended RoboCup factor as a provider of some standardization and testing method in case of computer discussion widely. The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. In addition, decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidently. Consequences, shows method of our discussion is the best way for Particle Swarm Optimization and Fuzzy system compare to other decision of robotics algorithmic.

Keywords: PSO algorithm, inference fuzzy system, chaos theory, soccer robot league

Procedia PDF Downloads 383

Authors: Jui-Pui Hung, Yong-Run Chen, Wei-Cheng Shih, Shen-He Tsui, Kung-Da Wu

Abstract:

This paper presents the effect on the tooling conditions on the machining stabilities of a milling machine tool. The machining stability was evaluated in different feeding direction in the X-Y plane, which was referred as the orientation-dependent machining stability. According to the machining mechanics, the machining stability was determined by the frequency response function of the cutter. Thus, we first conducted the vibration tests on the spindle tool of the milling machine to assess the tool tip frequency response functions along the principal direction of the machine tool. Then, basing on the orientation dependent stability analysis model proposed in this study, we evaluated the variation of the dynamic characteristics of the spindle tool and the corresponding machining stabilities at a specific feeding direction. Current results demonstrate that the stability boundaries and limited axial cutting depth of a specific cutter were affected to vary when it was fixed in the tool holder with different overhang length. The flute of the cutter also affects the stability boundary. When a two flute cutter was used, the critical cutting depth can be increased by 47 % as compared with the four flute cutter. The results presented in study provide valuable references for the selection of the tooling conditions for achieving high milling performance.

Keywords: tooling condition, machining stability, milling machine, chatter

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Authors: Mahsa Falahatpour

Abstract:

Introduction: This study aims to explore how inter-observer variability in manual tumor segmentation impacts the reliability of radiomic features in non–small cell lung cancer (NSCLC). Methods: The study included twenty-three NSCLC tumors. Each patient had three tumor segmentations (VOL1, VOL2, VOL3) contoured on PET/CT scans by three radiation oncologists. Dice coefficients (DCS) were used to measure the segmentation variability. Radiomic features were extracted with 3D-slicer software, consisting of 66 features: first-order (n=15), second-order (GLCM, GLDM, GLRLM, and GLSZM) (n=33). The inter-observer variability of radiomic features was assessed using the intraclass correlation coefficient (ICC). An ICC > 0.8 indicates good stability. Results: The mean DSC of VOL1, VOL2, and VOL3 was 0.80 ± 0.04, 0.85 ± 0.03, and 0.76 ± 0.06, respectively. 92% of all extracted radiomic features were found to be stable (ICC > 0.8). The GLCM texture features had the highest stability (96%), followed by GLRLM features (90%) and GLSZM features (87%). The DSC was found to be highly correlated with the stability of radiomic features. Conclusion: The variability in inter-observer segmentation significantly impacts radiomics analysis, leading to a reduction in the number of appropriate radiomic features.

Keywords: PET/CT, radiomics, radiotherapy, segmentation, NSCLC

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