Search results for: the health improvement network (THIN)

Authors: Hamnah Nisar

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As food is something which is particularly important for survival, in fact, it improves the quality of life and promotes health. Quality food is a key to a healthy life. Consumption of food depends on the knowledge we have regarding the nutrients it contains. Moreover, the awareness and knowledge about something is an initial stage for its improvement. We cannot work on anything unless we have knowledge about it. The pros and cons, effects, causes, dos, and don'ts, especially for an important things like food, are a necessity to learn. That is why my research would be all about analyzing what difference awareness makes on people and how making people more aware about a certain thing can help them improve their lifestyles and bring a positive change for them. The research would be done through questionnaires and interviews among two classes, one would be the upper class and the other would-be lower class. Because the upper class can easily access learning facilities and can know about the new things than the lower class. The questions would be related to what kind of food do they consume, what health issues they face, or what health issues are common among their regions. The results of the research would be helpful to know firstly the effects of awareness and education regarding food on health, how a basic thing like knowledge can have a significant effect on health and can be the cause of several diseases.

Keywords: nutrition, awareness, quality food, knowledge

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Authors: Jiro Takagi

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Approximately 90 percent of the casualties in the near-fault-type Kobe earthquake in 1995 resulted from the collapse of wooden houses, although a limited number of collapses of this type of building were reported in the more recent off-shore-type Tohoku Earthquake in 2011 (excluding direct damage by the Tsunami). Kumamoto earthquake in 2016 also revealed the vulnerability of old wooden houses in Japan. There are approximately 24.5 million wooden houses in Japan and roughly 40 percent of them are considered to have the inadequate seismic-resisting capacity. Therefore, seismic strengthening of these wooden houses is an urgent task. However, it has not been quickly done for various reasons, including cost and inconvenience during the reinforcing work. Residents typically spend their money on improvements that more directly affect their daily housing environment (such as interior renovation, equipment renewal, and placement of thermal insulation) rather than on strengthening against extremely rare events such as large earthquakes. Considering this tendency of residents, a new approach to developing a seismic strengthening method for wooden houses is needed. The seismic reinforcement method developed in this research uses folded galvanized thin steel plates as both shear walls and the new exterior architectural finish. The existing finish is not removed. Because galvanized steel plates are aesthetic and durable, they are commonly used in modern Japanese buildings on roofs and walls. Residents could feel a physical change through the reinforcement, covering existing exterior walls with steel plates. Also, this exterior reinforcement can be installed with only outdoor work, thereby reducing inconvenience for residents since they would not be required to move out temporarily during construction. The Durability of the exterior is enhanced, and the reinforcing work can be done efficiently since perfect water protection is not required for the new finish. In this method, the entire exterior surface would function as shear walls and thus the pull-out force induced by seismic lateral load would be significantly reduced as compared with a typical reinforcement scheme of adding braces in selected frames. Consequently, reinforcing details of anchors to the foundations would be less difficult. In order to attach the exterior galvanized thin steel plates to the houses, new wooden beams are placed next to the existing beams. In this research, steel connections between the existing and new beams are developed, which contain a gap for the existing finish between the two beams. The thin steel plates are screwed to the new beams and the connecting vertical members. The seismic-resisting performance of the shear walls with thin steel plates is experimentally verified both for the frames and connections. It is confirmed that the performance is high enough for bracing general wooden houses.

Keywords: experiment, seismic reinforcement, thin steel plates, wooden houses

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Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

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Authors: Suleiman Obeidat, Nabeel Mandahawi

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In this work, the packaging process for a move is improved. The customers of this move need their household stuff to be moved from their current house to the new one with minimum damage, in an organized manner, on time and with the minimum cost. Our goal was to improve the process between 10% and 20% time efficiency, 90% reduction in damaged parts and an acceptable improvement in the cost of the total move process. The expected ROI was 833%. Many improvement techniques have been used in terms of the way the boxes are prepared, their preparation cost, packing the goods, labeling them and moving them to a place for moving out. DMAIC technique is used in this work: SIPOC diagram, value stream map of “As Is” process, Root Cause Analysis, Maps of “Future State” and “Ideal State” and an Improvement Plan. A value of ROI=624% is obtained which is lower than the expected value of 833%. The work explains the techniques of improvement and the deficiencies in the old process.

Keywords: packaging, lean tools, six sigma, DMAIC methodology, SIPOC

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Vinod Kumar, Arun Kumar, Surjit Angra

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This paper addresses the junction stress analysis of orthogonally intersecting thin walled cylindrical shell and thin walled cylindrical nozzle subjected to external loading on nozzle. Junction stresses have been calculated theoretically by welding research council (WRC) bulletins 107 and 297 for different nozzle loads. WRC bulletins 107 and 297 have been used by design engineers for calculating nozzle-vessel junction stresses since their publication. They give simple empirical relations and easy in application. Also 3D FEA in which material is elastic has been done in ANSYS software with 8 node solid element model and results of FEA have been compared with WRC results. Stress intensities obtained by WRC 297 are generally slightly higher than obtained by WRC 107. Membrane stresses obtained by FEA are much higher than WRC and membrane plus bending stresses obtained by FEA are lower than WRC.

Keywords: FEA, junction stress, solid element, WRC 107, WRC 297

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Authors: Rodrigo S. Moreira, Nelson F. F. Ebecken

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This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs.

Keywords: ram memory, WiSARD weightless neural network, object tracking, quantization

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Authors: K. C. M. Wong, C. P. Y. Cheng, K. Y. Chan, G. S. C. Fung, T. F. O. Lau, K. F. C. Leung, J. P. C. Fok

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Hospital Authority (HA) is the statutory body to manage all public hospitals in Hong Kong. Occupational Care Medicine Service (OMCS) is an in-house multi-disciplinary team responsible for injury management in HA. Hospital administrative services (AS) provides essential support in hospital daily operation to facilitate the provision of quality healthcare services. An occupational health enhancement program in Tai Po Hospital (TPH) domestic service supporting unit (DSSU) was piloted in 2013 with satisfactory outcome, the keys to success were staff engagement and management support. Riding on the success, the program was rolled out to another 5 AS departments of Alice Ho Miu Ling Nethersole Hospital (AHNH) and TPH in 2015. This paper highlights the indispensable components of disability management and occupational health enhancement program in hospital settings. Objectives: 1) Facilitate workplace to support staff with health affecting work problem, 2) Enhance staff’s occupational health. Methodology: Hospital Occupational Safety and Health (OSH) team and AS departments (catering, linen services, and DSSU) of AHNH and TPH worked closely with OMCS. Focus group meetings and worksite visits were conducted with frontline staff engagement. OSH hazards were identified with corresponding OSH improvement measures introduced, e.g., invention of high dusting device to minimize working at height; tailor-made linen cart to minimize back bending at work, etc. Specific MHO trainings were offered to each AS department. A disability management workshop was provided to supervisors in order to enhance their knowledge and skills in return-to-work (RTW) facilitation. Based on injured staff's health condition, OMCS would provide work recommendation, and RTW plan was formulated with engagement of staff and their supervisors. Genuine communication among stakeholders with expectation management paved the way for realistic goals setting and success in our program. Outcome: After implementation of the program, a significant drop of 26% in musculoskeletal disorders related sickness absence day was noted in 2016 as compared to the average of 2013-2015. The improvement was postulated by innovative OSH improvement measures, teamwork, staff engagement and management support. Staff and supervisors’ feedback were very encouraging that 90% respondents rated very satisfactory in program evaluation. This program exemplified good work sharing among departments to support staff in need.

Keywords: disability management, occupational health, return to work, occupational medicine

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Ashraf Aly

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The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

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Authors: Lisa Fox, Jill Aylott

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There is a global need to identify ways to engage doctors in non-clinical matters such as medical leadership, service improvement and health system transformation. Using the core principles of Realistic Evaluation (RE), this study examined what works, for doctors of different grades, specialities and experience in an acute NHS Hospital Trust in the UK. Realistic Evaluation is an alternative to more traditional cause and effect evaluation models and seeks to understand the interdependencies of Context, Mechanism and Outcome proposing that Context (C) + Mechanism (M) = Outcome (O). In this study, the context, mechanism and outcome were examined from within individual medical leaders to determine what enables levels of medical engagement in a specific improvement project to reduce hospital inpatient mortality. Five qualitative case studies were undertaken with consultants who had regularly completed mortality reviews over a six month period. The case studies involved semi-structured interviews to test the theory behind the drivers for medical engagement. The interviews were analysed using a theory-driven thematic analysis to identify CMO configurations to explain what works, for whom and in what circumstances. The findings showed that consultants with a longer length of service became more engaged if there were opportunities to be involved in the beginning of an improvement project, with more opportunities to affect the design. Those that are new to a consultant role were more engaged if they felt able to apply any learning directly into their own settings or if they could use it as an opportunity to understand more about the organisation they are working in. This study concludes that RE is a useful methodology for better understanding the complexities of motivation and consultant engagement in a trust wide service improvement project. The study showed that there should be differentiated and bespoke training programmes to maximise each individual doctor’s propensity for medical engagement. The RE identified that there are different ways to ensure that doctors have the right skills to feel confident in service improvement projects.

Keywords: realistic evaluation, medical leadership, medical engagement, patient safety, service improvement

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Authors: Moulfi Bouchra, Ferouani Souheyla, Ziani Kerarti Djalal, Moulessehoul Wassila

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The wireless body network (WBAN) is the most interesting network these days and especially with the appearance of contagious illnesses such as covid 19, which require surveillance in the house. In this article, we have designed a circular microstrip antenna. Gold is the material used respectively for the patch and the ground plane and Gallium (εr=12.94) is chosen as the dielectric substrate. The dimensions of the antenna are 82.10*62.84 μm2 operating at a frequency of 3.85 THz. The proposed, designed antenna has a return loss of -46.046 dB and a gain of 3.74 dBi, and it can measure various physiological parameters and sensors that help in the overall monitoring of an individual's health condition.

Keywords: circular patch antenna, Terahertz transmission, WBAN applications, real-time monitoring

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Authors: K. Gomathi

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Mobile Ad hoc Networks (MANET) is defined as collection of routable wireless mobile nodes with no centralized administration and communicate each other using radio signals. Especially MANETs deployed in hostile environments where hackers will try to disturb the secure data transfer and drain the valuable network resources. Since MANET is battery operated network, preserving the network resource is essential one. For resource constrained computation, efficient routing and to increase the network stability, the network is divided into smaller groups called clusters. The clustering architecture consists of Cluster Head(CH), ordinary node and gateway. The CH is responsible for inter and intra cluster routing. CH election is a prominent research area and many more algorithms are developed using many different metrics. The CH with longer life sustains network lifetime, for this purpose Secondary Cluster Head(SCH) also elected and it is more economical. To nominate efficient CH, a Enhanced Distributed Weighted Clustering Algorithm (EDWCA) has been proposed. This approach considers metrics like battery power, degree difference and speed of the node for CH election. The proficiency of proposed one is evaluated and compared with existing algorithm using Network Simulator(NS-2).

Keywords: MANET, EDWCA, clustering, cluster head

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Authors: F. Slaven, M. Uys, Y. Erasmus

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The South African National Mental Health Education Programme (SANMHEP) was a National Department of Health (NDoH) initiative to strengthen mental health services in South Africa in collaboration with the Foundation for Professional Development (FPD), SANOFI and the various provincial departments of health. The programme was implemented against the backdrop of a number of challenges in the management of mental health in the country related to staff shortages and infrastructure, the intersection of mental health with the growing burden of non-communicable diseases and various forms of violence, and challenges around substance abuse and its relationship with mental health. The Mental Health Care Act (No. 17 of 2002) prescribes that mental health should be integrated into general health services including primary, secondary and tertiary levels to improve access to services and reduce stigma associated with mental illness. In order for the provisions of the Act to become a reality, and for the journey of mental health patients through the system to improve, sufficient and skilled health care providers are critical. SANMHEP specifically targeted Medical Doctors and Professional Nurses working within the facilities that are listed to conduct 72-hour assessments, as well as District Hospitals. The aim of the programme was to improve the clinical diagnosis and management of mental disorders/conditions and the understanding of and compliance with the Mental Health Care Act and related Regulations and Guidelines in the care, treatment and rehabilitation of mental health care users. The course used a blended-learning approach and trained 1 120 health care providers through 36 workshops between February and November 2019. Of those trained, 689 (61.52%) were Professional Nurses, 337 (30.09%) were Medical Doctors, and 91 (8.13%) indicated their occupation as ‘other’ (of these more than half were psychologists). The pre- and post-evaluation of the face-to-face training sessions indicated a marked improvement in knowledge and confidence level scores (both clinical and legislative) in the care, treatment and rehabilitation of mental health care users by participants in all the training sessions. There was a marked improvement in the knowledge and confidence of participants in performing certain mental health activities (on average the ratings increased by 2.72; or 27%) and in managing certain mental health conditions (on average the ratings increased by 2.55; or 25%). The course also required that participants obtain 70% or higher in their formal assessments as part of the online component. The 337 participants who completed and passed the course scored 90% on average. This illustrates that when participants attempted and completed the course, they did very well. To further assess the effect of the course on the knowledge and behaviour of the trained mental health care practitioners a mixed-method outcome evaluation is currently underway consisting of a survey with participants three months after completion, follow-up interviews with participants, and key informant interviews with department of health officials and course facilitators. This will enable a more detailed assessment of the impact of the training on participants' perceived ability to manage and treat mental health patients.

Keywords: mental health, public health facilities, South Africa, training

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Authors: Neha Batra Bali, Monika Tomar, Vinay Gupta

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A reagentless biosensor for detection of urea based on ZnO-CuO composite thin film is presented in following work. Biosensors have immense potential for varied applications ranging from environmental to clinical testing, health care, and cell analysis. Immense growth in the field of biosensors is due to the huge requirement in today’s world to develop techniques which are both cost effective and accurate for prevention of disease manifestation. The human body comprises of numerous biomolecules which in their optimum levels are essential for functioning. However mismanaged levels of these biomolecules result in major health issues. Urea is one of the key biomolecules of interest. Its estimation is of paramount significance not only for healthcare sector but also from environmental perspectives. If level of urea in human blood/serum is abnormal, i.e., above or below physiological range (15-40mg/dl)), it may lead to diseases like renal failure, hepatic failure, nephritic syndrome, cachexia, urinary tract obstruction, dehydration, shock, burns and gastrointestinal, etc. Various metal nanoparticles, conducting polymer, metal oxide thin films, etc. have been exploited to act as matrix to immobilize urease to fabricate urea biosensor. Amongst them, Zinc Oxide (ZnO), a semiconductor metal oxide with a wide band gap is of immense interest as an efficient matrix in biosensors by virtue of its natural abundance, biocompatibility, good electron communication feature and high isoelectric point (9.5). In spite of being such an attractive candidate, ZnO does not possess a redox couple of its own which necessitates the use of electroactive mediators for electron transfer between the enzyme and the electrode, thereby causing hindrance in realization of integrated and implantable biosensor. In the present work, an effort has been made to fabricate a matrix based on ZnO-CuO composite prepared by pulsed laser deposition (PLD) technique in order to incorporate redox properties in ZnO matrix and to utilize the same for reagentless biosensing applications. The prepared bioelectrode Urs/(ZnO-CuO)/ITO/glass exhibits high sensitivity (70µAmM⁻¹cm⁻²) for detection of urea (5-200 mg/dl) with high stability (shelf life ˃ 10 weeks) and good selectivity (interference ˂ 4%). The enhanced sensing response obtained for composite matrix is attributed to the efficient electron exchange between ZnO-CuO matrix and immobilized enzymes, and subsequently fast transfer of generated electrons to the electrode via matrix. The response is encouraging for fabricating reagentless urea biosensor based on ZnO-CuO matrix.

Keywords: biosensor, reagentless, urea, ZnO-CuO composite

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Authors: H. Elgubbi, A. Mlitan, A. Alzridy

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Ninhydrin is the most well known spray reagent for identification of amino acids. Spring with Ninhydrin as a non-specific reagent is well-known and widely used for its remarkable high sensitivity. Using Ninhydrin reagent alone to detect amino acid on thin layer chromatography (TLA) paper is not advisable due to its lower sensitivity. A new spray reagent, Stannus chloride solution (Sn CL2) has been used to detect amino acids on filtter paper (witman 14) and TLC paper, silica Gel, 60 F254 TLC Aluminium Sheet 20x20cm Merck- Germany. Also, modified TLC pre-staining method was used, which only consisted of 3 steps: spotting, separating and color. The improved method was rapid and inexpensive and the results obtained were clear and reliable. In addition, it is suitable for screening different amino acid.

Keywords: amino acid, ninhydrin, modified ninhydrin reagent, stannus chloride reagent, thin-layer chromatography (TLC), TLC pre-staining

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Authors: Jennifer Stephens, Nichole Parker, Kristin Petrovic

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To gain a better understanding of how students enrolled in a Bachelor of Nursing (BN) program are educated, faculty members in the BN program at Athabasca University (AU) in Alberta, Canada, developed a 3-phase comprehensive curriculum review project. Phase one of this review centered around hiring an external curriculum expert to examine and analyze the current curriculum and to propose recommendations focused on identifying gaps as well as building on strengths towards meeting changing health care trends. Phase two incorporated extensive institutional document analysis as well as qualitative and quantitative data collection in reciprocated critical reflection and has yielded insights into valuable processes, challenges, and solutions inherent to the complexities of undertaking curriculum review and analysis. Results of our phase one and two analysis generated a quality improvement (QI) template that could benefit other nursing education programs engaged in curriculum review and analysis. The key processes, lessons, and insights, as well as future project phase three plans, will be presented for iterative discussion and role modelling for other institutions undergoing, or planning, content-based curriculum review and evaluation.

Keywords: curriculum, education, nursing, nursing faculty practice, quality improvement

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Authors: Marinela Miclau, Melinda Vajda, Nicolae Miclau, Daniel Ursu

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Characterized by a simple structure, easy and low cost fabrication, the dye-sensitized solar cell (DSSC) attracted the interest of the scientific community as an attractive alternative of conventional Si-based solar cells and thin-film solar cells. Over the past 20 years, the main efforts have attempted to enhance the efficiency of n-type DSSCs, the highest efficiency record of 14.30% was achieved using the co-sensitization of two metal-free organic dyes and Co (II/III) tris(phenanthroline)-based redox electrolyte. In the last years, the development of the efficient p-type DSSC has become a research focus owing to the fact that the concept of tandem solar cell was proposed as the solution to increase the power conversion efficiency. A promising alternative for the photocathodes of p-type DSSC, cuprous (Cu2O) and cupric (CuO) oxides have been investigated because of its nontoxic nature, low cost, high natural abundance, a good absorption coefficient for visible light and a higher dielectric constant than NiO. In case of p-type DSSC based on copper oxides with I3-/I- as redox mediator, the highest conversion efficiency of 0.42% (Cu2O) and 0.03% (CuO) has achieved. Towards the increase in the performance, we have fabricated and analyzed the performance of p-type DSSC prepared with the binder-free porous Cu2O photocathodes. Porous thin film could be an attractive alternative for DSSC because of their large surface areas which enable the efficient absorption of the dyes and light. We propose a simple and one-step hydrothermal method for the preparation of porous Cu2O thin film using copper substrate, cupric acetate and ethyl cellulose. The cubic structure of Cu2O has been determined by X-ray diffraction (XRD) and porous morphology of thin film was emphasized by Scanning Electron Microscope Inspect S (SEM). Optical and Mott-Schottky measurements attest of the high quality of the Cu2O thin film. The binder-free porous Cu2O photocathode has confirmed the excellent photovoltaic properties, the best value reported for p-type DSSC (1%) in similar conditions being reached.

Keywords: cuprous oxide, dye-sensitized solar cell, hydrothermal method, porous photocathode

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Authors: Zouhour Neji Ben Salem

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Microscopic evacuation focuses on the evacuee behavior and way of search of safety place in an egress situation. In recent years, several models handled microscopic evacuation problem. Among them, we have proposed Artificial Neural Network (ANN) as an alternative to mathematical models that can deal with such problem. In this paper, we present two ANN models: SOM map and Hopfield Network used to predict the evacuee behavior in a disaster situation. These models are tested in a real case, the second floor of Tunisian children hospital evacuation in case of fire. The two models are studied and compared in order to evaluate their performance.

Keywords: artificial neural networks, self-organization map, hopfield network, microscopic evacuation, fire building evacuation

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Authors: Pornwipa Daoduong, Jairak Loysongkroa, Napaphan Viriyautsahakul, Wachira Pengjuntr

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Obesity is on of serious health problem in many countries including Thailand where the prevalence of childhood obesity has increased from 8.8 % in 2014 to 9.5 % in 2015 and 12.9 % in 2016. The Ministry of Public Health’s objective is to reduce prevalence of childhood Obesity to 10% or lower in 2017, by implementing the measure in relation to nutrition, physical activity (PA) and environment in 6,405 targeted school with proportion of school children with obesity is higher than 10 %. Smart Kids Coacher (SKC)” is a new innovative intervention created by Department of Health and consists of 252 regional and provincial officers. The SKC aims to train the super trainers about food and nutrition.PA and emotional control through implementing three learning activities including 1) Food for Fun is about Nutrition flag, Nutrition label, food portion and Nutrition surveillance; 2) Fun for Fit includes intermediated- and advanced level workouts within 60 minutes such as kangaroo dance, Chair stretching; and 3) Control emotional is about to prevent probability of access to unhealthy food, to ensure for having meal in appropriate time, and to recruit peers and family member to increase awareness among target groups. Apart from providing SKC lesson for 3,828 officers at district level, a number of students (2,176) as role model are selected through implementing “Smart Kids Leader: (SKL)”.Consequently. The SKC lowers proportion of childhood obesity from 17% in 2012 to 12.9% in 2016. Further, the SKC coverage should be expanded to other setting. Policy maker should be aware of the important of reduction of the prevalence of childhood obesity, and it’s related risk. Network and Collaboration between stakeholders are essential as well as an improvement of holistic intervention and knowledge “NuPETHS” for kids in the future.

Keywords: childhood obesity, model, obesity, smart kids coacher

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Authors: Mukondi Nethavhakone

Abstract:

The high prevalence of violence against women is a global public health problem. Our societies have become dangerous places for women. Women during their child-bearing ages are at a higher risk of experiencing emotional, physical, and sexual violence. What makes it more concerning is that these violent acts are perpetrated by family members or partners, or ex-partners. Intimate Partner Violence (IPV) is associated with long-lasting physical, reproductive, sexual, mental, and maternal health implications. Expectedly women’s mental health would dimmish as a result of experiencing IPV. The burden of violence against women is seen to be heavier in low- and middle-income countries (LMICs) compared to the rest of the world. Countries have committed to eliminating all forms of violence against women through the sustainable development goal, aiming to see changes by the year 2030. As such, various countries have implemented psychosocial interventions of different levels of impact. However, little is known, especially in low- and middle-income countries, with regard to the potential of psychosocial interventions for IPV to improve the mental health outcomes for the survivors and/or victims of IPV. Analysing the risk for IPV through a social-ecological theoretical approach, low- and middle-income countries still readdressing gender inequality which is the cause of intimate partner violence. That is why it is taking time for these countries to shift psychosocial interventions to focus more on the improvement of the mental health of the survivors. It is, therefore, against this backdrop that the researcher intends to undertake a scoping review to understand the nature and characteristics of psychosocial interventions that have been implemented in low- and middle-income countries. With the findings from the scoping review, the researcher aims to develop a conceptual framework that may be a useful resource for healthcare practitioners and researchers in low- and middle-income countries. As this area of research has not been thoroughly reviewed, the results from this scoping will determine whether a systematic review will be justifiable. Additionally, the researcher will identify gaps and opportunities for future research in this area.

Keywords: mental health improvement, psychosocial interventions, intimate partner violence, LMICs

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Authors: David Hasurungan

Abstract:

This paper objective is to analyze the impact from photovoltaic system integration to power distribution network. The case study in Badak Liquefied Natural Gas (LNG) plant is presented in this paper. Badak LNG electricity network is operated in islanded mode. The total power generation in Badak LNG plant is significantly affected to feed gas supply. Meanwhile, to support the Government regulation, Badak LNG continuously implemented the grid-connected photovoltaic system in existing power distribution network. The impact between train operational mode change in Badak LNG plant and the growth of photovoltaic system is also encompassed in analysis. The analysis and calculation are performed using software Power Factory 15.1.

Keywords: power quality, distribution network, grid-connected photovoltaic system, power management system

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Authors: Thomas E. Portegys

Abstract:

An animal behavior problem is presented in the form of a nest-building task that involves two cooperating virtual birds, a male and female. The female builds a nest into which she lays an egg. The male's job is to forage in a forest for food for both himself and the female. In addition, the male must fetch stones from a nearby desert for the female to use as nesting material. The task is completed when the nest is built, and an egg is laid in it. A goal-seeking neural network and a recurrent neural network were trained and tested with little success. The goal-seeking network was then enhanced with “place cells”, allowing the birds to spatially navigate the world, building the nest while keeping themselves fed. Place cells are neurons in the hippocampus that map space.

Keywords: artificial animal intelligence, artificial life, goal-seeking neural network, nest-building, place cells, spatial navigation

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Authors: Aboli Gore, Aritra Das, Sunil Sonthalia, Tanmay Mahapatra, Sridhar Srikantiah, Hemant Shah

Abstract:

AMANAT is an initiative, taken in collaboration with the Government of Bihar, aimed at improving the Quality of Maternal and Neonatal care services at Bihar’s public health facilities – those offering either the Basic Emergency Obstetric and Neonatal care (BEmONC) or Comprehensive Emergency Obstetric and Neonatal care (CEmONC) services. The effectiveness of this program is evaluated by conducting cross-sectional assessments at the concerned facilities prior to (baseline) and following completion (endline) of intervention. Direct Observation of Delivery (DOD) methodology is employed for carrying out the baseline and endline assessments – through which key obstetric and neonatal care practices among the Health Care Providers (especially the nurses) are assessed quantitatively by specially trained nursing professionals. Assessment of vitals prior to delivery improved during all three phases of BEmONC and all four phases of CEmONC training with statistically significant improvement noted in: i) pulse measurement in BEmONC phase 2 (9% to 68%), 3 (4% to 57%) & 4 (14% to 59%) and CEmONC phase 2 (7% to 72%) and 3 (0% to 64%); ii) blood pressure measurement in BEmONC phase 2 (27% to 84%), 3 (21% to 76%) & 4 (36% to 71%) and CEmONC phase 2 (23% to 76%) and 3 (2% to 70%); iii) fetal heart rate measurement in BEmONC phase 2 (10% to 72%), 3 (11% to 77%) & 4 (13% to 64%) and CEmONC phase 1 (24% to 38%), 2 (14% to 82%) and 3 (1% to 73%); and iv) abdominal examination in BEmONC phase 2 (14% to 59%), 3 (3% to 59%) & 4 (6% to 56%) and CEmONC phase 1 (0% to 24%), 2 (7% to 62%) & 3 (0% to 62%). Regarding infection control, wearing of apron, mask and cap by the delivery conductors improved significantly in all BEmONC phases. Similarly, the practice of handwashing improved in all BEmONC and CEmONC phases. Even on disaggregation, the handwashing showed significant improvement in all phases but CEmONC phase-4. Not only the positive practices related to handwashing improved but also negative practices such as turning off the tap with bare hands declined significantly in the aforementioned phases. Significant decline was also noted in negative maternal care practices such as application of fundal pressure for hastening the delivery process and administration of oxytocin prior to delivery. One of the notable achievement of AMANAT is an improvement in active management of the third stage of labor (AMTSL). The overall AMTSL (including administration of oxytocin or other uterotonics uterotonic in proper dose, route and time along with controlled cord traction and uterine massage) improved in all phases of BEmONC and CEmONC mentoring. Another key area of improvement, across phases, was in proper cutting/clamping of the umbilical cord. AMANAT mentoring also led to improvement in important immediate newborn care practices such as initiation of skin-to-skin care and timely initiation of breastfeeding. The next phase of the mentoring program seeks to institutionalize mentoring across the state that could potentially perpetuate improvement with minimal external intervention.

Keywords: capacity building, nurse-mentoring, quality of care, pregnancy, newborn care

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Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

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This paper studies a secondary voltage control framework of the microgrids based on the consensus for a communication network of multiagent. The proposed control is designed by the communication network with one-way links. The communication network is modeled by a directed graph. At this time, the concept of sampling is considered as the communication constraint among each distributed generator in the microgrids. To analyze the sampling effects on the secondary voltage control of the microgrids, by using Lyapunov theory and some mathematical techniques, the sufficient condition for such problem will be established regarding linear matrix inequality (LMI). Finally, some simulation results are given to illustrate the necessity of the consideration of the sampling effects on the secondary voltage control of the microgrids.

Keywords: microgrids, secondary control, multiagent, sampling, LMI

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Authors: Wullapa Wongsinlatam

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Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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Authors: Gabriel Efomeh Omolaiye, Jimoh Ajadi, Olatunji Seminu, Yusuf Ayoola Jimoh, Ubulom Daniel

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Identification and characterization of petrophysical properties of reservoirs in the Bima Formation were undertaken to understand their spatial distribution and impacts on hydrocarbon saturation in the highly heterolithic siliciclastic sequence. The study was carried out using nine well logs from Maiduguri and Baga/Lake sub-basins within the Borno Basin. The different log curves were combined to decipher the lithological heterogeneity of the serrated sand facies and to aid the geologic correlation of sand bodies within the sub-basins. Evaluation of the formation reveals largely undifferentiated to highly serrated and lenticular sand bodies from which twelve reservoirs named Bima Sand-1 to Bima Sand-12 were identified. The reservoir sand bodies are bifurcated by shale beds, which reduced their thicknesses variably from 0.61 to 6.1 m. The shale content in the sand bodies ranged from 11.00% (relatively clean) to high shale content of 88.00%. The formation also has variable porosity values, with calculated total porosity ranged as low as 10.00% to as high as 35.00%. Similarly, effective porosity values spanned between 2.00 to 24.00%. The irregular porosity values also accounted for a wide range of field average permeability estimates computed for the formation, which measured between 0.03 to 319.49 mD. Hydrocarbon saturation (Sh) in the thin lenticular sand bodies also varied from 40.00 to 78.00%. Hydrocarbon was encountered in three intervals in Ga-1, four intervals in Da-1, two intervals in Ar-1, and one interval in Ye-1. Ga-1 well encountered 30.78 m thick of hydrocarbon column in 14 thin sand lobes in Bima Sand-1, with thicknesses from 0.60 m to 5.80 m and average saturation of 51.00%, while Bima Sand-2 intercepted 45.11 m thick of hydrocarbon column in 12 thin sand lobes with an average saturation of 61.00% and Bima Sand-9 has 6.30 m column in 4 thin sand lobes. Da-1 has hydrocarbon in Bima Sand-8 (5.30 m, Sh of 58.00% in 5 sand lobes), Bima Sand-10 (13.50 m, Sh of 52.00% in 6 sand lobes), Bima Sand-11 (6.20 m, Sh of 58.00% in 2 sand lobes) and Bima Sand-12 (16.50 m, Sh of 66% in 6 sand lobes). In the Ar-1 well, hydrocarbon occurs in Bima Sand-3 (2.40 m column, Sh of 48% in a sand lobe) and Bima Sand-9 (6.0 m, Sh of 58% in a sand lobe). Ye-1 well only intersected 0.5 m hydrocarbon in Bima Sand-1 with 78% saturation. Although Bima Formation has variable saturation of hydrocarbon, mainly gas in Maiduguri, and Baga/Lake sub-basins of the research area, its highly thin serrated sand beds, coupled with very low effective porosity and permeability in part, would pose a significant exploitation challenge. The sediments were deposited in a fluvio-lacustrine environment, resulting in a very thinly laminated or serrated alternation of sand and shale beds lithofacies.

Keywords: Bima, Chad Basin, fluvio-lacustrine, lithofacies, serrated sand

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Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: artificial neural network, EDM, metal removal rate, modeling, surface roughness

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Authors: Ehsan Khademi, Mahdi Jalili

Abstract:

Despite the special features of bipartite networks, they are common in many systems. Real-world bipartite networks may show community structure, similar to what one can find in one-mode networks. However, the interpretation of the community structure in bipartite networks is different as compared to one-mode networks. In this manuscript, we compare a number of available methods that are frequently used to discover community structure of bipartite networks. These networks are categorized into two broad classes. One class is the methods that, first, transfer the network into a one-mode network, and then apply community detection algorithms. The other class is the algorithms that have been developed specifically for bipartite networks. These algorithms are applied on a model network with prescribed community structure.

Keywords: community detection, bipartite networks, co-clustering, modularity, network projection, complex networks

Procedia PDF Downloads 627