Search results for: care networks

Authors: Sunmyeng Kim

Abstract:

IEEE 802.11a/b/g standards support multiple transmission rates. Even though the use of multiple transmission rates increase the WLAN capacity, this feature leads to the performance anomaly problem. Cooperative communication was introduced to relieve the performance anomaly problem. Data packets are delivered to the destination much faster through a relay node with high rate than through direct transmission to the destination at low rate. In the legacy cooperative protocols, a source node chooses a relay node only based on the transmission rate. Therefore, they are not so feasible in multi-flow environments since they do not consider the effect of other flows. To alleviate the effect, we propose a new relay node selection algorithm based on the transmission rate and channel contention level. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and delay.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

Procedia PDF Downloads 334

Authors: Sherine Farrag

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Magnetic resonance imaging (MRI) presents safety hazards, with the general physical environment. The principal hazard of the MRI is the presence of static magnetic fields. Proper architectural design of MRI’s room ensure environment and health care staff safety. This research paper presents an easy approach for numerical computation of fringe static magnetic fields. Iso-gauss line of different MR intensities (0.3, 0.5, 1, 1.5 Tesla) was mapped and a polynomial function of the 7th degree was generated and tested. Matlab script was successfully applied for MRI SMF mapping. This method can be valid for any kind of commercial scanner because it requires only the knowledge of the MR scanner room map with iso-gauss lines. Results help to develop guidelines to guide healthcare architects to design of a safer Magnetic resonance imaging suite.

Keywords: designing MRI suite, MRI safety, radiology occupational exposure, static magnetic fields

Procedia PDF Downloads 486

Authors: Edmar Jose da Rocha

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This paper is a study on Brazilian irregular migrants living and working in two global cities in Europe, Milan and London. The aim of the journal is to show out why Brazilian choose irregular migration to Milan and London as a strategy. Few studies in Europe have focused on groups coming from the same place of origin and residing in different cities in comparative studies. It is this international comparison that makes this research original. Both in London and Milan there is an economic migration. The reasons showed to migrate to Milan were marriage, citizenship and work. The reasons indicated to migrate to London were work, studies and a better life. In London marriage is a channel for regularisation and citizenship. In both countries, fake documents is a channel for undocumented people to get a job and health care.

Keywords: border, immigration, integration, survival strategies, undocumented, regularisation

Procedia PDF Downloads 320

Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss

Abstract:

This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.

Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking

Procedia PDF Downloads 566

Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss

Abstract:

This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.

Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking

Procedia PDF Downloads 501

Authors: Parth Patel, Ying Zhu

Abstract:

Distributed systems have become ubiquitous, and they continue their growth through a range of services. With advances in resource virtualization technology such as Virtual Machines (VM) and software containers, developers no longer require high-end servers to test and develop distributed software. Even in commercial production, virtualization has streamlined the process of rapid deployment and service management. This paper introduces a distributed systems testbed that utilizes virtualization to enable distributed systems development on commodity computers. The testbed can be used to develop new services, implement theoretical distributed systems concepts for understanding, and experiment with virtual network topologies. We show its versatility through two case studies that utilize the testbed for implementing a theoretical algorithm and developing our own methodology to find high-risk edges. The results of using the testbed for these use cases have proven the effectiveness and versatility of this testbed across a range of scenarios.

Keywords: distributed systems, experimental testbed, peer-to-peer networks, virtual container technology

Procedia PDF Downloads 147

Authors: Samir Hessas

Abstract:

Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Stefan Bradu, Daniel Siegel, Jameson Loyal, Andrea Leaf, Alana Kurtti, Usha Alapati, Jared Jagdeo

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Compared with all other variants of nodular melanoma, patients with polypoid nodular melanoma have the lowest 5-year survival rate. The pathophysiology and management of polypoid melanoma are scarcely reported in the literature. Although surgical excision is the cornerstone of melanoma management, treatment of polypoid melanoma is complicated by several negative prognostic factors, including early metastasis. This report demonstrates the successful treatment of a rapidly developing red nodular polypoid melanoma with metastasis using surgery and adjuvant nivolumab in a SARS-CoV-2-positive patient who delayed seeking care due to the COVID-19 pandemic. In addition to detailing the successful treatment approach, the immunosuppressive effects of SARS-2-CoV and its possible contribution to the rapid progression of polypoid melanoma are discussed. This case highlights the complex challenges of melanoma diagnosis and management during the COVID-19 pandemic.

Keywords: covid-19, dermatology, immunotherapy, melanoma, nivolumab

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Authors: Niken Hartati

Abstract:

This study provides a description of the problem and sources of social support that given to 90 mothers from poor households. Data were collected using structured interviews with the three main questions: 1) what kind of problem in mothers daily life, 2) to whom mothers ask for help to overcome it and 3) the form of the assistances that provided. Furthermore, the data were analyzed using content analysis techniques were then coded and categorized. The results of the study illustrate the problems experienced by mothers of poor households in the form of: subsistence (37%), child care (27%), management of money and time (20%), housework (5%), bad place of living (5%), the main breadwinner (3%), and extra costs (3%). While the sources of social support that obtained by mothers were; neighbors (10%), extended family (8%), children (8%), husband (7%), parents (7%), and siblings (5%). Unfortunately, more mothers who admitted not getting any social support when having problems (55%). The form of social support that given to mother from poor household were: instrumental support (91%), emotional support (5%) and informational support (2%). Implications for further intervention also discussed in this study.

Keywords: household problems, social support, mothers, poor households

Procedia PDF Downloads 367

Authors: Somdatta Saha

Abstract:

The main purpose was to provide an implementable design scenario for underground coal mines using wireless sensor networks (WSNs). The main reason being that given the intricacies in the physical structure of a coal mine, only low power WSN nodes can produce accurate surveillance and accident detection data. The work mainly concentrated on designing and simulating various alternate scenarios for a typical mine and comparing them based on the obtained results to arrive at a final design. In the Era of embedded technology, the Zigbee protocols are used in more and more applications. Because of the rapid development of sensors, microcontrollers, and network technology, a reliable technological condition has been provided for our automatic real-time monitoring of coal mine. The underground system collects temperature, humidity and methane values of coal mine through sensor nodes in the mine; it also collects the number of personnel inside the mine with the help of an IR sensor, and then transmits the data to information processing terminal based on ARM.

Keywords: ARM, embedded board, wireless sensor network (Zigbee)

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Authors: Priyanka Manghani, Manthan Patel, Rahul Peddawad

Abstract:

Cervical Cancer is a major public health hurdle in the area of women’s health. The most common cause of Cervical Cancer is the Human Papilloma Virus (HPV). Human papilloma virus has various genotypes, with HPV 16 and HPV 18 being the major etiological factor causing carcinoma of the Cervix. Early screening and detection by Papanicolaou Smears (PAP) is an effective method for identifying premalignant and malignant lesions. In case of existing pre- malignant lesions /cervical dysplasia’s found with HPV 16 or 18, appropriate follow up can be done to prevent it from developing into a neoplasm. Aims and Objectives: Primary Aim; To study various abnormal cervical cytology reports as detected by Pap Smear Tests, using the Bethesda System in women at a Tertiary Care Hospital. Secondary Aim; To discuss the importance of Pap smear in Cervical Cancer Screening Program. Materials and Methods: Our study is a prospective study, based on 101 women who attended the Out-patient department of Obstetrics and Gynecology at a tertiary care hospital in age group 20-40 years with chief complaints of white/foul vaginal discharge, post-coital Bleeding, low back pain, irregular menstruation, etc. 60 women, who were tested, of the total no of women, were commercial sex workers, thus being a high-risk group for HPV infection. All women underwent conventional cytology. For all the abnormal smears, further cervical biopsies were done, and the final diagnosis was done on the basis of histopathology (gold standard). Results: In all these patients, 16 patients presented with normal smears out of which 2 belonged to the category of commercial sex workers (3.33%) and 14 being from the normal/control group (34.15%). 44 women presented with inflammatory smears out of which 30 were commercial sex workers (50%) and 14 from the control Group (34.15%). A total of 11 women presented with infectious etiology with 6 being commercial sex workers (10%) and 5 (12.2%) being in the control group. A total of 8 patients presented with low-grade squamous intra epithelial lesion (LSIL) with 7 (11.7%) being commercial sex workers and 1(2.44%) patient belonging to the control group. A Total of 7 patients presented with high-grade squamous intraepithelial lesion (HSIL) with 6 (10%) being commercial sex workers and 1 (2.44%) belonging to the control group. 9 patients in total presented with atypical squamous cells of undetermined significance (ASCUS) with 6(10%) being commercial sex workers and 3 (7.32%) belonging to the control group. Squamous cell carcinoma(SCC) presence was found only in 1(1.7%) commercial sex worker. Conclusion – We conclude that HSIL, LSIL, SCC and sexually related infections are comparatively more common in vulnerable groups such as sex workers due to a variety of factors such as multiple sexual partners and poor genital hygiene. Early screening and follow up interventions are highly needed for them along with Health education for risk factors and to emphasize on the importance of Pap smear screening.

Keywords: cervical cancer, papanicolaou (pap) smear, bethesda system, neoplasm

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Authors: Kittipob Kondee, Chutima Prommak

Abstract:

In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

Procedia PDF Downloads 247

Authors: Zohra Mhedhbi, Meheret Gaston, Sinda Haoues-Jouve, Julia Hidalgo, Pierre Mazzega

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In the current context of climate change, supporting national and local stakeholders to make climate-smart decisions is necessary but still underdeveloped in many countries. To overcome this problem, the Global Frameworks for Climate Services (GFCS), implemented under the aegis of the United Nations in 2012, has initiated many programs in different countries. The GFCS contributes to the development of Climate Services, an instrument based on the production and transfer of scientific climate knowledge for specific users such as citizens, urban planning actors, or agricultural professionals. As cities concentrate on economic, social and environmental issues that make them more vulnerable to climate change, the New Urban Agenda (NUA), adopted at Habitat III in October 2016, highlights the importance of paying particular attention to disaster risk management, climate and environmental sustainability and urban resilience. In order to support the implementation of the NUA, the World Meteorological Organization (WMO) has identified the urban dimension as one of its priorities and has proposed a new tool, the Integrated Urban Services (IUS), for more sustainable and resilient cities. In the southern countries, there’s a lack of development of climate services, which can be partially explained by problems related to their economic financing. In addition, it is often difficult to make climate change a priority in urban planning, given the more traditional urban challenges these countries face, such as massive poverty, high population growth, etc. Climate services and Integrated Urban Services, particularly in African cities, are expected to contribute to the sustainable development of cities. These tools will help promoting the acquisition of meteorological and socio-ecological data on their transformations, encouraging coordination between national or local institutions providing various sectoral urban services, and should contribute to the achievement of the objectives defined by the United Nations Framework Convention on Climate Change (UNFCCC) or the Paris Agreement, and the Sustainable Development Goals. To assess the state of the art on these various points, the Web of Science metadatabase is queried. With a query combining the keywords "climate*" and "urban*", more than 24,000 articles are identified, source of more than 40,000 distinct keywords (but including synonyms and acronyms) which finely mesh the conceptual field of research. The occurrence of one or more names of the 514 African cities of more than 100,000 inhabitants or countries, reduces this base to a smaller corpus of about 1410 articles (2990 keywords). 41 countries and 136 African cities are cited. The lexicometric analysis of the metadata of the articles and the analysis of the structural indicators (various centralities) of the networks induced by the co-occurrence of expressions related more specifically to climate services show the development potential of these services, identify the gaps which remain to be filled for their implementation and allow to compare the diversity of national and regional situations with regard to these services.

Keywords: African cities, climate change, climate services, integrated urban services, lexicometry, networks, urban planning, web of science

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Authors: Anwar H. Radwan, Jan Mrlina, El-Sayed A. Issawy, Ali Rayan, Salah M. Mahmoud

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Geodynamic investigations in the Aswan Lake region were started after the M=5.5 earthquake in 1981, triggered by the lake water fluctuations. Besides establishing the seismological networks, also the geodetic observations focused on the Kalabsha and Sayal fault zones were started. It was found that the Kalabsha fault is an active dextral strike-slip with normal component indicating uplift on its southern side. However, the annual velocity rates in both components do not exceed 2 mm/y, and do not therefore represent extremely active faulting. We also launched gravity monitoring in 1997, and performed another two campaigns in 2000 and 2002. The observed non- tidal temporal gravity changes indicate rather the flood water infiltration into the porous Nubian sandstone, than tectonic stress effect. The station nearest to the lake exhibited about 60 μGal positive gravity change within the 1997-2002 period.

Keywords: gravity monitoring, surface movements, Lake Aswan, groundwater change

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

Procedia PDF Downloads 425

Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss

Abstract:

This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using MATLAB simulink.

Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking

Procedia PDF Downloads 527

Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

Abstract:

Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

Procedia PDF Downloads 659

Authors: Babanyara Y. Y., Ibrahim D. B., Garba T., Bogoro A. G., Abubakar, M. Y.

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Medical care is vital for our life, health, and well-being. However, the waste generated from medical activities can be hazardous, toxic, and even lethal because of their high potential for diseases transmission. The hazardous and toxic parts of waste from healthcare establishments comprising infectious, medical, and radioactive material as well as sharps constitute a grave risks to mankind and the environment, if these are not properly treated/disposed or are allowed to be mixed with other municipal waste. In Nigeria, practical information on this aspect is inadequate and research on the public health implications of poor management of medical wastes is few and limited in scope. Findings drawn from Literature particularly in the third world countries highlights financial problems, lack of awareness of risks involved in MWM, lack of appropriate legislation and lack of specialized MWM staff. The paper recommends how MWM practices can be improved in medical facilities.

Keywords: environmental pollution, infectious, management, medical waste, public health

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Authors: Mihai Rebenciuc, Simona Mihaela Bibic

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Branch of modern mathematics, graphs represent instruments for optimization and solving practical applications in various fields such as economic networks, engineering, network optimization, the geometry of social action, generally, complex systems including contemporary urban problems (path or transport efficiencies, biourbanism, & c.). In this paper is studied the interconnection of some urban network, which can lead to a simulation problem of a digraph through another digraph. The simulation is made univoc or more general multivoc. The concepts of fragment and atom are very useful in the study of connectivity in the digraph that is simulation - including an alternative evaluation of k- connectivity. Rough set approach in (bi)digraph which is proposed in premier in this paper contribute to improved significantly the evaluation of k-connectivity. This rough set approach is based on generalized rough sets - basic facts are presented in this paper.

Keywords: (bi)digraphs, rough set theory, systems of interacting agents, complex systems

Procedia PDF Downloads 245

Authors: Shaikh Farhad Hossain, Liakot Ali

Abstract:

Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

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Authors: David Loh, Wan Chee Wai, Pei Nan, Chen Zhe

Abstract:

To increase the conveyance capacity to Western Singapore and to meet Singapore’s long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of two 2200 mm diameter water pipes and two 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the west region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected to lay the proposed 1.6km-long pipelines that cross a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examined the difficulties such as (1) construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater; (2) manpower and supply disruptions caused by the COVID-19 pandemic situation.

Keywords: underwater tunnel, subsea engineering, subsea tunnel construction, waterpipe construction

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Chinlun Lai, Yu-Mei Chang

Abstract:

In this paper, an augmented reality learning support system is proposed to replace the traditional teaching tool thus to help students improve their learning motivation, effectiveness, and efficiency. The system can not only reduce the exhaust of educational hardware and realistic material, but also provide an eco-friendly and self-learning practical environment in any time and anywhere with immediate practical experiences feedback. To achieve this, an interactive self-training methodology which containing step by step operation directions is designed using virtual 3D scenario and wearable device platforms. The course of nasogastric tube care of nursing skills is selected as the test example for self-learning and online test. From the experimental results, it is observed that the support system can not only increase the student’s learning interest but also improve the learning performance than the traditional teaching methods. Thus, it fulfills the strategy of learning by practice while reducing the related cost and effort significantly and is practical in various fields.

Keywords: augmented reality technology, learning support system, self-learning, simulation learning method

Procedia PDF Downloads 170

Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Liya Abraham

Abstract:

Eritrea is located along the Red Sea, north of the Horn of Africa, between Djibouti and Sudan and has a population of about 3.2 million as of 2010. It has six administrative regions; Anseba, Debub, Debubawi K’eyih Bahri, Gash-Barka, Ma'akel, and Semenawi K’eyih Bahri. Eritrea has got its independence in 1991 after 30 years war of liberation. The country is blessed with various medicinal flora and fauna, and marine and terrestrial biodiversity. Traditional Medicine (TM) has been an integral part of the Eritrean culture for centuries. So far, more than 19 TM modalities have been recognized, and are broadly categorized as; herbal, procedure-based and spiritual. Despite the availability of modern medicine to the majority of the population, TM is still widely practiced. The rationale behind widespread use is accessibility, affordability and cultural acceptability. Hence, TM is of great contribution to the Eritrean health care system. As a matter of fact, harnessing the potential contribution of effective and safe TM in order to attain Universal Health Coverage (UHC) has been emphasized in the WHO TM strategy 2014-2023. The Eritrean TM, however, was operating without regulation and reliable scientific justification behind its safety and efficacy. Thus, the Ministry of Health (MoH), in recognition of the role of TM in primary healthcare and safeguard public health, established a regulatory body for TM so-called as Traditional Medicine Unit (TMU) in 2012. The mission of the unit is to ensure rational TM use through an integrated health service delivery system and contribute to the country’s economic and social development. The unit has established its national TM policy in 2017. The activities of the unit are guided by the National TM Advisory Committee (TMAC), responsible for the provision of technical assistance and advisory role. Moreover, the Legal Framework and Code of Ethics and Practice which provide a legal basis for the regulation of TM have also been drafted. In recognition of the importance of TM research and development, the unit launched a nationwide TM survey in 2017 and had surveyed two zones (Gash-Barka and Debub). The findings of the survey were subjected to a research dissemination workshop and publication in international journals. Furthermore, TM-related adverse events reporting tool (Green Form) aiming to guide regulatory interventions and researches have been established by the unit, and ever since reports are flowing. The unit has also been offering training to THPs, pharmacy students and health care professionals regarding TM and its regulatory activities. In addition, as part of the establishment of the national medicinal plants' database and herbal monograph, more than 329 and 30 medicinal plants, have been compiled respectively. In conclusion, TM is still widely accepted and practiced in Eritrea. The TMU ever since its establishment is endeavoring to ensure the safety and efficacy of the TM, and its integration in the mainstream health service delivery system.

Keywords: efficacy, regulation, safety, traditional medicine, traditional medicine unit, universal health coverage

Procedia PDF Downloads 188

Authors: Doaa Wael, Naswa Abdelbaky

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Malware is malicious software that is built to cause destructive actions and damage information systems and networks. Malware infections increase rapidly, and types of malware have become more sophisticated, which makes the malware detection process more difficult. On the other side, the Internet of Things IoT technology is vulnerable to malware attacks. These IoT devices are always connected to the internet and lack security. This makes them easy for hackers to access. These malware attacks are becoming the go-to attack for hackers. Thus, in order to deal with this challenge, new malware detection techniques are needed. Currently, building a blockchain solution that allows IoT devices to download any file from the internet and to verify/approve whether it is malicious or not is the need of the hour. In recent years, blockchain technology has stood as a solution to everything due to its features like decentralization, persistence, and anonymity. Moreover, using blockchain technology overcomes some difficulties in malware detection and improves the malware detection ratio over-than the techniques that do not utilize blockchain technology. In this paper, we study malware detection models which are based on blockchain technology. Furthermore, we elaborate on the effect of blockchain technology in malware detection, especially in the android environment.

Keywords: malware analysis, blockchain, malware attacks, malware detection approaches

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Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 79

Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI

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Authors: JingWei Yu, Hong Yang Yu

Abstract:

At present, the increasingly serious air pollution in various cities of China has made people pay more attention to the air quality index(hereinafter referred to as AQI) of their living areas. To face this situation, it is of great significance to predict air pollution in heavily polluted areas. In this paper, based on the time series model of LSTM, a spatiotemporal prediction model of PM2.5 concentration in Mianyang, Sichuan Province, is established. The model fully considers the temporal variability and spatial distribution characteristics of PM2.5 concentration. The spatial correlation of air quality at different locations is based on the Air quality status of other nearby monitoring stations, including AQI and meteorological data to predict the air quality of a monitoring station. The experimental results show that the method has good prediction accuracy that the fitting degree with the actual measured data reaches more than 0.7, which can be applied to the modeling and prediction of the spatial and temporal distribution of regional PM2.5 concentration.

Keywords: LSTM, PM2.5, neural networks, spatio-temporal prediction

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Authors: Kay Thi Yar, Khin Mar Lar Tun

Abstract:

Nowadays, social networks are so popular and widely used in all over the world. In addition, searching personal information of each person and searching connection between them (peoples’ relation in real world) becomes interesting issue in our society. In this paper, we propose a framework with three portions for exploring peoples’ relations from their connected information. The first portion focuses on the Graph database structure to store the connected data of peoples’ information. The second one proposes the graph database searching algorithm, the Modified-SoS-ACO (Sense of Smell-Ant Colony Optimization). The last portion proposes the Deductive Reasoning Algorithm to define two persons’ relationship. This study reveals the proper storage structure for connected information, graph searching algorithm and deductive reasoning algorithm to predict and analyze the personnel relationship from peoples’ relation in their connected information.

Keywords: personnel information, graph storage structure, graph searching algorithm, deductive reasoning algorithm

Procedia PDF Downloads 453