Search results for: body area network

Authors: Jeffrey Ho, Scott Joing, Paul Nystrom, William Heegaard, Danielle Hart, David Plummer, James Miner

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Body-Worn Cameras (BWCs) are used in public safety to record encounters. They are shown to enhance the accuracy of documentation in virtually every situation. They are not widely used in medical encounters in part because of concern for patient acceptance. The goal of this pilot study was to determine if BWC use is acceptable to the patient. This was a prospective, observational study of the AXON Flex BWC (TASER International, Scottsdale, AZ) conducted at an urban, Level 1 Trauma Center Emergency Department (ED). The BWC was worn by Emergency Physicians (EPs) on their shifts during a 30-day period. The BWC was worn at eye-level mounted on a pair of clear safety glasses. Patients seen by the EP were enrolled in the study by a trained research associate. Patients who were <18 years old, who were with other people in the exam room, did not speak English, were critically ill, had chief complaints involving genitalia or sexual assault, were considered to be vulnerable adults, or with an altered mental status were excluded. Consented patients were given a survey after the encounter to determine their perception of the BWC. The questions asked involved the patients’ perceptions of a BWC being present during their interaction with their EP. Data were analyzed with descriptive statistics. There were 417 patients enrolled in the study. 3/417 (0.7%) patients were intimidated by the BWC, 1/417 (0.2%) was nervous because of the BWC, 0/417 (0%) were inhibited from telling the EP certain things because of the BWC, 57/417 (13.7%) patients did not notice the device, and 305/417 (73.1%) patients were had a favorable perception about the BWC being used during their encounter. The use of BWCs appears feasible in the ED, with largely favorable perceptions and acceptance of the device by the patients. Further study is needed to determine the best use and practices of BWCs during ED patient encounters.

Keywords: body-worn camera, documentation, patient satisfaction, video

Procedia PDF Downloads 369

Authors: Yu Song, Yuefei Jin

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Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

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Authors: David C. Ni

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In the previous efforts, we constructed N-Body Systems by an extended Blaschke product (EBP), which represents a non-temporal and nonlinear extension of Lorentz transformation. In this construction, we rely only on two parameters, nonlinear degree, and relative momentum to characterize the systems. We further explored root computation via iteration with an algorithm extended from Jenkins-Traub method. The solution sets demonstrate a form of σ+ i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various canonical distributions. In this paper, we correlate the convergent sets in the original domain with solution sets, which demonstrating large-deviation distributions in the codomain. We proceed to compare our approach with the formula or principles, such as Donsker-Varadhan and Wentzell-Freidlin theories. The deterministic model based on this construction allows us to explore applications in the areas of finance and statistical mechanics.

Keywords: nonlinear Lorentz transformation, Blaschke equation, iteration solutions, root computation, large deviation distribution, deterministic model

Procedia PDF Downloads 389

Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Muhammad Ilham Agus Salim, Muhammad Ikbal

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The ASEAN Economic Community (AEC) was set up in 2003 with the objectives of creating a single market and production base, enhancing equitable economic development as well as facilitating the integration into the global economy. The AEC involves liberalization and facilitation of trade in goods, skilled labour, services, and investment, as well as protection and promotion of investment. The thesis outlines the AEC Blueprint actions in scope of globalization of investment and capital market. Free flows of investment and freer flows of capital market urge countries in South East Asia to coordinate and to collaborate in securing the interest of public, and this leads to the importance of financial services authorities in ASEAN to prepare the mechanism of guarding the flows of investment. There is no exception, especially for Indonesian Financial Services Authority (OJK) as one of the authorized body in capital market supervision, to enforce its authorities as supervisory body.

Keywords: AEC blueprint, OJK, capital market, integration

Procedia PDF Downloads 310

Authors: Pavan Shah

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In an Embedded system, Virtualization and visualization technology can provide us an effective response and measurable work in a software development environment. In addition to work of virtualization and virtualization can be easily deserved to provide the best resource sharing between real-time hardware applications and a healthy environment. However, the virtualization is noticeable work to minimize the I/O work and utilize virtualization & virtualization technology for either a software development environment (SDE) or a runtime environment of real-time embedded systems (RTMES) or real-time operating system (RTOS) eras. In this Paper, we particularly focus on virtualization and visualization overheads data of network which generates the I/O and implementation of standardized I/O (i.e., Virto), which can work as front-end network driver in a real-time operating system (RTOS) hardware module. Even there have been several work studies are available based on the virtualization operating system environment, but for the Virto on a general-purpose OS, my implementation is on the open-source Virto for a real-time operating system (RTOS). In this paper, the measurement results show that implementation which can improve the bandwidth and latency of memory management of the real-time operating system environment (RTMES) for getting more accuracy of the trained model.

Keywords: virtualization, visualization, network driver, operating system

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Authors: Kalyani Kulkarni, Bharat Chaudhari

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This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.

Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation

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Authors: Kyere Francis, Sun Dongying, Asante Dennis, Nkrumah Nana Kwame Edmund, Naana Yaa Gyamea Kumah

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With a focus on renewable energy to achieve low-carbon transition objectives, there is a greater demand for effective collaborative strategies for planning, strategic decision mechanisms, and long-term policy designs to steer the transitions. Government agencies, NGOs, the private sector, and individual citizens play an important role in sustainable energy production. In Ghana, however, such collaboration is fragile in the fight against climate change. This current study seeks to re-examine the position or potential of network governance in Ghana's renewable energy transition. The study adopted a qualitative approach and employed semi-structured interviews for data gathering. To explore network governance and low carbon transitions in Ghana, we examine key themes such as political environment and impact, actor cooperation and stakeholder interactions, financing and the transition, market design and renewable energy integration, existing regulation and policy gaps for renewable energy transition, clean cooking accessibility, and affordability. The findings reveal the following; Lack of comprehensive consultations with relevant stakeholders leads to lower acceptance of the policy model and sometimes lack of policy awareness. Again, the unavailability and affordability of renewable energy technologies and access to credit facilities is a significant hurdle to long-term renewable transition. Ghana's renewable energy transitions require strong networking and interaction among the public, private, and non-governmental organizations. The study participants believe that the involvement of relevant energy experts and stakeholders devoid of any political biases is instrumental in accelerating renewable energy transitions, as emphasized in the proposed framework. The study recommends that the national renewable energy transition plan be evident to all stakeholders and political administrators. Such policy may encourage renewable energy investment through stable and fixed lending rates by the financial institutions and build a network with international organizations and corporations. These findings could serve as valuable information for the transition-based energy process, primarily aiming to govern sustainability changes through network governance.

Keywords: actors, development, sustainable energy, network governance, renewable energy transition

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Authors: Mukesh Singh Boori, Vít Voženílek

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Olomouc is a unique and complex landmark with widespread forestation and land use. This research work was conducted to assess important and complex land use change trajectories in Olomouc region. Multi-temporal satellite data from 1991, 2001 and 2013 were used to extract land use/cover types by object oriented classification method. To achieve the objectives, three different aspects were used: (1) Calculate the quantity of each transition; (2) Allocate location based landscape pattern (3) Compare land use/cover evaluation procedure. Land cover change trajectories shows that 16.69% agriculture, 54.33% forest and 21.98% other areas (settlement, pasture and water-body) were stable in all three decade. Approximately 30% of the study area maintained as a same land cove type from 1991 to 2013. Here broad scale of political and socio-economic factors was also affect the rate and direction of landscape changes. Distance from the settlements was the most important predictor of land cover change trajectories. This showed that most of landscape trajectories were caused by socio-economic activities and mainly led to virtuous change on the ecological environment.

Keywords: remote sensing, land use/cover, change trajectories, image classification

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Authors: Taleb Odeh, Nizar Abu-Jaber, Nour Khries

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The southern part of Wadi Al Yarmouk catchment area covers north of Jordan. It locates within latitudes 32° 20’ to 32° 45’N and longitudes 35° 42’ to 36° 23’ E and has an area of about 1426 km2. However, it has high relief topography where the elevation varies between 50 to 1100 meter above sea level. The variations in the topography causes different units of landforms, climatic zones, land covers and plant species. As a results of these different landscapes units exists in that region. Spatial planning is a major challenge in such a vital area for Jordan which could not be achieved without determining landscape units. However, an integrated approach of remote sensing and geographic information Systems (GIS) is an optimized tool to investigate and map landscape units of such a complicated area. Remote sensing has the capability to collect different land surface data, of large landscape areas, accurately and in different time periods. GIS has the ability of storage these land surface data, analyzing them spatially and present them in form of professional maps. We generated a geo-land surface data that include land cover, rock units, soil units, plant species and digital elevation model using ASTER image and Google Earth while analyzing geo-data spatially were done by ArcGIS 10.2 software. We found that there are twenty two different landscape units in the study area which they have to be considered for any spatial planning in order to avoid and environmental problems.

Keywords: landscape, spatial planning, GIS, spatial analysis, remote sensing

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

Procedia PDF Downloads 153

Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

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The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

Procedia PDF Downloads 62

Authors: Gwo-Hwa Wan, Tai-Ho Hung, Fen-Fang Chung, Wan-Ying Lee, Hui-Ching Yang

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Air pollutant exposure results in elevated concentrations of oxidative stress and inflammatory biomarkers in general populations. Increased concentrations of inflammatory biomarkers in pregnant women would be associated with preterm labor and low birth weight. To our best knowledge, the associations between air pollutants exposure and inflammation in pregnant women and fetuses are unknown, as well as their effects on fetal growth. This study aimed to evaluate the influences of outdoor air pollutants in northern Taiwan areas on the inflammatory biomarker (high sensitivity C-reactive protein, hs-CRP) concentration in the blood of healthy pregnant women and how the biomarker impacts fetal growth. In this study, 38 healthy pregnant women who are in their first trimester and live in northern Taiwan area were recruited from the Taipei Chang Gung Memorial Hospital. Personal characteristics and prenatal examination data (e.g., blood pressure) were obtained from recruited subjects. The concentrations of inflammatory mediators, hs-CRP, in the blood of healthy pregnant women were analyzed. Additionally, hourly data of air pollutants (PM10, SO2, NO2, O3, CO) concentrations were obtained from air quality monitoring stations in Taipei area, established by the Taiwan Environmental Protection Administration. The definition of lag 0 and lag 01 are the exposure to air pollutants on the day of blood withdrawal, and the average exposure to air pollutants one day before and on the day of blood withdrawal, respectively. The statistical analyses were conducted using SPSS software version 22.0 (SPSS, Inc., Chicago, IL, USA). This analytical result indicates that the healthy pregnant women aged between 28 and 42 years old. The body mass index before pregnancy averaged 21.51 (sd = 2.51) kg/m2. Around 90% of the pregnant women had never smoking habit, and 28.95% of them had allergic diseases. Approximately around 84% and 5.26% of the pregnant women worked at indoor and outdoor environments, respectively. The mean hematocrit level of the pregnant women was 37.10%, and the hemoglobin levels were ranged between 10.1 and 14.7 g/dL with 12.47 g/dL of mean value. The blood hs-CRP concentrations of healthy pregnant women in the first trimester ranged between 0.32 and 32.5 mg/L with 2.83 (sd = 5.69) mg/L of mean value. The blood hs-CRP concentrations were positively associated with ozone concentrations at lag 0-14 (r = 0.481, p = 0.017) in healthy pregnant women. Significant lag effects were identified in ozone at lag 0-14 with a positive excess concentration of blood hs-CRP.

Keywords: air pollutant, hs-CRP, pregnant woman, ozone, first trimester

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Authors: Evalita Amrita, Abdurrokhim, Ildrem Syafri

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Research area is located in Pasedan District, Rembang Regency, Central Java Province. This research is being held for the purpose of microfacies and diagenetic study of carbonate rocks. The study area is dominated by deformed carbonate rocks, folded and faulted. The research method is petrographic analysis with red alizarin staining to differentiate mineral types. Microfacies types and diagenetic processes can be known from petrographic analysis of rock texture, rock structure, type of grain, and fossils. Carbonate rocks in the study area can be divided into 4 types of microfacies: Reef Microfacies (SMF 7), Shallow Water Microfacies (SMF 9), and Textural Inversion Microfacies (SMF 10). Diagenetic processes that take place in carbonate rocks are microbial micritization, compaction, neomorphism, cementation, and dissolution.

Keywords: diagenetic, limestone, microfacies, Rembang

Procedia PDF Downloads 236

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Samai'la Abdullahi

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A graph is a pair of two set and so that a graph is a pictorial representation of a system using two basic element nodes and edges. A node is represented by a circle (either hallo shade) and edge is represented by a line segment connecting two nodes together. In this paper, we present a circuit network in the concept of graph theory application and also circuit models of graph are represented in logical connection method were we formulate matrix method of adjacency and incidence of matrix and application of truth table.

Keywords: euler circuit and path, graph representation of circuit networks, representation of graph models, representation of circuit network using logical truth table

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Authors: N. Tadrisi Parsa, A. R. Vali, R. Ghasemi

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Diabetes is a growing health problem in worldwide. Especially, the patients with Type 1 diabetes need strict glycemic control because they have deficiency of insulin production. This paper attempts to control blood glucose based on body mathematical body model. The Bergman minimal mathematical model is used to develop the nonlinear controller. A novel back-stepping based sliding mode control (B-SMC) strategy is proposed as a solution that guarantees practical tracking of a desired glucose concentration. In order to show the performance of the proposed design, it is compared with conventional linear and fuzzy controllers which have been done in previous researches. The numerical simulation result shows the advantages of sliding mode back stepping controller design to linear and fuzzy controllers.

Keywords: bergman model, nonlinear control, back stepping, sliding mode control

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Authors: Mohd Abdullah

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This review describes some of the effects of repetitive strain/stress injury (RSI) on the human body especially among computer professionals today that spend extended hours of prolonged sitting in front of a computer day in and day out. The review briefly introduces the main factors that contribute to an increase of RSI among such computer professionals. The review briefly discusses how the human spinal column and knees are mainly affected by the onset of RSI resulting in poor posture. The root and secondary causes and effects of RSI are reviewed. The importance and value of the various breathing techniques are reviewed in an attempt to alleviate some of the effects of RSI. The review concludes with a small sample of suggested office stretches and poses geared towards at reducing RSI follows in this review. Readers will learn about the effects of RSI, as well as ways to cope with it. A better understanding of coping strategies may lead to well-being and a healthier overall lifestyle. Ultimately, the investment of time to connect with oneself with the poses and the power of the breath would promote a well-being that is overall healthier thus resulting in a better ability to cope/manage life stresses.

Keywords: health, wellness, repetitive, chairs

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

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Authors: Oscar Rubiano, Oscar Ortiz, Natalia Morales, Lida Alfonso, Johana Alvarado, Adriana Gutierrez, Daniel Botero

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Athletes who usually use protein supplements, are those who practice strength and power sports, whose goal is to achieve a large muscle mass. However, it has also been explored in sports or endurance activities such as cycling, and where despite requiring high power, prominent muscle development can impede good competitive performance due to the determinant of body mass for good performance of the athlete body. This research shows, the effect with protein supplements establishes a protein - muscle mass ratio, although in a lesser proportion the relationship between protein types and muscle power. Thus, we intend to explore as a first approximation, the behavior of muscle power in lower limbs after the intake of two protein supplements from different sources. The aim of the study was to describe the behavior of muscle power in lower limbs after the consumption of animal protein (AP) and vegetable protein (VP) in four route cyclists from 18 to 20 years of the Bogota cycling league. The methodological design of this study is quantitative, with a non-probabilistic sampling, based on a pre-experimental model. The jumping power was evaluated before and after the intervention by means of the squat jump test (SJ), Counter movement jump (CMJ) and Abalacov (AB). Cyclists consumed a drink with whey protein and a soy isolate after training four times a week for three months. The amount of protein in each cyclist, was calculated according to body weight (0.5 g / kg of muscle mass). The results show that subjects who consumed PV improved muscle strength and landing strength. In contrast, the power and landing force decreased for subjects who consumed PA. For the group that consumed PV, the increase was positive at 164.26 watts, 135.70 watts and 33.96 watts for the AB, SJ and CMJ jumps respectively. While for PA, the differences of the medians were negative at -32.29 watts, -82.79 watts and -143.86 watts for the AB, SJ and CMJ jumps respectively. The differences of the medians in the AB jump were positive for both the PV (121.61 Newton) and PA (454.34 Newton) cases, however, the difference was greater for PA. For the SJ jump, the difference for the PA cases was 371.52 Newton, while for the PV cases the difference was negative -448.56 Newton, so the difference was greater in the SJ jump for PA. In jump CMJ, the differences of the medians were negative for the cases of PA and PV, being -7.05 for PA and - 958.2 for PV. So the difference was greater for PA. The conclusion of this study shows that serum protein supplementation showed no improvement in muscle power in the lower limbs of the cyclists studied, which could suggest that whey protein does not have a beneficial effect on performance in terms of power, either, showed an impact on body composition. In contrast, supplementation with soy isolate showed positive effects on muscle power, body.

Keywords: animal protein (AP), muscle power, supplements, vegetable protein (VP)

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Deepak Mohan, Sushma Sharma

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Diclofenac sodium, a member of the acetic acid family of non-steroidal anti-inflammatory drugs, is used to retard inflammation, arthritis pain and ankylosing spondylitis. The drug is known to cause severe injury in different tissues due to formation of reactive oxygen species. The present study is focused on the effect of different doses of diclofenac (4 mg/kg/body weight and 14 mg/kg/body weight on histoarchitecture of the liver from 7-28 days of the investigation. Diclofenac administration resulted in distorted hepatic degeneration and formation of wide areas in the form of sinusoidal gaps. Hepatic fibrosis noticed in different stages of investigation could be attributed to chronic inflammation and reactive oxygen species which results in deposition of extracellular matrix proteins. The abrupt degenerative changes observed during later stages of the experiment showed maximum damage to the liver, and there was enlargement of sinusoidal gaps accompanied by maximum necrosis in the tissues.

Keywords: arthritis, diclofenac, histoarchitecture, sinusoidal

Procedia PDF Downloads 268

Authors: James D. Beauchemin

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Introduction: The incarceration of people with mental illness and substance use disorders is a major public health issue with social, clinical, and economic implications. Yoga participation has been associated with numerous psychological benefits; however, there is a paucity of research examining impacts of yoga with incarcerated populations. The purpose of this study was to evaluate effectiveness of a six-week yoga intervention on several mental health-related variables, including emotion regulation, body awareness, and warnings of substance relapse among incarcerated females. Methods: This study utilized a pre-post, three-arm design, with participants assigned to intervention, therapeutic community, or general population groups. A between-group analysis of covariance (ANCOVA) was conducted across groups to assess intervention effectiveness using the Difficulties in Emotion Regulation Scale (DERS), Scale of Body Connection (SBC), and Warnings of Relapse (AWARE) Questionnaire. Results: ANCOVA results for warnings of relapse (AWARE) revealed significant between-group differences F(2, 80) = 7.15, p = .001; np2 = .152), with significant pairwise comparisons between the intervention group and both the therapeutic community (p = .001) and the general population (p = .005) groups. Similarly, significant differences were found for emotional regulation (DERS) F(2, 83) = 10.521, p = .000; np2 = .278). Pairwise comparisons indicated a significant difference between the intervention and general population (p = .01). Finally, significant differences between the intervention and control groups were found for body awareness (SBC) F(2, 84) = 3.69, p = .029; np2 = .081). Between-group differences were clarified via pairwise comparisons, indicating significant differences between the intervention group and both the therapeutic community (p = .028) and general population groups (p = .020). Implications: Study results suggest that yoga may be an effective addition to integrative mental health and substance use treatment for incarcerated women and contributes to increasing evidence that holistic interventions may be an important component for treatment with this population. Specifically, given the prevalence of mental health and substance use disorders, findings revealed that changes in body awareness and emotion regulation might be particularly beneficial for incarcerated populations with substance use challenges as a result of yoga participation. From a systemic perspective, this proactive approach may have long-term implications for both physical and psychological well-being for the incarcerated population as a whole, thereby decreasing the need for traditional treatment. By integrating a more holistic, salutogenic model that emphasizes prevention, interventions like yoga may work to improve the wellness of this population while providing an alternative or complementary treatment option for those with current symptoms.

Keywords: wellness, solution-focused coaching, college students, prevention

Procedia PDF Downloads 117

Authors: Fatema Akram, Mohammad Golam Rasul, Mohammad Masud Kamal Khan, Md. Sharif Imam Ibne Amir

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A variety of routing techniques are available to develop surface runoff hydrographs from rainfall. The selection of runoff routing method is very vital as it is directly related to the type of watershed and the required degree of accuracy. There are different modelling softwares available to explore the rainfall-runoff process in urban areas. XPSTORM, a link-node based, integrated storm-water modelling software, has been used in this study for developing surface runoff hydrograph for a Golf course area located in Rockhampton in Central Queensland in Australia. Four commonly used methods, namely SWMM runoff, Kinematic wave, Laurenson, and Time-Area are employed to generate runoff hydrograph for design storm of this study area. In runoff mode of XPSTORM, the rainfall, infiltration, evaporation and depression storage for sub-catchments were simulated and the runoff from the sub-catchment to collection node was calculated. The simulation results are presented, discussed and compared. The total surface runoff generated by SWMM runoff, Kinematic wave and Time-Area methods are found to be reasonably close, which indicates any of these methods can be used for developing runoff hydrograph of the study area. Laurenson method produces a comparatively less amount of surface runoff, however, it creates highest peak of surface runoff among all which may be suitable for hilly region. Although the Laurenson hydrograph technique is widely acceptable surface runoff routing technique in Queensland (Australia), extensive investigation is recommended with detailed topographic and hydrologic data in order to assess its suitability for use in the case study area.

Keywords: ARI, design storm, IFD, rainfall temporal pattern, routing techniques, surface runoff, XPSTORM

Procedia PDF Downloads 450

Authors: Mustafa M. Donma, Orkide Donma

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Anthropometric obesity indices such as waist circumference (WC), indices derived from anthropometric measurements such as waist-to-hip ratio (WHR), and indices created from body fat mass composition such as trunk-to-leg fat ratio (TLFR) are commonly used for the evaluation of mild or severe forms of obesity. Their clinical utilities are being compared using body mass index (BMI) percentiles to classify obesity groups. The best of them is still being investigated to make a clear-cut discrimination between healthy normal individuals (N-BMI) and overweight or obese (OB) or morbid obese patients. The aim of this study is to derive a new index, which best suits the purpose for the discrimination of children with N-BMI from OB children. A total of eighty-three children participated in the study. Two groups were constituted. The first group comprised 42 children with N-BMI, and the second group was composed of 41 OB children, whose age- and sex- adjusted BMI percentile values vary between 95 and 99. The corresponding values for the first group were between 15 and 85. This classification was based upon the tables created by World Health Organization. The institutional ethics committee approved the study protocol. Informed consent forms were filled by the parents of the participants. Anthropometric measurements were taken and recorded following a detailed physical examination. Within this context, weight, height (Ht), WC, hip C (HC), neck C (NC) values were taken. Body mass index, WHR, (WC+HC)/2, WC/Ht, (WC/HC)/Ht, WC*NC were calculated. Bioelectrical impedance analysis was performed to obtain body’s fat compartments in terms of total fat, trunk fat, leg fat, arm fat masses. Trunk-to-leg fat ratio, trunk-to-appendicular fat ratio (TAFR), (trunk fat+leg fat)/2 ((TF+LF)/2) were calculated. Fat mass index (FMI) and diagnostic obesity notation model assessment-II (D2I) index values were calculated. Statistical analysis of the data was performed. Significantly increased values of (WC+HC)/2, (TF+LF)/2, D2I, and FMI were observed in OB group in comparison with those of N-BMI group. Significant correlations were calculated between BMI and WC, (WC+HC)/2, (TF+LF)/2, TLFR, TAFR, D2I as well as FMI both in N-BMI and OB groups. The same correlations were obtained for WC. (WC+HC)/2 was correlated with TLFR, TAFR, (TF+LF)/2, D2I, and FMI in N-BMI group. In OB group, the correlations were the same except those with TLFR and TAFR. These correlations were not present with WHR. Correlations were observed between TLFR and BMI, WC, (WC+HC)/2, (TF+LF)/2, D2I as well as FMI in N-BMI group. Same correlations were observed also with TAFR. In OB group, correlations between TLFR or TAFR and BMI, WC as well as (WC+HC)/2 were missing. None was noted with WHR. From these findings, it was concluded that (WC+HC)/2, but not WHR, was much more suitable as an anthropometric obesity index. The only correlation valid in both groups was that exists between (WC+HC)/2 and (TF+LF)/2. This index was suggested as a link between anthropometric and fat-based indices.

Keywords: children, hip circumference, obesity, waist circumference

Procedia PDF Downloads 166

Authors: Xinli Chi, Xiaoqi Wei

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Background: Body-mind theory refers to the concept that the mind and body are interconnected; in this case, combining aerobic exercise and mindfulness-based training may be beneficial for mind-body health; however, there is limited evidence regarding their effects and potential mechanisms among Chinese university students. Therefore, the current study aims to examine the preliminary effects and feasibility of the combined intervention on depressive and insomnia symptoms, as well as to explore the underlying mechanisms. Methods: This is a two-arm pilot study of a randomized, controlled trial. Sixty-one Chinese university students were randomly allocated to 8-week combined intervention group (aerobic exercise plus mindfulness, N = 36) or control group (N = 36). In addition, 8 participants in combined intervention group were later volunteer to engage in semi-structured interview. The Self-Rating Depression Scale (SDS) and the Youth Self-Rating Insomnia Scales (YSIS) were used to measure depressive and insomnia symptoms, respectively. The intervention outcome and feasibility were tested by repeated-measures ANOVA, mediation model, and qualitative analysis. Results: The study included 31 participants in the intervention group and 30 participants in the control group, all of whom completed pre-test and post-test questionnaires. The results of the repeated-measures ANOVA showed that the combined intervention was effective in reducing depressive and insomnia symptoms among university students. Moreover, the mediation analysis suggested that improvement in insomnia symptoms might be a significant mechanism for the combined intervention. Qualitative analysis identified two main themes: “Helpful aspects of mind-body state” (including 7 sub-themes) and “Factors that influence the training effects” (including 3 sub-themes). Conclusions: The study confirmed the preliminary effect and feasibility of the combined intervention of mindfulness and aerobic exercise, while also exploring the potential mechanisms underlying this effect. Additionally, qualitative data provided valuable insights for optimizing future protocols.

Keywords: combined intervention, mindfulness, aerobic exercise, depressive symptoms, insomnia symptoms

Procedia PDF Downloads 98