Search results for: network security management
6852 AI Software Algorithms for Drivers Monitoring within Vehicles Traffic - SiaMOTO
Authors: Ioan Corneliu Salisteanu, Valentin Dogaru Ulieru, Mihaita Nicolae Ardeleanu, Alin Pohoata, Bogdan Salisteanu, Stefan Broscareanu
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Creating a personalized statistic for an individual within the population using IT systems, based on the searches and intercepted spheres of interest they manifest, is just one 'atom' of the artificial intelligence analysis network. However, having the ability to generate statistics based on individual data intercepted from large demographic areas leads to reasoning like that issued by a human mind with global strategic ambitions. The DiaMOTO device is a technical sensory system that allows the interception of car events caused by a driver, positioning them in time and space. The device's connection to the vehicle allows the creation of a source of data whose analysis can create psychological, behavioural profiles of the drivers involved. The SiaMOTO system collects data from many vehicles equipped with DiaMOTO, driven by many different drivers with a unique fingerprint in their approach to driving. In this paper, we aimed to explain the software infrastructure of the SiaMOTO system, a system designed to monitor and improve driver driving behaviour, as well as the criteria and algorithms underlying the intelligent analysis process.Keywords: artificial intelligence, data processing, driver behaviour, driver monitoring, SiaMOTO
Procedia PDF Downloads 916851 Multichannel Surface Electromyography Trajectories for Hand Movement Recognition Using Intrasubject and Intersubject Evaluations
Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha
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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation
Procedia PDF Downloads 1426850 A Cost-Benefit Analysis of Routinely Performed Transthoracic Echocardiography in the Setting of Acute Ischemic Stroke
Authors: John Rothrock
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Background: The role of transthoracic echocardiography (TTE) in the diagnosis and management of patients with acute ischemic stroke remains controversial. While many stroke subspecialist reserve TTE for selected patients, others consider the procedure obligatory for most or all acute stroke patients. This study was undertaken to assess the cost vs. benefit of 'routine' TTE. Methods: We examined a consecutive series of patients who were admitted to a single institution in 2019 for acute ischemic stroke and underwent TTE. We sought to determine the frequency with which the results of TTE led to a new diagnosis of cardioembolism, redirected therapeutic cerebrovascular management, and at least potentially influenced the short or long-term clinical outcome. We recorded the direct cost associated with TTE. Results: There were 1076 patients in the study group, all of whom underwent TTE. TTE identified an unsuspected source of possible/probable cardioembolism in 62 patients (6%), confirmed an initially suspected source (primarily endocarditis) in an additional 13 (1%) and produced findings that stimulated subsequent testing diagnostic of possible/probable cardioembolism in 7 patients ( < 1%). TTE results potentially influenced the clinical outcome in a total of 48 patients (4%). With a total direct cost of $1.51 million, the mean cost per case wherein TTE results potentially influenced the clinical outcome in a positive manner was $31,375. Diagnostically and therapeutically, TTE was most beneficial in 67 patients under the age of 55 who presented with 'cryptogenic' stroke, identifying patent foramen ovale in 21 (31%); closure was performed in 19. Conclusions: The utility of TTE in the setting of acute ischemic stroke is modest, with its yield greatest in younger patients with cryptogenic stroke. Given the greater sensitivity of transesophageal echocardiography in detecting PFO and evaluating the aortic arch, TTE’s role in stroke diagnosis would appear to be limited.Keywords: cardioembolic, cost-benefit, stroke, TTE
Procedia PDF Downloads 1266849 Microfluidic Fluid Shear Mechanotransduction Device Using Linear Optimization of Hydraulic Channels
Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das
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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear
Procedia PDF Downloads 1306848 Innovating Electronics Engineering for Smart Materials Marketing
Authors: Muhammad Awais Kiani
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The field of electronics engineering plays a vital role in the marketing of smart materials. Smart materials are innovative, adaptive materials that can respond to external stimuli, such as temperature, light, or pressure, in order to enhance performance or functionality. As the demand for smart materials continues to grow, it is crucial to understand how electronics engineering can contribute to their marketing strategies. This abstract presents an overview of the role of electronics engineering in the marketing of smart materials. It explores the various ways in which electronics engineering enables the development and integration of smart features within materials, enhancing their marketability. Firstly, electronics engineering facilitates the design and development of sensing and actuating systems for smart materials. These systems enable the detection and response to external stimuli, providing valuable data and feedback to users. By integrating sensors and actuators into materials, their functionality and performance can be significantly enhanced, making them more appealing to potential customers. Secondly, electronics engineering enables the creation of smart materials with wireless communication capabilities. By incorporating wireless technologies such as Bluetooth or Wi-Fi, smart materials can seamlessly interact with other devices, providing real-time data and enabling remote control and monitoring. This connectivity enhances the marketability of smart materials by offering convenience, efficiency, and improved user experience. Furthermore, electronics engineering plays a crucial role in power management for smart materials. Implementing energy-efficient systems and power harvesting techniques ensures that smart materials can operate autonomously for extended periods. This aspect not only increases their market appeal but also reduces the need for constant maintenance or battery replacements, thus enhancing customer satisfaction. Lastly, electronics engineering contributes to the marketing of smart materials through innovative user interfaces and intuitive control mechanisms. By designing user-friendly interfaces and integrating advanced control systems, smart materials become more accessible to a broader range of users. Clear and intuitive controls enhance the user experience and encourage wider adoption of smart materials in various industries. In conclusion, electronics engineering significantly influences the marketing of smart materials by enabling the design of sensing and actuating systems, wireless connectivity, efficient power management, and user-friendly interfaces. The integration of electronics engineering principles enhances the functionality, performance, and marketability of smart materials, making them more adaptable to the growing demand for innovative and connected materials in diverse industries.Keywords: electronics engineering, smart materials, marketing, power management
Procedia PDF Downloads 596847 Child Feeding Practices of Mothers (Childbearing) and Exploration of Their Household Food Insecurity in a Coastal Region of Bangladesh
Authors: Md Abdullah Al Mamun
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Background: The current situation of Ensuring WHO recommended feeding practices for infant and young children which is becoming a challenge nowadays in many developing countries, especially in areas where household food security is at risk. Because many households of the developing countries often encounter severe food insecurity hence provision of adequate child nutrition is threatened. Aim: The study aimed to assess the child feeding practices of 0-24 months childbearing mothers and explore their household food insecurity in a coastal region of Bangladesh. Methods: This study was conducted in Suborno Char (one of the coastal suburbs in Noakhali District in Bangladesh) from October 2019 to April 2020. A total of 400 mothers were selected with their children of 0-24 months following a cross sectional study sampling procedure of the population. Data were collected through a standard questionnaire and analyzed using statistical tests in SPSS version 20.0.0. Results: The frequency of exclusive breastfeeding, timely initiation of complementary feeding, and giving foods from four food groups to the children were 53.5%, 75.5%, and 22.2%, respectively. Mother's level of education showed a strong association with the child feeding practices of the mothers. Mothers of severely food insecure households showed lower odds in exclusive breastfeeding practice (COR 0.233 at 95% CI 0.083, 0.655; and AOR 0.478 at 95% CI 0.133, 1.713) than mothers of food secured households. Similar results have also been found in case of timely initiation of complementary feeding and minimum dietary diversity of the children.Keywords: household food insecurity, exclusive breastfeeding, complementary feeding, maternal education, mothers age, household income
Procedia PDF Downloads 1596846 Maximum-likelihood Inference of Multi-Finger Movements Using Neural Activities
Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin
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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.Keywords: finger movement, neural activity, blind decoding, M1
Procedia PDF Downloads 3216845 A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification
Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh
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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.Keywords: cancer classification, feature selection, deep learning, genetic algorithm
Procedia PDF Downloads 1116844 Study on Gender Mainstreaming: The Case Study of a Rural University in Limpopo Province, South Africa
Authors: Tsoaledi D. Thobejane, Barnabas C. Okere
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Gender mainstreaming has been adopted as a strategy for promoting gender equality in institutions of higher learning Worldwide, not least in Africa. This study investigated Gender Mainstreaming at the University of Venda, in Limpopo Province, South Africa. The study was based on the Feminist Theoretical Framework. Both qualitative and quantitative approaches were used. A case study research design was adopted. The study involved a population of 60 participants and a sample of 25 male and female workers selected using the purposive sampling technique. Data were presented in pie charts, tables, themes and in textual forms. Data were analysed through descriptive statistics and thematic analysis. The major findings and conclusions of the study were that the University of Venda faces enormous challenges in mainstreaming gender in the university functions. There are perceptions that most strategic higher positions in the institution are dominated by men while women are marginalized. Although the University has policies on gender, staff members do not know about them while management does not implement its policies. University of Venda makes use of the Employment Equity Act of 1998, but it is not clear whether line managers are aware of its implementation and how. In addition, favouritism, nepotism, patronage, and patriarchy played a role in gender mainstreaming. The study recommended that there should be more gender awareness activities, such as workshops, conferences, and symposia for workers and staff members in order to sensitize them about gender towards understanding. The study also recommended that deserving female staff members should be promoted, and all employees should be encouraged to read and understand gender policies. In addition, management should implement the institutions and national gender policies without fear or favour.Keywords: gender mainstreaming, gender equality, institutions, representation
Procedia PDF Downloads 3606843 A Case Study of the Political Determinant of Health on the Public Health Crisis of Malaria in Nigeria
Authors: Bisola Olumegbon
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Globally, there were about 229 million cases of malaria in 2022. The sub-Saharan African region accounted for 92% of the reported cases and 94% of deaths. Nigeria had the highest number of malaria cases and deaths, representing 27% of global cases. This scholarly project was a case study guided by the political determinants of health. Triangulation of data using thematic analysis was used to identify the political determinants of malaria in Nigeria and to understand how the concept of interaction contributes to the persistence of the disease. The analysis involved a deductive and inductive approach based on the literature review and the evidence of political determinants gathered in the data. Participants’ in-depth interviews were used to collect data from frontline personnel. Data triangulation was done using thematic analysis, a method used to identify patterns and themes in qualitative data. The study findings revealed a correlation between political determinants of health and malaria management efforts in Nigeria. Some influencing factors included voting challenges, inadequate funding, lack of health priority from the government, noncompliance among patients, and hurdles to effective communication. The findings suggest a need to deliberately increase dedication to the political agenda, provide sufficient financial resources, enhance communication, and active community involvement to address the persistent malaria endemic effectively. Further study is recommended to identify interventions to address identified factors of political determinants of health to reduce malaria in Nigeria. Such intervention must involve collaboration with diverse stakeholders such as policymakers, healthcare professionals, community leaders, and researchers.Keywords: malaria, malaria management, health worker, stakeholders, political determinant of health
Procedia PDF Downloads 716842 Attribution of Strategic Motive, Business Efficiencies, Firm Economies, and Market Factors as Motivations of Restaurant Industry Vertical Integration Adoption: A Structural Equation Model
Authors: Sy, Melecio Jr
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The decision to adopt vertical integration (VI) is firm-specific, but there is a common practice among businesses in an industry to maximize the massive potential benefits of VI. This study aims to determine VI adoption in the restaurant industry in Davao City. Using a two-step sampling process, the study used a validated survey questionnaire among 264 restaurant owners and managers randomly selected and geographically classified. It is a quantitative study where the data were subjected to a structural equation model (SEM). The results revealed that VI is present but limited to procurement, production, restaurant services, and online marketing. Raw materials were outsourced while delivery to customers through third-party delivery services. VI slowly increased over ten years except for online marketing, which has grown significantly in a few years. The endogenous and exogenous variables were correlated and established the linear regression model. The SEM's best fit model revealed that strategic motives (SMOT) and market factors (MFAC) influenced VI adoption while MFAC is the best predictor. Favorable market factors may lead restaurants to adopt VI. It is, thus, recommended for restaurants to institutionalize strategic management, quantify the impact of double marginalization in future studies as a reason for VI and conduct this study during the new normal to see the influence of business efficiencies and firm economies on VI adoption.Keywords: business efficiencies, business management, davao city, firm economies, market factors, philippines, strategic motives, structural equation model, supply chain, vertical integration adoption
Procedia PDF Downloads 706841 A Bayesian Population Model to Estimate Reference Points of Bombay-Duck (Harpadon nehereus) in Bay of Bengal, Bangladesh Using CMSY and BSM
Authors: Ahmad Rabby
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The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase
Procedia PDF Downloads 1246840 Analysis of Brain Signals Using Neural Networks Optimized by Co-Evolution Algorithms
Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,
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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model
Procedia PDF Downloads 2826839 The Effect of Female Access to Healthcare and Educational Attainment on Nigerian Agricultural Productivity Level
Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote
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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.Keywords: agricultural productivity, education, female, healthcare, investment
Procedia PDF Downloads 816838 Synthesis and Electromagnetic Wave Absorbing Property of Amorphous Carbon Nanotube Networks on a 3D Graphene Aerogel/BaFe₁₂O₁₉ Nanorod Composite
Authors: Tingkai Zhao, Jingtian Hu, Xiarong Peng, Wenbo Yang, Tiehu Li
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Homogeneous amorphous carbon nanotube (ACNT) networks have been synthesized using floating catalyst chemical vapor deposition method on a three-dimensional (3D) graphene aerogel (GA)/BaFe₁₂O₁₉ nanorod (BNR) composite which prepared by a self-propagating combustion process. The as-synthesized ACNT/GA/BNR composite which has 3D network structures could be directly used as a good absorber in the electromagnetic wave absorbent materials. The experimental results indicated that the maximum absorbing peak of ACNT/GA/BNR composite with a thickness of 2 mm was -18.35 dB at 10.64 GHz in the frequency range of 2-18 GHz. The bandwidth of the reflectivity below -10 dB is 3.32 GHz. The 3D graphene aerogel structures which composed of dense interlined tubes and amorphous structure of ACNTs bearing quantities of dihedral angles could consume the incident waves through multiple reflection and scattering inside the 3D web structures. The interlinked ACNTs have both the virtues of amorphous CNTs (multiple reflections inside the wall) and crystalline CNTs (high conductivity), consuming the electromagnetic wave as resistance heat. ACNT/GA/BNR composite has a good electromagnetic wave absorbing performance.Keywords: amorphous carbon nanotubes, graphene aerogel, barium ferrite nanorod, electromagnetic wave absorption
Procedia PDF Downloads 2816837 Modeling of Micro-Grid System Components Using MATLAB/Simulink
Authors: Mahmoud Fouad, Mervat Badr, Marwa Ibrahim
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Micro-grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. Renewable power sources such as wind, solar and hydro offer high potential of benign power for future micro-grid systems. Micro-Grid (MG) is basically a low voltage (LV) or medium voltage (MV) distribution network which consists of a number of called distributed generators (DG’s); micro-sources such as photovoltaic array, fuel cell, wind turbine etc. energy storage systems and loads; operating as a single controllable system, that could be operated in both grid-connected and islanded mode. The capacity of the DG’s is sufficient to support all; or most, of the load connected to the micro-grid. This paper presents a micro-grid system based on wind and solar power sources and addresses issues related to operation, control, and stability of the system. Using Matlab/Simulink, the system is modeled and simulated to identify the relevant technical issues involved in the operation of a micro-grid system based on renewable power generation units.Keywords: micro-grid system, photovoltaic, wind turbine, energy storage, distributed generation, modeling
Procedia PDF Downloads 4356836 Passive Attenuation of Nitrogen Species at Northern Mine Sites
Authors: Patrick Mueller, Alan Martin, Justin Stockwell, Robert Goldblatt
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Elevated concentrations of inorganic nitrogen (N) compounds (nitrate, nitrite, and ammonia) are a ubiquitous feature to mine-influenced drainages due to the leaching of blasting residues and use of cyanide in the milling of gold ores. For many mines, the management of N is a focus for environmental protection, therefore understanding the factors controlling the speciation and behavior of N is central to effective decision making. In this paper, the passive attenuation of ammonia and nitrite is described for three northern water bodies (two lakes and a tailings pond) influenced by mining activities. In two of the water bodies, inorganic N compounds originate from explosives residues in mine water and waste rock. The third water body is a decommissioned tailings impoundment, with N compounds largely originating from the breakdown of cyanide compounds used in the processing of gold ores. Empirical observations from water quality monitoring indicate nitrification (the oxidation of ammonia to nitrate) occurs in all three waterbodies, where enrichment of nitrate occurs commensurately with ammonia depletion. The N species conversions in these systems occurred more rapidly than chemical oxidation kinetics permit, indicating that microbial mediated conversion was occurring, despite the cool water temperatures. While nitrification of ammonia and nitrite to nitrate was the primary process, in all three waterbodies nitrite was consistently present at approximately 0.5 to 2.0 % of total N, even following ammonia depletion. The persistence of trace amounts of nitrite under these conditions suggests the co-occurrence denitrification processes in the water column and/or underlying substrates. The implications for N management in mine waters are discussed.Keywords: explosives, mining, nitrification, water
Procedia PDF Downloads 3196835 Irregular Meal Pattern: What Is the Impact on Weight
Authors: Maha Alhussain, Moira A Taylor, Ian A. Macdonald
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Background: It is well established that dietary composition has effects on metabolism and therefore impacts on health; however other aspects of diet, such as meal pattern, could also be important in both obesity management and promoting health. The present study investigated the effect of irregular meal frequency on anthropometric measurements and energy expenditure (EE) in healthy women. Design: 11 healthy weight women (18–40 years) were studied in a randomized crossover trial with two phases of 2 weeks each. In Phase 1, participants consumed either a regular meal pattern (6 meals/day) or an irregular meal pattern (varying from 3 to 9 meals/day). In Phase 2, participants followed the alternative meal pattern to that followed in Phase 1, after a 2-weeks washout period. In the two phases, identical foods were provided to a participant in amounts designed to keep body weight constant. Participants came to the laboratory after an overnight fast at the start and end of each phase. EE was measured in fasting state by indirect calorimetry. Postprandial EE was measured during the 3 h period after consumption of a milkshake, test drink. Results: There were no significant changes in body weight and anthropometric measurements after both meal pattern interventions. There was also no significant difference in mean daily energy intake between the regular and irregular meal pattern (2043 ±31 and 2099 ±33 respectively). EE in the fasting state showed no significant differences cross the experiment visits. There was a significant difference in Postprandial EE (measured for 3 h) by visit (P=0.04). Postprandial EE after the regular meal pattern was significantly higher than at baseline (P=0.002) or than after the irregular meal pattern (P= 0.04). Conclusion: Eating regularly for 14-day period significantly increases Postprandial EE which may contribute to weight loss and obesity management.Keywords: energy expenditure, energy intake, meal pattern, weight loss
Procedia PDF Downloads 4136834 Modelling Urban Rigidity and Elasticity Growth Boundaries: A Spatial Constraints-Suitability Based Perspective
Authors: Pengcheng Xiang Jr., Xueqing Sun, Dong Ngoduy
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In the context of rapid urbanization, urban sprawl has brought about extensive negative impacts on ecosystems and the environment, resulting in a gradual shift from "incremental growth" to ‘stock growth’ in cities. A detailed urban growth boundary is a prerequisite for urban renewal and management. This study takes Shenyang City, China, as the study area and evaluates the spatial distribution of urban spatial suitability in the study area from the perspective of spatial constraints-suitability using multi-source data and simulates the future rigid and elastic growth boundaries of the city in the study area using the CA-Markov model. The results show that (1) the suitable construction area and moderate construction area in the study area account for 8.76% and 19.01% of the total area, respectively, and the suitable construction area and moderate construction area show a trend of distribution from the urban centre to the periphery, mainly in Shenhe District, the southern part of Heping District, the western part of Dongling District, and the central part of Dadong District; (2) the area of expansion of construction land in the study area in the period of 2023-2030 is 153274.6977hm2, accounting for 44.39% of the total area of the study area; (3) the rigid boundary of the study area occupies an area of 153274.6977 hm2, accounting for 44.39% of the total area of the study area, and the elastic boundary of the study area contains an area of 75362.61 hm2, accounting for 21.69% of the total area of the study area. The study constructed a method for urban growth boundary delineation, which helps to apply remote sensing to guide future urban spatial growth management and urban renewal.Keywords: urban growth boundary, spatial constraints, spatial suitability, urban sprawl
Procedia PDF Downloads 326833 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures
Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara
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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.Keywords: IoT, fog computing, task offloading, efficient crow search algorithm
Procedia PDF Downloads 586832 Transnational Educators in Japan, Russia, and America: Historical Trends in Global Education in the 1990’s and Early 2000’s
Authors: Peter J. Glinos
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The Alternative Education Resource Organization (AERO), one of the largest international hubs for alternative educators led by Jerry Mintz, has had a major impact on the global alternative education movement. The organization’s publications, like the AERO-Gramme Newsletter and its successor, the Education Revolution Magazine, allowed members across the globe to discuss issues, share support, and submit writings on policies and reforms. Stored on AERO's online digital archive, this work uses these publications from 1989 to 2011 to investigate the network's entanglements with America, Canada, Russia, Ukraine, Israel, Palestine, Japan, India, and Guatemala. Inspired by Reinhart Koselleck, this historical analysis will trace AERO’s entanglements within the United States, Japan, and Russia, contextualizing each of these multiple temporalities within the history of each nation’s education system, the developments within AERO, and the global geo-political climate at the time of AERO’s expansion. To help remedy the lack of attention paid by global historians to the role state organizations play supporting global networks, as noted in What is Global History? by Sebastian Conrad, this work will focus on the relationship between AERO and state actors.Keywords: global history, history of education, neoliberalism, transnational history, alternative education
Procedia PDF Downloads 286831 Performance Analysis of Search Medical Imaging Service on Cloud Storage Using Decision Trees
Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel
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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine
Procedia PDF Downloads 2046830 Assessment of Bio-Control Quality of Ethanolic Extracts of Some Tropical Plants on Fruit Rot Pathogens of Pineapple Fruits in Ado Ekiti
Authors: J. Y. Ijato, A. Adewumi, H. O Yakubu, O. O. Olajide, B. O. Ojo, B. A. Adanikin
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Post-harvest fruit rot pathogens are one of the major factors that are responsible for food security challenges in developing countries like Nigeria. These pathogens also cause fruit food poisoning. Biocidal effects of ethanolic extracts of Khaya grandifoliola, Hyptis suaveolens, Zingiber officinale, Calophyllum inophyllum, Datura stramonium on the mycelia growth of fungal rot pathogens of pineapple fruit was investigated, the ethanolic extracts of these test plants exhibited high significant inhibitory effects on the rot pathogens, the highest ethanolic extract inhibition of Zingiber officinale was on Aspergillus flavus (38.40%) at 1.0g/ml while the least inhibitory effect was on Aspergillus fumigatus (23.10%) at 1.0g/ml, the highest ethanol extract inhibition of Datura stramonium was on Aspergillus tubingensis (24.00%) at 1.0g/ml while the least inhibitory effect was 10.00% on Colletotrichum fruticola at 1.0g/ml, the highest ethanol extract inhibition of Calophyllum inophyllum was on Trichoderma harzianum (18.50%) at 1.0g/ml while the least inhibitory effect was on Aspergillus flavus (15.00%) at 1.0g/ml, the highest ethanol extract inhibition of Hyptis suaveolens was on Aspergillus fumigatus (35.00%) at 1.0g/ml while the least inhibitory effect was on Aspergillus niger (20.00%) at 1.0g/ml, the highest ethanol extract inhibition of Khaya grandifoliola was on Aspergillus flavus (35.00%) at 1.00g/ml while the least inhibitory effect was on Aspergillus fumigates (22.00%) at 1.0g/ml, the antifungal capacity of these test plant extracts on rot causing fungi on pineapple fruit reveals the possibility of their use by farmers and fruit traders as alternative to chemical fungicide that portends great threat to human and environmental health.Keywords: fruit rot, pathogens, plant extracts, pineapple, food poisoning
Procedia PDF Downloads 1106829 The Role of Entrepreneurial Orientation in Strengthening Goat Farm Competitiveness in Banjarnegara District, Indonesia
Authors: Mochamad Sugiarto, Yusmi Nw
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Goat farming became an important alternative in eradicating poverty in Banjarnegara District. The success of goat farming in delivering products through efficient business management will improve business competitiveness. Entrepreneurship based farming has been able to survive in an ever-changing and increasingly complex global economy. Entrepreneurial farmers characterized by the ability to provide products of goats by applying the principles of efficient business. To achieve, this requires an understanding and a positive outlook related to entrepreneurship involving the values of courage to take risks, creativity and innovation as well as management's ability to find and read the opportunities. Entrepreneurial orientation owned by farmers is an important spirit of farmers to make decision for developing the goat farming. Entrepreneurial orientation is the view of farmers against the values of confidence, result-oriented, future-oriented, and creativity/innovation in goat farming. This study aims to (1) identify the entrepreneurial orientation of goat farmers in Banjarnegara District (2) analyze business competitiveness (cost efficiency) of goat farming in the Banjarnegara District and (3) analyze the relationship between the entrepreneurial perception and cost efficiency of goat farming in the Banjarnegara District. 178 respondents (goat farmers) were taken using stratified random sampling based on altitude. Banjarnegara district with heterogeneous topography grouped into areas of high ( > 1500m), moderate (500m-1000m) and low ( < 500m). The goat farmers in Banjarnegara District has a moderate entrepreneurial orientation. The manage their goat farming efficiently by having R/C = 2.58. Strengthening the entrepreneurial orientation will significantly increase the cost efficiency, which has an impact on strengthening the competitiveness of goat farming in Banjarnegara District.Keywords: entrepreneurial orientation, cost efficiency, farm competitiveness, goat farming
Procedia PDF Downloads 3086828 Measuring and Evaluating the Effectiveness of Mobile High Efficiency Particulate Air Filtering on Particulate Matter within the Road Traffic Network of a Sample of Non-Sparse and Sparse Urban Environments in the UK
Authors: Richard Maguire
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This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution
Procedia PDF Downloads 1246827 Review of the Legislative and Policy Issues in Promoting Infrastructure Development to Promote Automation in Telecom Industry
Authors: Marvin Ricardo Awarab
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There has never been a greater need for telecom services. The Internet of Things (IoT), 5G networking, and edge computing are the driving forces behind this increased demand. The fierce demand offers communications service providers significant income opportunities. The telecom sector is centered on automation, and realizing a digital operation that functions as a real-time business will be crucial for the industry as a whole. Automation in telecom refers to the application of technology to create a more effective, quick, and scalable alternative to the conventional method of operating the telecom industry. With the promotion of 5G and the Internet of Things (IoT), telecom companies will continue to invest extensively in telecom automation technology. Automation offers benefits in the telecom industry; developing countries such as Namibia may not fully tap into such benefits because of the lack of funds and infrastructural resources to invest in automation. This paper fully investigates the benefits of automation in the telecom industry. Furthermore, the paper identifies hiccups that developing countries such as Namibia face in their quest to fully introduce automation in the telecom industry. Additionally, the paper proposes possible avenues that Namibia, as a developing country, adopt investing in automation infrastructural resources with the aim of reaping the full benefits of automation in the telecom industry.Keywords: automation, development, internet, internet of things, network, telecom, telecommunications policy, 5G
Procedia PDF Downloads 636826 Advancing Dialysis Care Access and Health Information Management: A Blueprint for Nairobi Hospital
Authors: Kimberly Winnie Achieng Otieno
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The Nairobi Hospital plays a pivotal role in healthcare provision in East and Central Africa, yet it faces challenges in providing accessible dialysis care. This paper explores strategic interventions to enhance dialysis care, improve access and streamline health information management, with an aim of fostering an integrated and patient-centered healthcare system in our region. Challenges at The Nairobi Hospital The Nairobi Hospital currently grapples with insufficient dialysis machines which results in extended turn around times. This issue stems from both staffing bottle necks and infrastructural limitations given our growing demand for renal care services. Our Paper-based record keeping system and fragmented flow of information downstream hinders the hospital’s ability to manage health data effectively. There is also a need for investment in expanding The Nairobi Hospital dialysis facilities to far reaching communities. Setting up satellite clinics that are closer to people who live in areas far from the main hospital will ensure better access to underserved areas. Community Outreach and Education Implementing education programs on kidney health within local communities is vital for early detection and prevention. Collaborating with local leaders and organizations can establish a proactive approach to renal health hence reducing the demand for acute dialysis interventions. We can amplify this effort by expanding The Nairobi Hospital’s corporate social responsibility outreach program with weekend engagement activities such as walks, awareness classes and fund drives. Enhancing Efficiency in Dialysis Care Demand for dialysis services continues to rise due to an aging Kenyan population and the increasing prevalence of chronic kidney disease (CKD). Present at this years International Nursing Conference are a diverse group of caregivers from around the world who can share with us their process optimization strategies, patient engagement techniques and resource utilization efficiencies to catapult The Nairobi Hospital to the 21st century and beyond. Plans are underway to offer ongoing education opportunities to keep staff updated on best practices and emerging technologies in addition to utilizing a patient feedback mechanisms to identify areas for improvement and enhance satisfaction. Staff empowerment and suggestion boxes address The Nairobi Hospital’s organizational challenges. Current financial constraints may limit a leapfrog in technology integration such as the acquisition of new dialysis machines and an investment in predictive analytics to forecast patient needs and optimize resource allocation. Streamlining Health Information Management Fully embracing a shift to 100% Electronic Health Records (EHRs) is a transformative step toward efficient health information management. Shared information promotes a holistic understanding of patients’ medical history, minimizing redundancies and enhancing overall care quality. To manage the transition to community-based care and EHRs effectively, a phased implementation approach is recommended. Conclusion By strategically enhancing dialysis care access and streamlining health information management, The Nairobi Hospital can strengthen its position as a leading healthcare institution in both East and Central Africa. This comprehensive approach aligns with the hospital’s commitment to providing high-quality, accessible, and patient-centered care in an evolving landscape of healthcare delivery.Keywords: Africa, urology, diaylsis, healthcare
Procedia PDF Downloads 586825 A Modeling Approach for Blockchain-Oriented Information Systems Design
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The blockchain technology is regarded as the most promising technology that has the potential to trigger a technological revolution. However, besides the bitcoin industry, we have not yet seen a large-scale application of blockchain in those domains that are supposed to be impacted, such as supply chain, financial network, and intelligent manufacturing. The reasons not only lie in the difficulties of blockchain implementation, but are also root in the challenges of blockchain-oriented information systems design. As the blockchain members are self-interest actors that belong to organizations with different existing information systems. As they expect different information inputs and outputs of the blockchain application, a common language protocol is needed to facilitate communications between blockchain members. Second, considering the decentralization of blockchain organization, there is not any central authority to organize and coordinate the business processes. Thus, the information systems built on blockchain should support more adaptive business process. This paper aims to address these difficulties by providing a modeling approach for blockchain-oriented information systems design. We will investigate the information structure of distributed-ledger data with conceptual modeling techniques and ontology theories, and build an effective ontology mapping method for the inter-organization information flow and blockchain information records. Further, we will study the distributed-ledger-ontology based business process modeling to support adaptive enterprise on blockchain.Keywords: blockchain, ontology, information systems modeling, business process
Procedia PDF Downloads 4496824 Effect on Physicochemical and Sensory Attributes of Bread Substituted with Different Levels of Matured Soursop (Anona muricata) Flour
Authors: Mardiana Ahamad Zabidi, Akmalluddin Md. Yunus
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Soursop (Anona muricata) is one of the underutilized tropical fruits containing nutrients, particularly dietary fibre and antioxidant properties that are beneficial to human health. This objective of this study is to investigate the feasibility of matured soursop pulp flour (SPF) to be substituted with high-protein wheat flour in bread. Bread formulation was substituted with different levels of SPF (0%, 5%, 10% and 15%). The effect on physicochemical properties and sensory attributes were evaluated. Higher substitution level of SPF resulted in significantly higher (p<0.05) fibre, protein and ash content, while fat and carbohydrate content reduced significantly (p<0.05). FESEM showed that the bread crumb surface of control and 5% SPF appeared to distribute evenly and coalesced by thin gluten film. However, higher SPF substitution level in bread formulation exhibited a deleterious effect by formation of discontinuous gluten network. For texture profile analysis, 5% SPF bread resulted in the lowest value of hardness. The score of sensory evaluation showed that 5% SPF bread received good acceptability and is comparable with control bread.Keywords: soursop pulp flour, bread, physicochemical properties, sensory attributes, scanning electron microscopy (SEM)
Procedia PDF Downloads 3226823 An Explanatory Study Approach Using Artificial Intelligence to Forecast Solar Energy Outcome
Authors: Agada N. Ihuoma, Nagata Yasunori
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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.Keywords: artificial Intelligence, backward elimination, linear regression, solar energy
Procedia PDF Downloads 157