Search results for: geometric search algorithm

Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

Procedia PDF Downloads 143

Authors: Gusa Hall, Barrie Keeler, Achal Khanna

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Introduction: NICE guidelines have highlighted the consequences of IV fluid mismanagement. The main aim of this study was to audit fluid prescribing post laparotomies to identify if fluids were prescribed in accordance to NICE guidelines. Methodology: Retrospective database search of eight specific laparotomy procedures (colectomy right and left, Hartmann’s procedure, small bowel resection, perforated ulcer, abdominal perineal resection, anterior resection, pan proctocolectomy, subtotal colectomy) highlighted 29 laparotomies between April 2019 and May 2019. Two of 29 patients had secondary procedures during the same admission, n=27 (patients). Database case notes were reviewed for date of procedure, length of admission, fluid prescribed and amount, nasal gastric tube output, daily bloods results for electrolytes sodium and potassium and operational losses. Results: n=27 based on 27 identified patients between April 2019 – May 2019, 93% (25/27) received IV fluids, only 19% (5/27) received the correct IV fluids in accordance to NICE guidelines, 93% (25/27) who received IV fluids had the correct electrolytes levels (sodium & potassium), 100% (27/27) patients received blood tests (U&E’s) for correct electrolytes levels. 0% (0/27) no documentation on operational losses. IV fluids matched nasogastric tube output in 100% (3/3) of the number of patients that had a nasogastric tube in situ. Conclusion: A PubMed database literature review on barriers to safer IV prescribing highlighted educational interventions focused on prescriber knowledge rather than how to execute the prescribing task. This audit suggests IV fluids post laparotomies are not being prescribed consistently in accordance to NICE guidelines. Surgical management plans should be clearer on IV fluids and electrolytes requirements for the following 24 hours after the plan has been initiated. In addition, further teaching and training around IV prescribing is needed together with frequent surgical audits on IV fluid prescribing post-surgery to evaluate improvements.

Keywords: audit, IV Fluid prescribing, laparotomy, NICE guidelines

Procedia PDF Downloads 112

Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 190

Authors: Sodamade A., Bolaji K. A.

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Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that could serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of the plant (Vaccinium pavifolium) was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education Campus, Oyo. The sample was authenticated at the Forestry Research Institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition, mineral analysis phytochemical and antimicrobial properties were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive. The mineral analysis of the sample showed; Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g, Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g Cadmium and Mercury were not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, Steroids, Terpenoids, Cardiac glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Vaccinium parvifolium L. leaf protein concentrates showed that it contains bioactive compounds that are capable of combating the following microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisialae pneumonia and Proteus mirabilis. The results of the analysis of Vaccinium parvifolium L. leaf protein concentrates showed that the sample contains valuable nutrient and mineral constituents, and phytochemical compounds that could make the sample useful for medicinal activities.

Keywords: leaf protein concentrates, vaccinium parvifolium, nutritional characteristics, mineral composition, antimicrobial activity

Procedia PDF Downloads 69

Authors: Alime Cengiz, Talip Kahyaoglu

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Roasting process has the major importance to obtain desired aromatic taste of nuts. In this study, two kinds of roasting process were applied to hulled sesame seeds - vacuum oven and hot air roasting. Efficiency of Gene Expression Programming (GEP), a new soft computing technique of evolutionary algorithm that describes the cause and effect relationships in the data modelling system, and response surface methodology (RSM) were examined in the modelling of roasting processes over a range of temperature (120-180°C) for various times (30-60 min). Color attributes (L*, a*, b*, Browning Index (BI)), textural properties (hardness and fracturability) and moisture content were evaluated and modelled by RSM and GEP. The GEP-based formulations and RSM approach were compared with experimental results and evaluated according to correlation coefficients. The results showed that both GEP and RSM were found to be able to adequately learn the relation between roasting conditions and physical and textural parameters of roasted seeds. However, GEP had better prediction performance than the RSM with the high correlation coefficients (R2 >0.92) for the all quality parameters. This result indicates that the soft computing techniques have better capability for describing the physical changes occuring in sesame seeds during roasting process.

Keywords: genetic expression programming, response surface methodology, roasting, sesame seed

Procedia PDF Downloads 413

Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

Procedia PDF Downloads 492

Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

Procedia PDF Downloads 443

Authors: Maryam Kalkatechi

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The paper presents the construction unit that was proposed as a result of researching and finding solutions for challenges of the traditional masonry unit. The concept of ‘unit as arrangements of cells’ was investigated in four categories of structure, handling and assembly, thermal characteristics and weather ability which resulted in construction unit as an independent system which shapes a part of the envelope. Comparing to the traditional wall systems in which the system is in layers, the part system is a monolithic piece by itself. Even though the overall wythe-10 inches- is less than the combined layers-14 inches- in a traditional wall system, it is still seen as a spatial component. The component as a furnishing of envelope is discussed from material application point of view. The algorithm definition of the arrangement cells crafts the relationship between cells and functionality with material. This craft is realized as the envelope furnishing. Three alternative materials in relation to furnishing the envelope are discussed for printing the construction unit; transparent plastic, opaque plastic and glass. The qualities vary in the four categories, however this paper focuses on the visual qualities of materials applied. In a diagram the qualities of the materials are compared in relation to each other.

Keywords: furnishing envelope, 3D printed construction unit, opaque plastic, transparent plastic, glass

Procedia PDF Downloads 172

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

Procedia PDF Downloads 347

Authors: Rideci Farias, Haroldo Paranhos, Joyce Silva, Elson Almeida, Hellen Silva, Lucas Silva

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The constant growth of the fleet of vehicles in the big cities, makes that the Engineering is dynamic, with respect to the new solutions for traffic flow in general. In the Federal District (DF), Brazil, it is no different. The city of Brasilia, Capital of Brazil, and Cultural Heritage of Humanity by UNESCO, is projected to 500 thousand inhabitants, and today circulates more than 3 million people in the city, and with a fleet of more than one vehicle for every two inhabitants. The growth of the city to the North region, made that the urban planning presented solutions for the fleet in constant growth. In this context, a complex of viaducts, road accesses, creation of new rolling roads and duplication of the Bragueto bridge over Paranoa lake in the northern part of the city was designed, giving access to the BR-020 highway, denominated Clover of North Triage (TTN). In the geopedological context, the region is composed of hydromorphic soils, with the presence of the water level at some times of the year. From the geotechnical point of view, are soils with SPT < 4 and Resistance not drained, Su < 50 kPa. According to urban planning in Brasília, special art works can not rise in the urban landscape, contrasting with the urban characteristics of the architects Lúcio Costa and Oscar Niemeyer. Architects hired to design the new Capital of Brazil. The urban criterion then created the technical impasse, resulting in the technical need to ‘bury’ the works of art and in turn the access greenhouses at different levels, in regions of low support soil and water level Outcrossing, generally inducing the need for this study and design. For the adoption of the appropriate solution, Standard Penetration Test (SPT), Vane Test, Diagnostic peritoneal lavage (DPL) and auger boring campaigns were carried out. With the comparison of the results of these tests, the profiles of resistance of the soils and water levels were created in the studied sections. Geometric factors such as existing sidewalks and lack of elevation for the discharge of deep drainage water have inhibited traditional techniques for total removal of soft soils, thus avoiding the use of temporary drawdown and shoring of excavations. Thus, a structural layer was designed to reinforce the subgrade by means of the ‘needling’ of the soft soil, without the need for longitudinal drains. In this context, the article presents the geological and geotechnical studies carried out, but also the dimensioning of the reinforcement layer on the soft soil with a view to the main objective of this solution that is to allow the execution of the civil works without the interference in the roads in use, Execution of services in rainy periods, presentation of solution compatible with drainage characteristics and soft soil reinforcement.

Keywords: layer, reinforcement, soft soil, clover of north triage

Procedia PDF Downloads 222

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 382

Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

Procedia PDF Downloads 387

Authors: Mohammad Pourmohammadi Fallah, Maziar Salahi

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In the literature, a mixed-integer linear programming model for the integrated production planning and warehouse layout problem is proposed. To solve the model, the authors proposed a Lagrangian relax-and-fix heuristic that takes a significant amount of time to stop with gaps above 5$\%$ for large-scale instances. Here, we present two heuristic algorithms to solve the problem. In the first one, we use a greedy approach by allocating warehouse locations with less reservation costs and also less transportation costs from the production area to locations and from locations to the output point to items with higher demands. Then a smaller model is solved. In the second heuristic, first, we sort items in descending order according to the fraction of the sum of the demands for that item in the time horizon plus the maximum demand for that item in the time horizon and the sum of all its demands in the time horizon. Then we categorize the sorted items into groups of 3, 4, or 5 and solve a small-scale optimization problem for each group, hoping to improve the solution of the first heuristic. Our preliminary numerical results show the effectiveness of the proposed heuristics.

Keywords: capacitated lot-sizing, warehouse layout, mixed-integer linear programming, heuristics algorithm

Procedia PDF Downloads 190

Authors: Mahmoud Nadir, Adel Ghenaiet

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The main purpose of this study is the thermodynamic modeling, the parametric analysis, and the optimization of three pressure level reheat HRSG (Heat Recovery Steam Generator) using PSO method (Particle Swarm Optimization). In this paper, a parametric analysis followed by a thermodynamic optimization is presented. The chosen objective function is the specific work of the steam cycle that may be, in the case of combined cycle (CC), a good criterion of thermodynamic performance analysis, contrary to the conventional steam turbines in which the thermal efficiency could be also an important criterion. The technologic constraints such as maximal steam cycle temperature, minimal steam fraction at steam turbine outlet, maximal steam pressure, minimal stack temperature, minimal pinch point, and maximal superheater effectiveness are also considered. The parametric analyses permitted to understand the effect of design parameters and the constraints on steam cycle specific work variation. PSO algorithm was used successfully in HRSG optimization, knowing that the achieved results are in accordance with those of the previous studies in which genetic algorithms were used. Moreover, this method is easy to implement comparing with the other methods.

Keywords: combined cycle, HRSG thermodynamic modeling, optimization, PSO, steam cycle specific work

Procedia PDF Downloads 376

Authors: Inaam Khalaf, Nadin M. Abdel Razeq, Hamza Alduraidi, Suhaila Halasa, Omayyah S. Nassar, Eman Al-Horani, Jumana Shehadeh, Anna Talal

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Background: Nursing researchers are responsible for generating knowledge that corresponds to national and global research priorities in order to promote, restore, and maintain the health of individuals and societies. The objectives of this scoping review of Jordanian literature are to assess the existing research on pediatric nursing in terms of evolution, authorship and collaborations, funding sources, methodologies, topics of research, and pediatric subjects' age groups so as to identify gaps in research. Methodology: A search was conducted using related keywords obtained from national and international databases. The reviewed literature included pediatric health articles published through December 2019 in English and Arabic, authored by nursing researchers. The investigators assessed the retrieved studies and extracted data using a data-mining checklist. Results: The review included 265 articles authored by Jordanian nursing researchers concerning children's health, published between 1987 and 2019; 95% were published between 2009 and 2019. The most commonly applied research methodology was the descriptive non-experimental method (76%). The main generic topics were health promotion and disease prevention (23%), chronic physical conditions (19%), mental health, behavioral disorders, and forensic issues (16%). Conclusion: The review findings identified a grave shortage of evidence concerning nursing care issues for children below five years of age, especially those between ages two and five years. The research priorities identified in this review resonate with those identified in international reports. Implications: Nursing researchers are encouraged to conduct more research targeting topics of national-level importance in collaboration with clinically involved nurses and international scholars.

Keywords: Jordan, scoping review, children health nursing, pediatric, adolescents

Procedia PDF Downloads 78

Authors: S. K. Ghosh, C. Srivastava, P. K. Limaye, V. Kain

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Electroplated hard chromium is widely known in coatings and surface finishing, automobile and aerospace industries because of its excellent hardness, wear resistance and corrosion properties. However, its precursor, Cr+6 is highly carcinogenic in nature and a consensus has been adopted internationally to eradicate this coating technology with an alternative one. The search for alternate coatings to electroplated hard chrome is continuing worldwide. Various alloys and nanocomposites like Co-W alloys, Ni-Graphene, Ni-diamond nanocomposites etc. have already shown promising results in this regard. Basically, in this study, electroless Ni-P alloys with excellent corrosion resistance was taken as the base matrix and incorporation of tungsten as third alloying element was considered to improve the hardness and wear resistance of the resultant alloy coating. The present work is focused on the preparation of Ni–W–P coatings by electrodeposition with different content of phosphorous and its effect on the electrochemical, mechanical and tribological performances. The results were also compared with Ni-W alloys. Composition analysis by EDS showed deposition of Ni-32.85 wt% W-3.84 wt% P (designated as Ni-W-LP) and Ni-18.55 wt% W-8.73 wt% P (designated as Ni-W-HP) alloy coatings from electrolytes containing of 0.006 and 0.01M sodium hypophosphite respectively. Inhibition of tungsten deposition in the presence of phosphorous was noted. SEM investigation showed cauliflower like growth along with few microcracks. The as-deposited Ni-W-P alloy coating was amorphous in nature as confirmed by XRD investigation and step-wise crystallization was noticed upon annealing at higher temperatures. For all the coatings, the nanohardness was found to increase after heat-treatment and typical nanonahardness values obtained for 400°C annealed samples were 18.65±0.20 GPa, 20.03±0.25 GPa, and 19.17±0.25 for alloy coatings Ni-W, Ni-W-LP and Ni-W-HP respectively. Therefore, the nanohardness data show very promising results. Wear and coefficient of friction data were recorded by applying a different normal load in reciprocating motion using a ball on plate geometry. Post experiment, the wear mechanism was established by detail investigation of wear-scar morphology. Potentiodynamic measurements showed coating with a high content of phosphorous was most corrosion resistant in 3.5wt% NaCl solution.

Keywords: corrosion, electrodeposition, nanohardness, Ni-W-P alloy coating

Procedia PDF Downloads 345

Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

Procedia PDF Downloads 284

Authors: Dawit Gebreegzabher Hagos, Yazezew Kebede Kiro, Mahmud Abdulkader, Henk H. D. F. Schallig, Dawit Wolday

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Rapid and accurate visceral leishmaniasis (VL) diagnosis is needed to initiate prompt treatment to reduce morbidity and mortality. Here, we evaluated the performance of loop-mediated isothermal amplification (LAMP) assay for the diagnosis of VL from blood in an endemic area in Ethiopia. LAMP was positive in 117/122 confirmed VL cases and negative in 149/152 controls, resulting in a sensitivity of 95.9% (95% CI: 90.69–98.66) and a specificity of 98.0% (95% CI: 94.34–99.59), respectively. The sensitivity of the LAMP assay was 95.0% (95% CI: 88.61–98.34) in HIV-negatives and 100% (95% CI: 85.18–100.0) in HIV-positives. Compared with microscopy, LAMP detected 82/87 (94.3%, 95% CI: 87.10–98.11) of the microscopy1 cases and was negative in 11/27 (40.7%, 95% CI: 22.39–61.20) of the microscopy2 cases. Compared with the rK39 serology, LAMP detected 113/120 (94.2%, 95% CI: 88.35–97.62) of the rK391 cases and was negative in 149/154 (96.8%, 95% CI: 92.59–98.94) of the rK392 cases. However, when compared with microscopy only, rK39 detected 83/87 (95.4%, 95% CI: 88.64–98.73) of the microscopy1 cases and negative in only 12/27 (44.4%, 95% CI: 25.48–64.67) of the microscopy– cases. There was an excellent agreement between rK39 and LAMP (Kappa 5 0.91, 95% CI: 0.86–0.96). Furthermore, an algorithm using rK39 followed by LAMP would yield a sensitivity of 99.2% (95%CI: 95.52–99.89) and a specificity of 98.0% (95% CI: 94.34–99.59). The findings demonstrate that the LAMP assay is an accurate and rapid molecular assay for VL diagnosis, including in HIV-1 co-infected patients, in an endemic setting.

Keywords: visceral leishmaniasis, HIV, diagnosis, LAMP, Ethiopia

Procedia PDF Downloads 87

Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

Procedia PDF Downloads 516

Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

Procedia PDF Downloads 452

Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: brain-machine interface, decision-making, mobile robot, neural network

Procedia PDF Downloads 291

Authors: Mohammad Obeidat, Ayman Mansour

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In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.

Keywords: atrial fibrillation, communication channels, closed loop, estimation

Procedia PDF Downloads 373

Authors: Adrianna D. Hendricks

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This paper examines the factors that contribute to the re-traumatization of victims of sex trafficking within the Canadian context. Sex trafficking occurring domestically in Canada is severely under-researched, stigmatized, and under-prosecuted, leading to the re-traumatization of victims by various levels of government. This is in part due to the Canadian criminal justice system unethically utilizing prostitution laws in cases of sex trafficking and partially due to the unaddressed stigmatization victims face within the justice system itself. Utilizing evidence from a current literature review, personal correspondence, and personal life experiences, this paper will demonstrate the need for victim involvement in policy reform. The current literature review was done through an academic database search using the terms: “Sex Trafficking, Exploitation, Canada”, with the limitation of articles written within the last five years and written within the Canadian context. Overall, from the results, only eight articles precisely matched the criteria. The current literature argues strongly and unanimously for more research and education of professionals who have close contact with high-risk populations (doctors, police officers, social workers, etc.) to protect both minors and adults from being sexually trafficked. Additionally, for women and girls who do not have Canadian citizenship, the fear of deportation becomes a barrier to disclosing exploitation experiences to professionals. There is a desperate need for more research done in tandem with survivors and victims to inform policymaking in a meaningful way. The researcher is a survivor of sex trafficking both as a youth and as an adult, giving the researcher a unique insight into the realities of the criminal justice system for victims of sex trafficking. Congruent to the current research, the author calls for standardized professional training for people in healthcare, police officers, court officials, and victim services, with the additional layer of victim involvement. Justice for victims/survivors can only be obtained if they have been consulted and believed. Without meaningful consultation with survivors, victims who are both minors and adults will continue to fall through the cracks in policy.

Keywords: Canadian policy, re-traumatization, sex-trafficking, stigmatization

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

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High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch

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Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: Soumaya Mrabet, Taieb Ach, Imen Akkari, Amira Atig, Neirouz Ghannouchi, Koussay Ach, Elhem Ben Jazia

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Introduction: Celiac disease (CD) is an immune-mediated small intestinal disorder that occurs in genetically susceptible people. It is significantly associated with other autoimmune disorders represented mainly by type 1 diabetes and autoimmune dysthyroidism. The aim of our study is to determine the prevalence and the type of the various autoimmune diseases associated with CD in adult patients. Material and methods: This is a retrospective study including patients diagnosed with CD, explored in Internal Medicine, Gastroenterology and Endocrinology and Diabetology Departments of the Farhat Hached University Hospital, between January 2005 and January 2016. The diagnosis of CD was confirmed by serological tests and duodenal biopsy. The screening of autoimmune diseases was based on physical examination, biological and serological tests. Results: Sixty five patients with a female predominance were included, 48women (73.8%) and 17 men (26.2%). The mean age was 31.8 years (17-75). A family history of CD or other autoimmune diseases was present in 5 and 10 patients respectively. Clinical presentation of CD was made by recurrent abdominal pain in 49 cases, diarrhea in 29 cases, bloating in 17 cases, constipation in 25 cases and vomiting in 8 cases. Autoimmune diseases associated with CD were found in 30 cases (46.1%): type 1 diabetes in 15 patients attested by the positivity of anti-GAD antibodies in 11 cases and anti-IA2 in 4 cases, Hashimoto thyroiditis in 8 cases confirmed by the positivity of anti-TPO antibodies, Addison's disease in 2 patients, Anemia of Biermer in 2 patients, autoimmune hepatitis, Systemic erythematosus lupus, Gougerot Sjögren syndrome, rheumatoid arthritis, Vitiligo and antiphospholipid syndrome in one patient each. CD was associated with more than one autoimmune disease defining multiple autoimmune syndrome in 2 female patients. The first patient had Basedow disease, Addison disease and type 1 diabetes. The second patient had systemic erythematosus lupus and Gougerot Sjögren syndrome. Conclusion: In our study autoimmune diseases were associated with CD in 46.1% of cases and were dominated by diabetes and dysthroidism. After establishing the diagnosis of CD the search of associated autoimmune diseases is necessary in order to avoid any therapeutic delay which can alter the prognosis of the patient.

Keywords: association, autoimmune thyroiditis, celiac disease, diabetes

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Authors: Shi-Yu Xu

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The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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Authors: Christos Konstantopoulos, Thomas Ussmueller

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Digital low drop-out regulators, in contrast to analog counterparts, provide an architecture of sub-1 V regulation with low power consumption, high power efficiency, and system integration. Towards an optimized integration in the ultra-low-power system-on-chip Internet of Things architecture that is operated through a radio frequency energy harvesting scheme, the D-LDO regulator should constitute the main regulator that operates the master-clock and rest loads of the SoC. In this context, we present a D-LDO with linear search coarse regulation and asynchronous fine regulation, which incorporates an in-regulator clock generation unit that provides an autonomous, self-start-up, and power-efficient D-LDO design. In contrast to contemporary D-LDO designs that employ ring-oscillator architecture which start-up time is dependent on the frequency, this work presents a fast start-up burst oscillator based on a high-gain stage with wake-up time independent of coarse regulation frequency. The design is implemented in a 55-nm Global Foundries CMOS process. With the purpose to validate the self-start-up capability of the presented D-LDO in the presence of ultra-low input power, an on-chip test-bench with an RF rectifier is implemented as well, which provides the RF to DC operation and feeds the D-LDO. Power efficiency and load regulation curves of the D-LDO are presented as extracted from the RF to regulated DC operation. The D-LDO regulator presents 83.6 % power efficiency during the RF to DC operation with a 3.65 uA load current and voltage regulator referred input power of -27 dBm. It succeeds 486 nA maximum quiescent current with CL 75 pF, the maximum current efficiency of 99.2%, and 1.16x power efficiency improvement compared to analog voltage regulator counterpart oriented to SoC IoT loads. Complementary, the transient performance of the D-LDO is evaluated under the transient droop test, and the achieved figure-of-merit is compared with state-of-art implementations.

Keywords: D-LDO, Internet of Things, RF energy harvesting, voltage regulators

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Authors: Muhammad Awais Kiani, Maryam Kiani

Abstract:

This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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