Search results for: wireless mesh network (WMN)

Authors: Yanchun Zuo, Yingao Liu, Wei Liu, Le Yu, Run Huang, Lixin Guo

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Electric field detection is important in many application scenarios. The traditional strategy is measuring the electric field with a man walking around in the area under test. This strategy cannot provide a satisfactory measurement accuracy. To solve the mentioned problem, an autopilot measurement system is divided. A mini-car is produced, which can travel in the area under test according to respect to the program within the CPU. The electric field measurement platform (EFMP) carries a central computer, two horn antennas, and a vector network analyzer. The mini-car stop at the sampling points according to the preset. When the car stops, the EFMP probes the electric field and stores data on the hard disk. After all the sampling points are traversed, an electric field map can be plotted. The proposed system can give an accurate field distribution description of the chamber.

Keywords: autopilot mini-car measurement system, electric field detection, field map, static zone measurement

Procedia PDF Downloads 104

Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

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The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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Authors: Asem Alhnity, Nicholas Pickett

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The leisure home industry is experiencing an increase in sales due to the rise in popularity of staycations. However, there is also a demand for improvements in thermal and structural behaviour from customers. Existing standards and codes of practice outline the requirements for leisure home design. However, there is a lack of expertise in applying Finite Element Analysis (FEA) to complex structures in this industry. As a result, manufacturers rely on standardized design approaches, which often lead to excessively engineered or inadequately designed products. This study aims to address this issue by investigating the impact of the habitation structure on chassis performance in leisure homes. The aim of this research is to comprehensively analyse the impact of the habitation structure on chassis performance in leisure homes. By employing FEA on the entire unit, including both the habitation structure and the chassis, this study seeks to develop a novel framework for designing and analysing leisure homes. The objectives include material reduction, enhancing structural stability, resolving existing design issues, and developing innovative modular and wooden chassis designs. The methodology used in this research is quantitative in nature. The study utilizes FEA to analyse the performance of leisure home chassis under various loads. The analysis procedures involve running the FEA simulations on the numerical model of the leisure home chassis. Different load scenarios are applied to assess the stress and deflection performance of the chassis under various conditions. FEA is a numerical method that allows for accurate analysis of complex systems. The research utilizes flexible mesh sizing to calculate small deflections around doors and windows, with large meshes used for macro deflections. This approach aims to minimize run-time while providing meaningful stresses and deflections. Moreover, it aims to investigate the limitations and drawbacks of the popular approach of applying FEA only to the chassis and replacing the habitation structure with a distributed load. The findings of this study indicate that the popular approach of applying FEA only to the chassis and replacing the habitation structure with a distributed load overlooks the strengthening generated from the habitation structure. By employing FEA on the entire unit, it is possible to optimize stress and deflection performance while achieving material reduction and enhanced structural stability. The study also introduces innovative modular and wooden chassis designs, which show promising weight reduction compared to the existing heavily fabricated lattice chassis. In conclusion, this research provides valuable insights into the impact of the habitation structure on chassis performance in leisure homes. By employing FEA on the entire unit, the study demonstrates the importance of considering the strengthening generated from the habitation structure in chassis design. The research findings contribute to advancements in material reduction, structural stability, and overall performance optimization. The novel framework developed in this study promotes sustainability, cost-efficiency, and innovation in leisure home design.

Keywords: static homes, caravans, motor homes, holiday homes, finite element analysis (FEA)

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Authors: Arturo Galvan, Jatziri Y. Moreno-Martinez, Daniel Arroyo-Montoya, Jose M. Gutierrez-Villalobos

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Bridges are one of the most seismically vulnerable structures on highway transportation systems. The general process for assessing the seismic vulnerability of a bridge involves the evaluation of its overall capacity and demand. One of the most common procedures to obtain this capacity is by means of pushover analysis of the structure. Typically, the bridge capacity is assessed using non-linear static methods or non-linear dynamic analyses. The non-linear dynamic approaches use step by step numerical solutions for assessing the capacity with the consuming computer time inconvenience. In this study, a nonlinear static analysis (‘pushover analysis’) was performed to predict the collapse mechanism of a typical bridge built in the central zone of Mexico (Celaya, Guanajuato). The bridge superstructure consists of three simple supported spans with a total length of 76 m: 22 m of the length of extreme spans and 32 m of length of the central span. The deck width is of 14 m and the concrete slab depth is of 18 cm. The bridge is built by means of frames of five piers with hollow box-shaped sections. The dimensions of these piers are 7.05 m height and 1.20 m diameter. The numerical model was created using a commercial software considering linear and non-linear elements. In all cases, the piers were represented by frame type elements with geometrical properties obtained from the structural project and construction drawings of the bridge. The deck was modeled with a mesh of rectangular thin shell (plate bending and stretching) finite elements. The moment-curvature analysis was performed for the sections of the piers of the bridge considering in each pier the effect of confined concrete and its reinforcing steel. In this way, plastic hinges were defined on the base of the piers to carry out the pushover analysis. In addition, time history analyses were performed using 19 accelerograms of real earthquakes that have been registered in Guanajuato. In this way, the displacements produced by the bridge were determined. Finally, pushover analysis was applied through the control of displacements in the piers to obtain the overall capacity of the bridge before the failure occurs. It was concluded that the lateral deformation of the piers due to a critical earthquake occurred in this zone is almost imperceptible due to the geometry and reinforcement demanded by the current design standards and compared to its displacement capacity, they were excessive. According to the analysis, it was found that the frames built with five piers increase the rigidity in the transverse direction of the bridge. Hence it is proposed to reduce these frames of five piers to three piers, maintaining the same geometrical characteristics and the same reinforcement in each pier. Also, the mechanical properties of materials (concrete and reinforcing steel) were maintained. Once a pushover analysis was performed considering this configuration, it was concluded that the bridge would continue having a “correct” seismic behavior, at least for the 19 accelerograms considered in this study. In this way, costs in material, construction, time and labor would be reduced in this study case.

Keywords: collapse mechanism, moment-curvature analysis, overall capacity, push-over analysis

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Authors: Melikhaya Skhephe, Robert Mawuli Kwasi Boadzo, Zanoxolo Berington Gobingca

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This research study sought to examine parental monitoring of learners’ cell phone use in the Eastern Cape, South Africa. To this end, the researchers employed a quantitative approach. Data were obtained through questionnaires, with a sample of 15 parents having been purposively selected. The findings revealed that parents are unaware that they have to monitor the learner’s cell phone. Another finding was that parents in the 21-century did not support the use of mobile phones in education. The researchers recommend that parent’s discussion forums be created to educate parents on how a cell phone can be used in education. Cellphone companies need to be encouraged to educate parents on how they monitor cell phones used by learners. Another recommendation was that network providers need to restrict access to searching on the internet according to age.

Keywords: parental monitoring, app blocking services, learner’s cell phone use, cell phone

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: Ismael Ávila, José Reynaldo F. Filho, Vasco Varanda Picchi

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The ever-growing consumer awareness of food provenance in Brazil is driving the creation of a trusted ecosystem around the animal protein supply chain. The traceability and accountability requirements of such an ecosystem demand a blockchain layer to strengthen the weak links in that chain. For that, direct involvement of the companies in the blockchain transactions, including as validator nodes of the network, implies formalizing a partnership with the consortium behind the ecosystem. Yet, their compliance standards usually require that a formal governance structure is in place before they agree with any membership terms. In light of such a strategic role of blockchain governance, the paper discusses a framework for tailoring a governance model for a blockchain-based solution aimed at the meat supply chain and evaluates principles and attributes in terms of their relevance to the development of a robust trust ecosystem.

Keywords: blockchain, governance, trust ecosystem, supply chain, traceability

Procedia PDF Downloads 123

Authors: J. Waita, S. Wamuhu, J. Makoyo, M. Rachel, T. Ngangari, W. Christine, M. Zipporah

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Contraceptive use is one of the key global strategies to alleviate maternal mortality. Global efforts through advocating for contraceptive uptake and service provision has led improved contraceptive prevalence. In Kenya maternal mortality rate has remained a challenged despites efforts by government and non-governmental organizations. Objective: To describe the uptake of contraceptives among women in Tunza Clinics, Kenya. Design and Methods: Ps Kenya through health care marketing fund is implementing a family planning program among its 350 Tunza fractional franchise facilities. Through private partnership, private owned facilities in low socio-economic areas are recruited and trained on contraceptive technology update. The providers are supported through facilitative supervision through a mobile based application Health Network Quality Improvement System (HNQIS) and interpersonal communication through 150 community based volunteers. The data analyzed in this paper was collected between January to July 2017 to show the uptake of modern Contraceptives among women in the Tunza franchise, method mix, age and distribution among the age bracket. Further analysis compares two different service delivery strategies; outreach and walk ins. Supportive supervision HNQIS scores was analyzed. Results: During the time period, a total of 132121 family planning clients were attended in 350 facilities. The average age of clients was 29.6 years. The average number of clients attended in the facilities per month was 18874. 73.7 %( n=132121) of the clients attended in the Tunza facilities were aged above 25 years while 22.1% 20-24 years and 4.2% 15-19 years. On contraceptive method mix, intra uterine device insertions clients contributed to 7.5%, implant insertions 15.3%, pills 11.2%, injections 62.7% while condoms and emergency pills had 2.7% and 0.6% respectively. Analysis of service delivery strategy indicated more than 79% of the clients were walk ins while 21% were attended to during outreaches. Uptake of long term contraceptive methods during outreaches was 73% of the clients while short term modern methods were 27%. Health Network Quality Improvement system assessment scores indicated 51% of the facilities scored over 90%, 25% scoring 80-89% while 21% scored below 80%. Conclusion: Preference for short term methods by women is possibly associated to cost as they are cheaper and easy to administer. When the cost of intra uterine device Implants is meant affordable during outreaches, the uptake is observed to increase. Making intra uterine device and implants affordable to women is a key strategy in increasing contraceptive prevalence hence averting maternal mortality.

Keywords: contraceptives, contraceptive uptake, low socio economic, supportive supervision

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Authors: K. Senthil Kumar, A. Vasumalaikannan

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In this paper, teleoperation of the quadrotor using Internet with Force feedback is addressed. Teleoperation with Force feedback is the ability to remotely control a robot, where contact (obstacle) or environment (wind gust etc) information (force feedback) is communicated from the quadrotor to the master joystick and thus giving the operator a sense of telepresence. The stability and performance of such a teleoperator is highly dependent on the amount of time delay present in the control loop. This problem is further complicated given the fact that for network based communication the time delay is itself time varying and highly non deterministic. In this paper, a novel method using Neural based Smith Predictor at the master side the stability is achieved. The performance of the system even during worst case scenario is within acceptable.

Keywords: teleoperation, quadrotor, neural smith predictor, time delay

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Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

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Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

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Authors: Mohammad Javaherian, Siamak Bashardoust Tajali, Monavvar Hadizadeh

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Objective: This systematic review study was conducted to evaluate the effects of Pulsed Electromagnetic (PEMF) and Static Magnetic Fields (SMG) on pain relief and functional improvement in patients with musculoskeletal Low Back Pain (LBP). Methods: Seven electronic databases were searched by two researchers independently to identify the published Randomized Controlled Trials (RCTs) on the efficacy of pulsed electromagnetic, static magnetic, and therapeutic nuclear magnetic fields. The identified databases for systematic search were Ovid Medline®, Ovid Cochrane RCTs and Reviews, PubMed, Web of Science, Cochrane Library, CINAHL, and EMBASE from 1968 to February 2016. The relevant keywords were selected by Mesh. After initial search and finding relevant manuscripts, all references in selected studies were searched to identify second hand possible manuscripts. The published RCTs in English would be included to the study if they reported changes on pain and/or functional disability following application of magnetic fields on chronic musculoskeletal low back pain. All studies with surgical patients, patients with pelvic pain, and combination of other treatment techniques such as acupuncture or diathermy were excluded. The identified studies were critically appraised and the data were extracted independently by two raters (M.J and S.B.T). Probable disagreements were resolved through discussion between raters. Results: In total, 1505 abstracts were found following the initial electronic search. The abstracts were reviewed to identify potentially relevant manuscripts. Seventeen possibly appropriate studies were retrieved in full-text of which 48 were excluded after reviewing their full-texts. Ten selected articles were categorized into three subgroups: PEMF (6 articles), SMF (3 articles), and therapeutic nuclear magnetic fields (tNMF) (1 article). Since one study evaluated tNMF, we had to exclude it. In the PEMF group, one study of acute LBP did not show significant positive results and the majority of the other five studies on Chronic Low Back Pain (CLBP) indicated its efficacy on pain relief and functional improvement, but one study with the lowest sessions (6 sessions during 2 weeks) did not report a significant difference between treatment and control groups. In the SMF subgroup, two articles reported near significant pain reduction without any functional improvement although more studies are needed. Conclusion: The PEMFs with a strength of 5 to 150 G or 0.1 to 0.3 G and a frequency of 5 to 64 Hz or sweep 7 to 7KHz can be considered as an effective modality in pain relief and functional improvement in patients with chronic low back pain, but there is not enough evidence to confirm their effectiveness in acute low back pain. To achieve the appropriate effectiveness, it is suggested to perform this treatment modality 20 minutes per day for at least 9 sessions. SMFs have not been reported to be substantially effective in decreasing pain or improving the function in chronic low back pain. More studies are necessary to achieve more reliable results.

Keywords: pulsed electromagnetic field, static magnetic field, magnetotherapy, low back pain

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Authors: Andreas Hirseland, Lukas Kerschbaumer

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In Germany, during the past years there constantly are about one million long term unemployed who did not benefit from the prospering labor market while most short term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long term unemployment thus turns into a main obstacle to regular employment, especially if accompanied by other impediments such as low level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. Almost two thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Hiring them is often considered as an investment too risky for employers. Therefore formal application schemes based on formal qualification certificates and vocational biographies might reduce employers’ risks but at the same time are not helpful for long-term unemployed and welfare recipients. The panel survey ‘Labor market and social security’ (PASS; ~15,000 respondents in ~10,000 households), carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency), shows that their chance to get back to work tends to fall to nil. Only 66 cases of such unlikely transitions could be observed. In a sequential explanatory mixed-method study, the very scarce ‘success stories’ of unlikely transitions from long term unemployment to work were explored by qualitative inquiry – in-depth interviews with a focus on biography accompanied by qualitative network techniques in order to get a more detailed insight of relevant actors involved in the processes which promote the transition from being a welfare recipient to work. There is strong evidence that sustainable transitions are influenced by biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation.

Keywords: against-all-odds, economic sociology, long-term unemployment, mixed-methods

Procedia PDF Downloads 239

Authors: C. M. Choi, H. C. Tsang, W. K. Fong, Y. K. Cheng, T. K. Chui, L. Y. Chan, K. W. Lee, C. K. Yuen, P. W. Lau, Y. L. To, K. C. Chow

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Six-minute walk test (6MWT) is a sub-maximal exercise test to assess aerobic capacity and exercise tolerance of patients with chronic respiratory disease and heart failure. This has been proven to be a reliable and valid tool and commonly used in clinical situations. Traditional 6MWT is labour-intensive and time-consuming especially for patients who require assistance in ambulation and oxygen use. When performing the test with these patients, one staff will assist the patient in walking (with or without aids) while another staff will need to manually record patient’s oxygen saturation, heart rate and walking distance at every minute and/or carry oxygen cylinder at the same time. Physiotherapist will then have to document the test results in bed notes in details. With the use of electronic 6MWT (E-6MWT), patients wear a wireless oximeter that transfers data to a tablet PC via Bluetooth. Real-time recording of oxygen saturation, heart rate, and distance are displayed. No manual work on recording is needed. The tablet will generate a comprehensive report which can be directly attached to the patient’s bed notes for documentation. Data can also be saved for later patient follow up. This study was carried out in North District Hospital. Patients who followed commands and required 6MWT assessment were included. Patients were assigned to study or control groups. In the study group, patients adopted the E-6MWT while those in control group adopted the traditional 6MWT. Manpower and time consumed were recorded. Physiotherapists also completed a questionnaire about the use of E-6MWT. Total 12 subjects (Study=6; Control=6) were recruited during 11-12/2017. An average number of staff required and time consumed in traditional 6MWT were 1.67 and 949.33 seconds respectively; while in E-6MWT, the figures were 1.00 and 630.00 seconds respectively. Compared to traditional 6MWT, E-6MWT required 67.00% less manpower and 50.10% less in time spent. Physiotherapists (n=7) found E-6MWT is convenient to use (mean=5.14; satisfied to very satisfied), requires less manpower and time to complete the test (mean=4.71; rather satisfied to satisfied), has better data management (mean=5.86; satisfied to very satisfied) and is recommended to be used clinically (mean=5.29; satisfied to very satisfied). It is proven that E-6MWT requires less manpower input with higher efficiency and better data management. It is welcomed by the clinical frontline staff.

Keywords: electronic, physiotherapy, six-minute walk test, 6MWT

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Authors: Anubhav Shrivastava, Lakshya Bhat, Shivarudraswamy

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Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic.

Keywords: distributed generation, fuzzy logic, matlab, newton raphson, IEEE 14 bus, voltage regulation, radial network

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Authors: Abdollah Kavousi Fard

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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Vijay Kr. Yadav, Nilam Rathi

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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

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Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

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Authors: Ali Heydarimoghim

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In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

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Authors: Gueridi Bachir, Dadache Derradji, Rouabah Farid

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This work is focused on the preparation and characterization of poly (vinyl alcohol)/silica gel/Nano-TiO₂, and the study of titanium dioxide (TiO₂) nanoparticles 1% on the properties of poly (vinyl alcohol) (PVA)/silica films. Fourier transform infrared (FT-IR), water contact angle, ultraviolet-visible spectrometry (UV-VIS)) were used to characterize the hybrid films obtained. The PVA/SiO₂/Nano-TiO₂ films were successfully synthesized. Owing to the FT-IR Analysis, the chemical bonds have clearly shown that the PVA backbone is linked to the (SiO₂-TiO₂) network. UV-VIS tests indicated that the hybrid films' UV shielding properties were drastically enhanced as a result of the addition of TiO₂. The water contact angle results revealed that TiO₂ nanoparticles used as a doping compound possess an important influence on the hydrophilicity of PVA/SiO₂ as thin films.

Keywords: sol-gel method, hybrid materials, PVA/SIO₂/TiO₂, spectroscopical characterization

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

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Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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Authors: Fajar Ajie Setiawan, Ratu Azima Mayangsari, Bunga Aprilia

Abstract:

The emergence of creative hubs around the world, including in Bandung, was primarily driven by the needs of collaborative-innovative spaces for creative industry activities such as the Maker Movement and the Coworking Movement. These activities pose challenges for identification and formulation of sets of indicators for modeling creative hubs in Bandung to help stakeholders in formulating strategies. This study intends to identify their characteristics. This research was conducted using a qualitative approach comparing three concepts of creative hub categorization and integrating them into a single instrument to analyze 12 selected creative hubs. Our results showed three new functions of creative hubs in Bandung: (1) cultural, (2) retail business, and (3) community network. Results also suggest that creative hubs in Bandung are commonly established for networking and community activities. Another result shows that there was a shifting pattern of creative hubs before the 2000s and after the 2000s, which also creates a hybrid group of creative hubs.

Keywords: creative industry, creative hubs, Ngariung, Bandung

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

Abstract:

Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Matthaios Katsanikas

Abstract:

We study the structure of the invariant manifolds of complex unstable periodic orbits of a family of periodic orbits, in a 3D autonomous Hamiltonian system of galactic type, after a transition of this family from stability to complex instability (Hamiltonian Hopf bifurcation). We consider the case of a supercritical Hamiltonian Hopf bifurcation. The invariant manifolds of complex unstable periodic orbits have two kinds of structures. The first kind is represented by a disk confined structure on the 4D space of section. The second kind is represented by a complicated central tube structure that is associated with an extended network of tube structures, strips and flat structures of sheet type on the 4D space of section.

Keywords: dynamical systems, galactic dynamics, chaos, phase space

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Authors: Sabri Arik

Abstract:

In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

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Authors: Lucy W. Mburu, Richard Karanja, Simon N. Mwendia

Abstract:

Over recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing. As motivated by the global sustainable development goal to ensure inclusive and equitable learning opportunities, this research has developed a framework hinged on the knowledge-as-a-service architecture that utilizes knowledge from ambient learning systems. Through statistical analysis and decision tree modeling, the study discovers influential variables for ambient learning among university students. The main aim is to generate a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve educational support on the ambient learning system. The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge, which benefits knowledge consumers, such as the developers of ambient learning systems.

Keywords: actionable knowledge, ambient learning, cloud computing, decision trees, knowledge as a service

Procedia PDF Downloads 162

Authors: Aman Johri, Sidhant Sood, Pooja Suresh

Abstract:

This paper suggests a new and more efficient method of atomization of fuel in a combustor nozzle of a high bypass turbofan engine, using ultrasonic vibrations. Since atomization of fuel just before the fuel spray is injected into the combustion chamber is an important and crucial aspect related to functioning of a propulsion system, the technology suggested by this paper and the experimental analysis on the system components eventually proves to assist in complete and rapid combustion of the fuel in the combustor module of the engine. Current propulsion systems use carburetors, atomization nozzles and apertures in air intake pipes for atomization. The idea of this paper is to deploy new age hybrid technology, namely the Ultrasound Field Effect (UFE) to effectively atomize fuel before it enters the combustion chamber, as a viable and effective method to increase efficiency and improve upon existing designs. The Ultrasound Field Effect is applied axially, on diametrically opposite ends of an atomizer tube that gloves onto the combustor nozzle, where the fuel enters and exits under a pre-defined pressure. The Ultrasound energy vibrates the fuel particles to a breakup frequency. At reaching this frequency, the fuel particles start disintegrating into smaller diameter particles perpendicular to the axis of application of the field from the parent boundary layer of fuel flow over the baseplate. These broken up fuel droplets then undergo swirling effect as per the original nozzle design, with a higher breakup ratio than before. A significant reduction of the size of fuel particles eventually results in an increment in the propulsive efficiency of the engine. Moreover, the Ultrasound atomizer operates within a control frequency such that effects of overheating and induced vibrations are least felt on the overall performance of the engine. The design of an electrical manifold for the multiple-nozzle system over a typical can-annular combustor is developed along with this study, such that the product can be installed and removed easily for maintenance and repairing, can allow for easy access for inspections and transmits least amount of vibrational energy to the surface of the combustor. Since near-field ultrasound is used, the vibrations are easily controlled, thereby successfully reducing vibrations on the outer shell of the combustor. Experimental analysis is carried out on the effect of ultrasonic vibrations on flowing jet turbine fuel using an ultrasound generator probe and results of an effective decrease in droplet size across a constant diameter, away from the boundary layer of flow is noted using visual aid by observing under ultraviolet light. The choice of material for the Ultrasound inducer tube and crystal along with the operating range of temperatures, pressures, and frequencies of the Ultrasound field effect are also studied in this paper, while taking into account the losses incurred due to constant vibrations and thermal loads on the tube surface.

Keywords: atomization, ultrasound field effect, titanium mesh, breakup frequency, parent boundary layer, baseplate, propulsive efficiency, jet turbine fuel, induced vibrations

Procedia PDF Downloads 241