Search results for: optimized network
2356 A Hybrid MAC Protocol for Delay Constrained Mobile Wireless Sensor Networks
Authors: Hanefi Cinar, Musa Cibuk, Ismail Erturk, Fikri Aggun, Munip Geylani
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Mobile Wireless Sensor Networks (MWSNs) carry heterogeneous data traffic with different urgency and quality of service (QoS) requirements. There are a lot of studies made on energy efficiency, bandwidth, and communication methods in literature. But delay, high throughput, utility parameters are not well considered. Increasing demand for real-time data transfer makes these parameters more important. In this paper we design new MAC protocol which is delay constrained and targets for improving delay, utility, and throughput performance of the network and finding solutions on collision and interference problems. Protocol improving QoS requirements by using TDMA, FDM, and OFDMA hybrid communication methods with multi-channel communication.Keywords: MWSN, delay, hybrid MAC, TDMA, FDM, OFDMA
Procedia PDF Downloads 4842355 Feasibility Assessment of High-Temperature Superconducting AC Cable Lines Implementation in Megacities
Authors: Andrey Kashcheev, Victor Sytnikov, Mikhail Dubinin, Elena Filipeva, Dmitriy Sorokin
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Various variants of technical solutions aimed at improving the reliability of power supply to consumers of 110 kV substation are considered. For each technical solution, the results of calculation and analysis of electrical modes and short-circuit currents in the electrical network are presented. The estimation of electric energy consumption for losses within the boundaries of substation reconstruction was carried out in accordance with the methodology for determining the standards of technological losses of electricity during its transmission through electric networks. The assessment of the technical and economic feasibility of the use of HTS CL compared with the complex reconstruction of the 110 kV substation was carried out. It is shown that the use of high-temperature superconducting AC cable lines is a possible alternative to traditional technical solutions used in the reconstruction of substations.Keywords: superconductivity, cable lines, superconducting cable, AC cable, feasibility
Procedia PDF Downloads 1042354 Timely Screening for Palliative Needs in Ambulatory Oncology
Authors: Jaci Mastrandrea
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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening is directly correlated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project is to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline from March 15th, 2022, to April 29th, 2022. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated and evidence-based PC referral criteria. The tool was initially implemented using paper forms and later was integrated into the Epic-Beacon EHR system. Patients were screened by registered nurses on the SLCTC treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher were considered to be a positive screen. Scores of five or higher triggered a PC referral order in the patient’s EHR for the oncologist to review and approve. All patients with a positive screen received an educational handout on the topic of PC, and the EHR was flagged for follow-up. Results: Prior to implementation of the PSCNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the first 100 patient screenings completed within the eight-week data collection period. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting the criteria were flagged in the EHR for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.Keywords: oncology, palliative care, symptom management, symptom screening, ambulatory oncology, cancer, supportive care
Procedia PDF Downloads 782353 Construction Strategy of Urban Public Space in Driverless Era
Authors: Yang Ye, Hongfei Qiu, Yaqi Li
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The planning and construction of traditional cities are oriented by cars, which leads to the problems of insufficient urban public space, fragmentation, and low utilization efficiency. With the development of driverless technology, the urban structure will change from the traditional single-core grid structure to the multi-core model. In terms of traffic organization, with the release of land for traffic facilities, public space will become more continuous and integrated with traffic space. In the context of driverless technology, urban public reconstruction is characterized by modularization and high efficiency, and its planning and layout features accord with points (service facilities), lines (smart lines), surfaces (activity centers). The public space of driverless urban roads will provide diversified urban public facilities and services. The intensive urban layout makes the commercial public space realize the functions of central activities and style display, respectively, in the interior (building atrium) and the exterior (building periphery). In addition to recreation function, urban green space can also utilize underground parking space to realize efficient dispatching of shared cars. The roads inside the residential community will be integrated into the urban landscape, providing conditions for the community public activity space with changing time sequence and improving the efficiency of space utilization. The intervention of driverless technology will change the thinking of traditional urban construction and turn it into a human-oriented one. As a result, urban public space will be richer, more connected, more efficient, and the urban space justice will be optimized. By summarizing the frontier research, this paper discusses the impact of unmanned driving on cities, especially urban public space, which is beneficial for landscape architects to cope with the future development and changes of the industry and provides a reference for the related research and practice.Keywords: driverless, urban public space, construction strategy, urban design
Procedia PDF Downloads 1202352 Investigation of Different Control Stratgies for UPFC Decoupled Model and the Impact of Location on Control Parameters
Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider
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In order to evaluate the performance of a unified power flow controller (UPFC), mathematical models for steady state and dynamic analysis are to be developed. The steady state model is mainly concerned with the incorporation of the UPFC in load flow studies. Several load flow models for UPFC have been introduced in literature, and one of the most reliable models is the decoupled UPFC model. In spite of UPFC decoupled load flow model simplicity, it is more robust compared to other UPFC load flow models and it contains unique capabilities. Some shortcoming such as additional set of nonlinear equations are to be solved separately after the load flow solution is obtained. The aim of this study is to investigate the different control strategies that can be realized in the decoupled load flow model (individual control and combined control), and the impact of the location of the UPFC in the network on its control parameters.Keywords: UPFC, decoupled model, load flow, control parameters
Procedia PDF Downloads 5592351 IACOP - Route Optimization in Wireless Networks Using Improved Ant Colony Optimization Protocol
Authors: S. Vasundra, D. Venkatesh
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Wireless networks have gone through an extraordinary growth in the past few years, and will keep on playing a crucial role in future data communication. The present wireless networks aim to make communication possible anywhere and anytime. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Since an ad hoc network may consist of a large number of mobile hosts, this imposes a significant challenge on the design of an effective and efficient routing protocol that can work well in an environment with frequent topological changes. This paper proposes improved ant colony optimization (IACO) technique. It also maintains load balancing in wireless networks. The simulation results show that the proposed IACO performs better than existing routing techniques.Keywords: wireless networks, ant colony optimization, load balancing, architecture
Procedia PDF Downloads 4302350 Application of Deep Learning in Top Pair and Single Top Quark Production at the Large Hadron Collider
Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf
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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approachKeywords: top tagger, multivariate, deep learning, LHC, single top
Procedia PDF Downloads 1142349 Fexofenadine Hydrochloride Orodispersisble Tablets: Formulation and in vitro/in vivo Evaluation in Healthy Human Volunteers
Authors: Soad Ali Yehia, Mohamed Shafik El-Ridi, Mina Ibrahim Tadros, Nolwa Gamal El-Sherif
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Fexofenadine hydrochloride (FXD) is a slightly soluble, bitter-tasting, drug having an oral bioavailability of 35%. The maximum plasma concentration is reached 2.6 hours (Tmax) post-dose. The current work aimed to develop taste-masked FXD orodispersible tablets (ODTs) to increase extent of drug absorption and reduce Tmax. Taste masking was achieved via solid dispersion (SD) with chitosan (CS) or sodium alginate (ALG). FT-IR, DSC and XRD were performed to identify physicochemical interactions and FXD crystallinity. Taste-masked FXD-ODTs were developed via addition of superdisintegrants (crosscarmelose sodium or sodium starch glycolate, 5% and 10%, w/w) or sublimable agents (camphor, menthol or thymol; 10% and 20%, w/w) to FXD-SDs. ODTs were evaluated for weight variation, drug-content, friability, wetting time, disintegration time and drug release. Camphor-based (20%, w/w) FXD-ODT (F12) was optimized (F23) by incorporation of a more hydrophilic lubricant, sodium stearyl fumarate (Pruv®). The topography of the latter formula was examined via scanning electron microscopy (SEM). The in vivo estimation of FXD pharmacokinetics, relative to Allegra® tablets, was evaluated in healthy human volunteers. Based on the gustatory sensation test in healthy volunteers, FXD:CS (1:1) and FXD:ALG (1:0.5) SDs were selected. Taste-masked FXD-ODTs had appropriate physicochemical properties and showed short wetting and disintegration times. Drug release profiles of F23 and phenylalanine-containing Allegra® ODT were similar (f2 = 96) showing a complete release in two minutes. SEM micrographs revealed pores following camphor sublimation. Compared to Allegra® tablets, pharmacokinetic studies in healthy volunteers proved F23 ability to increase extent of FXD absorption (14%) and reduce Tmax to 1.83 h.Keywords: fexofenadine hydrochloride, taste masking, chitosan, orodispersible
Procedia PDF Downloads 3482348 Screening and Optimization of Conditions for Pectinase Production by Aspergillus Flavus
Authors: Rumaisa Shahid, Saad Aziz Durrani, Shameel Pervez, Ibatsam Khokhar
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Food waste is a prevalent issue in Pakistan, with over 40 percent of food discarded annually. Despite their decay, rotting fruits retain residual nutritional value consumed by microorganisms, notably fungi and bacteria. Fungi, preferred for their extracellular enzyme release, are gaining prominence, particularly for pectinase production. This enzyme offers several advantages, including clarifying juices by breaking down pectic compounds. In this study, three Aspergillus flavus isolates derived from decomposed fruits and manure were selected for pectinase production. The primary aim was to isolate fungi from diverse waste sources, identify the isolates and assess their capacity for pectinase production. The identification was done through morphological characteristics with the help of Light microscopy and Scanning Electron Microscopy (SEM). Pectinolytic potential was screened using pectin minimal salt agar (PMSA) medium, comparing clear zone diameters among isolates. Identification relied on morphological characteristics. Optimizing substrate (lemon and orange peel powder) concentrations, pH, temperature, and incubation period aimed to enhance pectinase yield. Spectrophotometry enabled quantitative analysis. The temperature was set at room temperature (28 ºC). The optimal conditions for Aspergillus flavus strain AF1(isolated from mango) included a pH of 5, an incubation period of 120 hours, and substrate concentrations of 3.3% for orange peels and 6.6% for lemon peels. For AF2 and AF3 (both isolated from soil), the ideal pH and incubation period were the same as AF1 i.e. pH 5 and 120 hours. However, their optimized substrate concentrations varied, with AF2 showing maximum activity at 3.3% for orange peels and 6.6% for lemon peels, while AF3 exhibited its peak activity at 6.6% for orange peels and 8.3% for lemon peels. Among the isolates, AF1 demonstrated superior performance under these conditions, comparatively.Keywords: pectinase, lemon peel, orange peel, aspergillus flavus
Procedia PDF Downloads 772347 The Influence of Polysaccharide Isolated from Morinda citrifolia Fruit to the Growth of Vero, He-La and T47D Cell Lines against Doxorubicin in vitro
Authors: Ediati Budi Cahyono, Triana Hertiani, Nauval Arrazy Asawimanda, Wahyu Puji Pratomo
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Background: Doxorubicin is widely used as a chemotherapeutic drug despite having many side effects. It may cause macrophage dysfunction and decreasing proliferation of lymphocyte. Noni (Morinda citrifolia) fruit which has rich of polysaccharide content has potential as antitumor and immunostimulant effect. The isolation of polysaccharide from Noni fruit has been optimized according to four different methods based on macrophage and lymphocyte activities. We found the highest polysaccharide content from one of the four methods isolation. A method of polysaccharide isolation which has the highest immunostimulant effect was used for further observation as co-chemotherapy. The aim of the study: was to evaluate the isolated polysaccharide from the method of choice as co-chemotherapy of doxorubicin for the growth of Vero, He-La, and T47D cell lines in vitro. The method: in vitro growth assay of Vero, He-La, and T47D cell lines was done using MTT-reduction method, and apoptosis test was done by double staining method to evaluate the induction apoptotic effect of the combination. Every group was treated with doxorubicin and isolated polysaccharide from method of choice with 4 variances of concentrations (25 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) a long with negative control (doxorubicin only) and normal control (without doxorubicin or polysaccharide administration). Results: The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin against He-La and T47D cell lines influenced the highest cytotoxic effect by suppressing cell viability comparing with doxorubicin only. The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin-induced apoptotic effect the He-La cell line comparing with doxorubicin only. The result of the study: it can be concluded that the combination of polysaccharide fraction and doxorubicin effect more selective toward He-La and T47D cell lines than to Vero cell line. It can be suggested isolated polysaccharide from the method of choice has co-chemotherapy activity against doxorubicin.Keywords: polysaccharide, noni fruit, doxorubicin, cancer cell lines, vero cell line
Procedia PDF Downloads 2562346 Identifying and Optimizing the Critical Excipients in Moisture Activated Dry Granulation Process for Two Anti TB Drugs of Different Aqueous Solubilities
Authors: K. Srujana, Vinay U. Rao, M. Sudhakar
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Isoniazide (INH) a freely water soluble and pyrazinamide (Z) a practically water insoluble first line anti tubercular (TB) drugs were identified as candidates for optimizing the Moisture Activated Dry Granulation (MADG) process. The work focuses on identifying the effect of binder type and concentration as well as the effect of magnesium stearate level on critical quality attributes of Disintegration time (DT) and in vitro dissolution test when the tablets are processed by the MADG process. Also, the level of the drug concentration, binder concentration and fluid addition during the agglomeration stage of the MADG process was evaluated and optimized. For INH, it was identified that for tablets with HPMC as binder at both 2% w/w and 5% w/w level and Magnesium stearate upto 1%w/w as lubrication the DT is within 1 minute and the dissolution rate is the fastest (> 80% in 15 minutes) as compared to when PVP or pregelatinized starch is used as binder. Regarding the process, fast disintegrating and rapidly dissolving tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 25% w/w 0% w/w binder and 0.033%. w/w. At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is also slower. For pyrazinamide,it was identified that for the tablets with 2% w/w level of each of PVP as binder and Cross Caramellose Sodium disintegrant the DT is within 2 minutes and the dissolution rate is the fastest(>80 in 15 minutes)as compared to when HPMC or pregelatinized starch is used as binder. This may be attributed to the fact that PVP may be acting as a solubilizer for the practically insoluble Pyrazinamide. Regarding the process,fast dispersing and rapidly disintegrating tablets are obtained when the level of drug, binder and fluid uptake in agglomeration stage is 10% w/w,25% w/w binder and 1% w/w.At the other 2 levels of these three ingredients, the DT is significantly impacted and dissolution is comparatively slower and less complete.Keywords: agglomeration stage, isoniazide, MADG, moisture distribution stage, pyrazinamide
Procedia PDF Downloads 2422345 Unleashing Potential in Pedagogical Innovation for STEM Education: Applying Knowledge Transfer Technology to Guide a Co-Creation Learning Mechanism for the Lingering Effects Amid COVID-19
Authors: Lan Cheng, Harry Qin, Yang Wang
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Background: COVID-19 has induced the largest digital learning experiment in history. There is also emerging research evidence that students have paid a high cost of learning loss from virtual learning. University-wide survey results demonstrate that digital learning remains difficult for students who struggle with learning challenges, isolation, or a lack of resources. Large-scale efforts are therefore increasingly utilized for digital education. To better prepare students in higher education for this grand scientific and technological transformation, STEM education has been prioritized and promoted as a strategic imperative in the ongoing curriculum reform essential for unfinished learning needs and whole-person development. Building upon five key elements identified in the STEM education literature: Problem-based Learning, Community and Belonging, Technology Skills, Personalization of Learning, Connection to the External Community, this case study explores the potential of pedagogical innovation that integrates computational and experimental methodologies to support, enrich, and navigate STEM education. Objectives: The goal of this case study is to create a high-fidelity prototype design for STEM education with knowledge transfer technology that contains a Cooperative Multi-Agent System (CMAS), which has the objectives of (1) conduct assessment to reveal a virtual learning mechanism and establish strategies to facilitate scientific learning engagement, accessibility, and connection within and beyond university setting, (2) explore and validate an interactional co-creation approach embedded in project-based learning activities under the STEM learning context, which is being transformed by both digital technology and student behavior change,(3) formulate and implement the STEM-oriented campaign to guide learning network mapping, mitigate the loss of learning, enhance the learning experience, scale-up inclusive participation. Methods: This study applied a case study strategy and a methodology informed by Social Network Analysis Theory within a cross-disciplinary communication paradigm (students, peers, educators). Knowledge transfer technology is introduced to address learning challenges and to increase the efficiency of Reinforcement Learning (RL) algorithms. A co-creation learning framework was identified and investigated in a context-specific way with a learning analytic tool designed in this study. Findings: The result shows that (1) CMAS-empowered learning support reduced students’ confusion, difficulties, and gaps during problem-solving scenarios while increasing learner capacity empowerment, (2) The co-creation learning phenomenon have examined through the lens of the campaign and reveals that an interactive virtual learning environment fosters students to navigate scientific challenge independently and collaboratively, (3) The deliverables brought from the STEM educational campaign provide a methodological framework both within the context of the curriculum design and external community engagement application. Conclusion: This study brings a holistic and coherent pedagogy to cultivates students’ interest in STEM and develop them a knowledge base to integrate and apply knowledge across different STEM disciplines. Through the co-designing and cross-disciplinary educational content and campaign promotion, findings suggest factors to empower evidence-based learning practice while also piloting and tracking the impact of the scholastic value of co-creation under the dynamic learning environment. The data nested under the knowledge transfer technology situates learners’ scientific journey and could pave the way for theoretical advancement and broader scientific enervators within larger datasets, projects, and communities.Keywords: co-creation, cross-disciplinary, knowledge transfer, STEM education, social network analysis
Procedia PDF Downloads 1192344 Wavelength Conversion of Dispersion Managed Solitons at 100 Gbps through Semiconductor Optical Amplifier
Authors: Kadam Bhambri, Neena Gupta
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All optical wavelength conversion is essential in present day optical networks for transparent interoperability, contention resolution, and wavelength routing. The incorporation of all optical wavelength convertors leads to better utilization of the network resources and hence improves the efficiency of optical networks. Wavelength convertors that can work with Dispersion Managed (DM) solitons are attractive due to their superior transmission capabilities. In this paper, wavelength conversion for dispersion managed soliton signals was demonstrated at 100 Gbps through semiconductor optical amplifier and an optical filter. The wavelength conversion was achieved for a 1550 nm input signal to1555nm output signal. The output signal was measured in terms of BER, Q factor and system margin.Keywords: all optical wavelength conversion, dispersion managed solitons, semiconductor optical amplifier, cross gain modultation
Procedia PDF Downloads 4592343 Comparison of Security Challenges and Issues of Mobile Computing and Internet of Things
Authors: Aabiah Nayeem, Fariha Shafiq, Mustabshra Aftab, Rabia Saman Pirzada, Samia Ghazala
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In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.Keywords: embedded computing, internet of things, mobile computing, wireless technologies
Procedia PDF Downloads 3232342 A Photoredox (C)sp³-(C)sp² Coupling Method Comparison Study
Authors: Shasline Gedeon, Tiffany W. Ardley, Ying Wang, Nathan J. Gesmundo, Katarina A. Sarris, Ana L. Aguirre
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Drug discovery and delivery involve drug targeting, an approach that helps find a drug against a chosen target through high throughput screening and other methods by way of identifying the physical properties of the potential lead compound. Physical properties of potential drug candidates have been an imperative focus since the unveiling of Lipinski's Rule of 5 for oral drugs. Throughout a compound's journey from discovery, clinical phase trials, then becoming a classified drug on the market, the desirable properties are optimized while minimizing/eliminating toxicity and undesirable properties. In the pharmaceutical industry, the ability to generate molecules in parallel with maximum efficiency is a substantial factor achieved through sp²-sp² carbon coupling reactions, e.g., Suzuki Coupling reactions. These reaction types allow for the increase of aromatic fragments onto a compound. More recent literature has found benefits to decreasing aromaticity, calling for more sp³-sp² carbon coupling reactions instead. The objective of this project is to provide a comparison between various sp³-sp² carbon coupling methods and reaction conditions, collecting data on production of the desired product. There were four different coupling methods being tested amongst three cores and 4-5 installation groups per method; each method ran under three distinct reaction conditions. The tested methods include the Photoredox Decarboxylative Coupling, the Photoredox Potassium Alkyl Trifluoroborate (BF3K) Coupling, the Photoredox Cross-Electrophile (PCE) Coupling, and the Weix Cross-Electrophile (WCE) Coupling. The results concluded that the Decarboxylative method was very difficult in yielding product despite the several literature conditions chosen. The BF3K and PCE methods produced competitive results. Amongst the two Cross-Electrophile coupling methods, the Photoredox method surpassed the Weix method on numerous accounts. The results will be used to build future libraries.Keywords: drug discovery, high throughput chemistry, photoredox chemistry, sp³-sp² carbon coupling methods
Procedia PDF Downloads 1482341 A Review of the Parameters Used in Gateway Selection Schemes for Internet Connected MANETs
Authors: Zainab S. Mahmood, Aisha H. Hashim, Wan Haslina Hassan, Farhat Anwar
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The wide use of the internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, hand off, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.Keywords: Internet Gateway, MANET, mobility, selection criteria
Procedia PDF Downloads 4262340 Identification of Vehicle Dynamic Parameters by Using Optimized Exciting Trajectory on 3- DOF Parallel Manipulator
Authors: Di Yao, Gunther Prokop, Kay Buttner
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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory
Procedia PDF Downloads 2702339 Optimal MPPT Charging Battery System for Photovoltaic Standalone Applications
Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia
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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.Keywords: modeling, battery, MPPT, charging, PV Panel
Procedia PDF Downloads 5272338 A New Approach for PE100 Characterization; An in-Reactor HDPE Alloy with Semi Hard and Soft Segments
Authors: Sasan Talebnezhad, Parviz Hamidia
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GPC and RMS analysis showed no distinct difference between PE 100 On, Off, and Reference grade. But FTIR spectra and multiple endothermic peaks obtained from SSA analysis, attributed to heterogeneity of ethylene sequence length, lamellar thickness and also the non-uniformity of short chain branching, showed sharp discrepancy and proposed a blend structure of high-density polyethylenes in PE 100 grade. Catalysis along with process parameters dictates poly blend PE 100 structure. This in-reactor blend is a mixture of compatible co-crystallized phases with different crystalinity, forming a physical semi hard and soft segment network responsible for improved impact properties in PE 100 pipe grade. We propose a new approach for PE100 evaluation that is more efficient than normal microstructure characterization.Keywords: HDPE, pipe grade, in-reactor blend, hard and soft segments
Procedia PDF Downloads 4492337 Post-Quantum Resistant Edge Authentication in Large Scale Industrial Internet of Things Environments Using Aggregated Local Knowledge and Consistent Triangulation
Authors: C. P. Autry, A. W. Roscoe, Mykhailo Magal
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We discuss the theoretical model underlying 2BPA (two-band peer authentication), a practical alternative to conventional authentication of entities and data in IoT. In essence, this involves assembling a virtual map of authentication assets in the network, typically leading to many paths of confirmation between any pair of entities. This map is continuously updated, confirmed, and evaluated. The value of authentication along multiple disjoint paths becomes very clear, and we require analogues of triangulation to extend authentication along extended paths and deliver it along all possible paths. We discover that if an attacker wants to make an honest node falsely believe she has authenticated another, then the length of the authentication paths is of little importance. This is because optimal attack strategies correspond to minimal cuts in the authentication graph and do not contain multiple edges on the same path. The authentication provided by disjoint paths normally is additive (in entropy).Keywords: authentication, edge computing, industrial IoT, post-quantum resistance
Procedia PDF Downloads 2042336 A Combination of Independent Component Analysis, Relative Wavelet Energy and Support Vector Machine for Mental State Classification
Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui
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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.Keywords: EEG, ICA, SVM, wavelet
Procedia PDF Downloads 3852335 Training a Neural Network Using Input Dropout with Aggressive Reweighting (IDAR) on Datasets with Many Useless Features
Authors: Stylianos Kampakis
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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.Keywords: neural networks, feature selection, regularization, aggressive reweighting
Procedia PDF Downloads 4632334 The Twin Terminal of Pedestrian Trajectory Based on City Intelligent Model (CIM) 4.0
Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao
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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network
Procedia PDF Downloads 1642333 A Fast Optimizer for Large-scale Fulfillment Planning based on Genetic Algorithm
Authors: Choonoh Lee, Seyeon Park, Dongyun Kang, Jaehyeong Choi, Soojee Kim, Younggeun Kim
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Market Kurly is the first South Korean online grocery retailer that guarantees same-day, overnight shipping. More than 1.6 million customers place an average of 4.7 million orders and add 3 to 14 products into a cart per month. The company has sold almost 30,000 kinds of various products in the past 6 months, including food items, cosmetics, kitchenware, toys for kids/pets, and even flowers. The company is operating and expanding multiple dry, cold, and frozen fulfillment centers in order to store and ship these products. Due to the scale and complexity of the fulfillment, pick-pack-ship processes are planned and operated in batches, and thus, the planning that decides the batch of the customers’ orders is a critical factor in overall productivity. This paper introduces a metaheuristic optimization method that reduces the complexity of batch processing in a fulfillment center. The method is an iterative genetic algorithm with heuristic creation and evolution strategies; it aims to group similar orders into pick-pack-ship batches to minimize the total number of distinct products. With a well-designed approach to create initial genes, the method produces streamlined plans, up to 13.5% less complex than the actual plans carried out in the company’s fulfillment centers in the previous months. Furthermore, our digital-twin simulations show that the optimized plans can reduce 3% of operation time for packing, which is the most complex and time-consuming task in the process. The optimization method implements a multithreading design on the Spring framework to support the company’s warehouse management systems in near real-time, finding a solution for 4,000 orders within 5 to 7 seconds on an AWS c5.2xlarge instance.Keywords: fulfillment planning, genetic algorithm, online grocery retail, optimization
Procedia PDF Downloads 862332 Fabrication of Chitosan/Polyacrylonitrile Blend and SEMI-IPN Hydrogel with Epichlorohydrin
Authors: Muhammad Omer Aijaz, Sajjad Haider, Fahad S. Al Mubddal, Yousef Al-Zeghayer, Waheed A. Al Masry
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The present study is focused on the preparation of chitosan-based blend and Semi-Interpenetrating Polymer Network (SEMI-IPN) with polyacrylonitrile (PAN). Blend Chitosan/Polyacrylonitrile (PAN) hydrogel films were prepared by solution blending and casting technique. Chitosan in the blend was cross-linked with epichlorohydrin (ECH) to prepare SEMI-IPN. The developed Chitosan/PAN blend and SEMI-IPN hydrogels were characterized with SEM, FTIR, TGA, and DSC. The result showed good miscibility between chitosan and PAN, crosslinking of chitosan in the blend, and improved thermal properties for SEMI-IPN. The swelling of the different blended and SEMI-IPN hydrogels samples were examined at room temperature. Blend (C80/P20) sample showed highest swelling (2400%) and fair degree of stability (28%) whereas SEMI-IPN hydrogel exhibited relatively low degree of swelling (244%) and high degree of aqueous stability (85.5%).Keywords: polymer hydrogels, chitosan, SEMI-IPN, polyacrylonitrile, epichlorohydrin
Procedia PDF Downloads 3792331 Instance Segmentation of Wildfire Smoke Plumes using Mask-RCNN
Authors: Jamison Duckworth, Shankarachary Ragi
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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands
Procedia PDF Downloads 1312330 In-vitro Metabolic Fingerprinting Using Plasmonic Chips by Laser Desorption/Ionization Mass Spectrometry
Authors: Vadanasundari Vedarethinam, Kun Qian
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The metabolic analysis is more distal over proteomics and genomics engaging in clinics and needs rationally distinct techniques, designed materials, and device for clinical diagnosis. Conventional techniques such as spectroscopic techniques, biochemical analyzers, and electrochemical have been used for metabolic diagnosis. Currently, there are four major challenges including (I) long-term process in sample pretreatment; (II) difficulties in direct metabolic analysis of biosamples due to complexity (III) low molecular weight metabolite detection with accuracy and (IV) construction of diagnostic tools by materials and device-based platforms for real case application in biomedical applications. Development of chips with nanomaterial is promising to address these critical issues. Mass spectroscopy (MS) has displayed high sensitivity and accuracy, throughput, reproducibility, and resolution for molecular analysis. Particularly laser desorption/ ionization mass spectrometry (LDI MS) combined with devices affords desirable speed for mass measurement in seconds and high sensitivity with low cost towards large scale uses. We developed a plasmonic chip for clinical metabolic fingerprinting as a hot carrier in LDI MS by series of chips with gold nanoshells on the surface through controlled particle synthesis, dip-coating, and gold sputtering for mass production. We integrated the optimized chip with microarrays for laboratory automation and nanoscaled experiments, which afforded direct high-performance metabolic fingerprinting by LDI MS using 500 nL of serum, urine, cerebrospinal fluids (CSF) and exosomes. Further, we demonstrated on-chip direct in-vitro metabolic diagnosis of early-stage lung cancer patients using serum and exosomes without any pretreatment or purifications. To our best knowledge, this work initiates a bionanotechnology based platform for advanced metabolic analysis toward large-scale diagnostic use.Keywords: plasmonic chip, metabolic fingerprinting, LDI MS, in-vitro diagnostics
Procedia PDF Downloads 1662329 A Low-Power, Low-Noise and High Linearity 60 GHz LNA for WPAN Applications
Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi
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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity
Procedia PDF Downloads 5192328 Implementation of Distributed Randomized Algorithms for Resilient Peer-to-Peer Networks
Authors: Richard Tanaka, Ying Zhu
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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks
Procedia PDF Downloads 2222327 Foot Recognition Using Deep Learning for Knee Rehabilitation
Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia
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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network
Procedia PDF Downloads 165