Search results for: passive solar architecture

Authors: Gregory E. Ofili

Abstract:

Introduction and Objective: Climate change and a global economy mean farmers must adapt and gain access to affordable and reliable automation technologies. Key barriers include a lack of transportation, electricity, and internet service, coupled with costly enabling technologies and limited local subject matter expertise. Methodology/Approach: Resourcefulness is essential to mechanization on a farm. This runs contrary to the tech industry practice of planned obsolescence and disposal. One solution is plug-and-play hardware that allows farmer to assemble, repair, program, and service their own fleet of industrial machines. To that end, we developed a method of manufacturing low-cost utility robots, transport vehicles, and solar/wind energy harvesting systems, all running on an open-source Robot Operating System (ROS). We demonstrate this technology by fabricating a utility robot and an all-terrain (4X4) utility vehicle. Constructed of aluminum trusses and weighing just 40 pounds, yet capable of transporting 200 pounds of cargo, on sale for less than $2,000. Conclusions & Policy Implications: Electricity, internet, and automation are essential for productivity and competitiveness. With planned obsolescence, the priorities of technology suppliers are not aligned with the farmer’s realities. This patent-pending method of manufacturing low-cost industrial robots and electric vehicles has met its objective. To create low-cost machines, the farmer can assemble, program, and repair with basic hand tools.

Keywords: automation, robotics, utility robot, small-hold farm, robot operating system

Procedia PDF Downloads 52

Authors: Gholamreza Momenzadeh, Forough Nematolahi

Abstract:

The Extended Enterprise Resource Planning (ERPII) system usually requires massive amounts of storage space, powerful servers, and large upfront and ongoing investments to purchase and manage the software and the related hardware which are not affordable for organizations. In recent decades, organizations prefer to adapt their business structures with new technologies for remaining competitive in the world economy. Therefore, cloud computing (which is one of the tools of information technology (IT)) is a modern system that reveals the next-generation application architecture. Also, cloud computing has had some advantages that reduce costs in many ways such as: lower upfront costs for all computing infrastructure and lower cost of maintaining and supporting. On the other hand, traditional ERPII is not responding for huge amounts of data and relations between the organizations. In this study, based on a literature study, ERPII is investigated in the context of cloud computing where the organizations operate more efficiently. Also, ERPII conditions have a response to needs of organizations in large amounts of data and relations between the organizations.

Keywords: extended enterprise resource planning, cloud computing, business process, enterprise information integration

Procedia PDF Downloads 201

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 181

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

Procedia PDF Downloads 262

Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

Abstract:

Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

Procedia PDF Downloads 341

Authors: Hedi Dghim, Ahmed El-Naggar, Istvan Erlich

Abstract:

Power electronic converters are being introduced in low voltage (LV) grids at an increasingly rapid rate due to the growing adoption of power electronic-based home appliances in residential grid. Photovoltaic (PV) systems are considered one of the potential installed renewable energy sources in distribution power systems. This trend has led to high distortion in the supply voltage which consequently produces harmonic currents in the network and causes an inherent voltage unbalance. In order to investigate the effect of harmonic distortions, a case study of a typical LV grid configuration with high penetration of 3-phase and 1-phase rooftop mounted PV from southern Germany was first considered. Electromagnetic transient (EMT) simulations were then carried out under the MATLAB/Simulink environment which contain detailed models for power electronic-based loads, ohmic-based loads as well as 1- and 3-phase PV. Note that, the switching patterns of the power electronic circuits were considered in this study. Measurements were eventually performed to analyze the distortion levels when PV operating under different solar irradiance. The characteristics of the load-side harmonic impedances were analyzed, and their harmonic contributions were evaluated for different distortion levels. The effect of the high penetration of PV on the harmonic distortion of both positive and negative sequences was also investigated. The simulation results are presented based on case studies. The current distortion levels are in agreement with relevant standards, otherwise the Total Harmonic Distortion (THD) increases under low PV power generation due to its inverse relation with the fundamental current.

Keywords: harmonic distortion analysis, power quality, PV systems, residential distribution system

Procedia PDF Downloads 249

Authors: Elena Bellini, Daniele Mugnaini, Michele Boschetto

Abstract:

People with an Autistic Spectrum Disorder and an Intellectual Disability who need to attend a Hospital Emergency Waiting Room frequently present high levels of discomfort and challenging behaviors due to stress-related hyperarousal, sensory sensitivity, novelty-anxiety, communication and self-regulation difficulties. Increased agitation and acting out also disturb the diagnostic and therapeutic processes, and the emergency room climate. Architectural design disciplines aimed at reducing distress in hospitals or creating autism-friendly environments are called for to find effective answers to this particular need. A growing number of researchers are considering the physical environment as an important point of intervention for people with autism. It has been shown that providing the right setting can help enhance confidence and self-esteem and can have a profound impact on their health and wellbeing. Environmental psychology has evaluated the perceived quality of care, looking at the design of hospital rooms, paths and circulation, waiting rooms, services and devices. Furthermore, many studies have investigated the influence of the hospital environment on patients, in terms of stress-reduction and therapeutic intervention’ speed, but also on health professionals and their work. Several services around the world are organizing autism-friendly hospital environments which involve the architecture and the specific staff training. In Italy, the association Spes contra spem has promoted and published, in 2013, the ‘Chart of disabled people in the hospital’. It stipulates that disabled people should have equal rights to accessible and high-quality care. There are a few Italian examples of therapeutic programmes for autistic people as the Dama project in Milan and the recent experience of Children and Autism Foundation in Pordenone. Careggi’s Emergency Waiting Room in Florence has been built to satisfy this challenge. This project of research comes from a collaboration between the technical staff of Careggi Hospital, the Center for autism PAMAPI and some architects expert in the sensory environment. The methodology of focus group involved architects, psychologists and professionals through a transdisciplinary research, centered on the links between the spatial characteristics and clinical state of people with ASD. The relationship between architectural space and quality of life is studied to pay maximum attention to users’ needs and to support the medical staff in their work by a specific program of training. The result of this research is a sum of criteria used to design the emergency waiting room, that will be illustrated. A protected room, with a clear space design, maximizes comprehension and predictability. The multisensory environment is thought to help sensory integration and relaxation. Visual communication through Ipad allows an anticipated understanding of medical procedures, and a specific technological system supports requests, choices and self-determination in order to fit sensory stimulation to personal preferences, especially for hypo and hypersensitive people. All these characteristics should ensure a better regulation of the arousal, less behavior problems, improving treatment accessibility, safety, and effectiveness. First results about patient-satisfaction levels will be presented.

Keywords: accessibility of care, autism-friendly architecture, personalized therapeutic process, sensory environment

Procedia PDF Downloads 246

Authors: Guru Prakash, Revanth Dugalam

Abstract:

A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

Procedia PDF Downloads 65

Authors: Mohamed A. Dkhil, Denis Delic, Saleh Al-Quraishy

Abstract:

Coccidiosis causes considerable economic loss in the poultry industry. The current study aimed to investigate the response of goblet cells as well as the induced tissue damage during Eimeria papilata infection. Mice were infected with sporulated E. papillata oocyts. On day 5 post-infection, the fecal output was determined. Also, the jejunum was prepared for the histological, histochemical and molecular studies. Our results revealed that the intestinal coccidian infection with E. papillata induced a marked goblet cell hypoplasia and depleted mucus secretion. Also, the infection was able to alter the jejuna architecture and increased the apoptotic cells inside the villi. In addition, the real time PCR results indicated that, the inflammatory cytokines TNF-α, iNOS, IFN-y and IL-1β were significantly up-regulated. In contrast, the mRNA expression patterns of IL-6 in response to E. papillata infection did not differ significantly between control and infected mice. Moreover, the mRNA expression of TLR4 was significantly up-regulated, whereas the expression of MUC2 is significantly down-regulated upon infection. Further studies are required to understand the regulatory mechanisms of goblet cells related genes.

Keywords: goblet cells, Eimeria papillata, mice, jejunum

Procedia PDF Downloads 260

Authors: Mouhamadou Diop, Mohamed I. Hassan

Abstract:

Molten metallic flow in metallurgical plant is highly turbulent and presents a complex coupling with heat transfer, phase transfer, chemical reaction, momentum transport, etc. Molten silicon flow has significant effect in directional solidification of multicrystalline silicon by affecting the temperature field and the emerging crystallization interface as well as the transport of species and impurities during casting process. Owing to the complexity and limits of reliable measuring techniques, computational models of fluid flow are useful tools to study and quantify these problems. The overall objective of this study is to investigate the potential of a traveling magnetic field for an efficient operating control of the molten metal flow. A multidimensional numerical model will be developed for the calculations of Lorentz force, molten metal flow, and the related phenomenon. The numerical model is implemented in a laboratory-scale silicon crystallization furnace. This study presents the potential of traveling magnetic field approach for an efficient operating control of the molten flow. A numerical model will be used to study the effects of magnetic force applied on the molten flow, and their interdependencies. In this paper, coupled and decoupled, steady and unsteady models of molten flow and crystallization interface will be compared. This study will allow us to retrieve the optimal traveling magnetic field parameter range for crystallization furnaces and the optimal numerical simulations strategy for industrial application.

Keywords: multidimensional, numerical simulation, solidification, multicrystalline, traveling magnetic field

Procedia PDF Downloads 229

Authors: William Whiteley, Jens Gregor

Abstract:

In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

Procedia PDF Downloads 94

Authors: Ghulam Abbas Shah, Maqsood Sadiq, Ahsan Yasin

Abstract:

Massive global plastic production, combined with poor degradation and recycling, leads to significant environmental pollution from microplastics, whose effects on plants in the soil remain understudied. Besides, effective mitigation strategies and their impact on ammonia (NH₃) emissions under varying fertilizer management practices remains sketchy. Therefore, the objectives of the study were (i) to determine the impact of organic fertilizers on the toxicity of microplastics in sorghum and physicochemical characteristics of microplastics-contaminated soil and (ii) to assess the impacts of these fertilizers on NH₃ emissions from this soil. A field experiment was conducted using sorghum as a test crop. Treatments were: (i) Control (C), (ii) Microplastics (MP), (iii) Inorganic fertilizer (IF), (iv) MPIF, (v) Farmyard manure (FM), (vi) MPFM, (vii) Biochar (BC), and (viii) MPBC, arranged in a randomized complete block design (RCBD) with three replicates. Microplastics of polyvinyl chloride (PVC) were applied at a rate of 1.5 tons ha-¹, and all fertilizers were applied at the recommended dose of 90 kg N ha-¹. Soil sampling was done before sowing and after harvesting the sorghum, with samples analyzed for chemical properties and microbial biomass. Crop growth and yield attributes were measured. In a parallel pot experiment, NH₃ emissions were measured using passive flux samplers over 72 hours following the application of treatments similar to those used in the field experiment. Application of MPFM, MPBC and MPIF reduced soil mineral nitrogen by 8, 20 and 38% compared to their sole treatments, respectively. Microbial biomass carbon (MBC) was reduced by 19, 25 and 59% in MPIF, MPBC and MPFM as compared to their sole application, respectively. Similarly, the respective reduction in microbial biomass nitrogen (MBN) was 10, 27 and 66%. The toxicity of microplastics was mitigated by MPFM and MPBC, each with only a 5% reduction in grain yield of sorghum relative to their sole treatments. The differences in nitrogen uptake between BC vs. MPBC, FM vs. MPFM, and IF vs. MPIF were 8, 10, and 12 kg N ha-¹, respectively, indicating that organic fertilizers mitigate microplastic toxicity in the soil. NH₃ emission was reduced by 5, 11 and 20% after application of MPFM, MPBC and MPIF than their sole treatments, respectively. The study concludes that organic fertilizers such as FM and BC can effectively mitigate the toxicity of microplastics in soil, leading to improved crop growth and yield.

Keywords: microplastics, soil characteristics, crop n uptake, biochar, NH₃ emissions

Procedia PDF Downloads 18

Authors: Patricia Portugal Marques de Carvalho Lourenco

Abstract:

Big Bang is like a dirty martini embroiled in a stew of personal individual scandals that have rocked the group’s image and perception, from G-Dragon’s and T.O.P. marijuana episodes in 2011 and 2016, respectively, to Daesung’s building illicit entertainment activities in 2018to the Burning Sun shebang that led to the Titanic sink of Big Bang’s youngest member Seungri in 2019 and the positive sentiment migration to the antithetical side. BTS, on the other hand, are like a martini, clear, clean, attracting as many crowds to their performances and online content as the Pope attracts believers to Sunday Mass in the Vatican, as exemplified by their latest MVs. Big Bang’s 2022 Still Life achieved 16.4 million views on Youtube in 24hours, whilst BTS Permission to Dance achieved 68.5 million in the same period of time. The difference is significant when added Big Bang’s and BTS overall award wins, a total of 117 in contrast to 460. Both groups are uniquely talented and exceptional performers that have been contributing greatly to the dissemination of Korean Pop Music on a global scale in their own inimitable ways. Both are exceptional in their own right and while the artists cannot, ought not, should not be compared for the grave injustice made in comparing one individual planet with one solar system, a contrast is merited and hence done. The reality, nonetheless, is about disengagement from a group that lives life humanly, learning and evolving with each challenge and mistake without a clean, perfect tag attached to it, demonstrating not only an inability to disassociate the person from the artist and the music but also an inability to understand the difference between a private and public life.

Keywords: K-Pop, big bang, BTS, music, public image, entertainment, korean entertainment

Procedia PDF Downloads 83

Authors: S. Masoud Barakati, Mohsen Rahmani Haredasht

Abstract:

Recently, the use of T-type nested neutral point clamped (T-NNPC) converter has increased in medium voltage applications. However, the T-NNPC converter architecture's reliability and continuous operation are at risk by including semiconductor switches. Semiconductor switches are a prone option for open-circuit faults. As a result, fault-tolerant converters are required to improve the system's reliability and continuous functioning. This study's primary goal is to provide a fault-tolerant T-NNPC converter configuration. In the proposed design utilizing the cold reservation approach, a redundant phase is considered, which replaces the faulty phase once the fault is diagnosed in each phase. The suggested fault-tolerant configuration can be easily implemented in practical applications due to the use of a simple PWM control mechanism. The performance evaluation of the proposed configuration under different scenarios in the MATLAB-Simulink environment proves its efficiency.

Keywords: T-type nested neutral point clamped converter, reliability, continuous operation, open-circuit faults, fault-tolerant converters

Procedia PDF Downloads 96

Authors: Nina Penkova, Kalin Krumov, Liliana Zashcova, Ivan Kassabov

Abstract:

The insulating glass units (IGU) are widely used in the advanced and renovated buildings in order to reduce the energy for heating and cooling. Rules for the choice of IGU to ensure energy efficiency and thermal comfort in the indoor space are well known. The existing of internal loads - gage or vacuum pressure in the hermetized gas space, requires additional attention at the design of the facades. The internal loads appear at variations of the altitude, meteorological pressure and gas temperature according to the same at the process of sealing. The gas temperature depends on the presence of coatings, coating position in the transparent multi-layer system, IGU geometry and space orientation, its fixing on the facades and varies with the climate conditions. An algorithm for modeling and numerical simulation of thermal fields and internal pressure in the gas cavity at insulating glass units as function of the meteorological conditions is developed. It includes models of the radiation heat transfer in solar and infrared wave length, indoor and outdoor convection heat transfer and free convection in the hermetized gas space, assuming the gas as compressible. The algorithm allows prediction of temperature and pressure stratification in the gas domain of the IGU at different fixing system. The models are validated by comparison of the numerical results with experimental data obtained by Hot-box testing. Numerical calculations and estimation of 3D temperature, fluid flow fields, thermal performances and internal loads at IGU in window system are implemented.

Keywords: insulating glass units, thermal loads, internal pressure, CFD analysis

Procedia PDF Downloads 259

Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

Abstract:

Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: augmented reality, e-learning, marker-based, monitor-based

Procedia PDF Downloads 208

Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

Abstract:

Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

Procedia PDF Downloads 103

Authors: S. Ghosh, L. Ramos, A. N. Kouamé, A.-L. Teillout, H. Remita

Abstract:

Catalytic materials have attracted continuous attention due to their promising applications in a variety of energy and environmental applications including clean energy, energy conversion and storage, purification and separation, degradation of pollutants and electrochemical reactions etc. With the advanced synthetic technologies, polymer nanostructures and nanocomposites can be directly synthesized through soft template mediated approach using swollen hexagonal mesophases and modulate the size, morphology, and structure of polymer nanostructures. As an alternative to conventional catalytic materials, one-dimensional PDPB polymer nanostructures shows high photocatalytic activity under visible light for the degradation of pollutants. These photocatalysts are very stable with cycling. Transmission electron microscopy (TEM), and AFM-IR characterizations reveal that the morphology and structure of the polymer nanostructures do not change after photocatalysis. These stable and cheap polymer nanofibers and metal polymer nanocomposites are easy to process and can be reused without appreciable loss of activity. The polymer nanocomposites formed via one pot chemical redox reaction with 3.4 nm Pd nanoparticles on poly(diphenylbutadiyne) (PDPB) nanofibers (30 nm). The reduction of Pd (II) ions is accompanied by oxidative polymerization leading to composites materials. Hybrid Pd/PDPB nanocomposites used as electrode materials for the electrocatalytic oxidation of ethanol without using support of proton exchange Nafion membrane. Hence, these conducting polymer nanofibers and nanocomposites offer the perspective of developing a new generation of efficient photocatalysts for environmental protection and in electrocatalysis for fuel cell applications.

Keywords: conducting polymer, swollen hexagonal mesophases, solar photocatalysis, electrocatalysis, water depollution

Procedia PDF Downloads 368

Authors: Sweta Pandey, Samridhi Dhyani, Susmita Chaudhuri

Abstract:

Klebsiella pneumoniae causes a wide range of infections, including urinary tract infections, sepsis, bacteremia, pneumonia, and liver abscesses. The emergence of multi-drug resistance in this bacterium led to a major setback for clinical management. WHO also endorsed a need for finding alternative therapy to antibiotics for the treatment of these infections. Development of vaccines and passive antibody therapy has been proven as a potent alternative to antibiotics in the case of MDR, XDR, and PDR Klebsiella infections. Siderophore receptors have been demonstrated to be overexpressed for the internalization of iron siderophore complexes during infections in most Gram-negative bacteria. For the present study, immune response to siderophore receptors to establish this protein as a potential immunogen for the development of therapeutic leads was explored. Clinical strains of Klebsiella pneumoniae were grown in iron-deficient conditions, and the iron-regulated outer membrane proteins were extracted and characterized through mass spectrometry for specific identification. The gene for identified protein was cloned in pET- 28a vector and expressed in E. coli. The native protein and the recombinant protein were isolated and purified and used as antigens for the generation of immune response in BALB/c mice. The native protein of Klebsiella pneumoniae grown in iron-deficient conditions was identified as FepA (Ferrienterobactin receptor) and other siderophore receptors. This 80 kDa protein generated an immune response in BALB/c mice. The antiserum from mice after subsequent booster doses was collected and showed binding with FepA protein in western blot and phagocytic uptake of the K. pneumoniae in the presence antiserum from immunized mice also observed from the animal studies after bacterial challenge post immunisation in mice have shown bacterial clearance. The antiserum from mice showed binding and clearance of the Klebsiella pneumoniae bacteria in vitro and in vivo. These antigens used for generating an active immune response in mice can further be used for therapeutic monoclonal antibody development against Klebsiella pneumoniae infections.

Keywords: antiserum, FepA, Klebsiella pneumoniae, multi drug resistance, siderophore receptor

Procedia PDF Downloads 84

Authors: Qiang Zhang, Chun Yuan

Abstract:

Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

Procedia PDF Downloads 384

Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

Abstract:

Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

Procedia PDF Downloads 191

Authors: Seyyed Hossein Alavi, Soudabe Mehri Talarposhti

Abstract:

Passages urban landscape is made up of various components that the component parts of the whole and vice versa has relationships. In today’s cities, we have not seen a dual relationship and only one side of the equation which is the relationships of the component parts are considered. However, the effect of the component to whole is stronger and also longer. This means that every time the outer shell of the building was constructed instant impact on the viewers while it takes a long time to understand the impact of the building in its environment and basically, it seems city portrait has the sensory and untouchable effect on observer. Today, building facades are designated individually and in isolation from the context. Designers are familiar with the details of the facade, but they are not informed with the science of combination and its impact on portrait. The importance of city and also more important than that, the city portrait haven’t confirmed for those involved in the building and authorities and the construction been changed to a market for more glaring taste of designers and attracting more business and the city and its landscape has been forgotten. This essay is an attempt to collect a part of the principles and definitions needed on perspective issues and portrait, and it is hoped that it will open arena for more research and studies in this field and other related fields.

Keywords: facade, urban housing, urban design, sustainable architecture

Procedia PDF Downloads 467

Authors: Baha Hasan, Jan Wikander

Abstract:

This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

Procedia PDF Downloads 293

Authors: Maria Hopkins

Abstract:

Research on student engagement is founded on a desire to improve the quality of online instruction in both course design and delivery. A high level of student engagement is associated with a wide range of educational practices including purposeful student-faculty contact, peer to peer contact, active and collaborative learning, and positive factors such as student satisfaction, persistence, achievement, and learning. By encouraging student engagement, institutions of higher education can have a positive impact on student success that leads to retention and degree completion. The current research presents the results of an online student engagement survey which support faculty teaching practices to maximize the learning experience for online students. The ‘Indicators of Engaged Learning Online’ provide a framework that measures level of student engagement. Social constructivism and collaborative learning form the theoretical basis of the framework. Social constructivist pedagogy acknowledges the social nature of knowledge and its creation in the minds of individual learners. Some important themes that flow from social constructivism involve the importance of collaboration among instructors and students, active learning vs passive consumption of information, a learning environment that is learner and learning centered, which promotes multiple perspectives, and the use of social tools in the online environment to construct knowledge. The results of the survey indicated themes that emphasized the importance of: Interaction among peers and faculty (collaboration); Timely feedback on assignment/assessments; Faculty participation and visibility; Relevance and real-world application (in terms of assignments, activities, and assessments); and Motivation/interest (the need for faculty to motivate students especially those that may not have an interest in the coursework per se). The qualitative aspect of this student engagement study revealed what instructors did well that made students feel engaged in the course, but also what instructors did not do well, which could inform recommendations to faculty when expectations for teaching a course are reviewed. Furthermore, this research provides evidence for the connection between higher student engagement and persistence and retention in online programs, which supports our rationale for encouraging student engagement, especially in the online environment because attrition rates are higher than in the face-to-face environment.

Keywords: instructional design, learning effectiveness, online learning, student engagement

Procedia PDF Downloads 278

Authors: Javier Carroquino, Nieves García-Casarejos, Pilar Gargallo

Abstract:

Climate change, depletion of non-renewable resources in the current energies, pollution from them, the greater ecological awareness of the population, are factors that suggest the change of energy sources in business. The agri-food industry is a growth sector, concerned about product innovation, process and with a clear awareness of what climate change may mean for it. This sector is supposed to have a high receptivity to the implementation of clean energy, as this favors not only the environment but also the essence of its business. This work, through surveys, aims to know the willingness of Spanish wineries to implement renewable energies in their vineyards, as well as the limitations they perceive for their implementation. This questionnaire allows the characterization of the sector in terms of its geographical typologies, their activity levels, their perception of environmental issues, the degree of implementation of measures to mitigate climate change and improve energy efficiency, and its uses and energy consumption. The analysis of data proves that the penetration of renewable energies is still at low levels, being the most used energies, solar thermal, photovoltaic and biomass. The initial investment seems to be at the origin of the lack of implantation of this type of energy in the wineries, and not so much the costs of operations and maintenance. The environmental management of the wineries is still at an embryonic stage within the company's organization chart, because these services are either outsourced or, if technicians are available, they are not exclusively dedicated to these tasks. However, there is a strong environmental awareness, as evidenced by the number of climate change mitigation and energy efficiency measures already adopted. The gap between high awareness and low achievement is probably due to the lack of knowledge about how to do it or the perception of a high cost.

Keywords: survey, renewable energy, winery, Spanish case

Procedia PDF Downloads 241

Authors: Pedro Esteban

Abstract:

Most installations nowadays are exposed to many power quality problems, and they also face numerous challenges to comply with grid code and energy efficiency requirements. The reason behind this is that they are not designed to support nonlinear, non-balanced, and variable loads and generators that make up a large percentage of modern electric power systems. These problems and challenges become especially critical when designing green buildings and smart cities. These problems and challenges are caused by equipment that can be typically found in these installations like variable speed drives (VSD), transformers, lighting, battery chargers, double-conversion UPS (uninterruptible power supply) systems, highly dynamic loads, single-phase loads, fossil fuel generators and renewable generation sources, to name a few. Moreover, events like capacitor switching (from existing capacitor banks or passive harmonic filters), auto-reclose operations of transmission and distribution lines, or the starting of large motors also contribute to these problems and challenges. Active power filters (APF) are one of the fastest-growing power electronics technologies for solving power quality problems and meeting grid code and energy efficiency requirements for a wide range of segments and applications. They are a high performance, flexible, compact, modular, and cost-effective type of power electronics solutions that provide an instantaneous and effective response in low or high voltage electric power systems. They enable longer equipment lifetime, higher process reliability, improved power system capacity and stability, and reduced energy losses, complying with most demanding power quality and energy efficiency standards and grid codes. There can be found several types of active power filters, including active harmonic filters (AHF), static var generators (SVG), active load balancers (ALB), hybrid var compensators (HVC), and low harmonic drives (LHD) nowadays. All these devices can be used in applications in Smart Cities bringing several technical and economic benefits.

Keywords: power quality improvement, energy efficiency, grid code compliance, green buildings, smart cities

Procedia PDF Downloads 100

Authors: L. Vafaei, McDominic Eze

Abstract:

The performance of thermal energy in homes and buildings is a significant factor in terms of energy efficiency of a building. In a large sense, the performance of thermal energy is dependent on many factors of which the amount of thermal insulation is at one end a considerable factor, as likewise the essence of mass and the wall thickness and also the thermal resistance of wall material. This study is aimed at illustrating the different wall system in Turkish Republic of North Cyprus (TRNC), acknowledge the problem and suggest a solution through comparing the effect of thermal radiation two model rooms- L1 (Ytong wall) and L2 (heat insulated wall using stone wool) set up for experimentation. The model room has four face walls. The study consists of two stage, the first test is to access the effect of solar radiation for south facing wall and the second stage is to test the thermal performance of Ytong and heat insulated wall, the effects of climatic condition during winter. The heat insulated wall contains material hollow brick, stone wool, and gypsum while the Ytong wall contains cement concrete, for the outer surface and the inner surface and Ytong stone. The total heat of the wall was determined, 7T-Type thermocouple was used with a data logger system to record the data, temperature change recorded at an interval of 10 minutes. The result obtained was that Ytong wall save more energy than the heat insulated wall at night while heat insulated wall saves energy during the day when intensity is at maximum.

Keywords: heat insulation, hollow bricks, south facing, Ytong bricks wall

Procedia PDF Downloads 250

Authors: A. Rong, P. B. Luh, R. Lahdelma

Abstract:

High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

Procedia PDF Downloads 351

Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

Abstract:

Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

Procedia PDF Downloads 56

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

Procedia PDF Downloads 28