Search results for: Wireless Sensor Network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6171

Search results for: Wireless Sensor Network

2361 Bread-Making Properties of Rice Flour Dough Using Fatty Acid Salt

Authors: T. Hamaishi, Y. Morinaga, H. Morita

Abstract:

Introduction: Rice consumption in Japan has decreased, and Japanese government has recommended use of rice flour in order to expand the consumption of rice. There are two major protein components present in flour, called gliadin and glutenin. Gluten forms when water is added to flour and is mixed. As mixing continues, glutenin interacts with gliadin to form viscoelastic matrix of gluten. Rice flour bread does not expand as much as wheat flour bread. Because rice flour is not included gluten, it cannot construct gluten network in the dough. In recent years, some food additives have been used for dough-improving agent in bread making, especially surfactants has effect in order to improve dough extensibility. Therefore, we focused to fatty acid salt which is one of anionic surfactants. Fatty acid salt is a salt consist of fatty acid and alkali, it is main components of soap. According to JECFA(FAO/WHO Joint Expert Committee on Food Additives), salts of Myristic(C14), Palmitic(C16) and Stearic(C18) could be used as food additive. They have been evaluated ADI was not specified. In this study, we investigated to improving bread-making properties of rice flour dough adding fatty acid salt. Materials and methods: The sample of fatty acid salt is myristic (C14) dissolved in KOH solution to a concentration of 350 mM and pH 10.5. Rice dough was consisted of 100 g of flour using rice flour and wheat gluten, 5 g of sugar, 1.7 g of salt, 1.7g of dry yeast, 80 mL of water and fatty acid salt. Mixing was performed for 500 times by using hand. The concentration of C14K in the dough was 10 % relative to flour weight. Amount of gluten in the dough was 20 %, 30 % relative to flour weight. Dough expansion ability test was performed to measure physical property of bread dough according to the methods of Baker’s Yeast by Japan Yeast Industry Association. In this test, 150 g of dough was filled from bottom of the cylinder and fermented at 30 °C,85 % humidity for 120 min on an incubator. The height of the expansion in the dough was measured and determined its expansion ability. Results and Conclusion: Expansion ability of rice dough with gluten content of 20 %, 30% showed 316 mL, 341 mL for 120 min. When C14K adding to the rice dough, dough expansion abilities were 314 mL, 368 mL for 120 min, there was no significant difference. Conventionally it has been known that the rice flour dough contain gluten of 20 %. The considerable improvement of dough expansion ability was achieved when added C14K to wheat flour. The experimental result shows that c14k adding to the rice dough with gluten content more than 20 % was not improving bread-making properties. In conclusion, rice bread made with gluten content more than 20 % without C14K has been suggested to contribute to the formation of the sufficient gluten network.

Keywords: expansion ability, fatty acid salt, gluten, rice flour dough

Procedia PDF Downloads 244
2360 Effect of Rice Cultivars and Water Regimes Application as Mitigation Strategy for Greenhouse Gases in Paddy Fields

Authors: Mthiyane Pretty, Mitsui Toshiake, Aycan Murat, Nagano Hirohiko

Abstract:

Methane (CH₄) is one of the most dangerous greenhouse gases (GHG) emitted into the atmosphere by terrestrial ecosystems, with a global warming potential (GWP) 25-34 times that of CO2 on a centennial scale. Paddy rice cultivations are a major source of methane emission and is the major driving force for climate change. Thus, it is necessary to find out GHG emissions mitigation strategies from rice cultivation. A study was conducted at Niigata University. And the prime objective of this research was to determine the effects of rice varieties CH4 lowland (NU1, YNU, Nipponbare, Koshihikari) and upland (Norin 1, Norin 24, Hitachihatamochi) japonica rice varieties using different growth media which was paddy field soil and artificial soil. The treatments were laid out in a split plot design. The soil moisture was kept at 40-50% and 70%, respectively. The CH₄ emission rates were determined by collecting air samples using the closed chamber technique and measuring CH₄ concentrations using a gas chromatograph. CH₄ emission rates varied with the growth, growth media type and development of the rice varieties. The soil moisture was monitored at a soil depth of 5–10 cm with an HydraGO portable soil sensor system every three days for each pot, and temperatures were be recorded by a sensitive thermometer. The lowest cumulative CH4 emission rate was observed in Norin 24, particularly under 40 to 50% soil moisture. Across the rice genotypes, 40-50% significantly reduced the cumulative CH4 , followed by irrigation of 70% soil moisture. During the tillering stage, no significant variation in tillering and plant height was observed between and 70% soil moisture. This study suggests that the cultivation of Norin 24 and Norin 1 under 70% soil irrigation could be effective at reducing the CH4 in rice fields.

Keywords: methane, paddy fields, rice varieties, soil moisture

Procedia PDF Downloads 93
2359 Real Estate Trend Prediction with Artificial Intelligence Techniques

Authors: Sophia Liang Zhou

Abstract:

For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

Procedia PDF Downloads 103
2358 Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds

Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

Abstract:

Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

Procedia PDF Downloads 161
2357 Impact of Neuron with Two Dendrites in Heart Behavior

Authors: Kaouther Selmi, Alaeddine Sridi, Mohamed Bouallegue, Kais Bouallegue

Abstract:

Neurons are the fundamental units of the brain and the nervous system. The variable structure model of neurons consists of a system of differential equations with various parameters. By optimizing these parameters, we can create a unique model that describes the dynamic behavior of a single neuron. We introduce a neural network based on neurons with multiple dendrites employing an activation function with a variable structure. In this paper, we present a model for heart behavior. Finally, we showcase our successful simulation of the heart's ECG diagram using our Variable Structure Neuron Model (VSMN). This result could provide valuable insights into cardiology.

Keywords: neural networks, neuron, dendrites, heart behavior, ECG

Procedia PDF Downloads 85
2356 Doped and Co-doped ZnO Based Nanoparticles and their Photocatalytic and Gas Sensing Property

Authors: Neha Verma, Manik Rakhra

Abstract:

Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

Procedia PDF Downloads 155
2355 Bio-Functional Polymeric Protein Based Materials Utilized for Soft Tissue Engineering Application

Authors: Er-Yuan Chuang

Abstract:

Bio-mimetic matters have biological functionalities. This might be valuable in the development of versatile biomaterials. At biological fields, protein-based materials might be components to form a 3D network of extracellular biomolecules, containing growth factors. Also, the protein-based biomaterial provides biochemical and structural assistance of adjacent cells. In this study, we try to prepare protein based biomaterial, which was harvested from living animal. We analyzed it’s chemical, physical and biological property in vitro. Besides, in vivo bio-interaction of the prepared biomimetic matrix was tested in an animal model. The protein-based biomaterial has degradability and biocompatibility. This development could be used for tissue regenerations and be served as platform technologies.

Keywords: protein based, in vitro study, in vivo study, biomaterials

Procedia PDF Downloads 189
2354 Facial Emotion Recognition Using Deep Learning

Authors: Ashutosh Mishra, Nikhil Goyal

Abstract:

A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

Procedia PDF Downloads 231
2353 Active Disturbance Rejection Control for Wind System Based on a DFIG

Authors: R. Chakib, A. Essadki, M. Cherkaoui

Abstract:

This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.

Keywords: doubly fed induction generator (DFIG), active disturbance rejection control (ADRC), vector control, MPPT, extended state observer, back-to-back converter, wind turbine

Procedia PDF Downloads 488
2352 Internet Protocol Television: A Research Study of Undergraduate Students Analyze the Effects

Authors: Sabri Serkan Gulluoglu

Abstract:

The study is aimed at examining the effects of internet marketing with IPTV on human beings. Internet marketing with IPTV is emerging as an integral part of business strategies in today’s technologically advanced world and the business activities all over the world are influences with the emergence of this modern marketing tool. As the population of the Internet and on-line users’ increases, new research issues have arisen concerning the demographics and psychographics of the on-line user and the opportunities for a product or service. In recent years, we have seen a tendency of various services converging to the ubiquitous Internet Protocol based networks. Besides traditional Internet applications such as web browsing, email, file transferring, and so forth, new applications have been developed to replace old communication networks. IPTV is one of the solutions. In the future, we expect a single network, the IP network, to provide services that have been carried by different networks today. For finding some important effects of a video based technology market web site on internet, we determine to apply a questionnaire on university students. Recently some researches shows that in Turkey the age of people 20 to 24 use internet when they buy some electronic devices such as cell phones, computers, etc. In questionnaire there are ten categorized questions to evaluate the effects of IPTV when shopping. There were selected 30 students who are filling the question form after watching an IPTV channel video for 10 minutes. This sample IPTV channel is “buy.com”, it look like an e-commerce site with an integrated IPTV channel on. The questionnaire for the survey is constructed by using the Likert scale that is a bipolar scaling method used to measure either positive or negative response to a statement (Likert, R) it is a common system that is used is the surveys. By following the Likert Scale “the respondents are asked to indicate their degree of agreement with the statement or any kind of subjective or objective evaluation of the statement. Traditionally a five-point scale is used under this methodology”. For this study also the five point scale system is used and the respondents were asked to express their opinions about the given statement by picking the answer from the given 5 options: “Strongly disagree, Disagree, Neither agree Nor disagree, Agree and Strongly agree”. These points were also rates from 1-5 (Strongly disagree, Disagree, Neither disagree Nor agree, Agree, Strongly agree). On the basis of the data gathered from the questionnaire some results are drawn in order to get the figures and graphical representation of the study results that can demonstrate the outcomes of the research clearly.

Keywords: IPTV, internet marketing, online, e-commerce, video based technology

Procedia PDF Downloads 240
2351 The Usefulness and Usability of a Linkedin Group for the Maintenance of a Community of Practice among Hand Surgeons Worldwide

Authors: Vaikunthan Rajaratnam

Abstract:

Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

Procedia PDF Downloads 316
2350 Effect of Swelling Pressure on Drug Release from Polyelectrolyte Micro-Hydrogel Particles

Authors: Mina Boroujerdi, Javad Tavakoli

Abstract:

Hydrogels are extensively studied as matrices for the controlled release of drugs. To evaluate the mobility of embedded molecules, these drug delivery systems are usually characterized by release studies. In this contribution, an electronic device for swelling pressure measurement during drug release from hydrogel network was developed. Also, poly acrylic acid micro particles were prepared for prolonged and sustained controlled acetaminophen release. Effect of swelling pressure on drug release from micro particles studied under different environment pH in order to predict release profile in gastro-intestine medium. Swelling ratio and swelling pressure were measured in different pH.

Keywords: swelling pressure, drug delivery, hydrogel, polyelectrolyte

Procedia PDF Downloads 299
2349 A Visual Analytics Tool for the Structural Health Monitoring of an Aircraft Panel

Authors: F. M. Pisano, M. Ciminello

Abstract:

Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

Procedia PDF Downloads 124
2348 Application of the Discrete-Event Simulation When Optimizing of Business Processes in Trading Companies

Authors: Maxat Bokambayev, Bella Tussupova, Aisha Mamyrova, Erlan Izbasarov

Abstract:

Optimization of business processes in trading companies is reviewed in the report. There is the presentation of the “Wholesale Customer Order Handling Process” business process model applicable for small and medium businesses. It is proposed to apply the algorithm for automation of the customer order processing which will significantly reduce labor costs and time expenditures and increase the profitability of companies. An optimized business process is an element of the information system of accounting of spare parts trading network activity. The considered algorithm may find application in the trading industry as well.

Keywords: business processes, discrete-event simulation, management, trading industry

Procedia PDF Downloads 344
2347 Relation between Electrical Properties and Application of Chitosan Nanocomposites

Authors: Evgen Prokhorov, Gabriel Luna-Barcenas

Abstract:

The polysaccharide chitosan (CS) is an attractive biopolymer for the stabilization of several nanoparticles in acidic aqueous media. This is due in part to the presence of abundant primary NH2 and OH groups which may lead to steric or chemical stabilization. Applications of most CS nanocomposites are based upon the interaction of high surface area nanoparticles (NPs) with different substance. Therefore, agglomeration of NPs leads to decreasing effective surface area such that it may decrease the efficiency of nanocomposites. The aim of this work is to measure nanocomposite’s electrical conductivity phenomena that will allow one to formulate optimal concentrations of conductivity NPs in CS-based nanocomposites. Additionally, by comparing the efficiency of such nanocomposites, one can guide applications in the biomedical (antibacterial properties and tissue regeneration) and sensor fields (detection of copper and nitrate ions in aqueous solutions). It was shown that the best antibacterial (CS-AgNPs, CS-AgNPs-carbon nanotubes) and would healing properties (CS-AuNPs) are observed in nanocomposites with concentrations of NPs near the percolation threshold. In this regard, the best detection limit in potentiometric and impedimetric sensors for detection of copper ions (using CS-AuNPs membrane) and nitrate ions (using CS-clay membrane) in aqueous solutions have been observed for membranes with concentrations of NPs near percolation threshold. It is well known that at the percolation concentration of NPs an abrupt increasing of conductivity is observed due to the presence of physical contacts between NPs; above this concentration, agglomeration of NPs takes place such that a decrease in the effective surface and performance of nanocomposite appear. The obtained relationship between electrical percolation threshold and performance of polymer nanocomposites with conductivity NPs is important for the design and optimization of polymer-based nanocomposites for different applications.

Keywords: chitosan, conductivity nanoparticles, percolation threshold, polymer nanocomposites

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2346 A Horn Antenna Loaded with SIW FSS of Crossed Dipoles

Authors: Ibrahim Mostafa El-Mongy, Abdelmegid Allam

Abstract:

In this article analysis and investigation of the effect of loading a horn antenna with substrate integrated waveguide frequency selective surface (SIW FSS) of crossed dipoles of finite size is presented. It is fabricated on Rogers RO4350 (lossy) of relative permittivity 3.33, thickness 1.524mm and loss tangent 0.004. This structure is called a filtering antenna (filtenna). Basically it is applied for filtering and minimizing the interference and noise in the desired band. The filtration is carried out using a finite SIW FSS of crossed dipoles of overall dimensions 98x58 mm2. The filtration is shown by limiting the transmission bandwidth from 4 GHz (8–12 GHz) to 0.3 GHz (0.955–0.985 GHz). It is simulated using CST MWS and measured using network analyzer. There is a good agreement between the simulated and measured results.

Keywords: antenna, filtenna, frequency-selective surface (FSS), horn antennas

Procedia PDF Downloads 288
2345 Performance Evaluation of the Classic seq2seq Model versus a Proposed Semi-supervised Long Short-Term Memory Autoencoder for Time Series Data Forecasting

Authors: Aswathi Thrivikraman, S. Advaith

Abstract:

The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

Procedia PDF Downloads 155
2344 Online Monitoring of Airborne Bioaerosols Released from a Composting, Green Waste Site

Authors: John Sodeau, David O'Connor, Shane Daly, Stig Hellebust

Abstract:

This study is the first to employ the online WIBS (Waveband Integrated Biosensor Sensor) technique for the monitoring of bioaerosol emissions and non-fluorescing “dust” released from a composting/green waste site. The purpose of the research was to provide a “proof of principle” for using WIBS to monitor such a location continually over days and nights in order to construct comparative “bioaerosol site profiles”. Current impaction/culturing methods take many days to achieve results available by the WIBS technique in seconds.The real-time data obtained was then used to assess variations of the bioaerosol counts as a function of size, “shape”, site location, working activity levels, time of day, relative humidity, wind speeds and wind directions. Three short campaigns were undertaken, one classified as a “light” workload period, another as a “heavy” workload period and finally a weekend when the site was closed. One main bioaerosol size regime was found to predominate: 0.5 micron to 3 micron with morphologies ranging from elongated to elipsoidal/spherical. The real-time number-concentration data were consistent with an Andersen sampling protocol that was employed at the site. The number-concentrations of fluorescent particles as a proportion of total particles counted amounted, on average, to ~1% for the “light” workday period, ~7% for the “heavy” workday period and ~18% for the weekend. The bioaerosol release profiles at the weekend were considerably different from those monitored during the working weekdays.

Keywords: bioaerosols, composting, fluorescence, particle counting in real-time

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2343 A New Method Presentation for Locating Fault in Power Distribution Feeders Considering DG

Authors: Rahman Dashti, Ehsan Gord

Abstract:

In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

Procedia PDF Downloads 401
2342 Effective Energy Saving of a Large Building through Multiple Approaches

Authors: Choo Hong Ang

Abstract:

The most popular approach to save energy for large commercial buildings in Malaysia is to replace the existing chiller plant of high kW/ton to one of lower kW/ton. This approach, however, entails large capital outlay with a long payment period of up to 7 years. This paper shows that by using multiple approaches, other than replacing the existing chiller plant, an energy saving of up to 20 %, is possible. The main methodology adopted was to identify and then plugged all heat ingress paths into a building, including putting up glass structures to prevent mixing of internal air-conditioned air with the ambient environment, and replacing air curtains with glass doors. This methodology could save up to 10 % energy bill. Another methodology was to change fixed speed motors of air handling units (AHU) to variable speed drive (VSD) and changing escalators to motion-sensor type. Other methodologies included reducing heat load by blocking air supply to non-occupied parcels, rescheduling chiller plant operation, changing of fluorescent lights to LED lights, and conversion from tariff B to C1. A case example of Komtar, the tallest building in Penang, is given here. The total energy bill for Komtar was USD2,303,341 in 2016 but was reduced to USD 1,842,927.39 in 2018, a significant saving of USD460,413.86 or 20 %. In terms of kWh, there was a reduction from 18, 302,204.00 kWh in 2016 to 14,877,105.00 kWh in 2018, a reduction of 3,425,099.00 kWh or 18.71 %. These methodologies used were relatively low cost and the payback period was merely 24 months. With this achievement, the Komtar building was awarded champion of the Malaysian National Energy Award 2019 and second runner up of the Asean Energy Award. This experience shows that a strong commitment to energy saving is the key to effective energy saving.

Keywords: chiller plant, energy saving measures, heat ingress, large building

Procedia PDF Downloads 105
2341 Block Mining: Block Chain Enabled Process Mining Database

Authors: James Newman

Abstract:

Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

Procedia PDF Downloads 102
2340 Comparative Study of Ad Hoc Routing Protocols in Vehicular Ad-Hoc Networks for Smart City

Authors: Khadija Raissi, Bechir Ben Gouissem

Abstract:

In this paper, we perform the investigation of some routing protocols in Vehicular Ad-Hoc Network (VANET) context. Indeed, we study the efficiency of protocols like Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector Routing (AODV), Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing convention (OLSR) and Vehicular Multi-hop algorithm for Stable Clustering (VMASC) in terms of packet delivery ratio (PDR) and throughput. The performance evaluation and comparison between the studied protocols shows that the VMASC is the best protocols regarding fast data transmission and link stability in VANETs. The validation of all results is done by the NS3 simulator.

Keywords: VANET, smart city, AODV, OLSR, DSR, OLSR, VMASC, routing protocols, NS3

Procedia PDF Downloads 297
2339 Knowledge Discovery from Production Databases for Hierarchical Process Control

Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

Abstract:

The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system, thus, the proposed solution has been verified. The paper documents how it is possible to apply new discovery knowledge to be used in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: hierarchical process control, knowledge discovery from databases, neural network, process control

Procedia PDF Downloads 481
2338 Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems

Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

Abstract:

In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

Procedia PDF Downloads 656
2337 Factors Affecting Harvested Rain Water Quality and Quantity in Yatta Area, Palestine

Authors: Nibal Al-Batsh, Issam Al-Khatib, Subha Ghannam

Abstract:

Yatta is the study area for this research, located 9 km south of Hebron City in the West Bank in Palestine. It has been connected to a water network since 1974 serving nearly 85% of the households. The water network is old and inadequate to meet the needs of the population. The water supply made available to the area is also very limited, estimated to be around 20 l/c.d. Residents are thus forced to rely on water vendors which supply water with a lower quality compared to municipal water while being 400% more expensive. As a cheaper and more reliable alternative, rainwater harvesting is a common practice in the area, with the majority of the households owning at least one cistern. Rainwater harvesting is of great socio-economic importance in areas where water sources are scarce or polluted. The quality of harvested rainwater used for drinking and domestic purposes in the Yatta area was assessed throughout a year long period. A total of 100 water samples were collected from (50 rainfed cisterns) with an average capacity of 69 m3, adjacent to cement-roof catchment with an average area of 145 m2. Samples were analyzed for a number of parameters including: pH, Alkalinity, Hardness, Turbidity, Total Dissolved Solids (TDS), NO3, NH4, chloride and salinity. Microbiological contents such as Total Coliforms (TC) and Fecal Coliforms (FC) bacteria were also analyzed. Results showed that most of the rainwater samples were within WHO and EPA guidelines set for chemical parameters while revealing biological contamination. The pH values of mixed water ranged from 6.9 to 8.74 with a mean value of 7.6. collected Rainwater had lower pH values than mixed water ranging from 7.00 to 7.57 with a mean of 7.21. Rainwater also had lower average values of conductivity (389.11 µScm-1) compared to that of mixed water (463.74 µScm-1) thus indicating lower values of salinity (0.75%). The largest TDS value measured in rainwater was 316 mg/l with a mean of 199.86 mg /l. As far as microbiological quality is concerned, TC and FC were detected in 99%, 52% of collected rainwater samples, respectively. The research also addressed the impact of different socio-economic attributes on rainwater harvesting using information collected through a survey from the area. Results indicated that the majority of homeowners have the primary knowledge necessary to collect and store water in cisterns. Most of the respondents clean both the cisterns and the catchment areas. However, the research also arrives at a conclusion that cleaning is not done in a proper manner. Results show that cisterns with an operating capacity of 69 m3 would provide sufficient water to get through the dry summer months. However, the catchment area must exceed 146 m2 to produce sufficient water to fill a cistern of this size in a year receiving average precipitation.

Keywords: rainwater harvesting, runoff coefficient, water quality, microbiological contamination

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2336 Fluorescing Aptamer-Gold Nanoparticle Complex for the Sensitive Detection of Bisphenol A

Authors: Eunsong Lee, Gae Baik Kim, Young Pil Kim

Abstract:

Bisphenol A (BPA) is one of the endocrine disruptors (EDCs), which have been suspected to be associated with reproductive dysfunction and physiological abnormality in human. Since the BPA has been widely used to make plastics and epoxy resins, the leach of BPA from the lining of plastic products has been of major concern, due to its environmental or human exposure issues. The simple detection of BPA based on the self-assembly of aptamer-mediated gold nanoparticles (AuNPs) has been reported elsewhere, yet the detection sensitivity still remains challenging. Here we demonstrate an improved AuNP-based sensor of BPA by using fluorescence-combined AuNP colorimetry in order to overcome the drawback of traditional AuNP sensors. While the anti-BPA aptamer (full length or truncated ssDNA) triggered the self-assembly of unmodified AuNP (citrate-stabilized AuNP) in the presence of BPA at high salt concentrations, no fluorescence signal was observed by the subsequent addition of SYBR Green, due to a small amount of free anti-BPA aptamer. In contrast, the absence of BPA did not cause the self-assembly of AuNPs (no color change by salt-bridged surface stabilization) and high fluorescence signal by SYBP Green, which was due to a large amount of free anti-BPA aptamer. As a result, the quantitative analysis of BPA was achieved using the combination of absorption of AuNP with fluorescence intensity of SYBR green as a function of BPA concentration, which represented more improved detection sensitivity (as low as 1 ppb) than did in the AuNP colorimetric analysis. This method also enabled to detect high BPA in water-soluble extracts from thermal papers with high specificity against BPS and BPF. We suggest that this approach will be alternative for traditional AuNP colorimetric assays in the field of aptamer-based molecular diagnosis.

Keywords: bisphenol A, colorimetric, fluoroscence, gold-aptamer nanobiosensor

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2335 ELectromagnetic-Thermal Coupled Analysis of PMSM with Cooling Channel

Authors: Hyun-Woo Jun, Tae-Chul Jeong, Huai-Cong Liu, Ju Lee

Abstract:

The paper presents the electromagnetic-thermal flow coupled analysis of permanent magnet synchronous motor (PMSM) which has cooling channel in stator core for forced air cooling. Unlike the general PMSM design, to achieve ohmic loss reduction for high efficiency, cooling channel actively used in the stator core. Equivalent thermal network model was made to analyze the effect of the formation of the additional flow path in the core. According to the shape and position changing of the channel design, electromagnetic-thermal coupled analysis results were reviewed.

Keywords: coupled problems, electric motors, equivalent circuits, fluid flow, thermal analysis

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2334 Analysis of Storm Flood in Typical Sewer Networks in High Mountain Watersheds of Colombia Based on SWMM

Authors: J. C. Hoyos, J. Zambrano Nájera

Abstract:

Increasing urbanization has led to changes in the natural dynamics of watersheds, causing problems such as increases in volumes of runoff, peak flow rates, and flow rates so that the risk of storm flooding increases. Sewerage networks designed 30 – 40 years ago don’t account for these increases in flow volumes and velocities. Besides, Andean cities with high slopes worsen the problem because velocities are even higher not allowing sewerage network work and causing cities less resilient to landscape changes and climatic change. In Latin America, especially Colombia, this is a major problem because urban population at late XX century was more than 70% is in urban areas increasing approximately in 790% in 1940-1990 period. Thus, it becomes very important to study how changes in hydrological behavior affect hydraulic capacity of sewerage networks in Andean Urban Watersheds. This research aims to determine the impact of urbanization in high-sloped urban watersheds in its hydrology. To this end it will be used as study area experimental urban watershed named Palogrande-San Luis watershed, located in the city of Manizales, Colombia. Manizales is a city in central western Colombia, located in Colombian Central Mountain Range (part of Los Andes Mountains) with an abrupt topography (average altitude is 2.153 m). The climate in Manizales is quite uniform, but due to its high altitude it presents high precipitations (1.545 mm/year average) with high humidity (83% average). Behavior of the current sewerage network will be reviewed by the hydraulic model SWMM (Storm Water Management Model). Based on SWMM the hydrological response of urban watershed selected will be evaluated under the design storm with different frequencies in the region, such as drainage effect and water-logging, overland flow on roads, etc. Cartographic information was obtained from a Geographic Information System (GIS) thematic maps of the Institute of Environmental Studies of the Universidad Nacional de Colombia and the utility Aguas de Manizales S.A. Rainfall and streamflow data is obtained from 4 rain gages and 1 stream gages. This information will allow determining critical issues on drainage systems design in urban watershed with very high slopes, and which practices will be discarded o recommended.

Keywords: land cover changes, storm sewer system, urban hydrology, urban planning

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2333 Modelling Vehicle Fuel Consumption Utilising Artificial Neural Networks

Authors: Aydin Azizi, Aburrahman Tanira

Abstract:

The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

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2332 Promoting Innovation Pedagogy in a Capacity Building Project in Indonesia

Authors: Juha Kettunen

Abstract:

This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

Procedia PDF Downloads 286