Search results for: kinematic global positioning system

Authors: Sudipto Sarkar, Anamika Paul

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Pseudoplastic (n<1, n is the power index) fluids have great importance in food, pharmaceutical and chemical process industries which require a lot of attention. Unfortunately, due to its complex flow behavior inadequate research works can be found even in laminar flow regime. A practical problem is solved in the present research work by numerical simulation where we tried to control the vortex shedding from a square cylinder using a horizontal splitter plate placed at the downstream flow region. The position of the plate is at the centerline of the cylinder with varying distance from the cylinder to calculate the critical gap-ratio. If the plate is placed inside this critical gap, the vortex shedding from the cylinder suppressed completely. The Reynolds number considered here is in unsteady laminar vortex shedding regime, Re = 100 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid). Flow behavior has been studied for three different gap-ratios (G/a = 2, 2.25 and 2.5, where G is the gap between cylinder and plate) and for a fluid with three different flow behavior indices (n =1, 0.8 and 0.5). The flow domain is constructed using Gambit 2.2.30 and this software is also used to generate the mesh and to impose the boundary conditions. For G/a = 2, the domain size is considered as 37.5a × 16a with 316 × 208 grid points in the streamwise and flow-normal directions respectively after a thorough grid independent study. Fine and equal grid spacing is used close to the geometry to capture the vortices shed from the cylinder and the boundary layer developed over the flat plate. Away from the geometry meshes are unequal in size and stretched out. For other gap-ratios, proportionate domain size and total grid points are used with similar kind of mesh distribution. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain boundary conditions are used for the simulation. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. Discretized forms of fully conservative 2-D unsteady Navier Stokes equations are then solved by Ansys Fluent 14.5. SIMPLE algorithm written in finite volume method is selected for this purpose which is a default solver inculcate in Fluent. The results obtained for Newtonian fluid flow agree well with previous works supporting Fluent’s usefulness in academic research. A thorough analysis of instantaneous and time-averaged flow fields are depicted both for Newtonian and pseudoplastic fluid flow. It has been observed that as the value of n reduces the stretching of shear layers also reduce and these layers try to roll up before the plate. For flow with high pseudoplasticity (n = 0.5) the nature of vortex shedding changes and the value of critical gap-ratio reduces. These are the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: CFD, pseudoplastic fluid flow, wake-boundary layer interactions, critical gap-ratio

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Authors: Zhiqiang Yan, Chen Fan, Beicheng Xia

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Urban lakes play an invaluable role in urban water systems such as flood control, landscape, entertainment, and energy utilization, and have suffered from severe eutrophication over the past few years. To investigate the ecological response of main aquatic species and system stability to chlorine interference in shallow urban lakes, a mini system dynamic model, based on the competition and predation of main aquatic species and TP circulation, was developed. The main species of submerged macrophyte, phytoplankton, zooplankton, benthos and TP in water and sediment were simulated as variables in the model with the interference of chlorine which effect function was attenuation equation. The model was validated by the data which was investigated in the Lotus Lake in Guangzhou from October 1, 2015 to January 31, 2016. Furthermore, the eco-exergy was used to analyze the change in complexity of the shallow urban lake. The results showed the correlation coefficient between observed and simulated values of all components presented significant. Chlorine showed a significant inhibitory effect on Microcystis aeruginosa，Rachionus plicatilis, Diaphanosoma brachyurum Liévin and Mesocyclops leuckarti (Claus).The outbreak of Spiroggra spp. inhibited the growth of Vallisneria natans (Lour.) Hara, caused a gradual decrease of eco-exergy, reflecting the breakdown of ecosystem internal equilibria. It was concluded that the study gives important insight into using chlorine to achieve eutrophication control and understand mechanism process.

Keywords: system dynamic model, urban lake, chlorine, eco-exergy

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Authors: Anil S. Khopkar, Umesh N. Soni

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Surge voltage arises in the system either by switching operations of heavy load or by natural lightning. Surge voltages cause significant failure of power system equipment if adequate protection is not provided. A Surge Arrester is a device connected to a power system to protect the equipment against surge voltages. To protect the transformers against surge voltages, metal oxide surge arresters (MOSA) are connected across each terminal. Basic Insulation Level (BIL) has been defined in national and international standards of transformers based on their voltage rating. While designing transformer insulation, the BIL of the transformer, Surge arrester ratings and its operating voltage have to be considered. However, the performance of transformer insulation largely depends on the ratings of the surge arrester connected, the location of the surge arrester, the margin considered in the insulation design, the quantity of surge voltage strike, etc. This paper demonstrates the role of Surge arresters in the protection of transformers against over-voltage, transformer insulation design, optimum location of surge arresters and their connection lead length, Insulation coordination for transformer, protection margin in BIL and methods of protection of transformers against surge voltages, in detail.

Keywords: surge voltage, surge arresters, insulation coordination, protection margin

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Authors: Zhala Ahmad, Zainab Lazim, Haider Hamzah

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Bacterial resistance is a pressing global health issue, with multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) strains to pose a serious threat. In this context, researchers are investigating effective, safe, and affordable metabolites to combat these pathogens. This study focuses on gum essential oil (GEO) extracted from Pistacia atlantica and its activity and the mechanism of action against XDR Gram-negative Acinetobacter baumannii. GEO was extracted by hydrodistillation and analyzed using GC-MS. Eleven A. baumannii isolates were collected from the ward environment of Burn and Plastic Surgery Hospital in Al Sulaymaniyah City, Iraq. They were identified using the VITEK 2 system, 16S rRNA gene, and confirmed with the blaₒₓₐ₋₅₁ gene; A. baumannii ATCC 19606 was used as a reference strain. The isolates were identified as resistant to twelve different antibiotics spanning six distinct antibiotic classes while showing susceptibility to tetracycline and trimethoprim. Over 40 chemical constituents were detected in the gum's essential oils, with α-pinene being the most abundant. GEO was found to inhibit the growth of A. baumannii isolates; the minimum inhibitory concentration (MIC) of GEO was 2.5 µl/ml. GEO induced protein leakage, phosphate, and potassium ion efflux, distorted cell morphology, and cell death in the tested bacteria. GEO exhibited bacterial clearance and anti-adhesion activity using Band-Aids. This study's findings suggest that GEO could be used as a potential alternative treatment for infectious diseases caused by XRD pathogens, shedding further light on the importance of GEO in biomedical applications. Future studies must focus on generating clinically feasible sources of GEO for testing in small animal models before proceeding to human trials, ensuring safe and effective translation from the laboratory to the clinic.

Keywords: antibiotic resistance, Acinetobacter baumannii, essential oils, Pistacia atlantica, alpha-pinene

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Jéssica Bernegossi, Lívia Nordi Dovigo, Marlus Chorilli

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Mucoadhesive liquid crystalline systems are emerging how delivery systems for oral cavity. These systems are interesting since they facilitate the targeting of medicines and change the release enabling a reduction in the number of applications made by the patient. The buccal mucosa is permeable besides present a great blood supply and absence of first pass metabolism, it is a good route of administration. It was developed two systems liquid crystals utilizing as surfactant the ethyl alcohol ethoxylated and propoxylated (30%) as oil phase the oleic acid (60%), and the aqueous phase (10%) dispersion of polymer polyethylenimine (0.5%) or dispersion of polymer poloxamer 407 (16%), with the intention of applying the buccal mucosa. Initially, was performed for characterization of systems the conference by polarized light microscopy and rheological analysis. For the preparation of the systems the components described was added above in glass vials and shaken. Then, 30 and 100% artificial saliva were added to each prepared formulation so as to simulate the environment of the oral cavity. For the verification of the system structure, aliquots of the formulations were observed in glass slide and covered with a coverslip, examined in polarized light microscope (PLM) Axioskop - Zeizz® in 40x magnifier. The formulations were also evaluated for their rheological profile Rheometer TA Instruments®, which were obtained rheograms the selected systems employing fluency mode (flow) in temperature of 37ºC (98.6ºF). In PLM, it was observed that in formulations containing polyethylenimine and poloxamer 407 without the addition of artificial saliva was observed dark-field being indicative of microemulsion, this was also observed with the formulation that was increased with 30% of the artificial saliva. In the formulation that was increased with 100% simulated saliva was shown to be a system structure since it presented anisotropy with the presence of striae being indicative of hexagonal liquid crystalline mesophase system. Upon observation of rheograms, both systems without the addition of artificial saliva showed a Newtonian profile, after addition of 30% artificial saliva have been given a non-Newtonian behavior of the pseudoplastic-thixotropic type and after adding 100% of the saliva artificial proved plastic-thixotropic. Furthermore, it is clearly seen that the formulations containing poloxamer 407 have significantly larger (15-800 Pa) shear stress compared to those containing polyethyleneimine (5-50 Pa), indicating a greater plasticity of these. Thus, it is possible to observe that the addition of saliva was of interest to the system structure, starting from a microemulsion for a liquid crystal system, thereby also changing thereby its rheological behavior. The systems have promising characteristics as controlled release systems to the oral cavity, as it features good fluidity during its possible application and greater structuring of the system when it comes into contact with environmental saliva.

Keywords: liquid crystal system, poloxamer 407, polyethylenimine, rheology

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Shengjun Zhang, Xu Cheng, Feng Shen

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The passive containment cooling system (PCCS) is widely used in the advanced nuclear reactor in case of the loss of coolant accident (LOCA) and the main steam line break accident (MSLB). The internal heat exchanger is one of the most important equipment in the PCCS and its heat transfer characteristic determines the performance of the system. In this investigation, a theoretical model is presented for predicting the heat and mass transfer which accompanies condensation. The conduction through the liquid condensate is considered and the interface temperature is defined by iteration. The parameter in the correlation to describe the suction effect should be further determined through experimental data.

Keywords: non-condensable gas, condensation, heat transfer coefficient, heat and mass transfer analogy

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Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

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Authors: Ravi Nandu, Kuldeep Singh

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A helmet is a protective layer that is worn in order to prevent head injury. Helmet is the most important safety gear for two wheeler riders. However, due to carelessness of people, less importance toward safety, lot of causalities is every year. According to National Crime Records Bureau (NCRB) two wheelers claimed 92 lives every day out of which most were due to helmetless drive. The system design will be such that without wearing the helmet the rider cannot start two wheelers. The helmet will be connected to vehicle key ignition systems which will be electronically controlled. The smart helmet will be having proximity sensor fitted inside it, which will act as our switch for ignition and further with wireless connection the helmet sensor circuit will be connected to the vehicle ignition system.

Keywords: helmet, proximity sensor, microcontroller, head injury

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Authors: Adel A. Ghoneim

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Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 134

Authors: Dawid Sołoducha, Tomasz Borowski, Marian Kordas, Rafał Rakoczy

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The magnetic field in the past few years became an important part of many studies. Magnetic field (MF) may be used to affect the process in many ways; for example, it can be used as a factor to stabilize the system. We can use MF to steer the operation, to activate or inhibit the process, or even to affect the vital activity of microorganisms. Using various types of magnetic field generators is always connected with the delivery of some heat to the system. Heat transfer is a very important phenomenon; it can influence the process positively and negatively, so it’s necessary to measure heat stream transferred from the place of generation and prevent negative influence on the operation. The aim of the presented work was to apply various types of magnetic fields and to measure heat transfer phenomena. The results were obtained by continuous measurement at several measuring points with temperature probes. Results were compilated in the form of temperature profiles. The study investigated the undetermined heat transfer in a custom system equipped with a magnetic field generator. Experimental investigations are provided for the explanation of the influence of the various type of magnetic fields on the heat transfer process. The tested processes are described by means of the criteria which defined heat transfer intensification under the action of magnetic field.

Keywords: heat transfer, magnetic field, undetermined heat transfer, temperature profile

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Geothermal reservoirs (GTRs) have garnered global recognition as a sustainable energy source. The Thermo-Hydro-Mechanical-Chemical (THMC) integration coupling proves to be a practical and effective method for optimizing production in GTRs. The study outcomes demonstrate that THMC coupling serves as a versatile and valuable tool, offering in-depth insights into GTRs and enhancing their operational efficiency. This is achieved through temperature analysis and pressure changes and their impacts on mechanical properties, structural integrity, fracture aperture, permeability, and heat extraction efficiency. Moreover, THMC coupling facilitates potential benefits assessment and risks associated with different geothermal technologies, considering the complex thermal, hydraulic, mechanical, and chemical interactions within the reservoirs. However, THMC-coupling utilization in GTRs presents a multitude of challenges. These challenges include accurately modeling and predicting behavior due to the interconnected nature of processes, limited data availability leading to uncertainties, induced seismic events risks to nearby communities, scaling and mineral deposition reducing operational efficiency, and reservoirs' long-term sustainability. In addition, material degradation, environmental impacts, technical challenges in monitoring and control, accurate assessment of resource potential, and regulatory and social acceptance further complicate geothermal projects. Addressing these multifaceted challenges is crucial for successful geothermal energy resources sustainable utilization. This paper aims to illuminate the challenges and opportunities associated with THMC coupling in enhanced geothermal systems. Practical solutions and strategies for mitigating these challenges are discussed, emphasizing the need for interdisciplinary approaches, improved data collection and modeling techniques, and advanced monitoring and control systems. Overcoming these challenges is imperative for unlocking the full potential of geothermal energy making a substantial contribution to the global energy transition and sustainable development.

Keywords: geothermal reservoirs, THMC coupling, interdisciplinary approaches, challenges and opportunities, sustainable utilization

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Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Benga Ebouele, Thomas Tengen

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Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

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Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

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Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

Procedia PDF Downloads 126

Authors: Sara Khan Mohammadi

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The world is facing a major challenge of feeding a growing population while ensuring the sustainability of food systems. The United Nations estimates that the global population will reach 9.7 billion by 2050, which means that food production needs to increase by 70% to meet the demand. However, this increase in food production should not come at the cost of environmental degradation, loss of biodiversity, and climate change. Therefore, there is a need for sustainable food systems that can provide healthy and nutritious food while minimizing their impact on the environment. Nutrition and Food Engineering: Nutrition and food engineering play a crucial role in promoting sustainable food system. Nutrition is concerned with the study of nutrients in foods, their absorption, metabolism, and their effects on health. Food engineering involves the application of engineering principles to design, develop, and optimize food processing operations. Together, nutrition and food engineering can help to create sustainable food systems by: 1. Developing Nutritious Foods: Nutritionists and food engineers can work together to develop foods that are rich in nutrients such as vitamins, minerals, fiber, and protein. These foods can be designed to meet the nutritional needs of different populations while minimizing waste. 2. Reducing Food Waste: Food waste is a major problem globally as it contributes to greenhouse gas emissions and wastes resources such as water and land. Nutritionists and food engineers can work together to develop technologies that reduce waste during processing, storage, transportation, and consumption. 3. Improving Food Safety: Unsafe foods can cause illnesses such as diarrhea, cholera, typhoid fever among others which are major public health concerns globally. Nutritionists and food engineers can work together to develop technologies that improve the safety of foods from farm to fork. 4. Enhancing Sustainability: Sustainable agriculture practices such as conservation agriculture can help reduce soil erosion while improving soil fertility. Nutritionists and food engineers can work together to develop technologies that promote sustainable agriculture practices.

Keywords: sustainable food, developing food, reducing food waste, food safety

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Authors: A. Vahanyan

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The paper touches upon the problem of revision and modernization of the current curriculum on translation studies at the Armenian Higher Education Institutions (HEIs). In the contemporary world where quality and speed of services provided are mostly valued, certain higher education centers in Armenia though do not demonstrate enough flexibility in terms of the revision and amendment of courses taught. This issue is present for various curricula at the university level and Translation Studies related curriculum, in particular. Technological innovations that are of great help for translators have been long ago smoothly implemented into the global Translation Industry. According to the European Master's in Translation (EMT) framework, translation service provision comprises linguistic, intercultural, information mining, thematic, and technological competencies. Therefore, to form the competencies mentioned above, the curriculum should be seriously restructured to meet the modern education and job market requirements, relevant courses should be proposed. New courses, in particular, should focus on the formation of technological competences. These suggestions have been made upon the author’s research of the problem across various HEIs in Armenia. The updated curricula should include courses aimed at familiarization with various computer-assisted translation (CAT) tools (MemoQ, Trados, OmegaT, Wordfast, etc.) in the translation process, creation of glossaries and termbases compatible with different platforms), which will ensure consistency in translation of similar texts and speeding up the translation process itself. Another aspect that may be strengthened via curriculum modification is the introduction of interdisciplinary and Project-Based Learning courses, which will enable info mining and thematic competences, which are of great importance as well. Of course, the amendment of the existing curriculum with the mentioned courses will require corresponding faculty development via training, workshops, and seminars. Finally, the provision of extensive internship with translation agencies is strongly recommended as it will ensure the synthesis of theoretical background and practical skills highly required for the specific area. Summing up, restructuring and modernization of the existing curricula on Translation Studies should focus on three major aspects, i.e., introduction of new courses that meet the global quality standards of education, professional development for faculty, and integration of extensive internship supervised by experts in the field.

Keywords: competencies, curriculum, modernization, technical literacy, translation studies

Procedia PDF Downloads 125

Authors: Seyed Nima Tayarani Bathaie

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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: face detection algorithm, Haar features, security of ATM

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Authors: Thi Phuong Lan Nguyen

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Alongside technical skills, the employability is crucial for any graduates in the fast-evolving 21st century. It is reported that 78% of Australian students believe soft skills give advantages in the changing workforce due to technological automation (Oxford, 2020), which motivated to investigate how students whose English as a foreign or second language (EFL/ESL) are ready for the employability requirements in the new normal. Literature review, document analysis, and Interviews with EFL teachers are used in this research. The results of this research are helpful in preparing international EFL/ESL students to achieve the best preparation for currently increasing demanding employment markets, which are also meaningful for students themselves to be ready of being global citizens in the new normal.

Keywords: readiness, employability, EFL, ESL

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Authors: Ainoa Guinart, Maria Korpidou, Daniel Doellerer, Cornelia Palivan, Ben L. Feringa

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Stimuli responsive systems arise from the need to meet unsolved needs of current molecular drugs. Our study presents the design of a delivery system with high spatiotemporal control and tuneable release profiles. We study the incorporation of a hydrophobic synthetic molecular motor into PDMS-b-PMOXA block copolymer vesicles to create a self-assembled system. We prove their successful incorporation and selective activation by low powered visible light (λ 430 nm, 6.9 mW). We trigger the release of a fluorescent dye with high release efficiencies over sequential cycles (up to 75%) with the ability to turn on and off the release behaviour on demand by light irradiation. Low concentrations of photo-responsive units are proven to trigger release down to 1 mol% of molecular motor. Finally, we test our system in relevant physiological conditions using a lung cancer cell line and the encapsulation of an approved drug. Similar levels of cell viability are observed compared to the free-given drugshowing the potential of our platform to deliver functional drugs on demand with the same efficiency and lower toxicity.

Keywords: molecular motor, polymer, drug delivery, light-responsive, cancer, selfassembly

Procedia PDF Downloads 127

Authors: Yener Ekiz

Abstract:

Knowledge development is a proactive process that covers collection, analysis, storage and distribution of information that helps to contribute the understanding of the environment. To transfer knowledge correctly and fastly, you have to use new emerging information system technologies. Actionable knowledge is only of value if it is understandable and usable by target users. The purpose of the paper is to enlighten how technology eases and affects the process of knowledge development. While preparing the paper, literature review, survey and interview methodology will be used. The hypothesis is that the technology and knowledge development are inseparable and the technology will formalize the DIKW hierarchy again. As a result, today there is huge data. This data must be classified sharply and quickly.

Keywords: DIKW hierarchy, knowledge development, technology

Procedia PDF Downloads 431

Authors: F. Felipe

Abstract:

Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: air defense, effectiveness, system, simulation, decision-support

Procedia PDF Downloads 155

Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

Procedia PDF Downloads 311

Authors: Azwadi Mohamad, Pauzi Yahaya, Nadiah Hudi

Abstract:

Earthing system for high-voltage transmission tower is designed to protect the working personnel and equipments, and to maintain the quality of supply during fault. The existing earthing system for transmission towers in TNB’s system is purposely designed for normal power frequency (low-frequency) fault conditions that take into account the step and touch voltages. This earthing design is found to be inapt for lightning (transient) condition to a certain extent, which involves a high-frequency domain. The current earthing practice of laying the electrodes radially in straight 60 m horizontal lines under the ground, in order to achieve the specified impedance value of less than 10 Ω, was deemed ineffective in reducing the high-frequency impedance. This paper introduces a new earthing design that produces low impedance value at the high-frequency domain, without compromising the performance of low-frequency impedance. The performances of this new earthing design, as well as the existing design, are simulated for various soil resistivity values at varying frequency. The proposed concentrated earthing design is found to possess low TFR value at both low and high-frequency. A good earthing design should have a fine balance between compact and radial electrodes under the ground.

Keywords: earthing design, high-frequency, lightning, tower footing impedance

Procedia PDF Downloads 156

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 133

Authors: Shreya Goyal

Abstract:

The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

Procedia PDF Downloads 60

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

Abstract:

The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

Procedia PDF Downloads 180

Authors: Yu-Hong Lin

Abstract:

Background: An adverse drug reaction (ADR) reported is an injury which caused by taking medicines. Sometimes the severity of ADR reported may be minor, but sometimes it could be a life-threatening situation. In order to provide healthcare professionals as a better reference in clinical practice, we do data collection and analysis from our hospital. Methods: This was a retrospective study of ADRs reported performed from 2014 to 2015 in our hospital in Taiwan. We collected assessment items of ADRs reported, which contain gender and age, occurring sources, Anatomical Therapeutic Chemical (ATC) classification of suspected drugs, types of adverse reactions, Naranjo score calculating by Naranjo Adverse Drug Reaction Probability Scale and so on. Results: The investigation included two hundred and seven ADRs reported. Most of ADRs reported were occurring in outpatient department (92%). The average age of ADRs reported was 65.3 years. Less than 65 years of age were in the majority in this study (54%). Majority of all ADRs reported were males (51%). According to ATC classification system, the major classification of suspected drugs was cardiovascular system (19%) and antiinfectives for systemic use (18%) respectively. Among the adverse reactions, Dermatologic Effects (35%) were the major type of ADRs. Also, the major Naranjo scores of all ADRs reported ranged from 1 to 4 points (91%), which represents a possible correlation between ADRs reported and suspected drugs. Conclusions: Definitely, ADRs reported is still an extremely important information for healthcare professionals. For that reason, we put all information of ADRs reported into our hospital's computer system, and it will improve the safety of medication use. By hospital's computer system, it can remind prescribers to think of information about patient's ADRs reported. No drugs are administered without risk. Therefore, all healthcare professionals should have a responsibility to their patients, who themselves are becoming more aware of problems associated with drug therapy.

Keywords: adverse drug reaction, Taiwan, healthcare professionals, safe use of medicines

Procedia PDF Downloads 224