Search results for: adjusted network
2368 The Usefulness and Usability of a Linkedin Group for the Maintenance of a Community of Practice among Hand Surgeons Worldwide
Authors: Vaikunthan Rajaratnam
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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 3162367 Performance Comparison of Reactive, Proactive and Hybrid Routing Protocols in Wireless Ad Hoc Networks
Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti, Kumar Prashant
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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper we compare AODV, DSDV, DSR and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyses these routing protocols by extensive simulations in OPNET simulator and show that how pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, data traffic sent, throughput, retransmission attempts.Keywords: MANET, AODV, DSDV, DSR, ZRP
Procedia PDF Downloads 6782366 Effect of Swelling Pressure on Drug Release from Polyelectrolyte Micro-Hydrogel Particles
Authors: Mina Boroujerdi, Javad Tavakoli
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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 2992365 A Compact Wearable Slot Antenna for LTE and WLAN Applications
Authors: Haider K. Raad
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In this paper, a compact wide-band, ultra-thin and flexible slot antenna intended for wearable applications is presented. The presented antenna is designed to provide Wireless Local Area Network (WLAN) and Long Term Evolution (LTE) connectivity. The presented design exhibits a relatively wide bandwidth (1600-3500 MHz below -6 dB impedance bandwidth limit). The antenna is positioned on a 33 mm x 30 mm flexible substrate with a thickness of 50 µm. Antenna properties, such as the far-field radiation patterns, scattering parameter S11 are provided. The presented compact, thin and flexible design along with excellent radiation characteristics are deemed suitable for integration into flexible and wearable devices.Keywords: wearable electronics, slot Antenna, LTE, WLAN
Procedia PDF Downloads 2342364 Application of the Discrete-Event Simulation When Optimizing of Business Processes in Trading Companies
Authors: Maxat Bokambayev, Bella Tussupova, Aisha Mamyrova, Erlan Izbasarov
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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 3442363 A Horn Antenna Loaded with SIW FSS of Crossed Dipoles
Authors: Ibrahim Mostafa El-Mongy, Abdelmegid Allam
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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 2882362 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
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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 1562361 A New Method Presentation for Locating Fault in Power Distribution Feeders Considering DG
Authors: Rahman Dashti, Ehsan Gord
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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 4032360 Block Mining: Block Chain Enabled Process Mining Database
Authors: James Newman
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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 1032359 Comparative Study of Ad Hoc Routing Protocols in Vehicular Ad-Hoc Networks for Smart City
Authors: Khadija Raissi, Bechir Ben Gouissem
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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 2972358 Knowledge Discovery from Production Databases for Hierarchical Process Control
Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata
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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 4812357 An Overview of PFAS Treatment Technologies with an In-Depth Analysis of Two Case Studies
Authors: Arul Ayyaswami, Vidhya Ramalingam
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Per- and polyfluoroalkyl substances (PFAS) have emerged as a significant environmental concern due to their ubiquity and persistence in the environment. Their chemical characteristics and adverse effects on human health demands more effective and sustainable solutions in remediation of the PFAS. The work presented here encompasses an overview of treatment technologies with two case studies that utilize effective approaches in addressing PFAS contaminated media. Currently the options for treatment of PFAS compounds include Activated carbon adsorption, Ion Exchange, Membrane Filtration, Advanced oxidation processes, Electrochemical treatment, and Precipitation and Coagulation. In the first case study, a pilot study application of colloidal activated carbon (CAC) was completed to address PFAS from aqueous film-forming foam (AFFF) used to extinguish a large fire. The pilot study was used to demonstrate the effectiveness of a CAC in situ permeable reactive barrier (PRB) in effectively stopping the migration of PFOS and PFOA, moving from the source area at high concentrations. Before the CAC PRB installation, an injection test using - fluorescein dye was conducted to determine the primary fracture-induced groundwater flow pathways. A straddle packer injection delivery system was used to isolate discrete intervals and gain resolution over the 70 feet saturated zone targeted for treatment. Flow rates were adjusted, and aquifer responses were recorded for each interval. The results from the injection test were used to design the pilot test injection plan using CAC PRB. Following the CAC PRB application, the combined initial concentration 91,400 ng/L of PFOS and PFOA were reduced to approximately 70 ng/L (99.9% reduction), after only one month following the injection event. The results demonstrate the remedy's effectiveness to quickly and safely contain high concentrations of PFAS in fractured bedrock, reducing the risk to downgradient receptors. The second study involves developing a reductive defluorination treatment process using UV and electron acceptor. This experiment indicates a significant potential in treatment of PFAS contaminated waste media such as landfill leachates. The technology also shows a promising way of tacking these contaminants without the need for secondary waste disposal or any additional pre-treatments.Keywords: per- and polyfluoroalkyl substances (PFAS), colloidal activated carbon (CAC), destructive PFAS treatment technology, aqueous film-forming foam (AFFF)
Procedia PDF Downloads 602356 Care: A Cluster Based Approach for Reliable and Efficient Routing Protocol in Wireless Sensor Networks
Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan
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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks
Procedia PDF Downloads 5052355 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
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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 6562354 Factors Affecting Harvested Rain Water Quality and Quantity in Yatta Area, Palestine
Authors: Nibal Al-Batsh, Issam Al-Khatib, Subha Ghannam
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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
Procedia PDF Downloads 2852353 High Acid-Stable α-Amylase Production by Milk in Liquid Culture
Authors: Shohei Matsuo, Saki Mikai, Hiroshi Morita
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Objectives: Shochu is a popular Japanese distilled spirits. In the production of shochu, the filamentous fungus Aspergillus kawachii has traditionally been used. A. kawachii produces two types of starch hydrolytic enzymes, α-amylase (enzymatic liquefaction) and glucoamylase (enzymatic saccharification). Liquid culture system is a relatively easy microorganism to ferment with relatively low cost of production compared for solid culture. In liquid culture system, acid-unstable α-amylase (α-A) was produced abundantly, but, acid-stable α-amylase (Aα-A) was not produced. Since there is high enzyme productivity, most in shochu brewing have been adopted by a solid culture method. In this study, therefore, we investigated production of Aα-A in liquid culture system. Materials and methods: Microorganism Aspergillus kawachii NBRC 4308 was used. The mold was cultured at 30 °C for 7~14 d to allow formation of conidiospores on slant agar medium. Liquid Culture System: A. kawachii was cultured in a 100 ml of following altered SLS medium: 1.0 g of rice flour, 0.1 g of K2HPO4, 0.1 g of KCl, 0.6 g of tryptone, 0.05 g of MgSO4・7H2O, 0.001 g of FeSO4・7H2O, 0.0003 g of ZnSO4・7H2O, 0.021 g of CaCl2, 0.33 of citric acid (pH 3.0). The pH of the medium was adjusted to the designated value with 10 % HCl solution. The cultivation was shaking at 30 °C and 200 rpm for 72 h. It was filtered to obtain a crude enzyme solution. Aα-A assay: The crude enzyme solution was analyzed. An acid-stable α-amylase activity was carried out using an α-amylase assay kit (Kikkoman Corporation, Noda, Japan). It was conducted after adding 9 ml of 100 mM acetate buffer (pH 3.0) to 1 ml of the culture product supernatant and acid treatment at 37°C for 1 h. One unit of a-amylase activity was defined as the amount of enzyme that yielded 1 mmol of 2-chloro-4-nitrophenyl 6-azide-6-deoxy-b-maltopentaoside (CNP) per minute. Results and Conclusion: We experimented with co-culture of A. kawachii and lactobacillus in order to get control of pH in altered SLS medium. However, high production of acid-stable α-amylase was not obtained. We experimented with yoghurt or milk made an addition to liquid culture. The result indicated that high production of acid-stable α-amylase (964 U/g-substrate) was obtained when milk made an addition to liquid culture. Phosphate concentration in the liquid medium was a major cause of increased acid-stable α-amylase activity. In liquid culture, acid-stable α-amylase activity was enhanced by milk, but Fats and oils in the milk were oxidized. In addition, Tryptone is not approved as a food additive in Japan. Thus, alter SLS medium added to skim milk excepting for the fats and oils in the milk instead of tryptone. The result indicated that high production of acid-stable α-amylase was obtained with the same effect as milk.Keywords: acid-stable α-amylase, liquid culture, milk, shochu
Procedia PDF Downloads 2842352 ELectromagnetic-Thermal Coupled Analysis of PMSM with Cooling Channel
Authors: Hyun-Woo Jun, Tae-Chul Jeong, Huai-Cong Liu, Ju Lee
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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
Procedia PDF Downloads 6202351 Analysis of Storm Flood in Typical Sewer Networks in High Mountain Watersheds of Colombia Based on SWMM
Authors: J. C. Hoyos, J. Zambrano Nájera
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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
Procedia PDF Downloads 2622350 Modelling Vehicle Fuel Consumption Utilising Artificial Neural Networks
Authors: Aydin Azizi, Aburrahman Tanira
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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
Procedia PDF Downloads 4052349 Promoting Innovation Pedagogy in a Capacity Building Project in Indonesia
Authors: Juha Kettunen
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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 2862348 The Role of Group Size, Public Employees’ Wages and Control Corruption Institutions in a Game-Theoretical Model of Public Corruption
Authors: Pablo J. Valverde, Jaime E. Fernandez
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This paper shows under which conditions public corruption can emerge. The theoretical model includes variables such as the public employee wage (w), a control corruption parameter (c), and the group size of interactions (GS) between clusters of public officers and contractors. The system behavior is analyzed using phase diagrams based on combinations of such parameters (c, w, GS). Numerical simulations are implemented in order to contrast analytic results based on Nash equilibria of the theoretical model. Major findings include the functional relationship between wages and network topology, which attempts to reduce the emergence of corrupt behavior.Keywords: public corruption, game theory, complex systems, Nash equilibrium.
Procedia PDF Downloads 2422347 Proposal for a Web System for the Control of Fungal Diseases in Grapes in Fruits Markets
Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso
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Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow
Procedia PDF Downloads 832346 Emerging Technology for 6G Networks
Authors: Yaseein S. Hussein, Victor P. Gil Jiménez, Abdulmajeed Al-Jumaily
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Due to the rapid advancement of technology, there is an increasing demand for wireless connections that are both fast and reliable, with minimal latency. New wireless communication standards are developed every decade, and the year 2030 is expected to see the introduction of 6G. The primary objectives of 6G network and terminal designs are focused on sustainability and environmental friendliness. The International Telecommunication Union-Recommendation division (ITU-R) has established the minimum requirements for 6G, with peak and user data rates of 1 Tbps and 10-100 Gbps, respectively. In this context, Light Fidelity (Li-Fi) technology is the most promising candidate to meet these requirements. This article will explore the various advantages, features, and potential applications of Li-Fi technology, and compare it with 5G networking, to showcase its potential impact among other emerging technologies that aim to enable 6G networks.Keywords: 6G networks, artificial intelligence (AI), Li-Fi technology, Terahertz (THz) communication, visible light communication (VLC)
Procedia PDF Downloads 942345 Prototyping a Portable, Affordable Sign Language Glove
Authors: Vidhi Jain
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Communication between speakers and non-speakers of American Sign Language (ASL) can be problematic, inconvenient, and expensive. This project attempts to bridge the communication gap by designing a portable glove that captures the user’s ASL gestures and outputs the translated text on a smartphone. The glove is equipped with flex sensors, contact sensors, and a gyroscope to measure the flexion of the fingers, the contact between fingers, and the rotation of the hand. The glove’s Arduino UNO microcontroller analyzes the sensor readings to identify the gesture from a library of learned gestures. The Bluetooth module transmits the gesture to a smartphone. Using this device, one day speakers of ASL may be able to communicate with others in an affordable and convenient way.Keywords: sign language, morse code, convolutional neural network, American sign language, gesture recognition
Procedia PDF Downloads 632344 Optimizing Inanda Dam Using Water Resources Models
Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno
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The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.Keywords: complex, water resources, planning, cost effective and management
Procedia PDF Downloads 5732343 Deepfake Detection for Compressed Media
Authors: Sushil Kumar Gupta, Atharva Joshi, Ayush Sonawale, Sachin Naik, Rajshree Khande
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The usage of artificially created videos and audio by deep learning is a major problem of the current media landscape, as it pursues the goal of misinformation and distrust. In conclusion, the objective of this work targets generating a reliable deepfake detection model using deep learning that will help detect forged videos accurately. In this work, CelebDF v1, one of the largest deepfake benchmark datasets in the literature, is adopted to train and test the proposed models. The data includes authentic and synthetic videos of high quality, therefore allowing an assessment of the model’s performance against realistic distortions.Keywords: deepfake detection, CelebDF v1, convolutional neural network (CNN), xception model, data augmentation, media manipulation
Procedia PDF Downloads 102342 Detect QOS Attacks Using Machine Learning Algorithm
Authors: Christodoulou Christos, Politis Anastasios
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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping
Procedia PDF Downloads 612341 Radar-Based Classification of Pedestrian and Dog Using High-Resolution Raw Range-Doppler Signatures
Authors: C. Mayr, J. Periya, A. Kariminezhad
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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.Keywords: machine learning, radar, signal processing, autonomous driving
Procedia PDF Downloads 2462340 QCARNet: Networks for Quality-Adaptive Compression Artifact
Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho
Abstract:
We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.Keywords: compression artifact reduction, deblocking, image denoising, image restoration
Procedia PDF Downloads 1412339 Differentially Expressed Genes in Atopic Dermatitis: Bioinformatics Analysis Of Pooled Microarray Gene Expression Datasets In Gene Expression Omnibus
Abstract:
Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.Keywords: atopic dermatitis, bioinformatics, biomarkers, genes
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