Search results for: improve
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8271

Search results for: improve

5781 Dissecting Big Trajectory Data to Analyse Road Network Travel Efficiency

Authors: Rania Alshikhe, Vinita Jindal

Abstract:

Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

Procedia PDF Downloads 157
5780 Effect of Carbon Nanotubes Functionalization with Nitrogen Groups on Pollutant Emissions in an Internal Combustion Engine

Authors: David Gamboa, Bernardo Herrera, Karen Cacua

Abstract:

Nanomaterials have been explored as alternatives to reduce particulate matter from diesel engines, which is one of the most common pollutants of the air in urban centers. However, the use of nanomaterials as additives for diesel has to overcome the instability of the dispersions to be considered viable for commercial use. In this work, functionalization of carbon nanotubes with amide groups was performed to improve the stability of these nanomaterials in a mix of 90% petroleum diesel and 10% palm oil biodiesel (B10) in concentrations of 50 and 100 ppm. The resulting nano fuel was used as the fuel for a stationary internal combustion engine, where the particulate matter, NOx, and CO were measured. The results showed that the use of amide groups significantly enhances the time for the carbon nanotubes to remain suspended in the fuel, and at the same time, these nanomaterials helped to reduce the particulate matter and NOx emissions. However, the CO emissions with nano fuel were higher than those ones with the combustion of B10. These results suggest that carbon nanotubes have thermal and catalytic effects on the combustion of B10.

Keywords: carbon nanotubes, diesel, internal combustion engine, particulate matter

Procedia PDF Downloads 128
5779 Improving Communication System through Router Configuration: The Nigerian Navy Experience

Authors: Saidu I. Rambo, Emmanuel O. Ibam, Sunday O. Adewale

Abstract:

The configuration of routers for effective communication in the Nigerian Navy (NN) enables the navy to improve on the current communication systems. The current system is faced with challenges that make the systems partially effective. The major implementation of the system is to configure routers using hierarchical model and obtaining a VSAT option on C-band platform. These routers will act as a link between Naval Headquarters and the Commands under it. The routers main responsibilities are to forward packets from source location to destination using a Link State Routing Protocol (LSRP). Also using the Point to Point Protocol (PPP), creates a strong encrypted password using Challenge Handshake Authentication Protocol (CHAP) which uses one-way hash function of Message Digest 5 (MD5) to provide complete protection against hackers/intruders. Routers can be configured using a Linux operating system or internet work operating system in the Microsoft platform. With this, system packets can be forwarded to various locations more effectively than the present system being used.

Keywords: C-band, communication, router, VSAT

Procedia PDF Downloads 366
5778 Use of Natural Fibers in Landfill Leachate Treatment

Authors: Araujo J. F. Marina, Araujo F. Marcus Vinicius, Mulinari R. Daniella

Abstract:

Due to the resultant leachate from waste decomposition in landfills has polluter potential hundred times greater than domestic sewage, this is considered a problem related to the depreciation of environment requiring pre-disposal treatment. In seeking to improve this situation, this project proposes the treatment of landfill leachate using natural fibers intercropped with advanced oxidation processes. The selected natural fibers were palm, coconut and banana fiber. These materials give sustainability to the project because, besides having adsorbent capacity, are often part of waste discarded. The study was conducted in laboratory scale. In trials, the effluents were characterized as Chemical Oxygen Demand (COD), Turbidity and Color. The results indicate that is technically promising since that there were extremely oxidative conditions, the use of certain natural fibers in the reduction of pollutants in leachate have been obtained results of COD removals between 67.9% and 90.9%, Turbidity between 88.0% and 99.7% and Color between 67.4% and 90.4%. The expectation generated is to continue evaluating the association of efficiency of other natural fibers with other landfill leachate treatment processes.

Keywords: lndfill leachate, chemical treatment, natural fibers, advanced oxidation processes

Procedia PDF Downloads 357
5777 Using Project MIND - Math Is Not Difficult Strategies to Help Children with Autism Improve Mathematics Skills

Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu

Abstract:

This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.

Keywords: autism, mathematics, technology, family

Procedia PDF Downloads 105
5776 Forecasting Stock Prices Based on the Residual Income Valuation Model: Evidence from a Time-Series Approach

Authors: Chen-Yin Kuo, Yung-Hsin Lee

Abstract:

Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

Procedia PDF Downloads 316
5775 Clarification of the Essential of Life Cycle Cost upon Decision-Making Process: An Empirical Study in Building Projects

Authors: Ayedh Alqahtani, Andrew Whyte

Abstract:

Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: building projects, capital cost, life cycle cost, maintenance costs, operation costs

Procedia PDF Downloads 546
5774 Total Dissolved Solids and Total Iron in High Rate Activated Sludge System

Authors: M. Y. Saleh, G. M. ELanany, M. H. Elzahar, M. Z. Elshikhipy

Abstract:

Industrial wastewater discharge, which carries high concentrations of dissolved solids and iron, could be treated by high rate activated sludge stage of the multiple-stage sludge treatment plant, a system which is characterized by high treatment efficiency, optimal prices, and small areas compared with conventional activated sludge treatment plants. A pilot plant with an influent industrial discharge flow of 135 L/h was designed following the activated sludge system to simulate between the biological and chemical treatment with the addition of dosages 100, 150, 200 and 250 mg/L alum salt to the aeration tank. The concentrations of total dissolved solids (TDS) and iron (Fe) in industrial discharge flow had an average range of 140000 TDS and 4.5 mg/L iron. The optimization of the chemical-biological process using a dosage of 200 mg/L alum succeeded to improve the removal efficiency of TDS and total iron to 48.15% and 68.11% respectively.

Keywords: wastewater, activated sludge, TDS, total iron

Procedia PDF Downloads 296
5773 Utilization of Rice and Corn Bran with Dairy By-Product in Tarhana Production

Authors: Kübra Aktaş, Nihat Akin

Abstract:

Tarhana is a traditional Turkish fermented food. It is widely consumed as soup and includes many different ingredients such as wheat flour, various vegetables, and spices, yoghurt, bakery yeast. It can also be enriched by adding other ingredients. Thus, its nutritional properties can be enhanced. In this study, tarhana was supplemented with two different types of brans (rice bran and corn bran) and WPC (whey protein concentrate powder) to improve its nutritional and functional properties. Some chemical properties of tarhana containing two different brans and their levels (0, 5, 10 and 15%) and WPC (0, 5, 10%) were investigated. The results indicated that addition of WPC increased ash content in tarhanas which were fortified with rice and corn bran. The highest antioxidant and phenolic content values were obtained with addition of rice bran in tarhana formulation. Compared to tarhana with corn bran, rice bran addition gave higher oil content values. The cellulose content of tarhana samples was determined between 0.75% and 2.74% and corn bran showed an improving effect on cellulose contents of samples. In terms of protein content, addition of WPC into the tarhana raised protein content for the samples.

Keywords: corn, rice, tarhana, whey

Procedia PDF Downloads 334
5772 Categorization of Biosolids, a Vital Biological Resource for Sustainable Agriculture

Authors: Susmita Sharma, Pankaj Pathak

Abstract:

Biosolids are by-products of municipal and industrial wastewater treatment process. The generation of the biosolids is increasing at an alarming rate due to the implementation of strict environmental legislation to improve the quality of discharges from wastewater treatment plant. As such, proper management and safe disposal of sewage sludge have become a worldwide topic of research. Biosolids, rich in organic matter and essential micro and macronutrients; can be used as a soil conditioner, to cut fertilizer costs and create favorable conditions for vegetation. However, it also contains pathogens and heavy metals which are undesirable as they are harmful to both humans and the environment. Therefore, for safe utilization of biosolids for land application purposes, categorization of the contaminant and pathogen is mandatory. In this context, biosolids collected from a wastewater treatment plant in Maharashtra are utilized to determine its physical, chemical and microbiological attributes. This study would ascertain, if the use of these materials from the specific site, are suitable for agriculture. Further, efforts have also been made to present the internationally acceptable legal standards and guidelines for biosolids management or application.

Keywords: biosolids, sewage, heavy metal, sustainable agriculture

Procedia PDF Downloads 327
5771 Margin-Based Feed-Forward Neural Network Classifiers

Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

Procedia PDF Downloads 341
5770 Mechanical Prosthesis Controlled by Brain-Computer Interface

Authors: Tianyu Cao, KIRA (Ruizhi Zhao)

Abstract:

The purpose of our research is to study the possibility of people with physical disabilities manipulating mechanical prostheses through brain-computer interface (BCI) technology. The brain-machine interface (BCI) of the neural prosthesis records signals from neurons and uses mathematical modeling to decode them, converting desired movements into body movements. In order to improve the patient's neural control, the prosthesis is given a natural feeling. It records data from sensitive areas from the body to the prosthetic limb and encodes signals in the form of electrical stimulation to the brain. In our research, the brain-computer interface (BCI) is a bridge connecting patients’ cognition and the real world, allowing information to interact with each other. The efficient work between the two is achieved through external devices. The flow of information is controlled by BCI’s ability to record neuronal signals and decode signals, which are converted into device control. In this way, we could encode information and then send it to the brain through electrical stimulation, which has significant medical application.

Keywords: biomedical engineering, brain-computer interface, prosthesis, neural control

Procedia PDF Downloads 181
5769 Data Rate Based Grouping Scheme for Cooperative Communications in Wireless LANs

Authors: Sunmyeng Kim

Abstract:

IEEE 802.11a/b/g standards provide multiple transmission rates, which can be changed dynamically according to the channel condition.Cooperative communications we reintroduced to improve the overallperformance of wireless LANs with the help of relay nodes with higher transmission rates. The cooperative communications are based on the fact that the transmission is much faster when sending data packets to a destination node through a relay node with higher transmission rate, rather than sending data directly to the destination node at low transmission rate. To apply the cooperative communications in wireless LAN, several MAC protocols have been proposed. Some of them can result in collisions among relay nodes in a dense network. In order to solve this problem, we propose a new protocol. Relay nodes are grouped based on their transmission rates. And then, relay nodes only in the highest group try to get channel access. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and collision probability.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

Procedia PDF Downloads 466
5768 Installing Cloud Computing Model for E-Businesses in Small Organizations

Authors: Khader Titi

Abstract:

Information technology developments have changed the way how businesses are working. Organizations are required to become visible online and stay connected to take advantages of costs reduction and improved operation of existing resources. The approval and the application areas of the cloud computing has significantly increased since it was presented by Google in 2007. Internet Cloud computing has attracted the IT enterprise attention especially the e-business enterprise. At this time, there is a great issue of environmental costs during the enterprises apply the e- business, but with the coming of cloud computing, most of the problem will be solved. Organizations around the world are facing with the continued budget challenges and increasing in the size of their computational data so, they need to find a way to deliver their services to clients as economically as possible without negotiating the achievement of anticipated outcomes. E- business companies need to provide better services to satisfy their clients. In this research, the researcher proposed a paradigm that use and deploy cloud computing technology environment to be used for e-business in small enterprises. Cloud computing might be a suitable model for implementing e-business and e-commerce architecture to improve efficiency and user satisfaction.

Keywords: E-commerce, cloud computing, B2C, SaaS

Procedia PDF Downloads 317
5767 Parkinson's Disease and Musculoskeletal Problems

Authors: Ozge Yilmaz Kusbeci, Ipek Inci

Abstract:

Aim: Musculoskeletal problems are very common in Parkinson’s disease (PD). They affect quality of life and cause disabilities. However they are under-evaluated, and under-treated. The aim of this study is to evaluate the prevalence and clinical features of musculoskeletal problems in patients with Parkinson disease (PD) compared to controls. Methods: 50 PD patients and 50 age and sex matched controls were interviewed by physicians about their musculoskeletal problems. Results: The prevalence of musculoskeletal problems was significantly higher in the PD group than in the control group (p < 0.05). Commonly involved body sites were the shoulder, low back, and knee. The shoulder and low back was more frequently involved in the PD group than in the control group. However, the knee was similarly involved in both groups. Among the past diagnoses associated with musculoskeletal problems, frozen shoulder, low back pain and osteoporosis more common in the PD group than in the control group (p < 0.05). Furthermore, musculoskeletal problems in the PD group tended to receive less treatment than that of the control group. Conclusion: Musculoskeletal problems were more common in the PD group than in the controls. Therefore assessment and treatment of musculoskeletal problems could improve quality of life in PD patients.

Keywords: parkinson disease, musculoskeletal problems, quality of life, PD disease

Procedia PDF Downloads 396
5766 Artificial Intelligence for Traffic Signal Control and Data Collection

Authors: Reggie Chandra

Abstract:

Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

Procedia PDF Downloads 169
5765 Effects of Li2O Doping on Mechanical and Electrical Properties of Bovine Hydroxyapatite Composites (BHA)

Authors: Sibel Daglilar, Isil Kerti, Murat Karagoz, Fatih Dumludag, Oguzhan Gunduz, Faik Nuzhet Oktar

Abstract:

Hydroxyapatite (HA) materials have common use in bone repairing due to its ability to accelerate the bone growth around the implant. In spite of being a biocompatible and bioactive material, HA has a limited usage as an implant material because of its weak mechanical properties. HA based composites are required to improve the strength and toughness properties of the implant materials without compromising of biocompatibility. The excellent mechanical properties and higher biocompatibilities are expected from each of biomedical composites. In this study, HA composites were synthesized by using bovine bone reinforced doped with different amount of (wt.%) Li2O. The pressed pellets were sintered at various sintering temperatures between 1000ºC and 1300°C, and mechanical, electrical properties of the obtained products were characterized. In addition to that, in vitro stimulated body fluid (SBF) tests for these samples were conducted. The most suitable composite composition for biomedical applications was discussed among the composites studied.

Keywords: biocomposites, sintering temperature, biocompatibility, electrical property, conductivity, mechanical property

Procedia PDF Downloads 400
5764 Sound Exposure Effects towards Ross Broilers Growth Rate

Authors: Rashidah Ghazali, Herlina Abdul Rahim, Mashitah Shikh Maidin, Shafishuhaza Sahlan, Noramli Abdul Razak

Abstract:

Sound exposure effects have been investigated by broadcasting a group of broilers with sound of Quran verses (Group B) whereas the other group is the control broilers (Group C). The growth rate comparisons in terms of weight and raw meat texture measured by shear force have been investigated. Twenty-seven broilers were randomly selected from each group on Day 24 and weight measurement was carried out every week till the harvest day (Day 39). Group B showed a higher mean weight on Day 24 (1.441±0.013 kg) than Group C. Significant difference in the weight on Day 39 existed for Group B compared to Group C (p< 0.05). However, there was no significant (p> 0.05) difference of shear force in the same muscles (breast and drumstick raw meat) of both groups but the shear force of the breast meat for Group B and C broilers was lower (p < 0.05) than that of their drumstick meat. Thus, broadcasting the sound of Quran verses in the coop can be applied to improve the growth rate of broilers for producing better quality poultry.

Keywords: broilers, sound, shear force, weight

Procedia PDF Downloads 418
5763 Crystalline Structure of Starch Based Nano Composites

Authors: Farid Amidi Fazli, Afshin Babazadeh, Farnaz Amidi Fazli

Abstract:

In contrast with literal meaning of nano, researchers have been achieving mega adventures in this area and every day more nanomaterials are being introduced to the market. After long time application of fossil-based plastics, nowadays accumulation of their waste seems to be a big problem to the environment. On the other hand, mankind has more attention to safety and living environment. Replacing common plastic packaging materials with degradable ones that degrade faster and convert to non-dangerous components like water and carbon dioxide have more attractions; these new materials are based on renewable and inexpensive sources of starch and cellulose. However, the functional properties of them do not suitable for packaging. At this point, nanotechnology has an important role. Utilizing of nanomaterials in polymer structure will improve mechanical and physical properties of them; nanocrystalline cellulose (NCC) has this ability. This work has employed a chemical method to produce NCC and starch bio nanocomposite containing NCC. X-Ray Diffraction technique has characterized the obtained materials. Results showed that applied method is a suitable one as well as applicable one to NCC production.

Keywords: biofilm, cellulose, nanocomposite, starch

Procedia PDF Downloads 405
5762 Design of a New Package for Saffron Using Kansei Engineering

Authors: Sotiris Papantonopoulos, Marianna Bortziou

Abstract:

This study aimed at developing a new package of saffron using emotional design and specifically the Kansei Engineering method. Kansei Engineering is a proactive product development methodology, which aims to improve the product development process and to translate consumers' feelings and image of a product into design elements. A survey was conducted with two major purposes: (1) to determine the target group of saffron use and to collect information about the adequacy of the product’s promotion and the importance of its packaging, (2) to collect the most important properties of a package according to consumers and to evaluate the existing saffron packages according to these properties (benchmarking). The interaction with the general public conducted by the distribution of online questionnaires and personal interviews as well as the statistical analysis of the results were performed using the SPSS software. The results of the survey were used in all stages of Kansei Engineering. Based on the results, a new saffron package was designed by using various designing and image processing software. This improved package is expected to achieve a better promotion and increased sales of the product.

Keywords: design, emotional design, Kansei Engineering, packaging, saffron

Procedia PDF Downloads 162
5761 Deep Learning-Based Channel Estimation for RIS-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

Procedia PDF Downloads 57
5760 Performance Study of Scraped Surface Heat Exchanger with Helical Ribbons

Authors: S. Ali, M. Baccar

Abstract:

In this work, numerical simulations were carried out using a specific CFD code in order to study the performance of an innovative Scraped Surface Heat Exchanger (SSHE) with helical ribbons for Bingham fluids (threshold fluids). The resolution of three-dimensional form of the conservation equations (continuity, momentum and energy equations) was carried out basing on the finite volume method (FVM). After studying the effect of dimensionless numbers (axial Reynolds, rotational Reynolds and Oldroyd numbers) on the hydrodynamic and thermal behaviors within SSHE, a parametric study was developed, by varying the width of the helical ribbon, the clearance between the stator wall and the tip of the ribbon and the number of turns of the helical ribbon, in order to improve the heat transfer inside the exchanger. The effect of these geometrical numbers on the hydrodynamic and thermal behaviors was discussed.

Keywords: heat transfer, helical ribbons, hydrodynamic behavior, parametric study, SSHE, thermal behavior

Procedia PDF Downloads 214
5759 Green Walls and Living Facades: The Portuguese Experience

Authors: Andreia Cortes, Carla Pimentel-Rodrigues, Joao Almeida, Myriam Kanoun-Boule, Carla Carvalho, Antonio Tadeu, Armando Silva-Afonso

Abstract:

The adoption of green infrastructure is nowadays encouraged as an essential measure of urban planning and territorial development whenever it offers a better alternative, or is complementary, to current solutions. Green walls and living facades often provide healthy alternatives to traditional grey infrastructures, offering many benefits for both citizens and cities. Beyond the ability to improve environmental conditions and quality of life, they can augment the energy efficiency of buildings, enhance biodiversity and deliver a range of ecosystem services such as water purification, reduction of the urban heat island effect, improvement of air quality and climate change adaptation. For this communication, a systematic survey of the existing green walls and living facades in Portugal was carried out. Different systems were analyzed and compared in terms of dimensions, constructive solutions, vegetative species, maintenance necessities and environmental aspects.

Keywords: green buildings, green walls, living facades, sustainability construction

Procedia PDF Downloads 425
5758 Influence of Transportation Mode to the Deterioration Rate: Case Study of Food Transport by Ship

Authors: Danijela Tuljak-Suban, Valter Suban

Abstract:

Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing of its physical or chemical characteristics considerably influences the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure stability conditions that limit the deterioration, since the value of the deterioration rate could be easily influenced by the transportation mode. Fuzzy definition of variables allows taking into account these variations. Furthermore an appropriate choice of the defuzzification method permits to adapt results, as much as possible, to real conditions. In the article will be applied the those methods to the relationship between the deterioration rate of perishable goods and transportation by ship, with the aim: (a) to minimize the total costs function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) to improve supply chain sustainability by reducing the environmental impact and waste disposal costs.

Keywords: perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability

Procedia PDF Downloads 543
5757 Preparation of Ag-Doped and MOFs Coupled-LaFeO₃ Nanosheet for Electrochemical CO₂ Conversion

Authors: Iltaf Khan, Munzir H. Suliman, Muhammad Usman

Abstract:

The rapid growth of modern industries has led to increased energy demand and worsened fossil fuel depletion, resulting in global warming, while organic pollutants pose significant threats to aquatic environments due to their stability, insolubleness, and non-biodegradability. So, scientists are investigating high-performance materials to resolve these issues. In this study, we prepared LaFeO₃ nanosheets (LFONS) employing a solvothermal method via a soft template such as polyvinylpyrrolidone (PVP). The LFONS have good performance regarding surface area and charge separation as compared to LaFeO₃ nanoparticles (LFONP). To improve the efficiency of LFONS, it was further modified with Ag and ZIF-67 and utilized for CO₂ conversion. Herein, the results confirm that Ag-doped and ZIF-67 coupled LFONS (ZIF-67/Ag-LFONS) exhibit superior performance compared to pristine LFONP. In addition, the stability tests confirm that our optimal sample is the most active and stable one among various nanocomposites. Ultimately, our studies will open a new pave for cost-effective, eco-friendly, and electroactive nanomaterials for CO₂ conversion.

Keywords: LaFeO₃ nanosheets, Ag incorporation, MOFs coupling, CO₂ conversion

Procedia PDF Downloads 51
5756 Predict Suspended Sediment Concentration Using Artificial Neural Networks Technique: Case Study Oued El Abiod Watershed, Algeria

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

Abstract:

The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

Procedia PDF Downloads 418
5755 Organizational Learning, Job Satisfaction and Work Performance among Nurses

Authors: Rafia Rafique, Arifa Khadim

Abstract:

This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 445
5754 Benchmarking of Pentesting Tools

Authors: Esteban Alejandro Armas Vega, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Abstract:

The benchmarking of tools for dynamic analysis of vulnerabilities in web applications is something that is done periodically, because these tools from time to time update their knowledge base and search algorithms, in order to improve their accuracy. Unfortunately, the vast majority of these evaluations are made by software enthusiasts who publish their results on blogs or on non-academic websites and always with the same evaluation methodology. Similarly, academics who have carried out this type of analysis from a scientific approach, the majority, make their analysis within the same methodology as well the empirical authors. This paper is based on the interest of finding answers to questions that many users of this type of tools have been asking over the years, such as, to know if the tool truly test and evaluate every vulnerability that it ensures do, or if the tool, really, deliver a real report of all the vulnerabilities tested and exploited. This kind of questions have also motivated previous work but without real answers. The aim of this paper is to show results that truly answer, at least on the tested tools, all those unanswered questions. All the results have been obtained by changing the common model of benchmarking used for all those previous works.

Keywords: cybersecurity, IDS, security, web scanners, web vulnerabilities

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5753 Readout Development of a LGAD-based Hybrid Detector for Microdosimetry (HDM)

Authors: Pierobon Enrico, Missiaggia Marta, Castelluzzo Michele, Tommasino Francesco, Ricci Leonardo, Scifoni Emanuele, Vincezo Monaco, Boscardin Maurizio, La Tessa Chiara

Abstract:

Clinical outcomes collected over the past three decades have suggested that ion therapy has the potential to be a treatment modality superior to conventional radiation for several types of cancer, including recurrences, as well as for other diseases. Although the results have been encouraging, numerous treatment uncertainties remain a major obstacle to the full exploitation of particle radiotherapy. To overcome therapy uncertainties optimizing treatment outcome, the best possible radiation quality description is of paramount importance linking radiation physical dose to biological effects. Microdosimetry was developed as a tool to improve the description of radiation quality. By recording the energy deposition at the micrometric scale (the typical size of a cell nucleus), this approach takes into account the non-deterministic nature of atomic and nuclear processes and creates a direct link between the dose deposited by radiation and the biological effect induced. Microdosimeters measure the spectrum of lineal energy y, defined as the energy deposition in the detector divided by most probable track length travelled by radiation. The latter is provided by the so-called “Mean Chord Length” (MCL) approximation, and it is related to the detector geometry. To improve the characterization of the radiation field quality, we define a new quantity replacing the MCL with the actual particle track length inside the microdosimeter. In order to measure this new quantity, we propose a two-stage detector consisting of a commercial Tissue Equivalent Proportional Counter (TEPC) and 4 layers of Low Gain Avalanche Detectors (LGADs) strips. The TEPC detector records the energy deposition in a region equivalent to 2 um of tissue, while the LGADs are very suitable for particle tracking because of the thickness thinnable down to tens of micrometers and fast response to ionizing radiation. The concept of HDM has been investigated and validated with Monte Carlo simulations. Currently, a dedicated readout is under development. This two stages detector will require two different systems to join complementary information for each event: energy deposition in the TEPC and respective track length recorded by LGADs tracker. This challenge is being addressed by implementing SoC (System on Chip) technology, relying on Field Programmable Gated Arrays (FPGAs) based on the Zynq architecture. TEPC readout consists of three different signal amplification legs and is carried out thanks to 3 ADCs mounted on a FPGA board. LGADs activated strip signal is processed thanks to dedicated chips, and finally, the activated strip is stored relying again on FPGA-based solutions. In this work, we will provide a detailed description of HDM geometry and the SoC solutions that we are implementing for the readout.

Keywords: particle tracking, ion therapy, low gain avalanche diode, tissue equivalent proportional counter, microdosimetry

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5752 Effect of TEOS Electrospun Nanofiber Modified Resin on Interlaminar Shear Strength of Glass Fiber/Epoxy Composite

Authors: Dattaji K. Shinde, Ajit D. Kelkar

Abstract:

Interlaminar shear strength (ILSS) of fiber reinforced polymer composite is an important property for most of the structural applications. Matrix modification is an effective method used to improve the interlaminar shear strength of composite. In this paper, EPON 862/w epoxy system was modified using Tetraethyl orthosilicate (TEOS) electrospun nanofibers (ENFs) which were produced using electrospinning method. Unmodified and nanofibers modified resins were used to fabricate glass fiber reinforced polymer composite (GFRP) using H-VARTM method. The ILSS of the Glass Fiber Reinforced Polymeric Composites (GFRP) was investigated. The study shows that introduction of TEOS ENFs in the epoxy resin enhanced the ILSS of GFRPby 15% with 0.6% wt. fraction of TEOS ENFs.

Keywords: electrospun nanofibers, H-VARTM, interlaminar shear strength, matrix modification

Procedia PDF Downloads 220