Search results for: artificial neural networks controller

Authors: Ahmed Noor Al-Qayyim

Abstract:

During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

Procedia PDF Downloads 331

Authors: Panagiotis I. Mallios, Vassilis S. Moustakis

Abstract:

The research reported herein presents a conceptual model that explores the relationship between social media factors and entrepreneurial intention, with a focus on the Greek startup ecosystem. The significance of the study is that social media have gained importance in explaining the entrepreneurial process, and through them, nascent and potential entrepreneurs seem to get inspired and motivated to initiate their businesses. The research methodology employed in this study included a qualitative research approach, utilizing in-depth interviews with a sample of 15 startup entrepreneurs providing valuable retrospective information. The data collected were analyzed using the content analysis method. The major findings of the study are that social media factors such as usefulness, influence, and credibility have a significant impact on entrepreneurial intention. We also found that social media can be a powerful tool for entrepreneurs to access resources, knowledge and networks that can help them in their venture creation. Overall, this research contributes to the entrepreneurship literature by uncovering the relationship between social media factors and entrepreneurial intention and has implications for entrepreneurial education, policymakers, and official partners, highlighting the potential of social media to enhance the startup ecosystem.

Keywords: entrepreneurial intention, social media, start up ecosystem, entrepreneurship

Procedia PDF Downloads 150

Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

Abstract:

In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

Procedia PDF Downloads 97

Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

Abstract:

The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

Procedia PDF Downloads 110

Authors: Arūnas Burinskas

Abstract:

Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

Procedia PDF Downloads 126

Authors: Sagri Sharma

Abstract:

Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

Procedia PDF Downloads 416

Authors: Salwa Salman

Abstract:

On February 2016, Egypt’s President Abdel Fattah Al-Sisi ordered the former Prime Minister, Ibrahim Mehleb, to establish a committee responsible for retrieving looted state lands or providing squatters with land titles according to their individual cases. The specificity of desert lands emerges from its unique position in both Islamic law and Egypt’s Civil Code. In Egypt, desert lands can be transferred to private ownership through peaceful occupation and cultivation. This study explores the (re-) conceptualization of land rights, state territoriality, and sovereignty as a part of an emerging narrative on informal land tenure. Through the lens of an informal settlement, the study employs methodological insights from studies in the anthropology of development and their interpretation of Foucauldian discourse analysis to examine official representations on squatting over state lands and put them in conversation with individual narratives on land ownership and dispossession. It also employs Bruno Latour’s actor-network theory to explore the development of social networks through primary land contracts and informal local resource management.

Keywords: State lands, squatter community, Islamic law, Egypt’s Civil Code

Procedia PDF Downloads 152

Authors: Esmeralda Hysenbelliu

Abstract:

Over the last years, the demand for high bandwidth services, such as live (IPTV Service) and on-demand video streaming, steadily and rapidly increased. It has been predicted that video traffic (IPTV, VoD, and WEB TV) will account more than 90% of global Internet Protocol traffic that will cross the globe in 2016. Consequently, the importance and consideration on requirements and challenges of service providers faced today in supporting user’s requests for entertainment video across the various IPTV services through virtualization over Software Defined Networks (SDN), is tremendous in the highest stage of attention. What is necessarily required, is to deliver optimized live and on-demand services like Internet Protocol Service (IPTV Service) with low cost and good quality by strictly fulfill the essential requirements of Clients and ISP’s (Internet Service Provider’s) in the same time. The aim of this study is to present an overview of the important requirements and challenges of IPTV service with two network trends on solving challenges through virtualization (SDN and Network Function Virtualization). This paper provides an overview of researches published in the last five years.

Keywords: challenges, IPTV service, requirements, software defined networking (SDN)

Procedia PDF Downloads 256

Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

Abstract:

This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

Procedia PDF Downloads 60

Authors: Habibi Said Mustafa, Hiroko Ono

Abstract:

Since 2006, Afghanistan is dealing with one of the most dramatic trend of urban movement in its history, cities and towns are expanding in size and number. Kabul is the capital of Afghanistan and as well as the fast-growing city in the Asia. The influx of the returnees from neighbor countries and other provinces of Afghanistan caused high rate of artificial growth which slums increased. As an unwanted consequence of this growth, today informal settlements have covered a vast portion of the city. Land Readjustment (LR) has proved to be an important tool for developing informal settlements and reorganizing urban areas but its implementation always varies from country to country and region to region within the countries. Consequently, to successfully develop the informal settlements in Kabul, we need to define an Afghan model of LR specifically for Afghanistan which needs to incorporate all those factors related to the socio-economic condition of the country. For this purpose, a part of the old city of Kabul has selected as a study area which is located near the Central Business District (CBD). After the further analysis and incorporating all needed factors, the result shows a positive potential for the implementation of an adaptable Land Readjustment model for Kabul city which is more sustainable and socio-economically friendly. It will enhance quality of life and provide better urban services for the residents. Moreover, it will set a vision and criteria by which sustainable developments shall proceed in other similar informal settlements of Kabul.

Keywords: adaptation, informal settlements, Kabul, land readjustment, preservation

Procedia PDF Downloads 187

Authors: Luana Parisi, Sohrab Donyavi

Abstract:

Cities have become the nodes of global networks, standing at the intersection points of the flows of capital, goods, workers, businesses and travellers, making them the spots where innovation, progress and economic development occur. The primary challenge for them is to create the most fertile ecosystems for triggering innovation activities. Design emerges as an essential feature in this process of laboratorisation of cities. This paper aims at exploring the spatial hubs of transformation within the knowledge economy, providing an overview of the current models of innovation spaces, before focusing on the innovation district of one of the cities that are riding the innovation wave, namely, Boston, USA. Useful lessons will be drawn from the case study of the innovation district in Boston, allowing to define precious tools for policymakers, in the form of a range of factors that define the broad strategy able to implement the model successfully. A mixed methodology is implemented, including information from observations, exploratory interviews to key stakeholders and on-desk data.

Keywords: Innovation District, innovation ecosystem, economic development, urban regeneration

Procedia PDF Downloads 97

Authors: Farid Eltom A. E., Mustafa Abdul-Halim, Abdalla Markaz, Sami Atta, Mohamed Azhari, Ahmed Rashed

Abstract:

Smart environment sensors integrated with ‘Internet of Things’ (IoT) technology can provide a new concept in tracking, sensing, and monitoring objects in the environment. The aim of the study is to evaluate the farm environmental monitoring system based on (IoT) and to realize the automated management of agriculture and the implementation of precision production. Until now, irrigation monitoring operations in Sudan have been carried out using traditional methods, which is a very costly and unreliable mechanism. However, by utilizing soil moisture sensors, irrigation can be conducted only when needed without fear of plant water stress. The result showed that software application allows farmers to display current and historical data on soil moisture and nutrients in the form of line charts. Design measurements of the soil factors: moisture, electrical, humidity, conductivity, temperature, pH, phosphorus, and potassium; these factors, together with a timestamp, are sent to the data server using the Lora WAN interface. It is considered scientifically agreed upon in the modern era that artificial intelligence works to arrange the necessary procedures to take care of the terrain, predict the quality and quantity of production through deep analysis of the various operations in agricultural fields, and also support monitoring of weather conditions.

Keywords: smart environment, monitoring systems, IoT, LoRa Gateway, center pivot

Procedia PDF Downloads 37

Authors: Kate Smith, Shuming Liu, Yi Liu, Dragan Savic, Gustaf Olsson, Tian Chang, Xue Wu

Abstract:

In a water supply system, a great deal of care goes into sourcing, treating and delivering water to consumers, but less thought is given to the energy consumed during these processes. This study uses 2011 data to quantify energy use for urban water supply in China and investigates population density as a possible influencing factor. The objective is to provide information that can be used to develop energy-conscious water infrastructure policy, calculate the energy co-benefits of water conservation and compare energy use between China and other countries. The average electrical energy intensity and per capita electrical energy consumption for urban water supply in China in 2011 were 0.29 kWh/m3 and 33.2 kWh/cap•yr, respectively. Comparison between provinces revealed a direct correlation between energy intensity of urban water supply and population served per unit length of pipe. This could imply energy intensity is lower when more densely populated areas are supplied by relatively dense networks of pipes. This study also found that whereas the percentage of energy used for urban water supply tends to increase with the percentage of population served this increase is slower where water supply is more energy efficient and where a larger percentage of population is already supplied.

Keywords: china, electrical energy use, water-energy nexus, water supply

Procedia PDF Downloads 482

Authors: Alexander Hempfing

Abstract:

The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

Procedia PDF Downloads 258

Authors: Moschos Vogiatzis, K. Perakis

Abstract:

Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: classification, land use/land cover, mapping, random forest

Procedia PDF Downloads 111

Authors: Moataz Ammar, Ahdab Elmorshedy

Abstract:

The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

Procedia PDF Downloads 380

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

Procedia PDF Downloads 133

Authors: Arsenio Jose Mindu

Abstract:

The concern to carry out a study related to Energy Efficiency arose based on the various debates in international television networks and not only, but also in several forums of national debates. The concept of Energy Efficiency is not yet widely disseminated and /or taken into account in terms of energy consumption, not only at the domestic level but also at the industrial level in Mozambique. In the context of the energy audit, the time during which each of the appliances is connected to the voltage source, the time during which they are in standby mode was recorded on a spreadsheet basis. Based on these data, daily and monthly consumption was calculated. In order to have more accurate information on the daily levels of daily consumption, the electricity consumption was read every hour of the day (from 5:00 am to 11:00 pm), since after 23:00 the energy consumption remains constant. For ten days. Based on the daily energy consumption and the maximum consumption power, the design of the photovoltaic system for the residence was made. With the implementation of the photovoltaic system in order to guarantee energy efficiency, there was a significant reduction in the use of electricity from the public grid, increasing from approximately 17 kwh per day to around 11 kwh, thus achieving an energy efficiency of 67.4 %. That is to say, there was a reduction not only in terms of the amount of energy consumed but also of the monthly expenses with electricity, having increased from around 2,500,00Mt (2,500 meticais) to around 800Mt per month.

Keywords: energy efficiency, photovoltaic system, residential sector, Mozambique

Procedia PDF Downloads 190

Authors: Nancy Ayman Kamal Mohamed Mehrz

Abstract:

As the economies of other countries in the Mediterranean Basin, the tourism sector in our country has a high denominator in economics. Tourism businesses, which are building blocks of tourism, sector faces with a variety of problems during their activities. These problems faced make business efficiency and competition conditions of the businesses difficult. Most of the problems faced by the tourism businesses and the information of consumers about consumers’ rights were used in this study, which is conducted to determine the problems of tourism businesses in the Central Anatolia Region. It is aimed to contribute the awareness of staff and executives working at tourism sector and to attract attention of businesses active concurrently with tourism sector and legislators. E-tourism is among the issues that have recently been entered into the field of tourism. In order to achieve this type of tourism, Information and Communications Technology (or ICT) infrastructures as well as Co-governmental organizations and tourism resources are important. In this study, the opinions of managers and tourism officials about the e-tourism in Leman city were measured; it also surveyed the impact of level of digital literacy of managers and tourism officials on attracting tourists. This study was conducted. One of the environs of the Esfahan province. This study is a documentary – survey and the sources include library resources and also questionnaires. The results obtained indicate that if managers use ICT, it may help e-tourism to be developed in the region, and increasing managers’ beliefs on e-tourism and upgrading their level of digital literacy may affect e-tourism development.

Keywords: financial problems, the problems of tourism businesses, tourism businesses, internet, marketing, tourism, tourism management economic competitiveness, enhancing competitiveness

Procedia PDF Downloads 56

Authors: John Onyima, Ikechukwu Ezepue

Abstract:

Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

Procedia PDF Downloads 287

Authors: Basak Ozkendirci

Abstract:

The discovery of chemical dyes, the development of regenerated fibers, and warp knitting technology have enormous effects on the fashion world. The trends created by the information obtained in the context of various studies today shape the fashion world. Trend analysts must follow scientific developments as well as sociological events, political developments and artwork to obtain healthy data on trends. Digital printing technologies have changed the dynamics of textile printing production and also the style of printed designs. Fashion designers already have started design 3D printed accessories and garments. The research fields like the internet of things, artificial intelligence, hologram technologies, mechatronics, energy storage systems, nanotechnology are seen as the technologies that will change the social life and economy of the future. It is clear that research carried out in these areas will affect the textiles of the future and whereat the trends of fashion. The article aims to create a future vision for trend researchers and designers by giving clues about the changes to be experienced in the fashion world. In the first part of the article, information about the scientific studies that are thought to shape the future is given, and the forecasting about how the inventions that can be obtained from these studies can be adapted at the textile are presented. In the second part of the article, examples of how the new generation of innovative textiles will affect the daily life experience of the user are given.

Keywords: biotextiles, fashion trends, nanotextiles, new materials, smart textiles, techno textiles

Procedia PDF Downloads 326

Authors: A. Alem, Y. Dahmani, A. Hadjali, A. Boualem

Abstract:

Managing the problem of the conflict, either by using the Dempster-Shafer theory, or by the application of the fusion process to push researchers in recent years to find ways to get to make best decisions especially; for information systems, vision, robotic and wireless sensor networks. In this paper we are interested to take account of the conflict in the combination step that took the conflict into account and tries to manage such a way that it does not influence the decision step, the conflict what from reliable sources. According to [1], the conflict lead to erroneous decisions in cases where was with strong degrees between sources of information, if the conflict is more than the maximum of the functions of belief mass K > max1...n (mi (A)), then the decision becomes impossible. We will demonstrate in this paper that the multiplication of mass functions by coefficients of reliability is a decreasing function; it leads to the reduction of conflict and a good decision. The definition of reliability coefficients accurately and multiply them by the mass functions of each information source to resolve the conflict and allow deciding whether the degree of conflict. The evaluation of this technique is done by a use case; a comparison of the combination of springs with a maximum conflict without, and with reliability coefficients.

Keywords: Dempster-Shafer theory, fusion process, conflict managing, reliability factors, decision

Procedia PDF Downloads 411

Authors: Khalidou Ba, Abdelkrim Chahine, Mohamed Ebn Touhami

Abstract:

A strong industrial interest is focused on the development of coatings for anticorrosion protection. In this context, phosphate composite materials are expanding strongly due to their chemical characteristics and their interesting physicochemical properties. Sol-gel coatings offer high homogeneity and purity that may lead to obtain coating presenting good adhesion to metal surface. The goal behind this work is to develop efficient coatings for corrosion protection of steel to extend its life. In this context, a sol gel process allowing to obtain thin film coatings on carbon steel with high resistance to corrosion has been developed. The optimization of several experimental parameters such as the hydrolysis time, the temperature, the coating technique, the molar ratio between precursors, the number of layers and the drying mode has been realized in order to obtain a coating showing the best anti-corrosion properties. The effect of these parameters on the microstructure and anticorrosion performance of the films sol gel coating has been investigated using different characterization methods (FTIR, XRD, Raman, XPS, SEM, Profilometer, Salt Spray Test, etc.). An optimized coating presenting good adhesion and very stable anticorrosion properties in salt spray test, which consists of a corrosive attack accelerated by an artificial salt spray consisting of a solution of 5% NaCl, pH neutral, under precise conditions of temperature (35 °C) and pressure has been obtained.

Keywords: sol gel, coating, corrosion, XPS

Procedia PDF Downloads 117

Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

Abstract:

The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation

Procedia PDF Downloads 474

Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

Abstract:

Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

Procedia PDF Downloads 104

Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

Abstract:

Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

Procedia PDF Downloads 161

Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

Abstract:

Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

Procedia PDF Downloads 97

Authors: A. Fayad, Q. Alqhazaly, T. Cinkler

Abstract:

In light of the substantial increase in end-user requirements and the incessant need of network operators to upgrade the capabilities of access networks, in this paper, the performance of the different modulation formats on eight-channels Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) transmission system has been examined and compared. Limitations and features of modulation formats have been determined to outline the most suitable design to enhance the data rate and transmission reach to obtain the best performance of the network. The considered modulation formats are On-Off Keying Non-Return-to-Zero (NRZ-OOK), Carrier Suppressed Return to Zero (CSRZ), Duo Binary (DB), Modified Duo Binary (MODB), Quadrature Phase Shift Keying (QPSK), and Differential Quadrature Phase Shift Keying (DQPSK). The performance has been analyzed by varying transmission distances and bit rates under different channel spacing. Furthermore, the system is evaluated in terms of minimum Bit Error Rate (BER) and Quality factor (Qf) without applying any dispersion compensation technique, or any optical amplifier. Optisystem software was used for simulation purposes.

Keywords: BER, DuoBinary, NRZ-OOK, TWDM-PON

Procedia PDF Downloads 131

Authors: Jaturong Matidtor, Krisna R. Torrissen, Saengtong Pongjareankit, Sudaporn Tongsiri, Jiraporn Rojtinnakorn

Abstract:

Low survival rate has being particular problem in nursery of marble goby juvenile. The aim of this study was to investigate effect of garlic extract on protein digestive pancreatic enzymes, trypsin (T) and chymotrypsin (C). The marble goby were reared with commercial feed mixed garlic extract at concentration of 0 (control), 0.3, 0.5, 1.0, 3.0 and 5.0% (w/w) for 6 weeks. Analysis of the digestive enzymes at 2 and 6 weeks was performed. Growth parameters; weight gain (WG), specific growth rate (SGR) and feed efficiency (FE), were identified. For T, C and T/C at 2 weeks, values of T and T/C ratio of 0.3% (w/w) group showed significant difference (p < 0.05) with the highest values of 17685.64± 11981.77 U/mg protein and of 51.64 ± 27.46 U/mg protein, respectively. For C at 2 weeks, 0% (w/w) group showed the highest values of 16191.76± 2225.56 U/mg protein. Whereas value of T, C and T/C ratio at 6 weeks, there was no significant difference (p > 0.05). For growth performance, it significantly increased in all garlic extract fed groups (0.3-5.0%, w/w), both at 2 and 6 weeks. At 2 weeks, values of WG and SGR of 0.5% (w/w) group showed the highest values of 71.51 ± 1.60%, and 3.85 ± 0.07%, respectively. For FE, 0.3% (w/w) group showed the highest value of 60.21 ± 6.51%. At 6 weeks, it illustrated that all growth parameters of 5.0% (w/w) group were the highest values; WG = 35.06 ± 5.66%, SGR = 2.14 ± 0.30%, and FE = 5.86 ± 0.68%. We suggested that garlic extract could be available for protein digestive enzyme and growth enhancement in marble goby nursery with artificial feed. This result will be high benefit for commercial aquaculture of marble goby.

Keywords: marble goby, nursery, garlic extract, digestive enzyme, growth

Procedia PDF Downloads 307

Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

Abstract:

Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

Procedia PDF Downloads 275