Search results for: Artificial Neural network

Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

Abstract:

In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

Procedia PDF Downloads 307

Authors: Abdul Basit Kiani, Maryam Kiani

Abstract:

Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

Procedia PDF Downloads 76

Authors: Carla Idely Palencia-Aguilar

Abstract:

Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

Procedia PDF Downloads 116

Authors: Boon Lee

Abstract:

Research publication is an essential output of universities because it not only promotes university recognition, it also receives government funding. The history of university research culture has been one of ‘publish or perish’ and universities have consistently encouraged their academics and researchers to produce research articles in reputable journals in order to maintain a level of competitiveness. In turn, the United Kingdom (UK) government funding is determined by the number and quality of research publications. This paper aims to investigate on whether more government funding leads to more quality papers. To that end, the paper employs a Network DEA model to evaluate the UK higher education performance over a period. Sources of efficiency are also determined via second stage regression analysis.

Keywords: efficiency, higher education, network data envelopment analysis, universities

Procedia PDF Downloads 112

Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

Abstract:

The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

Procedia PDF Downloads 127

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

Procedia PDF Downloads 60

Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

Abstract:

In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

Procedia PDF Downloads 61

Authors: Nidhal Azawi

Abstract:

Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

Procedia PDF Downloads 110

Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

Abstract:

The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

Procedia PDF Downloads 472

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

Abstract:

The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

Procedia PDF Downloads 145

Authors: Henry Hexmoor, Kailash Yelasani

Abstract:

We present vehicular platooning as a special case of crowd-sensing framework where sharing sensory information among a crowd is used for their collective benefit. After offering an abstract policy that governs processes involving a vehicular platoon, we review several common scenarios and components surrounding vehicular platooning. We then present a simulated prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that one of the paramount benefits of platooning that is overlooked elsewhere, is the substantial computational savings (i.e., economizing benefits) in acquisition and processing of sensory data among vehicles sharing the road. The most capable vehicle can share data gathered from its sensors with nearby vehicles grouped into a platoon.

Keywords: cloud network, collaboration, internet of things, social network

Procedia PDF Downloads 190

Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang

Abstract:

In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.

Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning

Procedia PDF Downloads 417

Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

Abstract:

The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

Procedia PDF Downloads 341

Authors: José Anderson Rodrigues de Souza, Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, Jeronimo Silva Rocha

Abstract:

Mobile devices are increasingly occupying sectors of society and one of its most important features is mobility. However, the use of mobile devices is subject to the lifetime of the batteries. Thus, the use of energy batteries has become an important issue in the study of wireless network technologies. In this context, new solutions that enable aggregate energy efficiency not only through energy saving, and principally they are evaluated from a more realistic model of energy discharge, if easy adaptation to existing protocols. This paper presents a study on the energy needed and the lifetime for Wireless Sensor Networks (WSN) using a heterogeneous network and applying the LEACH protocol.

Keywords: wireless sensor networks, energy efficiency, heterogeneous, LEACH protocol

Procedia PDF Downloads 575

Authors: Pi Hsia Liang

Abstract:

The rise of Facebook, Twitter, and other social networks significantly changes in interconnections between people, enhancing the process of information dissemination and amplify the influence of that information. Therefore, to develop informational efficiency or signaling equilibrium type of information environment among social networks, without adverse selection effects, becomes an important issue. Thus, someone may post a piece of intentional information in relation to personal interest for trying to create marginal influence. Therefore, economists are seeking to establish theories of informational efficiency under social network environment in order to resolve adverse selection issues. Reputation could be one of the important factors in the process of creating informational efficiency. Additionally, investors how to process green information, or information of corporate social responsibility is a very important study. This study essentially employs experimental study for examining how investors use stock relevant green information in Facebook and various Taiwan local networks. Facebook, and blogs of Money DJ, Technews and cnYES, respectively, are the primary sites for this examination that also allow to differentiate effects between Facebook and other local social networks. Questionnaire is developed for such an experimental testing. Note that questionnaire allows this study to group, for example, decision frequency and length of time duration focusing on social networks that are used for discriminating investor type and competence of informed investor. This study selects 500 investors that can be separated into two respective 250 samples as the control group and 250 samples in such an experimental. The quantity of sample investor sufficiently results in statistic significance of this experimental study. The empirical results of this study can be used for explaining how financial information in relation to corporate social responsibility would be disseminated in social websites. Therefore, we can lead to better interpretation of price/earnings relationship type of study and empirical studies of green information usefulness or informational efficiency Note that the above mentioned empirical studies did not exist any social network and annual report of corporate social responsibility. This study expects to find the results that both network degree and network cluster significantly affected green information dissemination frequency. In other words, investors with more connections and with high clustered connections might exert a greater influence on their green information dissemination process. The preferred users of financial social networks could make better stock decision that could amplify effects of green information. In addition, Facebook would be more influential than other local Taiwan financial social networks, although Facebook is not a specialized financial social network. In other words, the popularity and reputation effects of Facebook significantly contribute to usefulness of green information and influence of green information. Third, it has a better chance to find rumor or cheating information in local Taiwan financial social networks than Facebook. In other words, Facebook possesses reputation effect, or a better informational efficiency. Or, even though Taiwan local financial social networks have marginal informational effects on stock price, because of shortage of informational efficiency or monitoring system, information could be a tool for those whom owning superior information.

Keywords: network effect on financial services, informational efficiency theory, social networks, social websites

Procedia PDF Downloads 242

Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

Abstract:

The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control

Procedia PDF Downloads 335

Authors: Yun-Chung Yu, Yan-Wen Wang, Min-Sheng Liao, Joe-Air Jiang, Yuen-Chung Lee

Abstract:

This paper proposes to use a Long Range Wide Area Network (LoRaWAN) for a smart pest monitoring system which aims at the oriental fruit fly (Bactrocera dorsalis) to improve the communication efficiency of the system. The oriental fruit fly is one of the main pests in Southeast Asia and the Pacific Rim. Different smart pest monitoring systems based on the Internet of Things (IoT) architecture have been developed to solve problems of employing manual measurement. These systems often use Octopus II, a communication module following the 2.4GHz IEEE 802.15.4 ZigBee specification, as sensor nodes. The Octopus II is commonly used in low-power and short-distance communication. However, the energy consumption increase as the logical topology becomes more complicate to have enough coverage in the large area. By comparison, LoRaWAN follows the Low Power Wide Area Network (LPWAN) specification, which targets the key requirements of the IoT technology, such as secure bi-directional communication, mobility, and localization services. The LoRaWAN network has advantages of long range communication, high stability, and low energy consumption. The 433MHz LoRaWAN model has two superiorities over the 2.4GHz ZigBee model: greater diffraction and less interference. In this paper, The Octopus II module is replaced by a LoRa model to increase the coverage of the monitoring system, improve the communication performance, and prolong the network lifetime. The performance of the LoRa-based system is compared with a ZigBee-based system using three indexes: the packet receiving rate, delay time, and energy consumption, and the experiments are done in different settings (e.g. distances and environmental conditions). In the distance experiment, a pest monitoring system using the two communication specifications is deployed in an area with various obstacles, such as buildings and living creatures, and the performance of employing the two communication specifications is examined. The experiment results show that the packet receiving the rate of the LoRa-based system is 96% , which is much higher than that of the ZigBee system when the distance between any two modules is about 500m. These results indicate the capability of a LoRaWAN-based monitoring system in long range transmission and ensure the stability of the system.

Keywords: LoRaWan, oriental fruit fly, IoT, Octopus II

Procedia PDF Downloads 349

Authors: Lina Abou Haibeh, Nadir Hakem, Ousama Abu Safia

Abstract:

In this paper, the performance and quality of Voice over IP (VoIP) calls carried over a Mobile Ad Hoc Network (MANET) which has a number of SIP nodes registered on a SIP Proxy are analyzed. The testing campaigns are carried out in an indoor corridor structure having a well-defined channel’s characteristics and model for the different voice codecs, G.711, G.727 and G.723.1. These voice codecs are commonly used in VoIP technology. The calls’ quality are evaluated using four Quality of Service (QoS) metrics, namely, mean opinion score (MOS), jitter, delay, and packet loss. The relationship between the wireless channel’s parameters and the optimum codec is well-established. According to the experimental results, the voice codec G.711 has the best performance for the proposed MANET topology

Keywords: wireless channel modelling, Voip, MANET, session initiation protocol (SIP), QoS

Procedia PDF Downloads 222

Authors: Mohd Salmi Md Noorani, Ghada Al-Mahbashi, Sakhinah Abu Bakar

Abstract:

This paper investigates projective lag synchronization (PLS) behavior in drive response dynamical networks (DRDNs) model with identical nodes. A hybrid feedback control method is designed to achieve the PLS with mismatch and without mismatch terms. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Moreover, the numerical simulations results demonstrate the validity of the proposed method.

Keywords: drive-response dynamical network, projective lag synchronization, hybrid feedback control, stability theory

Procedia PDF Downloads 388

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

Procedia PDF Downloads 302

Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

Abstract:

The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

Procedia PDF Downloads 415

Authors: Bahaa Eldin A. Fouda, Khaled N. Yossef, Mohamed Elhosseny, Ahmed Lotfy, Mohamed Salama, Mohamed Sobh

Abstract:

Developmental neurotoxicity (DNT) entails the toxic effects imparted by various chemicals on the brain during the early childhood period. As human brains are vulnerable during this period, various chemicals would have their maximum effects on brains during early childhood. Some toxicants have been confirmed to induce developmental toxic effects on CNS e.g. lead, however; most of the agents cannot be identified with certainty due the defective nature of predictive toxicology models used. A novel alternative method that can overcome most of the limitations of conventional techniques is the use of 3D neurospheres system. This in-vitro system can recapitulate most of the changes during the period of brain development making it an ideal model for predicting neurotoxic effects. In the present study, we verified the possible DNT of epoxomicin which is a naturally occurring selective proteasome inhibitor with anti-inflammatory activity. Rat neural progenitor cells were isolated from rat embryos (E14) extracted from placental tissue. The cortices were aseptically dissected out from the brains of the fetuses and the tissues were triturated by repeated passage through a fire-polished constricted Pasteur pipette. The dispersed tissues were allowed to settle for 3 min. The supernatant was, then, transferred to a fresh tube and centrifuged at 1,000 g for 5 min. The pellet was placed in Hank’s balanced salt solution cultured as free-floating neurospheres in proliferation medium. Two doses of epoxomicin (1µM and 10µM) were used in cultured neuropsheres for a period of 14 days. For proliferation analysis, spheres were cultured in proliferation medium. After 0, 4, 5, 11, and 14 days, sphere size was determined by software analyses. The diameter of each neurosphere was measured and exported to excel file further to statistical analysis. For viability analysis, trypsin-EDTA solution were added to neurospheres for 3 min to dissociate them into single cells suspension, then viability evaluated by the Trypan Blue exclusion test. Epoxomicin was found to affect proliferation and viability of neuropsheres, these effects were positively correlated to doses and progress of time. This study confirms the DNT effects of epoxomicin on 3D neurospheres model. The effects on proliferation suggest possible gross morphologic changes while the decrease in viability propose possible focal lesion on exposure to epoxomicin during early childhood.

Keywords: neural progentor cells, epoxomicin, neurosphere, medical and health sciences

Procedia PDF Downloads 421

Authors: A. M. Raseona, D. M. Barry, T. L. Nedambale

Abstract:

Preservation of semen is an important process to ensure that semen quality is sufficient for assisted reproductive technology. This study evaluated the effectiveness of different extenders to preserve Nguni bull semen stored at controlled room temperature 24 °C for three days, as an alternative to frozen-thawed semen straws used for artificial insemination. Semen samples were collected from two Nguni bulls using an electro-ejaculator and transported to the laboratory for evaluation. Pooled semen was aliquot into three extenders Triladyl, Ham’s F10 and M199 at a dilution ratio of 1:4 then stored at controlled room temperature 24 °C. Sperm motility was analysed after 0, 24, 48 and 72 hours. Morphology and viability were analysed after 72 hours. The study was replicated four times and data was analysed by analysis of variance (ANOVA). Triladyl showed higher viability percentage and consistent total motility for three days. Ham’s F10 showed higher progressive motility compared to the other extenders. There was no significant difference in viability between Ham’s F10 and M199. No significant difference was also observed in total abnormality between the two Nguni bulls. In conclusion, Nguni semen can be preserved in Triladyl or Ham’s F10 and M199 culture media stored at 24 °C and stay alive for three days. Triladyl proved to be the best extender showing high viability and consistency in total motility as compared to Ham’s F10 and M199.

Keywords: bull semen, artificial insemination, Triladyl, Ham’s F10, M199, viability

Procedia PDF Downloads 498

Authors: Mohamed Lotfy, Ghada Soliman

Abstract:

Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

Procedia PDF Downloads 84

Authors: Bilal Haider, Farhan Aadil

Abstract:

A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

Procedia PDF Downloads 167

Authors: Tzu-Jung Huang, Hsun-Jung Cho, Chien-Chia Liäm Huang

Abstract:

To improve the level of service (LoS) of urban arterial systems containing a series of signalized intersections, a proper design of offsets for all intersections associated is of great importance. The MAXBAND model has been the most common approach for this purpose. In this paper, we propose a MAXBAND model with phase constraints so that the lengths of the phases in a cycle are variable. In other words, the length of a cycle is also variable in our setting. We conduct experiments on a real-world traffic network, having several major paths, in Taiwan for numerical evaluations. Actual traffic data were collected through on-site experiments. Numerical evidences suggest that the improvements are around 32%, on average, in terms of total delay of the entire network.

Keywords: arterial progression, MAXBAND, signal control, offset

Procedia PDF Downloads 352

Authors: Karina Guimaraes, Lilian Santos

Abstract:

This study has the purpose of planning and instituting monitoring actions as a way of knowing the scenario of assistance to the patient with stoma, treated in the public health network in Brazil, from January to November of the year 2016, from the elaboration of a technical document containing the survey of the number of procedures offered and the value of the ostomy services, accredited in the Unified Health System-SUS. The purpose of this document is to improve the quality of these services in the efficient management of available financial resources, making it indispensable for the creation of strategies for the implementation and implementation of care services for people with stomata as a strategic tool in the promotion, prevention, qualification and efficiency in health care.

Keywords: health economic, management, ostomy, unified health system

Procedia PDF Downloads 309

Authors: Wided Abidi, Tahar Ezzedine

Abstract:

Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

Procedia PDF Downloads 328

Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

Abstract:

Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

Procedia PDF Downloads 129

Authors: F. Z. Benabid, F. Zouai, A. Douibi, D. Benachour

Abstract:

These Fluorinated polymers and polyacrylics have known a wide use in the field of historical monuments. PVDF provides a great easiness to processing, a good UV resistance and good chemical inertia. Although the quality of physical characteristics of the PMMA and its low price with a respect to PVDF, its deterioration against UV radiations limits its use as protector agent for the stones. On the other hand, PVDF/PMMA blend is a compromise of a great development in the field of architectural restoration, since it is the best method in term of quality and price to make new polymeric materials having enhanced properties. Films of different compositions based on the two polymers within an adequate solvent (DMF) were obtained to perform an exposition to artificial ageing and to the salted fog, a spectroscopic analysis (FTIR and UV) and optical analysis (refractive index). Based on its great interest in the field of building, a variety of standard tests has been elaborated for the first time at the central laboratory of ENAP (Souk-Ahras) in order to evaluate our blend performance. The obtained results have allowed observing the behavior of the different compositions of the blend under various tests. The addition of PVDF to PMMA enhances the properties of this last to know the exhibition to the natural and artificial ageing and to the saline fog. On the other hand, PMMA enhances the optical properties of the blend. Finally, 70/30 composition of the blend is in concordance with results of previous works and it is the adequate proportion for an eventual application.

Keywords: blend, PVDF, PMMA, preservation, historic monuments

Procedia PDF Downloads 304