Search results for: convolutional recurrent networks
2526 Artificial Neural Network Modeling of a Closed Loop Pulsating Heat Pipe
Authors: Vipul M. Patel, Hemantkumar B. Mehta
Abstract:
Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant
Procedia PDF Downloads 2852525 Generating Swarm Satellite Data Using Long Short-Term Memory and Generative Adversarial Networks for the Detection of Seismic Precursors
Authors: Yaxin Bi
Abstract:
Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors
Procedia PDF Downloads 262524 Neural Network Based Approach of Software Maintenance Prediction for Laboratory Information System
Authors: Vuk M. Popovic, Dunja D. Popovic
Abstract:
Software maintenance phase is started once a software project has been developed and delivered. After that, any modification to it corresponds to maintenance. Software maintenance involves modifications to keep a software project usable in a changed or a changing environment, to correct discovered faults, and modifications, and to improve performance or maintainability. Software maintenance and management of software maintenance are recognized as two most important and most expensive processes in a life of a software product. This research is basing the prediction of maintenance, on risks and time evaluation, and using them as data sets for working with neural networks. The aim of this paper is to provide support to project maintenance managers. They will be able to pass the issues planned for the next software-service-patch to the experts, for risk and working time evaluation, and afterward to put all data to neural networks in order to get software maintenance prediction. This process will lead to the more accurate prediction of the working hours needed for the software-service-patch, which will eventually lead to better planning of budget for the software maintenance projects.Keywords: laboratory information system, maintenance engineering, neural networks, software maintenance, software maintenance costs
Procedia PDF Downloads 3482523 Representativity Based Wasserstein Active Regression
Authors: Benjamin Bobbia, Matthias Picard
Abstract:
In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression
Procedia PDF Downloads 782522 Influence of the Refractory Period on Neural Networks Based on the Recognition of Neural Signatures
Authors: José Luis Carrillo-Medina, Roberto Latorre
Abstract:
Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network
Procedia PDF Downloads 4842521 Impact of Social Networks on Agricultural Technology Adoption: A Case Study of Ongoing Extension Programs for Paddy Cultivation in Matara District in Sri Lanka
Authors: Paulu Saramge Shalika Nirupani Seram
Abstract:
The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.Keywords: agricultural extension, paddy cultivation, social network, technology adoption
Procedia PDF Downloads 562520 Double Encrypted Data Communication Using Cryptography and Steganography
Authors: Adine Barett, Jermel Watson, Anteneh Girma, Kacem Thabet
Abstract:
In information security, secure communication of data across networks has always been a problem at the forefront. Transfer of information across networks is susceptible to being exploited by attackers engaging in malicious activity. In this paper, we leverage steganography and cryptography to create a layered security solution to protect the information being transmitted. The first layer of security leverages crypto- graphic techniques to scramble the information so that it cannot be deciphered even if the steganography-based layer is compromised. The second layer of security relies on steganography to disguise the encrypted in- formation so that it cannot be seen. We consider three cryptographic cipher methods in the cryptography layer, namely, Playfair cipher, Blowfish cipher, and Hills cipher. Then, the encrypted message is passed through the least significant bit (LSB) to the steganography algorithm for further encryption. Both encryption approaches are combined efficiently to help secure information in transit over a network. This multi-layered encryption is a solution that will benefit cloud platforms, social media platforms and networks that regularly transfer private information such as banks and insurance companies.Keywords: cryptography, steganography, layered security, Cipher, encryption
Procedia PDF Downloads 742519 The Impact of Neighbourhood Built-Environment on the Formulation and Facilitation of Bottom-up Mutual Help Networks for Senior Residents in Singapore
Authors: Wei Zhang, Chye Kiang Heng, John Chye Fung
Abstract:
Background: The world’s demographics is currently undergoing the largest wave of both rapid ageing and dramatic urbanisation in human history. As one of the most rapidly ageing countries, Singapore will see about one in four residents aged 65 years and above by 2030 in its high-rise and high-density urban environment. Research questions: To support urban seniors ageing in place and interdependence among senior residents and their informal caregivers, this study argues a community-based care model with bottom-up mutual help networks and asks how neighbourhood built-environment influences the formulation and facilitation of bottom-up mutual help networks in Singapore. Methods: Two public housing communities with different physical environment and rich age-friendly neighbourhood initiatives were chosen as the case studies. The categories, participants and places of bottom-up mutual help activities will be obtained via field observation, non-structural interviews of participants, service providers and managers of care facilities, and documents. Mapping and content analysis will be used to explore the influences of neighbourhood built-environment on the formulation and facilitation of bottom-up mutual help networks. Results and conclusions: The results showed that neighbourhood design, place programming, and place governance have a confluence on the bottom-up mutual help networks for senior residents. Significance: The outcomes of this study will provide fresh evidence for paradigm shifts of community-based care for the elderly and neighbourhood planning. In addition, the research findings will shed light on meaningful implications of urban planners and policy makers as they tackle with the issues arising from the ageing society.Keywords: Built environment, Mutual help, Neighbourhood, Senior residents, Singapore
Procedia PDF Downloads 1342518 Investigation of Delivery of Triple Play Service in GE-PON Fiber to the Home Network
Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar
Abstract:
Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT
Procedia PDF Downloads 7252517 Increase in the Persistence of Various Invaded Multiplex Metacommunities Induced by Heterogeneity of Motifs
Authors: Dweepabiswa Bagchi, D. V. Senthilkumar
Abstract:
Numerous studies have typically demonstrated the devastation of invasions on an isolated ecosystem or, at most, a network of dispersively coupled similar ecosystem patches. Using such a simplistic 2-D network model, one can only consider dispersal coupling and inter-species trophic interactions. However, in a realistic ecosystem, numerous species co-exist and interact trophically and non-trophically in groups of 2 or more. Even different types of dispersal can introduce complexity in an ecological network. Therefore, a more accurate representation of actual ecosystems (or ecological networks) is a complex network consisting of motifs formed by two or more interacting species. Here, the apropos structure of the network should be multiplex or multi-layered. Motifs between different patches or species should be identical within the same layer and vary from one layer to another. This study investigates three distinct ecological multiplex networks facing invasion from one or more external species. This work determines and quantifies the criteria for the increased extinction risk of these networks. The dynamical states of the network with high extinction risk, i.e., the danger states, and those with low extinction risk, i.e., the resistive network states, are both subsequently identified. The analysis done in this study further quantifies the persistence of the entire network corresponding to simultaneous changes in the strength of invasive dispersal and higher-order trophic and non-trophic interactions. This study also demonstrates that the ecosystems enjoy an inherent advantage against invasions due to their multiplex network structure.Keywords: increased ecosystem persistence, invasion on ecosystems, multiplex networks, non-trophic interactions
Procedia PDF Downloads 572516 Construction of the Large Scale Biological Networks from Microarrays
Authors: Fadhl Alakwaa
Abstract:
One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method.Keywords: gene regulatory network, biclustering, denoising, system biology
Procedia PDF Downloads 2282515 A Location-based Authentication and Key Management Scheme for Border Surveillance Wireless Sensor Networks
Authors: Walid Abdallah, Noureddine Boudriga
Abstract:
Wireless sensor networks have shown their effectiveness in the deployment of many critical applications especially in the military domain. Border surveillance is one of these applications where a set of wireless sensors are deployed along a country border line to detect illegal intrusion attempts to the national territory and report this to a control center to undergo the necessary measures. Regarding its nature, this wireless sensor network can be the target of many security attacks trying to compromise its normal operation. Particularly, in this application the deployment and location of sensor nodes are of great importance for detecting and tracking intruders. This paper proposes a location-based authentication and key distribution mechanism to secure wireless sensor networks intended for border surveillance where the key establishment is performed using elliptic curve cryptography and identity-based public key scheme. In this scheme, the public key of each sensor node will be authenticated by keys that depend on its position in the monitored area. Before establishing a pairwise key between two nodes, each one of them must verify the neighborhood location of the other node using a message authentication code (MAC) calculated on the corresponding public key and keys derived from encrypted beacon messages broadcast by anchor nodes. We show that our proposed public key authentication and key distribution scheme is more resilient to node capture and node replication attacks than currently available schemes. Also, the achievement of the key distribution between nodes in our scheme generates less communication overhead and hence increases network performances.Keywords: wireless sensor networks, border surveillance, security, key distribution, location-based
Procedia PDF Downloads 6512514 Wireless Information Transfer Management and Case Study of a Fire Alarm System in a Residential Building
Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar
Abstract:
The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system
Procedia PDF Downloads 492513 Interorganizational Relationships in the Brazilian Milk Production Chain
Authors: Marcelo T. Okano, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi
Abstract:
The literature on the interorganizational relationship between companies and organizations has increased in recent years, but there are still doubts about the various settings. The interorganizational networks are important in economic life, the fact facilitate the complex interdependence between transactional and cooperative organizations. A need identified in the literature is the lack of indicators to measure and identify the types of existing networks. The objective of this research is to examine the interorganizational relationships of two milk chains through indicators proposed by the theories of the four authors, characterizing them as network or not and what the benefits obtained by the chain organization. To achieve the objective of this work was carried out a survey of milk producers in two regions of the state of São Paulo. To collect the information needed for the analysis, exploratory research, qualitative nature was used. The research instrument of this work consists of a roadmap of semistructured interviews with open questions. Some of the answers were directed by the interviewer in the form of performance notes aimed at detecting the degree of importance, according to the perception of intensity to that regard. The results showed that interorganizational relationships are small and largely limited to the sale of milk or dairy cooperatives. These relationships relate only to trade relations between the owner and purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships and increase benefits for all participants in the network. The various visits and interviews in several dairy farms in the regions of São Pau-lo (indicated that the inter-relationships are small and largely limited to the sale of milk to cooperatives or dairy. These relationships refer only to trade relations between the owner and the purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships increase and bring benefits to all participants in the network.Keywords: interorganizational networks, dairy chain, interorganizational system, São Pau-lo
Procedia PDF Downloads 5742512 Peak Frequencies in the Collective Membrane Potential of a Hindmarsh-Rose Small-World Neural Network
Authors: Sun Zhe, Ruggero Micheletto
Abstract:
As discussed extensively in many studies, noise in neural networks have an important role in the functioning and time evolution of the system. The mechanism by which noise induce stochastic resonance enhancing and influencing certain operations is not clarified nor is the mechanism of information storage and coding. With the present research we want to study the role of noise, especially focusing on the frequency peaks in a three variable Hindmarsh−Rose Small−World network. We investigated the behaviour of the network to external noises. We demonstrate that a variation of signal to noise ratio of about 10 dB induces an increase in membrane potential signal of about 15%, averaged over the whole network. We also considered the integral of the whole membrane potential as a paradigm of internal noise, the one generated by the brain network. We showed that this internal noise is attenuated with the size of the network or with the number of random connections. By means of Fourier analysis we found that it has distinct peaks of frequencies, moreover, we showed that increasing the size of the network introducing more neurons, reduced the maximum frequencies generated by the network, whereas the increase in the number of random connections (determined by the small-world probability p) led to a trend toward higher frequencies. This study may give clues on how networks utilize noise to alter the collective behaviour of the system in their operations.Keywords: neural networks, stochastic processes, small-world networks, discrete Fourier analysis
Procedia PDF Downloads 2862511 Seamless Mobility in Heterogeneous Mobile Networks
Authors: Mohab Magdy Mostafa Mohamed
Abstract:
The objective of this paper is to introduce a vertical handover (VHO) algorithm between wireless LANs (WLANs) and LTE mobile networks. The proposed algorithm is based on the fuzzy control theory and takes into consideration power level, subscriber velocity, and target cell load instead of only power level in traditional algorithms. Simulation results show that network performance in terms of number of handovers and handover occurrence distance is improved.Keywords: vertical handover, fuzzy control theory, power level, speed, target cell load
Procedia PDF Downloads 3422510 Rumour Containment Using Monitor Placement and Truth Propagation
Authors: Amrah Maryam
Abstract:
The emergence of online social networks (OSNs) has transformed the way we pursue and share information. On the one hand, OSNs provide great ease for the spreading of positive information while, on the other hand, they may also become a channel for the spreading of malicious rumors and misinformation throughout the social network. Thus, to assure the trustworthiness of OSNs to its users, it is of vital importance to detect the misinformation propagation in the network by placing network monitors. In this paper, we aim to place monitors near the suspected nodes with the intent to limit the diffusion of misinformation in the social network, and then we also detect the most significant nodes in the network for propagating true information in order to minimize the effect of already diffused misinformation. Thus, we initiate two heuristic monitor placement using articulation points and truth propagation using eigenvector centrality. Furthermore, to provide real-time workings of the system, we integrate both the monitor placement and truth propagation entities as well. To signify the effectiveness of the approaches, we have carried out the experiment and evaluation of Stanford datasets of online social networks.Keywords: online social networks, monitor placement, independent cascade model, spread of misinformation
Procedia PDF Downloads 1532509 Using Pump as Turbine in Drinking Water Networks to Monitor and Control Water Processes Remotely
Authors: Sara Bahariderakhshan, Morteza Ahmadifar
Abstract:
Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. In the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PaT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and, therefore, more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore due to increasing the area of the network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PaT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.Keywords: new energies, pump as turbine, drinking water, distribution network, remote control equipments
Procedia PDF Downloads 4582508 Comparison between LQR and ANN Active Anti-Roll Control of a Single Unit Heavy Vehicle
Authors: Babesse Saad, Ameddah Djemeleddine
Abstract:
In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.Keywords: rollover, single unit heavy vehicle, neural networks, nonlinear side force
Procedia PDF Downloads 4642507 Downscaling Daily Temperature with Neuroevolutionary Algorithm
Authors: Min Shi
Abstract:
State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms
Procedia PDF Downloads 3432506 Diaper Dermatitis and Pancytopenia as the Primary Manifestation in an Infant with Vitamin B12 Deficiency
Authors: Ekaterina Sánchez Romero, Emily Gabriela Aguirre Herrera, Sandra Luz Espinoza Esquerra, Jorge García Campos
Abstract:
Female, 7 months old, daughter of a mother with anemia during pregnancy, with no history of atopy in the family, since birth she presents with recurrent dermatological and gastrointestinal infections, chronically treated for recurrent diaper dermatitis. At 6 months of age, she begins with generalized pallor, hyperpigmentation in hands and feet, smooth tongue, psychomotor retardation with lack of head support, sedation, and hypoactivity. She was referred to our hospital for a fever of 38°C, severe diaper rash, and pancytopenia with HB 9.3, platelets 38000, neutrophils 0.39 MCV: 86.80 high for her age. The approach was initiated to rule out myeloproliferative syndrome, with negative immunohistochemical results of bone marrow aspirate; during her stay, she presented neurological regression, lack of sucking, and focal seizures. CT scan showed cortical atrophy. The patient was diagnosed with primary immunodeficiency due to history; gamma globulin was administered without improvement with normal results of immunoglobulins and metabolic screening. When dermatological and neurological diagnoses were ruled out as the primary cause, a nutritional factor was evaluated, and a therapeutic trial was started with the administration of vitamin B12 and zinc, presenting clinical neurological improvement and resolution of pancytopenia in 2 months. It was decided to continue outpatient management. Discussion: We present a patient with neurological, dermatological involvement, and pancytopenia, so the most common differential diagnoses in this population were ruled out. Vitamin B12 deficiency is an uncommon entity. Due to maternal and clinical history, a therapeutic trial was started resulting in an improvement. Conclusion: VitaminB12 deficiency should be considered one of the differential diagnoses in the approach to pancytopenia with megaloblastic anemia associated with dermatologic and neurologic manifestations. Early treatment can reduce irreversible damage in these patients.Keywords: vitamin B12 deficiency, pediatrics, pancytopenia, diaper dermatitis
Procedia PDF Downloads 902505 Computational Identification of Signalling Pathways in Protein Interaction Networks
Authors: Angela U. Makolo, Temitayo A. Olagunju
Abstract:
The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways
Procedia PDF Downloads 5342504 Using Pump as Turbine in Urban Water Networks to Control, Monitor, and Simulate Water Processes Remotely
Authors: Morteza Ahmadifar, Sarah Bahari Derakhshan
Abstract:
Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. On the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables, therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PAT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and therefore more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore, due to increasing the area of network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PAT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.Keywords: clean energies, pump as turbine, remote control, urban water distribution network
Procedia PDF Downloads 3882503 Wireless Sensor Networks for Water Quality Monitoring: Prototype Design
Authors: Cesar Eduardo Hernández Curiel, Victor Hugo Benítez Baltazar, Jesús Horacio Pacheco Ramírez
Abstract:
This paper is devoted to present the advances in the design of a prototype that is able to supervise the complex behavior of water quality parameters such as pH and temperature, via a real-time monitoring system. The current water quality tests that are performed in government water quality institutions in Mexico are carried out in problematic locations and they require taking manual samples. The water samples are then taken to the institution laboratory for examination. In order to automate this process, a water quality monitoring system based on wireless sensor networks is proposed. The system consists of a sensor node which contains one pH sensor, one temperature sensor, a microcontroller, and a ZigBee radio, and a base station composed by a ZigBee radio and a PC. The progress in this investigation shows the development of a water quality monitoring system. Due to recent events that affected water quality in Mexico, the main motivation of this study is to address water quality monitoring systems, so in the near future, a more robust, affordable, and reliable system can be deployed.Keywords: pH measurement, water quality monitoring, wireless sensor networks, ZigBee
Procedia PDF Downloads 3912502 Loss Function Optimization for CNN-Based Fingerprint Anti-Spoofing
Authors: Yehjune Heo
Abstract:
As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer
Procedia PDF Downloads 1322501 Comparison between Hardy-Cross Method and Water Software to Solve a Pipe Networking Design Problem for a Small Town
Authors: Ahmed Emad Ahmed, Zeyad Ahmed Hussein, Mohamed Salama Afifi, Ahmed Mohammed Eid
Abstract:
Water has a great importance in life. In order to deliver water from resources to the users, many procedures should be taken by the water engineers. One of the main procedures to deliver water to the community is by designing pressurizer pipe networks for water. The main aim of this work is to calculate the water demand of a small town and then design a simple water network to distribute water resources among the town with the smallest losses. Literature has been mentioned to cover the main point related to water distribution. Moreover, the methodology has introduced two approaches to solve the research problem, one by the iterative method of Hardy-cross and the other by water software Pipe Flow. The results have introduced two main designs to satisfy the same research requirements. Finally, the researchers have concluded that the use of water software provides more abilities and options for water engineers.Keywords: looping pipe networks, hardy cross networks accuracy, relative error of hardy cross method
Procedia PDF Downloads 1562500 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception
Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu
Abstract:
Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish
Procedia PDF Downloads 1362499 Survey on Fiber Optic Deployment for Telecommunications Operators in Ghana: Coverage Gap, Recommendations and Research Directions
Authors: Francis Padi, Solomon Nunoo, John Kojo Annan
Abstract:
The paper "Survey on Fiber Optic Deployment for Telecommunications Operators in Ghana: Coverage Gap, Recommendations and Research Directions" presents a comprehensive survey on the deployment of fiber optic networks for telecommunications operators in Ghana. It addresses the challenges encountered by operators using microwave transmission systems for backhauling traffic and emphasizes the advantages of deploying fiber optic networks. The study delves into the coverage gap, provides recommendations, and outlines research directions to enhance the telecommunications infrastructure in Ghana. Additionally, it evaluates next-generation optical access technologies and architectures tailored to operators' needs. The paper also investigates current technological solutions and regulatory, technical, and economic dimensions related to sharing mobile telecommunication networks in emerging countries. Overall, this paper offers valuable insights into fiber optic network deployment for telecommunications operators in Ghana and suggests strategies to meet the increasing demand for data and mobile applications.Keywords: survey on fiber optic deployment, coverage gap, recommendations, research directions
Procedia PDF Downloads 92498 Development and Investigation of Sustainable Wireless Sensor Networks for forest Ecosystems
Authors: Shathya Duobiene, Gediminas Račiukaitis
Abstract:
Solar-powered wireless sensor nodes work best when they operate continuously with minimal energy consumption. Wireless Sensor Networks (WSNs) are a new technology opens up wide studies, and advancements are expanding the prevalence of numerous monitoring applications and real-time aid for environments. The Selective Surface Activation Induced by Laser (SSAIL) technology is an exciting development that gives the design of WSNs more flexibility in terms of their shape, dimensions, and materials. This research work proposes a methodology for using SSAIL technology for forest ecosystem monitoring by wireless sensor networks. WSN monitoring the temperature and humidity were deployed, and their architectures are discussed. The paper presents the experimental outcomes of deploying newly built sensor nodes in forested areas. Finally, a practical method is offered to extend the WSN's lifespan and ensure its continued operation. When operational, the node is independent of the base station's power supply and uses only as much energy as necessary to sense and transmit data.Keywords: internet of things (IoT), wireless sensor network, sensor nodes, SSAIL technology, forest ecosystem
Procedia PDF Downloads 672497 Quantum Graph Approach for Energy and Information Transfer through Networks of Cables
Authors: Mubarack Ahmed, Gabriele Gradoni, Stephen C. Creagh, Gregor Tanner
Abstract:
High-frequency cables commonly connect modern devices and sensors. Interestingly, the proportion of electric components is rising fast in an attempt to achieve lighter and greener devices. Modelling the propagation of signals through these cable networks in the presence of parameter uncertainty is a daunting task. In this work, we study the response of high-frequency cable networks using both Transmission Line and Quantum Graph (QG) theories. We have successfully compared the two theories in terms of reflection spectra using measurements on real, lossy cables. We have derived a generalisation of the vertex scattering matrix to include non-uniform networks – networks of cables with different characteristic impedances and propagation constants. The QG model implicitly takes into account the pseudo-chaotic behavior, at the vertices, of the propagating electric signal. We have successfully compared the asymptotic growth of eigenvalues of the Laplacian with the predictions of Weyl law. We investigate the nearest-neighbour level-spacing distribution of the resonances and compare our results with the predictions of Random Matrix Theory (RMT). To achieve this, we will compare our graphs with the generalisation of Wigner distribution for open systems. The problem of scattering from networks of cables can also provide an analogue model for wireless communication in highly reverberant environments. In this context, we provide a preliminary analysis of the statistics of communication capacity for communication across cable networks, whose eventual aim is to enable detailed laboratory testing of information transfer rates using software defined radio. We specialise this analysis in particular for the case of MIMO (Multiple-Input Multiple-Output) protocols. We have successfully validated our QG model with both TL model and laboratory measurements. The growth of Eigenvalues compares well with Weyl’s law and the level-spacing distribution agrees so well RMT predictions. The results we achieved in the MIMO application compares favourably with the prediction of a parallel on-going research (sponsored by NEMF21.)Keywords: eigenvalues, multiple-input multiple-output, quantum graph, random matrix theory, transmission line
Procedia PDF Downloads 165