Search results for: wireless sensor networks (WSN)

Authors: Arkadiusz Urzędowski, Dorota Wójcicka-Migasiuk, Andrzej Sachajdak, Magdalena Paśnikowska-Łukaszuk

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Due to the impact of climate changes and inevitability to reduce greenhouse gases, the need to use low-carbon and sustainable construction has increased. In this work, it is investigated how texture of the surface building materials and radiative heat transfer phenomenon in flat multilayer can be correlated. Attempts to test the surface emissivity are taken however, the trustworthiness of measurement results remains a concern since sensor size and thickness are common problems. This paper presents an experimental method to studies surface emissivity with use self constructed thermal sensors and thermal imaging technique. The surface of building materials was modified by mechanical and chemical treatment affecting the reduction of the emissivity. For testing the shaping surface of materials and mapping its three-dimensional structure, scanning profilometry were used in a laboratory. By comparing the results of laboratory tests and performed analysis of 3D computer fluid dynamics software, it can be shown that a change in the surface coverage of materials affects the heat transport by radiation between layers. Motivated by recent advancements in variational inference, this publication evaluates the potential use a dedicated data processing approach, and properly constructed temperature sensors, the influence of the surface emissivity on the phenomenon of radiation and heat transport in the entire partition can be determined.

Keywords: heat transfer, surface roughness, surface emissivity, radiation

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

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Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

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After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

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Authors: Aishrith Rao

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Human activity recognition is an important aspect of video analytics, and many approaches have been recommended to enable action recognition. In this approach, the model is used to identify the action of the multiple people in the frame and classify them accordingly. A few approaches use RNNs and 3D CNNs, which are computationally expensive and cannot be trained with the small datasets which are currently available. Multi-person action recognition has been performed in order to understand the positions and action of people present in the video frame. The size of the video frame can be adjusted as a hyper-parameter depending on the hardware resources available. OpenPose has been used to calculate pose estimate using CNN to produce heap-maps, one of which provides skeleton features, which are basically joint features. The features are then extracted, and a classification algorithm can be applied to classify the action.

Keywords: human activity recognition, computer vision, pose estimates, convolutional neural networks

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Authors: Erika Ruíz, Luis Amaya, Diego Carreño

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The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

Procedia PDF Downloads 217

Authors: Richard Grant, Landolf Rhode-Barbarigos, Shouraseni Sen Roy, Lucas Brittan, Change Li, Aiden Rowe

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Ports are critical for the US economy, connecting farmers, manufacturers, retailers, consumers and an array of transport and storage operators. Port facilities vary widely in terms of their productivity, footprint, specializations, and governance. In this context, Port Miami is considered as one of the busiest ports providing both cargo and cruise services in connecting the wider region of the Caribbean and Mesoamerica to the global networks. It is considered as the “Cruise Capital of the World and Global Gateway of the Americas” and “leading container port in Florida.” Furthermore, it has also been ranked as one of the top container ports in the world and the second most efficient port in North America. In this regard, Port Miami has made significant investments in the strategic and capital infrastructure of about US$1 billion, including increasing the channel depth and other onshore infrastructural enhancements. Therefore, this study involves a detailed analysis of Port Miami’s network, using publicly available multiple years of data about marine vessel traffic, cargo, and connectivity and performance indices from 2015-2021. Through the analysis of cargo and cruise vessels to and from Port Miami and its relative performance at the global scale from 2015 to 2021, this study examines the port’s long-term resilience and future growth potential. The main results of the analyses indicate that the top category for both inbound and outbound cargo is manufactured products and textiles. In addition, there are a lot of fresh fruits, vegetables, and produce for inbound and processed food for outbound cargo. Furthermore, the top ten port connections for Port Miami are all located in the Caribbean region, the Gulf of Mexico, and the Southeast USA. About half of the inbound cargo comes from Savannah, Saint Thomas, and Puerto Plata, while outbound cargo is from Puerto Corte, Freeport, and Kingston. Additionally, for cruise vessels, a significantly large number of vessels originate from Nassau, followed by Freeport. The number of passenger's vessels pre-COVID was almost 1,000 per year, which dropped substantially in 2020 and 2021 to around 300 vessels. Finally, the resilience and competitiveness of Port Miami were also assessed in terms of its network connectivity by examining the inbound and outbound maritime vessel traffic. It is noteworthy that the most frequent port connections for Port Miami were Freeport and Savannah, followed by Kingston, Nassau, and New Orleans. However, several of these ports, Puerto Corte, Veracruz, Puerto Plata, and Santo Thomas, have low resilience and are highly vulnerable, which needs to be taken into consideration for the long-term resilience of Port Miami in the future.

Keywords: port, Miami, network, cargo, cruise

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

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Authors: Farnaz Fotovvatikhah, Javad Akbari

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Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

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Authors: Prikhil Agrawal, N. Priyanka

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With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

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Authors: Klaus Froehlich-Gildhoff, Ullrich Boettinger, Katharina Rauh, Angela Schickler

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The Prevention Network Ortenaukreis, PNO, funded by the German Ministry of Education and Research, aims to promote physical and mental health as well as the social inclusion of 3 to 10 years old children and their families in the Ortenau district. Within a period of four years starting 11/2014 a community network will be established. One regional and five local prevention representatives are building networks with stakeholders of the prevention and health promotion field bridging the health care, educational and youth welfare system in a multidisciplinary approach. The regional prevention representative implements regularly convening prevention and health conferences. On a local level, the 5 local prevention representatives implement round tables in each area as a platform for networking. In the setting approach, educational institutions are playing a vital role when gaining access to children and their families. Thus the project will offer 18 month long organizational development processes with specially trained coaches to 25 kindergarten and 25 primary schools. The process is based on a curriculum of prevention and health promotion which is adapted to the specific needs of the institutions. Also to ensure that the entire region is reached demand oriented advanced education courses are implemented at participating day care centers, kindergartens and schools. Evaluation method: The project is accompanied by an extensive research design to evaluate the outcomes of different project components such as interview data from community prevention agents, interviews and network analysis with families at risk on their support structures, data on community network development and monitoring, as well as data from kindergarten and primary schools. The latter features a waiting-list control group evaluation in kindergarten and primary schools with a mixed methods design using questionnaires and interviews with pedagogues, teachers, parents, and children. Results: By the time of the conference pre and post test data from the kindergarten samples (treatment and control group) will be presented, as well as data from the first project phase, such as qualitative interviews with the prevention coordinators as well as mixed methods data from the community needs assessment. In supporting this project, the Federal Ministry aims to gain insight into efficient components of community prevention and health promotion networks as it is implemented and evaluated. The district will serve as a model region, so that successful components can be transferred to other regions throughout Germany. Accordingly, the transferability to other regions is of high interest in this project.

Keywords: childhood research, health promotion, physical health, prevention network, psychological well-being, social inclusion

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Authors: Luís Farinha, João J. Ferreira

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Nowadays innovation represents a challenge crucial to remaining globally competitive. This study seeks to develop a conceptual model aimed at measuring the dynamic interactions of the triple/quadruple helix, balancing innovation and entrepreneurship initiatives as pillars of regional competitiveness – the Regional Helix Scoreboard (RHS). To this aim, different strands of literature are identified according to their focus on specific regional competitiveness governance mechanisms. We put forward an overview of the state-of-the-art of research and is duly assessed in order to develop and propose a framework of analysis that enables an integrated approach in the context of collaborative dynamics. We conclude by presenting the RHS for the study of regional competitiveness dynamics, which integrates and associates different backgrounds and identifies a number of key performance indicators for research challenges.

Keywords: entrepreneurship, KPIs, innovation, performance measurement, regional competitiveness, regional helix scoreboard

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Authors: Jisong Zhang, Yinghua Zhao

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The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: H. M. Avanesyan

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Economists have been discussing the importance of intangible assets for the success of organization for many years. The term intellectual capital was popularized in the 1990s by Thomas Stewart. “Intellectual capital is the knowledge, applied experience, enterprise processes and technology customer relationship and professional skills which are valuable assets to an organization.” Human capital – includes employee brainpower, competence, skills, experience and knowledge. Customer capital – includes relations and networks with partners, suppliers, distributors, and customers. The objective of the article is to assess one of the key components of organizational culture – organizational values. The focus of the survey was on assessing how intellectual capital presented in these values of the organization. In the conclusion section the article refers to underestimation of intellectual capital by the organization management and the various possible negative effects of the latter.

Keywords: human capital, intellectual capital, organizational culture, management, social identity, organization

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

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Authors: Sivaraman Karthikeyan

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Due to rapidly developing power electronics devices and technologies such as power line communication or self-commutating converters, voltage and current distortion, as well as interferences, have increased in the frequency range of 2 kHz to 150 kHz; there is an urgent need for regulation of electromagnetic compatibility (EMC) standards in this frequency range. Measuring or testing compliance with emission and immunity limitations necessitates the use of precise, repeatable measuring methods. Appropriate filters to minimize the fundamental component and its harmonics below 2 kHz in the measuring signal would improve the measurement accuracy in this frequency range leading to better analysis. This paper discusses filter suggestions in the current measurement standard and proposes an infinite impulse response (IIR) filter design that is optimized for a low number of poles, strong fundamental damping, and high accuracy above 2 kHz. The new filter’s transfer function is delivered as a result. An analog implementation is derived from the overall design.

Keywords: supraharmonics, 2 kHz, 150 kHz, filter, analog filter

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Authors: B. Casper

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The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: Magdi. M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

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Authors: Emil Mathew

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Liberalisation policies adopted by a large number of countries, implementation of technological innovations with development in communication networks and continuous reduction in transport costs contributed towards the growth of international transportation of goods over the last 50 to 60 years. The present paper examines the environmental externalities of maritime transportation, that is, externalities associated with the movement of cargoes, as distinct from those emanate from production and consumption of goods. Though shipping is less polluting compared to other modes of transportation, considering the huge volume of goods transported and future growth prospects, it is important to examine environmental externalities of maritime transportation. It focuses on varied types of environmental externalities of maritime transportation and suggests that appropriate policies may be adopted by international agencies to address this issue without adversely affecting the course of international trade and also its possibility to get diverted to alternate modes of transportation.

Keywords: externalities of globalisation, maritime environment, maritime externality, transportation externality

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Authors: Devi Srinivas, K. Sindhuja

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This paper presents architecture to improve surveillance applications based on the usage of the service oriented paradigm, with smart phones as user terminals, allowing application dynamic composition and increasing the flexibility of the system. According to the result of moving object detection research on video sequences, the movement of the people is tracked using video surveillance. The moving object is identified using the image subtraction method. The background image is subtracted from the foreground image, from that the moving object is derived. So the Background subtraction algorithm and the threshold value is calculated to find the moving image by using background subtraction algorithm the moving frame is identified. Then, by the threshold value the movement of the frame is identified and tracked. Hence, the movement of the object is identified accurately. This paper deals with low-cost intelligent mobile phone-based wireless video surveillance solution using moving object recognition technology. The proposed solution can be useful in various security systems and environmental surveillance. The fundamental rule of moving object detecting is given in the paper, then, a self-adaptive background representation that can update automatically and timely to adapt to the slow and slight changes of normal surroundings is detailed. While the subtraction of the present captured image and the background reaches a certain threshold, a moving object is measured to be in the current view, and the mobile phone will automatically notify the central control unit or the user through SMS (Short Message System). The main advantage of this system is when an unknown image is captured by the system it will alert the user automatically by sending an SMS to user’s mobile.

Keywords: security, graphical password, persuasive cued click points

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Meng-Chyi Wu, Bonn Lin, Jyun-Hao Liao, Chein-Ju Chen, Yu-Cheng Jhuang, Mau-Phon Houng, Fang-Hsing Wang, Min-Chu Liu, Cheng-Fu Yang, Cheng-Shong Hong

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Since the use of wireless communications has become critical nowadays, the available RF spectrum has become limited. Ultraviolet (UV) communication system can alleviate the spectrum constraint making UV communication system a potential alternative to future communication demands. Also, UV links can provide faster communication rate and can be used in combination with existing RF communication links, providing new communications diversity with higher user capacity. The UV region of electromagnetic spectrum has been of interest to detector, imaging and communication technologies because the stratospheric ozone layer effectively absorbs some solar UV radiation from reaching the earth surface. The wavebands where most of UV radiation is absorbed by the ozone are commonly known as the solar blind region. By operating in UV-C band (200-280 nm) the communication system can minimize the transmission power consumption since it will have less radiation noise. UV communication uses the UV ray as the medium. Electric signal is carried on this band after being modulated and then be transmitted within the atmosphere as channel. Though the background noise of UV-C communication is very low owing to the solar-blind feature, it leads to a large propagation loss. The 370 nm UV provides a much lower propagation loss than that the UV-C does and the recent device technology for UV source on this band is more mature. The fabricated 370 nm AlGaN light-emitting diodes (LEDs) with an aperture size of 45 m exhibit a modulation bandwidth of 165 MHz at 30 mA and a high power of 7 W/cm2 at 230 A/cm2. In order to solve the problem of low power in single UV LED, a UV LED array is presented in.

Keywords: ultraviolet (UV) communication, light-emitting diodes (LEDs), modulation bandwidth, LED array, 370 nm

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Authors: Egor E. Nuzhin, Nikolay V. Brilliantov

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We propose an approach for addressing Reinforcement Learning (RL) problems. It combines the ideas of umbrella sampling, borrowed from Monte Carlo technique of computational physics and chemistry, with optimal control methods, and is realized on the base of neural networks. This results in a powerful algorithm, designed to solve hard RL problems – the problems, with long-time delayed reward, state-traps sticking and a lack of terminal states. It outperforms the prominent algorithms, such as PPO, RND, iLQR and VI, which are among the most efficient for the hard problems. The new algorithm deals with a continuous ensemble of agents and expected return, that includes the ensemble entropy. This results in a quick and efficient search of the optimal policy in terms of ”exploration-exploitation trade-off” in the state-action space.

Keywords: umbrella sampling, reinforcement learning, policy gradient, dynamic programming

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Authors: M. Caramihai, Irina Severin

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This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

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Authors: Mariela González, Zoraide Lugli

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Objective: to determine the relationship between perceived social support and adherence to therapy in patients who have been placed BioEnteric intragastric balloon (BIB). Material and method: 75 obese (56 women and 19 men) between 18 and 65 years (M = 39.29, SD = 11.82), who attended five centers in the city of Caracas, where he carried out this procedure. We used Social Support Scale and treatment adherence behavior respectively. The procedure was contacted the centers and the sample was selected. Subsequently, the inventories were applied before and the month after the before and three months after the balloon set. Results: Show that participants were characterized by moderate levels in the variables. On the other hand, those who perceive that they perceived support from friends are those who report adherence to therapy. Conclusions: From the results, it is suggested promote social support networks, which could be essential to achieve and maintain adherence to therapy in patients with BioEnterics intragastric balloon.

Keywords: BioEnteric intragastric balloon, perceived social support, adherence to therapy, patients

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Authors: G. La Scalia, M. Enea, R. Micale, O. Corona, L. Settanni

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The quality and condition of perishable products delivered to the market and their subsequent selling prices are directly affected by the care taken during harvesting and handling. Mechanical injury, in fact, occurs at all stages, from pre-harvest operations through post-harvest handling, packing and transport to the market. The main implications of this damage are the reduction of the product’s quality and economical losses related to the shelf life diminution. For most perishable products, the shelf life is relatively short and it is typically dictated by microbial growth related to the application of dynamic and static loads during transportation. This paper presents the correlation between vibration levels and microbiological growth on strawberries and woodland strawberries and detects the presence of volatile organic compounds (VOC) in order to develop an intelligent logistic unit capable of monitoring VOCs using a specific sensor system. Fresh fruits were exposed to vibrations by means of a vibrating table in a temperature-controlled environment. Microbiological analyses were conducted on samples, taken at different positions along the column of the crates. The values obtained were compared with control samples not exposed to vibrations and the results show that different positions along the column influence the development of bacteria, yeasts and filamentous fungi.

Keywords: microbiological analysis, shelf life, transport damage, volatile organic compounds

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Authors: Jin Song Gui, Han Li, Rui Jin Zhang, Heng Jiang Cai

Abstract:

There is a large deviation between the measured wave power at the vertical breast wall and the calculated one according to current specification in the case of overtopping. In order to investigate the reasons for the deviation, the wave forces of vertical breast wall under overtopping conditions have been measured through physical model experiment and compared with the calculated results. The effect of water depth, period and the wave height on the wave forces of the vertical breast wall have been also investigated. The distribution of wave pressure under different wave actions was tested based on the force sensor which is installed in the vertical breakwater. By comparing and analyzing the measured values and norms calculated values, the applicability of the existing norms recommended method were discussed and a reference for the design of vertical breakwater was provided. Experiment results show that with the decrease of the water depth, the gap is growing between the actual wave forces and the specification values, and there are no obvious regulations between these two values with the variation of period while wave force greatly reduces with the overtopping reducing. The amount of water depth and wave overtopping has a significant impact on the wave force of overtopping section while the period has no obvious influence on the wave force. Finally, some favorable recommendations for the overtopping wave force design of the vertical breakwater according to the model experiment results are provided.

Keywords: overtopping wave, physical model experiment, vertical breakwater, wave forces

Procedia PDF Downloads 303

Authors: Kusuma Urs M. B., Navakant Bhat, Vinayak B. Kamble

Abstract:

Metal oxide semiconductors (MOS) are known to be excellent candidates for solid-state gas sensor devices. However, in spite of high sensitivities, their high operating temperatures and lack of selectivity is a big concern limiting their practical applications. A lot of research has been devoted so far to enhance their sensitivity and selectivity, often empirically. Some of the promising routes to achieve the same are reducing dimensionality and formation of heterostructures. These heterostructures offer improved sensitivity, selectivity even at relatively low operating temperatures compared to bare metal oxides. Thus, a combination of n-type and p-type metal oxides leads to the formation of p-n junction at the interface resulting in the diffusion of the carriers across the barrier along with the surface adsorption. In order to achieve this and to study their sensing mechanism, we have designed and lithographically fabricated a suspended nanobeam of NiO, which is a p-type semiconductor. The response of the same has been studied for various gases and is found to exhibit selective response towards hydrogen gas at room temperature. Further, the same has been radially coated with TiO₂ shell of varying thicknesses, in order to study the effect of radial p-n junction thus formed. Subsequently, efforts have been made to study the effect of shell thickness on the space charge region and to shed some light on the basic mechanism involved in gas sensing of MOS sensors.

Keywords: gas sensing, heterostructure, metal oxide semiconductor, space charge region

Procedia PDF Downloads 131

Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

Abstract:

The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

Procedia PDF Downloads 469