Search results for: hybrid expert system

Authors: Keerthi Katam, Abhinav B. Tirunaghari, Vinod Vadithya, Toshiyuki Shimizu, Satoshi Soda, Debraj Bhattacharyya

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Researchers worldwide are increasingly focusing on the removal of carbon and nutrient from wastewater using algal-bacterial hybrid systems. Algae produce oxygen during photosynthesis, which is taken up by heterotrophic bacteria for mineralizing organic carbon to carbon dioxide. This phenomenon reduces the net mechanical aeration requirement of aerobic biological wastewater treatment processes. Consequently, the treatment cost is also reduced. Microalgae also participate in the treatment process by taking up nutrient (N, P) from wastewater. Algal biomass, if harvested, can generate value-added by-products. The aim of the present study was to compare the performance of two systems - System A (mixed microalgae and bacteria) and System B (diatoms and bacteria) in treating kitchen wastewater (KWW). The test reactors were operated at five different solid retention times (SRTs) -2, 4, 6, 8, and 10-days in draw-and-fill mode. The KWW was collected daily from the dining hall-kitchen area of the Indian Institute of Technology Hyderabad. The influent and effluent samples were analyzed for total organic carbon (TOC), total nitrogen (TN) using TOC-L analyzer. A colorimetric method was used to analyze anionic surfactant. Phosphorus (P) and chlorophyll were measured by following standard methods. The TOC, TN, and P of KWW were in the range of 113.5 to 740 mg/L, 2 to 22.8 mg/L, and 1 to 4.5 mg/L, respectively. Both the systems gave similar results with 85% of TOC removal and 60% of TN removal at 10-d SRT. However, the anionic surfactant removal in System A was 99% and 60% in System B. The chlorophyll concentration increased with an increase in SRT in both the systems. At 2-d SRT, no chlorophyll was observed in System B, whereas 0.5 mg/L was observed in System A. At 10-d SRT, the chlorophyll concentration in System A was 7.5 mg/L, whereas it was 4.5 mg/L in System B. Although both the systems showed similar performance in treatment, the increase in chlorophyll concentration suggests that System A demonstrated a better algal-bacterial symbiotic relationship in treating KWW than System B.

Keywords: diatoms, microalgae, retention time, wastewater treatment

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Authors: Aliouane Toufik, Hamdi Amine, Bouzid Djamel

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Aspheric optical components are an alternative to the use of conventional lenses in the implementation of imaging systems for the visible range. Spherical lenses are capable of producing aberrations. Therefore, they are not able to focus all the light into a single point. Instead, aspherical lenses correct aberrations and provide better resolution even with compact lenses incorporating a small number of lenses. Metrology of these components is very difficult especially when the resolution requirements increase and insufficient or complexity of conventional tools requires the development of specific approaches to characterization. This work is part of the problem existed because the objectives are the study and comparison of different methods used to measure surface rays hybrid aspherical lenses.

Keywords: manufacture of lenses, aspherical surface, precision molding, radius of curvature, roughness

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Authors: Adrien Cornille, Sylvain Caillol, Bernard Boutevon

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The development of polyurethanes began in 1937 at I. G. Farbenindustrie where Bayer with coworkers discovered the addition polymerization reaction between diisocyanates and diols. Since their discovery, the demand in PU has continued to increase and it will attain in 2016 a production of 18 million tons. However, isocyanates compounds are harmful to human and environment. Methylene diphenyl 4,4’-diisocyanate (MDI) and toluene diisocyanate (TDI), the most widely used isocyanates in PU industry, are classified as CMR (Carcinogen, Mutagen, and Reprotoxic). In order to design isocyanate-free materials, an interesting alternative is the use of Polyhydroxyurethanes (PHUs) by reaction between cyclic carbonate and polyfunctional amines. The main problem concerning PHUs synthesis relates to the low reactivity of carbonate/amine reaction. To solve this issue, many studies in the literature have been conducted to design PHU from more reactive cyclic-carbonates, bearing electro-withdrawing substituent or by using six-membered, seven-membered or thio-cyclic carbonate. The main drawback of all these systems remains the low molar masses obtained for the synthesized PHUs, which hinders their use for material applications. Therefore, we developed another strategy to afford new hybrid PHU with high conversion. This very innovative two-step approach consists in the first step in the synthesis of aminotelechelic PHU oligomers with different chain length from bis-cyclic carbonate with different excess of primary amine functions. In the second step, these aminotelechelic PHU oligomers were used in formulation with biobased epoxy monomers (from cashew nut shell liquid and tannins) to synthesize hybrid polyepoxyurethane polymers. These materials were then characterized by thermal and mechanical analyses.

Keywords: polyurethane, polyhydroxyurethane, aminotelechelic NIPU oligomers, carbonates, epoxy, amine, epoxyurethane polymers, hybrid polymers

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Authors: Mustafa Alshawaqfeh, Bilal Wajidy, Echin Serpedin, Jan Suchodolski

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Inflammatory Bowel disease (IBD) is a disease of the colon with characteristic inflammation. Clinically IBD is detected using laboratory tests (blood and stool), radiology tests (imaging using CT, MRI), capsule endoscopy and endoscopy. There are two variants of IBD referred to as Ulcerative Colitis (UC) and Crohn’s disease. This study employs a hybrid feature selection method that combines a correlation-based variable ranking approach with exhaustive search wrapper methods in order to find potential biomarkers for UC. The proposed biomarkers presented accurate discriminatory power thereby identifying themselves to be possible ingredients to UC therapeutics.

Keywords: ulcerative colitis, biomarker detection, feature selection, inflammatory bowel disease (IBD)

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Authors: Mariam Ismail, Kazeem Rufai, Jeremiah Balogun

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A study was conducted to apply fuzzy logic to the development of a monitoring model for child pornography based on associated risk factors, which can be used by forensic experts or integrated into forensic systems for the early detection of child pornographic activities. A number of methods were adopted in the study, which includes an extensive review of related works was done in order to identify the factors that are associated with child pornography following which they were validated by an expert sex psychologist and guidance counselor, and relevant data was collected. Fuzzy membership functions were used to fuzzify the associated variables identified alongside the risk of the occurrence of child pornography based on the inference rules that were provided by the experts consulted, and the fuzzy logic expert system was simulated using the Fuzzy Logic Toolbox available in the MATLAB Software Release 2016. The results of the study showed that there were 4 categories of risk factors required for assessing the risk of a suspect committing child pornography offenses. The results of the study showed that 2 and 3 triangular membership functions were used to formulate the risk factors based on the 2 and 3 number of labels assigned, respectively. The results of the study showed that 5 fuzzy logic models were formulated such that the first 4 was used to assess the impact of each category on child pornography while the last one takes the 4 outputs from the 4 fuzzy logic models as inputs required for assessing the risk of child pornography. The following conclusion was made; there were factors that were related to personal traits, social traits, history of child pornography crimes, and self-regulatory deficiency traits by the suspects required for the assessment of the risk of child pornography crimes committed by a suspect. Using the values of the identified risk factors selected for this study, the risk of child pornography can be easily assessed from their values in order to determine the likelihood of a suspect perpetuating the crime.

Keywords: fuzzy, membership functions, pornography, risk factors

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Authors: Ariful Islam, Showkat Ahmad Lone

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Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Vitalijus Leibenka

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After 2014 the world of Russia’s actions in annexing Crimea has seen a hybrid war that has helped Russia achieve its goals. The world and NATO nations have pointed out that hybrid action can help achieve not only military but also economic and political goals. One of the weapons of action in hybrid warfare is information warfare tools, the use of which helps to carry out actions in the context of hybrid warfare as a whole. In addition, information war tools can be used alone, over time and for long-term purposes. Although forms of information war, such as propaganda and disinformation, have been used in the past, in old conflicts and wars, new forms of information war have emerged as a result of technological development, making the dissemination of information faster and more efficient. The world understands that information is becoming a weapon, but not everyone understands that both information war and information warfare differ in their essence and full content. In addition, the damage and impact of the use of information war, which may have worse consequences than a brief military conflict, is underestimated. Lithuania is also facing various interpretations of the information war. Some believe that the information attack is an information war and the understanding of the information war is limited to a false message in the press. Others, however, deepen and explain the essence of the information war. Society has formed in such a way that not all people are able to assess the threats of information war, to separate information war from information attack. Recently, the Lithuanian government has been taking measures in the context of the information war, making decisions that allow the development of the activities of the state and state institutions in order to create defense mechanisms in the information war. However, this is happening rather slowly and incompletely. Every military conflict, related to Lithuania in one way or another, forces Lithuanian politicians to take up the theme of information warfare again. As a result, a national cyber security center is being set up, and Russian channels spreading lies are banned. However, there is no consistent development and continuous improvement of action against information threats. Although a sufficiently influential part of society (not a political part) helps to stop the spread of obscure information by creating social projects such as “Demaskuok” and “Laikykis ten su Andriumi tapinu”, it goes without saying that it will not become a key tool in the fight against information threats. Therefore, in order to achieve clean dissemination of information in Lithuania, full-fledged and substantial political decisions are necessary, the adoption of which would change the public perception of the information war, its damage, impact and actions that would allow to combat the spread. Political decisions should cover the educational, military, economic and political areas, which are one of the main and most important in the state, which would allow to fundamentally change the situation against the background of information war.

Keywords: information war, information warfare, hybrid war, hybrid warfare, NATO, Lithuania, Russia

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Authors: A. M. Sagir

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Discrete linear multistep block method of uniform order for the solution of first order Initial Value Problems (IVPs) in Ordinary Differential Equations (ODEs) is presented in this paper. The approach of interpolation and collocation approximation are adopted in the derivation of the method which is then applied to first order ordinary differential equations with associated initial conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain four discrete schemes, which were used in block form for parallel or sequential solutions of the problems. Furthermore, a stability analysis and efficiency of the block method are tested on ordinary differential equations, and the results obtained compared favorably with the exact solution.

Keywords: block method, first order ordinary differential equations, hybrid, self-starting

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: U. Achutha Kini, S. S. Sharma, K. Jagannath, P. R. Prabhu, M. C. Gowri Shankar

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Aluminium matrix composites with alumina reinforcements give superior mechanical & physical properties. Their applications in several fields like automobile, aerospace, defense, sports, electronics, bio-medical and other industrial purposes are becoming essential for the last several decades. In the present work, fabrication of hybrid composite was done by Stir casting technique using Al 6061 as a matrix with alumina and silicon carbide (SiC) as reinforcement materials. The weight percentage of alumina is varied from 2 to 4% and the silicon carbide weight percentage is maintained constant at 2%. Hardness and wear tests are performed in the as cast and heat treated conditions. Age hardening treatment was performed on the specimen with solutionizing at 550°C, aging at two temperatures (150 and 200°C) for different time durations. Hardness distribution curves are drawn and peak hardness values are recorded. Hardness increase was very sensitive with respect to the decrease in aging temperature. There was an improvement in wear resistance of the peak aged material when aged at lower temperature. Also increase in weight percent of alumina, increases wear resistance at lower temperature but opposite behavior was seen when aged at higher temperature.

Keywords: hybrid composite, hardness test, wear test, heat treatment, pin on disc wear testing machine

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Kritika Bansal, Akwinder Kaur, Shruti Gujral

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In this paper, the approach of denoising is solved by using a new hybrid technique which associates the different denoising methods. Wavelet thresholding and anisotropic diffusion filter are the two different filters in our hybrid techniques. The Wavelet thresholding removes the noise by removing the high frequency components with lesser edge preservation, whereas an anisotropic diffusion filters is based on partial differential equation, (PDE) to remove the speckle noise. This PDE approach is used to preserve the edges and provides better smoothing. So our new method proposes a combination of these two filtering methods which performs better results in terms of peak signal to noise ratio (PSNR), coefficient of correlation (COC) and equivalent no of looks (ENL).

Keywords: denoising, anisotropic diffusion filter, multiplicative noise, speckle, wavelets

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Authors: Huda Al Shuaily, Karen Renaud

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Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

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Authors: Golnoosh Torabian, P. Valtchev, F. Dehghani

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The need for efficient nutraceutical products has been dramatically changing the approach of the industrial processes. The development of novel mild processes is highly demanded for the production of such products; especially when both quality and safety need to be guaranteed during their long shelf life. Within this research, for the first time, we investigated the effect of supercritical carbon dioxide treatment for the inactivation of microbes and enzymes in a berry juice possessing therapeutic effect. We demonstrated that a complete inactivation of microbes can be achieved at optimized conditions of treatment. However, the bottle neck of the process was represented by the unpromising inactivation of the degradative enzyme by supercritical carbon dioxide treatment. However, complete enzyme inactivation was achieved by applying two strategies: the first was optimizing juicing method by adding a mechanical step and the second strategy was addition of natural inhibitors to the juice. Overall these results demonstrate that our hybrid process has a significant effect on the inactivation of microorganism and enzymes in the fresh juice. The developed process opens the possibility for the evolution of new products with optimal nutritional and sensorial characteristics, as well as offering a competitive cost and an environmentally friendly alternative for pasteurization and extension of shelf life in a wide range of natural therapeutic products.

Keywords: hybrid method, berry juice, pasteurization, enzymes inactivation

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Authors: M. Talebzadegan, S. Bina , I. Riazi

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The purpose of this paper is to present an active solar energy system to supply heating demands of the teaching staff dormitory of Islamic Azad University of Ramhormoz. The design takes into account the solar radiations and climate data of Ramhormoz town and is based on the daily warm water consumption for health demands of 450 residents of the dormitory, which is equal to 27000 lit of 50 C° water, and building heating requirements with an area of 3500 m² well-protected by heatproof materials. First, heating demands of the building were calculated, then a hybrid system made up of solar and fossil energies was developed and finally, the design was economically evaluated. Since there is only roof space for using 110 flat solar water heaters, the calculations were made to hybridize solar water heating system with heat pumping system in which solar energy contributes 67% of the heat generated. According to calculations, the Net Present Value “N.P.V.” of revenue stream exceeds “N.P.V.” of cash paid off in this project over three years, which makes economically quite promising. The return of investment and payback period of the project is 4 years. Also, the Internal Rate of Return (IRR) of the project was 25%, which exceeds bank rate of interest in Iran and emphasizes the desirability of the project.

Keywords: solar energy, heat demand, renewable, pollution

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Authors: Sungsik Jo, Hyeonwoo Kim, Iksu Choi, Hunmo Kim

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In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode.

Keywords: smart hybrid powerpack (SHP), electro hydraulic actuator (EHA), permanent sensor fault tolerance, sliding mode observer (SMO), graphic user interface (GUI)

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Authors: Sławomir Lasota, Tomasz Kajdanowicz

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This paper delves into adapting the Tweeting Factory paradigm to achieve universal production optimization under the Industry 5.0 framework. The proposed system creates a dynamic decision-making environment by collecting and analyzing structured telemetry data (”tweets”) from production lines. A hybrid recommendation engine combines rule-based systems with machine learning models to enhance real-time responsiveness and operator engagement. The research evaluates the system’s ability to optimize diverse industrial processes through predictive KPIs and real-time feedback loops. Results indicate significant advancements in eco-efficiency and operator productivity, showcasing the versatility of the Tweeting Factory approach in meeting the demands of human-centric and sustainable production.

Keywords: tweeting factory, production optimization, industry 5.0, recommendation

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Authors: M. S. H. Chowdhury, Ishak Hashim

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In this paper, linear and non-linear stiff systems of ordinary differential equations are solved by the classical Adomian decomposition method (ADM) and the multi-stage Adomian decomposition method (MADM). The MADM is a technique adapted from the standard Adomian decomposition method (ADM) where standard ADM is converted into a hybrid numeric-analytic method called the multistage ADM (MADM). The MADM is tested for several examples. Comparisons with an explicit Runge-Kutta-type method (RK) and the classical ADM demonstrate the limitations of ADM and promising capability of the MADM for solving stiff initial value problems (IVPs).

Keywords: stiff system of ODEs, Runge-Kutta Type Method, Adomian decomposition method, Multistage ADM

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Authors: Gabriel S. Adesina, Ruixue Cheng, Geetika Aggarwal, Michael Short

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With the global shift towards sustainability and technological advancements, electric Hybrid vehicles (EHVs) are increasingly being seen as viable alternatives to traditional internal combustion (IC) engine vehicles, which also require efficient cooling systems. The electric Automotive Water Pump (AWP) has been introduced as an alternative to IC engine belt-driven pump systems. However, current control methods for AWPs typically employ fixed gain settings, which are not ideal for the varying conditions of dynamic vehicle environments, potentially leading to overheating issues. To overcome the limitations of fixed gain control, this paper proposes implementing an artificial neural network (ANN) for managing the AWP in EHVs. The proposed ANN provides an intelligent, adaptive control strategy that enhances the AWP's performance, supported through MATLAB simulation work illustrated in this paper. Comparative analysis demonstrates that the ANN-based controller surpasses conventional PID and fuzzy logic-based controllers (FLC), exhibiting no overshoot, 0.1secs rapid response, and 0.0696 IAE performance. Consequently, the findings suggest that ANNs can be effectively utilized in EHVs.

Keywords: automotive water pump, cooling system, electric hybrid vehicles, artificial neural networks, PID control, fuzzy logic control, IAE, MATLAB

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Authors: Viviane da Costa Correia, Sergio Francisco Santos, Holmer Savastano Junior

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The main purpose of this work was verify the influence of the accelerated carbonation in the physical and mechanical properties of the hybrid composites, reinforced with micro and nanofibers and composites with microfibers. The composites were produced by the slurry vacuum dewatering method, followed by pressing. It was produced using two formulations: 8% of eucalyptus pulp + 1% of the nanofibrillated cellulose and 9% of eucalyptus pulp, both were subjected to accelerated carbonation. The results showed that the accelerated carbonation contributed to improve the physical and mechanical properties of the hybrid composites and of the composites reinforced with microfibers (eucalyptus pulp).

Keywords: carbonation, cement composites, nanofibrillated cellulose, eucalyptus pulp

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Authors: Aldona Guzik

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Experts have always played a special role in society. Drawing on their opinions was and most certainly is one of the most important strategies that direct people when they make decisions; something often used with the aim of exerting influence and ensuring social conformism. Many factors decide on who becomes an expert. The most important of these have hitherto been: the possession of extensive knowledge, charisma, authority as well as experience. Increasingly, however, these factors are insufficient and may even be deemed unnecessary. This state of affairs has been brought about (among other things) by the development of the media and the media’s influence on our lives. The inspiration to write the present article has its grounding in the book by Tom Nichols The Death of Expertise. The Campaign Against Established Knowledge and Why it Matters, in which the author claims that in our present-day open society experts and their expertise count for increasingly less for everyone who has unlimited access to the Internet and education. This has, in turn, resulted in the creation of so-called ‘collective wisdom,’ which is placed higher than any of the specialist knowledge proclaimed by experts. However, this is an incomplete picture, because admittedly, access to knowledge is nowadays unlimited, but on the other hand, the ubiquitous risk causes that the expert is someone who allows them to minimize it. Therefore, a modern society so readily refers to their opinion; from the smallest matters, eg home appliance, to important political issues. Hence, many information services include numerous experts (scientists, journalists, specialists, celebrities), whose task is to explain to the viewers in a simple way the presented reality. However, more and more often their role is also to give credence to what they explain. Hence the questions arise: who are the experts, what is their typology and what roles they play in Polish information services? To answer them, quantitative and qualitative research was used, such as analysis of lists of 100 most influential experts, analysis of expert profiles and their statements in three differentiated information services (TVN - commercial, TVP1 - public, TV Trwam - non-commercial/religious). They will be the basis for answering the above-mentioned questions and, above all, determining their role in information services in Poland.

Keywords: experts, media, public discours, symbolic elites

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Authors: Hao Wang, Shuguo Pan

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The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Fatima Babar, Majid I. Khan, Malik Najmus Saqib, Muhammad Tahir

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This article provides range based improvements over a well-known single-hop range free localization scheme, Approximate Point in Triangulation (APIT) by proposing an energy efficient Barycentric coordinate based Point-In-Triangulation (PIT) test along with PIT based trilateration. These improvements result in energy efficiency, reduced localization error and improved localization coverage compared to APIT and its variants. Moreover, we propose to embed Received signal strength indication (RSSI) based distance estimation in DV-Hop which is a multi-hop localization scheme. The proposed localization algorithm achieves energy efficiency and reduced localization error compared to DV-Hop and its available improvements. Furthermore, a hybrid multi-hop localization scheme is also proposed that utilize Barycentric coordinate based PIT test and both range based (Received signal strength indicator) and range free (hop count) techniques for distance estimation. Our experimental results provide evidence that proposed hybrid multi-hop localization scheme results in two to five times reduction in the localization error compare to DV-Hop and its variants, at reduced energy requirements.

Keywords: Localization, Trilateration, Triangulation, Wireless Sensor Networks

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Authors: Suvalux Chaichuchote, Ratchadaporn Thonghem

Abstract:

Pleurotus mushroom is one of popular edible mushrooms in Thailand. It is much favored by consumers due to its delicious taste and high nutrition. It is commonly used as an ingredient in several dishes. The commercially cultivated strain grown in most farms is the Pleurotus sp., Hed Bhutan, that is widely distributed to mushroom farms throughout the country and can be cultivated almost all year round. However, it demands different cultivated strains from mushroom growers, therefore, the improving mushroom strains should be done to their benefits. In this study, we used a di-mon mating method to hybrid production from Hed Bhutan (P-3) as dikaryon material and monokaryotic mycelium were isolated from basidiospores of other three Pleurotus sp. by single spore isolation. The 3 hybrids: P-3XSA-6, P-3XSB-24 and P-3XSE-5 were recognized from the 12 hybridized successfully. They were appropriate hybridized in terms of fruiting body performance in the three time cycles of cultivation such as the number of days until growing, time for pinning, color and shape of fruiting bodies and yield. For genetic study, genomic DNAs of both Hed Bhutan (P-3) and three hybrids were extracted. A couple of primer ITS1 and ITS4 were used to amplify the gene coding for ITS1, ITS2 and 5.8S rRNA. The similarities between these amplified genes and databases of DNA revealed that Hed Bhutan (P-3) was the Pleurotus pulmonarius as well as P-3XSA-6, P-3XSB-24 and P-3XSE-5 hybrids. Furthermore, Hed Bhutan (P3) and three hybrids were distributed to 3 small-scale farms, with mushroom farming experience, in the countryside. To address this, one hundred and twenty mushroom bags of each strain were supplied to them. The findings, by interview, indicated two mushroom farmers were satisfied with P-3XSA-6 hybrid and P-3XSB-24 hybrid, thanks to their simultaneous fruiting time and good yield. While the other was satisfied with P-3XSB-24 hybrid due to its good yield and P-3XSE-5 hybrids thanks to its gradually fruiting body, benefiting in frequent harvest. Overall, farmers adopted all hybrids to grow as commercially cultivated strains as well as Hed Bhutan (P-3) strain.

Keywords: dikaryon, monokaryon, pleurotus, strain improvement

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

Abstract:

Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

Procedia PDF Downloads 156

Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu

Abstract:

Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.

Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model

Procedia PDF Downloads 252

Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Edison E. Haro, Akindele G. Odeshi, Jerzy A. Szpunar

Abstract:

Hybrid bio-composites are developed for use in protective armor through positive hybridization offered by reinforcement of high-density polyethylene (HDPE) with Kevlar short fibers and palm wood micro-fillers. The manufacturing process involved a combination of extrusion and compression molding techniques. The mechanical behavior of Kevlar fiber reinforced HDPE with and without palm wood filler additions are compared. The effect of the weight fraction of the added palm wood micro-fillers is also determined. The Young modulus was found to increase as the weight fraction of organic micro-particles increased. However, the flexural strength decreased with increasing weight fraction of added micro-fillers. The interfacial interactions between the components were investigated using scanning electron microscopy. The influence of the size, random alignment and distribution of the natural micro-particles was evaluated. Ballistic impact and dynamic shock loading tests were performed to determine the optimum proportion of Kevlar short fibers and organic micro-fillers needed to improve impact strength of the HDPE. These results indicate a positive hybridization by deposition of organic micro-fillers on the surface of short Kevlar fibers used in reinforcing the thermoplastic matrix leading to enhancement of the mechanical strength and dynamic impact behavior of these materials. Therefore, these hybrid bio-composites can be promising materials for different applications against high velocity impacts.

Keywords: hybrid bio-composites, organic nano-fillers, dynamic shocking loading, ballistic impacts, energy absorption

Procedia PDF Downloads 116