Search results for: Dynamic system

Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: Mobile augmented reality, remote collaboration, user experience, cognitive model.

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Authors: Mohammed Sani Abdulai

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Ghana’s Public Financial Management reforms have been going on for some two decades now (1997/98 to 2017/18). Given this long period of reforms, Ghana in 2019 is putting together both a Public Financial Management (PFM) strategy and a Ghana Integrated Financial Management Information System (GIFMIS) strategy for the next 5-years (2020-2024). The primary aim of these dual strategies is assisting the country in moving beyond reforms to consolidation and sustainability. In this paper we, first, examined the evolution of Ghana’s PFM reforms. We, secondly, reviewed the legal and institutional reforms undertaken to strengthen the country’s key PFM institutions. Thirdly, we summarized the strengths and weaknesses identified by the 2018 Public Expenditure and Financial Accountability (PEFA) assessment of Ghana’s PFM system relating to its macro-fiscal framework, budget preparation and approval, budget execution, accounting and fiscal reporting as well as external scrutiny and audit. We, finally, considered what the country should be doing to achieve its intended goal of PFM consolidation and sustainability. Using a qualitative method of review and analysis of existing documents, we, through this paper, brought to the fore the lessons that could be learnt by other developing countries from Ghana’s PFM reforms experiences. These lessons included the need to: (a) undergird any PFM reform with a comprehensive PFM reform strategy; (b) undertake a legal and institutional reforms of the key PFM institutions; (c) assess the strengths and weaknesses of those reforms using PFM performance evaluation tools such as PEFA framework; and (d) move beyond reforms to consolidation and sustainability.

Keywords: Public financial management, public expenditure and financial accountability (PEFA), reforms, consolidation, sustainability.

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Authors: Francis Chinweuba Eboh, Peter Ahlström, Tobias Richards

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Entropy, as an outcome of the second law of thermodynamics, measures the level of irreversibility associated with any process. The identification and reduction of irreversibility in the energy conversion process helps to improve the efficiency of the system. The entropy of pure substances known as absolute entropy is determined at an absolute reference point and is useful in the thermodynamic analysis of chemical reactions; however, municipal solid waste (MSW) is a structurally complicated material with unknown absolute entropy. In this work, an empirical model to calculate the absolute entropy of MSW based on the content of carbon, hydrogen, oxygen, nitrogen, sulphur, and chlorine on a dry ash free basis (daf) is presented. The proposed model was derived from 117 relevant organic substances which represent the main constituents in MSW with known standard entropies using statistical analysis. The substances were divided into different waste fractions; namely, food, wood/paper, textiles/rubber and plastics waste and the standard entropies of each waste fraction and for the complete mixture were calculated. The correlation of the standard entropy of the complete waste mixture derived was found to be s^o_msw= 0.0101C + 0.0630H + 0.0106O + 0.0108N + 0.0155S + 0.0084Cl (kJ.K^-1.kg) and the present correlation can be used for estimating the absolute entropy of MSW by using the elemental compositions of the fuel within the range of 10.3% ≤ C ≤ 95.1%, 0.0% ≤ H ≤ 14.3%, 0.0% ≤ O ≤ 71.1%, 0.0 ≤ N ≤ 66.7%, 0.0% ≤ S ≤ 42.1%, 0.0% ≤ Cl ≤ 89.7%. The model is also applicable for the efficient modelling of a combustion system in a waste-to-energy plant.

Keywords: Absolute entropy, irreversibility, municipal solid waste, waste-to-energy.

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Authors: Camelia Frigioiu, Katica (Stevanovic) Hedrih, Iulian Gabriel Birsan

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In this paper we study the rheonomic mechanical systems from the point of view of Lagrange geometry, by means of its canonical semispray. We present an example of the constraint motion of a material point, in the rheonomic case.

Keywords: Lagrange's equations, mechanical system, non-linear connection, rheonomic Lagrange space.

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

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

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: A. Suñol, D. Vucinic, S.Vanlanduit, T. Markova, A. Aksenov, I. Moskalyov

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Feeder is one of the airships of the Multibody Advanced Airship for Transport (MAAT) system, under development within the EU FP7 project. MAAT is based on a modular concept composed of two different parts that have the possibility to join; respectively they are the so-called Cruiser and Feeder, designed on the lighter than air principle. Feeder, also named ATEN (Airship Transport Elevator Network), is the smaller one which joins the bigger one, Cruiser, also named PTAH (Photovoltaic modular Transport Airship for High altitude),envisaged to happen at 15km altitude. During the MAAT design phase, the aerodynamic studies of the both airships and their interactions are analyzed. The objective of these studies is to understand the aerodynamic behavior of all the preselected configurations, as an important element in the overall MAAT system design. The most of these configurations are only simulated by CFD, while the most feasible one is experimentally analyzed in order to validate and thrust the CFD predictions. This paper presents the numerical and experimental investigation of the Feeder “conical like" shape configuration. The experiments are focused on the aerodynamic force coefficients and the pressure distribution over the Feeder outer surface, while the numerical simulation cover also the analysis of the velocity and pressure distribution. Finally, the wind tunnel experiment is compared with its CFD model in order to validate such specific simulations with respective experiments and to better understand the difference between the wind tunnel and in-flight circumstances.

Keywords: MAAT project Feeder, CFD simulations, wind tunnel experiments, lateral wind influence.

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: Expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis.

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Authors: M. Rossini, A. Portioli Studacher

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The market competition is moving from the single firm to the whole supply chain because of increasing competition and growing need for operational efficiencies and customer orientation. Supply chain management allows companies to look beyond their organizational boundaries to develop and leverage resources and capabilities of their supply chain partners. This creates competitive advantages in the marketplace and because of this SCM has acquired strategic importance. Lean Approach is a management strategy that focuses on reducing every type of waste present in an organization. This approach is becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In particular, it is not well studied which are the impacts of lean approach principles in a supply chain context. In literature there are only few studies aimed at understanding the qualitative impact of the lean approach in supply chains. Therefore, the goal of this research work is to study the impacts of lean principles implementation along a supply chain. To achieve this, a simulation model of a threeechelon multi-product supply chain has been built. Kanban system (and several priority policies) and setup time reduction degrees are implemented in the lean-configured supply chain to apply pull and lot-sizing decrease principles respectively. To evaluate the benefits of lean approach, lean supply chain is compared with an EOQ-configured supply chain. The simulation results show that Kanban system and setup-time reduction improve inventory stock level. They also show that logistics efforts are affected to lean implementation degree. The paper concludes describing performances of lean supply chain in different contexts.

Keywords: Inventory policy, Kanban, lean supply chain, simulation study, supply chain management, planning.

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Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani

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Rural electrification rates are generally low in Iran and many parts of the world that lack sustainable renewable energy resources. Many homes are based on polluting solutions such as crude oil and diesel generators for lighting, heating, and charging electrical gadgets. Small-scale portable solar battery packs are accessible to the public; however, they have low capacity and are challenging to be distributed in developing countries. To design a battery-based microgrid power systems, the load profile is one of the key parameters. Additionally, the reliability of the system should be taken into account. A conventional microgrid system can be either AC or coupling DC. Both AC and DC microgrids have advantages and disadvantages depending on their application and can be either connected to the main grid or perform independently. This article proposes a tool for optimal sizing of microgrid-independent systems via respective analysis. To show such an analysis, the type of power generation, number of panels, battery capacity, microgrid size, and group of available consumers should be considered. Therefore, the optimization of different design scenarios is based on number of solar panels and super saving sources, ranges of the depth of discharges, to calculate size and estimate the overall cost. Generally, it is observed that there is an inverse relationship between the depth spectrum of discharge and the solar microgrid costs.

Keywords: Storage, super-storage, grid-independent, economic factors, microgrid.

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Authors: Ayub Khan, Net Ram Garg, Geeta Jain

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In this paper, Backstepping method is proposed to synchronize two fractional-order systems. The simulation results show that this method can effectively synchronize two chaotic systems.

Keywords: Backstepping method, Fractional order, Synchronization.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

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A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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Authors: Ioannis P. Panagopoulos, Christos C. Pavlatos, George K. Papakonstantinou

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Conventional approaches in the implementation of logic programming applications on embedded systems are solely of software nature. As a consequence, a compiler is needed that transforms the initial declarative logic program to its equivalent procedural one, to be programmed to the microprocessor. This approach increases the complexity of the final implementation and reduces the overall system's performance. On the contrary, presenting hardware implementations which are only capable of supporting logic programs prevents their use in applications where logic programs need to be intertwined with traditional procedural ones, for a specific application. We exploit HW/SW codesign methods to present a microprocessor, capable of supporting hybrid applications using both programming approaches. We take advantage of the close relationship between attribute grammar (AG) evaluation and knowledge engineering methods to present a programmable hardware parser that performs logic derivations and combine it with an extension of a conventional RISC microprocessor that performs the unification process to report the success or failure of those derivations. The extended RISC microprocessor is still capable of executing conventional procedural programs, thus hybrid applications can be implemented. The presented implementation is programmable, supports the execution of hybrid applications, increases the performance of logic derivations (experimental analysis yields an approximate 1000% increase in performance) and reduces the complexity of the final implemented code. The proposed hardware design is supported by a proposed extended C-language called C-AG.

Keywords: Attribute Grammars, Logic Programming, RISC microprocessor.

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Authors: Guanglin Song

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Situated within the context of China's tiered medical treatment system, this study aims to analyze spatial causes of urban healthcare access difficulties from the perspective of the configuration of healthcare facilities. A social network analysis approach is employed to construct a healthcare demand and supply flow network between major residential clusters and various tiers of hospitals in the city. The findings reveal that: 1) There exists overall maldistribution and over-concentration of healthcare resources in the study area, characterized by structural imbalance. 2) The low rate of primary care utilization in the study area is a key factor contributing to congestion at higher-tier hospitals, as excessive reliance on these institutions by neighboring communities exacerbates the problem. 3) Gradual optimization of the healthcare facility layout in the study area, encompassing holistic, local, and individual institutional levels, can enhance systemic efficiency and resource balance. This research proposes a method for evaluating urban healthcare resource distribution structures based on service flows within hierarchical networks. It offers spatially targeted optimization suggestions for promoting the implementation of the tiered healthcare system and alleviating challenges related to accessibility and congestion in seeking medical care. In addition, the study provides some new ideas for researchers and healthcare managers in countries, cities, and healthcare management around the world with similar challenges.

Keywords: Flow of public services, healthcare facilities, spatial planning, urban networks.

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Authors: P. Pimsee, C. Sablayrolles, P. de Caro, J. Guyomarch, N. Lesage, M. Montréjaud-Vignoles

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The MIGR’HYCAR research project was initiated to provide decisional tools for risks connected to oil spill drifts in continental waters. These tools aim to serve in the decision-making process once oil spill pollution occurs and/or as reference tools to study scenarios of potential impacts of pollutions on a given site. This paper focuses on the study of the distribution of polycyclic aromatic hydrocarbons (PAHs) and derivatives from oil spill in water as function of environmental parameters. Eight petroleum oils covering a representative range of commercially available products were tested. 41 polycyclic aromatic hydrocarbons (PAHs) and derivates, among them 16 EPA priority pollutants were studied by dynamic tests at laboratory scale. The chemical profile of the water soluble fraction was different from the parent oil profile due to the various water solubility of oil components. Semi-volatile compounds (naphtalenes) constitute the major part of the water soluble fraction. A large variation in composition of the water soluble fraction was highlighted depending on oil type. Moreover, four environmental parameters (temperature, suspended solid quantity, salinity and oil: water surface ratio) were investigated with the Taguchi experimental design methodology. The results showed that oils are divided into three groups: the solubility of Domestic fuel and Jet A1 presented a high sensitivity to parameters studied, meaning they must be taken into account. For Gasoline (SP95-E10) and Diesel fuel, a medium sensitivity to parameters was observed. In fact, the four others oils have shown low sensitivity to parameters studied. Finally, three parameters were found to be significant towards the water soluble fraction.

Keywords: Monitoring, PAHs, SBSE, water soluble fraction, Taguchi experimental design.

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Authors: Prasanta Kundu, N.K. Kishore, A.K. Sinha

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Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.

Keywords: Acoustic emission, discrete wavelet transform, partial discharge, wavelet packet analysis.

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Authors: Maumita Bhattacharya

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Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

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Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: R. S. Fyath, Mustafa A. B. Al-Qadi

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The inphase/quadrature (I/Q) amplitude and phase imbalance effects are studied in coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. An analytical model for the I/Q imbalance is developed and supported by simulation results. The results indicate that the I/Q imbalance degrades the BER performance considerably.

Keywords: Coherent detection, I/Q imbalance, OFDM, optical communications

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

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In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: Bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset.

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Authors: Omid A. Zargar

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Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.

Keywords: Gas turbine, turbine compressor, vibration data collector, utility, condition monitoring, non-contact probe, Relative Vibration, Absolute Vibration, Split Resonance, Time Wave Form (TWF), Fast Fourier transform (FFT).

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Authors: Gesine Hellwig

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Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Keywords: Functional imaging, Tracer kinetic modeling, LTIsystem, Indicator dilution theory / convolution approach, Two-Compartment model.

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Authors: Rafal Stegierski, Krzysztof Dmitruk

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The paper focus on robotic telepresence system build around humanoid robot operated with controller-less Wizard of Oz technique. Proposed solution gives possibility to quick start acting as a operator with short, if any, initial training.

Keywords: Robotics, Motion Capture, Wizard of Oz, Humanoid Robots, Human Robot Interaction.

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Authors: Hamed Khani Arani, Mohammad Shariyat, Armaghan Mohammadian

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In the present study, the free vibration of magnetostrictive nano-plate (MsNP) resting on the Pasternak foundation is investigated. Firstly, the modified couple stress (MCS) and nonlocal elasticity theories are compared together and taken into account to consider the small scale effects; in this paper not only two theories are analyzed but also it improves the MCS theory is more accurate than nonlocal elasticity theory in such problems. A feedback control system is utilized to investigate the effects of a magnetic field. First-order shear deformation theory (FSDT), Hamilton’s principle and energy method are utilized in order to drive the equations of motion and these equations are solved by differential quadrature method (DQM) for simply supported boundary conditions. The MsNP undergoes in-plane forces in x and y directions. In this regard, the dimensionless frequency is plotted to study the effects of small scale parameter, magnetic field, aspect ratio, thickness ratio and compression and tension loads. Results indicate that these parameters play a key role on the natural frequency. According to the above results, MsNP can be used in the communications equipment, smart control vibration of nanostructure especially in sensor and actuators such as wireless linear micro motor and smart nano valves in injectors.

Keywords: Feedback control system, magnetostrictive nano-plate, modified couple stress theory, nonlocal elasticity theory, vibration analysis.

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Authors: P. G. Siddheshwar, T. N. Sakshath

Abstract:

In the paper we make linear and non-linear stability analyses of Rayleigh-Bénard convection of a Newtonian nanoliquid in a rotating medium (called as Rayleigh-Bénard-Taylor convection). Rigid-rigid isothermal boundaries are considered for investigation. Khanafer-Vafai-Lightstone single phase model is used for studying instabilities in nanoliquids. Various thermophysical properties of nanoliquid are obtained using phenomenological laws and mixture theory. The eigen boundary value problem is solved for the Rayleigh number using an analytical method by considering trigonometric eigen functions. We observe that the critical nanoliquid Rayleigh number is less than that of the base liquid. Thus the onset of convection is advanced due to the addition of nanoparticles. So, increase in volume fraction leads to advanced onset and thereby increase in heat transport. The amplitudes of convective modes required for estimating the heat transport are determined analytically. The tri-modal standard Lorenz model is derived for the steady state assuming small scale convective motions. The effect of rotation on the onset of convection and on heat transport is investigated and depicted graphically. It is observed that the onset of convection is delayed due to rotation and hence leads to decrease in heat transport. Hence, rotation has a stabilizing effect on the system. This is due to the fact that the energy of the system is used to create the component V. We observe that the amount of heat transport is less in the case of rigid-rigid isothermal boundaries compared to free-free isothermal boundaries.

Keywords: Nanoliquid, rigid-rigid, rotation, single-phase.

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Authors: Prasanth Sabarish Nair, Thomas Binu, Madiajagan Muthaiyan

Abstract:

This paper discusses a software application to aid in the smooth functioning of a university internship program, including a student, faculty and an administration module. The software can also calculate the most apt combination of students to stations and allocate them respectively.

Keywords: Academic evaluation, administration monitoring, automatic allocation system, internship, student preferences.

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Authors: N.H. Abdurahman, Y. M. Rosli, N. H. Azhari, S. F. Tam

Abstract:

The direct discharge of palm oil mill effluent (POME) wastewater causes serious environmental pollution due to its high chemical oxygen demand (COD) and biochemical oxygen demand (BOD). Traditional ways for POME treatment have both economical and environmental disadvantages. In this study, a membrane anaerobic system (MAS) was used as an alternative, cost effective method for treating POME. Six steady states were attained as a part of a kinetic study that considered concentration ranges of 8,220 to 15,400 mg/l for mixed liquor suspended solids (MLSS) and 6,329 to 13,244 mg/l for mixed liquor volatile suspended solids (MLVSS). Kinetic equations from Monod, Contois and Chen & Hashimoto were employed to describe the kinetics of POME treatment at organic loading rates ranging from 2 to 13 kg COD/m3/d. throughout the experiment, the removal efficiency of COD was from 94.8 to 96.5% with hydraulic retention time, HRT from 400.6 to 5.7 days. The growth yield coefficient, Y was found to be 0.62gVSS/g COD the specific microorganism decay rate was 0.21 d-1 and the methane gas yield production rate was between 0.25 l/g COD/d and 0.58 l/g COD/d. Steady state influent COD concentrations increased from 18,302 mg/l in the first steady state to 43,500 mg/l in the sixth steady state. The minimum solids retention time, which was obtained from the three kinetic models ranged from 5 to 12.3 days. The k values were in the range of 0.35 – 0.519 g COD/ g VSS • d and values were between 0.26 and 0.379 d-1. The solids retention time (SRT) decreased from 800 days to 11.6 days. The complete treatment reduced the COD content to 2279 mg/l equivalent to a reduction of 94.8% reduction from the original.

Keywords: COD reduction, POME, kinetics, membrane, anaerobic, monod, contois equation.

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Authors: Debolina Chatterjee, Suhita Chopra Chatterjee

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Imprisonment is an expansive concept, as it is regulated by laws under criminal justice system of the state. The state sets principles of punishment to control offenders and also puts limits to excess punitive control. One significant way through which it exercises control is through rules governing healthcare of imprisoned population. Prisons signify specialized settings which accommodate both medical and legal concerns. The provision of care operates within the institutional paradigm of punishment. This requires the state to negotiate adequately between goals of punishment and fulfilment of basic human rights of offenders. The present study is based on a critical analysis of prison healthcare standards in India, which include government policies and guidelines. It also demonstrates how healthcare is delivered by drawing insights from a primary study conducted in a correctional home in the state of West Bengal, India, which houses both male and female inmates. Forty women were interviewed through semi-structured interviews, followed by focus group discussions. Doctors and administrative personnel were also interviewed. Findings show how institutional practices control women through subversion of the role of doctors to prison administration. Also, poor healthcare infrastructure, unavailability of specialized services, hierarchies between personnel and inmates make prisons unlikely sites for therapeutic intervention. The paper further discusses how institutional practices foster gender-based discriminatory practices.

Keywords: Imprisonment, imprisoned women, prison healthcare, prison policies.

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Authors: Markus Nordlund, Arkadiusz K. Kuczaj

Abstract:

Philip Morris International (PMI) is developing a range of novel tobacco products with the potential to reduce individual risk and population harm in comparison to smoking cigarettes. One of these products is the Tobacco Heating System 2.2 (THS 2.2), (named as the Electrically Heated Tobacco System (EHTS) in this paper), already commercialized in a number of countries (e.g., Japan, Italy, Switzerland, Russia, Portugal and Romania). During use, the patented EHTS heats a specifically designed tobacco product (Electrically Heated Tobacco Product (EHTP)) when inserted into a Holder (heating device). The EHTP contains tobacco material in the form of a porous plug that undergoes a controlled heating process to release chemical compounds into vapors, from which an aerosol is formed during cooling. The aim of this work was to investigate the aerosol formation characteristics for realistic operating conditions of the EHTS as well as for relevant gas mixture compositions measured in the EHTP aerosol consisting mostly of water, glycerol and nicotine, but also other compounds at much lower concentrations. The nucleation process taking place in the EHTP during use when operated in the Holder has therefore been modeled numerically using an extended Classical Nucleation Theory (CNT) for multicomponent gas mixtures. Results from the performed simulations demonstrate that aerosol droplets are formed only in the presence of an aerosol former being mainly glycerol. Minor compounds in the gas mixture were not able to reach a supersaturated state alone and therefore could not generate aerosol droplets from the multicomponent gas mixture at the operating conditions simulated. For the analytically characterized aerosol composition and estimated operating conditions of the EHTS and EHTP, glycerol was shown to be the main aerosol former triggering the nucleation process in the EHTP. This implies that according to the CNT, an aerosol former, such as glycerol needs to be present in the gas mixture for an aerosol to form under the tested operating conditions. To assess if these conclusions are sensitive to the initial amount of the minor compounds and to include and represent the total mass of the aerosol collected during the analytical aerosol characterization, simulations were carried out with initial masses of the minor compounds increased by as much as a factor of 500. Despite this extreme condition, no aerosol droplets were generated when glycerol, nicotine and water were treated as inert species and therefore not actively contributing to the nucleation process. This implies that according to the CNT, an aerosol cannot be generated without the help of an aerosol former, from the multicomponent gas mixtures at the compositions and operating conditions estimated for the EHTP, even if all minor compounds are released or generated in a single puff.

Keywords: Aerosol, Classical Nucleation Theory (CNT), Electrically Heated Tobacco Product (EHTP), Electrically Heated Tobacco System (EHTS), modeling, multicomponent, nucleation.

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Authors: S. Rao Rayapudi

Abstract:

Economic Load Dispatch (ELD) is a method of determining the most efficient, low-cost and reliable operation of a power system by dispatching available electricity generation resources to supply load on the system. The primary objective of economic dispatch is to minimize total cost of generation while honoring operational constraints of available generation resources. In this paper an intelligent water drop (IWD) algorithm has been proposed to solve ELD problem with an objective of minimizing the total cost of generation. Intelligent water drop algorithm is a swarm-based natureinspired optimization algorithm, which has been inspired from natural rivers. A natural river often finds good paths among lots of possible paths in its ways from source to destination and finally find almost optimal path to their destination. These ideas are embedded into the proposed algorithm for solving economic load dispatch problem. The main advantage of the proposed technique is easy is implement and capable of finding feasible near global optimal solution with less computational effort. In order to illustrate the effectiveness of the proposed method, it has been tested on 6-unit and 20-unit test systems with incremental fuel cost functions taking into account the valve point-point loading effects. Numerical results shows that the proposed method has good convergence property and better in quality of solution than other algorithms reported in recent literature.

Keywords: Economic load dispatch, Transmission loss, Optimization, Valve point loading, Intelligent Water Drop Algorithm.

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