Search results for: time – varying feed back

Authors: A. T. Eswara

Abstract:

This paper analyses the unsteady, two-dimensional stagnation point flow of an incompressible viscous fluid over a flat sheet when the flow is started impulsively from rest and at the same time, the sheet is suddenly stretched in its own plane with a velocity proportional to the distance from the stagnation point. The partial differential equations governing the laminar boundary layer forced convection flow are non-dimensionalised using semi-similar transformations and then solved numerically using an implicit finitedifference scheme known as the Keller-box method. Results pertaining to the flow and heat transfer characteristics are computed for all dimensionless time, uniformly valid in the whole spatial region without any numerical difficulties. Analytical solutions are also obtained for both small and large times, respectively representing the initial unsteady and final steady state flow and heat transfer. Numerical results indicate that the velocity ratio parameter is found to have a significant effect on skin friction and heat transfer rate at the surface. Furthermore, it is exposed that there is a smooth transition from the initial unsteady state flow (small time solution) to the final steady state (large time solution).

Keywords: Forced flow, Keller-box method, Stagnation point, Stretching flat sheet, Unsteady laminar boundary layer, Velocity ratio parameter.

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Authors: É. Kónya, E. Szabó, I. Bata-Vidács, T. Deák, M. Ottucsák, N. Adányi, A. Székács

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Spice paprika is a major spice commodity in the European Union (EU), produced locally and imported from non-EU countries, reported not only for chemical and microbiological contamination, but also for fraud. The effective interaction between producers’ quality management practices and government and EU activities is described on the example of spice paprika production and control in Hungary, a country of leading spice paprika producer and per capita consumer in Europe. To demonstrate the importance of various contamination factors in the Hungarian production and EU trade of spice paprika, several aspects concerning food safety of this commodity are presented. Alerts in the Rapid Alert System for Food and Feed (RASFF) of the EU between 2005 and 2013, as well as Hungarian state inspection results on spice paprika in 2004 are discussed, and quality non-compliance claims regarding spice paprika among EU member states are summarized in by means of network analysis. Quality assurance measures established along the spice paprika production technology chain at the leading Hungarian spice paprika manufacturer, Kalocsai Fűszerpaprika Zrt. are surveyed with main critical control points identified. The structure and operation of the Hungarian state food safety inspection system is described. Concerted performance of the latter two quality management systems illustrates the effective interaction between internal (manufacturer) and external (state) quality control measures.

Keywords: Spice paprika, quality control, reporting mechanisms, RASFF, vulnerable points, HACCP, BRC Global Standard.

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Authors: Joshua S. Valeta, Marc C. Verdegem

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A study was undertaken to assess the potential of an Algal Turf Scrubber to remove nitrogen from aquaculture effluent to reduce environmental pollution. High total ammonia nitrogen concentrations were introduced to an Algal Turf Scrubber developed under varying hydraulic surface loading rates of African catfish (Clarius gariepinus) effluent in a recirculating aquaculture system. Nutrient removal rates were not affected at total suspended solids concentration of up to 0.04g TSS/l (P > 0.05). Nitrogen removal rates 0.93-0.99g TAN/m²/d were recorded at very high loading rates 3.76-3.81 g TAN/m²/d. Total ammonia removal showed ½ order kinetics between 1.6 to 2.3mg/l Total Ammonia Nitrogen concentrations. Nitrogen removal increased with its loading, which increased with hydraulic surface loading rate. Total Ammonia Nitrogen removal by Algal turf scrubber was higher than reported values for fluidized bed filters and trickling filters. The algal turf scrubber also effectively removed nitrate thereby reducing the need for water exchange.

Keywords: Algal turf, loading rate, nitrogen, organic matter, removal rate.

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Authors: G. Zazzaro, F.M. Pisano, G. Romano

Abstract:

During last decades, worldwide researchers dedicated efforts to develop machine-based seismic Early Warning systems, aiming at reducing the huge human losses and economic damages. The elaboration time of seismic waveforms is to be reduced in order to increase the time interval available for the activation of safety measures. This paper suggests a Data Mining model able to correctly and quickly estimate dangerousness of the running seismic event. Several thousand seismic recordings of Japanese and Italian earthquakes were analyzed and a model was obtained by means of a Bayesian Network (BN), which was tested just over the first recordings of seismic events in order to reduce the decision time and the test results were very satisfactory. The model was integrated within an Early Warning System prototype able to collect and elaborate data from a seismic sensor network, estimate the dangerousness of the running earthquake and take the decision of activating the warning promptly.

Keywords: Bayesian Networks, Decision Support System, Magnitude Classification, Seismic Early Warning System

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Authors: Delfim Soares Jr., Webe J. Mansur

Abstract:

The Time-Domain Boundary Element Method (TDBEM) is a well known numerical technique that handles quite properly dynamic analyses considering infinite dimension media. However, when these analyses are also related to nonlinear behavior, very complex numerical procedures arise considering the TD-BEM, which may turn its application prohibitive. In order to avoid this drawback and model nonlinear infinite media, the present work couples two BEM formulations, aiming to achieve the best of two worlds. In this context, the regions expected to behave nonlinearly are discretized by the Domain Boundary Element Method (D-BEM), which has a simpler mathematical formulation but is unable to deal with infinite domain analyses; the TD-BEM is employed as in the sense of an effective non-reflexive boundary. An iterative procedure is considered for the coupling of the TD-BEM and D-BEM, which is based on a relaxed renew of the variables at the common interfaces. Elastoplastic models are focused and different time-steps are allowed to be considered by each BEM formulation in the coupled analysis.

Keywords: Boundary Element Method, Dynamic Elastoplastic Analysis, Iterative Coupling, Multiple Time-Steps.

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Authors: A. Razavykia, A. Esmaeilzadeh, S. Iranmanesh

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Many orthopedic implants like proximal humerus cases require lower surface roughness and almost immediate/short lead time surgery. Thus, rapid response from the manufacturer is very crucial. Tool path strategy of milling process has a direct influence on the surface roughness and lead time of medical implant. High-speed milling as promised process would improve the machined surface quality, but conventional or super-abrasive grinding still required which imposes some drawbacks such as additional costs and time. Currently, many CAD/CAM software offers some different tool path strategies to milling free form surfaces. Nevertheless, the users must identify how to choose the strategies according to cutting tool geometry, geometry complexity, and their effects on the machined surface. This study investigates the effect of different tool path strategies for milling a proximal humerus head during finishing operation on stainless steel 316L. Experiments have been performed using MAHO MH700 S vertical milling machine and four machining strategies, namely, spiral outward, spiral inward, and radial as well as zig-zag. In all cases, the obtained surfaces were analyzed in terms of roughness and dimension accuracy compared with those obtained by simulation. The findings provide evidence that surface roughness, dimensional accuracy, and machining time have been affected by the considered tool path strategy.

Keywords: CAD/CAM software, milling, orthopedic implants, tool path strategy.

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Authors: Vishal Awasthi, Tanya Soni, Vigya Awasthi, Swati Singh, Shivali Verma

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There is a growing demand for a network that grants a high level of data security and confidentiality. For this reason, the semantic web was introduced, which allows data to be shared and reused across applications while safeguarding users privacy and user’s will grab back control of their data. The earlier Web 1.0 and Web 2.0 versions were built on client-server architecture, in  which there was the risk of data theft and unconsented sale of user data. A decentralized version, Known as Web 3.0, that is mostly built on blockchain technology was interjected to resolve these issues. The recent research focuses on blockchain technology, deals with privacy, security, transparency, and innovation of decentralized applications (DApps), e.g. a Twitter Clone, Whatsapp clone. In this paper the Twitter Alike built on the Ethereum blockchain will replace traditional techniques with improved latency, throughput, and data ownership. The central principle of this DApp is smart contract implemented using Solidity which is an object- oriented and highlevel language. Consequently, this will provide a better Quality Services, high data security, and integrity for both present and future internet technologies.

Keywords: Blockchain, DApps, Ethereum, Semantic Web, Smart Contract, Solidity.

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Authors: Hsuan-Ku Liu, Ming Long Liu

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In this paper, we investigate the solution of a two dimensional parabolic free boundary problem. The free boundary of this problem is modelled as a nonlinear integral equation (IE). For this integral equation, we propose an asymptotic solution as time is near to maturity and develop an integral iterative method. The computational results reveal that our asymptotic solution is very close to the numerical solution as time is near to maturity.

Keywords: Integral equation, asymptotic solution, free boundary problem, American exchange option.

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Authors: M. Kumpugdee-Vollrath, J.-P. Krause, S. Bürk

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Most of the drugs used for pharmaceutical purposes are poorly water-soluble drugs. About 40% of all newly discovered drugs are lipophilic and the numbers of lipophilic drugs seem to increase more and more. Drug delivery systems such as nanoparticles, micelles or liposomes are applied to improve their solubility and thus their bioavailability. Besides various techniques of solubilization, oil-in-water emulsions are often used to incorporate lipophilic drugs into the oil phase. To stabilize emulsions surface active substances (surfactants) are generally used. An alternative method to avoid the application of surfactants was of great interest. One possibility is to develop O/W-emulsion without any addition of surface active agents or the so called “surfactant-free emulsion or SFE”. The aim of this study was to develop and characterize SFE as a drug carrier by varying the production conditions. Lidocaine base was used as a model drug. The injection method was developed. Effects of ultrasound as well as of temperature on the properties of the emulsion were studied. Particle sizes and release were determined. The long-term stability up to 30 days was performed. The results showed that the surfactant-free O/W emulsions with pharmaceutical oil as drug carrier can be produced.

Keywords: Emulsion, lidocaine, Miglyol, size, surfactant, light scattering, release, injection, ultrasound, stability.

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Authors: Shang-En Yu

Abstract:

Human society, there are many uncertainties, such as economic growth rate forecast of the financial crisis, many scholars have, since the the Song Chissom two scholars in 1993 the concept of the so-called fuzzy time series (Fuzzy Time Series)different mode to deal with these problems, a previous study, however, usually does not consider the relevant variables selected and fuzzy process based solely on subjective opinions the fuzzy semantic discrete, so can not objectively reflect the characteristics of the data set, in addition to carrying outforecasts are often fuzzy rules as equally important, failed to consider the importance of each fuzzy rule. For these reasons, the variable selection (Factor Selection) through self-organizing map (Self-Organizing Map, SOM) and proposed high-end weighted multivariate fuzzy time series model based on fuzzy neural network (Fuzzy-BPN), and using the the sequential weighted average operator (Ordered Weighted Averaging operator, OWA) weighted prediction. Therefore, in order to verify the proposed method, the Taiwan stock exchange (Taiwan Stock Exchange Corporation) Taiwan Weighted Stock Index (Taiwan Stock Exchange Capitalization Weighted Stock Index, TAIEX) as experimental forecast target, in order to filter the appropriate variables in the experiment Finally, included in other studies in recent years mode in conjunction with this study, the results showed that the predictive ability of this study further improve.

Keywords: Heterogeneity, residential mortgage loans, foreclosure.

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Authors: Wanli Ma, Dat Tran, Dharmendra Sharma

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The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.

Keywords: Artificial Immune Systems, ComputationalIntelligence, Negative Selection, Pattern Discovery.

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Authors: M. H. M. Rusli, A. Jaffar, M. T. Ali, S. Muhamud @ Kayat

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Lean manufacturing is a production philosophy made popular by Toyota Motor Corporation (TMC). It is globally known as the Toyota Production System (TPS) and has the ultimate aim of reducing cost by thoroughly eliminating wastes or muda. TPS embraces the Just-in-time (JIT) manufacturing; achieving cost reduction through lead time reduction. JIT manufacturing can be achieved by implementing Pull system in the production. Furthermore, TPS aims to improve productivity and creating continuous flow in the production by arranging the machines and processes in cellular configurations. This is called as Cellular Manufacturing Systems (CMS). This paper studies on integrating the CMS with the Pull system to establish a Big Island-Pull system production for High Mix Low Volume (HMLV) products in an automotive component industry. The paper will use the build-in JIT system steps adapted from TMC to create the Pull system production and also create a shojinka line which, according to takt time, has the flexibility to adapt to demand changes simply by adding and taking out manpower. This will lead to optimization in production.

Keywords: Big Island layout, Lean manufacturing, Material and Information Flow Chart, Pull system production, TPS.

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Authors: Sun K. Yoo, Hee Cheol Kang

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Analysis of amplitude and phase characteristics for delta, theta, and alpha bands at localized time instant from EEG signals is important for the characterizing information processing in the brain. In this paper, complex demodulation method was used to analyze EEG (Electroencephalographic) signal, particularly for auditory evoked potential response signal, with sufficient time resolution and designated frequency bandwidth resolution required. The complex demodulation decomposes raw EEG signal into 3 designated delta, theta, and alpha bands with complex EEG signal representation at sampled time instant, which can enable the extraction of amplitude envelope and phase information. Throughout simulated test data, and real EEG signal acquired during auditory attention task, it can extract the phase offset, phase and frequency changing instant and decomposed amplitude envelope for delta, theta, and alpha bands. The complex demodulation technique can be efficiently used in brain signal analysis in case of phase, and amplitude information required.

Keywords: EEG, Complex Demodulation, Amplitude, Phase.

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: Convolutional neural network, discrete wavelet transform, deep learning, heart sound classification.

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Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G.M. Petrakis

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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called affective disorders, which is characterized by great mood swings. We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s nonresponse to treatment. We propose an architecture as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: Bipolar disorder, intelligent systems patient monitoring, semantic web technologies, IoT.

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Authors: Yi Chao Ma, Cheng Siong Chin, Wai Lok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: Hard disk drive noise, jury test, neural network model, psychoacoustic annoyance.

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Authors: Sura Al-Khafaji, Phil Purnell

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Measurement of the ultrasonic pulse velocity (UPV) is an important tool in diagnostic examination of concrete. In this method piezoelectric transducers are normally held in direct contact with the concrete surface. The current study aims to test the hypothesis that a preferential coupling effect might exist i.e. that the speed of sound measured depends on the couplant used. In this study, different coupling media of varying acoustic impedance were placed between the transducers and concrete samples made with constant aggregate content but with different compressive strengths. The preliminary results show that using coupling materials (both solid and a range of liquid substances) has an effect on the pulse velocity measured in a given concrete. The effect varies depending on the material used. The UPV measurements with solid coupling were higher than these from the liquid coupling at all strength levels. The tests using couplants generally recorded lower UPV values than the conventional test, except when carbon fiber composite was used, which retuned higher values. Analysis of variances (ANOVA) was performed to confirm that there are statistically significant differences between the measurements recorded using a conventional system and a coupled system.

Keywords: Compressive strength, coupling effect, statistical analysis, ultrasonic.

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Authors: B. S. Raghavendra, D. Narayana Dutt

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Many recent electrophysiological studies have revealed the importance of investigating meditation state in order to achieve an increased understanding of autonomous control of cardiovascular functions. In this paper, we characterize heart rate variability (HRV) time series acquired during meditation using nonlinear dynamical parameters. We have computed minimum embedding dimension (MED), correlation dimension (CD), largest Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV time series of eight Chi and four Kundalini meditation practitioners. The pre-meditation state has been used as a baseline (control) state to compare the estimated parameters. The chaotic nature of HRV during both pre-meditation and meditation is confirmed by MED. The meditation state showed a significant decrease in the value of CD and increase in the value of LLE of HRV, in comparison with premeditation state, indicating a less complex and less predictable nature of HRV. In addition, it was shown that the HRV of meditation state is having highest NLS than pre-meditation state. The study indicated highly nonlinear dynamic nature of cardiac states as revealed by HRV during meditation state, rather considering it as a quiescent state.

Keywords: Correlation dimension, Embedding dimension, Heartrate variability, Largest Lyapunov exponent, Meditation, Nonlinearity score.

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Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

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Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, Dengue, Space-time clustering analysis, Sri Lanka.

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Authors: Hani Mekdash, Lina Jaber, Yehia Temsah

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Underground space is becoming a necessity nowadays, especially in highly congested urban areas. Retaining underground excavations using shoring systems is essential in order to protect adjoining structures from potential damage or collapse. Reinforced Concrete Piles (RCP) supported by multiple rows of tie-back anchors are commonly used type of shoring systems in deep excavations. However, executing anchors can sometimes be challenging because they might illegally trespass neighboring properties or get obstructed by infrastructure and other underground facilities. A technique is proposed in this paper, and it involves the addition of eccentric high-strength steel strands to the RCP section through ducts without providing the pile with lateral supports. The strands are then vertically stressed externally on the pile cap using a hydraulic jack, creating a compressive strengthening force in the concrete section. An experimental study about the behavior of the shoring wall by pre-stressed piles is presented during the execution of an open excavation in an urban area (Beirut city) followed by numerical analysis using finite element software. Based on the experimental results, this technique is proven to be cost-effective and provides flexible and sustainable construction of shoring works.

Keywords: Excavation, inclinometer, prestressing, shoring system.

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modeling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modeling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modeling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: Content analysis, factors, integrated waste management system, time series.

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Authors: M. S. Kaiser, Swagata Dutta

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In the present work, the effect of load and sliding distance on the performance tribology of commercially used aluminium-silicon engine block and piston was evaluated at ambient conditions with humidity of 80% under dry sliding conditions using a pin-on-disc with two different loads of 5N and 20N yielding applied pressure of 0.30MPa and 1.4MPa, respectively, at sliding velocity of 0.29ms-1 and with varying sliding distance ranging from 260m- 4200m. Factors and conditions that had significant effect were identified. The results showed that the load and the sliding distance affect the wear rate of the alloys and the wear rate increased with increasing load for both the alloys. Wear rate also increases almost linearly at low loads and increase to a maximum then attain a plateau with increasing sliding distance. For both applied loads the piston alloy showed the better performance due to higher Ni and Mg content. The worn surface and wear debris was characterized by optical microscope, SEM and EDX analyzer. The worn surface was characterized by surface with shallow grooves at loads while the groove width and depth increased as the loads increases. Oxidative wear was found to be the predominant mechanisms in the dry sliding of Al-Si alloys at low loads.

Keywords: Wear, friction, gravimetric analysis, aluminiumsilicon alloys, SEM, EDX.

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Authors: Nader Gharibnavaz, Naser Gharibnavaz

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This study extends research on the relationship between marketing strategy and market segmentation by investigating on market segments in the cement industry. Competitive strength and rivals distance from the factory were used as business environment. A three segment (positive, neutral or indifferent and zero zones) were identified as strategic segments. For each segment a marketing strategy (aggressive, defensive and decline) were developed. This study employed data from cement industry to fulfill two objectives, the first is to give a framework to the segmentation of cement industry and the second is developing marketing strategy with varying competitive strength. Fifty six questionnaires containing close-and open-ended questions were collected and analyzed. Results supported the theory that segments tend to be more aggressive than defensive when competitive strength increases. It is concluded that high strength segments follow total market coverage, concentric diversification and frontal attack to their competitors. With decreased competitive strength, Business tends to follow multi-market strategy, product modification/improvement and flank attack to direct competitors for this kind of segments. Segments with weak competitive strength followed focus strategy and decline strategy.

Keywords: Marketing strategy, Competitive strength, Market Segmentation

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Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

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Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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Authors: S. Tangjuank, N. Insuk , J. Tontrakoon , V. Udeye

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Cashew nut shells were converted into activated carbon powders using KOH activation plus CO2 gasification at 1027 K. The increase both of impregnation ratio and activation time, there was swiftly the development of mesoporous structure with increasing of mesopore volume ratio from 20-28% and 27-45% for activated carbon with ratio of KOH per char equal to 1 and 4, respectively. Activated carbon derived from KOH/char ratio equal to 1 and CO2 gasification time from 20 to 150 minutes were exhibited the BET surface area increasing from 222 to 627 m2.g-1. And those were derived from KOH/char ratio of 4 with activation time from 20 to 150 minutes exhibited high BET surface area from 682 to 1026 m2.g-1. The adsorption of Lead(II) and Cadmium(II) ion was investigated. This adsorbent exhibited excellent adsorption for Lead(II) and Cadmium(II) ion. Maximum adsorption presented at 99.61% at pH 6.5 and 98.87% at optimum conditions. The experimental data was calculated from Freundlich isotherm and Langmuir isotherm model. The maximum capacity of Pb2+ and Cd2+ ions was found to be 28.90 m2.g-1 and 14.29 m2.g-1, respectively.

Keywords: Activated carbon, cashew nut shell, heavy metals, adsorption.

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Authors: M. A. S. Fahim, J. Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realization often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: Air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter.

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Authors: Bandula-Heva, T., Dhanasekar, M.

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True stress-strain curve of railhead steel is required to investigate the behaviour of railhead under wheel loading through elasto-plastic Finite Element (FE) analysis. To reduce the rate of wear, the railhead material is hardened through annealing and quenching. The Australian standard rail sections are not fully hardened and hence suffer from non-uniform distribution of the material property; usage of average properties in the FE modelling can potentially induce error in the predicted plastic strains. Coupons obtained at varying depths of the railhead were, therefore, tested under axial tension and the strains were measured using strain gauges as well as an image analysis technique, known as the Particle Image Velocimetry (PIV). The head hardened steel exhibit existence of three distinct zones of yield strength; the yield strength as the ratio of the average yield strength provided in the standard (σyr=780MPa) and the corresponding depth as the ratio of the head hardened zone along the axis of symmetry are as follows: (1.17 σyr, 20%), (1.06 σyr, 20%-80%) and (0.71 σyr, > 80%). The stress-strain curves exhibit limited plastic zone with fracture occurring at strain less than 0.1.

Keywords: Stress-Strain Curve, Tensile Test, Particle Image Velocimetry, Railhead Metal Properties

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Authors: M. M. Hossain, M. Z. Hasan, M. Alauddin, S. Akhter

Abstract:

Climate change has become a major concern across the world as the intensity along with quantity of the rainfall, mean surface temperature and other climatic parameters have been changed not only in Bangladesh but also in the entire globe. Bangladesh has already experienced many natural hazards. Among them changing of rainfall pattern, erratic and heavy rainfalls are very common. But changes of rainfall pattern and its amount is still in question to some extent. This study aimed to unfold how the historical rainfalls varied over time and how would be their future trends. In this context, historical rainfall data (1975-2014) were collected from Bangladesh Metrological Department (BMD) and then a time series model was developed using Box-Jenkins algorithm in IBM SPSS to forecast the future rainfall. From the historical data analysis, this study revealed that the amount of rainfall decreased over the time and shifted to the post monsoons. Forecasted rainfall shows that the pre-monsoon and early monsoon will get drier in future whereas late monsoon and post monsoon will show huge fluctuations in rainfall magnitudes with temporal variations which means Bangladesh will get comparatively drier seasons in future which may be a serious problem for the country as it depends on agriculture.

Keywords: Monsoon, Pre-monsoon, rainfall, pattern, variations, IBM-SPSS.

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Authors: Minsoo Lee, Yun-mi Kim, Yoon-kyung Lee

Abstract:

XML data consists of a very flexible tree-structure which makes it difficult to support the storing and retrieving of XML data. The node numbering scheme is one of the most popular approaches to store XML in relational databases. Together with the node numbering storage scheme, structural joins can be used to efficiently process the hierarchical relationships in XML. However, in order to process a tree-structured XPath query containing several hierarchical relationships and conditional sentences on XML data, many structural joins need to be carried out, which results in a high query execution cost. This paper introduces mechanisms to reduce the XPath queries including branch nodes into a much more efficient form with less numbers of structural joins. A two step approach is proposed. The first step merges duplicate nodes in the tree-structured query and the second step divides the query into sub-queries, shortens the paths and then merges the sub-queries back together. The proposed approach can highly contribute to the efficient execution of XML queries. Experimental results show that the proposed scheme can reduce the query execution cost by up to an order of magnitude of the original execution cost.

Keywords: XML, Xpath, tree-structured query, query reduction.

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Authors: Pramod Goyal, S. K. Saxena

Abstract:

The convergence of heterogeneous wireless access technologies characterizes the 4G wireless networks. In such converged systems, the seamless and efficient handoff between different access technologies (vertical handoff) is essential and remains a challenging problem. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the “best" available network at “best" time to reduce the unnecessary handoffs. This paper proposes a dynamic decision model to decide the “best" network at “best" time moment to handoffs. The proposed dynamic decision model make the right vertical handoff decisions by determining the “best" network at “best" time among available networks based on, dynamic factors such as “Received Signal Strength(RSS)" of network and “velocity" of mobile station simultaneously with static factors like Usage Expense, Link capacity(offered bandwidth) and power consumption. This model not only meets the individual user needs but also improve the whole system performance by reducing the unnecessary handoffs.

Keywords: Dynamic decision model, Seamless handoff, Vertical handoff, Wireless networks

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