Search results for: exponential entropy

Authors: Kailash C. Madan

Abstract:

We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: A three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state.

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Authors: M. Sadeghi, A.H. Jafari, S.M.P. Firoozabadi

Abstract:

Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.

Keywords: Chaos, Deep Brain Stimulation, Parkinson's Disease, Stimulation Parameters, tremor.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

Abstract:

The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: Fathi Taibi

Abstract:

Reusability is a quality desired attribute in software products. Generally, it could be achieved through adopting development methods that promote it and achieving software qualities that have been linked with high reusability proneness. With the exponential growth in mobile application development, software reuse became an integral part in a substantial number of projects. Similarly, software reuse has become widely practiced in start-up companies. However, this has led to new emerging problems. Firstly, the reused code does not meet the required quality and secondly, the reuse intentions are dubious. This work aims to propose a framework to support reuse in Object-Oriented (OO) software development. The framework comprises a process that uses a proposed reusability assessment metric and a formal foundation to specify the elements of the reused code and the relationships between them. The framework is empirically evaluated using a wide range of open-source projects and mobile applications. The results are analyzed to help understand the reusability proneness of OO software and the possible means to improve it.

Keywords: Software reusability, software metrics, object-oriented software, modularity, low complexity, understandability.

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Authors: Choon Ling Sia, Yani Shi, Jiaqi Yan, Huaping Chen

Abstract:

With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer-s trust. For new or unknown Internet business, consumers- lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer-s trust in new or unknown online store.

Keywords: Trust, Web site design, Human-ComputerInteraction, E-Commerce, Design science, Bayesian network.

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Authors: Y. Laidani, G. Henini, S. Hanini, A. Labbaci, F. Souahi

Abstract:

In this study, pomegranate skin, a material suitable for the conditions in Algeria, was chosen as adsorbent material for removal of lead in an aqueous solution. Biosorption studies were carried out under various parameters such as mass adsorbent particle, pH, contact time, the initial concentration of metal, and temperature. The experimental results show that the percentage of biosorption increases with an increase in the biosorbent mass (0.25 g, 0.035 mg/g; 1.25 g, 0.096 mg/g). The maximum biosorption occurred at pH value of 8 for the lead. The equilibrium uptake was increased with an increase in the initial concentration of metal in solution (Co = 4 mg/L, q_t = 1.2 mg/g). Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The best fit was obtained by the Langmuir model with high correlation coefficients (R² > 0.995) and a maximum monolayer adsorption capacity of 0.85 mg/g for lead. The adsorption of the lead was exothermic in nature (ΔH° = -17.833 kJ/mol for Pb (II). The reaction was accompanied by a decrease in entropy (ΔS° = -0.056 kJ/K. mol). The Gibbs energy (ΔG°) increased from -1.458 to -0.305 kJ/mol, respectively for Pb (II) when the temperature was increased from 293 to 313 K.

Keywords: Biosorption, Pb(II), pomegranate skin, wastewater.

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Authors: J. Tonkonogij, A. Pedišius, A. Stankevičius

Abstract:

The new semi-experimental method for simulation of the turbine flow meters rotation in the transitional flow has been developed. The method is based on the experimentally established exponential low of changing of dimensionless relative turbine gas meter rotation frequency and meter inertia time constant. For experimental evaluation of the meter time constant special facility has been developed. The facility ensures instant switching of turbine meter under test from one channel to the other channel with different flow rate and measuring the meter response. The developed method can be used for evaluation and predication of the turbine meters response and dynamic error in the transitional flow with any arbitrary law of flow rate changing. The examples of the method application are presented.

Keywords: Dynamic error, pulsing flow, numerical simulation, response, turbine gas meters.

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Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

Abstract:

Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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Authors: Himanshu Patel, R. T. Vashi

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Adsorption of Toluidine blue dye from aqueous solutions onto Neem Leaf Powder (NLP) has been investigated. The surface characterization of this natural material was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (AG"), enthalpy change (AH') and entropy change (AS°) were also determined and evaluated.

Keywords: Adsorption, isotherm models, kinetic models, temperature, toluidine blue dye, surface chemistry.

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Authors: Ren Jian-min, Wu Si-wei, Jin Wei

Abstract:

CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.

Keywords: Characterization, Adsorption, Crystal violet, Bentonite, BTEA, CTMA

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Authors: P. C. Tewari, Parveen Kumar

Abstract:

The paper describes the availability analysis of milling system of a rice milling plant using probabilistic approach. The subsystems under study are special purpose machines. The availability analysis of the system is carried out to determine the effect of failure and repair rates of each subsystem on overall performance (i.e. steady state availability) of system concerned. Further, on the basis of effect of repair rates on the system availability, maintenance repair priorities have been suggested. The problem is formulated using Markov Birth-Death process taking exponential distribution for probable failures and repair rates. The first order differential equations associated with transition diagram are developed by using mnemonic rule. These equations are solved using normalizing conditions and recursive method to drive out the steady state availability expression of the system. The findings of the paper are presented and discussed with the plant personnel to adopt a suitable maintenance policy to increase the productivity of the rice milling plant.

Keywords: Markov process, milling system, availability modeling, rice milling plant.

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Authors: Lambros V. Skarlas, Grigorios N. Beligiannis, Efstratios F. Georgopoulos, Adam V. Adamopoulos

Abstract:

The aim of this contribution is to present a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network is being used in order to exhibit a subset of the dynamics of the electrical behavior of the human heart. The proposed model can also be used, when integrated, as a diagnostic tool of the human heart system. What makes this approach unique is the fact that every model is being developed from physiological measurements of an individual. This kind of approach is very difficult to apply successfully in many modeling problems, because of the complexity and entropy of the free variables describing the complex system. Differences between the modeled variables and the variables of an individual, measured at specific moments, can be used for diagnostic purposes. The sensor fusion used in order to optimize the utilization of biomedical sensors is another point that this paper focuses on. Sensor fusion has been known for its advantages in applications such as control and diagnostics of mechanical and chemical processes.

Keywords: Artificial Neural Networks, Diagnostic System, Health Condition Modeling Tool, Heart Diagnostics Model, Heart Electricity Model.

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Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

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In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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Authors: Kang Won Lee, Jung Won Lee

Abstract:

Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: Betweenness centrality, correlation coefficient, power-law distribution, Korea traffic data base.

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Authors: Mohamed K. Watfa, Khaled Abdel Naby, Chetan Govind Bhatia

Abstract:

With the exponential rise in the number of multimedia applications available, the best-effort service provided by the Internet today is insufficient. Researchers have been working on new architectures like the Next Generation Network (NGN) which, by definition, will ensure Quality of Service (QoS) in an all-IP based network [1]. For this approach to become a reality, reservation of bandwidth is required per application per user. WiMAX (Worldwide Interoperability for Microwave Access) is a wireless communication technology which has predefined levels of QoS which can be provided to the user [4]. IPv6 has been created as the successor for IPv4 and resolves issues like the availability of IP addresses and QoS. This paper provides a design to use the power of WiMAX as an NSP (Network Service Provider) for NGN using IPv6. The use of the Traffic Class (TC) field and the Flow Label (FL) field of IPv6 has been explained for making QoS requests and grants [6], [7]. Using these fields, the processing time is reduced and routing is simplified. Also, we define the functioning of the ASN gateway and the NGN gateway (NGNG) which are edge node interfaces in the NGNWiMAX design. These gateways ensure QoS management through built in functions and by certain physical resources and networking capabilities.

Keywords: WiMAX, NGN, QoS, IPv6, Flow Label, ASNGateway

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Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

Abstract:

Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: Production line, layout planning, complexity measurement, optimization, mass customization.

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Authors: C. Ardil

Abstract:

The paper presents a multiple criteria decision making analysis process to determine the most suitable regional aircraft type according to a set of evaluation criteria. The main purpose of this study is to use different decision making methods to determine the most suitable regional aircraft for aviation operators. In this context, the nine regional aircraft types were analyzed using multiple criteria decision making analysis methods. Preference analysis for reference ideal solution (PARIS) was used in regional aircraft selection process. The findings of the proposed model show that the ranking results of the multiple criteria decision making models are consistent with each other, and the proposed method is efficient, and the results are valid. Finally, the Embraer E195-E2 model regional aircraft is chosen as the most suitable aircraft type.

Keywords: aircraft, regional aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

Abstract:

In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: Breast cancer, compartmental modeling, 177Lu, dosimetry.

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Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

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There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: Chlorodifluoromethane (HCFC-142b), ozone (O3), least squares method, regression models.

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Authors: Harpreet Kaur, Sudipta Majumdar

Abstract:

In this paper a method for image dehazing is proposed in lifting wavelet transform domain. Lifting Daubechies (D4) wavelet has been used to obtain the approximate image and detail images.  As the haze is contained in low frequency part, only the approximate image is used for further processing. This region is processed by dehazing algorithm based on dark channel prior (DCP). The dehazed approximate image is then recombined with the detail images using inverse lifting wavelet transform. Implementation of lifting wavelet transform has the advantage of auxiliary memory saving, fast implementation and simplicity. Also, the proposed method deals with near white scene problem, blue horizon issue and localized light sources in a way to enhance image quality and makes the algorithm robust. Simulation results present improvement in terms of visual quality, parameters such as root mean square (RMS) contrast, structural similarity index (SSIM), entropy and execution time.

Keywords: Dark channel prior, image dehazing, lifting wavelet transform.

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Authors: K. Nirmala Devi, V. Murali Bhaskaran

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The exponential growth of social media arouses much attention on public opinion information. The online forums, blogs, micro blogs are proving to be extremely valuable resources and are having bulk volume of information. However, most of the social media data is unstructured and semi structured form. So that it is more difficult to decipher automatically. Therefore, it is very much essential to understand and analyze those data for making a right decision. The online forums hotspot detection is a promising research field in the web mining and it guides to motivate the user to take right decision in right time. The proposed system consist of a novel approach to detect a hotspot forum for any given time period. It uses aging theory to find the hot terms and E-K-means for detecting the hotspot forum. Experimental results demonstrate that the proposed approach outperforms k-means for detecting the hotspot forums with the improved accuracy.

Keywords: Hotspot forums, Micro blog, Blog, Sentiment Analysis, Opinion Mining, Social media, Twitter, Web mining.

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Authors: T. S. Myers, J. Trevathan

Abstract:

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany

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Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.

Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification

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Authors: J. Berčík, A. Mravcová, J. Gálová, K. Neomániová

Abstract:

In an era when everything is increasingly digital, consumers are always looking for new options in solutions to their everyday needs. In this context, mobile apps are developing at an exponential pace. One of the fastest growing segments of mobile technologies is, obviously, e-commerce. It can be predicted that mobile commerce will record nearly three times the global growth of e-commerce across all platforms, which indicates its importance in the given segment. The current coronavirus pandemic is also changing many of the existing paradigms both socially, economically, and technologically, which has a major impact on changing consumer behavior and the emphasis on simplification and clarity of mobile solutions. This is the area that User Experience (UX) and User Interface (UI) designers deal with. Their task is to design a sufficiently attractive and interesting solution that will be available on all mobile devices and at the same time will be easy enough for the customer/visitor to get to the destination or to get the necessary information in a few clicks. The basis for changes in UX design can now be obtained not only through online analytical tools, but also through neuromarketing, especially in the case of mobile devices. The paper highlights possibilities for testing UX design applications on mobile devices using a special platform that combines a stationary eye camera (eye tracking) and facial analysis (facial coding).

Keywords: Emotions, mobile design, user experience, visual attention.

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

Abstract:

Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: EMG, feature extraction, muscle status, pedaling exercise, relaxation segment.

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Authors: Abdul Rashid Husain, Mohamad Noh Ahmad, Abdul Halim Mohd. Yatim

Abstract:

In this paper, stabilization of an Active Magnetic Bearing (AMB) system with varying rotor speed using Sliding Mode Control (SMC) technique is considered. The gyroscopic effect inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Also, transformation of the AMB dynamic model into a new class of uncertain system shows that this gyroscopic effect lies in the mismatched part of the system matrix. Moreover, the current gain parameter is allowed to be varied in a known bound as an uncertainty in the input matrix. SMC design method is proposed in which the sufficient condition that guarantees the global exponential stability of the reduced-order system is represented in Linear Matrix Inequality (LMI). Then, a new chattering-free control law is established such that the system states are driven to reach the switching surface and stay on it thereafter. The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.

Keywords: Active Magnetic Bearing (AMB), Sliding ModeControl (SMC), Linear Matrix Inequality (LMI), mismatcheduncertainty.

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain and how various stakeholders will interact with the system.

Keywords: Internet of Things, IoT, blockchain, data integrity, authentication, data privacy.

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Authors: Yue-Tzu Yang, Hsiang-Wen Tang, Jian-Zhang Yin, Chao-Han Wu

Abstract:

Three-dimensional incompressible turbulent fluid flow and heat transfer of pin fin heat sinks using air as a cooling fluid are numerically studied in this study. Two different kinds of pin fins are compared in the thermal performance, including circular and square cross sections, both are in-line and staggered arrangements. The turbulent governing equations are solved using a control-volume- based finite-difference method. Subsequently, numerical computations are performed with the realizable k - ԑ turbulence for the parameters studied, the fin height H, fin diameter D, and Reynolds number (Re) in the range of 7 ≤ H ≤ 10, 0.75 ≤ D ≤ 2, 2000 ≤ Re ≤ 126000 respectively. The numerical results are validated with available experimental data in the literature and good agreement has been found. It indicates that circular pin fins are streamlined in comparing with the square pin fins, the pressure drop is small than that of square pin fins, and heat transfer is not as good as the square pin fins. The thermal performance of the staggered pin fins is better than that of in-line pin fins because the staggered arrangements produce large disturbance. Both in-line and staggered arrangements show the same behavior for thermal resistance, pressure drop, and the entropy generation.

Keywords: Pin-fin, heat sinks, simulations, turbulent flow.

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cécile Donzé

Abstract:

Multiple Sclerosis (MS) is a disease which affects the central nervous system and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. 40 volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and 2 types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: Balance, multiple sclerosis, nonlinear analysis, postural sway.

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Authors: Johann Barbier, Eric Filiol, Kichenakoumar Mayoura

Abstract:

We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.

Keywords: Compressed frequency domain, Fisher discriminant, specific JPEG steganalysis.

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