Search results for: configurational entropy

Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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Authors: Sumandeep Kaur, Allam Srinivasa Rao, Mula Jayasimhadri

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In recent years, rare earth (RE) ions doped inorganic luminescent materials are seeking great attention due to their excellent physical and chemical properties. These materials offer high thermal and chemical stability and exhibit good luminescence properties due to the presence of RE ions. The luminescent properties of these materials are attributed to their intra-configurational f-f transitions in RE ions. A series of Tb³⁺ doped calcium aluminozincate has been synthesized via sol-gel method. The structural and morphological studies have been carried out by recording X-ray diffraction patterns and SEM image. The luminescent spectra have been recorded for a comprehensive study of their luminescence properties. The XRD profile reveals the single-phase orthorhombic crystal structure with an average crystallite size of 65 nm as calculated by using DebyeScherrer equation. The SEM image exhibits completely random, irregular morphology of micron size particles of the prepared samples. The optimization of luminescence has been carried out by varying the dopant Tb³⁺ concentration within the range from 0.5 to 2.0 mol%. The as-synthesized phosphors exhibit intense emission at 544 nm pumped at 478 nm excitation wavelength. The optimized Tb³⁺ concentration has been found to be 1.0 mol% in the present host lattice. The decay curves show bi-exponential fitting for the as-synthesized phosphor. The colorimetric studies show green emission with CIE coordinates (0.334, 0.647) lying in green region for the optimized Tb³⁺ concentration. This report reveals the potential utility of Tb³⁺ doped calcium aluminozincate phosphors for display and solid-state lighting devices.

Keywords: concentration quenching, phosphor, photoluminescence, XRD

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Authors: Malay K. Pramanik

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In recent years, climate change has become a major threat and has been widely documented in the geographic distribution of many plant species. However, the impacts of climate change on the distribution of ecologically vulnerable medicinal species remain largely unknown. The identification of a suitable habitat for a species under climate change scenario is a significant step towards the mitigation of biodiversity decline. The study, therefore, aims to predict the impact of current, and future climatic scenarios on the distribution of the threatened Garcinia indica across the northern Western Ghats using Maximum Entropy (MaxEnt) modelling. The future projections were made for the year 2050 and 2070 with all Representative Concentration Pathways (RCPs) scenario (2.6, 4.5, 6.0, and 8.5) using 56 species occurrence data, and 19 bioclimatic predictors from the BCC-CSM1.1 model of the Intergovernmental Panel for Climate Change’s (IPCC) 5th assessment. The bioclimatic variables were minimised to a smaller number of variables after a multicollinearity test, and their contributions were assessed using jackknife test. The AUC value of 0.956 ± 0.023 indicates that the model performs with excellent accuracy. The study identified that temperature seasonality (39.5 ± 3.1%), isothermality (19.2 ± 1.6%), and annual precipitation (12.7 ± 1.7%) would be the major influencing variables in the current and future distribution. The model predicted 10.5% (19318.7 sq. km) of the study area as moderately to very highly suitable, while 82.60% (151904 sq. km) of the study area was identified as ‘unsuitable’ or ‘very low suitable’. Our predictions of climate change impact on habitat suitability suggest that there will be a drastic reduction in the suitability by 5.29% and 5.69% under RCP 8.5 for 2050 and 2070, respectively. Finally, the results signify that the model might be an effective tool for biodiversity protection, ecosystem management, and species re-habitation planning under future climate change scenarios.

Keywords: Garcinia Indica, maximum entropy modelling, climate change, MaxEnt, Western Ghats, medicinal plants

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Authors: Gurcharan Singh Buttar

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It has been discovered that although these two areas, statistics, and information theory, are independent in their nature, they can be combined to create applications in multidisciplinary mathematics. This is due to the fact that where in the field of statistics, statistical parameters (measures) play an essential role in reference to the population (distribution) under investigation. Information measure is crucial in the study of ambiguity, assortment, and unpredictability present in an array of phenomena. The following communication is a link between the two, and it has been demonstrated that the well-known conventional statistical measures can be used as a measure of information.

Keywords: probability distribution, entropy, concavity, symmetry, variance, central tendency

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Authors: Parveen Kumar

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This article discusses institute information resources. Information, in its most restricted technical sense, is a sequence of symbols that can be interpreted as message information can be recorded as signs, or transmitted as signals. Information is any kind of event that affects the state of a dynamic system. Conceptually, information is the message being conveyed. This concept has numerous other meanings in different contexts. Moreover, the concept of information is closely related to notions of constraint, communication, control, data, form, instruction, knowledge, meaning, mental stimulus, pattern, perception, representation, and especially entropy.

Keywords: institutions, information institutions, information services for mission-oriented institute, pattern

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Authors: Andrey Egorov

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A product of the specific Lagrangian and the entropy factor is defined. Its positive definiteness is stated for the proper coupling constant. The passage from statistical mechanics to quantum field theory is performed by Wick rotation. The Green function (a convolution of the spectral amplitude and the propagator) is positive. Masses of quasiparticles are computed as residues. The role of the zeta derivative at zeta zeros is then highlighted, and the correspondent low bound is obtained.

Keywords: mass gap, positive definite kernels, quantum fields, Riemann zeta zeros

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Authors: Jun Ying Lin, Tzu Hsiang Yen, Cha'o Kuang Chen

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Nowadays, the great majority believe that there is great potentiality in hydrogen storage alloy storing hydrogen by physical and chemical absorption. However, the hydrogen storage alloy is limited by high operation temperature. Scientists find that adding transition elements can improve the properties of hydrogen storage alloy. In this research, outstanding improvements of kinetic and thermal properties are given by the addition of Palladium and Titanium hydride to Magnesium-based hydrogen storage alloy. Magnesium-based alloy is the main material, into which TiH2 / Pd are added separately. Following that, materials are milled by a Planetary Ball Miller at 650 rpm. TGA/DSC and PCT measure the capacity, spending time and temperature of abs/des-orption. Additionally, SEM and XRD analyze the structures and components of material. It is clearly shown that Pd is beneficial to kinetic properties. 2MgH2-0.1Pd has the highest capacity of all the alloys listed, approximately 5.5 wt%. Secondly, there are not any new Ti-related compounds found from XRD analysis. Thus, TiH2, considered as the catalyst, leads to the condition of 2MgH2-TiH2 and 2MgH2-TiH2-0.1Pd efficiently absorbing hydrogen in low temperature. 2MgH2-TiH2 can reach roughly 3.0 wt% in 82.4 minutes at 50°C and 8 minutes at 100°C, while2MgH2-TiH2-0.1Pd can reach 2.0 wt% in 400 minutes at 50°C and in 48 minutes at 100°C. The lowest temperature of 2MgH2-0.1Pd and 2MgH2-TiH2 is similar (320°C), otherwise the lowest temperature of 2MgH2-TiH2-0.1Pd decrease by 20°C. From XRD, it can be observed that PdTi2 and Pd3Ti are produced by mechanical alloying when adding Pd as well as TiH2 into MgH2. Due to the synergistic effects between Pd and TiH2, 2MgH2-TiH2-0.1Pd owns the lowest dehydrogenation temperature. Furthermore, the Pressure-Composition-Temperature (PCT) curve of 2MgH2-TiH2-0.1Pd is measured at different temperature, 370°C, 350°C, 320°C and 300°C separately. The plateau pressure is given form the PCT curves above. In accordance to different plateau pressures, enthalpy and entropy in the Van’t Hoff equation can be solved. In 2MgH2-TiH2-0.1Pd, the enthalpy is 74.9 KJ/mol and the entropy is 122.9 J/mol. Activation means that hydrogen storage alloy undergoes repeat abs/des-orpting processes. It plays an important role in the abs/des-orption. Activation shortens the abs/des-orption time because of the increase in surface area. From SEM, it is clear that the grain size and surface become smaller and rougher

Keywords: hydrogen storage materials, magnesium hydride, abs-/des-orption performance, Plateau pressure

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Authors: Pouneh Soleimaninejadian, Chengyu Yang

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In this paper, we use data on Household Income and Expenditure survey of Statistics Centre of Iran, conducted from 2005-2014, to calculate several inequality measures and to estimate the effects of Iran’s targeted subsidy reform act on consumption and income inequality. We first calculate Gini coefficients for income and consumption in order to study the relation between the two and also the effects of subsidy reform. Results show that consumption inequality has not been always mirroring changes in income inequality. However, both Gini coefficients indicate that subsidy reform caused improvement in inequality. Then we calculate Generalized Entropy Index based on consumption and income for years before and after the Subsidy Reform Act of 2010 in order to have a closer look into the changes in internal structure of inequality after subsidy reforms. We find that the improvement in income inequality is mostly caused by the decrease in inequality of lower income individuals. At the same time consumption inequality has been decreased as a result of more equal consumption in both lower and higher income groups. Moreover, the increase in Engle coefficient after the subsidy reform shows that a bigger portion of income is allocated to consumption on food which is a sign of lower living standard in general. This increase in Engle coefficient is due to rise in inflation rate and relative increase in price of food which partially is another consequence of subsidy reform. We have conducted some experiments on effect of subsidy payments and possible effects of change on distribution pattern and amount of cash subsidy payments on income inequality. Result of the effect of cash payments on income inequality shows that it leads to a definite decrease in income inequality and had a bigger share in improvement of rural areas compared to those of urban households. We also examine the possible effect of constant payments on the increasing income inequality for years after 2011. We conclude that reduction in value of payments as a result of inflation plays an important role regardless of the fact that there may be other reasons. We finally experiment with alternative allocations of transfers while keeping the total amount of cash transfers constant or make it smaller through eliminating three higher deciles from the cash payment program, the result shows that income equality would be improved significantly.

Keywords: consumption inequality, generalized entropy index, income inequality, Irans subsidy reform

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: P. Sathyakala, G. Sai Sundara Krishnan

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The objective of this paper is to derive an exergy model for a solar water heater with honey comb structure in order to identify the element which has larger irreversibility in the system. This will help us in finding the means to reduce the wasted work potential so that the overall efficiency of the system can be improved by finding the ways to reduce those wastages.

Keywords: exergy, energy balance, entropy balance, work potential, degradation, honey comb, flat plate collector

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Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: Zahira Belkacemi

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One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. In this study, we used maximum-entropy niche modeling (Maxent) to predict the current and future distribution of Anthus pratensis using climatic variables. The results showed that the species would not be highly affected by the climate change in shifting its distribution; however, the results of this study should be improved by taking into account other predictors, and that the NATURA 2000 protected sites will be efficient at 42% in protecting the species.

Keywords: anthus pratensis, climate change, Europe, species distribution model

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Authors: Ahmad Absetan, Mahdi Nooshyar

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The importance map is an image-based measure and is a core part of the resizing algorithm. Importance measures include image gradients, saliency and entropy, as well as high level cues such as face detectors, motion detectors and more. In this work we proposed a new method to calculate the importance map, the importance map is generated automatically using a novel combination of image edge density and Harel saliency measurement. Experiments of different type images demonstrate that our method effectively detects prominent areas can be used in image resizing applications to aware important areas while preserving image quality.

Keywords: content-aware image resizing, visual saliency, edge density, image warping

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Authors: Hazem M. Al-Mofleh

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In this paper, a new four-parameter univariate continuous distribution called the Normal-Generalized Hyperbolic Secant Distribution (NGHS) is defined and studied. Some general and structural distributional properties are investigated and discussed, including: central and non-central n-th moments and incomplete moments, quantile and generating functions, hazard function, Rényi and Shannon entropies, shapes: skewed right, skewed left, and symmetric, modality regions: unimodal and bimodal, maximum likelihood (MLE) estimators for the parameters. Finally, two real data sets are used to demonstrate empirically its flexibility and prove the strength of the new distribution.

Keywords: bimodality, estimation, hazard function, moments, Shannon’s entropy

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Manouchehr Amiri

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This article introduces a general notion of physical bit information that is compatible with the basics of quantum mechanics and incorporates the Shannon entropy as a special case. This notion of physical information leads to the Binary data matrix model (BDM), which predicts the basic results of quantum mechanics, general relativity, and black hole thermodynamics. The compatibility of the model with holographic, information conservation, and Landauer’s principles are investigated. After deriving the “Bit Information principle” as a consequence of BDM, the fundamental equations of Planck, De Broglie, Beckenstein, and mass-energy equivalence are derived.

Keywords: physical theory of information, binary data matrix model, Shannon information theory, bit information principle

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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

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This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

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Authors: Xiujing Chen, Thammananya Sakcharoen, Wilailuk Niyommaneerat

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China's tourism industry is in a state of shock and recovery, although COVID-19 has brought great impact and challenges to the tourism industry. The theory of sustainable development originates from the contradiction of increasing awareness of environmental protection and the pursuit of economic interests. The sustainable development of tourism should consider social, economic, and environmental factors and develop tourism in a planned and targeted way from the overall situation. Guilin is one of the popular tourist cities in China. However, there exist several problems in Guilin tourism, such as low quality of scenic spot construction and low efficiency of tourism resource development. Due to its unwell-managed, Guilin's tourism industry is facing problems such as supply and demand crowding pressure for tourists. According to the data from 2009 to 2019, there is a change in the degree of sustainable development of Guilin tourism. This research aimed to evaluate the sustainable development state of Guilin tourism using the DPSIR (driving force/pressure/state/impact/response) framework and to provide suggestions and recommendations for sustainable development in Guilin. An improved TOPSIS (technology for order preference by similarity to an ideal solution) model based on the entropy weights relationship is applied to the quantitative analysis and to analyze the mechanisms of sustainable development of tourism in Guilin. The DPSIR framework organizes indicators into sub-five categories: of which twenty-eight indicators related to sustainable aspects of Guilin tourism are classified. The study analyzed and summarized the economic, social, and ecological effects generated by tourism development in Guilin from 2009-2019. The results show that the conversion rate of tourism development in Guilin into regional economic benefits is more efficient than that into social benefits. Thus, tourism development is an important driving force of Guilin's economic growth. In addition, the study also analyzed the static weights of 28 relevant indicators of sustainable development of tourism in Guilin and ranked them from largest to smallest. Then it was found that the economic and social factors related to tourism revenue occupy the highest weight, which means that the economic and social development of Guilin can influence the sustainable development of Guilin tourism to a greater extent. Therefore, there is a two-way causal relationship between tourism development and economic growth in Guilin. At the same time, ecological development-related indicators also have relatively large weights, so ecological and environmental resources also have a great influence on the sustainable development of Guilin tourism.

Keywords: DPSIR framework, entropy weights analysis, sustainable development of tourism, TOPSIS analysis

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Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi

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in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.

Keywords: image encryption, logistic map, fibonacci matrix, grayscale images

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Authors: Reza Mokhtari Malek Abadi, Mohsen Saghaei, Fatemeh Iman

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This paper investigates the indices of a creative city in Isfahan. Its main aim is to evaluate quantitative status of the creative city indices in Isfahan city, analyze the dispersion and distribution of these indices in Isfahan city. Concerning these, this study tries to analyze the creative city indices in fifteen area of Isfahan through secondary data, questionnaire, TOPSIS model, Shannon entropy and SPSS. Based on this, the fifteen areas of Isfahan city have been ranked with 12 factors of creative city indices. The results of studies show that fifteen areas of Isfahan city are not equally benefiting from creative indices and there is much difference between the areas of Isfahan city.

Keywords: grading, creative city, creative city evaluation indicators, regional planning model

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: A. A. Azab

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In this work, Sm0.6Sr0.4CoxMn1-xO3 (x=0, 0.1, 0.2 and 0.3) was synthesized by sol-gel method for magnetocaloric effect (MCE) applications. XRD analysis confirmed formation of the required orthorhombic phase of perovskite, and there is crystallographic phase transition as a result of substitution. Maxwell-Wagner interfacial polarisation and Koops phenomenological theory were used to investigate and analyze the temperature and frequency dependency of the dielectric permittivity. The phase transition from the ferromagnetic to the paramagnetic state was demonstrated to be second order. Based on the isothermal magnetization curves obtained at various temperatures, the magnetic entropy change was calculated. A magnetocaloric effect (MCE) over a wide temperature range was studied by determining DSM and the relative cooling power (RCP).

Keywords: magnetocaloric effect, pperovskite, magnetic phase transition, dielectric permittivity

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Authors: Rossana Mancini

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The charm of a ruin colonised by wild plants and flowers is part of Western culture. The relationship between ruins and vegetation involves a wide range of different fields of research. During the first phase of the research the most important writings and projects about this argument were investigated, to understand how the perception of the co-existence of ruins and vegetation has changed over time and to investigate the various different approaches that these different fields have adopted when tackling this issue. The paper presents some practical examples of projects carried out from the early 1900s on. The major result is that specifically regards conservation, the best attitude is the management of change, an inevitable process when it comes to the co-existence of ruins and nature and, particularly, ruins and vegetation. Limiting ourselves to adopting measures designed to stop, or rather slow down, the increasing level of entropy (and therefore disorder) may not be enough.

Keywords: ruins, vegetation, conservation, archaeology, architecture

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Authors: M. Khundadze, V. Varazashvili, N. Lejava, R. Jorbenadze

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Phase transitions of cerium and neodymium are investigated by using high-temperature scanning calorimeter (HT-1500 Seteram). For cerium two types of transformation are detected: at 350-372 K - hexagonal close packing (hcp) - face-centered cubic lattice (fcc) transition, and at 880-960K the face-centered cubic lattice (fcc) transformation into body-centered cubic lattice (bcc). For neodymium changing of hexagonal close packing (hcp) into the body-centered cubic lattice (bcc) is detected at 1093-1113K. The thermal characteristics of transitions – enthalpy, entropy, temperature domains – are reported.

Keywords: cerium, calorimetry, enthalpy of phase transitions, neodymium

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Authors: Baljit Singh Khehra, Jagreeti Kaur

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In this paper, steganographic strategy is used to hide the text file inside an image. To increase the storage limit, predictive coding is utilized to implant information. In the proposed plan, one can exchange secure information by means of predictive coding methodology. The predictive coding produces high stego-image. The pixels are utilized to insert mystery information in it. The proposed information concealing plan is powerful as contrasted with the existing methodologies. By applying this strategy, a provision helps clients to productively conceal the information. Entropy, standard deviation, mean square error and peak signal noise ratio are the parameters used to evaluate the proposed methodology. The results of proposed approach are quite promising.

Keywords: cryptography, steganography, reversible image, predictive coding

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Authors: Michael Tupý, Dagmar Měřínská, Alice Tesaříková-Svobodová, Christian Carrot, Caroline Pillon, Vít Petránek

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The mechanical properties of blends consisting of plasticized poly(vinyl butyral) (PVB) and plasticized poly(vinyl chloride) (PVC) are studied, in order to evaluate the possibility of using recycled PVB waste derived from windshields. PVC was plasticized with 38% of diisononyl phthalate (DINP), while PVB was plasticized with 28% of triethylene glycol, bis(2-ethylhexanoate) (3GO). The optimal process conditions for the PVB/PVC blend in 1:1 ratio were determined. Entropy was used in order to theoretically predict the blends miscibility. The PVB content of each blend composition used was ranging from zero to 100%. Tensile strength and strain were tested. In addition, a comparison between recycled and original PVB, used as constituents of the blend, was performed.

Keywords: poly(vinyl butyral), poly(vinyl chloride), windshield, polymer waste, mechanical properties

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

Abstract:

Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

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