Search results for: classical reception

Authors: Mamoun S. Ideis, Zein Salah

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Virtual Rehabilitation (VR) refers to using Virtual Reality’s hardware and simulations as means of exercising tools to rehabilitate patients in need. These patients will undergo their treatment exercises while playing different computer games, which helps achieve greater motivation for patients undergoing their therapeutic exercises. Virtual Rehabilitation systems adopt computer games as part of the treatment therapy. In this paper, we present a preliminary proposal to using adaptive computer games in Virtual Rehabilitation therapy. We also present some tips in designing those adaptive computer games by using different machine learning algorithms in order to create a personalized experience for each patient, which in turn, increases the potential benefits of the treatment that each patient receives. Furthermore, we propose a method of comparing the results of treatment using the adaptive computer games with the results of using static and classical computer games.

Keywords: virtual rehabilitation, physiotherapy, adaptive computer games, post-stroke, game design

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Authors: Parham Bakhtiari

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The essence of Musical Impressionism is best captured in the compositions of Claude Debussy and Maurice Ravel. These two important individuals represent the core of this art form, with their piano compositions remaining significant, impactful, and commonly performed in contemporary times. Their piano works reflected a revolutionary compositional style that strayed from classical romanticism and drew heavy inspiration from Symbolist poets and Asian arts. Additionally, numerous technical applications are commonly utilized to exemplify the principles of impressionism style by composers who did not frequently use them in prior eras, resulting in effectively evoking impressionistic images through diverse sonorities. The goal of this study is to showcase the range of impressionistic elements and compositional techniques, such as dissonances, pentatonic and whole-tone scales, parallel movements, and polytonality, through an examination of their piano compositions.

Keywords: music, impressionism, Debussy, ravel, piano, composition

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Authors: Mohammad Tahmasebipour, Hosein Salarpour

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Micro cantilevers are one of the components used in the manufacture of micro-electromechanical systems. Epoxy microcantilevers have a variety of applications in the manufacture of micro-sensors and micro-actuators. In this paper, the Timoshenko Micro cantilever was statically and dynamically analyzed using the finite element method. First, all boundary conditions and initial conditions governing micro cantilevers were considered. The effect of size on the deflection, angle of rotation, natural frequencies, and mode shapes were then analyzed and evaluated under different frequencies. It was observed that an increased micro cantilever thickness reduces the deflection, rotation, and resonant frequency. A good agreement was observed between our results and those obtained by the couple stress theory, the classical theory, and the strain gradient elasticity theory.

Keywords: microcantilever, microsensor; epoxy, dynamic behavior, static behavior, finite element method

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Authors: Elijah Cavan

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In Major League Sports (MLB, NBA, NHL, NFL), it is the Front Office Staff (FOS) who make decisions about who plays for their respective team. The FOS bear the brunt of the responsibility for acquiring players through drafting, trading and signing players in free agency while typically contesting with maximum roster salary constraints. The players themselves are volatile assets of these teams- their value fluctuates with age and performance. A simple comparison can be made when viewing players as assets. The problem here is similar to that of optimizing your investment portfolio. The The goal is ultimately to maximize your periodic returns while tolerating a fixed risk (degree of uncertainty/ potential loss). Each franchise may value assets differently, and some may only tolerate lower risk levels- these are examples of factors that introduce additional constraints into the model. In this talk, we will detail the mathematical formulation of this problem as a constrained optimization problem- which can be solved with classical machine learning methods but is also well posed as a problem to be solved on quantum computers

Keywords: optimization, financial mathematics, sports analytics, simulated annealing

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Authors: M. Linek, P. Nita

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In the previous airfield construction industry, pavements made of reinforced concrete have been used very rarely; however, the necessity to use this type of pavements in an emergency situations justifies the need reference to this issue. The paper concerns the problem of airfield pavement dimensioning made of reinforced concrete and the evaluation of selected dimensioning methods of reinforced concrete slabs intended for airfield pavements. Analysis of slabs dimensioning, according to classical method of limit states has been performed and it has been compared to results obtained in case of methods complying with Eurocode 2 guidelines. Basis of an analysis was a concrete slab of class C35/45 with reinforcement, located in tension zone. Steel bars of 16.0 mm have been used as slab reinforcement. According to comparative analysis of obtained results, conclusions were reached regarding application legitimacy of the discussed methods and their design advantages.

Keywords: rainforced concrete, cement concrete, airport pavements, dimensioning

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Authors: Cheng Xu, Rui Zhong

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Utilizing a preregistered randomized experiment, this study explores the effects of anonymity and curated identity on trust within the Metaverse. Participants were randomly assigned to different conditions of anonymity and identity curation and engaged in a series of tasks designed to mirror the complexities of trust in real-world social interactions. Trust was measured using the classical trust game, allowing for a nuanced understanding of how these factors interact and influence trust. The findings reveal that higher levels of anonymity negatively impact trust, while identity curation can moderate this effect. Mechanism analysis uncovers how anonymity influences perceived reciprocity and group cohesion, and how curation can moderate these relationships. The results demonstrate a nuanced interaction between anonymity and trust, with variations across different curation levels. These insights provide a multifaceted understanding of trust within virtual environments, contributing valuable knowledge to the design, policy-making, and ethical considerations of the Metaverse

Keywords: metaverse, anonymity, curated identity, social behavior, trust

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Authors: Mike Tsionas

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The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

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Authors: Theddeus T. Akano, Omotayo A. Fakinlede

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The modelling of physical phenomena, such as the earth’s free oscillations, the vibration of strings, the interaction of atomic particles, or the steady state flow in a bar give rise to Sturm-Liouville (SL) eigenvalue problems. The boundary applications of some systems like the convection-diffusion equation, electromagnetic and heat transfer problems requires the combination of Dirichlet and Neumann boundary conditions. Hence, the incorporation of Robin boundary condition in the analyses of Sturm-Liouville problem. This paper deals with the computation of the eigenvalues and eigenfunction of generalized Sturm-Liouville problems with Robin boundary condition using the finite element method. Numerical solutions of classical Sturm–Liouville problems are presented. The results show an agreement with the exact solution. High results precision is achieved with higher number of elements.

Keywords: Sturm-Liouville problem, Robin boundary condition, finite element method, eigenvalue problems

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Authors: Ziyad Motala

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It is often proclaimed by leasers in Muslim majority countries that Islamic Law does not permit dissent against a ruler. This paper will evaluate and discuss freedom of speech and dissent as found in concrete prophetic examples during the time of the Prophet Muhammad. It will further look at the examples and practices during the time of the four Noble Caliphs, the immediate successors to the Prophet Muhammad. It will argue that the positivist position of absolute obedience to a ruler is inconsistent with the prophetic tradition. The examples of the Prophet and his immediate four successors (whose lessons Sunni Islam considers to be a source of Islamic Law) demonstrates among the earliest example of freedom of speech and dissent in human history. That tradition frowned upon an inert and uninvolved citizenry. It will conclude with lessons for modern day Muslim majority countries arguing with empirical evidence that freedom of speech, dissent and the right to be governed by consensus versus coercion are fundamental requisites of Islamic law.

Keywords: islamic law, demoracy, freedom of speech, right to dissent

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Authors: Hong Kai, Zhong Jun Jie, Chen Lin Qi, Wang Chen Guang

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There are inefficient global scheduling parallelism and local scheduling parallelism prone to processor starvation in current scheduling algorithms. Regarding this issue, this paper proposed a load-aware queue partitioning scheduling strategy by first allocating the queues according to the number of processor cores, calculating the load factor to specify the load queue capacity, and it assigned the awaiting nodes to the appropriate perceptual queues through the precursor nodes and the communication computation overhead. At the same time, real-time computation of the load factor could effectively prevent the processor from being starved for a long time. Experimental comparison with two classical algorithms shows that there is a certain improvement in both performance metrics of scheduling length and task speedup ratio.

Keywords: load-aware, scheduling algorithm, perceptual queue, heterogeneous multi-core

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Authors: B. Manikandan, A. Vijayaprabhu

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The conservative reversible gates are used to designed reversible sequential circuits. The sequential circuits are flip-flops and latches. The conservative logic gates are Feynman, Toffoli, and Fredkin. The design of two vectors testable sequential circuits based on conservative logic gates. All sequential circuit based on conservative logic gates can be tested for classical unidirectional stuck-at faults using only two test vectors. The two test vectors are all 1s, and all 0s. The designs of two vectors testable latches, master-slave flip-flops and double edge triggered (DET) flip-flops are presented. We also showed the application of the proposed approach toward 100% fault coverage for single missing/additional cell defect in the quantum- dot cellular automata (QCA) layout of the Fredkin gate. The conservative logic gates are in terms of complexity, speed, and area.

Keywords: DET, QCA, reversible logic gates, POS, SOP, latches, flip flops

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Sudhina H. K, Ravi M. Yadahalli, N. M. Shetti

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Reconfigurable antennas represent a recent innovation in antenna design that changes from classical fixed-form, Fixed function antennas to modifiable structures that can be adapted to fit the requirements of a time varying system. The ability to control the operating band of an antenna system can have many useful applications. Systems that operate in an acquire-and-track configuration would see a benefit from active bandwidth control. In such systems a wide band search mode is first employed to find a desired signal, Then a narrow band track mode is used to follow only that signal. Utilizing active antenna bandwidth control, A single antenna would function for both the wide band and narrow band configurations providing the rejection of unwanted signals with the antenna hardware. This ability to move a portion of the RF filtering out of the receiver and onto the antenna itself will also aid in reducing the complexity of the often expensive RF processing subsystems.

Keywords: designing methods, mems, stack, reconfigurable elements

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Authors: Aliyu Adamu, Fahrul Huyop, Roswanira Abdul Wahab, Mohd Shahir Shamsir

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Halogenated organic compounds occur in huge amount in biosphere. This is attributable to the diverse use of halogen-based compounds in the synthesis of various industrially important products. Halogenated compound is toxic and may persist in the environment, thereby causing serious health and environmental pollution problems. L-2-haloacid dehalogenases (EC 3.8.1.2) catalyse the specific cleavage of carbon-halogen bond in L-isomers of halogenated compounds, which consequently reverse the effects of environmental halogen-associated pollution. To enhance the efficiency and utility of these enzymes, this study investigates the catalytic amino acid residues and the molecular functional mechanism of DehL, by classical molecular dynamic simulations, MM-PBSA and ab initio fragments molecular orbital (FMO) calculations. The results of the study will serve as the basis for the molecular engineering of the enzyme.

Keywords: DehL, Functional mechanism, Catalytic residues, L-2-haloacid dehalogenase

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Authors: Basma Abdel Mohsen Al-Sheikh

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This study aimed to create textile designs inspired by Najdi Al-Sadu art, with the objective of highlighting Saudi identity and heritage. The research proposed clothing designs for women and children, utilizing textiles inspired by Najdi Al-Sadu art, and incorporated artificial intelligence techniques in the design process. The study employed a descriptive-analytical approach to describe Najdi Al-Sadu, and an experimental method involving the creation of textile designs inspired by Al-Sadu. The study sample consisted of 33 participants, including experts in the fashion and textile industry, fashion designers, lecturers, professors, and postgraduate students from King Abdulaziz University. A questionnaire was used as a tool to gather opinions regarding the proposed designs. The results demonstrated a clear acceptance of the designs inspired by Najdi Al-Sadu and incorporating artificial intelligence, with approval rates ranging from 22% to 81% across different designs. The study concluded that artificial intelligence applications have a significant impact on fashion design, particularly in the integration of Al-Sadu art. The findings also indicated a positive reception of the designs in terms of their aesthetic and functional aspects, although individual preferences led to some variations in opinions. The results highlighted a demand for designs that combine heritage and modern fashion, striking a balance between authenticity and contemporary style. The study recommended that designers continue to explore ways to integrate cultural heritage, such as Al-Sadu art, with contemporary design elements to achieve this balance. Furthermore, it emphasized the importance of enhancing the aesthetic and functional aspects of designs, taking into consideration the preferences of the target market and customer expectations. The effective utilization of artificial intelligence was also emphasized to improve design processes, expand creative possibilities, and foster innovation and authenticity.

Keywords: Najdi Al-Sadu art, artificial intelligence, women's and children's fashion, clothing designs

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Authors: Bohli Afef

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The fifth-generation (5G) wireless systems is featured by extreme densities of cell stations to overcome the higher future demand. Hence, interference management is a crucial challenge in 5G ultra-dense cellular networks. In contrast to the classical inter-cell interference coordination approach, which is no longer fit for the high density of cell-tiers, this paper proposes a novel virtual coordination based on the dynamic common cognitive monitor channel protocol to deal with the inter-cell interference issue. A tractable and flexible model for the coverage probability of a typical user is developed through the use of the stochastic geometry model. The analyses of the performance of the suggested protocol are illustrated both analytically and numerically in terms of coverage probability.

Keywords: ultra dense heterogeneous networks, dynamic common channel protocol, cognitive radio, stochastic geometry, coverage probability

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Dragos Ardeleanu, Silviu-Valentin Petre

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Written to satisfy the needs of Western powers, classical geopolitics bore the stint of Eurocentrism. Both Mackinder’s heartland and Nicholas Spykman’s rimland were intellectual creations set for the purpose of the Anglophone nations dealing with Eurasia. However, while today’s world is moving towards multipolarity, other emerging regional actors are following their own interests using a different geospatial map. Such is the case of Iran which has developed an engagement pattern in Africa, directed mostly towards costal states, in order to break the rimland grip of Arab states and also the international pressure established against Tehran’s nascent nuclear program. Capitalizing on literature review and analysing statements from key public figures, our paper argues that Iranian African geopolitics displays a dual message: on the one hand, it uses tiers-mondiste rhetoric to garner the support of different coastal African states and, on the other hand, it employs Shiism to gain a foothold in strategic parts of the black continent.

Keywords: African geopolitics, Iran, Shiism, tiers-mondisme

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Authors: Radovan Čobanović, Milica Rankov Šicar

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The meat is in the group of perishable food which can be spoiled very rapidly if stored at room temperature. Salting in combination with smoke is intended to extend shelf life, and also to form the specific taste, odor and color. The smoke do not affect only on taste and flavor of the product, it has a bactericidal and oxidative effect and that is the reason because smoked products are less susceptible to oxidation and decay processes. According to mentioned the goal of this study was to evaluate shelf life of smoked ham, which is stored in conditions of high temperature (+15 °C). For the purposes of this study analyzes were conducted on eight samples of smoked ham every 7th day from the day of reception until 21st day. During this period, smoked ham is subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analyzes (Listeria monocytogenes, Salmonella spp. and yeasts and molds) according to Serbian state regulation. All analyses were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11 290-1, Salmonella spp ISO 6579 and yeasts and molds ISO 21527-2. Results of sensory analysis of smoked ham indicating that the samples after the first seven days of storage showed visual changes at the surface in the form of allocations of salt, most likely due to the process of drying out the internal parts of the product. The sample, after fifteen days of storage had intensive exterior changes, but the taste was still acceptable. Between the fifteenth and twenty-first day of storage, there is an unacceptable change on the surface and inside of the product and the occurrence of molds and yeasts but neither one analyzed pathogen was found. Based on the obtained results it can be concluded that this type of product cannot be stored for more than seven days at an elevated temperature of +15°C because there are a visual changes that would certainly have influence on decision of customers when purchase of this product is concerned.

Keywords: sustainability, smoked meat products, food engineering, agricultural process engineering

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Authors: Galit Harel

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This article describes the long-term psychoanalytic psychotherapy of a young woman who had experienced trauma during her childhood. The details of the trauma were unknown, as all memory of the trauma had been repressed. Past trauma is analyzable through a prism of transference, dreaming and dreams, mental states, and thinking processes that offer an opportunity to explore and analyze the influence of both reality and fantasy on the patient. The presented case describes a therapeutic process that strives to discover hidden meanings through the unconscious system and illustrates the movement from unconscious to conscious during exploration of the patient’s personal trauma in treatment. The author discusses the importance of classical and contemporary psychoanalytic models of childhood sexual trauma through the discovery of manifest and latent content, unconscious fantasies, and actual events of trauma. It is suggested that the complexity of trauma is clarified by the tension between these models and by the inclusion of aspects of both of them for a complete understanding.

Keywords: dreams, psychoanalytic psychotherapy, thinking processes, transference, trauma

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Authors: Mousa Bani Baker, Raed Abendeh, Zaidoon Abu Salem, Hesham Ahmad

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This research paper was commissioned to discuss the Jordanian marble, which is a non-foliated metamorphic rock composed of recrystallized carbonate minerals, most commonly calcite or dolomite. Geologists use the term "marble" to refer to metamorphosed limestone; however, stonemasons use the term more broadly to encompass unmetamorphised limestone. Marble is commonly used for sculpture and as a building material. The marble has many uses; one of them is using the white marble that has been prized for its use in sculptures since classical times. This preference has to do with its softness, relative isotropy and homogeneity, and a relative resistance to shattering. Another use of it is the construction marble which is “a stone which is composed of calcite, dolomite or serpentine which is capable of taking a polish” Marble Institute of America. This report focuses most about the marble in Jordan and its properties: rock definition, physical properties, the marble occurrences in Jordan, types of Jordanian marble and their prices and test done on this marble.

Keywords: marble, metamorphic, non-foliated, compressive strength, recrystallized, Moh’s hardness, abrasion, absorption, modulus of rupture, porosity

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Authors: Safia Hocine, Djamil Aïssani

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Risk models, recently studied in the literature, are becoming increasingly complex. It is rare to find explicit analytical relations to calculate the ruin probability. Indeed, the stability issue occurs naturally in ruin theory, when parameters in risk cannot be estimated than with uncertainty. However, in most cases, there are no explicit formulas for the ruin probability. Hence, the interest to obtain explicit stability bounds for these probabilities in different risk models. In this paper, we interest to the stability bounds of the univariate classical risk model established using the regenerative processes approach. By adopting an algorithmic approach, we implement this approximation and determine numerically the bounds of ruin probability in the case of large claims (heavy-tailed distribution).

Keywords: heavy-tailed distribution, large claims, regenerative process, risk model, ruin probability, stability

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Jongsoo Lee

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From the beginning of the conquest, the Spanish missionaries promoted indigenous intellectuality to prove that indigenous people were capable of receiving Christian doctrine. To prove indigenous intellectuality, Spanish missionaries focused on the highly advanced and complex level of indigenous political, religious, moral, artistic, and cultural practices. In this context, they frequently compared the Aztecs with European gentiles such as Greeks and Romans. In the chronicles of the Spanish missionaries such as Bernardino de Sahagún, indigenous wise men (tlamatinime) appear as clear evidence of indigenous civility and capability. As the pagan Greek and Roman philosophers, orators, rhetoricians, theologians, and physicians known as wise men in European history were responsible for the advanced level of social systems, some Spanish missionaries tried to identify those types of people, tlamatinime, in Aztec society. This paper examines how the Spanish colonizers invented European-style wise men in Prehispanic Mexico.

Keywords: Aztec, indigenous tradition, prehispanic Mexico, wise men

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Authors: Melanie Francois, Gilles Caboche, Frederic Demoisson, Francois Maeght, Maria Paola Carpanese, Lionel Combemale, Pascal Briois

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Finding new clean, and efficient way for energy production is one of the actual global challenges. Advances in fuel cell technology have shown that, for few years, Protonic Ceramic Fuel Cell (PCFC) has attracted much attention in the field of new hydrogen energy thanks to their lower working temperature, possible higher efficiency, and better durability than classical SOFC. On the contrary of SOFC, where O²⁻ oxygen ion is the charge carrier, PCFC works with H⁺ proton as a charge carrier. Consequently, the lower activation energy of proton diffusion compared to the one of oxygen ion explains those benefits and allows PCFC to work in the 400-600°C temperature range. Doped-BaCeO₃ is currently the most chosen material for this application because of its high protonic conductivity; for example, BaCe₀.₉Y₀.₁O₃ δ exhibits a total conductivity of 1.5×10⁻² S.cm⁻¹ at 600°C in wet H₂. However, BaCeO₃ based perovskite has low stability in H₂O and/or CO₂ containing atmosphere, which limits their practical application. On the contrary, BaZrO₃ based perovskite exhibits good chemical stability but lower total conductivity than BaCeO₃ due to its larger grain boundary resistance. By substituting zirconium with 20% of yttrium, it is possible to achieve a total conductivity of 2.5×10⁻² S.cm⁻¹ at 600°C in wet H₂. However, the high refractory property of BaZr₀.₈Y₀.₂O₃-δ (noted BZY20) causes problems to obtain a dense membrane with large grains. Thereby, using a synthesis process that gives fine particles could allow better sinterability and thus decrease the number of grain boundaries leading to a higher total conductivity. In this work, BaZr₀.₈Y₀.₂O₃-δ have been synthesized by classical batch hydrothermal device and by a continuous hydrothermal device developed at ICB laboratory. The two variants of this process are able to work in supercritical conditions, leading to the formation of nanoparticles, which could be sintered at a lower temperature. The as-synthesized powder exhibits the right composition for the perovskite phase, impurities such as BaCO₃ and YO-OH were detected at very low concentration. Microstructural investigation and densification rate measurement showed that the addition of 1 wt% of ZnO as sintering aid and a sintering at 1550°C for 5 hours give high densified electrolyte material. Furthermore, it is necessary to heat the synthesized powder prior to the sintering to prevent the formation of secondary phases. It is assumed that this thermal treatment homogenizes the crystal structure of the powder and reduces the number of defects into the bulk grains. Electrochemical impedance spectroscopy investigations in various atmospheres and a large range of temperature (200-700°C) were then performed on sintered samples, and the protonic conductivity of BZY20 has been highlighted. Further experiments on half-cell, NiO-BZY20 as anode and BZY20 as electrolyte, are in progress.

Keywords: hydrothermal synthesis, impedance measurement, Y-doped BaZrO₃, proton conductor

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Authors: Sadaf Nawaz, Adnan Ahmed Khan, Asad Mahmood, Chaudhary Farrukh Javed

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Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.

Keywords: cognitive radio, energy detector, periodogram, spectrum sensing

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: Samia Kouki

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Solving NP-hard combinatorial optimization problems by exact search methods, such as Branch-and-Bound, may degenerate to complete enumeration. For that reason, exact approaches limit us to solve only small or moderate size problem instances, due to the exponential increase in CPU time when problem size increases. One of the most promising ways to reduce significantly the computational burden of sequential versions of Branch-and-Bound is to design parallel versions of these algorithms which employ several processors. This paper describes a parallel Branch-and-Bound algorithm called GALB for solving the classical permutation flowshop scheduling problem as well as its implementation on a Grid computing infrastructure. The experimental study of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.

Keywords: grid computing, permutation flow shop problem, branch and bound, load balancing

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Authors: M. Kazou, A. Gavriil, O. Kalagkatsi, T. Paschos, E. Tsakalidou

Abstract:

Kopanisti cheese is a Greek soft Protected Designation of Origin (PDO) cheese made of raw cow, sheep or goat milk, or mixtures of them, with similar organoleptic characteristics to that of Roquefort cheese. Traditional manufacturing of Kopanisti cheese is limited in small-scale dairies, without the addition of starter cultures. Instead, an amount of over-mature Kopanisti cheese, called Mana Kopanisti, is used to initiate ripening. Therefore, the selection of proper starter cultures and the understanding of the contribution of various microbial groups to its overall quality is crucial for the production of a high-quality final product with standardized organoleptic and physicochemical characteristics. Taking the above into account, the aim of the present study was the investigation of Kopanisti cheese microbiota and its role in cheese quality. For this purpose, four different types of Kopanisti were produced in triplicates, all with pasteurized cow milk, with the addition of (A) the typical mesophilic species Lactococcus lactis and Lactobacillus paracasei used as starters in the production of soft spread cheeses, (B) strains of Lactobacillus acidipiscis and Lactobacillus rennini previously isolated from Kopanisti and Mana Kopanisti, (C) all the species from (A) and (B) as inoculum, and finally (D) the species from (A) and Mana Kopanisti. Physicochemical and microbiological analysis was performed for milk and cheese samples during ripening. Enumeration was performed for major groups of lactic acid bacteria (LAB), total mesophilic bacteria, yeasts as well as hygiene indicator microorganisms. Bacterial isolates from all the different LAB groups, apart from enterococci, alongside yeasts isolates, were initially grouped using repetitive sequence-based polymerase chain reaction (rep-PCR) and then identified at the species level using 16S rRNA gene and internal transcribed spacer (ITS) DNA region sequencing, respectively. Sensory evaluation was also performed for final cheese samples at the end of the ripening period (35 days). Based on the results of the classical microbiological analysis, the average counts of the total mesophilic bacteria and LAB, apart from enterococci, ranged between 7 and 10 log colony forming unit (CFU) g⁻¹, phychrotrophic bacteria, and yeast extract glucose chloramphenicol (YGC) isolates between 4 and 8 log CFU g⁻¹, while coliforms and enterococci up to 2 log CFU g⁻¹ throughout ripening in cheese samples A, C and D. In contrast, in cheese sample B, the average counts of the total mesophilic bacteria and LAB, apart from enterococci, phychrotrophic bacteria, and YGC isolates ranged between 0 and 10 log CFU g⁻¹ and coliforms and enterococci up to 2 log CFU g⁻¹. Although the microbial counts were not that different among samples, identification of the bacterial and yeasts isolates revealed the complex microbial community structure present in each cheese sample. Differences in the physicochemical characteristics among the cheese samples were also observed, with pH ranging from 4.3 to 5.3 and moisture from 49.6 to 58.0 % in the final cheese products. Interestingly, the sensory evaluation also revealed differences among samples, with cheese sample B ranking first based on the total score. Overall, the combination of these analyses highlighted the impact of different starter cultures on the Kopanisti microbiota as well as on the physicochemical and sensory characteristics of the final product.

Keywords: Kopanisti cheese, microbiota, classical microbiological analysis, physicochemical analysis

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