Search results for: variable precision rough sets theory

Authors: Philippe Gugler

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Goal of the study: The concept of competitiveness has been addressed by economic theorists and policymakers for several hundreds of years, with both groups trying to understand the drivers of economic prosperity and social welfare. The goal of this contribution is to address the major useful theoretical contributions that permit to identify the main drivers of a territory’s competitiveness. We first present the major contributions found in the classical and neo-classical theories. Then, we concentrate on two majors schools providing significant thoughts on the competitiveness of locations: the Economic Geography (EG) School and the International Business (IB) School. Methodology: The study is based on a literature review of the classical and neo-classical theories, on the economic geography theories and on the international business theories. This literature review establishes links between these theoretical mainstreams. This work is based on the academic framework establishing a meaningful literature review aimed to respond to our research question and to develop further research in this field. Results: The classical and neo-classical pioneering theories provide initial insights that territories are different and that these differences explain the discrepancies in their levels of prosperity and standards of living. These theories emphasized different factors impacting the level and the growth of productivity in a given area and therefore the degree of their competitiveness. However, these theories are not sufficient to more precisely identify the drivers and enablers of location competitiveness and to explain, in particular, the factors that drive the creation of economic activities, the expansion of economic activities, the creation of new firms and the attraction of foreign firms. Prosperity is due to economic activities created by firms. Therefore, we need more theoretical insights to scrutinize the competitive advantages of territories or, in other words, their ability to offer the best conditions that enable economic agents to achieve higher rates of productivity in open markets. Two major theories provide, to a large extent, the needed insights: the economic geography theory and the international business theory. The economic geography studies scrutinized in this study from Marshall to Porter, aim to explain the drivers of the concentration of specific industries and activities in specific locations. These activity agglomerations may be due to the creation of new enterprises, the expansion of existing firms, and the attraction of firms located elsewhere. Regarding this last possibility, the international business (IB) theories focus on the comparative advantages of locations as far as multinational enterprises (MNEs) strategies are concerned. According to international business theory, the comparative advantages of a location serves firms not only by exploiting their ownership advantages (mostly as far as market seeking, resource seeking and efficiency seeking investments are concerned) but also by augmenting and/or creating new ownership advantages (strategic asset seeking investments). The impact of a location on the competitiveness of firms is considered from both sides: the MNE’s home country and the MNE’s host country.

Keywords: competitiveness, economic geography, international business, attractiveness of businesses

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Authors: Ahmed F. Ghanem, Marwa I. Wahba, Asmaa N. El-Dein, Mohamed A. EL-Raey, Ghada E. A. Awad

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Numerous attempts are being performed in order to formulate suitable packaging materials for the meat products. However, to the best of our knowledge, the incorporation of the free hibiscus extract or its microcapsules in the pure polyvinyl alcohol (PVA) matrix as packaging materials for the meats is seldom reported. Therefore, this study aims at the protection of the aqueous crude extract of the hibiscus flowers utilizing the spry drying encapsulation technique. Results of the Fourier transform infrared (FTIR), the scanning electron microscope (SEM), and the particle size analyzer confirmed the successful formation of the assembled capsules via strong interactions, the spherical rough microparticles, and the particle size of ~ 235 nm, respectively. Also, the obtained microcapsules enjoy higher thermal stability than the free extract. Then, the obtained spray-dried particles were incorporated into the casting solution of the pure PVA film with a concentration of 10 wt. %. The segregated free-standing composite films were investigated, compared to the neat matrix, with several characterization techniques such as FTIR, SEM, thermal gravimetric analysis (TGA), mechanical tester, contact angle, water vapor permeability, and oxygen transmission. The results demonstrated variations in the physicochemical properties of the PVA film after the inclusion of the free and the extract microcapsules. Moreover, biological studies emphasized the biocidal potential of the hybrid films against the microorganisms contaminating the meat. Specifically, the microcapsules imparted not only antimicrobial but also antioxidant activities to the PVA matrix. Application of the prepared films on the real meat samples displayed a low bacterial growth with a slight increase in the pH over the storage time which continued up to 10 days at 4 oC, as further evidence to the meat safety. Moreover, the colors of the films did not significantly changed except after 21 days indicating the spoilage of the meat samples. No doubt, the dual-functional of the prepared composite films pave the way towards combined active and smart food packaging applications. This would play a vital role in the food hygiene, including also the quality control and the assurance.

Keywords: PVA, hibiscus, extraction, encapsulation, active packaging, smart and intelligent packaging, meat spoilage

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Hassan Ibrahim, Moses Anayo Mbah

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The idempotent generators in a finite full transformation and the digraph of full transformation semi group have been an interesting area of research in group theory. In this work, it characterized some idempotent elements in full transformation semigroup T_n by counting the strongly connected and disconnected digraphs, and also the weakly and unilaterally connected digraphs. The order for those digraphs was further obtained in T_n.

Keywords: digraphs, indempotent, semigroup, transformation

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Authors: Cruz Queen Allysa Rose, Bautista Joymeeh Anne, Lantoria Kaye, Barretto Katya Louise

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The study presents the preferences of passengers on the quality of service provided by the two airline check-in methods currently present in airports-traditional counter check-in and common-use self-service kiosks. Since a study has shown that airlines perceive self-service kiosks alone are sufficient enough to ensure adequate services and customer satisfaction, and in contrast, agents and passengers stated that it alone is not enough and that human interaction is essential. In reference with former studies that established opposing ideas about the choice of the more favorable airline check-in method to employ, it is the purpose of this study to present a recommendation that shall somehow fill-in the gap between the conflicting ideas by means of comparing the perceived quality of service through the RATER model. Furthermore, this study discusses the major competencies present in each method which are supported by the theories–FIRO Theory of Needs upholding the importance of inclusion, control and affection, and the Queueing Theory which points out the discipline of passengers and the length of the queue line as important factors affecting quality service. The findings of the study were based on the data gathered by the researchers from selected Thomasian third year and fourth year college students currently enrolled in the first semester of the academic year 2014-2015, who have already experienced both airline check-in methods through the implication of a stratified probability sampling. The statistical treatments applied in order to interpret the data were mean, frequency, standard deviation, t-test, logistic regression and chi-square test. The final point of the study revealed that there is a greater effect in passenger preference concerning the satisfaction experienced in common-use self-service kiosks in comparison with the application of the traditional counter check-in.

Keywords: traditional counter check-in, common-use self-service Kiosks, airline check-in methods

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Lorenzo Bonoldi, Gianluca Memoli, Abdelhalim Azbaid El Ouahabi

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In this paper, a series of ring-shaped attenuators utilizing Helmholtz and quarter wavelength resonators in variable, fixed, and combined configurations have been manufactured using a 3D printer. We illustrate possible uses by incorporating such devices into musical instruments (e.g. in acoustic guitar sound holes) and audio speakers with a view to controlling such devices tonal emissions without electronic equalization systems. Numerical investigations into the transmission loss values of these ring-shaped attenuators using finite element method simulations (COMSOL Multiphysics) have been presented in the frequency range of 100– 1000 Hz. We compare such results for each attenuator model with experimental measurements using different driving sources such as white noise, a maximum-length sequence (MLS), square and sine sweep pulses, and point scans in the frequency domain. Finally, we present a preliminary discussion on the comparison of numerical and experimental results.

Keywords: equaliser, metamaterials, musical, instruments

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Authors: Wei Zhao

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The pandemic crisis disrupted normal classroom practices so that the constraints of the traditional practice became apparent. This turns out to be new opportunities for technology-based learning and teaching. However, how the technology supports the preschool teachers go through this sudden crisis and how preschool teachers conceived of the use of technology, appropriate and design technological artifacts as a mediator of knowledge construction in order to suit young children’s literacy level are rarely explored. This study addresses these issues by looking at the influence of a web-supported teacher community on changes/shifts in preschool teachers’ epistemological beliefs and practices. This teachers’ professional development community was formulated before the pandemic time and developed virtually throughout the home-based learning caused by Covid-19. It served as a virtual and asynchronous community for those teachers to collaboratively plan for and conduct online lessons using the knowledge-building approach for the purpose of sustaining children’s learning curiosity and opening up new learning opportunities during the lock-down period. The knowledge-building approach helps to increase teachers’ collective responsibility to collaboratively work on shared educational goals in the teacher community and awareness of noticing new ideas or innovations in their classroom. Based on the data collected across five months during and after the lock-down period and the activity theory, results show a dynamic interplay between the evolution of the community culture, the growth of teacher community and teachers’ identity transformation and professional development. Technology is useful in this regard not only because it transforms the geographical distance and new gathering guidelines after the outbreak of pandemic into new ways of communal communication and collaboration. More importantly, while teachers selected, monitored and adapted the technology, it acts as a catalyst for changes in teachers’ old teaching practices and epistemological dispositions.

Keywords: activity theory, changes in epistemology and practice, knowledge building, web-based teachers’ professional development community

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Authors: Rasime Kalkan, Emine Ikbal Atli, Ali Arslantaş, Muhsin Özdemir, Sevilhan Artan

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Glioblastoma (WHO grade IV), is the malignant form of brain tumor, the genetic background of the GBM is highly variable. The tumor mass of a GBM is multilayered and every tumor layer shows distinct characteristics with a different cell population. The treatment planning of GBM should be focused on the tumor genetic characteristics. We screened primary glioblastoma multiforme (GBM) in a population-based study for MGMT and RARβ methylation and IDH1 mutation correlated them with clinical data and treatment. There was no correlation between MGMT-promoter methylation and overall survival. The overall survival time of the patients with methylated RARβ was statically (OS;p<0,05) significance between the patients who were treated with chemotherapy and radiotherapy. Here we showed the status of IDH1 gene associatied with younger age. We demonstrated that the together with MGMT gene the RARβ gene should be used as a potantial treatment decision marker for GBMs.

Keywords: RARβ, primary glioblastoma multiforme, methylation, MGMT

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Mikiyas Yonas Fufa

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- Maternal and child health service was a critical service which may have many risks and many maternal and newborn mortality is there if not managed properly. In middle and low countries like Ethiopia accessibility and quality of MCH service is low. During this COVID-19 Pandemics even the pervious access of MCH will be decreased. So many pregnant mothers are not attending their ANC, Delivery and other services in the hospital because they think they are more vulnerable to COVID-19. This condition may make an increase of maternal and neonatal morbidity and mortality. The innovation is an idea (which is development of a mobile app prepared by Maternity Foundation organization that focuses on midwifery care. The app has detailed videos on danger signs in pregnancy and procedures during labor and delivery). By telling this to clients it is planned to explore the perception, attitude towards this innovation and barriers to accepting it. What is planned to study is to explore the perceptions and barriers towards using of new idea which is innovation of mHealth on the MCH services. It is planned to interview the pregnant mothers who come for ANC at health facility and mothers who are absent from their appointment of services. In this way it is planned to explore how the mothers accept this idea and what barriers make them from accepting this idea. This is a phenomenological qualitative study and application of diffusion of innovation theory on the MCH services. The participant will be selected by using quota sampling methods for the mother who are interviewed at hospitals and snowball/quota sampling methods for the mother who are absent from their appointment/visits. Sample size of the participant depends on the saturation of data/idea. Each participant will be interviewed based the open-ended questionnaires, and the interview will be recorded then transcribed then finally analyzed by the open code 4.03. Beneficiaries: The federal ministry of health prepares them to develop the apk of mhealth. Health professionals in the MCH will have a low overload and accessibility and the quality of care will be increased during COVID-19 Different collaborations will be participated and promote the mother to enjoy the new idea.

Keywords: COVID-19, m health, MCH, diffusion of innovation

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Authors: Naveed Ul Hassan, Bilal Aziz, Maryam Mushtaq, Imran Ameen Khan

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Equity risk premium (ERP) is the stock return in excess of risk free return. Even though it is an essential topic of finance but still there is no common consensus upon its forecasting. For forecasting ERP, apart from the macroeconomic variables attention is devoted to technical indicators as well. For this purpose, set of 14 technical and 14 macro-economic variables is selected and all forecasts are generated based on a standard predictive regression framework, where ERP is regressed on a constant and a lag of a macroeconomic variable or technical indicator. The comparative results showed that technical indicators provide better indications about ERP estimates as compared to macro-economic variables. The relative strength of ERP predictability is also investigated by using National Bureau of Economic Research (NBER) data of business cycle expansion and recessions and found that ERP predictability is more than twice for recessions as compared to expansions.

Keywords: equity risk premium, forecasting, macroeconomic indicators, technical indicators

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Authors: Paolo Castaldo, Bruno Palazzo, Laura Lodato

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This study deals with the seizure effects of friction pendulum (FP) bearings on the seismic reliability of a 3D base-isolated nonlinear structural system, designed according to Italian seismic code (NTC08). The isolated system consists in a 3D reinforced concrete superstructure, a r.c. substructure and the FP devices, described by employing a velocity dependent model. The seismic input uncertainty is considered as a random variable relevant to the problem, by employing a set of natural seismic records selected in compliance with L’Aquila (Italy) seismic hazard as provided from NTC08. Several non-linear dynamic analyses considering the three components of each ground motion have been performed with the aim to evaluate the seismic reliability of the superstructure, substructure, and isolation level, also taking into account the seizure event of the isolation devices. Finally, a design solution aimed at increasing the seismic robustness of the base-isolated systems with FPS is analyzed.

Keywords: FP devices, seismic reliability, seismic robustness, seizure

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Authors: Seif Naoui, Lassaad Latrach, Ali Gharsallah

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This paper is specialized to highlight the method of miniaturization and improvement the patch antenna by using the complementary metamaterial. This method is presented by a simple technique is composed a structure of patch antenna integrated in its surface a cell of complementary split ring resonator. This resonator is placed at the middle of the radiating patch in parallel with the transmission line and with a variable angle of orientation. The objective is to find the ultimate angle where the best results are obtained on improving the characteristics of the considered antenna. This motif widespread at the traceability applications by wireless communication for RFID technology at the operation frequency 2.45 GHz. Our contribution is based on studies empirical often presented in this article. All simulation results were made by the CST Microwave Studio.

Keywords: complimentary split ring resonators, computer simulation technology microwave studio, metamaterials patch antennas, microstrip patch antenna, radio frequency identification

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Authors: Yunhui Sun, Qingquan Liu, Xiaoliang Wang

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Dense granular flows widely exist in geological flows such as debris flow, landslide, or sheet flow, where both the interparticle and solid-liquid interactions are important to modify the flow. So, a two-phase approach with both phases correctly modelled is important for a better investigation of the saturated granular flows. However, a proper closure model covering a wide range of flowing states for the solid phase is still lacking. This study first employs a chute flow experiment based on the refractive index matching method, which makes it possible to obtain internal flow information such as velocity, shear rate, granular fluctuation, and volume fraction. The granular stress is obtained based on a steady assumption. The kinetic theory is found to describe the stress dependence on the flow state well. More importantly, the granular rheology is found to be frictionally dominated under weak shear and collisionally dominated under strong shear. The results presented thus provide direct experimental evidence on a possible frictional-collisional closure model for the granular phase. The data indicates that both frictional stresses exist over a wide range of the volume fraction, though traditional theory believes it vanishes below a critical volume fraction. Based on the findings, a two-phase model is used to simulate the chute flow. Both phases are modelled as continuum media, and the inter-phase interactions, such as drag force and pressure gradient force, are considered. The frictional-collisional model is used for the closure of the solid phase stress. The profiles of the kinematic properties agree well with the experiments. This model is further used to simulate immersed granular collapse, which is unsteady in nature, to study the applicability of this model, which is derived from steady flow.

Keywords: closure model, collision, friction, granular flow, two-phase model

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Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

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Authors: Yingchen Yang

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In the present work, development of a new vertical-axis unidirectional wave rotor is reported. The wave rotor is a key component of a wave energy converter (WEC), which harvests energy from ocean waves. Differing from the huge majority of WEC designs that perform reciprocating motions (heaving up and down, swaying back and forth, etc.), our wave rotor performs unidirectional rotation about a vertical axis when directly exposed in waves. The unidirectional feature of the rotor makes the rotor respond well in a wide range of the wave frequency. The vertical axis arrangement of the rotor makes the rotor insensitive to the wave propagation direction. The rotor employs blades with a cross-section in an airfoil shape and a span curled into a semi-oval shape. Two sets of blades, with one nested inside the other, constitute the rotor. In waves, water particles perform an omnidirectional motion that constantly changes in both spatial and temporal domains. The blade nesting permits a compact rotor configuration that ‘sees’ a relatively uniform local flow in the spatial domain. The rotor was experimentally tested in simulated waves in a wave flume under various conditions. The testing results show a promising unidirectional rotor that is capable of extracting energy from waves at a capture width ratio of 0.08 to 0.15, depending on detailed wave conditions.

Keywords: unidirectional, vertical axis, wave energy converter, wave rotor

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Authors: Khodr Fakih

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The Ombudsman is a procedural mechanism that provides a different approach of dispute resolution. The ombudsman primarily deals with specific grievances from the public against governmental injustice and misconduct. The ombudsman theory is considered an important instrument to any democratic government. This is true since it improves the transparency of the governmental activities in a world in which executive power are rising. Many countries have adopted the concept of Ombudsman but under different terminologies. This paper will provide the different types of Ombudsman and the common activities/processes of fulfilling their mandates.

Keywords: administration, citizens, government, mediator, ombudsman, presidential mediator

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Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Aya Effat, Ossama A. Hosny, Elkhayam M. Dorra

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Estimating costs is a crucial step in construction management and should be completed at the beginning of every project to establish the project's budget. The precision of the cost estimate plays a significant role in the success of construction projects as it allows project managers to effectively manage the project's costs. Site overhead costs constitute a significant portion of construction project budgets, necessitating accurate prediction and management. These costs are influenced by a multitude of factors, requiring a thorough examination and analysis to understand their relative importance and impact. Thus, the main aim of this research is to enhance the contractor’s ability to predict and manage site overheads by identifying and analyzing the main factors influencing the site overheads costs in the Egyptian construction industry. Through a comprehensive literature review, key factors were first identified and subsequently validated using a thorough comparative analysis of data from 55 real-life construction projects. Through this comparative analysis, the relationship between each factor and site overheads percentage as well as each site overheads subcategory and each project construction phase was identified and examined. Furthermore, correlation analysis was done to check for multicollinearity and identify factors with the highest impact. The findings of this research offer valuable insights into the key drivers of site overhead costs in the Egyptian construction industry. By understanding these factors, construction professionals can make informed decisions regarding the estimation and management of site overhead costs.

Keywords: comparative analysis, cost estimation, construction management, site overheads

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Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

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Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Rika Uchida

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Claude Debussy's piano works can be divided into three categories in terms of style characteristics. The first category includes works which are strongly impressionistic, evoking a mood or an atmosphere, rather than making a direct, clear statement. These works often depict nature, and they are descriptive and sensitive in their character. Harmonic vocabulary is often complex, and the sense of tonality is often ambiguous in those works. Examples which belong to this category are ‘Clair de lune’ from Suite Bergamasque, Deux Arabesques, and ‘Reflets dans l'eau’ from Images Book 2. The second category shows little or no trace of impressionism. Works are not descriptive; rather, they are classical or absolute. Examples which belong to this category are Pour le Piano, ‘Hommage à Rameau’ and ‘Movement’ from Images Book 1 and Etudes. The third category can be called exotic. Debussy had a great interest in foreign lands such as the Far and Near East, and Spain. He employs pentatonic and quartal harmonies to describe the Orient, occasionally using the effect of the Javanese gamelan, which impressed him at the Paris Exhibition. His compositions in the Spanish style evoke the atmosphere of Spain. Though he borrowed some techniques from Spanish composers whom he knew, the tonal experimentation which occurs in these works sets them apart. Examples which belong to this category are ‘Pagodes’ and ‘la Soiree dans Grenade’ from Estampes, ‘la Puerta del Vino’ from Preludes Book 2.

Keywords: music, piano, Debussy, style

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Authors: Omotoyosi Bilikies Ilori, Adekunle Saheed Ajisebiyawo

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After the Second World War, there was an emergence of a new stage of capitalist globalization with its Neo-liberal ideology. There were global economic and political restructurings that affected third-world countries like Nigeria. Neo-liberalism is the driving force of globalization, which is the latest manifestation of imperialism that engenders endemic poverty in Nigeria. Poverty is severe and widespread in Nigeria. Poverty entails a situation where a person lives on less than one dollar per day and has no access to basic necessities of life. Poverty is inhuman and a breach of human rights. The Nigerian government initiated some strategies in the past to help in poverty reduction. Neo-liberalism manifested in the Third World, such as Nigeria, through the privatization of public enterprises, trade liberalization, and the rollback of the state investments in providing important social services. These main ideas of Neo-liberalism produced poverty in Nigeria and also encouraged the abandonment of the social contract between the government and the people. There is thus a gap in the provision of social services and subsidies for the masses, all of which Neo-liberal ideological positions contradict. This paper is a qualitative study which draws data from secondary sources. The theoretical framework is anchored on the market theory of capitalist globalization and public choice theory. The objectives of this study are to (i) examine the impacts of Neo-liberalism on poverty in Nigeria as a typical example of a Third World country and (ii) find out the effects of Neo-liberalism on the provision of social services and subsidies and employment. The findings from this study revealed that (i) the adoption of the Neo-liberal ideology by the Nigerian government has led to increased poverty and poor provision of social services and employment in Nigeria; and (ii) there is an increase in foreign debts which compounds poverty situation in Nigeria. This study makes the following recommendations: (i) Government should adopt strategies that are pro-poor to eradicate poverty; (ii) The Trade Unions and the masses should develop strategies to challenge Neo-liberalism and reject Neo-liberal ideology.

Keywords: neo-liberalism, poverty, employment, poverty reduction, structural adjustment programme

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Authors: Merouane Salhi, Mohamed Roudane, Abdelkader Kirad

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In this work, we present a new form of characteristics method, which is a technique for solving partial differential equations. Typically, it applies to first-order equations; the aim of this method is to reduce a partial differential equation to a family of ordinary differential equations along which the solution can be integrated from some initial data. This latter developed under the real gas theory, because when the thermal and the caloric imperfections of a gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with the gas parameters. The gas doesn’t stay perfect. Its state equation change and it becomes for a real gas. The presented equations of the characteristics remain valid whatever area or field of study. Here we need have inserted the developed Prandtl Meyer function in the mathematical system to find a new model when the effect of stagnation pressure is taken into account. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation, the thermodynamic parameters and the value of Prandtl Meyer function. However, with the assumptions that Berthelot’s state equation accounts for molecular size and intermolecular force effects, expressions are developed for analyzing the supersonic flow for thermally and calorically imperfect gas. The supersonic parameters depend directly on the stagnation parameters of the combustion chamber. The resolution has been made by the finite differences method using the corrector predictor algorithm. As results, the developed mathematical model used to design 2D minimum length nozzles under effect of the stagnation parameters of fluid flow. A comparison for air with the perfect gas PG and high temperature models on the one hand and our results by the real gas theory on the other of nozzles shapes and characteristics are made.

Keywords: numerical methods, nozzles design, real gas, stagnation parameters, supersonic expansion, the characteristics method

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Authors: Aisha Bano, Rizwan Nazir

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The present study aimed at exploring the impact of meaning in life on psychological well-being and stress among university students. Victor Frankl's paradigm provided the theoretical foundation for this study. A sample of 560 university students was drawn from Quaid-i-Azam University Islamabad. The sample was drawn using stratified random sampling technique. Data were collected using Existence Scale, Warwick-Edinburg Mental Well-Being Scale, and Stress Scale. Results of linear regression analysis reveals that high perception of meaning in life will lead to high psychological well-being and low stress among university students. Non-significant differences are found on meaning in life variable with regard to gender in the sample using t-test. Together these results suggest that meaning in life independent of gender, is a significant predictor of the levels of stress and psychological well-being being directly related to psychological well-being and inversely related to stress levels.

Keywords: existential meaning in life, psychological well-being, stress, students

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Authors: S. Visetpotjanakit, N. Nakkaew

Abstract:

Determination of ⁹⁰Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since ⁹⁰Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify ⁹⁰Y and Cherenkov counting using liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse ⁹⁰Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of ⁹⁰Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of ⁹⁰Sr determination in water and spruce needles samples using the same developed method.

Keywords: ALMERA proficiency test, Cerenkov counting, determination of 90Sr, environmental samples

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