Search results for: structural and statistical pattern recognition

Authors: D. V. S. Praneeth, V. R. Sankar Cheela, Brajesh Dubey

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Coal Combustion (CC) residues are the major by-products from thermal power plants. The disposal of ash on to land creates havoc to environment and humans. The leaching of the constituent elements pollutes ground water. Beneficiary use of coal combustion residues in structural components is being investigated as a part of this study. This application reduces stress on the convention materials in the construction industry. The present study involves determination of leaching parameters of the CC residues. Batch and column studies are performed based on Leaching Environmental Assessment Framework (LEAF) protocol. The column studies are conducted to simulate the real time percolation conditions in the field. The structural and environmental studies are performed to determine the usability of CC residues as bricks. The physical, chemical, geo environmental and mechanical properties of the alternate materials are investigated. Scanning electron microscopy (SEM), X-Ray Diffraction analysis (XRD), X-ray fluorescence (XRF) and Energy Dispersive X-ray Spectroscopy tests were conducted to determine the characteristics of CC residue ash and bricks.

Keywords: coal combustion residues, LEAF, leaching, SEM

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Authors: M. Abbasi

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A spillway structure is used to pass excess water and floods from upstream or upstream to downstream or tributary. The spillway is considered one of the most key members of the dam, and the failure of many dams is attributed to the inefficiency of their spillway. Weirs should be selected as strong, reliable and high-performance structures, and weirs should be ready for use in all conditions and able to drain the flood so that we do not witness many casualties and financial losses when a flood occurs. The purpose of this study is to simulate the flow pattern passing over the peak spillway in order to optimize and adjust the height of the spillway walls. In this research, the effect of the shape of the side wings on the flow pattern over the peak spillways of the Gotvand reservoir dam was simulated and modelled using Flow3D software. In this research, side wings with rounded walls with six different approach angles were used. In addition, the different value of H/Hd was used to check the effect of the tank head. The results showed that with the constant H/Hd ratio and the increase of the approach angle of the side wing, the flow depth first decreases and then increases. These changes were the opposite regarding the depth average speed of the flow and the depth average concentration of the air entering the flow. At the same time, with the constant angle of approach of the side wing and with the increase of H/Hd ratio, the flow depth increases. In general, a correct understanding of the operation of overflows and a correct design can significantly reduce construction costs and solve flooding problems.

Keywords: effect of the shape, gotvand reservoir dam, narrowing coefficients, supports of the gates

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Authors: Cuiyang Feng, Xu Tang, Yi Jin

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Coal is the most important primary energy source in China, which exerts a significant influence on the rapid economic growth. However, it makes the water resources to be a constraint on coal industry development, on account of the reverse geographical distribution between coal and water. To ease the pressure on water shortage, the ‘3 Red Lines’ water policies were announced by the Chinese government, and then ‘water for coal’ plan was added to that policies in 2013. This study utilized a structural path analysis (SPA) based on the multi-regional input-output table to quantify the virtual water flows caused by coal consumption in different stages. Results showed that the direct water input (the first stage) was the highest amount in all stages of coal consumption, accounting for approximately 30% of total virtual water content. Regional analysis demonstrated that virtual water trade alleviated the pressure on water use for coal consumption in water shortage areas, but the import of virtual water was not from the areas which are rich in water. Sectoral analysis indicated that the direct inputs from the sectors of ‘production and distribution of electric power and heat power’ and ‘Smelting and pressing of metals’ took up the major virtual water flows, while the sectors of ‘chemical industry’ and ‘manufacture of non-metallic mineral products’ importantly but indirectly consumed the water. With the population and economic growth in China, the water demand-and-supply gap in coal consumption would be more remarkable. In additional to water efficiency improvement measures, the central government should adjust the strategies of the virtual water trade to address local water scarcity issues. Water resource as the main constraints should be highly considered in coal policy to promote the sustainable development of the coal industry.

Keywords: coal consumption, multi-regional input-output model, structural path analysis, virtual water

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Authors: Azam Tabatabaee, Fereshteh Dastgoshadeh, Akram Tabatabaee

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This paper describes the use of by-products as adsorbents for removing heavy metals from aqueous effluent solutions. Products of almond skin, walnut shell, saw dust, rice bran and egg shell were evaluated as metal ion adsorbents in aqueous solutions. A comparative study was done with commercial adsorbents like ion exchange resins and activated carbon too. Batch experiments were investigated to determine the affinity of all of biomasses for, Cd(ΙΙ), Cr(ΙΙΙ), Ni(ΙΙ), and Pb(ΙΙ) metal ions at pH 5. The rate of metal ion removal in the synthetic wastewater by the biomass was evaluated by measuring final concentration of synthetic wastewater. At a concentration of metal ion (50 mg/L), egg shell adsorbed high levels (98.6 – 99.7%) of Pb(ΙΙ) and Cr(ΙΙΙ) and walnut shell adsorbed high levels (35.3 – 65.4%) of Ni(ΙΙ) and Cd(ΙΙ). In this study, it has been shown that by-products were excellent adsorbents for removal of toxic ions from wastewater with efficiency comparable to commercially available adsorbents, but at a reduced cost. Also statistical studies using Independent Sample t Test and ANOVA Oneway for statistical comparison between various elements adsorption showed that there isn’t a significant difference in some elements adsorption percentage by by-products and commercial adsorbents.

Keywords: adsorbents, heavy metals, commercial adsorbents, wastewater, by-products

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Authors: Laith K. Abbas, Xiaoting Rui, Pier Marzocca

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Aerospace systems, generally speaking, are inherently nonlinear. These nonlinearities may modify the behavior of the system. However, nonlinearities in an aeroelastic system can be divided into structural and aerodynamic. Structural nonlinearities can be subdivided into distributed and concentrated ones. Distributed nonlinearities are spread over the whole structure representing the characteristic of materials and large motions. Concentrated nonlinearities act locally, representing loose of attachments, worn hinges of control surfaces, and the presence of external stores. The concentrated nonlinearities can be approximated by one of the classical structural nonlinearities, namely, cubic, free-play and hysteresis, or by a combination of these, for example, a free-play and a cubic one. Compressibility, aerodynamic heating, separated flows and turbulence effects are important aspects that result in nonlinear aerodynamic behavior. An issue related to the low-speed flutter and its catastrophic/benign character represented by Limit Cycle Oscillation (LCO) of all-movable fin, as well to their control is addressed in the present work. To the approach of this issue: (1) Quasi-Steady (QS) Theory and Computational Fluid Dynamics (CFD) of subsonic flow are implemented, (2) Flutter motion equations of a two-dimensional typical section with cubic nonlinear stiffness in the pitching direction and free play gap are established, (3) Uncoupled bending/torsion frequencies of the selected fin are computed using recently developed Transfer Matrix Method of Multibody System Dynamics (MSTMM), and (4) Time simulations are carried out to study the bifurcation behavior of the aeroelastic system. The main objective of this study is to investigate how the LCO and chaotic behavior are influenced by the coupled aeroelastic nonlinearities and intend to implement a control capability enabling one to control both the flutter boundary and its character. By this way, it may expand the operational envelop of the aerospace vehicle without failure.

Keywords: aeroelasticity, CFD, MSTMM, flutter, freeplay, fin

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Authors: Brandtner-Hafner Martin

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Adhesives are increasingly being used in the construction sector. On the one hand, this concerns dowel reinforcements using chemical anchors. On the other hand, the sealing and repair of cracks in structural concrete components are still on the rise. In the field of bonding, the interface between the joined materials is the most critical area. Therefore, it is of immense importance to characterize and investigate this section sufficiently by fracture analysis. Since standardized mechanical test methods are not sufficiently capable of doing this, recourse is made to an innovative concept based on fracture energy. Therefore, a series of experimental tests were performed using the so-called GF-principle to study the interface bonding safety of adhesively bonded concrete joints. Several different structural adhesive systems based on epoxy, CA/A hybrid, PUR, MS polymer, dispersion, and acrylate were selected for bonding concrete substrates. The results show that stable crack propagation and prevention of uncontrolled failure in bonded concrete joints depend very much on the adhesive system used, and only fracture analytical evaluation methods can provide empirical information on this.

Keywords: interface bonding safety, adhesively bonded concrete joints, GF-principle, fracture analysis

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Authors: Mukhtar Raban

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Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Wenjin Zhu, Ian E. Jacobs, Henning Sirringhaus

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We have demonstrated a model system for the controlled incorporation of tie-chains into semicrystalline conjugated polymers using blends of different molecular weights that leads to a significant increase in electrical conductivity. Through careful assessment of the microstructural evolution upon tie chain incorporation we have demonstrated that no major changes in phase morphology or structural order in the crystalline domains occur and that the observed enhancement in electrical conductivity can only be explained consistently by tie chains facilitating the transport across grain boundaries between the crystalline domains. Here we studied the thermoelectric properties of aligned, ion exchange-doped ribbon phase PBTTT with blends of different molecular weight components. We demonstrate that in blended films higher electrical conductivities (up to 4810.1 S/cm), Seebeck coefficients and thermoelectric power factors of up to 172.6 μW m-1 K-2 can be achieved than in films with single component molecular weights. We investigate the underpinning thermoelectric transport physics, including structural and spectroscopic characterization, to better understand how controlled tie chain incorporation can be used to enhance the thermoelectric performance of aligned conjugated polymers.

Keywords: organic electronics, thermoelectrics, conjugated polymers, tie chain

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Authors: Maryam Kiani

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The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

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Authors: Nasreen Abdulmannan

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Fetal abnormalities are categorized as a structural abnormality, non-structural abnormality, or a combination of both. Fetal structural abnormalities (FSA) include, but are not limited, to Down syndrome, congenital diaphragmatic hernia, and cleft lip and palate. These abnormalities can be detected in the first weeks of pregnancy, which is almost around 9 - 20 weeks gestational. Etiological factors for FSA are unknown; however, transmitted genetic risk can be one of these factors. Consanguineous marriage often referred to as inbreeding, represents a significant risk factor for FSA due to the increased likelihood of deleterious genetic traits shared by both biological parents. In a country such as the Kingdom of Saudi Arabia (KSA), consanguineous marriage is high, which creates a significant risk of children being born with congenital abnormalities. Historically, the practice of consanguinity occurred commonly among European royalty. For example, Great Britain’s Queen Victoria married her German first cousin, Prince Albert of Coburg. Although a distant blood relationship, the United Kingdom’s Queen Elizabeth II married her cousin, Prince Philip of Greece and Denmark—both of them direct descendants of Queen Victoria. In Middle Eastern countries, a high incidence of consanguineous unions still exists, including in the KSA. Previous studies indicated that a significant gap exists in understanding the lived experiences of Saudi women dealing with an FSA-complicated pregnancy. Eleven participants were interviewed using a semi-structured interview format for this qualitative phenomenological study investigating the lived experiences of pregnant Saudi women carrying a child with FSA. This study explored the gaps in current literature regarding the lived experiences of pregnant Saudi women whose pregnancies were complicated by FSA. In addition, the researcher acquired knowledge about the available support and resources as well as the Saudi cultural perspective on FSA. This research explored the lived experiences of pregnant Saudi women utilizing Giorgi’s (2009) approach to data collection and data management. Findings for this study cover five major themes: (1) initial maternal reaction to the FSA diagnosis per ultrasound screening; (2) strengthening of the maternal relationship with God; (3) maternal concern for their child’s future; (4) feeling supported by their loved ones; and (5) lack of healthcare provider support and guidance. Future research in the KSA is needed to explore the network support for these mothers. This study recommended further clinical nursing research, nursing education, clinical practice, and healthcare policy/procedures to provide opportunities for improvement in nursing care and increase awareness in KSA society.

Keywords: fetal structural abnormalities, psychological distress, health provider, health care

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Pui-Lai To, Chechen Liao, Hen-Yi Huang

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Twenty years after Internet development, scholars have started to identify the negative impacts brought by the Internet. Overuse of Internet could develop Internet dependency and in turn cause addiction behavior. Therefore understanding the phenomenon of Internet addiction is important. With the joint efforts of experts and scholars, Internet addiction has been officially listed as a symptom that affects public health, and the diagnosis, causes and treatment of the symptom have also been explored. On the other hand, in the area of smartphone Internet usage, most studies are still focusing on the motivation factors of smartphone usage. Not much research has been done on smartphone Internet addiction. In view of the increasing adoption of smartphones, this paper is intended to find out whether smartphone Internet addiction exists in modern society or not. This study adopted the research methodology of online survey targeting users with smartphone Internet experience. A total of 434 effective samples were recovered. In terms of data analysis, Partial Least Square (PLS) in Structural Equation Modeling (SEM) is used for sample analysis and research model testing. Software chosen for statistical analysis is SPSS 20.0 for windows and SmartPLS 2.0. The research result successfully proved that smartphone users who access Internet service via smartphone could also develop smartphone Internet addiction. Factors including flow experience, depression, virtual social support, smartphone Internet affinity and maladaptive cognition all have significant and positive influence on smartphone Internet addiction. In the scenario of smartphone Internet use, descriptive norm has a positive and significant influence on perceived playfulness, while perceived playfulness also has a significant and positive influence on flow experience. Depression, on the other hand, is negatively influenced by actual social support and positive influenced by the virtual social support.

Keywords: internet addiction, smartphone usage, social support, perceived playfulness

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Sawsan J. Al-husseini, Talib A. Dosa

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Educational institutions are today facing increasing pressures due to economic, political and social upheaval. This is only exacerbated by the nature of education as an intangible good which relies upon the intellectual assets of the organisation, its staff. Top management support has been acknowledged as having a positive general influence on knowledge management and creativity. However, there is a lack of models linking top management support, knowledge sharing, and innovation within higher education institutions, in general within developing countries, and particularly in Iraq. This research sought to investigate the impact of top management support on innovation through the mediating role of knowledge sharing in Iraqi private HEIs. A quantitative approach was taken and 262 valid responses were collected to test the causal relationships between top management support, knowledge sharing, and innovation. Employing structural equation modelling with AMOS v.25, the research demonstrated that knowledge sharing plays a pivotal role in the relationship between top management support and innovation. The research has produced some guidelines for researchers as well as leaders, and provided evidence to support the use of knowledge sharing to increase innovation within the higher education environment in developing countries, particularly Iraq.

Keywords: top management support, knowledge sharing, innovation, structural equation modelling

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Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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Authors: Peter Shi

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Algorithmic trading is a rapidly expanding domain within quantitative finance, constituting a substantial portion of trading volumes in the US financial market. The demand for rigorous and robust mathematical theories underpinning these trading algorithms is ever-growing. In this study, the author establishes a new stock market model that integrates the Efficient Market Hypothesis and the statistical arbitrage. The model, for the first time, finds probabilistic relations between the rational price and the market price in terms of the conditional expectation. The theory consequently leads to a mathematical justification of the old market adage: buy-low and sell-high. The thresholds for “low” and “high” are precisely derived using a max-min operation on Bayes’s error. This explicit connection harmonizes the Efficient Market Hypothesis and Statistical Arbitrage, demonstrating their compatibility in explaining market dynamics. The amalgamation represents a pioneering contribution to quantitative finance. The study culminates in comprehensive numerical tests using historical market data, affirming that the “buy-low” and “sell-high” algorithm derived from this theory significantly outperforms the general market over the long term in four out of six distinct market environments.

Keywords: efficient market hypothesis, behavioral finance, Bayes' decision, algorithmic trading, risk control, stock market

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

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The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

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Authors: Monika Malik, Pooja Arora, Ruchi Sachdeva, Vishnampettai G. Ramachandran, Rahul Pal

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Apoptotic debris is believed to be the antigenic trigger in lupus. Whether such debris and autoantibodies induced in lupus-prone mice which specifically recognize its constituents can mediate differential effects on innate and humoral responses in such mice was assessed. The influence of apoptotic blebs and apoptotic cell-reactive monoclonal antibodies on phenotypic markers expressed on bone marrow-derived dendritic cells (BMDCs) and secreted cytokines were evaluated. Sera from lupus-prone and healthy mice immunized with the antibodies were analyzed for anti-self reactivity. Apoptotic blebs, as well as somatically-mutated IgG and non-mutated IgM apoptotic-cell reactive monoclonal antibodies, induced the preferential maturation of BMDCs derived from lupus-prone mice relative to BMDCs derived from healthy mice; antibody specificity and cell genotype both influenced the secretion of inflammatory cytokines. Immunization of lupus-prone mice with IgM and IgG antibodies led to hypergammaglobulinemia; elicited antibodies were self-reactive, and exhibited enhanced recognition of lupus-associated autoantigens (dsDNA, Ro60, RNP68, and Sm) in comparison with adjuvant-induced sera. While ‘natural’ IgM antibodies are believed to contribute to immune homeostasis, this study reveals that apoptotic cell-reactive IgM antibodies can promote inflammation and drive anti-self responses in lupus. Only in lupus-prone mice did immunization with IgG auto-antibodies enhance the kinetics of humoral anti-self responses, resulting in advanced-onset glomerulosclerosis. This study reveals that preferential innate and humoral recognition of the products of cell death in an autoimmune milieu influences the indices associated with lupus pathology.

Keywords: antigen spreading, apoptotic cell-reactive pathogenic IgG, and IgM autoantibodies, glomerulosclerosis, lupus

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Authors: S. Perera, T. R. Walsh, M. Solvang

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The structure-property relationships of calcium aluminosilicate (CAS) glass surfaces are of scientific and technological interest regarding dissolution phenomena. Molecular dynamics (MD) simulations can provide atomic-scale insights into the structure and properties of the CAS interfaces in vacuo as the first step to conducting computational dissolution studies on CAS surfaces. However, one limitation to date is that although the bulk properties of CAS glasses have been well studied by MD simulation, corresponding efforts on CAS surface properties are relatively few in number (both theoretical and experimental). Here, a systematic computational protocol to create CAS surfaces in vacuo is developed by evaluating the sensitivity of the resultant surface structure with respect to different factors. Factors such as the relative thickness of the surface layer, the relative thickness of the bulk region, the cooling rate, and the annealing schedule (time and temperature) are explored. Structural features such as ring size distribution, defect concentrations (five-coordinated aluminium (AlV), non-bridging oxygen (NBO), and tri-cluster oxygen (TBO)), and linkage distribution are identified as significant features in dissolution studies.

Keywords: MD simulation, CAS glasses, surface structure, structure-property, CAS interface

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Authors: Esther Van Andel, Stefanie C. Lange, Maarten M. J. Smulders, Han Zuilhof

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False outcomes of diagnostic tests are a major concern in medical health care. To improve the reliability of surface-based diagnostic tests, it is of crucial importance to diminish background signals that arise from the non-specific binding of biomolecules, a process called fouling. The aim is to create surfaces that repel all biomolecules except the molecule of interest. This can be achieved by incorporating antifouling protein repellent coatings in between the sensor surface and it’s recognition elements (e.g. antibodies, sugars, aptamers). Zwitterionic polymer brushes are considered excellent antifouling materials, however, to be able to bind the molecule of interest, the polymer brushes have to be functionalized and so far this was only achieved at the expense of either antifouling or binding capacity. To overcome this limitation, we combined both features into one single monomer: a zwitterionic sulfobetaine, ensuring antifouling capabilities, equipped with a clickable azide moiety which allows for further functionalization. By copolymerizing this monomer together with a standard sulfobetaine, the number of azides (and with that the number of recognition elements) can be tuned depending on the application. First, the clickable azido-monomer was synthesized and characterized, followed by copolymerizing this monomer to yield functionalizable antifouling brushes. The brushes were fully characterized using surface characterization techniques like XPS, contact angle measurements, G-ATR-FTIR and XRR. As a proof of principle, the brushes were subsequently functionalized with biotin via strain-promoted alkyne azide click reactions, which yielded a fully zwitterionic biotin-containing 3D-functionalized coating. The sensing capacity was evaluated by reflectometry using avidin and fibrinogen containing protein solutions. The surfaces showed excellent antifouling properties as illustrated by the complete absence of non-specific fibrinogen binding, while at the same time clear responses were seen for the specific binding of avidin. A great increase in signal-to-noise ratio was observed, even when the amount of functional groups was lowered to 1%, compared to traditional modification of sulfobetaine brushes that rely on a 2D-approach in which only the top-layer can be functionalized. This study was performed on stoichiometric silicon nitride surfaces for future microring resonator based assays, however, this methodology can be transferred to other biosensor platforms which are currently being investigated. The approach presented herein enables a highly efficient strategy for selective binding with retained antifouling properties for improved signal-to-noise ratios in binding assays. The number of recognition units can be adjusted to a specific need, e.g. depending on the size of the analyte to be bound, widening the scope of these functionalizable surface coatings.

Keywords: antifouling, signal-to-noise ratio, surface functionalization, zwitterionic polymer brushes

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Authors: Jin Uk Han, Hye Won Han, Hyo Lim Kang, Tae An Kim, Seung Ho Han

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Direct-drive generators for large-scale wind turbine, which are divided into AFPM(Axial Flux Permanent Magnet) and RFPM(Radial Flux Permanent Magnet) type machine, have attracted interest because of a higher energy density in comparison with gear train type generators. Each type of the machines provides distinguishable geometrical features such as narrow width with a large diameter for the AFPM-type machine and wide width with a certain diameter for the RFPM-type machine. When the AFPM-type machine is applied, an increase of electric power production through a multi-stage arrangement in axial direction is easily achieved. On the other hand, the RFPM-type machine can be applied by using its geometric feature of wide width. In this study, a hybrid two-stage direct-drive generator for 6.2MW class wind turbine was proposed, in which the two-stage AFPM-type machine for 5 MW was composed of two models arranged in axial direction with a hollow shape topology of the rotor with annular disc, the stator and the main shaft mounted on coupled slew bearings. In addition, the RFPM-type machine for 1.2MW was installed at the empty space of the rotor. Analytic results obtained from an electro-magnetic and structural interaction analysis showed that the structural weight of the proposed hybrid two-stage direct-drive generator can be achieved as 155tonf in a condition satisfying the requirements of structural behaviors such as allowable air-gap clearance and strength. Therefore, it was sure that the 6.2MW hybrid two-stage direct-drive generator is competitive than conventional generators. (NRF grant funded by the Korea government MEST, No. 2017R1A2B4005405).

Keywords: AFPM-type machine, direct-drive generator, electro-magnetic analysis, large-scale wind turbine, RFPM-type machine

Procedia PDF Downloads 172

Authors: Joy Ghosh, Debasmita Biswas

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The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

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Authors: Walaa Diab, Baher Atlam, Nadia El Nimer

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Egypt faces many obvious economic challenges, and it is so clear that a real economic transformation is needed to address those problems, especially after the recent decisions of floating the Egyptian pound and the gradual subsidy cuts that are trying to meet the needed conditions to get the IMF support of (a £12bn loan) for its economic reform program. Following the post-2008 revival of the interest in the fiscal policy and its vital role in speeding up or slowing down the economic growth. Here comes the value of this paper as it seeks to analyze the macroeconomic effects of fiscal policy in Egypt by applying A Bayesian SVAR Approach. The study uses the Bayesian method because it includes the prior information and no relevant information is omitted and so it is well suited for rational, evidence-based decision-making. Since the study aims to define the effects of fiscal policy shocks in Egypt to help the decision-makers in determining the proper means to correct the structural problems in the Egyptian economy, it has to study the period of 1990s economic reform, but unfortunately; the available data is on an annual frequency. Thus, it uses annual time series to study the period 1991: 2005 And quarterly data over the period 2006–2016. It uses a set of six main variables includes government expenditure and net tax revenues as fiscal policy arms affecting real GDP, unemployment, inflation and the interest rate. The study also tries to assess the 'crowding out' effects by considering the effects of government spending and government revenue shocks on the composition of GDP, namely, on private consumption and private investment. Last but not least the study provides its policy implications regarding the needed role of fiscal policy in Egypt in the upcoming economic reform building on the results it concludes from the previous reform program.

Keywords: fiscal policy, government spending, structural vector autoregression, taxation

Procedia PDF Downloads 283

Authors: Alexander Vaninsky

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The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.

Keywords: economic restructuring, input-output analysis, divisia index, factorial decomposition, E3 models

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Authors: Murat Demir Aydin, Elanur Celebi

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Adhesively bonded joints are used as an alternative to traditional joining methods due to the important advantages they provide. The most important consideration in the use of adhesively bonded joints is that these joints have appropriate requirements for their use in terms of safety. In order to ensure control of this condition, damage analysis of the adhesively bonded joints should be performed by determining the mechanical properties of the adhesives. When the literature is investigated; it is generally seen that the mechanical properties of adhesives are determined by traditional measurement methods. In this study, to determine the mechanical properties of adhesives, the Digital Image Correlation (DIC) method, which can be an alternative to traditional measurement methods, has been used. The DIC method is a new optical measurement method which is used to determine the parameters of displacement and strain in an appropriate and correct way. In this study, tensile tests of Thick Adherent Shear Test (TAST) samples formed using DP410 liquid structural adhesive and steel materials and bulk tensile specimens formed using and DP410 liquid structural adhesive was performed. The displacement and strain values of the samples were determined by DIC method and the shear stress-strain curves of the adhesive for TAST specimens and the tensile strain curves of the bulk adhesive specimens were obtained. Various methods such as numerical methods are required as conventional measurement methods (strain gauge, mechanic extensometer, etc.) are not sufficient in determining the strain and displacement values of the very thin adhesive layer such as TAST samples. As a result, the DIC method removes these requirements and easily achieves displacement measurements with sufficient accuracy.

Keywords: structural adhesive, adhesively bonded joints, digital image correlation, thick adhered shear test (TAST)

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Authors: Meena Kumari, Ajitha Sharma, Mohan Babu Amberkar, Hasitha Manohar, Joseph Thomas, K. L. Bairy

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Aim: To evaluate the pattern of occurrence of adverse drug reactions (ADRs) with platinum compounds in cancer chemotherapy at a tertiary care hospital. Methods: It was a retrospective, descriptive case record study done on patients admitted to the medical oncology ward of Kasturba Hospital, Manipal from July to November 2012. Inclusion criteria comprised of patients of both sexes and all ages diagnosed with cancer and were on platinum compounds, who developed at least one adverse drug reaction during or after the treatment period. CDSCO proforma was used for reporting ADRs. Causality was assessed using Naranjo Algorithm. Results: A total of 65 patients was included in the study. Females comprised of 67.69% and rest males. Around 49.23% of the ADRs were seen in the age group of 41-60 years, followed by 20 % in 21-40 years, 18.46% in patients over 60 years and 12.31% in 1-20 years age group. The anticancer agents which caused adverse drug reactions in our study were carboplatin (41.54%), cisplatin (36.92%) and oxaliplatin (21.54%). Most common adverse drug reactions observed were oral candidiasis (21.53%), vomiting (16.92%), anaemia (12.3%), diarrhoea (12.3%) and febrile neutropenia (0.08%). The results of the causality assessment of most of the cases were probable. Conclusion: The adverse effect of chemotherapeutic agents is a matter of concern in the pharmacological management of cancer as it affects the quality of life of patients. This information would be useful in identifying and minimizing preventable adverse drug reactions while generally enhancing the knowledge of the prescribers to deal with these adverse drug reactions more efficiently.

Keywords: adverse drug reactions, platinum compounds, cancer, chemotherapy

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Authors: Gurkirandeep Kaur, Rana Pratap Yadav

Abstract:

This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

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Authors: Mohammad Reza Boromand, Masoud Moradi, Amin Eskandari

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The present study attempts to determine ranking of managerial parameters impacting upon performance of football referees in Iran. The population consisted of all referees in Leagues 1, 2 and 3 as well as super league of Iran (N=273), of which we selected 160 referees and assistant referees in 2013-2014. A research-designed questionnaire was used for data collection which was divided into two sections: (1) Demographic details (age range, Marital status, employment, refereeing experience, education level, refereeing level and proficiency) and (2) items related to parameters impacting upon performance of referees (structural parameters, operational parameters, environmental parameters, temporal parameters, economic parameters, facilities and tools, personal performance and performance evaluation). Internal consistency was calculated by Cronbach's alpha (r=0.85). For data analysis, we performed Freedman's Test and used SPSS software (α>0.05), along with descriptive statistics. The findings showed the following ranking for the above-mentioned managerial parameters: Facilities and tools, personal performance, economic parameters, structural parameters, operational parameters, environmental parameters, temporal parameters, and performance evaluation.

Keywords: Iran, football referees, managerial parameters, performance

Procedia PDF Downloads 575