Search results for: large language models (LLMS)

Authors: Clifford De Raffaele, Luana Bugeja, Serengul Smith

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The adaptation of social networking sites within higher education has garnered significant interest in the recent years with numerous researches considering it as a possible shift from the traditional classroom based learning paradigm. Notwithstanding this increase in research and conducted studies however, the adaption of SNS based modules have failed to proliferate within Universities. This paper, commences its contribution by analyzing the various models and theories proposed in literature and amalgamates together various effective aspects for the inclusion of social technology within e-Learning. A three phased framework is further proposed which details the necessary considerations for the successful adaptation of SNS in enhancing the students learning experience. This proposal outlines the theoretical foundations which will be analyzed in practical implementation across international university campuses.

Keywords: eLearning, higher education, social network sites, student learning

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Authors: A. Kraiem, A. Ayadi

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The squeeze flow tests were studied by many authors to measure the rheological properties of fluid. Experimental squeezing flow test with constant area between two parallel disks of bitumen is investigated in the present work. The effect of the temperature, the process of preparing the sample and the gap between the discs were discussed. The obtained results were compared with the theoretical models. The behavior of bitumen depends on the viscosity and the yield stress. Thus, the bitumen was presented as a power law for a small power law exponent and as a biviscous fluid when the viscosity ratio was smaller than one. Also, the influence of the ambient temperature is required for the compression test. Therefore, for a high temperature the yield stress decrease.

Keywords: bitumen, biviscous fluid, squeeze flow, viscosity, yield stress

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Authors: Oleg Shovkovyy

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This research conducted in response to one of the most pressing questions on the agenda of many public administration offices around the world: “What could be done for better integration and assimilation of immigrants into hosting communities?” In author’s view, the answer could be suggested by immigrants themselves. They, often ‘bogged down in the past,’ snared by own idols and demons, perceive things differently, which, in turn, may result in their inability to integrate smoothly into hosting communities. Brief literature review suggests that perceptions of immigrants are completely neglected or something unsought in the current research on migrants, which, often, based on opinion polls by members of hosting communities themselves or superficial research data by various research organizations. Even those specimens that include voices of immigrants, unlikely to shed any additional light onto the problem simply because certain things are not made to speak out loud, especially to those in whose hands immigrants’ fate is (authorities). In this regard, this qualitative study, conducted by an insider to a few Russian-speaking communities, represents a unique opportunity for all stakeholders to look at the question of integration through the eyes of immigrants, from a different perspective and thus, makes research findings especially valuable for better understanding of the problem. Case study research employed ethnographic methods of gathering data where, approximately 200 Russian-speaking immigrants of first and second generations were closely observed by the Russian-speaking researcher in their usual setting, for eight months, and at different venues. The number of informal interviews with 27 key informants, with whom the researcher managed to establish a good rapport and who were keen enough to share their experiences voluntarily, were conducted. The field notes were taken at 14 locations (study sites) within the Brisbane region of Queensland, Australia. Moreover, all this time, researcher lived in dwelling of one of the immigrants and was an active participant in the social life (worship, picnics, dinners, weekend schools, concerts, cultural events, social gathering, etc.) of observed communities, whose members, to a large extent, belong to various religious lines of the Russian and Protestant Church. It was found that the majority of immigrants had experienced some discrimination in matters of hiring, employment, recognition of educational qualifications from home countries, and simply felt a sort of dislike from society in various everyday situations. Many noted complete absences or very limited state assistance in terms of employment, training, education, and housing. For instance, the Australian Government Department of Human Services not only does not stimulate job search but, on the contrary, encourages to refuse short-term works and employment. On the other hand, offered free courses on adaptation, and the English language proved to be ineffective and unpopular amongst immigrants. Many interviewees have reported overstated requirements for English proficiency and local work experience, whereas it was not critical for the given task or job. Based on the result of long-term monitoring, the researcher also had the courage to assert the negative and decelerating roles of immigrants’ communities, particularly religious communities, on processes of integration and assimilation. The findings suggest that governments should either change current immigration policies in the direction of their toughening or to take more proactive and responsible role in dealing with immigrant-related issues; for instance, increasing assistance and support to all immigrants and probably, paying more attention to and taking stake in managing and organizing lives of immigrants’ communities rather, simply leaving it all to chance.

Keywords: Australia, immigration, integration, perceptions

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

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Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Satendra Pal Singh, Dalip Kr. Kakru, Jyoti Mishra, Rajesh Thakur, Tarana Sarwat

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COVID-19 is still an intrigue as far as morbidity or mortality is concerned. The rate of recovery varies from person to person, & it depends upon the accessibility of the healthcare system and the roles played by the physicians and caregivers. It is envisaged that with the passage of time, people would become immune to this virus, and those who are vulnerable would sustain themselves with the help of vaccines. The proposed study deals with the severeness of COVID-19 is associated with some specific biomarkers linked to correlate age and gender. We will be assessing the overall homeostasis of the persons who were affected by the coronavirus infection and also of those who recovered from it. Some people show more severe effects, while others show very mild symptoms, however, they show low CT values. Thus far, it is unclear why the new strain of Covid has different effects on different people in terms of age, gender, and ABO blood typing. According to data, the fatality rate with heart disease was 10.5 percent, 7.3 percent were diabetic, and 6 percent who are already infected from other comorbidities. However, some COVID-19 cases are worse than others & it is not fully explainable as of date. Overall data show that the ABO blood group is effective or prone to the risk of SARS-COV2 infection, while another study also shows the phenotypic effects of the blood group related to covid. It is an accepted fact that females have more strong immune systems than males, which may be related to the fact that females have two ‘X’ chromosomes, which might contain a more effective immunity booster gene on the X chromosome, and are capable to protect the female. Also specific sex hormones also induce a better immune response in a specific gender. This calls for in-depth analysis to be able to gain insight into this dilemma. COVID-19 is still not fully characterized, and thus we are not very familiar with its biology, mode of infection, susceptibility, and overall viral load in the human body. How many virus particles are needed to infect a person? How, then, comorbidity contribute to coronavirus infection? Since the emergence of this virus in 2020, a large number of papers have been published, and seemingly, vaccines have been prepared. But still, a large number of questions remain unanswered. The proneness of humans for infection by covid-19 needs to be established to be able to develop a better strategy to fight this virus. Our study will be on the Impact of demography on the Severity of covid-19 infection & at the same time, will look into gender-specific sensitivity of Covid-19 and the Operational variation of different biochemical markers in Covid-19 positive patients. Besides, we will be studying the co-relation, if any, of COVID severity & ABO Blood group type and the occurrence of the most common blood group type amongst positive patience.

Keywords: coronavirus, ABO blood group, age, gender

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Authors: S. Feli, S. Tavousi Tafreshi, A. Ghasemi

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The present paper aims at evaluating the response of three-dimensional buildings with in-plan stiffness irregularities that have been subjected to two-way excitation ground motion records simultaneously. This study is broadly-based fragility assessment with greater emphasis on structural response at in-plan flexible and stiff sides. To this end, three type of three-dimensional 5-story steel building structures with stiffness eccentricities, were subjected to extensive nonlinear incremental dynamic analyses (IDA) utilizing Ibarra-Krawinkler deterioration models. Fragility assessment was implemented for different configurations of braces to investigate the losses in buildings with center of resisting (CR) eccentricities.

Keywords: Ibarra-Krawinkler, fragility assessment, flexible and stiff side, center of resisting

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Authors: Heba Abdelmotaal, Magdy Abdel-Kader

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Purpose: This study explores whether a firm’s effective political risk management is preventing real and accrual earnings management . Design/methodology/approach: Based on a sample of 130 firms operating in Egypt during the period 2008-2013, two hypotheses are tested using the panel data regression models. Findings: The empirical findings indicate a significant relation between real and accrual earnings management and political risk. Originality/value: This paper provides a statistically evidence on the effects of the political risk management failure on the mangers’ engagement in the real and accrual earnings management practices, and its impact on the firm’s performance.

Keywords: political risk, risk management failure, real activities manipulation, accrual earnings management

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Authors: Nafisa Banu

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The present study is an attempt to analyze the regional disparities in the level of education in West Bengal. The data based on secondary sources obtained from a census of India. The study is divided into four sections. The first section presents introductions, objectives and brief descriptions of the study area, second part discuss the methodology and data base, while third and fourth comprise the empirical results, interpretation, and conclusion respectively. For showing the level of educational development, 8 indicators have been selected and Z- score and composite score techniques have been applied. The present study finds out there are large variations of educational level due to various historical, economical, socio-cultural factors of the study area.

Keywords: education, regional disparity, literacy rate, Z-score, composite score

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Authors: Silvia Sommella

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Islamic terrorism has gained a lot of media attention in the last years also because of the striking increase of terror attacks since 2014. The main aim of this paper is to illustrate the phenomenon of Islamic terrorism by applying frame semantics and metaphor analysis to German and Italian press headlines of the two online weekly publications Der Spiegel and L’Espresso between 2014 and 2019. This study focuses on how media discourse – through the use of conceptual metaphors – let arise in people a particular reception of the phenomenon of Islamic terrorism and accept governmental strategies and policies, perceiving terrorists as evildoers, as the members of an uncivilised group ‘other’ opposed to the civilised group ‘we’: two groups that are perceived as opposed. The press headlines are analyzed on the basis of the cognitive linguistics, namely Lakoff and Johnson’s conceptualization of metaphor to distinguish between abstract conceptual metaphors and specific metaphorical expressions. The study focuses on the contexts, frames, and metaphors. The method adopted in this study is Konerding’s frame semantics (1993). Konerding carried out on the basis of dictionaries – in particular of the Duden Deutsches Universalwörterbuch (Duden Universal German Dictionary) – in a pilot study of a lexicological work hyperonym reduction of substantives, working exclusively with nouns because hyperonyms usually occur in the dictionary meaning explanations as for the main elements of nominal phrases. The results of Konerding’s hyperonym type reduction is a small set of German nouns and they correspond to the highest hyperonyms, the so-called categories, matrix frames: ‘object’, ‘organism’, ‘person/actant’, ‘event’, ‘action/interaction/communication’, ‘institution/social group’, ‘surroundings’, ‘part/piece’, ‘totality/whole’, ‘state/property’. The second step of Konerding’s pilot study consists in determining the potential reference points of each category so that conventionally expectable routinized predications arise as predictors. Konerding found out which predicators the ascertained noun types can be linked to. For the purpose of this study, metaphorical expressions will be listed and categorized in conceptual metaphors and under the matrix frames that correspond to the particular conceptual metaphor. All of the corpus analyses are carried out using Ant Conc corpus software. The research will verify some previously analyzed metaphors such as TERRORISM AS WAR, A CRIME, A NATURAL EVENT, A DISEASE and will identify new conceptualizations and metaphors about Islamic terrorism, especially in the Italian language like TERRORISM AS A GAME, WARES, A DRAMATIC PLAY. Through the identification of particular frames and their construction, the research seeks to understand the public reception and the way to handle the discourse about Islamic terrorism in the above mentioned online weekly publications under a contrastive analysis in the German and in the Italian language.

Keywords: cognitive linguistics, frame semantics, Islamic terrorism, media

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Authors: Rajendra Kumar Kanojia

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Correction of the gap created by the resection of large juxtra-articular tumours of the femur would be difficult to manage, several bone substitutes, bone grafts, and artificial bone granules were tried but the results were not as good as with the distraction osteogensis, by the help of either Ilizarov ring fixator or the mono-rail fixators. We are presenting a small study of five cases of malignant tumours of the distal femur, removed, custom made mega prosthesis was applied and that failed twice in a span of five years. We had no better option left then to apply mono-rail fixator, and start the process of distraction osteogeneis, we got the union, gap was filled with new bone and patient has been made walking in few months.

Keywords: distal femur tumour, resection, defect non-union, mono-rail fixator

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Authors: Adel Belayadi

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The investigation of two-dimensional (2D) heterostructures, whether in the presence or the absence of magnetic substrates that sustain several induced spin-orbit couplings, has shown a promising/essential application for advancing the emerging fields of spintronics and valleytronics. In this contribution, we study spin/valley transport in graphene-like substrates in the presence of one or several locally induced spin-orbit coupling (SOC) terms resulting from graphene-based heterostructures. The models we proposed are based on the tight-binding approach, and our findings imply an alternative approach for conducting valley-polarized currents and suggest a corresponding mechanism for valley-dependent electron optics and optoelectronic devices.

Keywords: graphene-heterostructures, tight binding pproch, Spintronics, Valleytronics

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Authors: Gagandeep Kaur, Yadwinder Singh Brar, D. P. Kothari

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The paper has an aggregate analysis of animal dung for converting it into renewable biomass fuel source that could be used to help the Indian state Punjab to meet rising power demand. In Punjab district Bathinda produces over 4567 tonnes of animal dung daily on a renewable basis. The biogas energy potential has been calculated using values for the daily per head animal dung production and total no. of large animals in Bathinda of Punjab. The 379540 no. of animals in district could produce nearly 116918 m3 /day of biogas as renewable energy. By converting this biogas into electric energy could produce 89.8 Gwh energy annually.

Keywords: livestock, animal dung, biogas, renewable energy

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Authors: Andrus Pedai, Igor Astrov

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The focus of this paper is to compare common approaches for Systems of Innovation (SI) and identify proactive alternatives for driving the innovation. Proactive approaches will also consider short and medium term perspectives with developments in the field of Computer Technology and Artificial Intelligence. Concerning computer technology and large connected information systems, it is reasonable to predict that during current or the next century, intelligence and innovation will be separated from the constraints of human-driven management. After this happens, humans will no longer be driving the innovation and there is possibility that SI for new intelligent systems will set its own targets and exclude humans. Over long time scale, these developments could result in a scenario, which will lead to the development of larger, cross galactic (universal) proactive SI and Intelligence.

Keywords: artificial intelligence, DARPA, Moore’s law, proactive innovation, singularity, systems of innovation

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Authors: Kwounghee Choi

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Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

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Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

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Authors: Rabea Sefrin, Christian Glock, Juergen Schnell

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The preservation of existing structures is of great economic interest because it contributes to higher sustainability and resource conservation. In the case of existing buildings, in addition to repair and maintenance, modernization or reconstruction works often take place in the course of adjustments or changes in use. Since the structural framework and the associated load level are usually changed in the course of the structural measures, the stability of the structure must be verified in accordance with the currently valid regulations. The concrete compressive strength of the existing structures concrete and the derived mechanical parameters are of central importance for the recalculation and verification. However, the compressive strength of the existing concrete is usually set comparatively low and thus underestimated. The reasons for this are too small numbers, and large scatter of material properties of the drill cores, which are used for the experimental determination of the design value of the compressive strength. Within a structural component, the load is usually transferred over the area with higher stiffness and consequently with higher compressive strength. Therefore, existing strength variations within a component only play a subordinate role due to rearrangement effects. This paper deals with the experimental and numerical determination of such rearrangement effects in order to calculate the concrete compressive strength of existing structures more realistic and economical. The influence of individual parameters such as the specimen geometry (prism or cylinder) or the coefficient of variation of the concrete compressive strength is analyzed in experimental small-part tests. The coefficients of variation commonly used in practice are adjusted by dividing the test specimens into several layers consisting of different concretes, which are monolithically connected to each other. From each combination, a sufficient number of the test specimen is produced and tested to enable evaluation on a statistical basis. Based on the experimental tests, FE simulations are carried out to validate the test results. In the frame of a subsequent parameter study, a large number of combinations is considered, which had not been investigated in the experimental tests yet. Thus, the influence of individual parameters on the size and characteristic of the rearrangement effect is determined and described more detailed. Based on the parameter study and the experimental results, a calculation model for a more realistic determination of the in situ concrete compressive strength is developed and presented. By considering rearrangement effects in concrete during recalculation, a higher number of existing structures can be maintained without structural measures. The preservation of existing structures is not only decisive from an economic, sustainable, and resource-saving point of view but also represents an added value for cultural and social aspects.

Keywords: existing structures, in-situ concrete compressive strength, rearrangement effects, recalculation

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Imen Aouini, Lamia Ben Azzouz

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The energy need is growing rapidly due to the population growth and the large new usage of power. Several works put considerable efforts to make the electricity grid more intelligent to reduce essentially energy consumption and provide efficiency and reliability of power systems. The Smart Grid is a complex architecture that covers critical devices and systems vulnerable to significant attacks. Hence, security is a crucial factor for the success and the wide deployment of Smart Grids. In this paper, we present security issues of the Smart Grid architecture and we highlight open issues that will make the Smart Grid security a challenging research area in the future.

Keywords: smart grids, smart meters, home area network, neighbor area network

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Authors: Athar Imtiaz, Abduljalil S. Al-Mudhary, Taha Mirhashemi, Roslina Ibrahim

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Information Technology (IT) is being used by almost all organizations throughout the world. However, its success at supporting and improving business is debatable. There is always the risk of IT project failure and studies have proven that a large number of IT projects indeed do fail. There are many components that further the success of IT projects; these have been studied in previous studies. Studies have found the most necessary components for success in software development projects, executive information systems etc. In this study, previous literature that has looked into these success promoting factors have been critically reviewed and analyzed. Fifteen critical Success Factors (CSF) of IT projects were enlisted and examined. These factors can be applied to all IT projects and is not specific to a particular type of IT/IS project. A hypothesis was also generated after the evaluation of the factors.

Keywords: critical success factors, CSF, IT projects, IS projects, software development projects

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Emad E. Abdallah, Alaa E. Abdallah, Bajes Y. Alskarnah

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We introduce a robust three-dimensional watermarking algorithm for copyright protection and indexing. The basic idea behind our technique is to measure the interquartile range or the spread of the 3D model vertices. The algorithm starts by converting all the vertices to spherical coordinate followed by partitioning them into small groups. The proposed algorithm is slightly altering the interquartile range distribution of the small groups based on predefined watermark. The experimental results on several 3D meshes prove perceptual invisibility and the robustness of the proposed technique against the most common attacks including compression, noise, smoothing, scaling, rotation as well as combinations of these attacks.

Keywords: watermarking, three-dimensional models, perceptual invisibility, interquartile range, 3D attacks

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Catalina Iticescu, Lucian P. Georgescu, Mihaela Timofti, Gabriel Murariu

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Since the accumulation of large quantities of sewage sludge is producing serious environmental problems, numerous environmental specialists are looking for solutions to solve this problem. The sewage sludge obtained by treatment of municipal wastewater may be used as fertiliser on agricultural soils because such sludge contains large amounts of nitrogen, phosphorus and organic matter. In many countries, sewage sludge is used instead of chemical fertilizers in agriculture, this being the most feasible method to reduce the increasingly larger quantities of sludge. The use of sewage sludge on agricultural soils is allowed only with a strict monitoring of their physical and chemical parameters, because heavy metals exist in varying amounts in sewage sludge. Exceeding maximum permitted quantities of harmful substances may lead to pollution of agricultural soil and may cause their removal aside because the plants may take up the heavy metals existing in soil and these metals will most probably be found in humans and animals through food. The sewage sludge analyzed for the present paper was extracted from the Wastewater Treatment Station (WWTP) Galati, Romania. The physico-chemical parameters determined were: pH (upH), total organic carbon (TOC) (mg L⁻¹), N-total (mg L⁻¹), P-total (mg L⁻¹), N-NH₄ (mg L⁻¹), N-NO₂ (mg L⁻¹), N-NO₃ (mg L⁻¹), Fe-total (mg L⁻¹), Cr-total (mg L⁻¹), Cu (mg L⁻¹), Zn (mg L⁻¹), Cd (mg L⁻¹), Pb (mg L⁻¹), Ni (mg L⁻¹). The determination methods were electrometrical (pH, C, TSD) - with a portable HI 9828 HANNA electrodes committed multiparameter and spectrophotometric - with a Spectroquant NOVA 60 - Merck spectrophotometer and with specific Merck parameter kits. The tests made pointed out the fact that the sludge analysed is low heavy metal falling within the legal limits, the quantities of metals measured being much lower than the maximum allowed. The results of the tests made to determine the content of nutrients in the sewage sludge have shown that the existing nutrients may be used to increase the fertility of agricultural soils. Other tests were carried out on lands where sewage sludge was applied in order to establish the maximum quantity of sludge that may be used so as not to constitute a source of pollution. The tests were made on three plots: a first batch with no mud and no chemical fertilizers applied, a second batch on which only sewage sludge was applied, and a third batch on which small amounts of chemical fertilizers were applied in addition to sewage sludge. The results showed that the production increases when the soil is treated with sludge and small amounts of chemical fertilizers. Based on the results of the present research, a fertilization plan has been suggested. This plan should be reconsidered each year based on the crops planned, the yields proposed, the agrochemical indications, the sludge analysis, etc.

Keywords: agricultural use, crops, physico–chemical parameters, sewage sludge

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Authors: Mustafa Öztas, Metin Bedir, Yahya Özdemir

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Boron doped of In2O3 films were prepared by spray pyrolysis technique at 350 °C substrate temperature, which is a low cost and large area technique to be well-suited for the manufacture of solar cells, using boric acid (H3BO3) as dopant source, and their properties were investigated as a function of doping concentration. X-ray analysis showed that the films were polycrystalline fitting well with a hexagonal structure and have preferred orientation in (220) direction. The changes observed in the energy band gap and structural properties of the films related to the boric acid concentration are discussed in detail.

Keywords: spray pyrolysis, In2O3, boron, optical properties, boric acid

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Authors: Yue Huang, Yiheng Feng

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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

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Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

Abstract:

Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: coregionalization, heavy metals, multivariate geostatistical analysis, soil contamination, spatial distribution

Procedia PDF Downloads 300

Authors: Vahid Bairami Rad

Abstract:

Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

Procedia PDF Downloads 461

Authors: Dangut Maren David, Skaf Zakwan

Abstract:

Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 174

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 169

Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

Abstract:

Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

Procedia PDF Downloads 139