Search results for: effective Lagrangian approach

Authors: Satam Alotibi, Haya A. Al-Sunaidi, Almaymunah M. AlRoibah, Zahraa H. Al-Omaran, Mohammed Alyami, Fatehia S. Alhakami, Abdellah Kaiba, Mazen Alshaaer, Talal F. Qahtan

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This research study presents a novel approach to harnessing the potential of natural geopolymer in conjunction with TiO₂ nanoparticles (TiO₂ NPs) for the development of highly efficient photocatalytic materials for water decontamination. The study begins with the formulation of a geopolymer paste derived from natural sources, which is subsequently applied as a coating on glass substrates and allowed to air-dry at room temperature. The result is a series of geopolymer-coated glass films, serving as the foundation for further experimentation. To enhance the photocatalytic capabilities of these films, a critical step involves immersing them in a suspension of TiO₂ nanoparticles (TiO₂ NPs) in water for varying durations. This immersion process yields geopolymer-loaded TiO₂ NPs films with varying concentrations, setting the stage for comprehensive characterization and analysis. A range of advanced analytical techniques, including UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM), were meticulously employed to assess the structural, morphological, and chemical properties of the geopolymer-based TiO₂ films. These analyses provided invaluable insights into the materials' composition and surface characteristics. The culmination of this research effort sees the geopolymer-based TiO₂ films being repurposed as immobilized photocatalytic reactors for water decontamination under natural sunlight irradiation. Remarkably, the results revealed exceptional photocatalytic performance that exceeded the capabilities of conventional TiO₂-based photocatalysts. This breakthrough underscores the significant potential of natural geopolymer as a versatile and highly effective matrix for enhancing the photocatalytic efficiency of TiO₂ nanoparticles in water treatment applications. In summary, this study represents a significant advancement in the quest for sustainable and efficient photocatalytic materials for environmental remediation. By harnessing the synergistic effects of natural geopolymer and TiO₂ nanoparticles, these geopolymer-based films exhibit outstanding promise in addressing water decontamination challenges and contribute to the development of eco-friendly solutions for a cleaner and healthier environment.

Keywords: geopolymer, TiO2 nanoparticles, photocatalytic materials, water decontamination, sustainable remediation

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Authors: M. Hussaina, K. Mahboobb, S. Z. Ilyasa, S. Shaheena

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Plume dispersion modeling is a computational procedure to establish a relationship between emissions, meteorology, atmospheric concentrations, deposition and other factors. The emission characteristics (stack height, stack diameter, release velocity, heat contents, chemical and physical properties of the gases/particle released etc.), terrain (surface roughness, local topography, nearby buildings) and meteorology (wind speed, stability, mixing height, etc.) are required for the modeling of the plume dispersion and estimation of ground and air concentration. During the early phase of Fukushima accident, plume dispersion modeling and decisions were taken for the implementation of protective measures. A difference in estimated results and decisions made by different countries for taking protective actions created a concern in local and international community regarding the exact identification of the safe zone. The current study is focused to highlight the importance of accurate and exact weather data availability, scientific approach for decision making for taking urgent protective actions, compatible and harmonized approach for plume dispersion modeling during a nuclear emergency. As a case study, the influence of meteorological data on plume dispersion modeling and decision-making process has been performed.

Keywords: decision making process, radiation doses, nuclear emergency, meteorological implications

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Authors: Gia Sirbiladze

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Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

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Authors: H. M. Ferreira, H. Cockings, D. F. Gordon

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Climate change is driving a transition in the energy sector, with low-carbon energy sources such as hydrogen (H2) emerging as an alternative to fossil fuels. However, the successful implementation of a hydrogen economy requires an expansion of hydrogen production, transportation and storage capacity. The costs associated with this transition are high but can be partly mitigated by adapting the current oil and natural gas networks, such as pipeline, an important component of the hydrogen infrastructure, to transport pure or blended hydrogen. Steel pipelines are designed to withstand fatigue, one of the most common causes of pipeline failure. However, it is well established that some materials, such as steel, can fail prematurely in service when exposed to hydrogen-rich environments. Therefore, it is imperative to evaluate how defects (e.g. inclusions, dents, and pre-existing cracks) will interact with hydrogen under cyclic loading and, ultimately, to what extent hydrogen induced failure will limit the service conditions of steel pipelines. This presentation will explore how the exposure of API 5L X65 to a hydrogen-rich environment and cyclic loads will influence its susceptibility to hydrogen induced failure. That evaluation will be performed by a combination of several techniques such as hydrogen permeation testing (ISO 17081:2014), fatigue crack growth (FCG) testing (ISO 12108:2018 and AFGROW modelling), combined with microstructural and fractographic analysis. The development of a FCG test setup coupled with an electrochemical cell will be discussed, along with the advantages and challenges of measuring crack growth rates in electrolytic hydrogen environments. A detailed assessment of several electrolytic charging conditions will also be presented, using hydrogen permeation testing as a method to correlate the different charging settings to equivalent hydrogen concentrations and effective diffusivity coefficients, not only on the base material but also on the heat affected zone and weld of the pipelines. The experimental work is being complemented with AFGROW, a useful FCG modelling software that has helped inform testing parameters and which will also be developed to ultimately help industry experts perform structural integrity analysis and remnant life characterisation of pipeline steels under representative conditions. The results from this research will allow to conclude if there is an acceleration of the crack growth rate of API 5L X65 under the influence of a hydrogen-rich environment, an important aspect that needs to be rectified instandards and codes of practice on pipeline integrity evaluation and maintenance.

Keywords: AFGROW, electrolytic hydrogen charging, fatigue crack growth, hydrogen, pipeline, steel

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Authors: Rabi Abdullahi Danjuma, Fatima Binta Attahir

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Classroom discourse is important, and it is worth examining what the phenomena is and how it helps both the teacher and students in a classroom situation. This paper looks at the classroom as a traditional social setting which has its own norms and values. The paper also explains what discourse is, as extended communication in speech or writing often interactively dealing with some particular topics. It also discusses classroom discourse as the language which teachers and students use to communicate with each other in a classroom situation. The paper also looks at some strategies for effective classroom discourse. Finally, implications and recommendations were drawn.

Keywords: classroom, discourse, learning, student, strategies, communication

Procedia PDF Downloads 599

Authors: Mohammad Rostami Mehr, Seyed Arya Mir Rashed, Arndt Lueder, Magdalena Missler-Behr

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This paper represents the conception that complex problems do not necessarily need a similar complex solution in order to cope with the complexity. Furthermore, a simple solution based on established methods can provide a sufficient way to deal with the complexity. To verify this conception, the presented paper focuses on the field of change management as a part of the new product development process in the automotive sector. In this field, dealing with increasing complexity is essential, while only non-flexible rigid processes that are not designed to handle complexity are available. The basic methodology of this paper can be divided into four main sections: 1) analyzing the complexity of the change management, 2) literature review in order to identify potential solutions and methods, 3) capturing and implementing expertise of experts from the change management field of an automobile manufacturing company and 4) systematical comparison of the identified methods from literature and connecting these with defined requirements of the complexity of the change management in order to develop a solution. As a practical outcome, this paper provides a method to capture the complexity of engineering changes (EC) and includes it within the EC evaluation process, following case-related process guidance to cope with the complexity. Furthermore, this approach supports the conception that dealing with complexity is possible while utilizing rather simple and established methods by combining them into a powerful tool.

Keywords: complexity management, new product development, engineering change management, flexibility

Procedia PDF Downloads 191

Authors: Bendes Ákos

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Digital evidence will be the most widely used type of evidence in the future. With the development of the modern world, more and more new types of crimes have evolved and transformed. For this reason, it is extremely important to examine these types of crimes in order to get a comprehensive picture of them, with which we can help the authorities work. In 1865, with early technologies, people were able to forge a picture of a quality that is not even recognized today. With the help of today's technology, authorities receive a lot of false evidence. Officials are not able to process such a large amount of data, nor do they have the necessary technical knowledge to get a real picture of the authenticity of the given evidence. The digital world has many dangers. Unfortunately, we live in an age where we must protect everything digitally: our phones, our computers, our cars, and all the smart devices that are present in our personal lives and this is not only a burden on us, since companies, state and public utilities institutions are also forced to do so. The training of specialists and experts is essential so that the authorities can manage the incoming digital evidence at some level. When analyzing evidence, it is important to be able to examine it from the moment it is created. Establishing authenticity is a very important issue during official procedures. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. Otherwise, they will not have sufficient probative value and in case of doubt, the court will always decide in favor of the defendant. One of the most common problems in the world of digital data and evidence is doubt, which is why it is extremely important to examine the above-mentioned problems. The most effective way to avoid digital crimes is to prevent them, for which proper education and knowledge are essential. The aim is to present the dangers inherent in the digital world and the new types of digital crimes. After the comparison of the Hungarian investigative techniques with international practice, modernizing proposals will be given. A sufficiently stable yet flexible legislation is needed that can monitor the rapid changes in the world and not regulate afterward but rather provide an appropriate framework. It is also important to be able to distinguish between digital and digitalized evidence, as the degree of probative force differs greatly. The aim of the research is to promote effective international cooperation and uniform legal regulation in the world of digital crimes.

Keywords: digital crime, digital law, cyber crime, international cooperation, new crimes, skepticism

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Authors: Farzad Jalilian, Mehdi Mirzaei Alavijeh

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Background: E-interventions as a universal approach to prevent a high-risk behavior, such as alcohol drinking. This study was conducted to evaluate web-based alcohol drinking preventative intervention efficiency among medical university students in Iran. Methods: Overall, 150 freshman and sophomore male student’s college students participated in this study as intervention and control group. This was a longitudinal randomized pre- and post-test series control group design panel study to implement a behavior modification based intervention to alcohol drinking prevention among college students. Cross-tabulation, t-test, repeated measures, and GEE by using SPSS statistical package, version 21 was used for the statistical analysis. The participants were followed up for 6 months with data collection scheduled at baseline, 3 and 6 months. The primary outcomes are attitude, self-control, and sensation seeking. Furthermore, the secondary outcome is comparing alcohol drinking among the study groups. Results: It was found significant reduce in average response for an attitude towards alcohol drinking and sensation seeking among intervention group (P < 0.05). But after intervention not significant difference between intervention and control group of improve self-control and reduce alcohol drinking (P > 0.05). Conclusion: Our intervention has been accompanied with reducing alcohol use rate. These findings indicate that e-intervention may be effectiveness approach to address the alcohol prevention among college students.

Keywords: e-interventions, alcohol drinking, students, Iran

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Authors: Amir Reza Talaghat

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Since 2015, a new approach and policy regarding energy resources protection and using renewable energies has been started in Iran which was developing new projects. Investigating about the feasibility study of these new projects helped to figure out five steps to prepare an executive feasibility study of the concerned projects, which are proper site selections, authorizations, design and simulation, economic study and programming, respectively. The results were interesting and essential for decision makers and investors to start implementing of these projects in reliable condition. The research is obtained through collection and study of the project's documents as well as recalculation to review conformity of the results with GIS data and the technical information of the bidders. In this paper, it is attempted to describe the result of the performed research by describing the five steps as an executive methodology, for preparing a feasible study of installing a 10 MW – solar farm project. The corresponding results of the research also help decision makers to start similar projects is explained in this paper as follows: selecting the best location for the concerned PV plant, reliable and safe conditions for investment and the required authorizations to start implementing the solar farm project in the concerned region, selecting suitable component to achieve the best possible performance for the plant, economic profit of the investment, proper programming to implement the project on time.

Keywords: solar farm, solar energy, execution of PV power plant PV power plant

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Authors: Oxana Lukoshus

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The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: A. Kouloumpis, P. Zygouri, G. Potsi, K. Spyrou, D. Gournis

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Much of the research effort on graphene focuses on its use as building block for the development of new hybrid nanostructures with well-defined dimensions and behavior suitable for applications among else in gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biology. Towards this aim, here we describe a new bottom-up approach, which combines the self-assembly with the Langmuir Schaefer technique, for the production of fullerene-intercalated graphene hybrid materials. This new method uses graphene nanosheets as a template for the grafting of various fullerene C60 molecules (pure C60, bromo-fullerenes, C60Br24, and fullerols, C60(OH)24) in a bi-dimensional array, and allows for perfect layer-by-layer growth with control at the molecular level. Our film preparation approach involves a bottom-up layer-by-layer process that includes the formation of a hybrid organo-graphene Langmuir film hosting fullerene molecules within its interlayer spacing. A dilute water solution of chemically oxidized graphene (GO) was used as subphase on the Langmuir-Blodgett deposition system while an appropriate amino surfactant (that binds covalently with the GO) was applied for the formation of hybridized organo-GO. After the horizontal lift of a hydrophobic substrate, a surface modification of the GO platelets was performed by bringing the surface of the transferred Langmuir film in contact with a second amino surfactant solution (capable to interact strongly with the fullerene derivatives). In the final step, the hybrid organo-graphene film was lowered in the solution of the appropriate fullerene derivative. Multilayer films were constructed by repeating this procedure. Hybrid fullerene-based thin films deposited on various hydrophobic substrates were characterized by X-ray diffraction (XRD) and X-ray reflectivity (XRR), FTIR, and Raman spectroscopies, Atomic Force Microscopy, and optical measurements. Acknowledgments. This research has been co‐financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF)‐Research Funding Program: THALES. Investing in knowledge society through the European Social Fund (no. 377285).

Keywords: hybrids, graphene oxide, fullerenes, langmuir-blodgett, intercalated structures

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Authors: Mohammed H. Abu-Dieyeh, Mohammad M. Zalloum

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Plant growth-promoting rhizobacteria (PGPR) are known to enhance plant growth and/or reduce plant damage due to soil-borne pathogens. Tomato is the highest consumable vegetable world-wide including Jordan. Fusarium oxysporum is a pathogen that causes well-known damages and losses to many vegetable crops including tomato. In this study, purification of 112 isolates of PGPR strains from rhizosphere environment of different regions in Jordan was accomplished. All bacterial isolates were In-vitro screened for antagonistic effects against F. oxysporum. The eleven most effective isolates that caused 30%-50% in-vitro growth reduction of F. oxysporum were selected. 8 out of 11 of these isolates were collected from Al-Halabat (arid-land). 7 isolates of Al-Halabat exerted 40-54% In-vitro growth reduction of F. oxysporum. Four-week-old seedlings of tomato cultivar (Anjara, the most susceptible indigenous cultivar to F. oxysporum) treated with PGPR5 (Bacillus amyloliquefaciens), and exposed to F. oxysporum, showed no disease symptoms and no significant changes in biomasses or chlorophyll contents indicating a non-direct mechanism of action of PGPR on tomato plants. However PGPR3 (Bacillus sp.), PGPR4 (Bacillus cereus), and PGPR38 (Paenibacillus sp.) treated plants or PGPR treated and exposed to F. oxysporum showed a significant increasing growth of shoot and root biomasses as well as chlorophyll contents of leaves compared to control untreated plants or plants exposed to the fungus without PGPR treatment. A significant increase in number of flowers per plant was also recorded in all PGPR treated plants. The characterization of rhizobacterial strains were accomplished using 16S rRNA gene sequence analysis in addition to microscopic characterization. Further research is necessary to explore the potentiality of other collected PGPR isolates on tomato plants in addition to investigate the efficacy of the identified isolates on other plant pathogens and then finding a proper and effective methods of formulation and application of the successful isolates on selected crops.

Keywords: antagonism, arid land, growth promoting, rhizobacteria, tomato

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Authors: Nada Hamed, Mariam Aldhaheri, Sonia Abdennadher

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Islamic Finance is not a new term that emerging in the global market, but it is still under scope by many countries. Its characteristics and regulation are not widely clear and implemented. In 2015, The United Nation announced a plan about potential benefits of using Islamic Finance as a sustainable development approach. Enhancing its application in financial markets could protect from unexpected crisis that might be created from the traditional tools of finance. This paper focuses on this area to test if Islamic finance could be used for maintaining sustainable development and if the term of 'Green Islamic Finance' could be implemented to minimize the deficiencies and 'pollution’ generated from traditional techniques and tools of finance. This paper intends to measure the impact on financial performance and sustainability when financial institutions use Islamic finance or better practice it. The objective of this explanatory research is to measure the performance of Islamic Finance with using a case study of an Islamic bank. The paper would analyze and compare the behavior of financial institutions that used traditional financing tools and converted to Islamic banking system. The methodology used is based on a case study of an Islamic bank in Dubai with comparing its performance before implementing Islamic Finance and after. The selected case study represents the first national bank in Emirates Arab Unis who adopt the Islamic finance approach. Based on a time series analysis, a quantitative analysis would be also used through looking at various set of ratios that are routinely used to measure bank performance.

Keywords: Islamic finance, financial stability, green finance, Islamic finance practices, financial ratios

Procedia PDF Downloads 220

Authors: Jordan Gallant

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In the compound word processing literature, much attention has been paid to the relationship between a compound’s denotational meaning and that of its morphological whole-word constituents, which is referred to as ‘semantic transparency’. However, the parallel relationship between a compound’s connotation and that of its constituents has not been addressed at all. For instance, while a compound like ‘painkiller’ might be semantically transparent, it is not ‘affectively transparent’. That is, both constituents have primarily negative connotations, while the whole compound has a positive one. This paper investigates the role of affective transparency on compound processing using two methodologies commonly employed in this field: a lexical decision task and a typing task. The critical stimuli used were 112 English bi-constituent compounds that differed in terms of the effective transparency of their constituents. Of these, 36 stimuli contained constituents with similar connotations to the compound (e.g., ‘dreamland’), 36 contained constituents with more positive connotations (e.g. ‘bedpan’), and 36 contained constituents with more negative connotations (e.g. ‘painkiller’). Connotation of whole-word constituents and compounds were operationalized via valence ratings taken from an off-line ratings database. In Experiment 1, compound stimuli and matched non-word controls were presented visually to participants, who were then asked to indicate whether it was a real word in English. Response times and accuracy were recorded. In Experiment 2, participants typed compound stimuli presented to them visually. Individual keystroke response times and typing accuracy were recorded. The results of both experiments provided positive evidence that compound processing is influenced by effective transparency. In Experiment 1, compounds in which both constituents had more negative connotations than the compound itself were responded to significantly more slowly than compounds in which the constituents had similar or more positive connotations. Typed responses from Experiment 2 showed that inter-keystroke intervals at the morphological constituent boundary were significantly longer when the connotation of the head constituent was either more positive or more negative than that of the compound. The interpretation of this finding is discussed in the context of previous compound typing research. Taken together, these findings suggest that affective transparency plays a role in the recognition, storage, and production of English compound words. This study provides a promising first step in a new direction for research on compound words.

Keywords: compound processing, semantic transparency, typed production, valence

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: A. Mukrimah, M. Mohd Parid, H. F. Lim

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Wetland ecosystem has valuable resources that contribute to national income generation and public well-being, either directly by resources that have a market value or indirectly by resources that have no market value. Economic approach is used to evaluate the resources to determine the best use of wetland resources and should be emphasized in policy development planning. This approach is to prevent imbalance in the allocation of resources and welfare benefits. A case study was conducted in 2016 to assess the economic value of wetland ecosystem services at Pulau Kukup National Parks (PKNP). This study has applied dichotomous choice survey design Contingent Valuation Method (CVM) to investigate empirically the willingness-to-pay (WTP) by the public. The study interviewed 400 household respondents at Pontian, Johor. Analysis showed 81% of household interviewed were willing to contribute to the Wetland Conservation Trust Fund. The results also indicated that on average a household was willing to pay RM87 annually. By taking into account 21,664 households in Pontian district in 2016, public’s contribution to conserves wetland ecosystem at PKNP was calculated to be RM1, 884,334. From the public’s interest to contribute to the conservation of wetland ecosystem services at PKNP, it indicates that more concerted effort is needed by both the federal and state governments to conserve and rehabilitate the mangrove ecosystem in Malaysia.

Keywords: environmental economy, economic valuation, choice experiment, Pulau Kukup national parks

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Rahmi Yetri Kasri, Paulus Wirutomo

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Citizen engagement approach has become increasingly important in the rural water sector. However, the question remains as to what exactly is meant by citizen engagement and how this approach can lead to sustainable service delivery. To understand citizen engagement, this paper argues that we need to understand basic elements of social life that consist of social structure, process, and culture within the realm of community’s living environment. Extracting from empirical data from Pamsimas villages in rural West Java, Indonesia, this paper will identify basic elements of social life and environment that influence and form the engagement of citizen and government in delivering and sustaining rural water supply services in Indonesia. Pamsimas or the Water Supply and Sanitation for Low Income Communities project is the biggest rural water program in Indonesia, implemented since 1993 in more than 27,000 villages. The sustainability of this sector is explored through a rural water supply service delivery life-cycle, starts with capital investment, operational and maintenance, asset expansion or renewal, strategic planning for future services and matching cost with financing. Using mixed-method data collection in case study research, this paper argues that increased citizen engagement contributes to a more sustainable rural water service delivery.

Keywords: citizen engagement, rural water supply, sustainability, Indonesia

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

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Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

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Authors: Brendan Mooney

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Context: Feelings and emotions are commonly misunderstood and the terms often used interchangeably, leading to potential negative impacts on individuals' mental well-being and relationships. The distinction between these two fundamentally different experiences of human life is crucial for effective psychological practice and communication. Research Aim: The aim of this study is to outline the disparities between feelings and emotions, emphasising the significance of this differentiation in psychological practice to enhance clients' observation, decision-making, problem-solving, and communication skills. Methodology: This research utilises a conceptual model developed by the author in 2017 based on clinical experience, client observations, and feedback. The model serves to guide effective clinical practice by providing clear definitions and understanding of feelings versus emotions. Case study examples were utilised to support the efficacy of the model. Findings: The study highlights that recognising and expressing feelings rather than emotions is more empowering and conducive to resolving unresolved issues, thereby fostering better psychological well-being and interpersonal relationships. Theoretical Importance: This research underscores the importance of clarifying fundamental definitions related to feelings and emotions in enhancing psychological interventions and preventing various relationship conflicts and individual issues. Data Collection and Analysis Procedures: Data was collected through the author's clinical experience and interactions with clients, informing the development of the Feeling Emotions Mental (FEM) model. Analysis involved synthesising observations and feedback to elucidate the distinctions between feelings and emotions. Questions Addressed: What are the disparities between feelings and emotions? How does the confusion between these two fundamentally different experiences of human life impact individuals' mental well-being and relationships? Why is it essential to differentiate between feelings and emotions in psychological practice? Conclusion: The study advocates for a clear understanding of feelings versus emotions to support clients in addressing unresolved issues and improving their overall psychological functioning and communication skills, thereby preventing potential conflicts and relationship challenges.

Keywords: couples, mental, misinformation, misunderstanding, relationships

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Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

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Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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Authors: Teresa M. Odipo

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Inclusive physical education and an inclusive educational approach in German schools have received much attention in recent years due to the UN Convention on the rights of persons with disabilities proposals, which came into force in Germany in 2009. The aim of inclusive PE is to include children with disabilities and able bodied children, based on the idea, that all children should attend school together. While PE mostly took place in a heterogeneous environment, introducing children with all kinds of disabilities posed more challenges to the teachers, when children with disabilities were included. Therefore it is important that the educational approach should include pre-service teachers’ (PST) self-efficacy for and their attitudes towards inclusive practices. The PSTs’ self-efficacy for inclusive practices is one of the strongest predictors of the success of the inclusion reforms introduced in 2009, in order to improve PSTs’ ability to handle these very new challenges. PE stands out because the very nature of sport involves the body which means that all children, especially those with special needs should be treated in an appropriate manner. Up till now, it has been mostly English-speaking countries that have been assessed for inclusive practices in PE. Due to the lack of research in Germany, there is a strong need to question PSTs’ prepared-ness. This paper presents results from the 2016 survey conducted on around 100 PSTs by the German University of Sports in Cologne and opens up new directions within PSTs’ education, concerning their attitudes and self-efficacy towards inclusive PE. These new aspects will be included in the construction of new learning and teaching tools to improve pre-service teachers’ education for inclusive Physical Education.

Keywords: attitudes, inclusive physical education, pre-service teachers, self-efficacy

Procedia PDF Downloads 349

Authors: Sophie Lemoussu, Jean-Charles Chaudemar, Robertus A. Vingerhoeds

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Many innovative projects exist in the field of aeronautics, each addressing specific areas so to reduce weight, increase autonomy, reduction of CO2, etc. In many cases, such innovative developments are being carried out by very small enterprises (VSE’s) or small and medium sized-enterprises (SME’s). A good example concerns airships that are being studied as a real alternative to passenger and cargo transportation. Today, no international regulations propose a precise and sufficiently detailed framework for the development and certification of airships. The absence of such a regulatory framework requires a very close contact with regulatory instances. However, VSE’s/SME’s do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses an additional challenge for those VSE’s/SME’s, in particular those that have system integration responsibilities and that must provide all the necessary evidence to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The main objective of this research is to provide a methodological framework enabling VSE’s/SME’s with limited resources to organize the development of airships while taking into account the constraints of safety, cost, time and performance. This paper proposes to provide a contribution to this problematic by proposing a Model-Based Systems Engineering approach. Through a comprehensive process modeling approach applied to the development processes, the regulatory constraints, existing best practices, etc., a good image can be obtained as to the process landscape that may influence the development of airships. To this effect, not only the necessary regulatory information is taken on board, also other international standards and norms on systems engineering and project management are being modeled and taken into account. In a next step, the model can be used for analysis of the specific situation for given developments, derive critical paths for the development, identify eventual conflicting aspects between the norms, standards, and regulatory expectations, or also identify those areas where not enough information is available. Once critical paths are known, optimization approaches can be used and decision support techniques can be applied so to better support VSE’s/SME’s in their innovative developments. This paper reports on the adopted modeling approach, the retained modeling languages, and how they all fit together.

Keywords: aeronautics, certification, process modeling, project management, regulation, SME, systems engineering, VSE

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Authors: Sophie Sakka, Rénald Gaboriau

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This paper describes a preliminary work aimed at setting a therapeutic support for autistic teenagers using three humanoid robots NAO shared by ASD (Autism Spectrum Disorder) subjects. The studied population had attended successfully a first year program, and were observed with a second year program using the robots. This paper focuses on the content and the effects of the second year program. The approach is based on a master puppet concept: the subjects program the robots, and use them as an extension for communication. Twenty sessions were organized, alternating ten preparatory sessions and ten robotics programming sessions. During the preparatory sessions, the subjects write a story to be played by the robots. During the robot programming sessions, the subjects program the motions to be realized to make the robot tell the story. The program was concluded by a public performance. The experiment involves five ASD teenagers aged 12-15, who had all attended the first year robotics training. As a result, a progress in voluntary and organized communication skills of the five subjects was observed, leading to improvements in social organization, focus, voluntary communication, programming, reading and writing abilities. The changes observed in the subjects general behavior took place in a short time, and could be observed from one robotics session to the next one. The approach allowed the subjects to draw the limits of their body with respect to the environment, and therefore helped them confronting the world with less anxiety.

Keywords: autism spectrum disorder, robot, therapeutic support, rob'autism

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Authors: Umi Pudji Astuti, Dedi Sugandi

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The effectiveness of agricultural extension is determined by the component in the agricultural extension system among others are agricultural extension methods. Effective methods should be selected and defined based on the characteristics of the target, the resources, the materials, and the objectives to be achieved. Citrus agribusiness development in Lebong is certainly supported by the role of stakeholders and citrus farmers, as well as the proper dissemination methods. Adoption in the extension process substantially can be interpreted as the changes of behavior process such as knowledge (cognitive), attitudes (affective), and skill (psycho-motoric) in a person after receiving "innovation" from extension submitted by target communities. Knowledge and perception are needed as a first step in adopting a innovation, especially of citrus agribusiness development in Lebong. The process of Specific technology adoption is influenced by internal factors and farmer perceptions of technological innovation. Internal factors such as formal education, experience trying to farm, owned land, production farm goods. The output of this study: 1) to analyze the effectiveness of field trial methods in improving cognitive and affective farmers; 2) Knowing the relationship of adoption level and knowledge of farmers; 3) to analyze the factors that influence farmers' adoption of citrus technology innovation. The method of this study is through the survey to 40 respondents in Rimbo Pengadang Sub District, Lebong District in 2014. Analyzing data is done by descriptive and statistical parametric (multiple linear functions). The results showed that: 1) Field trip method is effective to improve the farmer knowledge (23,17% ) and positively affect the farmer attitude; 2) the knowledge level of PTKJS innovation farmers "positively and very closely related".; 3) the factors that influence the level of farmers' adoption are internal factors (education, knowledge, and the intensity of training), and external factors respondents (distance from the house to the garden and from the house to production facilities shop).

Keywords: affect, adoption technology, citrus gerga, effectiveness dissemination

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Authors: Durvi Yogesh Vagani

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This research paper explores the effectiveness of Research-informed teaching and Case-based teaching in enhancing the retention and recall of memory during discussions among university students. Additionally, it investigates the impact of using Artificial Intelligence (AI) tools on the quality of research conducted by students and its correlation with better recollection. The study hypothesizes that Case-based teaching will lead to greater recall and storage of information. The research gap in the use of AI in educational settings, particularly with actual participants, is addressed by leveraging a multi-method approach. The hypothesis is that the use of AI, such as ChatGPT and Bard, would lead to better retention and recall of information. Before commencing the study, participants' attention levels and IQ were assessed using the Digit Span Test and the Wechsler Adult Intelligence Scale, respectively, to ensure comparability among participants. Subsequently, participants were divided into four conditions, each group receiving identical information presented in different formats based on their assigned condition. Following this, participants engaged in a group discussion on the given topic. Their responses were then evaluated against a checklist. Finally, participants completed a brief test to measure their recall ability after the discussion. Preliminary findings suggest that students who utilize AI tools for learning demonstrate improved grasping of information and are more likely to integrate relevant information into discussions compared to providing extraneous details. Furthermore, Case-based teaching fosters greater attention and recall during discussions, while Research-informed teaching leads to greater knowledge for application. By addressing the research gap in AI application in education, this study contributes to a deeper understanding of effective teaching methodologies and the role of technology in student learning outcomes. The implication of the present research is to tailor teaching methods based on the subject matter. Case-based teaching facilitates application-based teaching, and research-based teaching can be beneficial for theory-heavy topics. Integrating AI in education. Combining AI with research-based teaching may optimize instructional strategies and deepen learning experiences. This research suggests tailoring teaching methods in psychology based on subject matter. Case-based teaching suits practical subjects, facilitating application, while research-based teaching aids understanding of theory-heavy topics. Integrating AI in education could enhance learning outcomes, offering detailed information tailored to students' needs.

Keywords: artificial intelligence, attention, case-based teaching, memory recall, memory retention, research-informed teaching

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Authors: Juntip Kanjanasilp, Ratree Sawangjit, Kanokporn Meelap, Kwanchanok Kruthakool

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Depression is a common mental health disorder. Antidepressants are effective pharmacological treatments, but most patients have low medication adherence. This study aims to systematic review and meta-analysis what method increase the antidepressants adherence efficiently and improve clinical outcome. Systematic review of articles of randomized controlled trials obtained by a computerized literature search of The Cochrane, Library, Pubmed, Embase, PsycINFO, CINAHL, Education search, Web of Science and ThaiLIS (28 December 2017). Twenty-three studies were included and assessed the quality of research by ROB 2.0. The results reported that printing media improved in number of people who had medication adherence statistical significantly (p= 0.018), but education, phone call, and program utilization were no different (p=0.172, p=0.127, p=0.659). There was no significant difference in pharmacist’s group, health care team’s group and physician’s group (p=0.329, p=0.070, p=0.040). Times of intervention at 1 month and 6 months improved medication adherence significantly (p= 0.0001, p=0.013). There was significantly improved adherence in single intervention (p=0.027) but no different in multiple interventions (p=0.154). When we analyzed medication adherence with the mean score, no improved adherence was found, not relevant with who gives the intervention and times to intervention. However, the multiple interventions group was statistically significant improved medication adherence (p=0.040). Phone call and the physician’s group were statistically significant improved clinical outcomes in number of improved patients (0.025 and 0.020, respectively). But in the pharmacist’s group and physician’s group were not found difference in the mean score of clinical outcomes (p=0.993, p=0.120, respectively). Times to intervention and number of intervention were not significant difference than usual care. The overall intervention can increase antidepressant adherence, especially the printing media, and the appropriate timing of the intervention is at least 6 months. For effective treatment, the provider should have experience and expert in caring for patients with depressive disorders, such as a psychiatrist. Medical personnel should have knowledge in caring for these patients also.

Keywords: depression, medication adherence, clinical outcomes, systematic review, meta-analysis

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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