Search results for: partially observable Markov decision processes

Authors: Ji-Wook Mauk, Yu-Suk Kim, Hyung-Joon Kim

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This study carried out comparative seismic performance of reinforced concrete frames infilled by masonry walls with different heights. Partial and fully infilled RC frames were modeled for the research objectives and the analysis model for a bare reinforced concrete frame was established for comparison. Non-linear static analyses for the studied frames were performed to investigate their structural behavior under extreme loading conditions and to find out their collapse mechanism. It was observed from analysis results that the strengths of the partial infilled RC frames are increased and their ductility is reduced, as infilled masonry walls are higher. Especially, Reinforced concrete frames with a higher partial infilled masonry wall would experience shear failures. Non-linear dynamic analyses using 10 earthquake records show that the bare and fully infilled reinforced concrete frames present stable collapse mechanism while the reinforced concrete frames with a partially infilled masonry wall collapse in more brittle manner due to short-column effects.

Keywords: fully infilled RC frame, partially infilled RC frame, masonry wall, short-column effect

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Authors: Mark E. Lokanan, Liz Lee

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This paper aims to examine the role of accountants as gatekeepers in anti-money laundering compliance in real estate transactions. The paper seeks to answer questions on ways in which accountants are involved in real estate transactions and mandatory compliance with regulatory authorities in Canada. The data for the study came from semi-structured interviews with accountants, lawyers, and government officials. Preliminary results reveal that there is a conflict between accountants’ obligation to disclose and loyalty to their clients. Accountants often do not see why they are obligated to disclose their clients' information to government agencies. The importance of the client in terms of the amount of revenue contributed to the accounting firm also plays a significant role in accountants' reporting decision-making process. Although the involvement of accountants in real estate purchase and sale transactions is limited to lawyers or notaries, they are often involved in designing financing schemes, which may involve money laundering activities. The paper is of wider public policy interests to both accountants and regulators. It is hard not to see Chartered Professional Accountant (CPA) Canada and government regulators using the findings to better understand the decision-making processes of accountants in their reporting practices to regulatory authorities.

Keywords: money laundering, real estate, disclosure, legislation, compliance

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Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Mushfiqur Rahman

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Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data integrity, smart contracts

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: M. Bahgat, H. A. Hanafy, S. Lakdawala

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Clustering phenomenon of pellets was observed frequently in shaft processes operating at higher temperatures. Clustering is a result of the growth of fibrous iron precipitates (iron whiskers) that become hooked to each other and finally become crystallized during the initial stages of metallization. If the pellet clustering is pronounced, sometimes leads to blocking inside the furnace and forced shutdown takes place. This work clarifies further the relation between metallic iron whisker growth and iron ore mineralogy. Various pellet sizes (6 – 12.0 & +12.0 mm) from three different ores (A, B & C) were (completely and partially) reduced at 985 ^oC with H₂/CO gas mixture using thermos-gravimetric technique. It was found that reducibility increases by decreasing the iron ore pellet’s size. Ore (A) has the highest reducibility than ore (B) and ore (C). Increasing the iron ore pellet’s size leads to increase the probability of metallic iron whisker formation. Ore (A) has the highest tendency for metallic iron whisker formation than ore (B) and ore (C). The reduction reactions for all iron ores A, B and C are mainly controlled by diffusion reaction mechanism.

Keywords: shaft furnace, cluster, metallic iron whisker, mineralogy, ferrous metallurgy

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Authors: Jae Hyun Lee

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Manufacturing companies use life-cycle inventory databases to analyze sustainability of their manufacturing processes. Life cycle inventory data provides reference data which may not be accurate for a specific company. Collecting accurate data of manufacturing processes for a specific company requires enormous time and efforts. An information model of typical manufacturing processes can reduce time and efforts to get appropriate reference data for a specific company. This paper shows an attempt to build an abstract information model which can be used to develop information models for specific manufacturing processes.

Keywords: process information model, sustainability, OWL, manufacturing

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Authors: Jeremy Goldsmith

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The Gambia, the smallest country in mainland Africa and one of the poorest countries on Earth, is currently experiencing historically unprecedented levels of out-migration to Europe. As a result, Gambians are currently among the top four nationalities emigrating to Europe. The central question that this thesis will address is: what factors impact the migration-related decision-making capabilities of Gambians? Based on interviews with NGOs, as well as those who have migrated and returned, are planning to migrate, and their friends and families, a pattern will emerge. This pattern will be woven into first person narratives which will explore the politico-economic, environmental, and socio-cultural factors that inform individual decision-making with regards to migration.

Keywords: migration, The Gambia, Africa, politico-economic, sociocultural, environmental

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Authors: Mariam Shah

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Strict liability is frequently used in magistrate’s courts for TV license and driving offences.There is existing research suggesting that the strict liability approach to criminal offences can result in ‘absurd’ judicial outcomes, or potentially ‘injustice’.This paper will discuss the potential merits of strict liability as a method for dealing with shoplifting offences.Currently, there is disparity in sentencing outcomes in the UK, particularly in relation to shoplifting offences.This paper will question whether ‘injustice’ is actually in the differentiation of defendants based upon their ‘perceived’ circumstances, which could be resulting in arbitrary judicial decision making.

Keywords: arbitrary, decision making, judicial decision making, shoplifting, stereotypes, strict liability

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Authors: Kuanrong Qiu, Sebnem Madrali, Evgueniy Entchev

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To achieve the satisfactory objectives in deploying integrated renewable energy systems, it is crucial to consider all the related parameters affecting the design and decision-making. The multi-criteria evaluation method is a reliable and efficient tool for achieving the most appropriate solution. The approach considers the influential factors and their relative importance in prioritizing the alternatives. In this paper, a multi-criteria decision framework, based on the criteria including technical, economic, environmental and reliability, is developed to evaluate and prioritize renewable energy technologies and configurations of their integrated systems for community applications, identify their viability, and thus support the adoption of the clean energy technologies and the decision-making regarding energy transitions and transition patterns. Case studies for communities in Canada show that resource availability and the configurations of the integrated systems significantly impact the economic performance and environmental performance.

Keywords: multi-criteria, renewables, integrated energy systems, decision-making, model

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Authors: Ghada Ben Hamad, Zohir Younsi, Fabien Salaun, Hassane Naji, Noureddine Lebaz

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The graphene oxide (GO) material has attracted much attention for solar energy applications. This paper reports the synthesis and characterization of partially oxidized graphite oxide (GTO). GTO was obtained by modified Hummers method, which is based on the chemical oxidation of natural graphite. Several samples were prepared with different oxidation degree by an adjustment of the oxidizing agent’s amount. The effect of the oxidation degree on the chemical structure and on the morphology of GTO was determined by using Fourier transform infrared (FT-IR) spectroscopy, Energy Dispersive X-ray Spectroscopy (EDS), and scanning electronic microscope (SEM). The thermal stability of GTO was evaluated by using thermogravimetric analyzer (TGA) in Nitrogen atmosphere. The results indicate high degree oxidation of graphite oxide for each sample, proving that the process is efficient. The GTO synthesized by modified Hummers method shows promising characteristics. Graphene oxide (GO) obtained by exfoliation of GTO are recognized as a good candidate for thermal energy storage, and it will be used as solid shell material in the encapsulation of phase change materials (PCM).

Keywords: modified hummers method, graphite oxide, oxidation degree, solar energy storage

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Authors: Xiuzhan Guo, Arthur Berrill, Ajinkya Kulkarni, Kostya Belezko, Min Luo

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Ontology operations, e.g., aligning and merging, were studied and implemented extensively in different settings, such as categorical operations, relation algebras, and typed graph grammars, with different concerns. However, aligning and merging operations in the settings share some generic properties, e.g., idempotence, commutativity, associativity, and representativity, labeled by (I), (C), (A), and (R), respectively, which are defined on an ontology merging system (D~M), where D is a non-empty set of the ontologies concerned, ~ is a binary relation on D modeling ontology aligning and M is a partial binary operation on D modeling ontology merging. Given an ontology repository, a finite set O ⊆ D, its merging closure Ô is the smallest set of ontologies, which contains the repository and is closed with respect to merging. If (I), (C), (A), and (R) are satisfied, then both D and Ô are partially ordered naturally by merging, Ô is finite and can be computed, compared, and sorted efficiently, including sorting, selecting, and querying some specific elements, e.g., maximal ontologies and minimal ontologies. We also show that the ontology merging system, given by ontology V -alignment pairs and pushouts, satisfies the properties: (I), (C), (A), and (R) so that the merging system is partially ordered and the merging closure of a given repository with respect to pushouts can be computed efficiently.

Keywords: ontology aligning, ontology merging, merging system, poset, merging closure, ontology V-alignment pair, ontology homomorphism, ontology V-alignment pair homomorphism, pushout

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Authors: Nurunnaher Nurunnaher

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This paper examines the impact of women’s participation in microcredit on women’s decision making in the slum areas of Dhaka city, Bangladesh. There is confusion in the literature about whether women’s empowerment is or is not a trickle down impact of poverty alleviation or household well-being, and the studies use more or less similar indicators to measure the status of household and the status of women. Studies very rarely conceptualize and operationalize the term ‘empowerment’ as the word is often used without proper care by policy makers and development practitioners instead of household wellbeing. Currently, decision making in many studies has been used as an indicator of women’s empowerment when assessing the impact of microcredit programs on women. Based on a qualitative and feminist study this paper operationalizes women’s empowerment through the development of a conceptual framework, the identification of assessment criteria and the development of proper indicators that guided the whole study. The testimonies of participants, both men and women, were the basis of exploration of women’s lived experiences, which is the most appropriate method to explore the impact of such programs on women’s empowerment. The study considers empowerment as a process that affects various levels of life and gender relationships. The study found that there is a positive change in women’s position in decision making when women have developed an independent economic base with credit money. However, predominantly, women’s decision making is shared with men with the final decision still in the men’s hands. It can be said that women’s microcredit participation has not significantly challenged the social norms, therefore it is not surprising that women who hand over credit to their husband rarely have any power in intra-household bargaining process. Nevertheless, overall it is evident that women are continuously struggling toward the freedom to have the authority over household, economic and personal matters. It is concluded that while making strategic choices or gaining empowerment requires several steps, women’s participation in decision-making has several implications on their lives and potentially challenges patriarchy.

Keywords: women, gender inequality/equality, decision making, empowerment, microcredit, slums, Dhaka, Bangladesh

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Dionne Coley B. A.

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The role of a lawyer as a mediator is to be impartial in assisting parties to arrive at a decision. This decision should be made in a voluntary and mutually acceptable manner where the mediator encourages the parties to communicate, identify their interests, assess risks and consider settlement options. One of the key components to mediation is impartiality where mediators are to have a duty to remain impartial throughout the course of mediation and uphold an “objective” demeanor with both parties. The question is whether a mediator should take on evaluative role while encouraging the parties to come to a decision. This means that the mediator would not only encourage dialogue and responses between the parties but also assess and provide an opinion on the matter. This paper submits the argument that the role of a mediator should not be one of evaluation as this does not encourage the dialogue, process or desired outcomes associated with mediation.

Keywords: evaluation, lawyer, mediation, reform

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Authors: Carlos Alberto Carvalho Castro, Nancy Del Ducca Barbedo, Edmilsom Otoni Côrrea

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With increase the production oil and lines transmission gases that are in ample expansion, the industries medium and great transport they had to adapt itself to supply the demand manufacture in this fabrication segment. In this context, two welding processes have been more extensively used: the GMAW (Gas Metal Arc Welding) and the FCAW (Flux Cored Arc Welding). In this work, welds using these processes were carried out in flat position on ASTM A-36 carbon steel plates in order to make a comparative evaluation between them concerning to mechanical and metallurgical properties. A statistical tool based on technical analysis and design of experiments, DOE, from the Minitab software was adopted. For these analyses, the voltage, current, and welding speed, in both processes, were varied. As a result, it was observed that the welds in both processes have different characteristics in relation to the metallurgical properties and performance, but they present good weldability, satisfactory mechanical strength e developed mathematical models.

Keywords: Flux Cored Arc Welding (FCAW), Gas Metal Arc Welding (GMAW), Design of Experiments (DOE), mathematical models

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Authors: Markou Vasiliki, Serdaris Panagiotis

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The consumer behavior and decision-making process of consumers is a process that is affected by the factor of uncertainty. The onslaught of the Covid 19 pandemic has changed the consumer decision-making process in many ways. This change can be seen both in the buying process (how and where they shop) but also in the types of goods and services they are looking for. In addition, due to the mainly economic uncertainty that came from this event, but also the effects on both society and the economy in general, new consumer behaviors were created. Traditional forms of shopping are no longer a primary choice, consumers have turned to digital channels such as e-commerce and social media to fulfill needs. The purpose of this particular article is to examine how much the consumer's decision-making process has been affected after the pandemic and if consumer behavior has changed. An online survey was conducted to examine the change in decision making. Essentially, the demographic factors that influence the decision-making process were examined, as well as the social and economic factors. The research is divided into two parts. The first part included a literature review of the research that has been carried out to identify the factors, and the second part where the empirical investigation was carried out using a questionnaire and was done electronically with the help of Google Forms. The questionnaire was divided into several sections. They included questions about consumer behavior, but mainly about how they make decisions today, whether those decisions have changed due to the pandemic, and whether those changes are permanent. Also, for decision-making, goods were divided into essential products, high-tech products, transactions with the state and others. Αbout 500 consumers aged between 18 and 75 participated in the research. The data was processed with both descriptive statistics and econometric models. The results showed that the consumer behavior and decision-making process has changed. Now consumers widely use the internet for shopping, consumer behaviors and consumer patterns have changed. Social and economic factors play an important role. Income, gender and other factors were found to be statistically significant. In addition, it is worth noting that the percentage who made purchases during the pandemic through the internet for the first time was remarkable and related to age. Essentially, the arrival of the pandemic caused uncertainty for individuals, mainly financial, and this affected the decision-making process. In addition, shopping through the internet is now the first choice, especially among young people, and it seems that it is about to become established.

Keywords: consumer behavior, decision making, COVID-19, Greece, behavior change

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Authors: Kemi Olalekan Oduntan

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This paper was carried out in order to empirical, and descriptively analysis how interest rate and foreign exchange rate liberalization influence investment decision in Nigeria. The study spanned through the period of 1985 – 2014, secondary data were restricted to relevant variables such as investment (Proxy by Gross Fixed Capital Formation) saving rate, interest rate and foreign exchange rate. Theories and empirical literature from various scholars were reviews in the paper. Ordinary Least Square regression method was used for the analysis of data collection. The result of the regression was critically interpreted and discussed. It was discovered for empirical finding that tax investment decision in Nigeria is highly at sensitive rate. Hence, all the alternative hypotheses were accepted while the respective null hypotheses were rejected as a result of interest rate and foreign exchange has significant effect on investment in Nigeria. Therefore, impact of interest rate and foreign exchange rate on the state of investment in the economy cannot be over emphasized.

Keywords: interest rate, foreign exchange liberalization, investment decision, economic growth

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: S. Mat Radzi, N. J. Abd Rahman, H. Mohd Noor, N. Ariffin

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Ferulic acid has widespread industrial potential by virtue of its antioxidant properties. However, it is partially soluble in aqueous media, limiting their usefulness in oil-based processes in food, cosmetic, pharmaceutical, and material industry. Therefore, modification of ferulic acid should be made by producing of more lipophilic derivatives. In this study, a preliminary investigation of lipase-catalyzed trans-esterification reaction of ethyl ferulate and olive oil was investigated. The reaction was catalyzed by immobilized lipase from Candida antarctica (Novozym 435), to produce ferulate ester, a sunscreen agent. A statistical approach of Response surface methodology (RSM) was used to evaluate the interactive effects of reaction temperature (40-80°C), reaction time (4-12 hours), and amount of enzyme (0.1-0.5 g). The optimum conditions derived via RSM were reaction temperature 60°C, reaction time 2.34 hours, and amount of enzyme 0.3 g. The actual experimental yield was 59.6% ferulate ester under optimum condition, which compared well to the maximum predicted value of 58.0%.

Keywords: ferulic acid, enzymatic synthesis, esters, RSM

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: I. Khutsishvili, G. Sirbiladze, B. Ghvaberidze

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This work proposes a fuzzy methodology to support the investment decisions. While choosing among competitive investment projects, the methodology makes ranking of projects using the new aggregation OWA operator – AsPOWA, presented in the environment of possibility uncertainty. For numerical evaluation of the weighting vector associated with the AsPOWA operator the mathematical programming problem is constructed. On the basis of the AsPOWA operator the projects’ group ranking maximum criteria is constructed. The methodology also allows making the most profitable investments into several of the project using the method developed by the authors for discrete possibilistic bicriteria problems. The article provides an example of the investment decision-making that explains the work of the proposed methodology.

Keywords: expert evaluations, investment decision making, OWA operator, possibility uncertainty

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Authors: J. S. S. Neto, R. A. A. Lima, D. K. K. Cavalcanti, J. P. B. Souza, R. A. A. Aguiar, M. D. Banea

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In the last decade, investments in sustainable processes and products have gained space in several segments, such as in the civil, automobile, textile and other industries. In addition to increasing concern about the development of environmentally friendly materials that reduce, energy costs and reduces environmental impact in the production of these products, as well as reducing CO2 emissions. Natural fibers offer a great alternative to replace synthetic fibers, totally or partially, because of their low cost and their renewable source. The purpose of this research is to study the effect of surface chemical treatment on the thermal properties of hybrid fiber reinforced natural fibers (NFRC), jute + ramie, jute + sisal, jute + curauá, and jute fiber in polymer matrices. Two types of chemical treatment: alkalinization and silanization were employed, besides the condition without treatment. Differential scanning calorimetry (DSC), thermogravimetry (TG) and dynamic-mechanical analysis (DMA) were performed to explore the thermal stability and weight loss in the natural fiber reinforced composite as a function of chemical treatment.

Keywords: chemical treatment, hybrid composite, jute, thermal

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Authors: Guerich Mohamed, Assaf Samir

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The application of viscoelastic materials in the form of constrained layers in mechanical structures is an efficient and cost-effective technique for solving noise and vibration problems. This technique requires a design tool to select the best location, type, and thickness of the damping treatment. This paper presents a finite element model for the vibration of beams partially or fully covered with a constrained viscoelastic damping material. The model is based on Bernoulli-Euler theory for the faces and Timoshenko beam theory for the core. It uses four variables: the through-thickness constant deflection, the axial displacements of the faces, and the bending rotation of the beam. The sandwich beam finite element is compatible with the conventional C1 finite element for homogenous beams. To validate the proposed model, several free vibration analyses of fully or partially covered beams, with different locations of the damping patches and different percent coverage, are studied. The results show that the proposed approach can be used as an effective tool to study the influence of the location and treatment size on the natural frequencies and the associated modal loss factors. Then, a parametric study regarding the variation in the damping characteristics of partially covered beams has been conducted. In these studies, the effect of core shear modulus value, the effect of patch size variation, the thickness of constraining layer, and the core and the locations of the patches are considered. In partial coverage, the spatial distribution of additive damping by using viscoelastic material is as important as the thickness and material properties of the viscoelastic layer and the constraining layer. Indeed, to limit added mass and to attain maximum damping, the damping patches should be placed at optimum locations. These locations are often selected using the modal strain energy indicator. Following this approach, the damping patches are applied over regions of the base structure with the highest modal strain energy to target specific modes of vibration. In the present study, a more efficient indicator is proposed, which consists of placing the damping patches over regions of high energy dissipation through the viscoelastic layer of the fully covered sandwich beam. The presented approach is used in an optimization method to select the best location for the damping patches as well as the material thicknesses and material properties of the layers that will yield optimal damping with the minimum area of coverage.

Keywords: finite element model, damping treatment, viscoelastic materials, sandwich beam

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Liz van Acker, Linda Colley

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Political processes are shaped by the gendered culture of parliaments. This paper examines how the institution of parliament has been affected by the changing number of women in politics. In order to understand how and why gender change occurs, the paper employs a feminist historical institutionalism approach. It argues that while it is difficult to change the gendered nature of political institutions, it is possible, from a gender perspective, to understand the processes of change both formally and informally. Increasing women’s representation has been a slow process which has not occurred without political struggles. A broadly defined ‘feminist historical institutionalism’ has critiqued existing approaches to institutions and combined historical institutional analysis with tools of gender to enhance our understanding of institutional processes and change. The paper examines the gendered rules, norms, and practices that influence institutional design choices and processes. Institutions such as Parliament often are able to adjust to women’s entry and absorb them without too much interruption. Exploring the hidden aspects to informal institutions involves identifying unspoken and accepted norms that may guide decision-making – exposing and questioning the gender status quo. This paper examines the representation of women in the Queensland Parliament, Australia. It places the Queensland experience in historical context, as well as in the national and international context. The study is interesting, given that its gender representation has rocketed from one of the worst performing states in 2012 to one of the best performing in 2015 with further improvements in 2017. The state currently has a re-elected female Premier, a female Deputy Premier and a female-dominated cabinet – in fact, Queensland was the first ministry in Australia to have a majority of women in its Cabinet. However, it is unnecessary to dig far below these headlines to see that this is uncharacteristic of its history: progress towards this current position has been slow and patchy. The paper finds that matters such as the glass ceiling and the use of quotas explain women’s recent success in Queensland politics.

Keywords: feminist historical institutional approach, glass ceiling, quotas, women’s participation in politics

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Authors: Sihem Oujdi, Hafida Belbachir

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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

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Authors: Ammar Alsabery, Habibis Saleh, Norazam Arbin, Ishak Hashim

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Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal non-equilibrium model is studied in this paper. The left vertical wall is maintained at a constant hot temperature and the right vertical wall is maintained at a constant cold temperature, while the horizontal walls are adiabatic. The governing equations are obtained by applying the Darcy model and Boussinesq approximation. COMSOL's finite element method is used to solve the non-dimensional governing equations together with specified boundary conditions. The governing parameters of this study are the Rayleigh number, the modified thermal conductivity ratio, the inter-phase heat transfer coefficien and the time independent. The results presented for values of the governing parameters in terms of streamlines in both fluid/porous layer, isotherms of fluid and solid porous layer, isotherms of fluid layer, and average Nusselt number.

Keywords: unsteady natural convection, thermal non-equilibrium model, Darcy model

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Authors: Rebecca J. Hafner, Daniel Read, David Elmes

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The current research applies decision making theory in order to address the problem of increasing uptake of energy-efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. Specifically, in two studies we apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. As researchers in the Interdisciplinary centre for Storage, Transformation and Upgrading of Thermal Energy (i-STUTE) are currently developing energy efficient heating systems for homes and businesses, we focus on the context of home heating choice, and compare preference for a standard condensing boiler versus an energy efficient heat pump, according to experimental manipulations in the structure of prior information. In Study 1, we find that people prefer stronger alignable features when options are similar; an effect which is mediated by an increased tendency to infer missing information is the same. Yet, in contrast to previous research, we find no effects of alignability on option preference when options differ. The advanced methodological approach used here, which is the first study of its kind to randomly allocate features as either alignable or non-alignable, highlights potential design effects in previous work. Study 2 is designed to explore the interaction between alignability and construal level as an explanation for the shift in attentional focus when options differ. Theoretical and applied implications for promoting energy efficient technologies are discussed.

Keywords: energy-efficient technologies, decision-making, alignability effects, construal level theory, CO2 reduction

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Authors: Michael Lousis

Abstract:

This research study is concerned with learner’s errors on Arithmetic and Algebra. The data resulted from a broader international comparative research program called Kassel Project. However, its conceptualisation differed from and contrasted with that of the main program, which was mostly based on socio-demographic data. The way in which the research study was conducted, was not dependent on the researcher’s discretion, but was absolutely dictated by the nature of the problem under investigation. This is because the phenomenon of learners’ mathematical errors is due neither to the intentions of learners nor to institutional processes, rules and norms, nor to the educators’ intentions and goals; but rather to the way certain information is presented to learners and how their cognitive apparatus processes this information. Several approaches for the study of learners’ errors have been developed from the beginning of the 20th century, encompassing different belief systems. These approaches were based on the behaviourist theory, on the Piagetian- constructivist research framework, the perspective that followed the philosophy of science and the information-processing paradigm. The researcher of the present study was forced to disclose the learners’ course of thinking that led them in specific observable actions with the result of showing particular errors in specific problems, rather than analysing scripts with the students’ thoughts presented in a written form. This, in turn, entailed that the choice of methods would have to be appropriate and conducive to seeing and realising the learners’ errors from the perspective of the participants in the investigation. This particular fact determined important decisions to be made concerning the selection of an appropriate framework for analysing the mathematical errors and giving explanations. Thus the rejection of the belief systems concerning behaviourism, the Piagetian-constructivist, and philosophy of science perspectives took place, and the information-processing paradigm in conjunction with the philosophy of mind were adopted as a general account for the elaboration of data. This paper explains why these decisions were appropriate and beneficial for conducting the present study and for the establishment of the ensued thesis. Additionally, the reasons for the adoption of the information-processing paradigm in conjunction with the philosophy of mind give sound and legitimate bases for the development of future studies concerning mathematical error analysis are explained.

Keywords: advantages-disadvantages of theoretical prospects, behavioral prospect, critical evaluation of theoretical prospects, error analysis, information-processing paradigm, opting for the appropriate approach, philosophy of science prospect, Piagetian-constructivist research frameworks, review of research in mathematical errors

Procedia PDF Downloads 190