Search results for: adaptive modeling

Authors: S. I. Mwasha, Z. Robinson, M. Musgrave

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Communities, especially in the global south, have been reported to have low adaptive capacity to cope with climate change impacts. As an attempt to improve adaptive capacity, most studies have focused on understanding the access of the household resources which can contribute to resilience against changes. However, little attention has been shown in uncovering how the household resources could be used and their implications to resilience against weather related shocks. By using a case study qualitative study, this project analyzed the trends in livelihoods practices and their implication to social equity. The study was done in three different villages within Kilimanjaro region. Each in different agro ecological zone. Two focus group discussions in two agro-ecological zones were done, one for women and another one for men except in the third zone where focus group participant were combined together (due to unforeseen circumstances). In the focus group discussion, several participatory rural appraisal tools were used to understand trend in crops and animal production and the use in which it is made: climate trends, soil fertility, trees and other livelihoods resources. Data were analyzed using thematic network analysis. Using an amalgam of magnitude (to note weather comments made were positive or negative) and descriptive coding (to note the topic), six basic themes were identified under social equity: individual ownership, family ownership, love and respect, women no education, women access to education as well as women access to loans. The results implied that despite mum and dad in the family providing labor in the agro pastoral activities, there were separations on who own what, as well as individual obligations in the family. Dad owned mostly income creating crops and mum, food crops. therefore, men controlled the economy which made some of them become arrogant and spend money to meet their interests sometimes not taking care of the family. Separation in ownership was reported to contribute to conflicts in the household as well as causing controversy on the use income is spent. Men were reported to use income to promote matriarchy system. However, as women were capacitated through access to education and loans they become closer to their husband and get access to own and plan the income together for the interest of the family. Joint ownership and planning on the household resources were reported to be important if families have to better adapt to climate change. The aim of this study is not to show women empowerment and joint ownership and planning as only remedy for low adaptive capacity. There is the need to understand other practices that either directly or indirectly impacts environmental integrity, food security and economic development for household resilience against changing climate.

Keywords: adaptive capacity, climate change, resilience, women empowerment

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Catherine Felce, Lior Pachter

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Current methods for building phylogenetic trees from gene expression data consider mean expression levels. With single-cell technologies, we can leverage more information about cell dynamics by considering the entire distribution of gene expression across cells. Using biophysical modeling, we propose a method for constructing phylogenetic trees from scRNA-seq data, building on Felsenstein's method of continuous characters. This method can highlight genes whose level of expression may be unchanged between species, but whose rates of transcription/decay may have evolved over time.

Keywords: phylogenetics, single-cell, biophysical modeling, transcription

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Authors: Yi-You Hung

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Relational trauma has garnered significant attention recently, as it can create barriers in the personal, interpersonal, and professional realms. Without proper intervention, its psychological impact can be profound. In psychotherapy, the demand for culturally adaptive intervention models is growing. This article compares two therapeutic approaches focused on ‘self’ and ‘non-self’. It then incorporates Buddhist concepts of ‘dukkha’ (suffering), ‘samudaya’ (origin), ‘nirodha’ (cessation), and ‘magga’ (path) to develop culturally sensitive psychological interventions. Unlike Western psychotherapy, which often focuses on self, symptom relief, and restoring self-functioning, the ‘non-self’ approach encourages therapists to embody the principles of the Four Noble Truths. This perspective aims to help individuals reconstruct their internal relational state through shared suffering, compassion, wisdom, mindfulness, and righteous conduct. By understanding these concepts, therapists can guide individuals to ‘return to their inherent emptiness and non-self,’ resonating with the Buddhist belief that realizing this emptiness is a fundamental human goal. However, the model's limitations include individuals' need to embrace this cultural discourse and for therapists to learn Buddhist concepts deeply. Further research is essential to validate the effectiveness of this model in treating relational trauma cases.

Keywords: buddhism, buddhist principles, culturally adaptive interventions, relational trauma

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Authors: Mehrnaz Farzingohar, Mehran Yasemi, Ahmad Savari

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The oil products are imported and exported via Rajaee’s tanker terminal. Within loading and discharging in several cases the oil is released into the berths and made oil spills. The spills are distributed within short time and seriously affected Rajaee port’s environment and even extended areas. The trajectory and fate of oil spills investigated by modeling and parted by three risk levels base on the modeling results. First GNOME (General NOAA Operational Modeling Environment) applied to trajectory the liquid oil. Second, ALOHA (Areal Location Of Hazardous Atmosphere) air quality model, is integrated to predict the oil evaporation path within the air. Base on the identified zones the high risk areas are signed by colored dots which their densities calculated and clarified on a map which displayed the harm places. Wind and water circulation moved the pollution to the East of Rajaee Port that accumulated about 12 km of coastline. Approximately 20 km of north east of Qeshm Island shore is covered by the three levels of risky areas. Since the main wind direction is SSW the pollution pushed to the east and the highest risk zones formed on the crests edges hence the low risk appeared on the concavities. This assessment help the management and emergency systems to monitor the exposure places base on the priority factors and find the best approaches to protect the environment.

Keywords: oil spill, modeling, pollution, risk assessment

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Authors: A. E. Kobryn

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We present both descriptive and predictive modeling of structural properties of blends of PCBM or organic-inorganic hybrid perovskites of the type CH3NH3PbX3 (X=Cl, Br, I) with P3HT, P3BT or squaraine SQ2 dye sensitizer, including adsorption on TiO2 clusters having rutile (110) surface. In our study, we use a methodology that allows computing the microscopic structure of blends on the nanometer scale and getting insight on miscibility of its components at various thermodynamic conditions. The methodology is based on the integral equation theory of molecular liquids in the reference interaction site representation/model (RISM) and uses the universal force field. Input parameters for RISM, such as optimized molecular geometries and charge distribution of interaction sites, are derived with the use of the density functional theory methods. To compare the diffusivity of the PCBM in binary blends with P3HT and P3BT, respectively, the study is complemented with MD simulation. A very good agreement with experiment and the reports of alternative modeling or simulation is observed for PCBM in P3HT system. The performance of P3BT with perovskites, however, seems as expected. The calculated nanoscale morphologies of blends of P3HT, P3BT or SQ2 with perovskites, including adsorption on TiO2, are all new and serve as an instrument in rational design of organic/hybrid photovoltaics. They are used in collaboration with experts who actually make prototypes or devices for practical applications.

Keywords: multiscale theory and modeling, nanoscale morphology, organic-inorganic halide perovskites, three dimensional distribution

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Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka

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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'

Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling

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Authors: Rim Bouhaouel, Naoufel Kraïem, Zuhoor Al Khanjari

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Unified Modeling Language (UML) is considered as one of the widespread modeling language standardized by the Object Management Group (OMG). Therefore, the model driving engineering (MDE) community attempts to provide reuse of UML diagrams, and do not construct it from scratch. The UML model appears according to a specific software development process. The existing method generation models focused on the different techniques of transformation without considering the development process. Our work aims to construct an UML component from fragments of UML diagram basing on an agile method. We define UML fragment as a portion of a UML diagram, which express a business target. To guide the generation of fragments of UML models using an agile process, we need a flexible approach, which adapts to the agile changes and covers all its activities. We use the software product line (SPL) to derive a fragment of process agile method. This paper explains our approach, named RECUP, to generate UML fragments following an agile process, and overviews the different aspects. In this paper, we present the approach and we define the different phases and artifacts.

Keywords: UML, component, fragment, agile, SPL

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Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off-grid, PV module

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Authors: Maha Bakkari, Fatiha Lemmeni, Rachid Tadili

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In this work, we present some characteristics of the furnace studied, its operating principle and the experimental measurements of the evolutions of the temperatures inside and outside the walls of the This work deals with the problem of energy consumption of pottery kilns whose energy consumption is relatively too high. In this work, we determined the sources of energy loss by studying the heat transfer of a pottery furnace, we proposed a recovery system to reduce energy consumption, and then we developed a numerical model modeling the transfers through the walls of the furnace and to optimize the insulation (reduce heat losses) by testing multiple insulators. The recovery and reuse of energy recovered by the recovery system will present a significant gain in energy consumption of the oven and cooking time. This research is one of the solutions that helps reduce the greenhouse effect of the planet earth, a problem that worries the world.

Keywords: recovery lost energy, energy efficiency, modeling, heat transfer

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Reihaneh Mahdavishahri, Dumayi Gutierrez

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Emotionally focused couple therapy (EFCT) is one of the most effective and evidence-based approaches to couple therapy. Yet, literature is scarce of its effective application with trans and non-binary couples. It is estimated that 1.4 million trans adults live in the United Stated, with about 40% of these individuals experiencing serious psychological distress within the past month. Trans and nonbinary adults are significantly likely to experience discrimination, harassment, family rejection, and relationship challenges throughout the course of their lives. As systemic therapists, applying an informed lens when working with trans and nonbinary couples can contribute to providing effective mental health care to these individuals. This paper aims to provide a comprehensive, intersectional, and culturally informed application of EFCT with trans and nonbinary couples. We will address the current literature on applications of EFCT with diverse couples, EFCT’s strengths and limitations on cultural humility, and the gaps within current systems of care for trans and nonbinary couples. We will then provide an adaptive application of EFCT to help trans, and nonbinary couples recover from potential attachment injuries in their relationships, intersecting gender minority stressors, and achieve healing and restoration in their interpersonal dynamics.

Keywords: attachment, culturally informed care, emotionally focused couple therapy, trans and nonbinary couples

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Authors: Salima Djehaichia, Rachid Lassoued

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Reinforced concrete structural walls are very efficient elements for protecting buildings against excessive early damage and against collapse under earthquake actions. It is therefore of interest to develop a numerical model which simulates the typical behavior of these units, this paper presents and describes different modeling techniques that have been used by researchers and their advantages and limitations mentioned. The earthquake of Boumerdes in 2003 has demonstrated the fragility of structures and total neglect of sismique design rules in the realization of old buildings. Significant damage and destruction of buildings caused by this earthquake are not due to the choice of type of material, but the design and the study does not congruent with seismic code requirements and bad quality of materials. For idealizing the failure of rules, a parametric study focuses on: low rate of reinforcements, type of reinforcement, resistance moderate of concrete. As an application the modeling strategy based on finite elements combined with a discretization of wall more solicited by successive thin layers. The estimated performance level achieved during a seismic action is obtained from capacity curves under incrementally increasing loads. Using a pushover analysis, a characteristic non linear force-displacement relationship can be determined. The results of numeric model are confronted with those of Algerian Para seismic Rules (RPA) in force have allowed the determination of profits in terms of displacement, shearing action, ductility.

Keywords: modeling, old building, pushover analysis, structural walls

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Authors: Rahel Birhane Eshetu

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This research investigates the complex landscape of project management practices and operational challenges in conflict-affected areas, with a specific focus on Kewot Woreda in the North Shewa Zone of the Amhara region in Ethiopia. The study aims to identify essential project management methodologies, the significant operational hurdles faced, and the adaptive strategies employed by project managers in these challenging environments. Utilizing a mixed-methods approach, the research combines qualitative and quantitative data collection. Initially, a comprehensive literature review was conducted to establish a theoretical framework. This was followed by the administration of questionnaires to gather empirical data, which was then analyzed using statistical software. This sequential approach ensures a robust understanding of the context and challenges faced by project managers. The findings reveal that project managers in conflict zones encounter a range of escalating challenges. Initially, they must contend with immediate security threats and the presence of displaced populations, which significantly disrupt project initiation and execution. As projects progress, additional challenges arise, including limited access to essential resources and environmental disruptions such as natural disasters. These factors exacerbate the operational difficulties that project managers must navigate. In response to these challenges, the study highlights the necessity for project managers to implement formal project plans while simultaneously adopting adaptive strategies that evolve over time. Key adaptive strategies identified include flexible risk management frameworks, change management practices, and enhanced stakeholder engagement approaches. These strategies are crucial for maintaining project momentum and ensuring that objectives are met despite the unpredictable nature of conflict environments. The research emphasizes that structured scope management, clear documentation, and thorough requirements analysis are vital components for effectively navigating the complexities inherent in conflict-affected regions. However, the ongoing threats and logistical barriers necessitate a continuous adjustment to project management methodologies. This adaptability is not only essential for the immediate success of projects but also for fostering long-term resilience within the community. Concluding, the study offers actionable recommendations aimed at improving project management practices in conflict zones. These include the adoption of adaptive frameworks specifically tailored to the unique conditions of conflict environments and targeted training for project managers. Such training should focus on equipping managers with the skills to better address the dynamic challenges presented by conflict situations. The insights gained from this research contribute significantly to the broader field of project management, providing a practical guide for practitioners operating in high-risk areas. By emphasizing sustainable and resilient project outcomes, this study underscores the importance of adaptive management strategies in ensuring the success of projects in conflict-affected regions. The findings serve not only to enhance the understanding of project management practices in Kewot Woreda but also to inform future research and practice in similar contexts, ultimately aiming to promote stability and development in areas beset by conflict.

Keywords: project management practices, operational challenges, conflict zones, adaptive strategies

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Masoud Sheidaei, Melica Tabasi, Fahimeh Koohdar, Mona Sheidaei

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Juglans regia L. is an economically important species of edible nuts. Iran is known as a center of origin of genetically rich walnut germplasm and expected to be found a large diversity within Iranian walnut populations. A detailed population genetic of local populations is useful for developing an optimal strategy for in situ conservation and can assist the breeders in crop improvement programs. Different phylogenetic studies have been carried out in this genus, but none has been concerned with genetic changes associated with geographical divergence and the identification of adaptive SNPs. Therefore, we carried out the present study to identify discriminating ITS nucleotides among Juglans species and also reveal association between ITS SNPs and geographical variables. We used different computations approaches like DAPC, CCA, and RDA analyses for the above-mentioned tasks. We also performed population genetics analyses for population effective size changes associated with the species expansion. The results obtained suggest that latitudinal distribution has a more profound effect on the species genetic changes. Similarly, multiple analytical approaches utilized for the identification of both discriminating DNA nucleotides/ SNPs almost produced congruent results. The SNPs with different phylogenetic importance were also identified by using a parsimony approach.

Keywords: Persian walnut, adaptive SNPs, data analyses, genetic diversity

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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Authors: Mohammad Arabi

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Business Process Reengineering (BPR) is a systematic approach to fundamentally redesign organizational processes to achieve significant improvements in organizational performance. At Fars Regional Electric Company, implementing BPR is deemed essential to increase productivity, reduce costs, and improve service quality. This article examines how BPR can help enhance the performance of Fars Regional Electric Company. The objective of this research is to evaluate and analyze the advancements in process modeling and reengineering at Fars Regional Electric Company and to provide solutions for improving the productivity and efficiency of organizational processes. This study aims to demonstrate how BPR can be used to improve organizational processes and enhance the overall performance of the company. This research employs both qualitative and quantitative research methods and includes interviews with senior managers and experts at Fars Regional Electric Company. The analytical tools include process modeling software such as Bizagi and ARIS, and statistical analysis software such as SPSS and Minitab. Data analysis was conducted using advanced statistical methods. The results indicate that the use of BPR techniques can lead to a significant reduction in process execution time and overall improvement in quality. Implementing BPR at Fars Regional Electric Company has led to increased productivity, reduced costs, and improved overall performance of the company. This study shows that with proper implementation of BPR and the use of modeling tools, the company can achieve significant improvements in its processes. Recommendations: (1) Continuous Training for Staff: Invest in continuous training of staff to enhance their skills and knowledge in BPR. (2) Use of Advanced Technologies: Utilize modeling and analysis software to improve processes. (3) Implementation of Effective Management Systems: Employ knowledge and information management systems to enhance organizational performance. (4) Continuous Monitoring and Review of Processes: Regularly review and revise processes to ensure ongoing improvements. This article highlights the importance of improving organizational processes at Fars Regional Electric Company and recommends that managers and decision-makers at the company seriously consider reengineering processes and utilizing modeling technologies to achieve developmental goals and continuous improvement.

Keywords: business process reengineering, electric company, Fars province, process modeling advancements

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Authors: Murast Dicleli, Ali SalemMilani

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In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multi-directional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.

Keywords: seismic, isolation, damper, adaptive stiffness

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Authors: Hanbey Hazar, Hakan Gul

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In this study; piston, exhaust, and suction valves of a diesel engine were coated in 300 mm thickness with Tungsten Carbide (WC) by using the HVOF coating method. Mathematical modeling of a coated and uncoated (standardized) engine was performed by using ANN (Artificial Neural Networks). The purpose was to decrease the number of repetitions of tests and reduce the test cost through mathematical modeling of engines by using ANN. The results obtained from the tests were entered in ANN and therefore engines' values at all speeds were estimated. Results obtained from the tests were compared with those obtained from ANN and they were observed to be compatible. It was also observed that, with thermal barrier coating, hydrocarbon (HC), carbon monoxide (CO), and smoke density values of the diesel engine decreased; but nitrogen oxides (NOx) increased. Furthermore, it was determined that results obtained through mathematical modeling by means of ANN reduced the number of test repetitions. Therefore, it was understood that time, fuel and labor could be saved in this way.

Keywords: Artificial Neural Network, Diesel Engine, Mathematical Modelling, Thermal Barrier Coating

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Authors: Wen-Chung Wang, Xue-Lan Qiu

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Ipsative tests have been widely used in vocational and career counseling (e.g., the Jackson Vocational Interest Survey). Pairwise-comparison items are a typical item format of ipsative tests. When the two statements in a pairwise-comparison item measure two different constructs, the item is referred to as a multidimensional pairwise-comparison (MPC) item. A typical MPC item would be: Which activity do you prefer? (A) playing with young children, or (B) working with tools and machines. These two statements aim at the constructs of social interest and investigative interest, respectively. Recently, new item response theory (IRT) models for ipsative tests with MPC items have been developed. Among them, the Rasch ipsative model (RIM) deserves special attention because it has good measurement properties, in which the log-odds of preferring statement A to statement B are defined as a competition between two parts: the sum of a person’s latent trait to which statement A is measuring and statement A’s utility, and the sum of a person’s latent trait to which statement B is measuring and statement B’s utility. The RIM has been extended to polytomous responses, such as preferring statement A strongly, preferring statement A, preferring statement B, and preferring statement B strongly. To promote the new initiatives, in this study we developed computerized adaptive testing algorithms for MFC items and evaluated their performance using simulations and two real tests. Both the RIM and its polytomous extension are multidimensional, which calls for multidimensional computerized adaptive testing (MCAT). A particular issue in MCAT for MPC items is the within-person statement exposure (WPSE); that is, a respondent may keep seeing the same statement (e.g., my life is empty) for many times, which is certainly annoying. In this study, we implemented two methods to control the WPSE rate. In the first control method, items would be frozen when their statements had been administered more than a prespecified times. In the second control method, a random component was added to control the contribution of the information at different stages of MCAT. The second control method was found to outperform the first control method in our simulation studies. In addition, we investigated four item selection methods: (a) random selection (as a baseline), (b) maximum Fisher information method without WPSE control, (c) maximum Fisher information method with the first control method, and (d) maximum Fisher information method with the second control method. These four methods were applied to two real tests: one was a work survey with dichotomous MPC items and the other is a career interests survey with polytomous MPC items. There were three dependent variables: the bias and root mean square error across person measures, and measurement efficiency which was defined as the number of items needed to achieve the same degree of test reliability. Both applications indicated that the proposed MCAT algorithms were successful and there was no loss in measurement proficiency when the control methods were implemented, and among the four methods, the last method performed the best.

Keywords: computerized adaptive testing, ipsative tests, item response theory, pairwise comparison

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

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Authors: Farzingohar Mehrnaz, Yasemi Mehran, Esmaili Zinat, Baharlouian Maedeh

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Aboozar (Ardeshir) and Bahregansar are the two important Iranian oilfields in Persian Gulf waters. The operation activities cause to create spills which impacted on the marine environment. Assumed spills are molded by ADIOS II (Automated Data Inquiry for Oil Spills) which is NOAA’s weathering oil software. Various atmospheric and marine data with different oil types are used for the modeling. Numerous scenarios for 100 bbls with mean daily air temperature and wind speed are input for 5 days. To find the model sensitivity in each setting, one parameter is changed, but the others stayed constant. In both fields, the evaporated and dispersed output values increased hence the remaining rate is reduced. The results clarified that wind speed first, second air temperature and finally oil type respectively were the most effective factors on the oil weathering process. The obtained results can help the emergency systems to predict the floating (dispersed and remained) volume spill in order to find the suitable cleanup tools and methods.

Keywords: ADIOS, modeling, oil spill, sensitivity analysis

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Adil A. Mohammed, Seif-Eddeen K. Fateen, Tamer S. Ahmed, Tarek M. Moustafa

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Falling film were widely used for gas-liquid absorption and reaction process. Modeling of falling film for oligomerization of ethylene reaction to linear alpha olefins is developed. Although there are many researchers discuss modeling of falling film in many processes, there has been no publish study the simulation of falling film for the oligomerization of ethylene reaction to produce linear alpha olefins. The Comsol multiphysics software was used to simulate the mass transfer with chemical reaction in falling film absorption process. The effect of concentration profile absorption of the products through falling thickness is discussed. The effect of catalyst concentration, catalyst/co-catalyst ratio, and temperature is also studied. For the effect of the temperature, as it increase the concentration of C4 increase. For catalyst concentration and catalyst/co-catalyst ratio as they increases the concentration of C4 increases, till it reached almost constant value.

Keywords: falling film, oligomerization, comsol mutiphysics, linear alpha olefins

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Authors: Biruk Wolde, Atalay Ayele, Yonatan Garkabo, Trufat Hailmariam, Zemenu Germewu

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A comprehensive three-dimensional (3D) geological modeling and engineering geological characterization of shallow subsurface soils and rocks are essential for a wide range of geotechnical and seismological engineering applications, particularly in urban environments. The spatial distribution and geological variation of the shallow subsurface of Addis Ababa city have not been studied so far in terms of geological and geotechnical modeling. This study aims at the construction of a 3D geological model, as well as provides awareness into the engineering geological characteristics of shallow subsurface soil and rock of Addis Ababa city. The 3D geological model was constructed by using more than 1500 geotechnical boreholes, well-drilling data, and geological maps. A well-known geostatistical kriging 3D interpolation algorithm was applied to visualize the spatial distribution and geological variation of the shallow subsurface. Due to the complex nature of geological formations, vertical and lateral variation of the geological profiles horizons-solid command has been selected via the Groundwater Modelling System (GMS) graphical user interface software. For the engineering geological characterization of typical soils and rocks, both index and engineering laboratory tests have been used. The geotechnical properties of soil and rocks vary from place to place due to the uneven nature of subsurface formations observed in the study areas. The constructed model ascertains the thickness, extent, and 3D distribution of the important geological units of the city. This study is the first comprehensive research work on 3D geological modeling and subsurface characterization of soils and rocks in Addis Ababa city, and the outcomes will be important for further future research on subsurface conditions in the city. Furthermore, these findings provide a reference for developing a geo-database for the city.

Keywords: 3d geological modeling, addis ababa, engineering geology, geostatistics, horizons-solid

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Authors: Erin Lynne Plettenberg, Jeremy Vickery

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In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.

Keywords: electronic medical records, information extraction, logic modeling, ontology, vetted web mining

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

Procedia PDF Downloads 79