Search results for: Finite Mixture Models

Authors: Alireza Nikravanshallmani, Jamshid Dehmeshki, Mojtaba Ahmadi

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Modeling of business processes, based on BPMN (Business Process Modeling Notation), helps analysts and managers to understand business processes, and, identify their shortages. These models provide a context to make rational decision of organizing business processes activities in an understandable manner. The purpose of this paper is to provide a framework for better understanding of business processes and their problems by reducing the cognitive load of displayed information for their audience at different managerial levels while keeping the essential information which are needed by them. For this reason, we integrate business process diagrams across the different managerial levels to develop a framework to improve the performance of business process management (BPM) projects. The proposed framework is entitled ‘Business process improvement framework based on managerial levels (BPIML)’. This framework, determine a certain type of business process diagrams (BPD) based on BPMN with respect to the objectives and tasks of the various managerial levels of organizations and their roles in BPM projects. This framework will make us able to provide the necessary support for making decisions about business processes. The framework is evaluated with a case study in a real business process improvement project, to demonstrate its superiority over the conventional method. A questionnaire consisted of 10 questions using Likert scale was designed and given to the participants (managers of Bank Refah Kargaran three managerial levels). By examining the results of the questionnaire, it can be said that the proposed framework provide support for correct and timely decisions by increasing the clarity and transparency of the business processes which led to success in BPM projects.

Keywords: business process management (BPM), business process modeling, business process reengineering (BPR), business process optimizing, BPMN

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Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

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Authors: Mustapha Kamel Mihoubi, Mohamed Essadik Kerkar

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Probabilistic risk analysis models are used to provide a better understanding of the reliability and structural failure of works, including when calculating the stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of reliability analysis methods including the methods used in engineering. It is in our case, the use of level 2 methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type first order risk method (FORM) and the second order risk method (SORM). By way of comparison, a level three method was used which generates a full analysis of the problem and involves an integration of the probability density function of random variables extended to the field of security using the Monte Carlo simulation method. Taking into account the change in stress following load combinations: normal, exceptional and extreme acting on the dam, calculation of the results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities, thus causing a significant decrease in strength, shear forces then induce a shift that threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case the increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit-state, monte-carlo, reliability, probability, simulation, sliding, taylor

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Authors: Maria Florencia Ferrer, Saulo Fabiano Amancio-Vieira

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The use of the blockchain in the public sector is present today and no longer the future of disruptive institutional and technological models. There are still some cultural barriers and resistance to the proper use of its potential. This research aims to present the strengths and weaknesses of using a public-permitted and distributed network in the context of the public sector. Therefore, bibliographical/documentary research was conducted to raise the main aspects of the studied platform, focused on the use of the main demands of the public sector. The platform analyzed was LACChain, which is a global alliance composed of different actors in the blockchain environment, led by the Innovation Laboratory of the Inter-American Development Bank Group (IDB Lab) for the development of the blockchain ecosystem in Latin America and the Caribbean. LACChain provides blockchain infrastructure, which is a distributed ratio technology (DLT). The platform focuses on two main pillars: community and infrastructure. It is organized as a consortium for the management and administration of an infrastructure classified as public, following the ISO typologies (ISO / TC 307). It is, therefore, a network open to any participant who agrees with the established rules, which are limited to being identified and complying with the regulations. As benefits can be listed: public network (open to all), decentralized, low transaction cost, greater publicity of transactions, reduction of corruption in contracts / public acts, in addition to improving transparency for the population in general. It is also noteworthy that the platform is not based on cryptocurrency and is not anonymous; that is, it is possible to be regulated. It is concluded that the use of record platforms, such as LACChain, can contribute to greater security on the part of the public agent in the migration process of their informational applications.

Keywords: blockchain, LACChain, public sector, technological disruptions

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Authors: Gehan F. Abdel Raoof, Ataa A. Said, Khaled Y. Mohamed, Hala M. Mohammed

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Pleiogynium timorense(DC.) Leenh is one of the therapeutically active plants belonging to the family Anacardiaceae. The bark of Pleiogynium timorense needs further studies to investigate its phytochemical and biological activities. This work was carried out to investigate the chemical composition of petroleum ether extract of Pleiogynium timorense bark as well as to evaluate the analgesic and anti-inflammatory activities. The unsaponifiable matter and fatty acid methyl esters were analyzed by Gas chromatography–mass spectrometry (GC-MS). Moreover, analgesic and anti-inflammatory activities were evaluated using acetic acid-induced writhing test and carrageen hind paw oedema models in rats, respectively. The results showed that twenty one compounds in the unsaponifiable fraction were identified representing 92.54 % of the total beak area, the major compounds were 1-Heptene (35.32%), Butylated hydroxy toluene (19.42%) and phytol (12.53%), whereas fifteen compounds were identified in the fatty acid methyl esters fraction representing 94.15% of the total identified peak area. The major compounds were 9-Octadecenoic acid methyl ester (35.34%) and 9,12-Octadecadienoic acid methyl ester (29.32%). Moreover, petroleum ether extract showed a significant reduction in pain and inflammation in a dose dependent manner. This study aims to be the first step toward the use of petroleum ether extract of Pleiogynium timorense bark as analgesic and anti-inflammatory drug.

Keywords: analgesic, anti-inflammatory, bark, petroleum ether extract, Pleiogynium timorense

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Authors: Francisco J. Ortega, Claudia Roman, Moisés García-Morales, Francisco J. Navarro

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Asphaltic bitumen has been largely used in both industrial and civil engineering, mostly in pavement construction and roofing membrane manufacture. However, bitumen as such is greatly susceptible to temperature variations, and dramatically changes its in-service behavior from a viscoelastic liquid, at medium-high temperatures, to a brittle solid at low temperatures. Bitumen modification prevents these problems and imparts improved performance. Isocyanates like polymeric MDI (mixture of 4,4′-diphenylmethane di-isocyanate, 2,4’ and 2,2’ isomers, and higher homologues) have shown to remarkably enhance bitumen properties at the highest in-service temperatures expected. This comes from the reaction between the –NCO pendant groups of the oligomer and the most polar groups of asphaltenes and resins in bitumen. In addition, oxygen diffusion and/or UV radiation may provoke bitumen hardening and ageing. With the purpose of minimizing these effects, nano-layered-silicates (nanoclays) are increasingly being added to bitumen formulations. Montmorillonites, a type of naturally occurring mineral, may produce a nanometer scale dispersion which improves bitumen thermal, mechanical and barrier properties. In order to increase their lipophilicity, these nanoclays are normally treated so that organic cations substitute the inorganic cations located in their intergallery spacing. In the present work, the combined effect of polymeric MDI and the commercial montmorillonite Cloisite® 20A was evaluated. A selected bitumen with penetration within the range 160/220 was modified with 10 wt.% Cloisite® 20A and 2 wt.% polymeric MDI, and the resulting ternary composites were characterized by linear rheology, X-ray diffraction (XRD) and Atomic Force Microscopy (AFM). The rheological tests evidenced a notable solid-like behavior at the highest temperatures studied when bitumen was just loaded with 10 wt.% Cloisite® 20A and high-shear blended for 20 minutes. However, if polymeric MDI was involved, the sequence of addition exerted a decisive control on the linear rheology of the final ternary composites. Hence, in bitumen/Cloisite® 20A/polymeric MDI formulations, the previous solid-like behavior disappeared. By contrast, an inversion in the order of addition (bitumen/polymeric MDI/ Cloisite® 20A) enhanced further the solid-like behavior imparted by the nanoclay. In order to gain a better understanding of the factors that govern the linear rheology of these ternary composites, a morphological and microstructural characterization based on XRD and AFM was conducted. XRD demonstrated the existence of clay stacks intercalated by bitumen molecules to some degree. However, the XRD technique cannot provide detailed information on the extent of nanoclay delamination, unless the entire fraction has effectively been fully delaminated (situation in which no peak is observed). Furthermore, XRD was unable to provide precise knowledge neither about the spatial distribution of the intercalated/exfoliated platelets nor about the presence of other structures at larger length scales. In contrast, AFM proved its power at providing conclusive information on the morphology of the composites at the nanometer scale and at revealing the structural modification that yielded the rheological properties observed. It was concluded that high-shear blending brought about a nanoclay-reinforced network. As for the bitumen/Cloisite® 20A/polymeric MDI formulations, the solid-like behavior was destroyed as a result of the agglomeration of the nanoclay platelets promoted by chemical reactions.

Keywords: Atomic Force Microscopy, bitumen, composite, isocyanate, montmorillonite.

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Authors: Hasan Basaran, Emre Unal

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Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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Authors: Yousef Sharrab, Dimah Al-Fraihat, Monther Tarawneh, Aysh Alhroob, Ala’ Khalifeh, Nabil Sarhan

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This paper explores the evolution of Electrical Engineering (EE) and Computer Science (CS) education in higher learning, examining the feasibility of unifying them into Electrical Engineering and Computer Science (EECS) for the technology industry. It delves into the historical reasons for their separation and underscores the need for integration. Emerging technologies such as AI, Virtual Reality, IoT, Cloud Computing, and Cybersecurity demand an integrated EE and CS program to enhance students' understanding. The study evaluates curriculum integration models, drawing from prior research and case studies, demonstrating how integration can provide students with a comprehensive knowledge base for industry demands. Successful integration necessitates addressing administrative and pedagogical challenges. For academic institutions considering merging EE and CS programs, the paper offers guidance, advocating for a flexible curriculum encompassing foundational courses and specialized tracks in computer engineering, software engineering, bioinformatics, information systems, data science, AI, robotics, IoT, virtual reality, cybersecurity, and cloud computing. Elective courses are emphasized to keep pace with technological advancements. Implementing this integrated approach can prepare students for success in the technology industry, addressing the challenges of a technologically advanced society reliant on both EE and CS principles. Integrating EE and CS curricula is crucial for preparing students for the future.

Keywords: electrical engineering, computer science, EECS, curriculum integration of EE and CS

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Authors: Chen Zhang; Qiang Wang

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With the rapid development of the new generation of digital technology, various industries have created more and more value by using digital technology, accelerating the digital transformation of various industries. The economic form of human society has evolved with the progress of technology, and in this context, the power conversion, transformation and upgrading of the manufacturing industry in terms of quality, efficiency and energy change has become a top priority. Based on the digitalization background, this paper analyzes the transformation and upgrading efficiency of the manufacturing industry and evaluates the impact of the driving factors, which have very important theoretical and practical significance. This paper utilizes qualitative research methods, entropy methods, data envelopment analysis methods and econometric models to explore the transformation and upgrading efficiency of manufacturing enterprises and driving factors. The study shows that the transformation and upgrading efficiency of the manufacturing industry shows a steady increase, and regions rich in natural resources and social resources provide certain resources for transformation and upgrading. The ability of scientific and technological innovation has been improved, but there is still much room for progress in the transformation of scientific and technological innovation achievements. Most manufacturing industries pay more attention to green manufacturing and sustainable development. In addition, based on the existing problems, this paper puts forward suggestions for improving infrastructure construction, developing the technological innovation capacity of enterprises, green production and sustainable development.

Keywords: digitization, manufacturing firms, transformation and upgrading, efficiency, driving factors

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Authors: Mohammed Sherzad

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The Sahara desert covers third of the total surface of Africa with a quarter of this area within the national boundaries of Algeria. Sand drift and deposition is considered one of the major factors of the desertification process in the area. It is estimated that a third of the world's hot arid lands are covered by aeolian sand deposits, forming extensive sand bedforms. The Gourrara region in the Grand Erg Occidental (west of Algerian Sahara) and the region of Souf in the Grand Erg Oriental (east of Algerian Sahara) have been chosen as case studies. These were significant cultural and trading centers for many centuries despite their remote location and their harsh desert environment particularly solar radiation and sand drift and deposition. The architecture of the sustained vernacular settlements in each of the two regions has unique design features for this environment. So do the irrigation systems used - palm groves and the foggara system for capturing and distributing groundwater. However, the ecological balance which enabled the Saharans to live with the desert has been upset. New buildings often use technology based on models imported or imposed from areas that climatically have little in common. These make the inhabitants live ‘in the desert’ rather than ‘with the desert’. This paper will describe the qualities of the vernacular architecture and demonstrate its effectiveness and adaptability to the region’s harsh desert environment in comparison with contemporary buildings. Developing design guides and approaches based on lessons from the traditional architecture is important to ensure sustained livelihoods of the inhabitants in these areas.

Keywords: vernacular architecture, desert architecture, hot climate, aeolian sand deposition

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Authors: Yu-Cheng Lin, Yu-Chih Su

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Generally, there are many numerous existing problems during the construction phase special in civil engineering. The problems communication and management (PCM) of civil engineering are important and necessary to enhance the performance of construction management. The civil information modelling (CIM) approach is used to retain information with digital format and assist easy updating and transferring of information in the 3D environment for all related civil and infrastructure projects. When the application of CIM technology is adopted in infrastructure projects, all the related project participants can discuss problems and obtain feedback and responds among project participants integrated with the assistance of CIM models 3D illustration. Usually, electronic mail (e-mail) is one of the most popular communication tools among all related participants for rapid transit system (MRT), also known as a subway or metro, construction project in Taiwan. Furthermore, all interfaces should be traced and managed effectively during the process. However, there are many problems with the use of e-mail for communication of all interfaces. To solve the above problems, this study proposes a CIM-based Problem Communication and Management (CPCM) system to improve performance of problem communication and management. The CPCM system is applied to a case study of an MRT project in Taiwan to identify its CPCM effectiveness. Case study results show that the proposed CPCM system and Markup-enabled CIM Viewer are effective CIM-based communication tools in CIM-supported PCM work of civil engineering. Finally, this study identifies conclusion, suggestion, benefits, and limitations for further applications.

Keywords: building information modeling, civil information modeling, infrastructure, general contractor

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Authors: Rahul Paliwal, Gulshan Maheshwari, Anant S. Jhaveri, Channamallikarjun S. Mathpati

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Large pumping facility is the necessary requirement of the cooling water systems for power plants, process and manufacturing facilities, flood control and water or waste water treatment plant. With a large capacity of few hundred to 50,000 m3/hr, cares must be taken to ensure the uniform flow to the pump to limit vibration, flow induced cavitation and performance problems due to formation of air entrained vortex and swirl flow. Successful prediction of these phenomena requires numerical method and turbulence model to characterize the dynamics of these flows. In the past years, single phase shear stress transport (SST) Reynolds averaged Navier Stokes Models (like k-ε, k-ω and RSM) were used to predict the behavior of flow. Literature study showed that two phase model will be more accurate over single phase model. In this paper, a 3D geometries simulated using detached eddy simulation (LES) is used to predict the behavior of the fluid and the results are compared with experimental results. Effect of different grid structure and boundary condition is also studied. It is observed that two phase flow model can more accurately predict the mean flow and turbulence statistics compared to the steady SST model. These validate model will be used for further analysis of vortex structure in lab scale model to generate their frequency-plot and intensity at different location in the set-up. This study will help in minimizing the ill effect of vortex on pump performance.

Keywords: grid structure, pump intake, simulation, vibration, vortex

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Authors: Anu Jose, Sapna Nair

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By using the baseline data of a randomized cluster trial aiming to understand the effects of social, technological and business innovation on child development in two districts of Tamil Nadu, India, we examine the determinants of father involvement in childcare. While there is a growing literature on the role of fathers in child development and family systems, we particularly look at the effect of the attitude of mother and father towards father's involvement in childcare in rural South India. We find that father's own attitude and the mother's gatekeeping attitude significantly affect the father's behavior when other socio-economic characteristics of the parents are controlled. Further, the results are corroborated using different empirical models in which father involvement is conceptualized into three categories broadly; play, caretaking, and affection. We also examine the other socio-economic characteristics affecting paternal involvement using both quantitative and qualitative methods. For instance, child characteristics such as the age and birth order have a significant influence on the level of paternal involvement. That is, older the child, the more involved the father is and the father gets more involved in childcare of the second child as compared to the first child. The participants of the study included 1516 children of age 0 to 22 months from 1476 households. Results indicate that fathers of households where the mother and the father have less traditional attitude exhibit a higher level of involvement in childcare as opposed to parents having a more traditional attitude towards gender role in parenting. The results of this paper provide a major policy lesson aiming to improve paternal involvement in childcare.

Keywords: child development, father involvement, gender, parent’s attitude towards paternal involvement

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Authors: Rakesh Kumar, Fatima Electricwala

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One of the major thrusts of the Bus Rapid Transit System is to reduce the commuter’s dependency on private vehicles and increase the shares of public transport to make urban transportation system environmentally sustainable. In this study, commuter mode choice analysis is performed that examines behavioral responses to the proposed Bus Rapid Transit System (BRTS) in Surat, with estimation of the probable shift from private mode to public mode. Further, evaluation of the BRTS scenarios, using Surat’s transportation ecological footprint was done. A multi-modal simulation model was developed in Biogeme environment to explicitly consider private users behaviors and non-linear environmental impact. The data of the different factors (variables) and its impact that might cause modal shift of private mode users to proposed BRTS were collected through home-interview survey using revealed and stated preference approach. A multi modal logit model of mode-choice was then calibrated using the collected data and validated using proposed sample. From this study, a set of perception factors, with reliable and predictable data base, to explain the variation in modal shift behaviour and their impact on Surat’s ecological environment has been identified. A case study of the proposed BRTS connecting the Surat Industrial Hub to the coastal area is provided to illustrate the approach.

Keywords: BRTS, private modes, mode choice models, ecological footprint

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Ali Momeni

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Visual media has had a significant impact on the mental structure and behaviors of humanity. One interactive platform that has played a major role in this is Instagram. In Islamic countries, particularly Iran, many Muslims have embraced this interactive media platform for various reasons. Instagram has also provided an opportunity for individuals to become famous and gain micro-celebrity status through its semi-algorithmic features. A notable group of Iranian women who have gained fame through Instagram are religious Muslim women who have transitioned into bloggers. These Iranian religious women bloggers (IRWB) have garnered a large following by showcasing different models of hijab and their private lives. This research aims to qualitatively study the representation of femininity and religiosity of these women. The main question addressed in this study is the acceptance of Instagram activity by IRWB among religious women. Drawing on concepts such as 'The Society of the Spectacle' and 'Celebrity Online', this study utilized the netnography method to analyze 14 pages of IRWB. Data was collected in two phases, with the first phase involving the analysis of religious women's comments on posts related to these themes. The second phase included interviews with religious women students who view or follow these pages. A total of 120 comments and 14 interviews were thematically analyzed. The results revealed that the reception of these pages by religious women fell into four main themes: the spectacle of femininity, the commercialization of religiosity, the distortion of Islam, and the construction of religiosity and femininity. Ultimately, religious women did not find these pages to be reflective of their own experiences of female and religious life.

Keywords: women, bloggers, instagram, IRWB, reception.

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Authors: Yu-Chi Chou

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The purpose of this study was to establish a logical path of an instructional model of empathy and social regulation, providing feasibility evidence on the model implementation in students with autism spectrum disorder (ASD). This newly developed Emotional Bug-Out Bag (BoB) curriculum was designed to enhance the empathy and socially shared regulation of students with ASD. The BoB model encompassed three instructional phases of basic theory lessons (BTL), action plan practices (APP), and final theory practices (FTP) during implementation. Besides, a learning flow (teacher-directed instruction, student self-directed problem-solving, group-based task completion, group-based reflection) was infused into the progress of instructional phases to deliberately promote the social regulatory process in group-working activities. A total of 23 junior high school students with ASD were implemented with the BoB curriculum. To examine the logical path for model implementation, data was collected from the participating students’ self-report scores on the learning nodes and understanding questions. Path analysis using structural equation modeling (SEM) was utilized for analyzing scores on 10 learning nodes and 41 understanding questions through the three phases of the BoB model. Results showed (a) all participants progressed throughout the implementation of the BoB model, and (b) the models of learning nodes and phases were positive and significant as expected, confirming the hypothesized logic path of this curriculum.

Keywords: autism spectrum disorder, empathy, regulation, socially shared regulation

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Authors: Ghulam Muhammad Ali

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Unveiling of genes involved in drought and root architecture using transcriptomic analyses remained fragmented for further improvement of wheat through genome editing. The purpose of this research endeavor was to unveil the variations in different genes implicated in drought tolerance and root architecture in wheat through RNA-seq data analysis. In this study seedlings of 8 days old, 6 cultivars of wheat namely, Batis, Blue Silver, Local White, UZ888, Chakwal 50 and Synthetic wheat S22 were subjected to transcriptomic analysis for root and shoot genes. Total of 12 RNA samples was sequenced by Illumina. Using updated wheat transcripts from Ensembl and IWGC references with 54,175 gene models, we found that 49,621 out of 54,175 (91.5%) genes are expressed at an RPKM of 0.1 or more (in at least 1 sample). The number of genes expressed was higher in Local White than Batis. Differentially expressed genes (DEG) were higher in Chakwal 50. Expression-based clustering indicated conserved function of DRO1and RPK1 between Arabidopsis and wheat. Dendrogram showed that Local White is sister to Chakwal 50 while Batis is closely related to Blue Silver. This study flaunts transcriptomic sequence variations in different cultivars that showed mutations in genes associated with drought that may directly contribute to drought tolerance. DRO1 and RPK1 genes were fetched/isolated for genome editing. These genes are being edited in wheat through CRISPR-Cas9 for yield enhancement.

Keywords: transcriptomic, wheat, genome editing, drought, CRISPR-Cas9, yield enhancement

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Authors: Simone Rondelli, Damiano Rondelli, Bishesh Poudyal, Juan Jose Cabrera-Lazarini

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One of the main obstacles for Social Entrepreneurship is to find a business model that is financially sustainable. In other words, the captured value generates enough cash flow to ensure business continuity and reinvestment for growth. Providing Health Services in poor countries for the uninsured population affected by a high-cost chronical disease is not the exception for this challenge. As a prime example, cancer has become a high impact on a global disease not only because of the high morbidity but also of the financial impact on both the patient family and health services in underdeveloped countries. Therefore, it is relevant to find a Social Entrepreneurship Model that provides affordable treatment for this disease while maintaining healthy finances not only for the patient but also for the organization providing the treatment. Using the methodology of Constructive Research, this paper applied a Positive Theory and four business models of Social Entrepreneurship to a case of a Private Foundation model whose mission is to address the challenge previously described. It was found that the Foundation analyzed, in this case, is organized as an Embedded Business Model and complies with the four propositions of the Positive Theory considered. It is recommended for this Private Foundation to explore implementing the Integrated Business Model to ensure more robust sustainability in the long term. It evolves as a scalable model that can attract investors interested in contributing to expanding this initiative globally.

Keywords: affordable treatment, global healthcare, social entrepreneurship theory, sustainable business model

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Mustapha Rilwan Adewale, Salau Ayobami Muhammed

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This study focuses on the heat transfer analysis of magneto-hydrodynamics (MHD) squeezing flow between parallel disks, considering a viscous incompressible fluid. The upper disk exhibits both upward and downward motion, while the lower disk remains stationary but permeable. By employing similarity transformations, a system of nonlinear ordinary differential equations is derived to describe the flow behavior. To solve this system, a numerical approach, namely the Chebyshev collocation method, is utilized. The study investigates the influence of flow parameters and compares the obtained results with existing literature. The significance of this research lies in understanding the heat transfer characteristics of MHD squeezing flow, which has practical implications in various engineering and industrial applications. By employing the similarity transformations, the complex governing equations are simplified into a system of nonlinear ordinary differential equations, facilitating the analysis of the flow behavior. To obtain numerical solutions for the system, the Chebyshev collocation method is implemented. This approach provides accurate approximations for the nonlinear equations, enabling efficient computations of the heat transfer properties. The obtained results are compared with existing literature, establishing the validity and consistency of the numerical approach. The study's major findings shed light on the influence of flow parameters on the heat transfer characteristics of the squeezing flow. The analysis reveals the impact of parameters such as magnetic field strength, disk motion amplitude, fluid viscosity on the heat transfer rate between the disks, the squeeze number(S), suction/injection parameter(A), Hartman number(M), Prandtl number(Pr), modified Eckert number(Ec), and the dimensionless length(δ). These findings contribute to a comprehensive understanding of the system's behavior and provide insights for optimizing heat transfer processes in similar configurations. In conclusion, this study presents a thorough heat transfer analysis of magneto-hydrodynamics squeezing flow between parallel disks. The numerical solutions obtained through the Chebyshev collocation method demonstrate the feasibility and accuracy of the approach. The investigation of flow parameters highlights their influence on heat transfer, contributing to the existing knowledge in this field. The agreement of the results with previous literature further strengthens the reliability of the findings. These outcomes have practical implications for engineering applications and pave the way for further research in related areas.

Keywords: squeezing flow, magneto-hydro-dynamics (MHD), chebyshev collocation method(CCA), parallel manifolds, finite difference method (FDM)

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Authors: Cátia Gonçalves, Teresa Nunes, Inês Pina, Ana Vicente, C. Alves, Felix Charvet, Daniel Neves, A. Matos

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The production of charcoal relies on rudimentary technologies using traditional brick kilns. Charcoal is produced under pyrolysis conditions: breaking down the chemical structure of biomass under high temperature in the absence of air. The amount of the pyrolysis products (charcoal, pyroligneous extract, and flue gas) depends on various parameters, including temperature, time, pressure, kiln design, and wood characteristics like the moisture content. This activity is recognized for its inefficiency and high pollution levels, but it is poorly characterized. This activity is widely distributed and is a vital economic activity in certain regions of Portugal, playing a relevant role in the management of woody residues. The location of the units establishes the biomass used for charcoal production. The Portalegre district, in the Alto Alentejo region (Portugal), is a good example, essentially with rural characteristics, with a predominant farming, agricultural, and forestry profile, and with a significant charcoal production activity. In this district, a recent inventory identifies almost 50 charcoal production units, equivalent to more than 450 kilns, of which 80% appear to be in operation. A field campaign was designed with the objective of determining the composition of the emissions released during a charcoal production cycle. A total of 30 samples of particulate matter and 20 gas samples in Tedlar bags were collected. Particulate and gas samplings were performed in parallel, 2 in the morning and 2 in the afternoon, alternating the inlet heads (PM₁₀ and PM₂.₅), in the particulate sampler. The gas and particulate samples were collected in the plume as close as the emission chimney point. The biomass (dry basis) used in the carbonization process was a mixture of cork oak (77 wt.%), holm oak (7 wt.%), stumps (11 wt.%), and charred wood (5 wt.%) from previous carbonization processes. A cylindrical batch kiln (80 m³) with 4.5 m diameter and 5 m of height was used in this study. The composition of the gases was determined by gas chromatography, while the particulate samples (PM₁₀, PM₂.₅) were subjected to different analytical techniques (thermo-optical transmission technique, ion chromatography, HPAE-PAD, and GC-MS after solvent extraction) after prior gravimetric determination, to study their organic and inorganic constituents. The charcoal production cycle presents widely varying operating conditions, which will be reflected in the composition of gases and particles produced and emitted throughout the process. The concentration of PM₁₀ and PM₂.₅ in the plume was calculated, ranging between 0.003 and 0.293 g m⁻³, and 0.004 and 0.292 g m⁻³, respectively. Total carbon, inorganic ions, and sugars account, in average, for PM10 and PM₂.₅, 65 % and 56 %, 2.8 % and 2.3 %, 1.27 %, and 1.21 %, respectively. The organic fraction studied until now includes more than 30 aliphatic compounds and 20 PAHs. The emission factors of particulate matter to produce charcoal in the traditional kiln were 33 g/kg (wooddb) and 27 g/kg (wooddb) for PM₁₀ and PM₂.₅, respectively. With the data obtained in this study, it is possible to fill the lack of information about the environmental impact of the traditional charcoal production in Portugal. Acknowledgment: Authors thanks to FCT – Portuguese Science Foundation, I.P. and to Ministry of Science, Technology and Higher Education of Portugal for financial support within the scope of the project CHARCLEAN (PCIF/GVB/0179/2017) and CESAM (UIDP/50017/2020 + UIDB/50017/2020).

Keywords: brick kilns, charcoal, emission factors, PAHs, total carbon

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Authors: Euphrasia Susy Suhendra, Lies Handrijaningsih

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The banking sector as an intermediary party or intermediaries occupies a very important position in bridging the needs of working capital investment in the real sector with funds owner. This will certainly make money more effectively to improve the economic value added. As an intermediary, Islamic banks raise funds from the public and then distribute in the form of financing. In practice, the distribution of funding that is run by Islamic Banking is not as easy as, in theory, because, in fact, there are many financing problems; some are caused by lacking the assessment and supervision of banks to customers. This study aims to analyze the influence of the Third Party Funds, Return on Assets (ROA), Non Performing Financing (NPF), and Financing Deposit Ratio (FDR) to Total Financing provided to the Community by Islamic Banks in Indonesia. The data used is monthly data released by Bank of Indonesia in Islamic Banking Statistics in the time period of January 2009 - December 2013. This study uses cointegration test to see the long-term relationship, and use error correction models to examine the relationship of short-term. The results of this study indicate that the Third Party Fund has a short-term effect on total funding, Return on Assets has a long term effect on the total financing, Non Performing Financing has long-term effects of total financing, and Financing deposit ratio has the effect of short-term and long-term of the total financing provided by Islamic Banks in Indonesia.

Keywords: Islamic banking, third party fund, return on asset, non-performing financing, financing deposit ratio

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Authors: Yiannis Vacanas, Kyriacos Themistocleous, Athos Agapiou, Diofantos Hadjimitsis

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Building Information Modelling (BIM) technology is considered by construction professionals as a very valuable process in modern design, procurement and project management. Construction professionals of all disciplines can use a single 3D model which BIM technology provides, to design a project accurately and furthermore monitor the progress of construction works effectively and efficiently. Unmanned Aerial Vehicles (UAVs), a technology initially developed for military applications, is now without any difficulty accessible and has already been used by commercial industries, including the construction industry. UAV technology has mainly been used for collection of images that allow visual monitoring of building and civil engineering projects conditions in various circumstances. UAVs, nevertheless, have undergone significant advances in equipment capabilities and now have the capacity to acquire high-resolution imagery from many angles in a cost effective manner, and by using photogrammetry methods, someone can determine characteristics such as distances, angles, areas, volumes and elevations of an area within overlapping images. In order to examine the potential of using a combination of BIM and UAV technologies in construction project management, this paper presents the results of a case study of a typical road construction project where the combined use of the two technologies was used in order to achieve efficient and accurate as-built data collection of the works progress, with outcomes such as volumes, and production of sections and 3D models, information necessary in project progress monitoring and efficient project management.

Keywords: BIM, project management, project monitoring, UAV

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

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Authors: Ali H. Daraji, Ye Jianqiao

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The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Nosheen Fatima Warraich

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One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

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