Search results for: leadership models

Authors: Ali Muhammad

Abstract:

The purpose of this study is to develop a theoretical framework which demonstrates the effect of four personal factors on employees rule following behavior in Kuwaiti business organizations. The model suggested in this study includes organizational citizenship behavior, affective organizational commitment, organizational trust, and procedural justice as possible predictors of rule following behavior. The study also attempts to compare the effects of the suggested factors on employees rule following behavior. The new model will, hopefully, extend previous research by adding new variables to the models used to explain employees rule following behavior. A discussion of issues related to rule-following behavior is presented, as well as recommendations for future research.

Keywords: employee adherence to rules, organizational justice, organizational commitment, organizational citizenship behavior

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Authors: Miriam Sosa, Edgar Ortiz, Alejandra Cabello

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This paper examines the volatility changes and leverage effects of the MILA stock markets and their changes since the 2007 global financial crisis. This group integrates the stock markets from Chile, Colombia, Mexico and Peru. Volatility changes and leverage effects are tested with a symmetric GARCH (1,1) and asymmetric TARCH (1,1) models with a dummy variable in the variance equation. Daily closing prices of the stock indexes of Chile (IPSA), Colombia (COLCAP), Mexico (IPC) and Peru (IGBVL) are examined for the period 2003:01 to 2015:02. The evidence confirms the presence of an overall increase in asymmetric market volatility in the Peruvian share market since the 2007 crisis.

Keywords: financial crisis, Latin American Integrated Market, TARCH, GARCH

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Chang Seok Lee, Sang Whan Han, Girbo Ko, Debbie Kim

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Existing reinforced concrete structures are designed and built without considering seismic loads. The columns in such buildings generally exhibit widely spaced transverse reinforcements without using seismic hooks. Due to the insufficient reinforcement details in columns, brittle shear failure is expected in columns that may cause pre-mature building collapse mechanism during earthquakes. In order to retrofit those columns, the accurate seismic behavior of the columns needs to be predicted with proper analytical models. In this study, an analytical model is proposed for accurately simulating the cyclic behavior of shear critical columns. The parameters for pinching and cyclic deterioration in strength and stiffness are calibrated using test data of column specimens failed by shear.

Keywords: analytical model, cyclic deterioration, existing reinforced concrete columns, shear failure

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

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The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Ladislav Écsi, Roland Jančo

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Contemporary multiplicative plasticity models assume that the body's intermediate configuration consists of an assembly of locally unloaded neighbourhoods of material particles that cannot be reassembled together to give the overall stress-free intermediate configuration since the neighbourhoods are not necessarily compatible with each other. As a result, the plastic deformation gradient, an inelastic component in the multiplicative split of the deformation gradient, cannot be integrated, and the material particle moves from the initial configuration to the intermediate configuration without a position vector and a plastic displacement field when plastic flow occurs. Such behaviour is incompatible with the continuum theory and the continuum physics of elastoplastic deformations, and the related material models can hardly be denoted as truly continuum-based. The paper presents a proper continuum-based reformulation of current problems in finite strain plasticity. It will be shown that the incompatible neighbourhoods in real material are modelled by the product of the plastic multiplier and the yield surface normal when the plastic flow is defined in the current configuration. The incompatible plastic factor can also model the neighbourhoods as the solution of the system of differential equations whose coefficient matrix is the above product when the plastic flow is defined in the intermediate configuration. The incompatible tensors replace the compatible spatial plastic velocity gradient in the former case or the compatible plastic deformation gradient in the latter case in the definition of the plastic flow rule. They act as local imperfections but have the same position vector as the compatible plastic velocity gradient or the compatible plastic deformation gradient in the definitions of the related plastic flow rules. The unstressed intermediate configuration, the unloaded configuration after the plastic flow, where the residual stresses have been removed, can always be calculated by integrating either the compatible plastic velocity gradient or the compatible plastic deformation gradient. However, the corresponding plastic displacement field becomes permanent with both elastic and plastic components. The residual strains and stresses originate from the difference between the compatible plastic/permanent displacement field gradient and the prescribed incompatible second-order tensor characterizing the plastic flow in the definition of the plastic flow rule, which becomes an assignment statement rather than an equilibrium equation. The above also means that the elastic and plastic factors in the multiplicative split of the deformation gradient are, in reality, gradients and that there is no problem with the continuum physics of elastoplastic deformations. The formulation is demonstrated in a numerical example using the regularized Mooney-Rivlin material model and modified equilibrium statements where the intermediate configuration is calculated, whose analysis results are compared with the identical material model using the current equilibrium statements. The advantages and disadvantages of each formulation, including their relationship with multiplicative plasticity, are also discussed.

Keywords: finite strain plasticity, continuum formulation, regularized Mooney-Rivlin material model, compatibility

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Authors: S. Dhib, S. A. Addouche, T. Loukil, A. Elmhamedi

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In this paper, a reverse supply chain network is investigated for a decision making. This decision is surrounded by complex flows of returned products, due to the increasing quantity, the type of returned products and the variety of recovery option products (reuse, recycling, and refurbishment). The most important problem in the reverse logistic network (RLN) is to orient returned products to the suitable type of recovery option. However, returned products orientations from collect sources to the recovery disposition have not well considered in performance model. In this study, we propose a performance model for designing a network configuration on reverse logistics. Conceptual and analytical models are developed with taking into account operational, economic and environmental factors on designing network.

Keywords: reverse logistics, network design, performance model, open loop configuration

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Authors: Shonuga Olajumoke Adedoyinsola

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Staffing and Compensation are at the core of any employment exchange, and they serve as the defining characteristics of any employment relationship. Most organizations understand the benefits that a longer term approach to staff planning can bring and the answer to this problem lies not in trying to implement the traditional approach more effectively, but in implementing a completely different kind of process for strategic staffing. The study focuses on critical points of compensation, staffing and personnel management. The fundamentals of these programs include the elements of vision, potential, communication and motivation. The aim of the paper is to identify the most important attributes of compensation and incentives, staffing and personnel management. Research method is the analysis and synthesis of scientific literature, logical, comparative and graphic representation. On the basis of analysis, the author presents the models of these systems for positive employee attitudes and behaviors.

Keywords: compensation, employees, incentives, staffing, personnel management

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Slawomir Lasota, Tomasz Kajdanowicz

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This research examines the application of predictive modelling and optimization algorithms to improve production efficiency in smart factories. Utilizing gradient boosting and neural networks, the study builds robust KPI estimators to predict production outcomes based on real-time data. Optimization methods, including Bayesian optimization and gradient-based algorithms, identify optimal process configurations that maximize availability, efficiency, and quality KPIs. The paper highlights the modular architecture of a recommender system that integrates predictive models, data visualization, and adaptive automation. Comparative analysis across multiple production processes reveals significant improvements in operational performance, laying the foundation for scalable, self-regulating manufacturing systems.

Keywords: predictive modeling, optimization, smart factory, efficiency

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Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Débora V. Busman, Venerando E. Amaro, Mattheus da C. Prudêncio

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Prognostic studies of the shoreline are of utmost importance for Ponta Negra Beach, located in Natal, Northeastern Brazil, where the infrastructure recently built along the shoreline is severely affected by flooding and erosion. This study compares shoreline predictions using three linear regression methods (LMS, LRR and WLR) and tries to discern the best method for different shoreline position scenarios. The methods have shown erosion on the beach in each of the scenarios tested, even in less intense dynamic conditions. The WLA_A with confidence interval of 95% was the well-adjusted model and calculated a retreat of -1.25 m/yr to -2.0 m/yr in hot spot areas. The change of the shoreline on Ponta Negra Beach can be measured as a negative exponential curve. Analysis of these methods has shown a correlation with the morphodynamic stage of the beach.

Keywords: coastal erosion, prognostic model, DSAS, environmental safety

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Authors: Era Dorihi Kale, Sabina Gero, Uly Agustine

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Asylum seekers are people who come to other countries to get asylum. In line with that, they also carry the culture and health behavior of their country, which is very different from the new country they currently live in. This situation raises problems, also in the health sector. The approach taken must also be a culturally sensitive approach, where the culture and habits of the refugee's home area are also valued so that the health services provided can be right on target. Some risk factors that already exist in this group are lack of activity, consumption of fast food, smoking, and stress levels that are quite high. Overall this condition will increase the risk of an increased incidence of cardiovascular disease. This research is a descriptive and experimental study. The purpose of this study is to identify health status and develop a culturally sensitive health promotion model, especially related to the risk of cardiovascular disease for asylum seekers in detention homes in the city of Kupang. This research was carried out in 3 stages, stage 1 was conducting a survey of health problems and the risk of asylum seeker cardiovascular disease, Stage 2 developed a health promotion model, and stage 3 conducted a testing model of health promotion carried out. There were 81 respondents involved in this study. The variables measured were: health status, risk of cardiovascular disease and, health promotion models. Method of data collection: Instruments (questionnaires) were distributed to respondents answered for anamnese health status; then, cardiovascular risk measurements were taken. After that, the preparation of information needs and the compilation of booklets on the prevention of cardiovascular disease is carried out. The compiled booklet was then translated into Farsi. After that, the booklet was tested. Respondent characteristics: average lived in Indonesia for 4.38 years, the majority were male (90.1%), and most were aged 15-34 years (90.1%). There are several diseases that are often suffered by asylum seekers, namely: gastritis, headaches, diarrhea, acute respiratory infections, skin allergies, sore throat, cough, and depression. The level of risk for asylum seekers experiencing cardiovascular problems is 4 high risk people, 6 moderate risk people, and 71 low risk people. This condition needs special attention because the number of people at risk is quite high when compared to the age group of refugees. This is very related to the level of stress experienced by the refugees. The health promotion model that can be used is the transactional stress and coping model, using Persian (oral) and English for written information. It is recommended for health practitioners who care for refugees to always pay attention to aspects of culture (especially language) as well as the psychological condition of asylum seekers to make it easier to conduct health care and promotion. As well for further research, it is recommended to conduct research, especially relating to the effect of psychological stress on the risk of cardiovascular disease in asylum seekers.

Keywords: asylum seekers, health status, cardiovascular disease, health promotion

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: D. Liu, D. M. Donskoy

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The vibroacoustic modulation method is based on the modulation effect of high-frequency ultrasonic wave (carrier) by low-frequency vibration in the presence of various defects, primarily contact-type such as cracks, delamination, etc. The presence and severity of the defect are measured by the ratio of the spectral sidebands and the carrier in the spectrum of the modulated signal. This approach, however, does not differentiate between amplitude and frequency modulations, AM and FM, respectfully. It was experimentally shown that both modulations could be present in the spectrum, yet each modulation may be associated with different physical mechanisms. AM mechanisms are quite well understood and widely covered in the literature. This paper is a first attempt to explain the generation mechanisms of FM and its correlation with the flaw properties. Here we proposed two possible mechanisms leading to FM modulation based on nonlinear local defect resonance and dynamic acousto-elastic models.

Keywords: non-destructive testing, nonlinear acoustics, structural health monitoring, acousto-elasticity, local defect resonance

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Bing Yan

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Nanomaterials are widely used in various industrial sectors, biomedicine, and more than 1300 consumer products. Although there is still no standard safety regulation, their potential toxicity is a major concern worldwide. We discovered that nanoparticles target and enter human cells1, perturb cellular signaling pathways2, affect various cell functions3, and cause malfunctions in animals4,5. Because the majority of atoms in nanoparticles are on the surface, chemistry modification on their surface may change their biological properties significantly. We modified nanoparticle surface using nano-combinatorial chemistry library approach6. Novel nanoparticles were discovered to exhibit significantly reduced toxicity6,7, enhance cancer targeting ability8, or re-program cellular signaling machineries7. Using computational chemistry, quantitative nanostructure-activity relationship (QNAR) is established and predictive models have been built to predict biocompatible nanoparticles.

Keywords: nanoparticle, nanotoxicity, nano-bio, nano-combinatorial chemistry, nanoparticle library

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Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane

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Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.

Keywords: learning city, sustainable creative city, creative industry, good city form

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Authors: Abdol-Hassan Doulah

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In this research, some of the inorganic complexes of uranyl with N- donor ligands were synthesized. Complexes were characteriezed by FT-IR and UV spectra, ¹HNMR, ¹³CNMR and some physical properties. The uranyl unit (UO2) is composed of a center of uranium atom with the charge (+6) and two oxygen atom by forming two U=O double bonds. The structure is linear (O=U=O, 180) and usually stable. So other ligands often coordinate to the U atom in the plane perpendicularly to the O=U=O axis. The antitumor activity of some of ligand and their complexes against a panel of human tumor cell lines (HT29: Haman colon adenocarcinoma cell line T47D: human breast adenocarcinoma cell line) were determined by MTT(3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide) assay. These data suggest that some of these compounds provide good models for the further design of potent antitumor compounds.

Keywords: inorganic, uranyl complex-donor ligands, Schiff bases, anticancer activity

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Authors: Rozanne Janet Smith

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This article examined the corporate governance disclosures of the large and medium-sized auditing firms in South Africa. It is important that auditing firms disclose their practice of good corporate governance to the public, as they serve the public interest. The auditing profession has been criticized due to many corporate scandals in recent years. This has undermined the reputation of the profession, with experts and the public questioning whether auditing firms have corporate governance structures in place, and whether they are taking public interest into consideration. In South Africa there is no corporate governance code specifically for audit firms. Auditing firms are encouraged by IRBA to issue a transparency report in which they disclose corporate governance structures and application, but this is not compulsory in South Africa. Moreover, the information issued in these transparency reports is limited and often only focuses on audit quality, and not governance. Through a literature review it was found that the UK is one of only a few countries who has a corporate governance code for audit firms. As South Africa initially used the UK Cadbury report to develop the King IV Code, it was fitting to use the UK Audit Firm Governance Code as a benchmark to determine if audit firms in South Africa are disclosing relevant corporate governance information in their transparency reports and/or integrated reports. This study contributes to the existing body of knowledge by pursuing the following objective: To determine the improvement in the corporate governance disclosures of large and medium-sized auditing firms in South Africa through comparative research. Available data from 2019 will be used and compared to the disclosures in the 2023/2024 transparency and or integrated reports of the large and medium-sized auditing firms in South Africa. To achieve this objective a constructivist research paradigm was applied. Qualitative secondary information was gathered for the analysis. A content analysis was selected to collect the qualitative data by analyzing the integrated reports and/or transparency reports of large and medium-sized auditing firms with 20 or more partners and to determine what is disclosed on their corporate governance practices. These transparency reports and integrated reports were then read and analyzed in depth and compared to the principles stated in the UK Code. Since there are only nine medium-sized and large auditing firms in South Africa, the researcher was able to conduct the content analysis by reading each report in depth. The following six principles which are found in the UK Code were assessed for disclosure. (1) Leadership, (2) Values, (3) INED, (4) Operations, (5) Reporting, and (6) Dialogue. The results reveal that the auditing firms are not disclosing the corporate governance principles and practices to the necessary extent. Although there has been some improvement, the disclosure is not to the extent which it should be. There is still a need for a South African audit firm governance code.

Keywords: auditing firms, corporate governance, South Africa, disclosure

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Authors: I. Paeglite, A. Paeglitis

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The paper presents a study of dynamic effects obtained from the dynamic load testing of the city highway bridges in Latvia carried out from 2005 to 2012. 9 pre-stressed concrete bridges and 4 composite bridges were considered. 11 of 13 bridges were designed according to the Eurocodes but two according to the previous structural codes used in Latvia (SNIP 2.05.03-84). The dynamic properties of the bridges were obtained by heavy vehicles passing the bridge roadway with different driving speeds and with or without even pavement. The obtained values of the Dynamic amplification factor (DAF) and bridge natural frequency were analyzed and compared to the values of built-in traffic load models provided in Eurocode 1. The actual DAF values for even bridge deck in the most cases are smaller than the value adopted in Eurocode 1. Vehicle speed for uneven pavements significantly influence Dynamic amplification factor values.

Keywords: bridge, dynamic effects, load testing, dynamic amplification factor

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Olga V. Korotkaya

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This article is devoted to an important problem of calculation of deflected mode of the combustion chamber and the nozzle end of a new liquid-propellant rocket cruise engine. A special attention is given to the methodology of calculation. Three operating modes are considered. The analysis has been conducted in ANSYS software. The methods of conducted research are mathematical modelling, substructure method, cyclic symmetry, and finite element method. The calculation has been carried out to order of S. P. Korolev Rocket and Space Corporation «Energia». The main results are practical. Proposed methodology and created models would be able to use for a wide range of strength problems.

Keywords: combustion chamber, cyclic symmetry, finite element method, liquid-propellant rocket engine, nozzle end, substructure

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

Abstract:

With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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