Search results for: panel regression techniques

Authors: Gurinder Singh, Kulbir Singh

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Digital multimedia contents such as image, video, and audio can be tampered easily due to the availability of powerful editing softwares. Multimedia forensics is devoted to analyze these contents by using various digital forensic techniques in order to validate their authenticity. Digital image forensics is dedicated to investigate the reliability of digital images by analyzing the integrity of data and by reconstructing the historical information of an image related to its acquisition phase. In this paper, a survey is carried out on the forgery detection by considering the most recent and promising digital image forensic techniques.

Keywords: Computer Forensics, Multimedia Forensics, Image Ballistics, Camera Source Identification, Forgery Detection

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Authors: Hakeem Ade Omokayode Idowu

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The extent of the role played by human capabilities developments as well as knowledge management on employees’ performance in the nuclear energy sector of Nigeria remains unclear. This is in view of the important role which human resource capabilities could play in the desire to generate energy using nuclear resources. This study appraised the extent of human resource capabilities available in the nuclear energy sector of Nigeria. It further examined the relationship between knowledge management and employees’ performance in the nuclear energy sector. The study adopted a descriptive research design with a population that comprised all the 1736 members of staff of the selected centres, institutes, and the headquarters of the Nigeria Atomic Energy Commission (NAEC), Nigerian Nuclear Regulatory Authority (NNRA), and Energy Commission of Nigeria (ECN) and a sample size of 332 employees was selected using purposive and convenience sampling techniques. Data collected were subjected to analysis using frequency counts and simple regression. The results showed that majority of the employees perceived that they have to a high extent of availability of knowledge (118, 35.5%), credibility (134, 40.4%), alignment (130, 39.2%), performance (126, 38%) and innovation (138, 41.6%) The result of the hypothesis tested indicated that knowledge management has a positive and significant effect on employees’ performance (Beta weight = 0.336, R2 =0.113, F-value = 41.959, p-value = 0.000< 0.05). The study concluded that human resource capabilities and knowledge management could enhance employee performance within the nuclear energy sector of Nigeria.

Keywords: human resource capabilities, knowledge management, employees productivity, national development

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

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Authors: Haoming Ma, Guo Yu, Peiru Zhou

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Background: Previous studies show that dysglycemia, mostly hyperglycemia, hypoglycemia and glycemic variability(GV), are associated with excess mortality in critically ill patients, especially those without diabetes. Glycemic variability is an increasingly important measure of glucose control in the intensive care unit (ICU) due to this association. However, there is limited data pertaining to the relationship between different clinical factors and glycemic variability and clinical outcomes categorized by their DM status. This retrospective study of 958 intensive care unit(ICU) patients was conducted to investigate the relationship between GV and outcome in critically ill patients and further to determine the significant factors that contribute to the glycemic variability. Aim: We hypothesize that the factors contributing to mortality and the glycemic variability are different from critically ill patients with or without diabetes. And the primary aim of this study was to determine which dysglycemia (hyperglycemia\hypoglycemia\glycemic variability) is independently associated with an increase in mortality among critically ill patients in different groups (DM/Non-DM). Secondary objectives were to further investigate any factors affecting the glycemic variability in two groups. Method: A total of 958 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The glycemic variability was defined as the coefficient of variation (CV) of blood glucose. The main outcome was death during hospitalization. The secondary outcome was GV. The logistic regression model was used to identify factors associated with mortality. The relationships between GV and other variables were investigated using linear regression analysis. Results: Information on age, APACHE II score, GV, gender, in-ICU treatment and nutrition was available for 958 subjects. Predictors remaining in the final logistic regression model for mortality were significantly different in DM/Non-DM groups. Glycemic variability was associated with an increase in mortality in both DM(odds ratio 1.05; 95%CI:1.03-1.08,p＜0.001) or Non-DM group(odds ratio 1.07; 95%CI:1.03-1.11,p=0.002). For critically ill patients without diabetes, factors associated with glycemic variability included APACHE II score(regression coefficient, 95%CI:0.29,0.22-0.36,p＜0.001), Mean BG(0.73,0.46-1.01,p＜0.001), total parenteral nutrition(2.87,1.57-4.17,p＜0.001), serum albumin(-0.18,-0.271 to -0.082,p＜0.001), insulin treatment(2.18,0.81-3.55,p=0.002) and duration of ventilation(0.006,0.002-1.010,p=0.003).However, for diabetes patients, APACHE II score(0.203,0.096-0.310,p＜0.001), mean BG(0.503,0.138-0.869,p=0.007) and duration of diabetes(0.167,0.033-0.301,p=0.015) remained as independent risk factors of GV. Conclusion: We found that the relation between dysglycemia and mortality is different in the diabetes and non-diabetes groups. And we confirm that GV was associated with excess mortality in DM or Non-DM patients. Furthermore, APACHE II score, Mean BG, total parenteral nutrition, serum albumin, insulin treatment and duration of ventilation were significantly associated with an increase in GV in Non-DM patients. While APACHE II score, mean BG and duration of diabetes (years) remained as independent risk factors of increased GV in DM patients. These findings provide important context for further prospective trials investigating the effect of different clinical factors in critically ill patients with or without diabetes.

Keywords: diabetes, glycemic variability, predictors, severe disease

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Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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Watercourses in Brazilian urban areas are constantly being degraded due to the unplanned use of the urban space; however, due to the different contexts of land use and occupation in the river watersheds, different intervention strategies are required to requalify them. When it comes to requalifying watercourses, we can list three main techniques to fulfill this purpose: restoration, revitalization and recovery; each one being indicated for specific contexts of land use and occupation in the basin. In this study, it was demonstrated that the application of these three techniques to three small basins in São Paulo city, listing the aspects involved in each of the contexts and techniques of requalification. For a protected watercourse within a forest park, renaturalization was proposed, where the watercourse is preserved in a state closer to the natural one. For a watercourse in an urban context that still preserves open spaces for its maintenance as a landscape element, an intervention was proposed following the principles of revitalization, integrating the watercourse with the landscape and the population. In the case of a watercourse in a harder context, only recovery was proposed, since the watercourse is found under the road system, which makes it difficult to integrate it into the landscape.

Keywords: sustainable drainage, river restoration, river revitalization, river recovery

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Authors: Auliya Adzillatin Uzhma, M. Adrian Rizky, Puri Diah Santyarini

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Bekasi Industrial Area in Kab. Bekasi and SEZ (Special Economic Zone) Sei Mangkei in Kab. Simalungun are two areas whose have the same main economic activity that are manufacturing industrial. Manufacturing industry in Bekasi Industrial Area contributes more than 70% of Kab. Bekasi’s GDP, while manufacturing industry in SEZ Sei Mangkei contributes less than 20% of Kab. Simalungun’s GDP. The dependent variable in the research is labor productivity, while the independent variable is the amount of labor, the level of labor education, the length of work and salary. This research used linear regression method to find the model for represent actual condition of productivity in two industrial area, then the equalization using dummy variable on labor education level variable. The initial hypothesis (Ho) in this research is that labor productivity in Bekasi Industrial Area will be higher than the productivity of labor in SEZ Sei Mangkei. The variable that supporting the accepted hypothesis are more labor, higher education, longer work and higher salary in Bekasi Industrial Area.

Keywords: labor, industrial city, linear regression, productivity

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Authors: Aydin Azizi, Abdurrahman Tanira

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With the onset of climate change and limited fuel resources, improving fuel efficiency has become an important part of the motor industry. To maximize fuel efficiency, development of technologies must come hand-in-hand with awareness of efficient driving strategies. This study aims to explore the various driving habits that can impact fuel efficiency by reviewing available literature. Such habits include sudden and unnecessary acceleration or deceleration, improper hardware maintenance, driving above or below optimum speed and idling. By studying such habits and ultimately applying it to driving techniques, in combination with improved mechanics of the car, will optimize the use of fuel.

Keywords: fuel efficiency, driving techniques, optimum speed, optimizing fuel consumption

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Arun C. O., Shrijith M. B., Thakur Rajesh Singh

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The study aims to analyze and understand the biomechanical stability of the atlantoaxial complex under different posterior fixation techniques using the finite element method in the Indian context. The conventional cadaveric studies performed show heterogeneity in biomechanical properties. The finite element method being a versatile numerical tool, is being wisely used for biomechanics analysis of atlantoaxial complex. However, the biomechanics of posterior fixation techniques for an Indian subject is missing in the literature. It is essential to study in this context as the bone density and geometry of vertebrae vary from region to region, thereby requiring different screw lengths and it can affect the range of motion(ROM), stresses generated. The current study uses CT images for developing a 3D finite element model with C1-C2 geometry without ligaments. Instrumentation is added to this geometry to develop four models for four fixation techniques, namely C1-C2 TA, C1LM-C2PS, C1LM-C2Pars, C1LM-C2TL. To simulate Flexion, extension, lateral bending, axial rotation, 1.5 Nm is applied to C1 while the bottom nodes of C2 are fixed. Then Range of Motion (ROM) is compared with the unstable model(without ligaments). All the fixation techniques showed more than 97 percent reduction in the Range of Motion. The von-mises stresses developed in the screw constructs are obtained. From the studies, it is observed that Transarticular technique is most stable in Lateral Bending, C1LM-C2 Translaminar is found most stable in Flexion/extension. The Von-Mises stresses developed minimum in Trasarticular technique in lateral bending and axial rotation, whereas stress developed in C2 pars construct minimum in Flexion/ Extension. On average, the TA technique is stable in all motions and also stresses in constructs are less in TA. Tarnsarticular technique is found to be the best fixation technique for Indian subjects among the 4 methods.

Keywords: biomechanics, cervical spine, finite element model, posterior fixation

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Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada

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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.

Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Clive L. Morley

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Gravity models and panel data modelling of tourism flows are receiving renewed attention, after decades of general neglect. Such models have quite different underpinnings from conventional demand models derived from micro-economic theory. They operate at a different level of data and with different theoretical bases. These differences have important consequences for the interpretation of the results and their policy and managerial implications. This review compares and contrasts the two model forms, clarifying the distinguishing features and the estimation requirements of each. In general, gravity models are not recommended for use to address specific management and marketing purposes.

Keywords: gravity models, micro-economics, demand models, marketing

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Authors: Alhassan Dahiru

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Value management is widely accepted technique of eliminating unnecessary cost at different stages of project development that maximizes the functional value of a project by managing its evolution and development from concept to completion. Many construction industry practitioners are not aware of Value Management practice, and its use is less widespread in Nigeria. The aim of this research is to identify the level of awareness on value management practice amongst construction practitioners with a view to contribute to the improvement of the implementation of value management practice in the Nigerian construction industry. In this study, construction practitioners have been chosen as respondents from the 6 geopolitical zones of the federation including FCT Abuja. Through the survey, a total number of 360 semi-structured questionnaires were administered and 284 were returned and remained good for the analysis. The results indicate that most of the respondents were aware of the value management concept and issues surrounding construction industry in Nigeria, while about 32% of the respondents were not aware of its potential benefits. Therefore, organisations should review their techniques and processes from time to time for improvement on effective service delivery. Additionally, a change management strategy should also be part of every organization to ease the introduction of new techniques such as value management. There is also the need for more value management training workshops and seminars in order to enlighten the participants of the construction industry on the principles, concept, and techniques involved in the value management process.

Keywords: sustainability, value management, construction practitioners, Nigeria

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Authors: Pavel Shcherban, Vlad Golovanov

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Currently, there is an active geological exploration and development of the subsoil shelf of the Kaliningrad region. To carry out a comprehensive and accurate assessment of the volumes and degree of extraction of hydrocarbons from open deposits, it is necessary to establish not only a number of geological and lithological characteristics of the structures under study, but also to determine the oil quality, its viscosity, density, fractional composition as accurately as possible. In terms of considered works, gas chromatography is one of the most capacious methods that allow the rapid formation of a significant amount of initial data. The aspects of the application of the gas chromatography method for determining the chemical characteristics of the hydrocarbons of the Kaliningrad shelf fields are observed in the article, as well as the correlation-regression analysis of these parameters in comparison with the previously obtained chemical characteristics of hydrocarbon deposits located on the land of the region. In the process of research, a number of methods of mathematical statistics and computer processing of large data sets have been applied, which makes it possible to evaluate the identity of the deposits, to specify the amount of reserves and to make a number of assumptions about the genesis of the hydrocarbons under analysis.

Keywords: computer processing of large databases, correlation-regression analysis, hydrocarbon deposits, method of gas chromatography

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Authors: Can Liu, Graham Markowitz, John Balay, Ben Pratt

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Baseline or natural hydrology is commonly employed for hydrologic modeling and quantification of hydrologic alteration due to manmade activities. It can inform planning and policy related efforts for various state and federal water resource agencies to restore natural streamflow flow regimes. A common challenge faced by hydrologists is how to replicate unaltered streamflow conditions, particularly in large watershed settings prone to development and regulation. Three different methods were employed to estimate baseline streamflow conditions for 6 major subbasins the Susquehanna River Basin; those being: 1) incorporation of consumptive water use and reservoir operations back into regulated gaged records; 2) using a map correlation method and flow duration (exceedance probability) regression equations; 3) extending the pre-regulation streamflow records based on the relationship between concurrent streamflows at unregulated and regulated gage locations. Parallel analyses were perform among the three methods and limitations associated with each are presented. Results from these analyses indicate that generating baseline streamflow records at large-scale watersheds remain challenging, even with long-term continuous stream gage records available.

Keywords: baseline hydrology, streamflow gage, subbasin, regression

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Authors: Tauha Hussain Ali, Shabir Hussain Khahro, Nafees Ahmed Memon

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Accurate prediction of project time for planning and bid preparation stage should contain realistic dates. Constructors use their experience to estimate the project duration for the new projects, which is based on intuitions. It has been a constant concern to both researchers and constructors to analyze the accurate prediction of project duration for bid preparation stage. In Pakistan, such study for time cost relationship has been lacked to predict duration performance for the construction projects. This study is an attempt to explore the time cost relationship that would conclude with a mathematical model to predict the time for the drainage rehabilitation projects in the province of Sindh, Pakistan. The data has been collected from National Engineering Services (NESPAK), Pakistan and regression analysis has been carried out for the analysis of results. Significant relationship has been found between time and cost of the construction projects in Sindh and the generated mathematical model can be used by the constructors to predict the project duration for the upcoming projects of same nature. This study also provides the professionals with a requisite knowledge to make decisions regarding project duration, which is significantly important to win the projects at the bid stage.

Keywords: BTC Model, project time, relationship of time cost, regression

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Authors: H. Khomri, A. Bentellis

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Since century of the Development Activities extraction and a dispersed mineral processing Toxic metals and much more contaminated vast areas occupied by what they natural outcrops. New types of metalliferous habitats are so appeared. A species that is Lygeum spartum attracted our curiosity because apart from its valuable role in desertification, it is apparently able to exclude antimony and other metals can be. This species, green leaf blades which are provided as cattle feed, would be a good subject for phytoremediation of mineral soils. The study of absorption and translocation of chromium by the Lygeum spartum in the mining region of Djebel Hamimat and the interaction soil-plant, revealed that soils of this species living in this region are alkaline, calcareous majority in their fine texture medium and saline in their minority. They have normal levels of organic matter. They are moderately rich in nitrogen. They contain total chromium content reaches a maximum of 66,80 mg Kg^(-1) and a total absence of soluble chromium. The results of the analysis of variance of the difference between bare soils and soils appear Lygeum spartum made a significant difference only for the silt and organic matter. But for the other variables analyzed this difference is not significant. Thus, this plant has only one action on the amendment, only the levels of silt and organic matter in soils. The results of the multiple regression of the chromium content of the roots according to all soil variables studied did appear that among the studied variables included in the model, only the electrical conductivity and clay occur in the explanation of contents chromium in roots. The chromium content of the aerial parts analyzed by regression based on all studied soil variables allows us to see only the variables: electrical conductivity and content of chromium in the root portion involved in the explanation of the content chromium in the aerial part.

Keywords: absorption, translocation, analysis of variance, chrome, Lygeum spartum, multiple regression, the soil variables

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Authors: S. J. Bindhu, Edwina G. Rodrigues, Jijo Balakrishnan

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A grid-connected photovoltaic (PV) micro inverter with good performance properties is proposed in this paper. The proposed inverter with a quadrupler, having more efficiency and less voltage stress across the diodes. The stress that come across the diodes that use in the inverter section is considerably low in the proposed converter, also the protection scheme that we provided can eliminate the chances of the error due to fault. The proposed converter is implemented using perturb and observe algorithm so that the fluctuation in the voltage can be reduce and can attain maximum power point. Finally, some simulation and experimental results are also presented to demonstrate the effectiveness of the proposed converter.

Keywords: DC-DC converter, MPPT, quadrupler, PV panel

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Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar

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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.

Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry

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Authors: Mohd Taufiq bin Azmy, Yahaya Hassan, Shubashini Gnanasan, Loganathan Fahrni

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Inappropriate prescribing in older patients has been associated with resource utilization and adverse drug events (ADE) such as hospitalization, morbidity and mortality. Globally, there is a lack of published data on ADE induced by inappropriate prescribing. Our study is specific to an older population and is aimed at identifying risk factors for ADE and to develop a model that will link ADE to inappropriate prescribing. The design of the study was prospective whereby computerized medical records of 302 hospitalized elderly aged 65 years and above in 3 public hospitals in Malaysia (Hospital Serdang, Hospital Selayang and Hospital Sungai Buloh) were studied over a 7 month period from September 2013 until March 2014. Potentially inappropriate medications and potential prescribing omissions were determined using the published and validated START-STOPP criteria. Patients who had at least one inappropriate medication were included in Phase II of the study where ADE were identified by local expert consensus panel based on the published and validated Naranjo ADR probability scale. The panel also assessed whether ADE were causal or contributory to current hospitalization. The association between inappropriate prescribing and ADE (hospitalization, mortality and adverse drug reactions) was determined by identifying whether or not the former was causal or contributory to the latter. Rate of ADE avoidability was also determined. Our findings revealed that the prevalence of potential inappropriate prescribing was 58.6%. A total of ADEs were detected in 31 of 105 patients (29.5%) when STOPP criteria were used to identify potentially inappropriate medication; All of the 31 ADE (100%) were considered causal or contributory to admission. Of the 31 ADEs, 28 (90.3%) were considered avoidable or potentially avoidable. After adjusting for age, sex, comorbidity, dementia, baseline activities of daily living function, and number of medications, the likelihood of a serious avoidable ADE increased significantly when a potentially inappropriate medication was prescribed (odds ratio, 11.18; 95% confidence interval [CI], 5.014 - 24.93; p < .001). The medications identified by STOPP criteria, are significantly associated with avoidable ADE in older people that cause or contribute to urgent hospitalization but contributed less towards morbidity and mortality. Findings of the study underscore the importance of preventing inappropriate prescribing.

Keywords: adverse drug events, appropriate prescribing, health services research

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Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

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Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

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Authors: Syed Masood Hussain

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An effective control method, including system-level control and pulse width modulation for quasi-Z-source cascade multilevel inverter (qZS-CMI) based grid-tie photovoltaic (PV) power system is proposed. The system-level control achieves the grid-tie current injection, independent maximum power point tracking (MPPT) for separate PV panels, and dc-link voltage balance for all quasi-Z-source H-bridge inverter (qZS-HBI) modules. A recent upsurge in the study of photovoltaic (PV) power generation emerges, since they directly convert the solar radiation into electric power without hampering the environment. However, the stochastic fluctuation of solar power is inconsistent with the desired stable power injected to the grid, owing to variations of solar irradiation and temperature. To fully exploit the solar energy, extracting the PV panels’ maximum power and feeding them into grids at unity power factor become the most important. The contributions have been made by the cascade multilevel inverter (CMI). Nevertheless, the H-bridge inverter (HBI) module lacks boost function so that the inverter KVA rating requirement has to be increased twice with a PV voltage range of 1:2; and the different PV panel output voltages result in imbalanced dc-link voltages. However, each HBI module is a two-stage inverter, and many extra dc–dc converters not only increase the complexity of the power circuit and control and the system cost, but also decrease the efficiency. Recently, the Z-source/quasi-Z-source cascade multilevel inverter (ZS/qZS-CMI)-based PV systems were proposed. They possess the advantages of both traditional CMI and Z-source topologies. In order to properly operate the ZS/qZS-CMI, the power injection, independent control of dc-link voltages, and the pulse width modulation (PWM) are necessary. The main contributions of this paper include: 1) a novel multilevel space vector modulation (SVM) technique for the single phase qZS-CMI is proposed, which is implemented without additional resources; 2) a grid-connected control for the qZS-CMI based PV system is proposed, where the all PV panel voltage references from their independent MPPTs are used to control the grid-tie current; the dual-loop dc-link peak voltage control.

Keywords: Quzi-Z source inverter, Photo voltaic power system, space vector modulation, cascade multilevel inverter

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Authors: Zerzouri Nora

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In this paper, author presented the generalities of a photovoltaic system study and simulation. Author inserted the DC-DC converter to raise the voltage level and improve the operation of the PV panel by continuing the operating point at maximum power by using the Perturb and Observe technique (P&O). The connection to the network is made by inserting a three-phase voltage inverter allowing synchronization with the network the inverter is controlled by a PWM control. The simulation results allow the author to visualize the operation of the different components of the system, as well as the behavior of the system during the variation of meteorological values.

Keywords: photovoltaic generator PV, boost converter, P&O MPPT, PWM inverter, three phase grid

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Authors: Amil Suleimanov, Aigul Saduakassova, Denis Vinnikov

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Objective: To assess functional visceral fat (VAT) activity evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in colorectal cancer (CRC). Materials and methods: We assessed 60 patients with histologically confirmed CRC who underwent 18F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVmax) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also report the best areas under the curve (AUC) for SUVmax with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted for age regression models and ROC analysis, 18F-FDG accumulation in RLH (cutoff SUVmax 0.74; Se 75%; Sp 61%; AUC 0.668; p = 0.049), RU (cutoff SUVmax 0.78; Se 69%; Sp 61%; AUC 0.679; p = 0.035), RRL (cutoff SUVmax 1.05; Se 69%; Sp 77%; AUC 0.682; p = 0.032) and RRI (cutoff SUVmax 0.85; Se 63%; Sp 61%; AUC 0.672; p = 0.043) could predict later metastases in CRC patients, as opposed to age, sex, primary tumor location, tumor grade and histology. Conclusions: VAT SUVmax is significantly associated with later metastases in CRC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, colorectal cancer, predictive value

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Authors: A. Porshnev, A. Zaporozhtchuk

Abstract:

Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Amir Hossein Ghaffari Nejad, Forouhar Ferdowsi, Reza Mashhadi

Abstract:

In the interest-free banking system of Iran, the savings of society are in the form of bank deposits, and banks using the Islamic contracts, allocate the resources to applicants for obtaining facilities and credit. In the meantime, the central bank, with the aim of introducing monetary policy, determines the maximum interest rate on bank deposits in terms of macroeconomic requirements. But in recent years, the country's economic constraints with the stagflation and the consequence of the institutional weaknesses of the financial market of Iran have resulted in massive disturbances in the balance sheet of the banking system, resulting in a period of mismatch maturity in the banks' assets and liabilities and the implementation of a Ponzi game. This issue caused determination of the interest rate in long-term bank deposit contracts to be associated with non-observance of the maximum rate set by the central bank. The result of this condition was in the allocation of new sources of equipment to meet past commitments towards the old depositors and, as a result, a significant part of the supply of equipment was leaked out of the facilitating cycle and credit crunch emerged. The purpose of this study is to identify the most important factors affecting the occurrence of non-confirmatory financial banking behavior using data from 19 public and private banks of Iran. For this purpose, the causes of this non-confirmatory behavior of banks have been investigated using the panel vector autoregression method (PVAR) for the period of 2007-2015. Granger's causality test results suggest that the return of parallel markets for bank deposits, non-performing loans and the high share of the ratio of facilities to banks' deposits are all a cause of the formation of non-confirmatory behavior. Also, according to the results of impulse response functions and variance decomposition, NPL and the ratio of facilities to deposits have the highest long-term effect and also have a high contribution to explaining the changes in banks' non-confirmatory behavior in determining the interest rate on deposits.

Keywords: non-conformity behavior, Ponzi Game, panel vector autoregression, nonperforming loans

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Authors: Hosam Mohamed Darwish

Abstract:

In 2008, the Egyptian Ministry of Education introduced a new national coursebook ‘Hello for Secondary Schools, which recommends a shift in EFL teachers’ instructional practices. Since then, very little attention has been paid to teachers’ techniques in EFL writing classes. Hence, this study aimed at investigating teaching writing practices in secondary schools and exploring the teachers’ attitudes towards EFL writing skill in addition to exploring the difficulties that teachers encountered in EFL writing lessons. The study depended on data triangulation through administering two questionnaires: one to 44 teachers and the other to 24 students, and conducting semi-structured interviews with 11 teachers. Both teachers and students were asked to describe teaching practices in EFL writing classes while the open-ended questions and interviews collected data about the teachers’ difficulties in writing lessons. The questionnaires indicate that teachers have negative attitudes towards teaching writing, and most of their practices are still traditional. Five factors have influenced teachers’ practices: backwash of the test, teachers’ professional development, students’ culture of reading and large classes. The study recommends there has to be a necessary change in the students’ examination system, and ongoing teachers’ professional development should be considered. Finally, a teaching model and implications are suggested.

Keywords: EFL writing, Egyptian secondary schools, teachers’ attitudes, teachers’ techniques

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Authors: Saahith M. S., Sivakami R.

Abstract:

In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Mei-Yi Wu, Shang-Ming Huang

Abstract:

The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

Procedia PDF Downloads 346