Search results for: least mean square algorithm

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: Ketevan Janashia, Tamar Tsibadze, Levan Tvildiani, Nikoloz Invia, Elguja Kubaneishvili, Vasili Kukhianidze, George Ramishvili

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This study considers the possible effects of geomagnetic activity (GMA) on humans situated on Earth by performing experiments concerning specific sensitive reactions in humans in both: natural conditions during different GMA and by the simulation of different GMA in the lab. The measurements of autonomic nervous system (ANS) responses to different GMA via measuring the heart rate variability (HRV) indices and stress index (SI) and their comparison with the K-index of GMA have been presented and discussed. The results of experiments indicate an intensification of the sympathetic part of the ANS as a stress reaction of the human organism when it is exposed to high level of GMA as natural as well as in simulated conditions. Aim: We tested the hypothesis whether the GMF when disturbed can have effects on human ANS causing specific sensitive stress-reactions depending on the initial type of ANS. Methods: The study focuses on the effects of different GMA on ANS by comparing of HRV indices and stress index (SI) of n= 78, 18-24 years old healthy male volunteers. Experiments were performed as natural conditions on days of low (K= 1-3) and high (K= 5-7) GMA as well as in the lab by the simulation of different GMA using the device of geomagnetic storm (GMS) compensation and simulation. Results: In comparison with days of low GMA (K=1-3) the initial values of HRV shifted towards the intensification of the sympathetic part (SP) of the ANS during days of GMSs (K=5-7) with statistical significance p-values: HR (heart rate, p= 0.001), SDNN (Standard deviation of all Normal to Normal intervals, p= 0.0001), RMSSD (The square root of the arithmetical mean of the sum of the squares of differences between adjacent NN intervals, p= 0.0001). In comparison with conditions during GMSs compensation mode (K= 0, B= 0-5nT), the ANS balance was observed to shift during exposure to simulated GMSs with intensities in the range of natural GMSs (K= 7, B= 200nT). However, the initial values of the ANS resulted in different dynamics in its variation depending of GMA level. In the case of initial balanced regulation type (HR > 80) significant intensification of SP was observed with p-values: HR (p= 0.0001), SDNN (p= 0.047), RMSSD (p= 0.28), LF/HF (p=0.03), SI (p= 0.02); while in the case of initial parasympathetic regulation type (HR < 80), an insignificant shift to the intensification of the parasympathetic part (PP) was observed. Conclusions: The results indicate an intensification of SP as a stress reaction of the human organism when it is exposed to high level of GMA in both natural and simulated conditions.

Keywords: autonomic nervous system, device of magneto compensation/simulation, geomagnetic storms, heart rate variability

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Hesam Gholami

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Elevated suspended sediment loads in riverine systems resulting from accelerated erosion due to human activities are a serious threat to the sustainable management of watersheds and ecosystem services therein worldwide. Therefore, mitigation of deleterious sediment effects as a distributed or non-point pollution source in the catchments requires reliable provenance information. Sediment tracing or sediment fingerprinting, as a combined process consisting of sampling, laboratory measurements, different statistical tests, and the application of mixing or unmixing models, is a useful technique for discriminating the sources of sediments. From 1996 to the present, different aspects of this technique, such as grouping the sources (spatial and individual sources), discriminating the potential sources by different statistical techniques, and modification of mixing and unmixing models, have been introduced and modified by many researchers worldwide, and have been applied to identify the provenance of fine materials in agricultural, rural, mountainous, and coastal catchments, and in large catchments with numerous lakes and reservoirs. In the last two decades, efforts exploring the uncertainties associated with sediment fingerprinting results have attracted increasing attention. The frameworks used to quantify the uncertainty associated with fingerprinting estimates can be divided into three groups comprising Monte Carlo simulation, Bayesian approaches and generalized likelihood uncertainty estimation (GLUE). Given the above background, the primary goal of this study was to apply geochemical fingerprinting within the GLUE framework in the estimation of sub-basin spatial sediment source contributions in the arid Mehran River catchment in southern Iran, which drains into the Persian Gulf. The accuracy of GLUE predictions generated using four different sets of statistical tests for discriminating three sub-basin spatial sources was evaluated using 10 virtual sediments (VS) samples with known source contributions using the root mean square error (RMSE) and mean absolute error (MAE). Based on the results, the contributions modeled by GLUE for the western, central and eastern sub-basins are 1-42% (overall mean 20%), 0.5-30% (overall mean 12%) and 55-84% (overall mean 68%), respectively. According to the mean absolute fit (MAF; ≥ 95% for all target sediment samples) and goodness-of-fit (GOF; ≥ 99% for all samples), our suggested modeling approach is an accurate technique to quantify the source of sediments in the catchments. Overall, the estimated source proportions can help watershed engineers plan the targeting of conservation programs for soil and water resources.

Keywords: sediment source tracing, generalized likelihood uncertainty estimation, virtual sediment mixtures, Iran

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Shilpa Avarebeel

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Background: India is one of the seven identified countries in South-East Asia region, regularly reporting dengue infection and may soon transform into a major niche for dengue epidemics. Objective: To study the clinical profile of dengue in our setting with special reference to respiratory complication. Study design: Descriptive and exploratory study, for one year in 2014. All patients confirmed as dengue infection were followed and their clinical profile, along with outcome was determined. Study proforma was designed based on the objective of the study and it was pretested and used after modification. Data was analyzed using statistical software SPSS-Version 16. Data were expressed as mean ±S .D for parametric variables and actual frequencies or percentage for non-parametric data. Comparison between groups was done using students’ t-test for independent groups, Chie square test, one-way ANOVA test, Karl Pearson’s correlation test. Statistical significance is taken at P < 0.05. Results: Study included 134 dengue positive cases. 81% had dengue fever, 18% had dengue hemorrhagic fever, and one had dengue shock syndrome. Most of the cases reported were during the month of June. Maximum number of cases was in the age group of 26-35 years. Average duration of hospital stay was less than seven days. Fever and myalgia was present in all the 134 patients, 16 had bleeding manifestation. 38 had respiratory symptoms, 24 had breathlessness, and 14 had breathlessness and dry cough. On clinical examination of patients with respiratory symptoms, all twenty-eight had hypoxia features, twenty-four had signs of pleural effusion, and four had ARDS features. Chest x-ray confirmed the same. Among the patients with respiratory symptoms, the mean platelet count was 26,537 c/cmm. There was no statistical significant difference in the platelet count in those with ARDS and other dengue complications. Average four units of platelets were transfused to all those who had ARDS in view of bleeding tendency. Mechanical ventilator support was provided for ARDS patients. Those with pleural effusion and pulmonary oedema were given NIV (non-invasive ventilation) support along with supportive care. However, steroids were given to patients with ARDS and 10 patients with signs of respiratory distress. 100%. Mortality was seen in patients with ARDS. Conclusion: Dengue has to be checked for those presenting with fever and breathlessness. Supportive treatments remain the cornerstone of treatment. Platelet transfusion has to be given only by clinical judgment. Steroids have no role except in early ARDS, which is controversial. Early NIV support helps in speedy recovery of dengue patients with respiratory distress.

Keywords: adult respiratory distress syndrome, dengue fever, non-invasive ventilation, pulmonary complication

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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Authors: Olumuyiwa Ayoola Kokapi, Olugbenga Solomon Bello

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Dyes are organic compounds with complex aromatic molecular structure that resulted in fast colour on a substance. Dye effluent found in wastewater generated from the dyeing industries is one of the greatest contributors to water pollution. Groundnut hull (GH) is an agricultural material that constitutes waste in the environment. Environmental contamination by hazardous organic chemicals is an urgent problem, which is partially solved through adsorption technologies. The choice of groundnut hull was promised on the understanding that some materials of agricultural origin have shown potentials to act as Adsorbate for hazardous organic chemicals. The aim of this research is to evaluate the potential of groundnut hull to adsorb Crystal violet dye through kinetic, isotherm and thermodynamic studies. The prepared groundnut hulls was characterized using Brunauer, Emmett and Teller (BET), Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). Operational parameters such as contact time, initial dye concentration, pH, and effect of temperature were studied. Equilibrium time for the adsorption process was attained in 80 minutes. Adsorption isotherms used to test the adsorption data were Langmuir and Freundlich isotherms model. Thermodynamic parameters such as ∆G°, ∆H°, and ∆S° of the adsorption processes were determined. The results showed that the uptake of dye by groundnut hulls occurred at a faster rate, corresponding to an increase in adsorption capacity at equilibrium time of 80 min from 0.78 to 4.45 mg/g and 0.77 to 4.45mg/g with an increase in the initial dye concentration from 10 to 50 mg/L for pH 3.0 and 8.0 respectively. High regression values obtained for pseudo-second-order kinetic model, sum of square error (SSE%) values along with strong agreement between experimental and calculated values of qe proved that pseudo second-order kinetic model fitted more than pseudo first-order kinetic model. The result of Langmuir and Freundlich model showed that the adsorption data fit the Langmuir model more than the Freundlich model. Thermodynamic study demonstrated the feasibility, spontaneous and endothermic nature of the adsorption process due to negative values of free energy change (∆G) at all temperatures and positive value of enthalpy change (∆H) respectively. The positive values of ∆S showed that there was increased disorderliness and randomness at the solid/solution interface of crystal violet dye and groundnut hulls. The present investigation showed that, groundnut hulls (GH) is a good low-cost alternative adsorbent for the removal of Crystal Violet (CV) dye from aqueous solution.

Keywords: adsorption, crystal violet dye, groundnut halls, kinetics

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Authors: Mohammad R. Jalali

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Movement of liquid with a free surface in a container is known as slosh. For instance, slosh occurs when water in a closed tank is set in motion by a free surface displacement, or when liquid natural gas in a container is vibrated by an external driving force, such as an earthquake or movement induced by transport. Slosh is also derived from resonant switching of a natural basin. During sloshing, different types of motion are produced by energy exchange between the liquid and its container. In present study, a numerical model is developed to simulate the nonlinear even harmonic oscillations of free surface sloshing of an initial disturbance to the free surface of a liquid in a closed square basin. The response of the liquid free surface is affected by amplitude and motion frequencies of its container; therefore, sloshing involves complex fluid-structure interactions. In the present study, nonlinear interaction of free surface sloshing of an initial Gaussian hump with its uneven container is predicted numerically. For this purpose, Green-Naghdi (GN) equations are applied as governing equation of fluid field to produce nonlinear second-order and higher-order wave interactions. These equations reduce the dimensions from three to two, yielding equations that can be solved efficiently. The GN approach assumes a particular flow kinematic structure in the vertical direction for shallow and deep-water problems. The fluid velocity profile is finite sum of coefficients depending on space and time multiplied by a weighting function. It should be noted that in GN theory, the flow is rotational. In this study, GN numerical simulations of initial Gaussian hump are compared with Fourier series semi-analytical solutions of the linearized shallow water equations. The comparison reveals that satisfactory agreement exists between the numerical simulation and the analytical solution of the overall free surface sloshing patterns. The resonant free surface motions driven by an initial Gaussian disturbance are obtained by Fast Fourier Transform (FFT) of the free surface elevation time history components. Numerically predicted velocity vectors and magnitude contours for the free surface patterns indicate that interaction of Gaussian hump with its container has localized effect. The result of this sloshing is applicable to the design of stable liquefied oil containers in tankers and offshore platforms.

Keywords: fluid-structure interactions, free surface sloshing, Gaussian hump, Green-Naghdi equations, numerical predictions

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Authors: Giselly Barros Rodrigues, Carlos Leite de Souza

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In recent years, there has been a great discussion about urbanism, the right to the city, the search for the public space and the occupation and appropriation of people in the spaces of the city. This movement happens all over the world and also in the great Brazilian metropolises. The more human-friendly city - the desirable construction of urbanity - as well as the encouragement of walking or bicycling to the detriment of cars is one of the major issues addressed by urban planners and challenges in the process of reviewing regulatory frameworks. The fact is that even if there are public spaces or space for public use in private areas - it is essential that there be, besides a project focused on the people and the use of space, a good management not to generate excess of control and consequently the segregation between different ethnicities, classes or creed. With the insertion of the Strategic Master Plan of Sao Paulo (2014), there is great incentive for them to implement - in the private spaces - of mixed uses and active facades (Services and commerce in the basement of buildings), these incentives will generate a city for people in the medium and long term. This research seeks to discuss the extent to which these spaces are democratic, what their perceptions are in relation to the space of public use in private areas and why this perception may be the one that was originally idealized. For this study, we carried out bibliographic reviews where applied research were carried out in three case studies listed in Sao Paulo. Questionnaires were also applied to the actors who gave answers regarding their perceptions and how they were approached in the places analyzed. After analyzing the material, it was verified that in the three case studies analyzed, sitting on the floor is prohibited. In the two places in Paulista Avenue (Cetenco Plaza and Square of Mall Cidade Sao Paulo) there was no problem whatsoever in relation to the clothes or attitudes of the actors in the streets of Paulista Avenue in Sao Paulo city. Different from what happened in the Itaim neighborhood (Brascan Century Plaza), with more conservative characteristics, where the actors were heavily watched by security and observed by others due to their clothes and attitudes in that area. The city of Sao Paulo is slowly changing, people are increasingly looking for places of quality in public use in their daily lives. The Strategic Master Plan of Sao Paulo (2014) and the Legislation approved in 2016 envision a city more humane and people-oriented in the future. It is up to the private sector, the public, and society to work together so that this glimpse becomes an abundant reality in every city, generating quality of life and urbanity for all.

Keywords: urbanity, space for public use, appropriation of space, segregation

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Authors: Mingxia Zhu, Matthew Tingchi Liu

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AI grows gradually in the market with its efficiency and accuracy, influencing people’s perceptions, attitude, and even consequential behaviors. Current study extends prior research by focusing on AI’s impact on consumers’ morality. First, study 1 tested individuals’ believes about AI and human’s moral perceptions and people’s attribution of moral worth to AI and human. Moral perception refers to a computational system an entity maintains to detect and identify moral violations, while moral worth here denotes whether individual regard an entity as worthy of moral treatment. To identify the effect of AI on consumers’ morality, two studies were employed. Study 1 is a within-subjects survey, while study 2 is an experimental study. In the study 1, one hundred and forty participants were recruited through online survey company in China (M_age = 27.31 years, SD = 7.12 years; 65% female). The participants were asked to assign moral perception and moral worth to AI and human. A paired samples t-test reveals that people generally regard that human has higher moral perception (M_Human = 6.03, SD = .86) than AI (M_AI = 2.79, SD = 1.19; t(139) = 27.07, p < .001; Cohen’s d = 1.41). In addition, another paired samples t-test results showed that people attributed higher moral worth to the human personnel (M_Human = 6.39, SD = .56) compared with AIs (M_AI = 5.43, SD = .85; t(139) = 12.96, p < .001; d = .88). In the next study, two hundred valid samples were recruited from survey company in China (M_age = 27.87 years, SD = 6.68 years; 55% female) and the participants were randomly assigned to two conditions (AI vs. human). After viewing the stimuli of human versus AI, participants are informed that one insurance company would determine the price purely based on their declaration. Therefore, their open-ended answers were coded into ethical, honest behavior and unethical, dishonest behavior according to the design of prior literature. A Chi-square analysis revealed that 64% of the participants would immorally lie towards AI insurance inspector while 42% of participants reported deliberately lower mileage facing with human inspector (χ^2 (1) = 9.71, p = .002). Similarly, the logistic regression results suggested that people would significantly more likely to report fraudulent answer when facing with AI (β = .89, odds ratio = 2.45, Wald = 9.56, p = .002). It is demonstrated that people would be more likely to behave unethically in front of non-human agents, such as AI agent, rather than human. The research findings shed light on new practical ethical issues in human-AI interaction and address the important role of human employees during the process of service delivery in the new era of AI.

Keywords: AI agent, consumer morality, ethical behavior, human-AI interaction

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Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

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BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: layout optimization, dining efficiency, troops’ cafeteria, anylogic simulation, field experiment

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

Procedia PDF Downloads 170

Authors: J.R.S.S. Kumara, M.A.R.M. Fernando, S.Venkatesh, D.K. Jayaratne

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Protection of heritage monuments against lightning has become extremely important as far as their historical values are concerned. When such structures are large and tall, the risk of lightning initiated from both cloud and ground can be high. This paper presents a lightning risk analysis of three giant stupas in Anuradhapura era (fourth century BC onwards) in Sri Lanka. The three stupas are Jethawaaramaya (269-296 AD), Abayagiriya (88-76 BC) and Ruwanweliseya (161-137 BC), the third, fifth and seventh largest ancient structures in the world. These stupas are solid brick structures consisting of a base, a near hemispherical dome and a conical spire on the top. The ancient stupas constructed with a dielectric crystal on the top and connected to the ground through a conducting material, was considered as the hypothesis for their original lightning protection technique. However, at present, all three stupas are protected with Franklin rod type air termination systems located on top of the spire. First, a risk analysis was carried out according to IEC 62305 by considering the isokeraunic level of the area and the height of the stupas. Then the standard protective angle method and rolling sphere method were used to locate the possible touching points on the surface of the stupas. The study was extended to estimate the critical current which could strike on the unprotected areas of the stupas. The equations proposed by (Uman 2001) and (Cooray2007) were used to find the striking distances. A modified version of rolling sphere method was also applied to see the effects of upward leaders. All these studies were carried out for two scenarios: with original (i.e. ancient) lightning protection system and with present (i.e. new) air termination system. The field distribution on the surface of the stupa in the presence of a downward leader was obtained using finite element based commercial software COMSOL Multiphysics for further investigations of lightning risks. The obtained results were analyzed and compared each other to evaluate the performance of ancient and new lightning protection methods and identify suitable methods to design lightning protection systems for stupas. According to IEC standards, all three stupas with new and ancient lightning protection system has Level IV protection as per protection angle method. However according to rolling sphere method applied with Uman’s equation protection level is III. The same method applied with Cooray’s equation always shows a high risk with respect to Uman’s equation. It was found that there is a risk of lightning strikes on the dome and square chamber of the stupa, and the corresponding critical current values were different with respect to the equations used in the rolling sphere method and modified rolling sphere method.

Keywords: Stupa, heritage, lightning protection, rolling sphere method, protection level

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Authors: Saradiya Mukherjee

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Background: Indian Muslims, compared to their counterparts in other religions, generally do not fare well on many yardsticks related to socio-economic progress and the same is true with maternal health care utilization. Due to low age at marriage a major percentage of child birth is ascribed to young (15-24 years) Muslim mothers in, which pose serious concerns on the maternal health care of Young Married Muslim women (YMMW). A thorough search of past literature on Muslim women’s health and health care reveals that studies in India have mainly focused on religious differences in fertility levels and contraceptive use while the research on the determinants of maternal health care utilization among Muslim women are lacking in India. Data and Methods: Retrieving data from the National Family Health Survey -3 (2005-06) this study attempts to assess the level of utilization and factors effecting three key maternal health indicators (full ANC, safe delivery and PNC) among YMMW (15-24 years) in India. The key socio-economic and demographic variables taken as independent or predictor variables in the study was guided by existing literature particularly for India. Bi-variate analysis and chi square test was applied and variables which were found to be significant were further included in binary logistic regression. Results: The findings of the study reveal abysmally low levels of utilization for all three indicators i.e. full ANC, safe delivery and PNC of maternal health care included in the study. Mother’s education, mass media exposure, women’s autonomy, birth order, economic status wanted status of child and region of residence were found to be significant variables effecting maternal health care utilization among YMMW. Multivariate analysis reveals that no mass media exposure, lower autonomy, education, poor economic background, higher birth order and unintended pregnancy are some of the reasons behind low maternal health care utilization. Conclusion: Considering the low level of safe maternal health care utilization and its proximate determinants among YMMW the study suggests educating Muslim girls, promoting family planning use, involving media and collaboration between religious leader and health care system could be some important policy level interventions to address the unmet need of maternity services among YMMW.

Keywords: young Muslim women, religion, socio-economic condition, antenatal care, delivery, post natal care

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Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

Procedia PDF Downloads 112

Authors: M. De Filippo, J. S. Kuang

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In construction industry, reinforced concrete (RC) slabs represent fundamental elements of buildings and bridges. Different methods are available for analysing the structural behaviour of slabs. In the early ages of last century, the yield-line method has been proposed to attempt to solve such problem. Simple geometry problems could easily be solved by using traditional hand analyses which include plasticity theories. Nowadays, advanced finite element (FE) analyses have mainly found their way into applications of many engineering fields due to the wide range of geometries to which they can be applied. In such cases, the application of an elastic or a plastic constitutive model would completely change the approach of the analysis itself. Elastic methods are popular due to their easy applicability to automated computations. However, elastic analyses are limited since they do not consider any aspect of the material behaviour beyond its yield limit, which turns to be an essential aspect of RC structural performance. Furthermore, their applicability to non-linear analysis for modeling plastic behaviour gives very reliable results. Per contra, this type of analysis is computationally quite expensive, i.e. not well suited for solving daily engineering problems. In the past years, many researchers have worked on filling this gap between easy-to-implement elastic methods and computationally complex plastic analyses. This paper aims at proposing a numerical procedure, through which a pseudo-lower bound solution, not violating the yield criterion, is achieved. The advantages of moment distribution are taken into account, hence the increase in strength provided by plastic behaviour is considered. The lower bound solution is improved by detecting over-yielded moments, which are used to artificially rule the moment distribution among the rest of the non-yielded elements. The proposed technique obeys Nielsen’s yield criterion. The outcome of this analysis provides a simple, yet accurate, and non-time-consuming tool of predicting the lower-bound solution of the collapse load of RC slabs. By using this method, structural engineers can find the fracture patterns and ultimate load bearing capacity. The collapse triggering mechanism is found by detecting yield-lines. An application to the simple case of a square clamped slab is shown, and a good match was found with the exact values of collapse load.

Keywords: computational mechanics, lower bound method, reinforced concrete slabs, yield-line

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Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

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Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

Procedia PDF Downloads 270

Authors: Hacer Kobya Bulut, Ilknur Kahriman, Birsel C. Demirbag

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Introduction and Purpose: The lives of children with cancer are affected by long term hospitalizations in a negative way due to complications arising from diagnosis or treatment. However, the children's parents are known to have difficulties in meeting their children’s needs and providing home care after cancer treatment or during remission process. Supporting these children and their parents by giving a planned discharge training starting from the hospital and home care leads to reducing hospital applications, hospitalizations, hospital costs, shortening the length of hospital stay and increasing the satisfaction of the children with cancer and their families. This study was conducted to investigate the status of children and their parents' unplanned application to hospital and re-hospitalization. Methods: The study was carried out with 65 children with hematological malignancy in 0-17 age group and their families in a hematology clinic and polyclinic of a university hospital in Trabzon. Data were collected with survey methodology between August-November, 2015 through face to face interview using numbers, percentage and chi-square test in the evaluation. Findings: Most of the children were leukemia (90.8%) and 49.2% had been ill over 13 months. Few of the parents (32.3%) stated that they had received discharge and home care training (24.6%) but most of them (69.2%) found themselves enough in providing home care. Very few parents (6.2%) received home care training after their children being discharged and the majority of parents (61.5%) faced difficulties in home care and had no one to call around them. The parents expressed that in providing care to their children with hematological malignance, they faced difficulty in feeding them (74.6%), explaining their disease (50.0%), giving their oral medication (47.5%), providing hygiene (43.5%) and providing oral care (39.3%). The question ‘What are the emergency situations in which you have to bring your children to a doctor immediately?' was replied as fever (89.2%), severe nausea and vomiting (87.7%), hemorrhage (86.2%) and pain (81.5%). The study showed that 50.8% of the children had unplanned applications to hospitals and 33.8% of them identified as unplanned hospitalization and the first causes of this were fever and pain. The study showed that the frequency of applications (%78.8) and hospitalizations (%81.8) was higher for boys and a statistically significant difference was found between gender and unplanned applications (X=4.779; p=0.02). Applications (48.5%) and hospitalizations (40.9%) were found lower for the parents who had received hospital discharge training, and a significant difference was determined between receiving training and unplanned hospitalizations (X=8.021; p=0.00). Similarly, applications (30.3%) and hospitalizations (40.9%) was found lower for the ones who had received home care training, and a significant difference was determined between receiving home care training and unplanned hospitalizations (X=4.758; p=0.02). Conclusion: It was found out that caregivers of children with cancer did not receive training related to home care and complications about treatment after discharging from hospital, so they faced difficulties in providing home care and this led to an increase in unplanned hospital applications and hospitalizations.

Keywords: cancer, children, unplanned application, unplanned hospitalization

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Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Jalil Qoulizadeh, Hasan Sadeghi

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Brain waves are electrical wave patterns that are produced in the human brain. Knowing these waves and activating them can have a positive effect on brain function and ultimately create an ideal life. The brain has the ability to produce waves from 0.1 to above 65 Hz. (The Beta One device produces exactly these waves) This is because it is said that the waves produced by the Beta One device exactly match the waves produced by the brain. The function and method of this device is based on the magnetic stimulation of the brain. The technology used in the design and producƟon of this device works in a way to strengthen and improve the frequencies of brain waves with a pre-defined algorithm according to the type of requested function, so that the person can access the expected functions in life activities. to perform better. The effect of this field on neurons and their stimulation: In order to evaluate the effect of this field created by the device, on the neurons, the main tests are by conducting electroencephalography before and after stimulation and comparing these two baselines by qEEG or quantitative electroencephalography method using paired t-test in 39 subjects. It confirms the significant effect of this field on the change of electrical activity recorded after 30 minutes of stimulation in all subjects. The Beta One device is able to induce the appropriate pattern of the expected functions in a soft and effective way to the brain in a healthy and effective way (exactly in accordance with the harmony of brain waves), the process of brain activities first to a normal state and then to a powerful one. Production of inexpensive neuroscience equipment (compared to existing rTMS equipment) Magnetic brain stimulation for clinics - homes - factories and companies - professional sports clubs.

Keywords: stimulation, brain, waves, betaOne

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Authors: Tim Nikolsky

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This paper seeks to explore the different ways in which music producers choose to embrace various levels of technology based on musical values, objectives, affordability, access and workflow benefits. Current digital audio production workflow is questioned. Engineers and music producers of today are increasingly divorced from the tangibility of music production. Making music no longer requires you to reach over and turn a knob. Ideas of authenticity in music production are being redefined. Calculations from the mathematical algorithm with the pretty pictures are increasingly being chosen over hardware containing transformers and tubes. Are mouse clicks and movements equivalent or inferior to the master brush strokes we are seeking to conjure? We are making audio production decisions visually by constantly looking at a screen rather than listening. Have we compromised our music objectives and values by removing the ‘hands-on’ nature of music making? DAW interfaces are making our musical decisions for us not necessarily in our best interests. Technological innovation has presented opportunities as well as challenges for education. What do music production students actually need to learn in a formalised education environment, and to what extent do they need to know it? In this brave new world of omnipresent music creation tools, do we still need tangibility in music production? Interviews with prominent Australian music producers that work in a variety of fields will be featured in this paper, and will provide insight in answering these questions and move towards developing an understanding how tangibility can be rediscovered in the next generation of music production.

Keywords: analogue, digital, digital audio workstation, music production, plugins, tangibility, technology, workflow

Procedia PDF Downloads 266

Authors: M. Asl. Dehghan, M. H. Daemi, S. Radmard, S. H. Nabavi

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Thin disk lasers are engineered for efficient thermal cooling and exhibit superior performance for this task. However the disk thickness and large pumped area make the use of this gain format in a resonator difficult when constructing a single-mode laser. Choosing an unstable resonator design is beneficial for this purpose. On the other hand, the low gain medium restricts the application of unstable resonators to low magnifications and therefore to a poor beam quality. A promising idea to enable the application of unstable resonators to wide aperture, low gain lasers is to couple a fraction of the out coupled radiation back into the resonator. The output coupling gets dependent on the ratio of the back reflection and can be adjusted independently from the magnification. The excitation of the converging wave can be done by the use of an external reflector. The resonator performance is numerically predicted. First of all the threshold condition of linear, V and 2V shape resonator is investigated. Results show that the maximum magnification is 1.066 that is very low for high quality purposes. Inserting an additional reflector covers the low gain. The reflectivity and the related magnification of a 350 micron Yb:YAG disk are calculated. The theoretical model was based on the coupled Kirchhoff integrals and solved numerically by the Fox and Li algorithm. Results show that with back reflection mechanism in combination with increasing the number of beam incidents on disk, high gain and high magnification can occur.

Keywords: unstable resonators, thin disk lasers, gain, external reflector

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Authors: Lacheheb Dhia Eddine Zakaria, Ballout Amor

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Today, it is necessary to be thrifty for its planet, on one hand the space being a rare, nonrenewable resource, and on the other hand the ecological, economic and social cost of the urban sprawl. It is commonly asserted that the promotion of a more compact and dense city has a positive effect in terms of public costs of investment, functioning and costs for the citizens and the users of the city. It is clear that the modes urban development management have to evolve profoundly, in particular towards a densification favourable to the raising of the urban quality through an ideal urban density on the scale of the individual housing estate. The lot as an individual housing estate was adopted as an alternative development model to the collective housing, thought in an anthropocentric perspective to emerge as a quality model where the density plays an important role, by being included in operations of a global coherence, in an optimal organization without forgetting the main importance of the deadlines of construction and the finalization of the works. The image of eternal construction site inflicted to our cities explains the renewed interest for the application of the regulatory framework and the completion of these limited operations without global coherence, which are summed up in our case to a ground cut in plots of land, sold then built independently without being finished, and support the relevance of the essential question of the improvement of the outside aspect bound to the appearance which can be revealed as a so important factor for a better use and a better acceptance of its housing environment, that the ratio of a number of houses on a plot of land or the number of square meters by house. To demonstrate the impact of the completion degree of the subdivision dwellings, roads system and urban public utilities on the density or the densification and therefore on the urban quality, we studied two residential subdivisions, the private subdivision Sellam and the subdivision El Imane with a common situation, and a different land surface, density and cutting, being occupied by various social classes, with different needs and different household average size. The approach of this work is based on the typo morphological analysis to reveal the differences in the degrees of completions of the subdivision’s built environment and on the investigation, by a household’s survey, to demonstrate importance of the degree of completion and to reveal the conditions of qualitative densification favourable and convenient to a better subdivision’s appropriation.

Keywords: subdivision, degree of completion, densification, urban quality

Procedia PDF Downloads 369