Fighting COVID-19: Lessons and Experience from the World’s Largest Economies

The paper reviews the insights gained in combating COVID-19 in the US, Japan, and China. After evaluation and investigation, we found that China’s and Japan’s experience of fighting COVID-19 is commendable. The Chinese government and the Japanese administration have implemented highly effective governance and public health course of action to fight COVID-19. Government-led epidemic control with a staunch belief in science can roll out effective pandemic control strategies. In contrast, the US failed to react to COVID-19 effectively. The relaxed public health measures of ending shutdowns prematurely were not working. When the US keeps business open after the spring shutdown, COVID-19 cases are soaring. Such experiences inform us effective governance and a mandatory and stricter approach can better curb a pandemic than milder measures in handling a public health emergency. And China and Japan, where collectivistic culture reins, can better maneuver a public health crisis with collective efforts.

Evaluation of Gingival Hyperplasia Caused by Medications

Purpose: Drug gingival hyperplasia is an uncommon pathology encountered during routine work in dental units. The purpose of this paper is to present the clinical appearance of gingival hyperplasia caused by medications. There are already three classes of medications that cause hyperplasia and based on data from the literature, the clinical cases encountered and included in this study have been compared. Materials and Methods: The study was conducted in a total of 311 patients, out of which 182 patients were included in our study, meeting the inclusion criteria. After each patient's history was recorded and it was found that patients were in their knowledge of chronic illness, undergoing treatment of gingivitis hypertrophic drugs was performed with a clinical examination of oral cavity and assessment by vertical and horizontal evaluation according to the periodontal indexes. Results: Of the data collected during the study, it was observed that 97% of patients with gingival hyperplasia are treated with nifedipine. 84% of patients treated with selected medicines and gingival hyperplasia in the oral cavity has been exposed at time period for more than 1 year and 1 month. According to the GOI, in the first rank of this index are about 21% of patients, in the second rank are 52%, in the third rank are 24% and in the fourth grade are 3%. According to the horizontal growth index of gingival hyperplasia, grade 1 included about 61% of patients and grade 2 included about 39% of patients with gingival hyperplasia. Bacterial index divides patients by degrees: grading 0 - 8.2%, grading 1 - 32.4%, grading 2 - 14% and grading 3 - 45.1%. Conclusions: The highest percentage of gingival hyperplasia caused by drugs is due to dosing of nifedipine for a duration of dosing and application for systemic healing for more than 1 year.

Traditional Dyeing of Silk with Natural Dyes by Eco-Friendly Method

In traditional dyeing of natural fibers with natural dyes, metal salts are commonly used to increase color stability. This method always carries the risk of environmental pollution (contamination of arable soils and fresh groundwater) due to the release of dyeing effluents containing large amounts of metal. Therefore, researchers are always looking for new methods to obtain a green dyeing system. In this research, the use of the enzymatic dyeing method to prevent environmental pollution with metals and reduce production costs has been proposed. After degumming and bleaching, raw silk fabrics were dyed with natural dyes (Madder and Sumac) by three methods (pre-mordanting with a metal salt, one-step enzymatic dyeing, and two-step enzymatic dyeing). Results show that silk dyed with natural dyes by the enzymatic method has higher color strength and colorfastness than the pretreated with a metal salt. Also, the amount of remained dyes in the dyeing wastewater is significantly reduced by the enzymatic method. It is found that the enzymatic dyeing method leads to improvement of dye absorption, color strength, soft hand, no change in color shade, low production costs (due to low dyeing temperature), and a significant reduction in environmental pollution.

Solid State Drive End to End Reliability Prediction, Characterization and Control

A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Select-Low and Select-High Methods for the Wheeled Robot Dynamic States Control

The paper enquires on the two methods of the wheeled robot braking torque control. Those two methods are applied when the adhesion coefficient under left side wheels is different from the adhesion coefficient under the right side wheels. In case of the select-low (SL) method the braking torque on both wheels is controlled by the signals originating from the wheels on the side of the lower adhesion. In the select-high (SH) method the torque is controlled by the signals originating from the wheels on the side of the higher adhesion. The SL method is securing stable and secure robot behaviors during the braking process. However, the efficiency of this method is relatively low. The SH method is more efficient in terms of time and braking distance but in some situations may cause wheels blocking. It is important to monitor the velocity of all wheels and then take a decision about the braking torque distribution accordingly. In case of the SH method the braking torque slope may require significant decrease in order to avoid wheel blocking.

Development of Impressive Tensile Properties of Hybrid Rolled Ta0.5Nb0.5Hf0.5ZrTi1.5 Refractory High Entropy Alloy

The microstructure, texture, phase stability, and tensile properties of annealed Ta0.5Nb0.5Hf0.5ZrTi1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Toward Discovering an Architectural Typology Based on the Theory of Affordance

This paper revolves around the concept of affordance. It aims to discover and develop an architectural typology based on the ecological concept of affordance. In order to achieve this aim, an analytical study is conducted and two sources were taken into account: 1- Gibson's definition of the concept of affordance and 2- The researches that are concerned on the affordance categorisation. As a result, this paper concluded 16 typologies of affordances, including the possibilities of mixing them based on both sources. To clarify these typologies and provide further understanding, a wide range of architectural examples are presented and proposed in the paper. To prove this vocabulary’s capability to diagnose and evaluate the affordance of different environments, an experimental study with two processes have been adapted: 1. Diagnostic process: the interpretation of the environments with regards to its affordance by using the new vocabulary (the developed typologies). 2. Evaluating process: the evaluation of the environments that have been interpreted and classified with regards to their affordances. By using the measures of emotional experience (the positive affect ‘PA’ and the negative affect ‘NA’) and the architectural evaluation criteria (beauty, economy and function). The experimental study proves that the typologies are capable of reading the affordance within different environments. Additionally, it explains how these different typologies reflect different interactions based on the previous processes. The data which are concluded from the evaluation of measures explain how different typologies of affordance that have already reflected different environments had different evaluations. In fact, some of them are recommended while the others are not. In other words, the paper draws a roadmap for designers to diagnose, evaluate and analyse the affordance into different architectural environments. After that, it guides them through adapting the best interaction (affordance category), which they intend to adapt into their proposed designs.

Methodology for the Multi-Objective Analysis of Data Sets in Freight Delivery

Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Time and Wavelength Division Multiplexing Passive Optical Network Comparative Analysis: Modulation Formats and Channel Spacings

In light of the substantial increase in end-user requirements and the incessant need of network operators to upgrade the capabilities of access networks, in this paper, the performance of the different modulation formats on eight-channels Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) transmission system has been examined and compared. Limitations and features of modulation formats have been determined to outline the most suitable design to enhance the data rate and transmission reach to obtain the best performance of the network. The considered modulation formats are On-Off Keying Non-Return-to-Zero (NRZ-OOK), Carrier Suppressed Return to Zero (CSRZ), Duo Binary (DB), Modified Duo Binary (MODB), Quadrature Phase Shift Keying (QPSK), and Differential Quadrature Phase Shift Keying (DQPSK). The performance has been analyzed by varying transmission distances and bit rates under different channel spacing. Furthermore, the system is evaluated in terms of minimum Bit Error Rate (BER) and Quality factor (Qf) without applying any dispersion compensation technique, or any optical amplifier. Optisystem software was used for simulation purposes.

Treatment of the Modern Management Mechanism of the Debris Flow Processes Expected in the Mletiskhevi

The work reviewed and evaluated various genesis debris flow phenomena recently formatted in the Mletiskhevi, accordingly it revealed necessity of treatment modern debris flow against measures. Based on this, it is proposed the debris flow against truncated semi cone shape construction, which elements are contained in the car’s secondary tires. its constituent elements (sections), due to the possibilities of amortization and geometric shapes is effective and sustainable towards debris flow hitting force. The construction is economical, because after crossing the debris flows in the river bed, the riverbed is not cleanable, also the elements of the building are resource saving. For assessment of influence of cohesive debris flow at the construction and evaluation of the construction effectiveness have been implemented calculation in the specific assumptions with approved methodology. According to the calculation, it was established that after passing debris flow in the debris flow construction (in 3 row case) its hitting force reduces 3 times, that causes reduce of debris flow speed and kinetic energy, as well as sedimentation on a certain section of water drain in the lower part of the construction. Based on the analysis and report on the debris flow against construction, it can be said that construction is effective, inexpensive, technically relatively easy-to-reach measure, that’s why its implementation is prospective.

Cantilever Shoring Piles with Prestressing Strands: An Experimental Approach

Underground space is becoming a necessity nowadays, especially in highly congested urban areas. Retaining underground excavations using shoring systems is essential in order to protect adjoining structures from potential damage or collapse. Reinforced Concrete Piles (RCP) supported by multiple rows of tie-back anchors are commonly used type of shoring systems in deep excavations. However, executing anchors can sometimes be challenging because they might illegally trespass neighboring properties or get obstructed by infrastructure and other underground facilities. A technique is proposed in this paper, and it involves the addition of eccentric high-strength steel strands to the RCP section through ducts without providing the pile with lateral supports. The strands are then vertically stressed externally on the pile cap using a hydraulic jack, creating a compressive strengthening force in the concrete section. An experimental study about the behavior of the shoring wall by pre-stressed piles is presented during the execution of an open excavation in an urban area (Beirut city) followed by numerical analysis using finite element software. Based on the experimental results, this technique is proven to be cost-effective and provides flexible and sustainable construction of shoring works.

A Review on Process Parameters of Ti/Al Dissimilar Joint Using Laser Beam Welding

The use of laser beam welding for joining titanium and aluminum offers more advantages compared with conventional joining processes. Dissimilar metal combination is very much needed for aircraft structural industries and research activities. The quality of a weld joint is directly influenced by the welding input parameters. The common problem that is faced by the manufactures is the control of the process parameters to obtain a good weld joint with minimal detrimental. To overcome this issue, various parameters can be preferred to obtain quality of weld joint. In this present study an overall literature review on processing parameters such as offset distance, welding speed, laser power, shielding gas and filler metals are discussed with the effects on quality weldment. Additionally, mechanical properties of welds joint are discussed. The aim of the report is to review the recent progress in the welding of dissimilar titanium (Ti) and aluminum (Al) alloys to provide a basis for follow up research.

Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations

Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Loss Function Optimization for CNN-Based Fingerprint Anti-Spoofing

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Analysis of Differences between Public and Experts’ Views Regarding Sustainable Development of Developing Cities: A Case Study in the Iraqi Capital Baghdad

This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.

Study of the Energy Efficiency of Buildings under Tropical Climate with a View to Sustainable Development: Choice of Material Adapted to the Protection of the Environment

In the context of sustainable development and climate change, the adaptation of buildings to the climatic context in hot climates is a necessity if we want to improve living conditions in housing and reduce the risks to the health and productivity of occupants due to thermal discomfort in buildings. One can find a wide variety of efficient solutions but with high costs. In developing countries, especially tropical countries, we need to appreciate a technology with a very limited cost that is affordable for everyone, energy efficient and protects the environment. Biosourced insulation is a product based on plant fibers, animal products or products from recyclable paper or clothing. Their development meets the objectives of maintaining biodiversity, reducing waste and protecting the environment. In tropical or hot countries, the aim is to protect the building from solar thermal radiation, a source of discomfort. The aim of this work is in line with the logic of energy control and environmental protection, the approach is to make the occupants of buildings comfortable, reduce their carbon dioxide emissions (CO2) and decrease their energy consumption (energy efficiency). We have chosen to study the thermo-physical properties of banana leaves and sawdust, especially their thermal conductivities, direct measurements were made using the flash method and the hot plate method. We also measured the heat flow on both sides of each sample by the hot box method. The results from these different experiences show that these materials are very efficient used as insulation. We have also conducted a building thermal simulation using banana leaves as one of the materials under Design Builder software. Air-conditioning load as well as CO2 release was used as performance indicator. When the air-conditioned building cell is protected on the roof by banana leaves and integrated into the walls with solar protection of the glazing, it saves up to 64.3% of energy and avoids 57% of CO2 emissions.

Vulnerability Analysis for Risk Zones Boundary Definition to Support a Decision Making Process at CBRNE Operations

An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

The Ballistics Case Study of the Enrica Lexie Incident

On February 15, 2012 off the Indian coast of Kerala, in position 091702N-0760180E by the oil tanker Enrica Lexie, flying the Italian flag, bursts of 5.56 x45 caliber shots were fired from assault rifles AR/70 Italian-made Beretta towards the Indian fisher boat St. Anthony. The shots that hit the St. Anthony fishing boat were six, of which two killed the Indian fishermen Ajesh Pink and Valentine Jelestine. From the analysis concerning the kinematic engagement of the two ships and from the autopsy and ballistic results of the Indian judicial authorities it is possible to reconstruct the trajectories of the six aforementioned shots. This essay reconstructs the trajectories of the six shots that cannot be of direct shooting but have undergone a rebound on the water. The investigation carried out scientifically demonstrates the rebound of the blows on the water, the gyrostatic deviation due to the rebound and the tumbling effect always due to the rebound as regards intermediate ballistics. In consideration of the four shots that directly impacted the fishing vessel, the current examination proves, with scientific value, that the trajectories could not be downwards but upwards. Also, the trajectory of two shots that hit to death the two fishermen could not be downwards but only upwards. In fact, this paper demonstrates, with scientific value: The loss of speed of the projectiles due to the rebound on the water; The tumbling effect in the ballistic medium within the two victims; The permanent cavities subject to the injury ballistics and the related ballistic trauma that prevented homeostasis causing bleeding in one case; The thermo-hardening deformation of the bullet found in Valentine Jelestine's skull; The upward and non-downward trajectories. The paper constitutes a tool in forensic ballistics in that it manages to reconstruct, from the final spot of the projectiles fired, all phases of ballistics like the internal one of the weapons that fired, the intermediate one, the terminal one and the penetrative structural one. In general terms the ballistics reconstruction is based on measurable parameters whose entity is contained with certainty within a lower and upper limit. Therefore, quantities that refer to angles, speed, impact energy and firing position of the shooter can be identified within the aforementioned limits. Finally, the investigation into the internal bullet track, obtained from any autopsy examination, offers a significant “lesson learned” but overall a starting point to contain or mitigate bleeding as a rescue from future gunshot wounds.

The Profit Trend of Cosmetics Products Using Bootstrap Edgeworth Approximation

Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.