Search results for: component analysis

Authors: Mina Mortazavi

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The common approach in the construction industry for restraint requirements in existing structures or new constructions is to have Non-Structural Components (NSCs) assembled and installed on-site by different MEP subcontractors. This leads to a lack of coordination and higher costs, construction time, and complications due to inaccurate building information modelling (BIM) systems. Introducing NSCs to a consistent BIM system from the beginning of the design process and considering their seismic loads in the analysis and design process can improve coordination and reduce costs and time. One solution is to use prefabricated mounts with attached MEPs delivered as an integral module. This eliminates the majority of coordination complications and reduces design and installation costs and time. An advanced approach is to have as many NSCs as possible installed in the same prefabricated module, which gives the structural engineer the opportunity to consider the involved component weights and locations in the analysis and design of the prefabricated support. This efficient approach eliminates coordination and access issues, leading to enhanced quality control. This research will focus on the existing literature on modular sub-assemblies that are integrated with architectural and structural components. Modular MEP systems take advantage of the precision provided by BIM tools to meet exact requirements and achieve a buildable design every time. Modular installations that include MEP systems provide efficient solutions for the installation of MEP services or components.

Keywords: building services, modularisation, prefabrication, integral building design

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Authors: John Monro, Suman Mishra

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Choosing foods for health benefits requires information that accurately represents the relative effectiveness of foods with respect to specific health end points, or with respect to responses leading to health outcomes. At present consumers must rely on nutrient composition data, and on health claims to guide them to healthy food choices. Nutrient information may be of limited usefulness because it does not reflect the effect of food structure and food component interactions – that is, whole food effects. Health claims demand stringent criteria that exclude most foods, even though most foods have properties through which they may contribute to positive health outcomes in a diet. In this presentation, we show how the functional efficacy of foods may be expressed in the same format as nutrients, with weight units, as virtual food components that allow a nutrition information panel to show not only what a food is, but also what it does. In the presentation, two body responses linked to well-being are considered – glycaemic response and colonic bulk – in order to illustrate the concept. We show how the nutrient information on available carbohydrates and dietary fibre values obtained by food analysis methods fail to provide information of the glycaemic potency or the colonic bulking potential of foods, because of failings in the methods and approach taken to food analysis. It is concluded that a category of food values that represent the functional efficacy of foods is required to accurately guide food choices for health.

Keywords: dietary fibre, glycaemic response, food values, food effects, health

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Authors: Geun-Yeon Kim, S. P. Praveen Kumar, Kwon-Hee Lee

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A steering knuckle arm is the component that connects the steering system and suspension system. The structural performances such as stiffness, strength, and durability are considered in its design process. The former study suggested the lightweight design of a knuckle arm considering the structural performances and using the metamodel-based optimization. The six shape design variables were defined, and the optimum design was calculated by applying the kriging interpolation method. The finite element method was utilized to predict the structural responses. The suggested knuckle was made of the aluminum Al6082, and its weight was reduced about 60% in comparison with the base steel knuckle, satisfying the design requirements. Then, we investigated its manufacturability by performing foraging analysis. The forging was done as hot process, and the product was made through two-step forging. As a final step of its developing process, the durability is investigated by using the flexible dynamic analysis software, LS-DYNA and the pre and post processor, eta/VPG. Generally, a car make does not provide all the information with the part manufacturer. Thus, the part manufacturer has a limit in predicting the durability performance with the unit of full car. The eta/VPG has the libraries of suspension, tire, and road, which are commonly used parts. That makes a full car modeling. First, the full car is modeled by referencing the following information; Overall Length: 3,595mm, Overall Width: 1,595mm, CVW (Curve Vehicle Weight): 910kg, Front Suspension: MacPherson Strut, Rear Suspension: Torsion Beam Axle, Tire: 235/65R17. Second, the road is selected as the cobblestone. The road condition of the cobblestone is almost 10 times more severe than that of usual paved road. Third, the dynamic finite element analysis using the LS-DYNA is performed to predict the durability performance of the suggested knuckle arm. The life of the suggested knuckle arm is calculated as 350,000km, which satisfies the design requirement set up by the part manufacturer. In this study, the overall design process of a knuckle arm is suggested, and it can be seen that the developed knuckle arm satisfies the design requirement of the durability with the unit of full car. The VPG analysis is successfully performed even though it does not an exact prediction since the full car model is very rough one. Thus, this approach can be used effectively when the detail to full car is not given.

Keywords: knuckle arm, structural optimization, Metamodel, forging, durability, VPG (Virtual Proving Ground)

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Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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Authors: A. Zurraini, Syed Alwi Sar, H. Helmy, H. Nazeefah

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Early Dementia Questionnaire (EDQ) was developed as a screening tool to detect patients with early dementia in primary care. It was developed based on 20 symptoms of dementia. From a preliminary study, EDQ had been shown to be a promising alternative for screening of early dementia. This study was done to further test on EDQ’s reliability and validity. Using a systematic random sampling, 200 elderly patients attending primary health care centers in Kuching, Sarawak had consented to participate in the study and were administered the EDQ. Geriatric Depression Scale (GDS) was used to exclude patients with depression. Those who scored >21 MMSE, were retested using the EDQ. Reliability was determined by Cronbach’s alpha for internal consistency and construct validity was assessed using confirmatory factor analysis (principle component with varimax rotation). The result showed that the overall Cronbach’s alpha coefficient was good which was 0.874. Confirmatory factor analysis on 4 factors indicated that the Cronbach’s alpha for each domain were acceptable with memory (0.741), concentration (0.764), emotional and physical symptoms (0.754) and lastly sleep and environment (0.720). Pearson correlation coefficient between the first EDQ score and the retest EDQ score among those with MMSE of >21 showed a very strong, positive correlation between the two variables, r = 0.992, N=160, P <0.001. The results of the validation study showed that Early Dementia Questionnaire (EDQ) is a valid and reliable tool to be used as a screening tool to detect early dementia in primary care.

Keywords: Early Dementia Questionnaire (EDQ), screening, primary care, construct validity

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Authors: Chirawat Wattanapanich, Hong Wei

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This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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Authors: D. M. El-Tanbouly, R. M. Abdelsalam, A. S. Attia, M. T. Abdel-Aziz

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Lipopolysaccharide (LPS) endotoxin, a component of the outer membrane of Gram-negative bacteria, is involved in the pathogenesis of sepsis. LPS administration induces systemic inflammation that mimics many of the initial clinical features of sepsis and has deleterious effects on several organs including the liver and eventually leading to septic shock and death. The present study aimed to investigate the protective effect of magnesium, a well-known cofactor in many enzymatic reactions and a critical component of the antioxidant system, on hepatic damage associated with LPS induced- endotoxima in mice. Mg (20 and 40 mg/kg, po) was administered for 7 consecutive days. Systemic inflammation was induced one hour after the last dose of Mg by a single dose of LPS (2 mg/kg, ip) and three hours thereafter plasma was separated, animals were sacrificed and their livers were isolated. LPS-treated mice suffered from hepatic dysfunction revealed by histological observation, elevation in plasma transaminases activities, C-reactive protein content and caspase-3, a critical marker of apoptosis. Liver inflammation was evident by elevation in liver cytokines contents (TNF-α and IL-10) and myeloperoxidase (MPO) activity. Additionally, oxidative stress was manifested by increased liver lipoperoxidation, glutathione depletion, elevated total nitrate/nitrite (NOx) content and glutathione peroxidase (GPx) activity. Pretreatment with Mg largely mitigated these alternations through its anti-inflammatory and antioxidant potentials. Mg, therefore, could be regarded as an effective strategy for prevention of liver damage associated with septicemia.

Keywords: LPS, liver damage, magnesium, septicemia

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Authors: Zia Amjad, Salem Safar Alghamdi

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This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 Vicia faba, characterization, PCA, ago-morphological diversity. Icia faba L. accessions were based on ipove and ibpgr descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis. First 6 principle components with eigenvalue greater than one; accounted for 72% of available Vicia faba genetic diversity. However, first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86%, and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1), and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: Vicia faba, characterization, PCA, ago-morphological diversity

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Authors: Nadia Allouache, Mohamed Belmedani

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Energy source is a sustainable, totally inexhaustible and environmentally friendly alternative to the fossil fuels available. It is a renewable and economical energy that can be harnessed sustainably over the long term and thus stabilizes energy costs. Solar cooling technologies have been developed to decrease the augmentation electricity consumption for air conditioning and to displace the peak load during hot summer days. A numerical analysis of thermal and solar performances of an annular finned adsorber, which is the most important component of the adsorption solar refrigerating system, is considered in this work. Different adsorbent/adsorbate pairs, such as activated carbon AC35/methanol, activated carbon AC35/ethanol, and activated carbon BPL/Ammoniac, are undertaken in this study. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular finned adsorber. The Wilson and Dubinin- Astakhov models of the solid-adsorbate equilibrium are used to calculate the adsorbed quantity. The porous medium and the fins are contained in the annular space, and the adsorber is heated by solar energy. Effects of key parameters on the adsorbed quantity and on the thermal and solar performances are analysed and discussed. The AC35/methanol pair is the best pair compared to BPL/Ammoniac and AC35/ethanol pairs in terms of system performance. The system performances are sensitive to the fin geometry. For the considered data measured for clear type days of July 2023 in Algeria and Morocco, the performances of the cooling system are very significant in Algeria.

Keywords: activated carbon AC35-methanol pair, activated carbon AC35-ethanol pair, activated carbon BPL-ammoniac pair, annular finned adsorber, performance coefficients, numerical analysis, solar cooling system

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Authors: Tracy B.E. Omorogiuwa

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Understanding the role of social work in improving societal well-being cannot be separated from the place of field education, which is an integral aspect of social work education. Field learning provides students with knowledge and opportunities to experience solving issues in the field and giving them a clue of the practice situation. Despite being a crucial component in social work curriculum, field education occupies a large space in learning outcome, given the issues and challenges pertaining to its purpose and significance in the society. The drive of this paper is to provide insight on the specific ways in which field education has been conceived, realized and valued in the society. Emphasis is on the significance of field instruction; the link with classroom learning; and the structure of field experience in social work education. Given documented analysis and experience, this study intends to contribute to the development of social work curriculum, by analyzing the pattern, issues and challenges fronting the social work field education in the University of Benin, Nigeria.

Keywords: challenges, curriculum, field education, social work education

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Authors: Iman Shabanzadeh

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Over the last three decades, the main demands of the Iranian workforce have been focused on three areas: "The right to a decent wage", "The right to organize" and "The right to job security". In order to investigate and analyze this situation, the present study focuses on the component of job security. The purpose of the study is to figure out what mechanisms in Iran's Labor Law have led to the destabilization and undermining of workers' job security. The research method is descriptive-analytical. To collect information, library and document sources in the field of laws related to labor rights in Iran and, semi-structured interviews with experts have been used. In the data analysis stage, the qualitative content analysis method was also used. The trend analysis of the statistics related to the labor force situation in Iran in the last three decades shows that the employment structure has been facing an increase in the active population, but in the last decade, a large part of this population has been mainly active in the service sector, and contract-free enterprises, so a smaller share of this employment has insurance coverage and a larger share has underemployment. In this regard, the results of this study show that four contexts have been proposed as the main legal and executive mechanisms of labor instability in Iran, which are: 1) temporaryization of the labor force by providing different interpretations of labor law, 2) adjustment labor in the public sector and the emergence of manpower contracting companies, 3) the cessation of labor law protection of workers in small workshops and 4) the existence of numerous restrictions on the effective organization of workers. The theoretical conclusion of this article is that the main root of the challenges of the labor society and the destabilized workforce in Iran is the existence of structural inequalities in the field of labor security, whose traces can be seen in the legal provisions and executive regulations of this field.

Keywords: inequality, precariat, temporaryization, labor force, labor law

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Authors: Shahab Mirzaean Mahabadi, Elham Ebrahimi

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The urban development process in the historical urban context has predominately witnessed two main approaches: the first is the Preservation and conservation of the urban fabric and its value, and the second approach is urban renewal and redevelopment. The latter is generally supported by political and economic aspirations. These two approaches conflict evidently. The authors go through the history of urban planning in order to review the historical development of the mentioned approaches. In this article, various values which are inherent in the historical fabric of a city are illustrated by emphasizing on cultural identity and activity. In the following, it is tried to find an optimized plan which maximizes economic development and minimizes change in historical-cultural sites simultaneously. In the proposed model, regarding the decision maker’s intention, and the variety of functions, the selected zone is divided into a number of components. For each component, different alternatives can be assigned, namely, renovation, refurbishment, destruction, and change in function. The decision Variable in this model is to choose an alternative for each component. A set of decisions made upon all components results in a plan. A plan developed in this way can be evaluated based on the decision maker’s point of view. That is, interactions between selected alternatives can make a foundation for the assessment of urban context to design a historical-cultural landscape. A genetic algorithm (GA) approach is used to search for optimal future land use within the historical-culture landscape for a sustainable high-growth city.

Keywords: urban sustainability, green city, regeneration, genetic algorithm

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Authors: Pubudu K. Hitigala Kaluarachchilage, Champike Attanayake, Sasith Rajasooriya, Chris P. Tsokos

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Operating system (OS) security is a key component of computer security. Assessing and improving OSs strength to resist against vulnerabilities and attacks is a mandatory requirement given the rate of new vulnerabilities discovered and attacks occurring. Frequency and the number of different kinds of vulnerabilities found in an OS can be considered an index of its information security level. In the present study five mostly used OSs, Microsoft Windows (windows 7, windows 8 and windows 10), Apple’s Mac and Linux are assessed for their discovered vulnerabilities and the risk associated with each. Each discovered and reported vulnerability has an exploitability score assigned in CVSS score of the national vulnerability database. In this study the risk from vulnerabilities in each of the five Operating Systems is compared. Risk Indexes used are developed based on the Markov model to evaluate the risk of each vulnerability. Statistical methodology and underlying mathematical approach is described. Initially, parametric procedures are conducted and measured. There were, however, violations of some statistical assumptions observed. Therefore the need for non-parametric approaches was recognized. 6838 vulnerabilities recorded were considered in the analysis. According to the risk associated with all the vulnerabilities considered, it was found that there is a statistically significant difference among average risk levels for some operating systems, indicating that according to our method some operating systems have been more risk vulnerable than others given the assumptions and limitations. Relevant test results revealing a statistically significant difference in the Risk levels of different OSs are presented.

Keywords: cybersecurity, Markov chain, non-parametric analysis, vulnerability, operating system

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Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

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Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Gopalasingam Daisan

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Landmines and ammunitions have been creating a significant threat to the people and animals, after the war, the landmines remain in the land and it plays a vital role in civilian’s security. Especially the Children are at the highest risk because they are curious. After all, an unexploded bomb can look like a tempting toy to an inquisitive child. The initial step of designing the UAS (Unmanned Aircraft Systems) for landmine detection is to choose an appropriate and effective sensor to locate the landmines and other unexploded ammunitions. The sensor weight and other components related to the sensor supporting device’s weight are taken as a payload weight. The mission requirement is to find the landmines in a particular area by making a proper path that will cover all the vicinity in the desired area. The weight estimation of the UAV (Unmanned Aerial Vehicle) can be estimated by various techniques discovered previously with good accuracy at the first phase of the design. The next crucial part of the design is to calculate the power requirement and the wing loading calculations. The matching plot techniques are used to determine the thrust-to-weight ratio, and this technique makes this process not only easiest but also precisely. The wing loading can be calculated easily from the stall equation. After these calculations, the wing area is determined from the wing loading equation and the required power is calculated from the thrust to weight ratio calculations. According to the power requirement, an appropriate engine can be selected from the available engine from the market. And the wing geometric parameter is chosen based on the conceptual sketch. The important steps in the wing design to choose proper aerofoil and which will ensure to create sufficient lift coefficient to satisfy the requirements. The next component is the tail; the tail area and other related parameters can be estimated or calculated to counteract the effect of the wing pitching moment. As the vertical tail design depends on many parameters, the initial sizing only can be done in this phase. The fuselage is another major component, which is selected based on the slenderness ratio, and also the shape is determined on the sensor size to fit it under the fuselage. The landing gear is one of the important components which is selected based on the controllability and stability requirements. The minimum and maximum wheel track and wheelbase can be determined based on the crosswind and overturn angle requirements. The minor components of the landing gear design and estimation are not the focus of this project. Another important task is to calculate the weight of the major components and it is going to be estimated using empirical relations and also the mass is added to each such component. The CG and moment of inertia are also determined to each component separately. The sensitivity of the weight calculation is taken into consideration to avoid extra material requirements and also reduce the cost of the design. Finally, the aircraft performance is calculated, especially the V-n (velocity and load factor) diagram for different flight conditions such as not disturbed and with gust velocity.

Keywords: landmine, UAS, matching plot, optimization

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Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandr, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine enginesrequiresa good control of its component temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system is significantly important to elongatethe lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate 2D surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement, such as thermocouples, thermal wall paints, pyrometry, and phosphors, have shown disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve two-dimensional high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of combustor in gas-turbine engines.

Keywords: borescope, engine, long-wave-infrared, sensor

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Safaa M. Hassan; Safwat S. Gabr, Mohamed F. Sadek

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This study is proposed for the lithological and iron oxides detection in the old mine areas of El-Bahariya Depression, Western Desert, using ASTER and Landsat-8 remote sensing data. Four old iron ore occurrences, namely; El-Gedida, El-Haraa, Ghurabi, and Nasir mine areas found in the El-Bahariya area. This study aims to find new high potential areas for iron mineralization around El-Baharyia depression. Image processing methods such as principle component analysis (PCA) and band ratios (b4/b5, b5/b6, b6/b7, and 4/2, 6/7, band 6) images were used for lithological identification/mapping that includes the iron content in the investigated area. ASTER and Landsat-8 visible and short-wave infrared data found to help mapping the ferruginous sandstones, iron oxides as well as the clay minerals in and around the old mines area of El-Bahariya depression. Landsat-8 band ratio and the principle component of this study showed well distribution of the lithological units, especially ferruginous sandstones and iron zones (hematite and limonite) along with detection of probable high potential areas for iron mineralization which can be used in the future and proved the ability of Landsat-8 and ASTER data in mapping these features. Minimum Noise Fraction (MNF), Mixture Tuned Matched Filtering (MTMF), pixel purity index methods as well as Spectral Ange Mapper classifier algorithm have been successfully discriminated the hematite and limonite content within the iron zones in the study area. Various ASTER image spectra and ASD field spectra of hematite and limonite and the surrounding rocks are compared and found to be consistent in terms of the presence of absorption features at range from 1.95 to 2.3 μm for hematite and limonite. Pixel purity index algorithm and two sub-pixel spectral methods, namely Mixture Tuned Matched Filtering (MTMF) and matched filtering (MF) methods, are applied to ASTER bands to delineate iron oxides (hematite and limonite) rich zones within the rock units. The results are validated in the field by comparing image spectra of spectrally anomalous zone with the USGS resampled laboratory spectra of hematite and limonite samples using ASD measurements. A number of iron oxides rich zones in addition to the main surface exposures of the El-Gadidah Mine, are confirmed in the field. The proposed method is a successful application of spectral mapping of iron oxides deposits in the exposed rock units (i.e., ferruginous sandstone) and present approach of both ASTER and ASD hyperspectral data processing can be used to delineate iron-rich zones occurring within similar geological provinces in any parts of the world.

Keywords: Landsat-8, ASTER, lithological mapping, iron exploration, western desert

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Authors: Mirjana Ilic, Dragan Zivotic, Aleksandra Perovic, Predrag Gavrilovic

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The service quality perception depends on many factors, such as the area in which the services are provided, socioeconomic status, educational status, experience, age and gender of consumers, as well as many others. For this reason, it is not possible to apply instrument for establishing the service quality perception that is developed in other areas and in other populations. The aim of the research was to form an instrument for assessing the quality perception in the field of fitness in Serbia. After analyzing the available literature and conducting a pilot research, there were 15 isolated areas in which it was possible to observe the service quality perception. The areas included: material and technical basis, secondary facilities, coaches, programs, reliability, credibility, security, rapid response, compassion, communication, prices, satisfaction, loyalty, quality outcomes and motives. These areas were covered by a questionnaire consisted of 100 items where the number of items varied from area to area from 3 up to 11. The questionnaire was administered to 350 subjects of both genders (174 men and 176 women) aged from 18 to 68 years, being beneficiaries of fitness services for at least 1 year. In each of the areas was conducted a factor analysis in its exploratory form by principal components method. The number of significant factors has been determined in accordance with the Kaiser Guttman criterion. The initial factor solutions were simplified using the Varimax rotation. Analyses per areas have produced from 1 to 4 factors. Afterward, the factor analysis of factor scores on the first principal component of each of the respondents in each of the analyzed area was performed, and the factor structure was obtained with four latent dimensions interpreted as offer, the relationship with the coaches, the experience of quality and the initial impression. This factor structure was analysed by hierarchical analysis of Oblique factors, which in the second order space produced single factor interpreted as a general factor of the service quality perception. The resulting questionnaire represents an instrument which can serve managers in the field of fitness to optimize the centers development, raising the quality of services in line with consumers needs and expectations.

Keywords: fitness, hierarchical model, quality perception, factor analysis

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Authors: Noryani Natasha Yahaya, Anas Ibrahim, Juraidah Ahmad, Azura Ahmad, Mohd Ikmal Fazlan Rosli, Zailan Ramli, Muhd Sidek Muhd Norhasri

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The subgrade formation is an important element of the railway structure which holds overall track stability. Conventional track maintenance involves many substructure component replacements, as well as track re-ballasting on a regular basis is partially contributed to the embankment's long-term settlement problem. For subgrade long-term stability analysis, the geophysical method is commonly being used to diagnose those hidden sources/mechanisms of track deterioration problems that the normal visual method is unable to detect. Electrical resistivity tomography (ERT) is one of the applicable geophysical tools that are helpful in railway subgrade inspection/track monitoring due to its flexibility and reliability of the analysis. The ERT was conducted at KM 23.0 of Pinang Tunggal track to investigate the subgrade of railway track through the characterization/mapping on track formation profiling which was directly generated using 2D analysis of Res2dinv software. The profiles will allow examination of the presence and spatial extent of a significant subgrade layer and screening of any poor contact of soil boundary. Based on the finding, there is a mix/interpretation/intermixing of an interlayer between the sub-ballast and the sand. Although the embankment track considered here is at no immediate risk of settlement effect or any failure, the regular monitoring of track’s location will allow early correction maintenance if necessary. The developed data of track formation clearly shows the similarity of the side view with the assessed track. The data visualization in the 2D section of the track embankment agreed well with the initial assumption based on the main element structure general side view.

Keywords: ground track, assessment, resistivity, geophysical railway, method

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Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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Authors: Alvaro Aguinaga, Carlos Avila, Edgar Cando

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This article proposes a n-layer architecture, with a web client as a front-end, for the development of a virtual platform for process simulation on CNC machines. This Open-Source platform includes a CAD-CAM interface drawing primitives, and then used to furnish a CNC program that triggers a touch-screen virtual simulator. The objectives of this project are twofold. First one is an educational component that fosters new alternatives for the CAD-CAM/CNC learning process in undergrad and grade schools and technical and technological institutes emphasizing in the development of critical skills, discussion and collaborative work. The second objective puts together a research and technological component that will take the state of the art in CAD-CAM integration to a new level with the development of optimal algorithms and virtual platforms, on-line availability, that will pave the way for the long-term goal of this project, that is, to have a visible and active graduate school in Ecuador and a world wide Open-Innovation community in the area of CAD-CAM integration and operation of CNC machinery. The virtual platform, developed as a part of this study: (1) delivers improved training process of students, (2) creates a multidisciplinary team and a collaborative work space that will push the new generation of students to face future technological challenges, (3) implements industry standards for CAD/CAM, (4) presents a platform for the development of industrial applications. A protoype of this system was developed and implemented in a network of universities and technological institutes in Ecuador.

Keywords: CAD-CAM integration, virtual platforms, CNC machines, multi-layer based architecture

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Authors: Branimir Jurun, Elza Jurun

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Focus of this paper is description and functioning manner of the instrument for wave pressure metering. Moreover, an essential component of this paper is the proposal of a metering unit for the direct wave pressure measurement determined by the shape and surface of the instrument including the number of sensors and angle between them. Namely, far applied instruments by means of height, length, direction, wave time period and other components determine wave pressure on a particular area. This instrument, allows the direct measurement i.e. measurement without additional calculation, of the wave pressure expressed in a standardized unit of measure. That way the instrument has a standardized form, surface, number of sensors and the angle between them. In addition, it is made with the status that follows the wave and always is on the water surface. Database quality which is listed by the instrument is made possible by using the Arduino chip. This chip is programmed for receiving by two data from each of the sensors each second. From these data by a pre-defined manner a unique representative value is estimated. By this procedure all relevant wave pressure measurement results are directly and immediately registered. Final goal of establishing such a rich database is a comprehensive statistical analysis that ranges from multi-criteria analysis across different modeling and parameters testing to hypothesis accepting relating to the widest variety of man-made activities such as filling of beaches, security cages for aquaculture, bridges construction.

Keywords: instrument, metering, water, waves

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Authors: Narin Salehiyan, Ramin Ghasemi Shayan

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In order to investigate coronavirus RNA replication, transcription, recombination, protein processing and transport, virion assembly, the identification of coronavirus-specific cell receptors, and polymerase processing, the manipulation of coronavirus clones and complementary DNAs (cDNAs) of defective-interfering (DI) RNAs is the subject of this chapter. The idea of the Covid genome is nonsegmented, single-abandoned, and positive-sense RNA. When compared to other RNA viruses, its size is significantly greater, ranging from 27 to 32 kb. The quality encoding the enormous surface glycoprotein depends on 4.4 kb, encoding a forcing trimeric, profoundly glycosylated protein. This takes off exactly 20 nm over the virion envelope, giving the infection the appearance-with a little creative mind of a crown or coronet. Covid research has added to the comprehension of numerous parts of atomic science as a general rule, like the component of RNA union, translational control, and protein transport and handling. It stays a fortune equipped for creating startling experiences.

Keywords: covid-19, corona, virus, genome, genetic

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

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Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords: consumer behavior, electronic word-of-mouth, online review, online word-of-mouth, Thai online consumer, webcare

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Authors: Giovanni Masala, Stefania Marica

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Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values.

Keywords: ARMA-GARCH process, electricity load, fitting tests, Fourier series, Monte Carlo simulation, non-linear regression

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Authors: Naveed Ul Hassan, Bilal Aziz, Maryam Mushtaq, Imran Ameen Khan

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Equity risk premium (ERP) is the stock return in excess of risk free return. Even though it is an essential topic of finance but still there is no common consensus upon its forecasting. For forecasting ERP, apart from the macroeconomic variables attention is devoted to technical indicators as well. For this purpose, set of 14 technical and 14 macro-economic variables is selected and all forecasts are generated based on a standard predictive regression framework, where ERP is regressed on a constant and a lag of a macroeconomic variable or technical indicator. The comparative results showed that technical indicators provide better indications about ERP estimates as compared to macro-economic variables. The relative strength of ERP predictability is also investigated by using National Bureau of Economic Research (NBER) data of business cycle expansion and recessions and found that ERP predictability is more than twice for recessions as compared to expansions.

Keywords: equity risk premium, forecasting, macroeconomic indicators, technical indicators

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Authors: Nasiru Aliyu, Glyn Atkinson, Nick Stannard

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With increasing demand for electric motors used in nearly all sectors of our day to day activities, which range from the motor that rotates the washing machine and dishwasher to the tens of thousands of motors used in domestic appliance. The number of applications for soft magnetic composites (SMC) material is growing significantly. This paper presents the development of a compact single sided concentrated winding axial flux PM motor using soft magnetic composite as core for reducing core losses and cost. The effects of changing the flux carrying component to pressed SMC parts are investigated based on a comprehensive understanding of the properties of the material. A 3-D finite-element analysis is performed for accurate parameter calculation. To validate the simulation, a new static test measurement was fully conducted on a prototype motor and agree with the theoretical calculations and old measured static test.

Keywords: SMC, compact development, axial field motor, 3DFA

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Authors: Hala A. Alrumaih

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It is widely believed that mobile device is a promising technology for lending the opportunity for the third wave of electronic commerce. Mobile devices have changed the way companies do business. Many applications are under development or being incorporated into business processes. In this day, mobile applications are a vital component of any industry strategy. One of the greatest benefits of selling merchandise and providing services on a mobile application is that it widens a company’s customer base significantly. Mobile applications are accessible to interested customers across regional and international borders in different electronic business (e-business) area. But there is a dark side to this success story. The security risks associated with mobile devices and applications are very significant. This paper introduces a broad risk analysis for the various threats, vulnerabilities, and risks in mobile e-business applications and presents some important risk mitigation approaches. It reviews and compares two different frameworks for security assurance in mobile e-business applications. Based on the comparison, the paper suggests some recommendations for applications developers and business owners in mobile e-business application development process.

Keywords: e-business, mobile applications, risk mitigations, security assurance

Procedia PDF Downloads 282