Search results for: validation indexes

Authors: Babak Nemat Shahrbabaki, Arezo Fallahi, Masoomeh Hashemian

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Introduction: Health and safety are basic components of civil right. Health care systems in different countries were influenced by political, economic and cultural circumstances. In order to health services to people, these systems are organized with different forms, methods such as: prevention, treatment and rehabilitation and in this among, public satisfaction with the services provided is important. This study aimed to determine client satisfaction with family physician and relationship with physician’ demographic variables in health care centers of Jiroft county, Iran. Methods: This is a descriptive-analytical study. The collective data tool was a self-made questionnaire with two parts. The first part comprised demographic characteristics, and the second part contained 11 items for the assessment of satisfaction with family physician from different aspects. In addition, questionnaire, reliability and validity were confirmed. Random simple sampling method was used to determine samples. 234 people referred to the health centers filled questionnaire. The data were analyzed using SPSS software, and inferential statistical analysis was performed. Findings: The majority of the study population were women, married, and aged between 18 and 62 years (mean= 30.09±10.71). Total average satisfaction score was 42.63±3.68. Overall satisfaction averages were 9.47% very high, 30.04% high, 33.09% moderate, 15.12% low, and 12.28% very low. Except lodge on of family physician none of physician’ demographic variables did not effect on satisfaction index. Discussion & Conclusion: The Results showed that mean of satisfaction indexes of family physicians was high and lodge on of family physician effected on this index. Informing people about the main goals of family-doctor program will help to promote the quality of program and increase people satisfaction.

Keywords: family physician program, satisfaction, health-care centers, client

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Authors: Xinglu Nie, Feifei Tang, Chuntao Wei, Zhimin Ruan, Qianhong Zhu

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Current method of manual-style inspection can not fully meet the requirement of the urban rail transit security in China. In this paper, an intelligent inspection method using unmanned aerial vehicle (UAV) is utilized. A series of orthophoto of rail transit monitored area was collected by UAV, image correction and registration were operated among multi-phase images, then the change detection was used to detect the changes, judging the engineering activities and human activities that may become potential threats to the security of urban rail. Not only qualitative judgment, but also quantitative judgment of changes in the security control area can be provided by this method, which improves the objectives and efficiency of the patrol results. The No.6 line of Chongqing Municipality was taken as an example to verify the validation of this method.

Keywords: rail transit, control of protected areas, intelligent inspection, UAV, change detection

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Authors: A. Elbatran, Y. Ahmed, A. Radwan, M. Ishak

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The use of WIG craft is representing an ambitious technology that will support in reducing time, effort, and money of the conventional marine transportation in the future. This paper investigates the aerodynamic characteristic of compound wing-in-ground effect (WIG) craft model. Drag coefficient, lift coefficient and Lift and drag ratio were studied numerically with respect to the ground clearance and the wing angle of attack. The modifications of the wing has been done in order to investigate the most suitable wing configuration that can increase the wing lift-to-drag ratio at low ground clearance. A numerical investigation was carried out in this research work using finite volume Reynolds-Averaged Navier-Stokes Equations (RANSE) code ANSYS CFX, Validation was carried out by using experiments. The experimental and the numerical results concluded that the lift to drag ratio decreased with the increasing of the ground clearance.

Keywords: drag Coefficient, ground clearance, navier-stokes, WIG

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Authors: Lee Woong-Kyu

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Fierce competition in smartphone market may encourage users to switch brands when buying a new smartphone. However, many smartphone users continue to use the same brand although other branded smartphones are perceived to be more attractive. The purpose of this study is to identify and analyze the effects of brand loyalty toward incumbent smartphone on new smartphone adoption. For this purpose, a research model including two hypotheses, the positive effect on rational judgments and the negative effect on rational judgments, are proposed based on the dual process theory. For the validation of the research model, the data was collected by surveying Korean university students and tested by the group comparison between high and low brand loyalty. The results show that the two hypotheses were statistically supported.

Keywords: brand loyalty, dual process theory, incumbent smartphone, smartphone adoption

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Evgeniya Ivanova

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Nowadays, in the literature, there is still no fixed definition of knowledge management that often remains only as an academic discipline. The current market situation is changing very quickly, the need of new technologies is high, and knowledge management is the area that ensures that the know-how has not been lost during market development and adoption. The study examines how knowledge management is being leveraged and practiced in the management consultancy companies and provides not only the tips and best practices of applied knowledge management approaches but also the validation matrix for its successful or unsuccessful implementation. Different knowledge management approaches are explored on the basis of their practical implementation, including related challenges, knowledge sharing process, and barriers that are typical for consulting firms mostly driven by the agile working culture. The relevance of proposed topic is confirmed by the finding that corporate working culture and the exponentially developing technologies have a direct impact on the success of practical implementation of knowledge management.

Keywords: knowledge management, knowledge management in practice, consulting firm, knowledge management success

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: Gul Selin Erben

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Precariousness can be evaluated as the new employment climate of the neo-liberal employment markets. As the word refers to a new mode of employment experience and working practices, it was felt as a necessity to reveal the basic characteristics of this kind of employment experience. Furthermore, according to the literature, precarious employment practices have some negative outcomes such as alienation, sense of anger, and anomy. Thus, it has quite significant to reveal the conditions' characteristics and practices of precarious employment. This study has the purpose to develop an instrument which measures the precarious employment practices. In order to develop a precariousness scale, the relevant literature was examined, and 30 statements were established as a result of the literature review. The development and validation of the scale were done by a sample of 123 individuals who work in different sectors in İstanbul as a white color employee. Convenience sampling was used as a sampling methodology. Reliability and factor analysis were conducted. As a result of the exploratory factor analysis, 3 dimensions were gathered.

Keywords: employment, employment experience, precariousness, scale development

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Authors: Paul W. Murray, Marco Barajas

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Recent changes in supply chains, especially globalization and collaboration, have created new risks for enterprises of all sizes. A variety of complex frameworks, often based on enterprise risk management strategies have been presented under the heading of Supply Chain Risk Management (SCRM). The literature on promotes the benefits of a robust SCRM strategy; however, implementing SCRM is difficult and resource demanding for Large Enterprises (LEs), and essentially out of reach for Small and Medium Enterprises (SMEs). This research debunks the idea that SCRM is necessary for all enterprises and instead proposes a simple and effective Vendor Selection Template (VST). Empirical testing and a survey of supply chain practitioners provide a measure of validation to the VST. The resulting VSTis a valuable contribution because is easy to use, provides practical results, and is sufficiently flexible to be universally applied to SMEs.

Keywords: multiple regression analysis, supply chain management, risk assessment, vendor selection

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Authors: Natcha Lueangapapong, Chariya Chuthapisith, Lunliya Thampratankul

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Background: There is a need to find an appropriate tool to help healthcare providers determine sleep problems in children for early diagnosis and management. The Japanese Sleep Questionnaire for Preschoolers (JSQ-P) is a parent-reported sleep questionnaire that has good psychometric properties and can be used in the context of Asian culture, which is likely suitable for Thai children. Objectives: This study aimed to translate and validate the Japanese Sleep Questionnaire for Preschoolers (JSQ-P) into a Thai version and to evaluate factors associated with sleep disorders in preschoolers. Methods: After approval by the original developer, the cross-cultural adaptation process of JSQ-P was performed, including forward translation, reconciliation, backward translation, and final approval of the Thai version of JSQ-P (TH-JSQ-P) by the original creator. This study was conducted between March 2021 and February 2022. The TH-JSQ-P was completed by 2,613 guardians whose children were aged 2-6 years twice in 10-14 days to assess its reliability and validity. Content validity was measured by an index of item-objective congruence (IOC) and a content validity index (CVI). Face validity, content validity, structural validity, construct validity (discriminant validity), criterion validity and predictive validity were assessed. The sensitivity and specificity of the TH-JSQ-P were also measured by using a total JSQ-P score cutoff point 84, recommended by the original JSQ-P and each subscale score among the clinical samples of obstructive sleep apnea syndrome. Results: Internal consistency reliability, evaluated by Cronbach’s α coefficient, showed acceptable reliability in all subscales of JSQ-P. It also had good test-retest reliability, as the intraclass correlation coefficient (ICC) for all items ranged between 0.42-0.84. The content validity was acceptable. For structural validity, our results indicated that the final factor solution for the Th-JSQ-P was comparable to the original JSQ-P. For construct validity, age group was one of the clinical parameters associated with some sleep problems. In detail, parasomnias, insomnia, daytime excessive sleepiness and sleep habits significantly decreased when the children got older; on the other hand, insufficient sleep was significantly increased with age. For criterion validity, all subscales showed a correlation with the Epworth Sleepiness Scale (r = -0.049-0.349). In predictive validity, the Epworth Sleepiness Scale was significantly a strong factor that correlated to sleep problems in all subscales of JSQ-P except in the subscale of sleep habit. The sensitivity and specificity of the total JSQ-P score were 0.72 and 0.66, respectively. Conclusion: The Thai version of JSQ-P has good internal consistency reliability and test-retest reliability. It passed 6 validity tests, and this can be used to evaluate sleep problems in preschool children in Thailand. Furthermore, it has satisfactory general psychometric properties and good reliability and validity. The data collected in examining the sensitivity of the Thai version revealed that the JSQ-P could detect differences in sleep problems among children with obstructive sleep apnea syndrome. This confirmed that the measure is sensitive and can be used to discriminate sleep problems among different children.

Keywords: preschooler, questionnaire, validation, Thai version

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Authors: Abdel Hadi N. Ebraheim, Eman Azomi, Nefisa A. Fahmy

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This paper designs and implements a computer-aided system (CAS) to help detect and diagnose liver cirrhosis in patients with Chronic Hepatitis C. Our system reduces the required features (tests) the patient is asked to do to tests to their minimal best most informative subset of tests, with a diagnostic accuracy above 99%, and hence saving both time and costs. We use the Support Vector Machine (SVM) with cross-validation, a Multilayer Perceptron Neural Network (MLP), and a Generalized Regression Neural Network (GRNN) that employs a base of radial functions for functional approximation, as classifiers. Our system is tested on 199 subjects, of them 99 Chronic Hepatitis C.The subjects were selected from among the outpatient clinic in National Herpetology and Tropical Medicine Research Institute (NHTMRI).

Keywords: liver cirrhosis, artificial neural network, support vector machine, multi-layer perceptron, classification, accuracy

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Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

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Authors: Ali Asmari, Alex Symington, Htaik Than, Austin Caradonna, John Senft

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This paper presents the collaborative effort between ULC Technologies and Con Edison in developing a groundbreaking robotic cable splicing machine. The focus is on the machine's design, which integrates advanced robotics and automation to enhance safety and efficiency in power network maintenance. The paper details the operational steps of the machine, including cable grounding, cutting, and removal of different insulation layers, and discusses its novel technological approach. The significant benefits over traditional methods, such as improved worker safety and reduced outage times, are highlighted based on the field data collected during the validation phase of the project. The paper also explores the future potential and scalability of this technology, emphasizing its role in transforming the landscape of power network maintenance.

Keywords: cable splicing machine, power network maintenance, electric distribution, electric transmission, medium voltage cable

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Authors: Mary Allagoa, Abir Al-Tabbaa

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The study explores the use of binders and additives, such as Portland cement, pulverized fuel ash, ground granulated blast furnace slag, and MgO, to decrease the concentration and leachability of pollutants in contaminated site soils. The research investigates their effectiveness and associated risks of using the binders, with a focus on Total Heavy metals (THM) and Total Petroleum Hydrocarbon (TPH). The goal of this research is to evaluate the performance and effectiveness of binders and additives in remediating soil pollutants. The study aims to assess the suitability of the mixtures for ground improvement purposes, determine the optimal dosage, and investigate the associated risks. The research utilizes physical (unconfined compressive strength) and chemical tests (batch leachability test) to assess the efficacy of the binders and additives. A completely randomized design one-way ANOVA is used to determine the significance within mix binders of THM. The study also employs incremental lifetime cancer risk assessments (ILCR) and other indexes to evaluate the associated risks. The study finds that Ground Granulated Blast Furnace Slag (GGBS): MgO is the most effective binder for remediation, particularly when using low dosages of MgO combined with higher dosages of GGBS binders on TPH. The results indicate that binders and additives can encapsulate and immobilize pollutants, thereby reducing their leachability and toxicity. The mean unconfined compressive strength of the soil ranges from 285.0- 320.5 kPa, while THM levels are less than 10 µg/l in GGBS: MgO and CEM: PFA but below 1 µg/l in CEM I based. The ILCR ranged from 6.77E-02 - 2.65E-01 and 5.444E-01 – 3.20 E+00, with the highest values observed under extreme conditions. The hazard index (HI), Risk allowable daily dose intake (ADI), and Risk chronic daily intake (CDI) were all less than 1 for the THM. The study identifies MgO as the best additive for use in soil remediation.

Keywords: risk ADI, risk CDI, ILCR, novel binders, additives binders, hazard index

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Authors: Soulef Amamria, Mohamed Sadok Bensalem, Mohamed Ghanmi

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The structural and sedimentological study of fault-related- folds in the Southern Tunisian Atlas is distinguished by a special geometry of the gravitational structures. This distinct geometry is observable in the example of a flap structure in Jebel Ben Zannouch with the formation of a stuck syncline. This geometry can be explained by the mechanism of major thrusting in Orbata anticline in the occidental extremity of Gafsa chains, with asymmetrical flank dips and hinge migration kinematics. These kinematics was originally controlled by the Breakthrough structure; the study of this special geometry of gravity flap structure depends on the sedimentation domain, shortening ratios, and erosion speed. This study constitutes one of the complete examples of kinematic model validation on a field scale.

Keywords: fault-related-folds, southern Tunisian Atlas, flap structure, breakthrough

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Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

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Authors: Lokanath Barik, Abinash Kumar Swain

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This paper presents vibration analysis of FGM sandwich structure with a complex profile governed by refined higher-order shear deformation theory (RHSDT) using isogeometric analysis (IGA). Functionally graded sandwich plates provide a wide range of applications in aerospace, defence, and aircraft industries due to their ability to distribute material functions to influence the thermo-mechanical properties as desired. In practical applications, these structures generally have intrinsic profiles, and their response to loads is significantly affected due to cut-outs. IGA is primarily a NURBS-based technique that is effective in solving higher-order differential equations due to its inherent C1 continuity imposition in solution space for a single patch. Complex structures generally require multiple patches to accurately represent the geometry, and hence, there is a loss of continuity at adjoining patch junctions. Therefore, patch coupling is desired to maintain continuity requirements throughout the domain. In this work, a novel strong coupling approach is provided that generates a well-defined NURBS-based model while achieving continuity. The methodology is validated by free vibration analysis of sandwich plates with present literature. The results are in good agreement with the analytical solution for different plate configurations and power law indexes. Numerical examples of rectangular and annular plates are discussed with variable boundary conditions. Additionally, parametric studies are provided by varying the aspect ratio, porosity ratio and their influence on the natural frequency of the plate.

Keywords: vibration analysis, FGM sandwich structure, multipatch geometry, patch coupling, IGA

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Authors: Brayan S. Pabón, R. Ricardo Moreno, Edith Gonzalez

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Inside the wide Colombian natural fiber set is the banana stem leaf, known as Calceta de Plátano, which is a material present in several regions of the country and is a fiber extracted from the pseudo stem of the banana plant (Musa paradisiaca) as a regular maintenance process. Colombia had a production of 2.8 million tons in 2007 and 2008 corresponding to 8.2% of the international production, number that is growing. This material was selected to be studied because it is not being used by farmers due to it being perceived as a waste from the banana harvest and a propagation pest agent inside the planting. In addition, the Calceta does not have industrial applications in Colombia since there is not enough concrete knowledge that informs us about the properties of the material and the possible applications it could have. Based on this situation the industrial design is used as a link between the properties of the material and the need to transform it into industrial products for the market. Therefore, the project identifies potential design attributes that the banana stem leaf can have for product development. The methodology was divided into 2 main chapters: Methodology for the material recognition: -Data Collection, inquiring the craftsmen experience and bibliography. -Knowledge in practice, with controlled experiments and validation tests. -Creation of design attributes and material profile according to the knowledge developed. Moreover, the Design methodology: -Application fields selection, exploring the use of the attributes and the relation with product functions. -Evaluating the possible fields and selection of the optimum application. -Design Process with sketching, ideation, and product development. Different protocols were elaborated to qualitatively determine some material properties of the Calceta, and if they could be designated as design attributes. Once defined, performed and analyzed the validation protocols, 25 design attributes were identified and classified into 4 attribute categories (Environmental, Functional, Aesthetics and Technical) forming the material profile. Then, 15 application fields were defined based on the relation between functions of product and the use of the Calceta attributes. Those fields were evaluated to measure how much are being used the functional attributes. After fields evaluation, a final field was defined , influenced by traditional use of the fiber for packing food. As final result, two products were designed for this application field. The first one is the Multiple Container, which works to contain small or large-thin pieces of food, like potatoes chips or small sausages; it allows the consumption of food with sauces or dressings. The second is the Chorizo container, specifically designed for this food due to the long shape and the consumption mode. Natural fiber research allows the generation of a solider and a more complete knowledge about natural fibers. In addition, the research is a way to strengthen the identity through the investigation of the proper and autochthonous, allowing the use of national resources in a sustainable and creative way. Using divergent thinking and the design as a tool, this investigation can achieve advances in the natural fiber handling.

Keywords: banana stem leaf, Calceta de Plátano, design attributes, natural fibers, product design

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Authors: Alexandra Sargent, Sarah Ferris, Ioannis Theofanous

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The Abbott RealTime High Risk HPV test (RealTime HPV) is one of five assays clinically validated and approved by the English NHS Cervical Screening Programme (CSP) for HPV triage of low grade dyskaryosis and test-of-cure of treated Cervical Intraepithelial Neoplasia. The assay is a highly automated multiplex real-time PCR test for detecting 14 high risk (hr) HPV types, with simultaneous differentiation of HPV 16 and HPV 18 versus non-HPV 16/18 hrHPV. An endogenous internal control ensures sample cellularity, controls extraction efficiency and PCR inhibition. The original cervical specimen collected in SurePath (SP) liquid-based cytology (LBC) medium (BD Diagnostics) and the SP post-gradient cell pellets (SPG) after cytological processing are both CE marked for testing with the RealTime HPV test. During the 2011 NHSCSP validation of new tests only the original aliquot of SP LBC medium was investigated. Residual sample volume left after cytology slide preparation is low and may not always have sufficient volume for repeat HPV testing or for testing of other biomarkers that may be implemented in testing algorithms in the future. The SPG samples, however, have sufficient volumes to carry out additional testing and necessary laboratory validation procedures. This study investigates the correlation of RealTime HPV results of cervical specimens collected in SP LBC medium from women with low grade cytological abnormalities observed with matched pairs of original SP LBC medium and SP post-gradient cell pellets (SPG) after cytology processing. Matched pairs of SP and SPG samples from 750 women with borderline (N = 392) and mild (N = 351) cytology were available for this study. Both specimen types were processed and parallel tested for the presence of hrHPV with RealTime HPV according to the manufacturer´s instructions. HrHPV detection rates and concordance between test results from matched SP and SPGCP pairs were calculated. A total of 743 matched pairs with valid test results on both sample types were available for analysis. An overall-agreement of hrHPV test results of 97.5% (k: 0.95) was found with matched SP/SPG pairs and slightly lower concordance (96.9%; k: 0.94) was observed on 392 pairs from women with borderline cytology compared to 351 pairs from women with mild cytology (98.0%; k: 0.95). Partial typing results were highly concordant in matched SP/SPG pairs for HPV 16 (99.1%), HPV 18 (99.7%) and non-HPV16/18 hrHPV (97.0%), respectively. 19 matched pairs were found with discrepant results: 9 from women with borderline cytology and 4 from women with mild cytology were negative on SPG and positive on SP; 3 from women with borderline cytology and 3 from women with mild cytology were negative on SP and positive on SPG. Excellent correlation of hrHPV DNA test results was found between matched pairs of SP original fluid and post-gradient cell pellets from women with low grade cytological abnormalities tested with the Abbott RealTime High-Risk HPV assay, demonstrating robust performance of the test with both specimen types and reassuring the utility of the assay for cytology triage with both specimen types.

Keywords: Abbott realtime test, HPV, SurePath liquid based cytology, surepath post-gradient cell pellet

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Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Ahmed Hammed, Wady Naanaa

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In this paper, we propose a general approach to deal with the problem of a convolutive mixture of images. We use a direct blind source separation method by adding only one non-statistical justified constraint describing the relationships between different mixing matrix at the aim to make its resolution easy. This method can be applied, provided that this constraint is known, to degraded document affected by the overlapping of text-patterns and images. This is due to chemical and physical reactions of the materials (paper, inks,...) occurring during the documents aging, and other unpredictable causes such as humidity, microorganism infestation, human handling, etc. We will demonstrate that this problem corresponds to a convolutive mixture of images. Subsequently, we will show how the validation of our method through numerical examples. We can so obtain clear images from unreadable ones which can be caused by pages superposition, a phenomenon similar to that we find every often in archival documents.

Keywords: blind source separation, convoluted mixture, degraded documents, text-patterns overlapping

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Authors: Ashwini Umale

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Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning around obstacles and subsequent optimization of a trajectory satisfying dynamical constraints. An optimized trajectory of multi-axis robot is important and directly influences the Performance of the executing task. Optimal is defined to be the minimum time to transition from the current speed to the set speed. In optimization of trajectory through virtual environment explores the most suitable way to represent robot motion from virtual environment to real environment. This paper aims to review the research of trajectory optimization in virtual environment using simulation software Robcad. Improvements are to be expected in trajectory optimization to generate smooth and collision free trajectories with minimization of overall robot cycle time.

Keywords: trajectory optimization, forward kinematics and reverse kinematics, dynamic constraints, robcad simulation software

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Authors: Durga Toshniwal, Lokesh Agrawal

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As the web continues to play an increasing role in information exchange, and conducting daily activities, computer users have become the target of miscreants which infects hosts with malware or adware for financial gains. Unfortunately, even a single visit to compromised web site enables the attacker to detect vulnerabilities in the user’s applications and force the downloading of multitude of malware binaries. We provide an approach to effectively scan the so-called drive-by downloads on the Internet. Drive-by downloads are result of URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. To scan the web for malicious pages, the first step is to use a crawler to collect URLs that live on the Internet, and then to apply fast prefiltering techniques to reduce the amount of pages that are needed to be examined by precise, but slower, analysis tools (such as honey clients or antivirus programs). Although the technique is effective, it requires a substantial amount of resources. A main reason is that the crawler encounters many pages on the web that are legitimate and needs to be filtered. In this paper, to characterize the nature of this rising threat, we present implementation of a web crawler on Python, an approach to search the web more efficiently for pages that are likely to be malicious, filtering benign pages and passing remaining pages to antivirus program for detection of malwares. Our approaches starts from an initial seed of known, malicious web pages. Using these seeds, our system generates search engines queries to identify other malicious pages that are similar to the ones in the initial seed. By doing so, it leverages the crawling infrastructure of search engines to retrieve URLs that are much more likely to be malicious than a random page on the web. The results shows that this guided approach is able to identify malicious web pages more efficiently when compared to random crawling-based approaches.

Keywords: web crawler, malwares, seeds, drive-by-downloads, security

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Authors: A. Delimitsou, C. Gouedard, E. Konstanta, A. Koletis, S. Patera, E. Manou, K. Spaho, S. Murray

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Background: There remains a lack of International Standard Control Reference materials for Next Generation Sequencing-based approaches or device calibration. We have designed and validated dsDNA biomimetic reference materials for targeted such approaches incorporating proprietary motifs (patent pending) for device/test calibration. They enable internal single-sample calibration, alleviating sample comparisons to pooled historical population-based data assembly or statistical modelling approaches. We have validated such an approach for BRCA Copy Number Variation analytics using iQRS™-CNVSUITE versus Mixed Ligation-dependent Probe Amplification. Methods: Standard BRCA Copy Number Variation analysis was compared between mixed ligation-dependent probe amplification and next generation sequencing using a cohort of 198 breast/ovarian cancer patients. Next generation sequencing based copy number variation analysis of samples spiked with iQRS™ dsDNA biomimetics were analysed using proprietary CNVSUITE software. Mixed ligation-dependent probe amplification analyses were performed on an ABI-3130 Sequencer and analysed with Coffalyser software. Results: Concordance of BRCA – copy number variation events for mixed ligation-dependent probe amplification and CNVSUITE indicated an overall sensitivity of 99.88% and specificity of 100% for iQRS™-CNVSUITE. The negative predictive value of iQRS-CNVSUITE™ for BRCA was 100%, allowing for accurate exclusion of any event. The positive predictive value was 99.88%, with no discrepancy between mixed ligation-dependent probe amplification and iQRS™-CNVSUITE. For device calibration purposes, precision was 100%, spiking of patient DNA demonstrated linearity to 1% (±2.5%) and range from 100 copies. Traditional training was supplemented by predefining the calibrator to sample cut-off (lock-down) for amplicon gain or loss based upon a relative ratio threshold, following training of iQRS™-CNVSUITE using spiked iQRS™ calibrator and control mocks. BRCA copy number variation analysis using iQRS™-CNVSUITE™ was successfully validated and ISO15189 accredited and now enters CE-IVD performance evaluation. Conclusions: The inclusion of a reference control competitor (iQRS™ dsDNA mimetic) to next generation sequencing-based sequencing offers a more robust sample-independent approach for the assessment of copy number variation events compared to mixed ligation-dependent probe amplification. The approach simplifies data analyses, improves independent sample data analyses, and allows for direct comparison to an internal reference control for sample-specific quantification. Our iQRS™ biomimetic reference materials allow for single sample copy number variation analytics and further decentralisation of diagnostics to single patient sample assessment.

Keywords: validation, diagnostics, oncology, copy number variation, reference material, calibration

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

Abstract:

The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

Abstract:

This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: Othman Mohamed Altheni, Abdurrahman Abusaada

Abstract:

This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulsed current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg. Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters are simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used

Keywords: edm parameters, grey relational analysis, Taguchi method, ANOVA

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Authors: Shazia Bano

Abstract:

Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

Abstract:

This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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