Search results for: scale invariant feature

Authors: Ni Wayan Sinthia Widiastuti, Komang Rahayu Indrawati

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The increasing number of tourists coming to Bali, causing accommodation facilities, such as hotels have increased. The existence of hotel needs will be the source of labor and cost efficiency, so that hotel management employs employees with different working status. The hospitality industry is one of the sectors that require organizational citizenship behavior because, the main goal of every hotel, in general, was to provide the best service and quality to tourists. The purpose of this study was to determine the differences in organizational citizenship behavior based on work status of employees at the Hotel in Bali in terms of quality of work life. Research sample was chosen randomly through two-stage cluster sampling which succeeds to obtain 126 samples from 11 hotels in Denpasar, Bali. The subjects consisted of 64 employees with Employment Agreement of Uncertain Time or who is often called a permanent employee and 62 employees with Employment Agreement of Certain Time or better known as contract employees, outsourcing, and daily workers. Instruments in this study were the scale of organizational citizenship behavior and the scale of quality of work life. The results of ANCOVA analysis showed there were differences in organizational citizenship behavior based on employee work status in terms of quality of work life. Differences in organizational citizenship behavior and quality of work life based on work status of employees using comparative test was analysis by independent sample t-test shows there were differences in organizational citizenship behavior and quality of work life between employees with different working status in hotels in Bali. The result of the regression analysis showed the functional relationship between quality of work life and organizational citizenship behavior.

Keywords: hotel in Bali, organizational citizenship behavior, quality of work life, work status of employees

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Authors: Lee Tasker, Ali Karrech, Jeffrey Shragge, Matthew Josh

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Monitoring for the deterioration of concrete infrastructure is an important assessment tool for an engineer and difficulties can be experienced with monitoring for deterioration within an infrastructure. If a failure crack, or fluid seepage through such a crack, is observed from the surface often the source location of the deterioration is not known. Geophysical methods are used to assist engineers with assessing the subsurface conditions of materials. Techniques such as Ground Penetrating Radar (GPR) provide information on the location of buried infrastructure such as pipes and conduits, positions of reinforcements within concrete blocks, and regions of voids/cavities behind tunnel lining. This experiment underlines the application of GPR as an infrastructure-monitoring tool to highlight and monitor regions of possible deterioration within a concrete test wall due to an increase in the generation of fractures; in particular, during a time period of applied load to a concrete wall up to and including structural failure. A three-point load was applied to a concrete test wall of dimensions 1700 x 600 x 300 mm³ in increments of 10 kN, until the wall structurally failed at 107.6 kN. At each increment of applied load, the load was kept constant and the wall was scanned using GPR along profile lines across the wall surface. The measured radar amplitude responses of the GPR profiles, at each applied load interval, were reconstructed into depth-slice grids and presented at fixed depth-slice intervals. The corresponding depth-slices were subtracted from each data set to compare the radar amplitude response between datasets and monitor for changes in the radar amplitude response. At lower values of applied load (i.e., 0-60 kN), few changes were observed in the difference of radar amplitude responses between data sets. At higher values of applied load (i.e., 100 kN), closer to structural failure, larger differences in radar amplitude response between data sets were highlighted in the GPR data; up to 300% increase in radar amplitude response at some locations between the 0 kN and 100 kN radar datasets. Distinct regions were observed in the 100 kN difference dataset (i.e., 100 kN-0 kN) close to the location of the final failure crack. The key regions observed were a conical feature located between approximately 3.0-12.0 cm depth from surface and a vertical linear feature located approximately 12.1-21.0 cm depth from surface. These key regions have been interpreted as locations exhibiting an increased change in pore-space due to increased mechanical loading, or locations displaying an increase in volume of micro-cracks, or locations showing the development of a larger macro-crack. The experiment showed that GPR is a useful geophysical monitoring tool to assist engineers with highlighting and monitoring regions of large changes of radar amplitude response that may be associated with locations of significant internal structural change (e.g. crack development). GPR is a non-destructive technique that is fast to deploy in a production setting. GPR can assist with reducing risk and costs in future infrastructure maintenance programs by highlighting and monitoring locations within the structure exhibiting large changes in radar amplitude over calendar-time.

Keywords: 4D GPR, engineering geophysics, ground penetrating radar, infrastructure monitoring

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

Procedia PDF Downloads 277

Authors: Amjad Nusayr

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Software security is a general term used to any type of software architecture or model in which security aspects are incorporated in this architecture. These aspects are not part of the main logic of the underlying program. Software security can be achieved using a combination of approaches, including but not limited to secure software designs, third part component validation, and secure coding practices. Memory safety is one feature in software security where we ensure that any object in memory has a valid pointer or a reference with a valid type. Aspect-Oriented Programming (AOP) is a paradigm that is concerned with capturing the cross-cutting concerns in code development. AOP is generally used for common cross-cutting concerns like logging and DB transaction managing. In this paper, we introduce the concepts that enable AOP to be used for the purpose of memory and type safety. We also present ideas for extending AOP in software security practices.

Keywords: aspect oriented programming, programming languages, software security, memory and type safety

Procedia PDF Downloads 127

Authors: Gokcen Akyurek, Hulya Kayihan, Deniz Yuce, Selen Yilmaz

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The stigma towards mental illness is still very rooted in our society, despite the number of studies, campaigns, and anti-stigma programs developed in recent years. Stigma represents a serious obstacle to recovery and social integration for people who experience a mental illness, affecting directly their well-being and quality of life. It implies that these persons have to deal with many other barriers apart from the disease symptoms (1-5). Convergent, recent literature suggests that less positive attitudes by mental health professionals interfere with the self-determination and recovery process (4-10).The aim of this study was to translate the Attribution Questionnaire-27 (AQ-27) to the Turkish language (AQ-27-T), and to examine the reliability and validity of this new Turkish version. Cultural adaptation was implemented according to the internationally suggested method. To determine the understandability and appropriateness of this measure for the Turkish culture, a pretest was administered and the final form was generated. Then, 424 randomly chosen people took part in the study. Participant’s mean age was 36.9±12.7 years and %52 of them female. Cronbach's alpha and intra-class coefficients were used to estimate instrument reliability. The AQ-27-T was assessed again 14 days later for test retest reliability. The AQ-27-T demonstrated acceptable internal consistency, with a Cronbach's alpha of 0.88 for the total scale and ranging between 0.86 and 0.89 for the items. The test-retest reliability was good, with Pearson correlation coefficients of 0.79 for the total scale and ranging between 0.35 and 0.77 for the items (p<0.05). Correlation between subscales was moderate-good, with Pearson correlation coefficients of 0.18-0.88 (p<0.05). Fit indices of the model supported the factor structure and paths. The AQ-27-T is a reliable measure to assess stigmatizing attitudes in Turkish.

Keywords: attribution questionnaire, validity, reliability, stigma

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Authors: Salmi-Laouar Sihem, Aouissi Riadh

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The Cenomanian formations of the Bellezma-Batna Range are yielding very diversified fossiliferous beds. Among the abundant and well-preserved fossils stands out Aspidiscus cristatus (Lamarck). This taxon is assigned to the Family Latomeandridae (Alloiteau) for the presence of six symmetry axes. The outer morphology of sampled specimens documents a low-energy environment with a high sedimentary rate and a mud-supported bottom. Its provincialism evidences some characteristic thermal gradients of the marked Tethysian climatic areas. Biometric measurements are given. Coral size increases from the North towards the southeastern Tethysian margin where waters are supposed warmer; this feature is also underlined by a frequent bio-erosion of sampled specimens. Its limited stratigraphic range makes it a good candidate for an index species for the Middle Cenomanian.

Keywords: Aspidiscus cristatus, coral, Middle Cenomanian, Batna, Bellezma, Algeria

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Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

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Authors: Lucie Mrackova, Helena Kisvetrova

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Spirituality is an integral part of human life. In a secular environment, spiritual needs are often overlooked, especially in acute nursing care. Spiritual needs assessment for patients (SNAP), which also exists in the Czech version (SNAP-CZ), can be used for objective evaluation. The aim of this study was to measure the psychometric properties of SNAP-CZ and to find correlations between SNAP-CZ and sociodemographic and clinical variables. A cross-sectional study with tools assessing spiritual needs (SNAP-CZ), anxiety (Beck Anxiety Inventory; BAI), depression (Beck Depression Inventory; BDI), pain (Visual Analogue Scale; VAS), self-sufficiency (Barthel Index; BI); cognitive function (Montreal Cognitive Test; MoCa) and selected socio-demographic data was performed. The psychometric properties of SNAP-CZ were tested using factor analysis, reliability and validity tests, and correlations between the questionnaire and sociodemographic data and clinical variables. Internal consistency was established with Cronbach’s alfa for the overall score, respective domains, and individual items. Reliability was assessed by test-retest by Interclass correlation coefficient (ICC). Data for correlation analysis were processed according to Pearson's correlation coefficient. The study included 172 trauma patients (the mean age = 40.6 ± 12.1 years) who experienced polytrauma or severe monotrauma. There were a total of 106 (61.6%) male subjects, 140 (81.4%) respondents identified themselves as non-believers. The full-scale Cronbach's alpha was 0.907. The test-retest showed the reliability of the individual domains in the range of 0.924 to 0.960 ICC. Factor analysis resulted in a three-factor solution (psychosocial needs (alfa = 0.788), spiritual needs (alfa = 0.886) and religious needs (alfa = 0.841)). Correlation analysis using Pearson's correlation coefficient showed that the domain of psychosocial needs significantly correlated only with gender (r = 0.178, p = 0.020). Males had a statistically significant lower average value in this domain (mean = 12.5) compared to females (mean = 13.8). The domain of spiritual needs significantly correlated with gender (r = 0.199, p = 0.009), social status (r = 0.156, p = 0.043), faith (r = -0.250, p = 0.001), anxiety (r = 0.194, p = 0.011) and depression (r = 0.155, p = 0.044). The domain of religious needs significantly correlated with age (r = 0,208, p = 0,007), education (r = -0,161, p = 0,035), faith (r = -0,575, p < 0,0001) and depression (r = 0,179, p = 0,019). Overall, the whole SNAP scale significantly correlated with gender (r = 0.219, p = 0.004), social status (r = 0.175, p = 0.023), faith (r = -0.334, p <0.0001), anxiety (r = 0.177, p = 0.022) and depression (r = 0.173, p = 0.025). The results of this study corroborate the reliability of the SNAP-CZ and support its future use in the nursing care of trauma patients in a secular society. Acknowledgment: The study was supported by grant nr. IGA_FZV_2020_003.

Keywords: acute nursing care, assessment of spiritual needs, patient, psychometric validation, spirituality

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Authors: Paramjit Kaur, Harish Kundra

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In the recent years, swarm intelligence based firefly algorithm has become a great focus for the researchers to solve the real time optimization problems. Here, firefly algorithm is used for the application of satellite image classification. For experimentation, Alwar area is considered to multiple land features like vegetation, barren, hilly, residential and water surface. Alwar dataset is considered with seven band satellite images. Firefly Algorithm is based on the attraction of less bright fireflies towards more brightener one. For the evaluation of proposed concept accuracy assessment parameters are calculated using error matrix. With the help of Error matrix, parameters of Kappa Coefficient, Overall Accuracy and feature wise accuracy parameters of user’s accuracy & producer’s accuracy can be calculated. Overall results are compared with BBO, PSO, Hybrid FPAB/BBO, Hybrid ACO/SOFM and Hybrid ACO/BBO based on the kappa coefficient and overall accuracy parameters.

Keywords: image classification, firefly algorithm, satellite image classification, terrain classification

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Authors: Liu M. Hanmin

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Wong Kar-Wai’s multi-genre film 2046, world premiered in 2004, comes with a vibrant mediascape made up of multiple named languages, code-switching, intertitles, news footage from the real world, and extra-linguistic means of communication. In film- and multilingual studies it is still a challenge to incorporate non-languages into an analytical framework with conventional languages. This paper uses translanguaging theory to read silent practices in Wong Kar-Wai’ 2046. Two scenes that feature the silence experience the most are taken as case studies. In these two scenes, we can identify two tropes of intersemiotic relationships that are co-articulated by silence: patriarchy and unfinished romance, respectively. The conclusion argues that silence in Wong Kar-Wai’s 2046 exerts multimodal agency by ‘speaking’ directly to the audience and in mutual directions to characters. Thereby, it moves beyond the passive role of merely accentuating or assisting the aural register of a film.

Keywords: translanguaging, Wong Kar-Wai, multimodality, semiotics, inter semiotics, Hong Kong media, film culture

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Authors: Edgar Willy Rimarachin Valderrama, Eduardo Rojas Parra

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Thermal energy from solar radiation is widely present in power plants, food drying, chemical reactors, heating and cooling systems, water treatment processes, hydrogen production, and others. In the case of power plants, one of the technologies available to transform solar energy into thermal energy is by solar rotary kilns where a bed of granular matter is heated through concentrated radiation obtained from an arrangement of heliostats. Numerical modeling is a useful approach to study the behavior of granular beds in solar rotary kilns. This technique, once validated with small-scale experiments, can be used to simulate large-scale processes for industrial applications. This study gives a comprehensive classification of numerical models used to simulate the movement and heat transfer for beds of granular media within solar rotary furnaces. In general, there exist three categories of models: 1) continuum, 2) discrete, and 3) multiphysics modeling. The continuum modeling considers zero-dimensional, one-dimensional and fluid-like models. On the other hand, the discrete element models compute the movement of each particle of the bed individually. In this kind of modeling, the heat transfer acts during contacts, which can occur by solid-solid and solid-gas-solid conduction. Finally, the multiphysics approach considers discrete elements to simulate grains and a continuous modeling to simulate the fluid around particles. This classification allows to compare the advantages and disadvantages for each kind of model in terms of accuracy, computational cost and implementation.

Keywords: granular beds, numerical models, rotary kilns, solar thermal applications

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Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P ＜ 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Sopana Wongtawee

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Purpose: Adequate bowel cleansing is essential for a high quality, effective and safe colonoscopy. The aims of this study were to compare the efficacy of bowel preparation based on a low-residue diet before 8:00 followed by a clear-liquid diet, and a low-residue diet until 16:00 one day before colonoscopy using sodium phosphate solution (Xubil ®), the side effects of the two protocols and the patient satisfaction with them. Method: This was an endoscopist-blinded, prospective, randomized, controlled trial. A total of 224 patients (112 in each group) scheduled for outpatient colonoscopy met the criteria.They were randomized to either a low-residue diet consisting of white rice porridge with either fish, chicken or eggs before 8:00 followed by a clear-liquid diet (Group 1) or a low-residue diet consisting of the same food and drink, until 16:00 the day before colonoscopy(Group 2). All of them received 45 ml of sodium phosphate solution (Xubil ®) and three glasses of water (300 ml/glass) the evening before and the morning of the procedure. The cleansing efficacy of bowel preparation was rated according to the modified Rajawithi hospital bowel preparation score scale, patient satisfaction with bowel preparation was rated using Likert scale, and side effects of the 2 protocols was assessed using a patient questionnaire. Results: The cleansing efficacy between the two groups was significantly different (p=0.02). Satisfaction with bowel preparation and side effects were not different, except for the feeling of hunger in the first group (p=0.001). Conclusion: The low-residue diet consisting of white rice porridge with fish, chicken or eggs until 16:00 one day before colonoscopy achieved a better bowel-cleansing efficacy than the protocol consisting of clear liquid all day and rice porridge only before 8:00 one day before colonoscopy.

Keywords: bowel preparation, colonoscopy, sodium phosphate solution, nursing management

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Authors: Hsiu Hua Hu

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Digital transformation has widely affected various industries. It provides technological innovation, process redesign, new business model construction, and talent value creation. This transformation not only allows organizations to obtain and deploy specific technologies and methods suitable for organizational reengineering but also is an important way to solve management problems in human resource (HR) reengineering, business efficiency, and process redesign. In this study, we present the results of a qualitative study that offers insight into a series of key feature of reengineering related to the digital transformation and how to create talent value when the companies successfully perform digital transformation and human resource reengineering, which is led by business digitalization strategies including talent planning, talent acquisition, talent adjustment, and talent development. Drawing from the qualitative investigation findings, we built an inductive model of HR reengineering, which aims to provide research and practical references on future digital transformation and management inquiry.

Keywords: talent value creation, digital transformation, HR reengineering, qualitative study

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Authors: W. A. Nalaka Wijesooriya

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The increasing paddy production, stabilization of domestic rice consumption and the increasing dynamism of rice processing and domestic markets call for a rethinking of the general direction of the rice milling industry in Sri Lanka. The main purpose of the study was to explore levels of concentration in rice milling industry in Polonnaruwa and Hambanthota which are the major hubs of the country for rice milling. Concentration indices reveal that the rice milling industry in Polonnaruwa operates weak oligopsony and is highly competitive in Hambanthota. According to the actual quantity of paddy milling per day, 47 % is less than 8Mt/Day, while 34 % is 8-20 Mt/day, and the rest (19%) is greater than 20 Mt/day. In Hambanthota, nearly 50% of the mills belong to the range of 8-20 Mt/day. Lack of experience of the milling industry, poor knowledge on milling technology, lack of capital and finding an output market are the major entry barriers to the industry. Major problems faced by all the rice millers are the lack of a uniform electricity supply and low quality paddy. Many of the millers emphasized that the rice ceiling price is a constraint to produce quality rice. More than 80% of the millers in Polonnaruwa which is the major parboiling rice producing area have mechanical dryers. Nearly 22% millers have modern machineries like color sorters, water jet polishers. Major paddy purchasing method of large scale millers in Polonnaruwa is through brokers. In Hambanthota major channel is miller purchasing from paddy farmers. Millers in both districts have major rice selling markets in Colombo and suburbs. Huge variation can be observed in the amount of pledge (for paddy storage) loans. There is a strong relationship among the storage ability, credit affordability and the scale of operation of rice millers. The inter annual price fluctuation ranged 30%-35%. Analysis of market margins by using series of secondary data shows that farmers’ share on rice consumer price is stable or slightly increases in both districts. In Hambanthota a greater share goes to the farmer. Only four mills which have obtained the Good Manufacturing Practices (GMP) certification from Sri Lanka Standards Institution can be found. All those millers are small quantity rice exporters. Priority should be given for the Small and medium scale millers in distribution of storage paddy of PMB during the off season. The industry needs a proper rice grading system, and it is recommended to introduce a ceiling price based on graded rice according to the standards. Both husk and rice bran were underutilized. Encouraging investment for establishing rice oil manufacturing plant in Polonnaruwa area is highly recommended. The current taxation procedure needs to be restructured in order to ensure the sustainability of the industry.

Keywords: conduct, performance, structure (SCP), rice millers

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Authors: Eitan Elaad, Yeela Gal-Gonen

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Two studies examined gender differences in lying when the truth-telling bias prevailed and when inspiring lying and distrust. The first study used 156 participants from the community (78 pairs). First, participants completed the Narcissistic Personality Inventory, the Lie- and Truth Ability Assessment Scale (LTAAS), and the Rational-Experiential Inventory. Then, they participated in a deception game where they performed as senders and receivers of true and false communications. Their goal was to retain as many points as possible according to a payoff matrix that specified the reward they would gain for any possible outcome. Results indicated that males in the sender position lied more and were more successful tellers of lies and truths than females. On the other hand, males, as receivers, trusted less than females but were not better at detecting lies and truths. We explained the results by a. Male's high perceived lie-telling ability. We observed that confidence in telling lies guided participants to increase their use of lies. Male's lie-telling confidence corresponded to earlier accounts that showed a consistent association between high self-assessed lying ability, reports of frequent lying, and predictions of actual lying in experimental settings; b. Male's narcissistic features. Earlier accounts described positive relations between narcissism and reported lying or unethical behavior in everyday life situations. Predictions about the association between narcissism and frequent lying received support in the present study. Furthermore, males scored higher than females on the narcissism scale; and c. Male's experiential thinking style. We observed that males scored higher than females on the experiential thinking style scale. We further hypothesized that the experiential thinking style predicts frequent lying in the deception game. Results confirmed the hypothesis. The second study used one hundred volunteers (40 females) who underwent the same procedure. However, the payoff matrix encouraged lying and distrust. Results showed that male participants lied more than females. We found no gender differences in trust. Males and females did not differ in their success of telling and detecting lies and truths. Participants also completed the LTAAS questionnaire. Males assessed their lie-telling ability higher than females, but the ability assessment did not predict lying frequency. A final note. The present design is limited to low stakes. Participants knew that they were participating in a game, and they would not experience any consequences from their deception in the game. Therefore, we advise caution when applying the present results to lying under high stakes.

Keywords: gender, lying, detection of deception, information processing style, self-assessed lying ability

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Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

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As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

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Authors: S. M. Khairul Halim, Mojtaba Ghodsi, Morteza Mohammadzaheri

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Gait analysis is essential for diagnosing musculoskeletal and neurological conditions. However, current methods are often complex and expensive. This paper introduces a methodology for analysing gait parameters using a smart insole with a built-in accelerometer. The system measures stance time, swing time, step count, and cadence and wirelessly transmits data to a user-friendly IoT dashboard for centralized processing. This setup enables remote monitoring and advanced data analytics, making it a versatile tool for medical diagnostics and everyday usage. Integration with IoT enhances the portability and connectivity of the device, allowing for secure, encrypted data access over the Internet. This feature supports telemedicine and enables personalized treatment plans tailored to individual needs. Overall, the approach provides a cost-effective (almost 25 GBP), accurate, and user-friendly solution for gait analysis, facilitating remote tracking and customized therapy.

Keywords: gait analysis, IoT, smart insole, accelerometer sensor

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo

Abstract:

Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.

Keywords: cementitious materials, deformation, failure, material chemistry modeling

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Authors: Solomon Ngoako Mabapa, Selekane Ananias Motadi, Nteseng Mailula, Hlekani Vanessa Mbhatsani, Lindelani Fhumudzani Mushaphi

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Background: South Africa has indeed made good progress towards IDD elimination, as far as implementation of salt iodization and coverage of iodized salt are concerned, the education and promotion aspects of the iodized salt intervention are seriously lacking. Objective: To determine the iodine nutritional knowledge of food handlers at primary schools under the National School Nutrition Programme in Capricorn and Waterberg district. Design: This study included 300 food handlers recruited from 95 primary schools in Capricorn district and 105 primary schools in Waterberg district, Limpopo Province, South Africa. Primary schools and study participants where conveniently selected. The data was collected by means of a structured questionnaire. Information obtained was on the socio-demographic characteristics of the participants, general knowledge on salt fortification and knowledge test. Results: The iodine knowledge for the food handlers in two districts was poor with the entire population’s iodine nutritional knowledge of 12% on the Lickert scale. The mean score on the Lickert scale for Capricorn and Waterberg districts was 17% and 8.6% respectively indicated poor iodine nutritional knowledge. Conclusion: The two districts had poor iodine nutritional knowledge. Giving nutrition education to the public on the importance of iodine and the consequences of iodine deficiency disorder (IDD) and continue advocacy on mass media on the iodine fortification as an intervention strategy to combat the escalating problem of micronutrient malnutrition control.

Keywords: food handlers, nutritional knowledge, iodine, National School Nutrition Programme

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Authors: S. Sushma, S. Balasubramanian, K. C. Latha

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The mammographic image of breast cancer compressed and synthesized to get co-efficient values which will be converted (5x5) matrix to get ROI image where we get the highest value of effected region and with the same ideology the technique has been extended to differentiate between Calcification and normal cell image using mean value derived from 5x5 matrix values

Keywords: texture analysis, mammographic image, partitioned gray scale co-oocurance matrix, co-efficient

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Authors: Georgios Psakis, Imren Rahbay, David Spiteri, Jeanice Mallia, Martin Polidano, Vasilis P. Valdramidis

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Absence of surface water and progressive groundwater quality deterioration have exacerbated scarcity rapidly, making the Mediterranean island of Malta one of the most water-stressed countries in Europe. Water scarcity challenges have been addressed by reverse osmosis desalination of seawater, 60% of which is blended with groundwater to form the current potable tap-water supply. Chlorination has been the adopted method of water disinfection prior to distribution. However, with the Malteseconsumer chlorine sensory-threshold being as low as 0.34 ppm, presence of chorine residuals and chlorination by-products in the distributed tap-water impacts negatively on its organoleptic attributes, deterring the public from consuming it. As part of the PURILMA initiative, and with the aim of minimizing the impact of chlorine residual on the quality of the distributed water, UV-C, and hydrosonication, have been identified as cost- and energy-effective decontamination alternatives, paving the way for more sustainable water management. Bench-scale assessment of the decontamination efficiency of UV-C (254 nm), revealed 4.7-Log10 inactivation for both Escherichia coli and Enterococcus faecalis at 36 mJ/cm2. At >200 mJ/cm2fluence rates, there was a systematic 2-Log10 difference in the reductions exhibited by E. coli and E. faecalis to suggest that UV-C disinfection was more effective against E. coli. Hybrid treatment schemes involving hydrosonication(at 9.5 and 12.5 dm3/min flow rates with 1-5 MPa maximum pressure) and UV-C showed at least 1.1-fold greater bactericidal activity relative to the individualized UV-C treatments. The observed inactivation appeared to have stemmed from additive effects of the combined treatments, with hydrosonication-generated reactive oxygen species enhancing the biocidal activity of UV-C.

Keywords: disinfection, groundwater, hydrosonication, UV-C

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Authors: Chaiyaporn Yuksen, Tapanawat Chaiwan

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Introduction: Emergency medical service (EMS) care for trauma patients must be provided on-scene assessment and essential treatment and have appropriate transporting to the trauma center. The shock index (SI), reverse shock index Glasgow Coma Scale (rSIG), and National Early Warning Score (NEWS) triage tools are easy to use in a prehospital setting. There is no standardized on-scene triage protocol in prehospital care. The primary objective was to determine the accuracy of SI, rSIG, and NEWS to predict the severity of trauma patients in the emergency department (ED). Methods: This was a retrospective cross-sectional and diagnostic research conducted on trauma patients transported by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We included the injured patients receiving prehospital care and transport to the ED of Ramathibodi Hospital by the EMS team from January 2015 to September 2022. We compared the on-scene parameter (SI, rSIG, and NEWS) and ED (Emergency Severity Index) with the area under ROC. Results: 218 patients were traumatic patients transported by EMS to the ED. 161 was ESI level 1-2, and 57 was level 3-5. NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.743 (95%CI 0.70-0.79), 0.649 (95%CI 0.59-0.70), and 0.582 (95%CI 0.52-0.65), respectively (P-value <0.001). The cut point of NEWS to discriminate was 6 points. Conclusions: The NEWs was the most accurate triage tool in prehospital seeing in trauma patients.

Keywords: on-scene triage, trauma patient, ED triage, accuracy, NEWS

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Authors: Hassan Jassim Motlak

Abstract:

A novel design technique employing CMOS Current Feedback Operational Amplifier (CFOA) is presented. The feature of consumption whivh has a very low power in designing pseudo-OTA is used to decreasing the total power consumption of the proposed CFOA. This design approach applies pseudo-OTA as input stage cascaded with buffer stage. Moreover, the DC input offset voltage and harmonic distortion (HD) of the proposed CFOA are very low values compared with the conventional CMOS CFOA due to symmetrical input stage. P-Spice simulation results using 0.18µm MIETEC CMOS process parameters using supply voltage of ±1.2V and 50μA biasing current. The P-Spice simulation shows excellent improvement of the proposed CFOA over existing CMOS CFOA. Some of these performance parameters, for example, are DC gain of 62. dB, open-loop gain-bandwidth product of 108 MHz, slew rate (SR+) of +71.2V/µS, THD of -63dB and DC consumption power (PC) of 2mW.

Keywords: pseudo-OTA used CMOS CFOA, low power CFOA, high-performance CFOA, novel CFOA

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Authors: Chengming Li, Yong Yin, Peipei Guo, Xiaoli Liu

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Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Keywords: POI, road network, selection method, spatial information expression, distribution pattern

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Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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