Search results for: predictive tracking

Authors: Pei-Ti Hsu, I-Ju Chen, Jeu-Jung Chen, Cheng-Fen Chang, Shiu-Yan Yang

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Taiwan now is an aging society Research on the elderly should not be confined to caring for seniors, but should also be focused on ways to improve health and the quality of life. Senior citizens who participate in volunteer services could become less lonely, have new growth opportunities, and regain a sense of accomplishment. Thus, the question of how to get the elderly to participate in volunteer service is worth exploring. Apply the Transtheoretical Model to understand stages of change in regular volunteer service and voluntary service behaviour among the seniors. 1525 adults over the age of 65 from the Renai district of Keelung City were interviewed. The research tool was a self-constructed questionnaire and individual interviews were conducted to collect data. Then the data was processed and analyzed using the IBM SPSS Statistics 20 (Windows version) statistical software program. In the past six months, research subjects averaged 9.92 days of volunteer services. A majority of these elderly individuals had no intention to change their regular volunteer services. We discovered that during the maintenance stage, the self-efficacy for volunteer services was higher than during all other stages, but self-perceived barriers were less during the preparation stage and action stage. Self-perceived benefits were found to have an important predictive power for those with regular volunteer service behaviors in the previous stage, and self-efficacy was found to have an important predictive power for those with regular volunteer service behaviors in later stages. The research results support the conclusion that community nursing staff should group elders based on their regular volunteer services change stages and design appropriate behavioral change strategies.

Keywords: seniors, stages of change in regular volunteer services, volunteer service behavior, self-efficacy, self-perceived benefits

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Tom Wanyama

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We have developed a weight-based parts inventory monitoring system utilizing the Industrial Internet of Things (IIoT) to enhance operational efficiencies in manufacturing. The system addresses various challenges, including eliminating downtimes caused by stock-outs, preventing human errors in parts delivery and product assembly, and minimizing motion waste by reducing unnecessary worker movements. The system incorporates custom QR codes for simplified inventory tracking and retrieval processes. The generated data serves a dual purpose by enabling real-time optimization of parts flow within manufacturing facilities and facilitating retroactive optimization of stock levels for informed decision-making in inventory management. The pilot implementation at SEPT Learning Factory successfully eradicated data entry errors, optimized parts delivery, and minimized workstation downtimes, resulting in a remarkable increase of over 10% in overall equipment efficiency across all workstations. Leveraging the IIoT features, the system seamlessly integrates information into the process control system, contributing to the enhancement of product quality. This approach underscores the importance of effective tracking of parts inventory in manufacturing to achieve transparency, improved inventory control, and overall profitability. In the broader context, our inventory monitoring system aligns with the evolving focus on optimizing supply chains and maintaining well-managed warehouses to ensure maximum efficiency in the manufacturing industry.

Keywords: industrial Internet of Things, industrial systems integration, inventory monitoring, inventory control in manufacturing

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Authors: Herke Csongor

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The artificial intelligence (AI) has been used in the United States of America in the decisionmaking process of the criminal justice system for decades. In the field of law, including criminal law, AI can provide serious assistance in decision-making in many places. The paper reviews four main areas where AI still plays a role in the criminal justice system and where it is expected to play an increasingly important role. The first area is the predictive policing: a number of algorithms are used to prevent the commission of crimes (by predicting potential crime locations or perpetrators). This may include the so-called linking hot-spot analysis, crime linking and the predictive coding. The second area is the Big Data analysis: huge amounts of data sets are already opaque to human activity and therefore unprocessable. Law is one of the largest producers of digital documents (because not only decisions, but nowadays the entire document material is available digitally), and this volume can only and exclusively be handled with the help of computer programs, which the development of AI systems can have an increasing impact on. The third area is the criminal statistical data analysis. The collection of statistical data using traditional methods required enormous human resources. The AI is a huge step forward in that it can analyze the database itself, based on the requested aspects, a collection according to any aspect can be available in a few seconds, and the AI itself can analyze the database and indicate if it finds an important connection either from the point of view of crime prevention or crime detection. Finally, the use of AI during decision-making in both investigative and judicial fields is analyzed in detail. While some are skeptical about the future role of AI in decision-making, many believe that the question is not whether AI will participate in decision-making, but only when and to what extent it will transform the current decision-making system.

Keywords: artificial intelligence, international criminal cooperation, planning and organizing of the investigation, risk assessment

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Authors: Surabhi Agrawal Kohli, Sunita Gupta, Esha Khanuja, Parul Garg, P. Gupta

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Background: Adenomyosis is a common gynaecological condition that affects the menstruating women. Uterine enlargement, dysmenorrhoea, and menorrhagia are regarded as the cardinal clinical symptoms of adenomyosis. Classically it was thought, compared with ultrasonography, when adenomyosis is suspected, MRI enables more accurate diagnosis of the disease. Materials and Methods: 172 subjects were enrolled after an informed consent that had complaints of HMB, dyspareunia, dysmenorrhea, and chronic pelvic pain. Detailed history of the enrolled subjects was taken, followed by a clinical examination. These patients were then subjected to TVS where myometrial echo texture, presence of myometrial cysts, blurring of endomyometrial junction was noted. MRI was followed which noted the presence of junctional zone thickness and myometrial cysts. After hysterectomy, histopathological diagnosis was obtained. Results: 78 participants were analysed. The mean age was 44.2 years. 43.5% had parity of 4 or more. heavy menstrual bleeding (HMB) was present in 97.8% and dysmenorrhea in 93.48 % of HPE positive patient. Transvaginal sonography (TVS) and MRI had a sensitivity of 89.13% and 80.43%, specificity of 90.62% and 84.37%, positive likelihood ratio of 9.51 and 5.15, negative likelihood ratio of 0.12 and 0.23, positive predictive value of 93.18% and 88.1%, negative predictive value of 85.29% and 75% and a diagnostic accuracy of 89.74% and 82.5%. Comparison of sensitivity (p=0.289) and specificity (p=0.625) showed no statistically significant difference between TVS and MRI. Conclusion: Prevalence of 30.23%. HMB with dysmenorrhoea and chronic pelvic pain helps in diagnosis. TVS (Endomyometrial junction blurring) is both sensitive and specific in diagnosing adenomyosis without need for additional diagnostic tool. Both TVS and MRI are equally efficient, however because of certain additional advantages of TVS over MRI, it may be used as the first choice of imaging. MRI may be used additionally in difficult cases as well as in patients with existing co-pathologies.

Keywords: adenomyosis, heavy menstrual bleeding, MRI, TVS

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Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 125

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

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Authors: Mouktafi Amine, Tahiri Asmaa

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A substantial number of traditional medical research has been put forward to managing and treating mental disorders. At the present time, to our best knowledge, it is believed that a fundamental understanding of the underlying causes of the majority of psychological disorders needs to be explored further to inform early diagnosis, managing symptoms and treatment. The emerging field of evolutionary psychology is a promising prospect to address the origin of mental disorders, potentially leading to more effective treatments. Schizophrenia as a topical mental disorder has been linked to the evolutionary adaptation of the human brain represented in the brain connectivity and asymmetry directly linked to humans' higher brain cognition in contrast to other primates being our direct living representation of the structure and connectivity of our earliest common African ancestors. As proposed in the evolutionary psychology scientific literature, the pathophysiology of schizophrenia is expressed and directly linked to altered connectivity between the Hippocampal Formation (HF) and Dorsolateral Prefrontal Cortex (DLPFC). This research paper presents the results of the use of tractography analysis using multiple open access Diffusion Weighted Imaging (DWI) datasets of healthy subjects, schizophrenia-affected subjects and primates to illustrate the relevance of the aforementioned brain regions' connectivity and the underlying evolutionary changes in the human brain. Deterministic fiber tracking and streamline analysis were used to generate connectivity matrices from the DWI datasets overlaid to compute distances and highlight disconnectivity patterns in conjunction with other fiber tracking metrics: Fractional Anisotropy (FA), Mean Diffusivity (MD) and Radial Diffusivity (RD).

Keywords: tractography, diffusion weighted imaging, schizophrenia, evolutionary psychology

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Authors: Zofija Tupikovskaja-Omovie, David Tyler, Sam Dhanapala, Steve Hayes

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The UK is leading in online retail and mobile adoption. However, there is a dearth of information relating to mobile apparel retail, and developing an understanding about consumer browsing and purchase behavior in m-retail channel would provide apparel marketers, mobile website and app developers with the necessary understanding of consumers’ needs. Despite the rapid growth of mobile retail businesses, no published study has examined shopping behaviour on fashion mobile websites and apps. A mixed method approach helped to understand why fashion consumers prefer websites on mobile devices, when mobile apps are also available. The following research methods were employed: survey, eye-tracking experiments, observation, and interview with retrospective think aloud. The mobile gaze tracking device by SensoMotoric Instruments was used to understand frustrations in navigation and other issues facing consumers in mobile channel. This method helped to validate and compliment other traditional user-testing approaches in order to optimize user experience and enhance the development of mobile retail channel. The study involved eight participants - females aged 18 to 35 years old, who are existing mobile shoppers. The participants used the Topshop mobile app and website on a smart phone to complete a task according to a specified scenario leading to a purchase. The comparative study was based on: duration and time spent at different stages of the shopping journey, number of steps involved and product pages visited, search approaches used, layout and visual clues, as well as consumer perceptions and expectations. The results from the data analysis show significant differences in consumer behaviour when using a mobile app or website on a smart phone. Moreover, two types of problems were identified, namely technical issues and human errors. Having a mobile app does not guarantee success in satisfying mobile fashion consumers. The differences in the layout and visual clues seem to influence the overall shopping experience on a smart phone. The layout of search results on the website was different from the mobile app. Therefore, participants, in most cases, behaved differently on different platforms. The number of product pages visited on the mobile app was triple the number visited on the website due to a limited visibility of products in the search results. Although, the data on traffic trends held by retailers to date, including retail sector breakdowns for visits and views, data on device splits and duration, might seem a valuable source of information, it cannot explain why consumers visit many product pages, stay longer on the website or mobile app, or abandon the basket. A comprehensive list of pros and cons was developed by highlighting issues for website and mobile app, and recommendations provided. The findings suggest that fashion retailers need to be aware of actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added to which is the challenge of retaining existing and acquiring new customers. There seem to be differences in the way fashion consumers search and shop on mobile, which need to be explored in further studies.

Keywords: consumer behavior, eye-tracking technology, fashion retail, mobile app, m-retail, smart phones, topshop, user experience, website

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Semi autogenous mills are designed for grinding or primary crushed ore, and are the most widely used in concentrators globally. Any defect occurrence in semi autogenous mills can stop the production line. A Gearbox is a significant part of a rotating machine or a mill, so, the gearbox monitoring is a necessary process to prevent the unwanted defects. When a defect happens in a gearbox bearing, this defect can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. Vibration analysis is one of the most effective and common ways to detect the bearing defects in the mills. Vibration signal in a mill can be made by different parts of the mill including electromotor, pinion girth gear, different rolling bearings, and tire. When a vibration signal, made by the aforementioned parts, is added to the gearbox vibration spectrum, an accurate and on time defect detection in the gearbox will be difficult. In this paper, a new method is proposed to detect the gearbox bearing defects in the semi autogenous mill on time and accurately, using the vibration signal analysis method. In this method, if the vibration values are increased in the vibration curve, the probability of defect occurrence is investigated by comparing the equipment vibration values and the standard ones. Then, all vibration frequencies are extracted from the vibration signal and the equipment defect is detected using the vibration spectrum curve. This method is implemented on the semi autogenous mills in the Golgohar mining and industrial company in Iran. The results show that the proposed method can detect the bearing looseness on time and accurately. After defect detection, the bearing is opened before the equipment failure and the predictive maintenance actions are implemented on it.

Keywords: condition monitoring, gearbox defects, predictive maintenance, vibration analysis

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Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

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This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

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Authors: Sheeba Farhan

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This study is conducted to explore the predictive relationship of perceived stress and self-esteem with social support of students and to explore the factors, which contribute to develop or enhance the level of stress in students of private universities in Karachi-Pakistan. After literature review following hypotheses were formulated; 1)social support would predict perceived stress of students of business administration of private organizations of Higher education, 2) social support would predict the self-esteem of students of private organizations of Higher education, 3) there will be a relationship of perceived stress and self-esteem of students of private organizations of Higher education, 4) there will be a relationship of self esteem and social support of students of private organizations of Higher education. Sample of the study is comprise of 100 students of private organizations of Higher education in Karachi- Pakistan (i.e. males= 50 & females= 50). The age range of participants is 18-26 years. The measures, used in the study are: Demographic information form, a semi structured interview form, Rosenberg self esteem scale (Rosenberg, 1965) and perceived stress scale (Cohen, Kamarck, and Mermelstein, 1983) and multidimensional scale of perceived social support (Zimet, 1988) Descriptive statistics is used for getting a better statistical view of characteristics of sample. Regression analysis is used to explore the predictive relationship of study related stress and self esteem with academic achievement of students of private organizations of Higher education. Percentages and ratios were calculated to explore the level of perceived stress with respect to Socio-demographic characteristics in students of private organizations of Higher education. Finding shows that social support is significantly associated with the higher level of self-esteem among students of graduation but insignificantly associated with stress that has been experienced by them. These results are correlated with a wide variety of studies in which social support has proposed to be a predictor of well being for the students.

Keywords: private universities of Karachi-Pakistan, Self-esteem, social support, stress

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Authors: Aniqa Jabeen

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The aim of this study was to evaluate the effectiveness of Tc-99m MIBI (Technetium 99-methoxy-iso-butyl-isonitrile) scintigraphy to differentiate malignancies from benign lesions, which were detected on planar bone scans. Materials and Methods: 59 patients with bone lesions were enrolled in the study. The scintigraphic findings were compared with the clinical, radiological and the histological findings. Each patient initially underwent a three-phase bone scan with Tc-99m MDP (Methylene Diphosphonate) and if evidence of lesion found, the patient then underwent a dynamic and static MIBI scintigraphy after three to four days. The MDP and MIBI scans were evaluated visually and quantitatively. For quantitative analysis count ratios of lesions and contralateral normal side (L/C) were taken by region of interests drawn on scans. The Student T test was applied to assess the significant difference between benign and malignant lesions p-value < 0.05 was considered significant. Result: The MDP scans showed the increase tracer uptake, but there was no significant difference between benign and malignant uptake of the radiotracer. However significant difference (p-value 0.015), in uptake was seen in malignant (L/C = 3.51 ± 1.02) and benign lesion (L/C = 2.50±0.42) on MIBI scan. Three of thirty benign lesions did not show significant MIBI uptake. Seven malignant appeared as false negatives. Specificity of the scan was 86.66%, and its Negative Predictive Value (NPV) was 81.25% whereas the sensitivity of scan was 79.31%. In excluding the axial metastasis from the lesions, the sensitivity of MIBI scan increased to 91.66% and the NPV also increased to 92.85%. Conclusion: MIBI scintigraphy provides its usefulness by distinguishing malignant from benign lesions. MIBI also correctly identifies metastatic lesions. The negative predictive value of the scan points towards its ability to accurately diagnose the normal (benign) cases. However, biopsy remains the gold standard and a definitive diagnostic modality in musculoskeletal tumors. MIBI scan provides useful information in preoperative assessment and in distinguishing between malignant and benign lesions.

Keywords: benign, malignancies, MDP bone scan, MIBI scintigraphy

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Authors: Mohamed Abdalla Elamein Boshara, Peter Charles Woods, Nour Eldin Mohamed Elshaiekh

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Knowledge Management has become very important for Disaster Management response and planning. This paper proposes the implementation of a Knowledge Management System with a sustainable data collection mechanism for reliable and timely information management to support decision makers in making the right decisions in the timely manner.

Keywords: knowledge management, disaster management, incident tracking, web application

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Authors: K. M. Yoo, M. H. Kang

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Conventional commercial wind turbine design software is limited to large wind turbines due to not incorporating with low Reynold’s Number aerodynamic characteristics typically for small wind turbines. To extract maximum annual energy product from an intermediately designed small wind turbine associated with measured wind data, numerous simulation is highly recommended to have a best fitting planform design with proper airfoil configuration. Since depending upon wind distribution with average wind speed, an optimal wind turbine planform design changes accordingly. It is theoretically not difficult, though, it is very inconveniently time-consuming design procedure to finalize conceptual layout of a desired small wind turbine. Thus, to help simulations easier and faster, a GUI software is developed to conveniently iterate and change airfoil types, wind data, and geometric blade data as well. With magnetic generator torque curve, peak power tracking simulation is also available to better match with the magnetic generator. Small wind turbine often lacks starting torque due to blade optimization. Thus this simulation is also embedded along with yaw design. This software provides various blade cross section details at user’s design convenience such as skin thickness control with fiber direction option, spar shape, and their material properties. Since small wind turbine is under international safety regulations with fatigue damage during normal operations and safety load analyses with ultimate excessive loads, load analyses are provided with each category mandated in the safety regulations.

Keywords: GUI software, Low Reynold’s number aerodynamics, peak power tracking, safety regulations, wind turbine performance optimization

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Authors: Valeria Panzetta, Ida Musella, Sabato Fusco, Paolo Antonio Netti

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The study of the biophysics of living cells drew attention to the pivotal role of the cytoskeleton in many cell functions, such as mechanics, adhesion, proliferation, migration, differentiation and neoplastic transformation. In particular, during the complex process of malignant transformation and invasion cell cytoskeleton devolves from a rigid and organized structure to a more compliant state, which confers to the cancer cells a great ability to migrate and adapt to the extracellular environment. In order to better understand the malignant transformation process from a mechanical point of view, it is necessary to evaluate the direct crosstalk between the cells and their surrounding extracellular matrix (ECM) in a context which is close to in vivo conditions. In this study, human biopsy tissues of lung adenocarcinoma were analyzed in order to define their mechanical phenotype at cell and ECM level, by using particle tracking microrheology (PTM) technique. Polystyrene beads (500 nm) were introduced into the sample slice. The motion of beads was obtained by tracking their displacements across cell cytoskeleton and ECM structures and mean squared displacements (MSDs) were calculated from bead trajectories. It has been already demonstrated that the amplitude of MSD is inversely related to the mechanical properties of intracellular and extracellular microenvironment. For this reason, MSDs of particles introduced in cytoplasm and ECM of healthy and tumor tissues were compared. PTM analyses showed that cancerous transformation compromises mechanical integrity of cells and extracellular matrix. In particular, the MSD amplitudes in cells of adenocarcinoma were greater as compared to cells of normal tissues. The increased motion is probably associated to a less structured cytoskeleton and consequently to an increase of deformability of cells. Further, cancer transformation is also accompanied by extracellular matrix stiffening, as confirmed by the decrease of MSDs of matrix in tumor tissue, a process that promotes tumor proliferation and invasiveness, by activating typical oncogenic signaling pathways. In addition, a clear correlation between MSDs of cells and tumor grade was found. MSDs increase when tumor grade passes from 2 to 3, indicating that cells undergo to a trans-differentiation process during tumor progression. ECM stiffening is not dependent on tumor grade, but the tumor stage resulted to be strictly correlated with both cells and ECM mechanical properties. In fact, a greater stage is assigned to tumor spread to regional lymph nodes and characterized by an up-regulation of different ECM proteins, such as collagen I fibers. These results indicate that PTM can be used to get nanomechanical characterization at different scale levels in an interpretative and diagnostic context.

Keywords: cytoskeleton, extracellular matrix, mechanical properties, particle tracking microrheology, tumor

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Authors: Hosein I. Hosein, Ragab Azzam, Ahmed M. S. Menshawy, Sherin Rouby, Khaled Hendy, Ayman Mahrous, Hany Hussien

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Brucellosis is a highly contagious bacterial zoonotic disease of a worldwide spread and has different names; Infectious or enzootic abortion and Bang's disease in animals; and Mediterranean or Malta fever, Undulant Fever and Rock fever in humans. It is caused by the different species of genus Brucella which is a Gram-negative, aerobic, non-spore forming, facultative intracellular bacterium. Brucella affects a wide range of mammals including bovines, small ruminants, pigs, equines, rodents, marine mammals as well as human resulting in serious economic losses in animal populations. In human, Brucella causes a severe illness representing a great public health problem. The disease was reported in Egypt for the first time in 1939; since then the disease remained endemic at high levels among cattle, buffalo, sheep and goat and is still representing a public health hazard. The annual economic losses due to brucellosis were estimated to be about 60 million Egyptian pounds yearly, but actual estimates are still missing despite almost 30 years of implementation of the Egyptian control programme. Despite being the gold standard, bacterial isolation has been reported to show poor sensitivity for samples with low-level of Brucella and is impractical for regular screening of large populations. Thus, serological tests still remain the corner stone for routine diagnosis of brucellosis, especially in developing countries. In the present study, a total of 1533 cows (256 from Beni-Suef Governorate, 445 from Al-Fayoum Governorate and 832 from Damietta Governorate), were employed for estimation of relative sensitivity, relative specificity, positive predictive value and negative predictive value of buffered acidified plate antigen test (BPAT), rose bengal test (RBT) and complement fixation test (CFT). The overall seroprevalence of brucellosis revealed (19.63%). Relative sensitivity, relative specificity, positive predictive value and negative predictive value of BPAT,RBT and CFT were estimated as, (96.27 %, 96.76 %, 87.65 % and 99.10 %), (93.42 %, 96.27 %, 90.16 % and 98.35%) and (89.30 %, 98.60 %, 94.35 %and 97.24 %) respectively. BPAT showed the highest sensitivity among the three employed serological tests. RBT was less specific than BPAT. CFT showed the least sensitivity 89.30 % among the three employed serological tests but showed the highest specificity. Different tissues specimens of 22 seropositive cows (spleen, retropharyngeal udder, and supra-mammary lymph nodes) were subjected for bacteriological studies for isolation and identification of Brucella organisms. Brucella melitensis biovar 3 could be recovered from 12 (54.55%) cows. Bacteriological examinations failed to classify 10 cases (45.45%) and were culture negative. Bruce-ladder PCR was carried out for molecular identification of the 12 Brucella isolates at the species level. Three fragments of 587 bp, 1071 bp and 1682 bp sizes were amplified indicating Brucella melitensis. The results indicated the importance of using several procedures to overcome the problem of escaping of some infected animals from diagnosis.Bruce-ladder PCR is an important tool for diagnosis and epidemiologic studies, providing relevant information for identification of Brucella spp.

Keywords: brucellosis, relative sensitivity, relative specificity, Bruce-ladder, Egypt

Procedia PDF Downloads 349

Authors: Shu-Hui Jan, Hui-Ping Tserng, Shih-Ping Ho

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Construction project control attempts to obtain real-time as-built schedule information and to eliminate project delays by effectively enhancing dynamic schedule control and management. Suitable platforms for enhancing an as-built schedule visually during the construction phase are necessary and important for general contractors. As the application of building information modeling (BIM) becomes more common, schedule management integrated with the BIM approach becomes essential to enhance visual construction management implementation for the general contractor during the construction phase. To enhance visualization of the updated as-built schedule for the general contractor, this study presents a novel system called the Construction BIM-assisted Schedule Management (ConBIM-SM) system for general contractors in Taiwan. The primary purpose of this study is to develop a web ConBIM-SM system for the general contractor to enhance visual as-built schedule information sharing and efficiency in tracking construction as-built schedule. Finally, the ConBIM-SM system is applied to a case study of a commerce building project in Taiwan to verify its efficacy and demonstrate its effectiveness during the construction phase. The advantages of the ConBIM-SM system lie in improved project control and management efficiency for general contractors, and in providing BIM-assisted as-built schedule tracking and management, to access the most current as-built schedule information through a web browser. The case study results show that the ConBIM-SM system is an effective visual as-built schedule management platform integrated with the BIM approach for general contractors in a construction project.

Keywords: building information modeling (BIM), construction schedule management, as-built schedule management, BIM schedule updating mechanism

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

Procedia PDF Downloads 488

Authors: Sung Un Kim, Ivana Martinović, Snježana Stanarević Katavić

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As more and more youth use mobile devices, such as tablets and smartphones, for information seeking in their everyday lives, the purpose of this study is to understand the behaviors of youth seeking health information on mobile devices. The specific objective of this study is to examine 1) for what health issues youth use mobile devices, 2) for what reasons youth use mobile devices to obtain health information, 3) in what ways youth use mobile devices for health information, and 4) the features of health applications that youth find useful. The researchers devised a questionnaire for this study. Four hundred eight students from two high schools, located in Osijek, Croatia, participated by answering the questionnaire (281 girls and 127 boys). The collected data were analyzed using descriptive statistics and content analysis. The results show that among all participants, about 85 percent (n = 344) reported having used mobile devices for health information. The most frequent health topic for which they had been using mobile devices is physical activity (n = 273), followed by eating issues and nutrition (n = 224), mental health (n = 160), sexual health (n = 157), alcohol, drugs, and tobacco (n = 125), safety (n = 96) and particular diseases (n = 62). They use mobile devices to obtain health information due to the ease of use (n = 342), the ease of sharing health information (n = 281), portability (n = 215), timeliness (n = 162), and the ease of tracking/recording/monitoring health status (n = 147). Of those who have used mobile devices for health information, three-quarters (n = 261) use mobile devices to search health information, while 32.8% (n =113) use applications and 31.7% (n =109) browse information. Those who have used applications for health information (n = 113) consider the alert feature (n=107) as the most useful, followed by the tracking/recording/monitoring feature (n =92), the customized information feature (n = 86), the video feature (n = 58), and the sharing feature (n =39). It is notable that although health applications have been actively developed and studied, a majority of the participants search for or browse information on mobile devices, instead of using applications. The researchers will discuss reasons that some of them did not use mobile devices to obtain health information, students’ concerns about using health applications, and features that they wish to have in health applications.

Keywords: Croatia, health information, information seeking behaviors, mobile devices, youth

Procedia PDF Downloads 395

Authors: Racha El Kadiri, Mohamed Sultan, Henrique Momm, Zachary Blair, Rachel Schultz, Tamer Al-Bayoumi

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The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region.

Keywords: rainfall, neural networks, climatic indices, Mediterranean

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Authors: Prasad Kalagura, B. Veeresh kumar

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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 573

Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

Procedia PDF Downloads 77

Authors: Jennifer M. Glennon, Hana D'Souza, Luke Mason, Annette Karmiloff-Smith, Michael S. C. Thomas

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Genetic syndrome groups that feature high rates of autism comorbidity, like Down syndrome (DS) and fragile X syndrome (FXS), have been presented as useful models for understanding risk and protective factors involved in the emergence of autistic traits. Yet despite reaching clinical thresholds, these ‘syndromic’ forms of autism appear to differ in important ways from the idiopathic or ‘non-syndromic’ autism phenotype. To uncover the true nature of these comorbidities, it is necessary to extend definitions of autism to include the cognitive characteristics of the disorder and to then apply this broadened conceptualisation to the study of syndromic autism profiles. The current study employs a variety of well-established eye-tracking paradigms to assess visual attentional performance in children with DS and FXS who reach thresholds for autism on the Social Communication Questionnaire. It investigates whether autism profiles in these children are accompanied by visual orienting difficulties (‘sticky attention’), decreased social attention, and enhanced visual search performance, all of which are characteristic of the idiopathic autism phenotype. Data is collected from children with DS and FXS aged between 6 and 10 years, in addition to two control groups matched on age and intellectual ability (i.e., children with idiopathic autism and neurotypical controls). Cross-sectional developmental trajectory analyses are conducted to enable visuo-attentional profile comparisons. Significant differences in the visuo-attentional processes underpinning autism presentations in children with FXS and DS are hypothesised, supporting notions of syndrome specificity. The study provides insight into the complex heterogeneity associated with syndromic autism presentations and autism per se, with clinical implications for the utility of autism intervention programmes in DS and FXS populations.

Keywords: autism, down syndrome, fragile X syndrome, eye tracking

Procedia PDF Downloads 232

Authors: Rewadee Watakakosol, Arunya Tuicomepee, Panrapee Suttiwan, Sakkaphat T. Ngamake

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Health problems caused by alcohol consumption not only have short-term effects at the time of drinking but also leave long-lasting health conditions. Teenagers who start drinking in their middle-high or high school years or before entering college have higher likelihood to increase their alcohol use and abuse, and they were found to be less healthy compared with their non-drinking peers when entering adulthood. This study aimed to examine factors that predict intention and readiness to reduce and quit alcohol consumption among Thai teenagers. Participants were 826 high-school and vocational school students, most of whom were females (64.4%) with the average age of 16.4 (SD = 0.9) and the average age of first drinking at 13.7 (SD = 2.2). Instruments included the scales that developed based on the Theory of Planned Behaviour theoretical framework. They were the Attitude toward Alcohol Reduction and Cessation Scale, Normative Group and Influence Scale, Perceived Behavioral Control toward Alcohol Reduction and Cessation Scale, Behavioral Intent toward Alcohol Reduction and Cessation Scale, and Readiness to Reduce and Quit Alcohol Consumption Scale. Findings revealed that readiness to reduce / quit alcohol was the most powerful predictive factor (β=. 53, p < .01), followed by attitude of easiness in alcohol reduction and cessation (β=.46, p < .01), perceived behavioral control toward alcohol reduction and cessation (β =.41, p < .01), normative group and influence (β=.15, p < .01), and attitude of being accepted from alcohol reduction and cessation (β = -.12, p < .01), respectively. Attitude of improved health after alcohol reduction and cessation did not show statistically significantly predictive power. All factors significantly predict teenagers’ alcohol reduction and cessation behavior and accounted for 59 percent of total variance of alcohol consumption reduction and cessation.

Keywords: alcohol consumption reduction and cessation, intention, readiness to change, Thai teenagers

Procedia PDF Downloads 325

Authors: Shalu Jain, Anju Bansal, Anup Kumar, Sunita Saxena

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Objectives: The novel TMPRSS2:ERG gene fusion is a common somatic event in prostate cancer that in some studies is linked with a more aggressive disease phenotype. Thus, this study aims to determine whether clinical variables are associated with the presence of TMPRSS2:ERG-fusion gene transcript in Indian patients of prostate cancer. Methods: We evaluated the clinical variables with presence and absence of TMPRSS2:ERG gene fusion in prostate cancer and BPH association of clinical patients. Patients referred for prostate biopsy because of abnormal DRE or/and elevated sPSA were enrolled for this prospective clinical study. TMPRSS2:ERG mRNA copies in samples were quantified using a Taqman chemistry by real time PCR assay in prostate biopsy samples (N=42). The T2:ERG assay detects the gene fusion mRNA isoform TMPRSS2 exon1 to ERG exon4. Results: Histopathology report has confirmed 25 cases as prostate cancer adenocarcinoma (PCa) and 17 patients as benign prostate hyperplasia (BPH). Out of 25 PCa cases, 16 (64%) were T2: ERG fusion positive. All 17 BPH controls were fusion negative. The T2:ERG fusion transcript was exclusively specific for prostate cancer as no case of BPH was detected having T2:ERG fusion, showing 100% specificity. The positive predictive value of fusion marker for prostate cancer is thus 100% and the negative predictive value is 65.3%. The T2:ERG fusion marker is significantly associated with clinical variables like no. of positive cores in prostate biopsy, Gleason score, serum PSA, perineural invasion, perivascular invasion and periprostatic fat involvement. Conclusions: Prostate cancer is a heterogeneous disease that may be defined by molecular subtypes such as the TMPRSS2:ERG fusion. In the present prospective study, the T2:ERG quantitative assay demonstrated high specificity for predicting biopsy outcome; sensitivity was similar to the prevalence of T2:ERG gene fusions in prostate tumors. These data suggest that further improvement in diagnostic accuracy could be achieved using a nomogram that combines T2:ERG with other markers and risk factors for prostate cancer.

Keywords: prostate cancer, genetic rearrangement, TMPRSS2:ERG fusion, clinical variables

Procedia PDF Downloads 440

Authors: Sima Ajami, Batool Akbari

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Background: Radio frequency identification (RFID) system has been successfully applied to the areas of manufacturing, supply chain, agriculture, transportation, healthcare, and services. The RFID is already used to track and trace the victims in a disaster situation. Data can be collected in real time and be immediately available to emergency personnel and saves time by the RFID. Objectives: The aim of this study was, first, to identify stakeholders and customers for rescuing earthquake victims, second, to list key internal and external factors to use RFID to track earthquake victims, finally, to assess SWOT for rescuers' viewpoint. Materials and Methods: This study was an applied and analytical study. The study population included scholars, experts, planners, policy makers and rescuers in the "red crescent society of Isfahan province", "disaster management Isfahan province", "maintenance and operation department of Isfahan", "fire and safety services organization of Isfahan municipality", and "medical emergencies and disaster management center of Isfahan". After that, researchers held a workshop to teach participants about RFID and its usages in tracking earthquake victims. In the meanwhile of the workshop, participants identified, listed, and weighed key internal factors (strengths and weaknesses; SW) and external factors (opportunities and threats; OT) to use RFID in tracking earthquake victims. Therefore, participants put weigh strengths, weaknesses, opportunities, and threats (SWOT) and their weighted scales were calculated. Then, participants' opinions about this issue were assessed. Finally, according to the SWOT matrix, strategies to solve the weaknesses, problems, challenges, and threats through opportunities and strengths were proposed by participants. Results: The SWOT analysis showed that the total weighted score for internal and external factors were 3.91 (Internal Factor Evaluation) and 3.31 (External Factor Evaluation) respectively. Therefore, it was in a quadrant SO strategies cell in the SWOT analysis matrix and aggressive strategies were resulted. Organizations, scholars, experts, planners, policy makers and rescue workers should plan to use RFID technology in order to save more victims and manage their life. Conclusions: Researchers suppose to apply SO strategies and use a firm’s internal strength to take advantage of external opportunities. It is suggested, policy maker should plan to use the most developed technologies to save earthquake victims and deliver the easiest service to them. To do this, education, informing, and encouraging rescuers to use these technologies is essential. Originality/ Value: This study was a research paper that showed how RFID can be useful to track victims in earthquake.

Keywords: frequency identification system, strength, weakness, earthquake, victim

Procedia PDF Downloads 319

Authors: Lisete Barlach, Guilherme Ary Plonski

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Innovative ideas are not always synonymous with business opportunities. Any idea can be creative and not recognized as a potential project in which money and time will be invested, among other resources. Even in firms that promote and enhance innovation, there are two 'check-points', the first corresponding to the acknowledgment of the idea as creative and the second, its consideration as a business opportunity. Both the recognition of new business opportunities or new ideas involve cognitive and psychological frameworks which provide individuals with a basis for noticing connections between seemingly independent events or trends as if they were 'connecting the dots'. It also involves prototypes-representing the most typical member of a certain category–functioning as 'templates' for this recognition. There is a general assumption that these kinds of evaluation processes develop through experience, explaining why expertise plays a central role in this process: the more experienced a professional, the easier for him (her) to identify new opportunities in business. But, paradoxically, an increase in expertise can lead to the inflexibility of thought due to automation of procedures. And, besides this, other cognitive biases can also be present, because new ideas or business opportunities generally depend on heuristics, rather than on established algorithms. The paper presents a literature review about the Einstellung effect by tracking famous cases of rejected ideas, extracted from historical records. It also presents the results of empirical research, with data upon rejected ideas gathered from two different environments: projects rejected during first semester of 2017 at a large incubator center in Sao Paulo and ideas proposed by employees that were rejected by a well-known business company, at its Brazilian headquarter. There is an implicit assumption that Einstellung effect tends to be more and more present in contemporaneity, due to time pressure upon decision-making and idea generation process. The analysis discusses desirability, viability, and feasibility as elements that affect decision-making.

Keywords: cognitive biases, Einstellung effect, recognition of business opportunities, rejected ideas

Procedia PDF Downloads 198