Search results for: big data in higher education
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 35169

Search results for: big data in higher education

22599 Artificial Intelligence Based Abnormality Detection System and Real Valuᵀᴹ Product Design

Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

Abstract:

This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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22598 Frequency Recognition Models for Steady State Visual Evoked Potential Based Brain Computer Interfaces (BCIs)

Authors: Zeki Oralhan, Mahmut Tokmakçı

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SSVEP based brain computer interface (BCI) systems have been preferred, because of high information transfer rate (ITR) and practical use. ITR is the parameter of BCI overall performance. For high ITR value, one of specification BCI system is that has high accuracy. In this study, we investigated to recognize SSVEP with shorter time and lower error rate. In the experiment, there were 8 flickers on light crystal display (LCD). Participants gazed to flicker which had 12 Hz frequency and 50% duty cycle ratio on the LCD during 10 seconds. During the experiment, EEG signals were acquired via EEG device. The EEG data was filtered in preprocessing session. After that Canonical Correlation Analysis (CCA), Multiset CCA (MsetCCA), phase constrained CCA (PCCA), and Multiway CCA (MwayCCA) methods were applied on data. The highest average accuracy value was reached when MsetCCA was applied.

Keywords: brain computer interface, canonical correlation analysis, human computer interaction, SSVEP

Procedia PDF Downloads 251
22597 Enhancement Effect of Superparamagnetic Iron Oxide Nanoparticle-Based MRI Contrast Agent at Different Concentrations and Magnetic Field Strengths

Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

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Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, resovist, field strength, relaxivity, signal intensity

Procedia PDF Downloads 341
22596 Literature Review on Text Comparison Techniques: Analysis of Text Extraction, Main Comparison and Visual Representation Tools

Authors: Andriana Mkrtchyan, Vahe Khlghatyan

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The choice of a profession is one of the most important decisions people make throughout their life. With the development of modern science, technologies, and all the spheres existing in the modern world, more and more professions are being arisen that complicate even more the process of choosing. Hence, there is a need for a guiding platform to help people to choose a profession and the right career path based on their interests, skills, and personality. This review aims at analyzing existing methods of comparing PDF format documents and suggests that a 3-stage approach is implemented for the comparison, that is – 1. text extraction from PDF format documents, 2. comparison of the extracted text via NLP algorithms, 3. comparison representation using special shape and color psychology methodology.

Keywords: color psychology, data acquisition/extraction, data augmentation, disambiguation, natural language processing, outlier detection, semantic similarity, text-mining, user evaluation, visual search

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22595 Support Vector Regression for Retrieval of Soil Moisture Using Bistatic Scatterometer Data at X-Band

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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22594 Location Quotients Model in Turkey’s Provinces and Nuts II Regions

Authors: Semih Sözer

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One of the most common issues in economic systems is understanding characteristics of economic activities in cities and regions. Although there are critics to economic base models in conceptual and empirical aspects, these models are useful tools to examining the economic structure of a nation, regions or cities. This paper uses one of the methodologies of economic base models namely the location quotients model. Data for this model includes employment numbers of provinces and NUTS II regions in Turkey. Time series of data covers the years of 1990, 2000, 2003, and 2009. Aim of this study is finding which sectors are export-base and which sectors are import-base in provinces and regions. Model results show that big provinces or powerful regions (population, size etc.) mostly have basic sectors in their economic system. However, interesting facts came from different sectors in different provinces and regions in the model results.

Keywords: economic base, location quotients model, regional economics, regional development

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22593 The Compliance of Safe-Work Behaviors among Undergraduate Nursing Students with Different Clinical Experiences

Authors: K. C. Wong, K. L. Siu, S. N. Ng, K. N. Yip, Y. Y. Yuen, K. W. Lee, K. W. Wong, C. C. Li, H. P. Lam

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Background: Occupational injuries among nursing profession were found related to repeated bedside nursing care, such as transfer, lifting and manual handling patients from previous studies. Likewise, undergraduate nursing students are also exposed to potential safety hazard due to their similar work nature of registered nurses. Especially, those students who worked as Temporary undergraduate nursing students (TUNS) which is a part-time clinical job in hospitals in Hong Kong who mainly assisted in providing bedside cares appeared to at high risk of work-related injuries. Several studies suggested the level of compliance with safe work behaviors was highly associated with work-related injuries. Yet, it had been limitedly studied among nursing students. This study was conducted to assess and compare the compliance with safe work behaviors and the levels of awareness of different workplace safety issues between undergraduate nursing students with or without TUNS experiences. Methods: This is a quantitative descriptive study using convenience sampling. 362 undergraduate nursing students in Hong Kong were recruited. The Safe Work Behavior relating to Patient Handling (SWB-PH) was used to assess their compliance of safe-work behaviors and the level of awareness of different workplace safety issues. Results: The results showed that most of the participants (n=250, 69.1%) who were working as TUNS. However, students who worked as TUNS had significantly lower safe-work behaviors compliance (mean SWB-PH score = 3.64±0.54) than those did not worked as TUNS (SWB-PH score=4.21±0.54) (p<0.001). Particularly, these students had higher awareness to seek help and use assistive devices but lower awareness of workplace safety issues and awareness of proper work posture than students without TUNS experiences. The students with TUNS experiences had higher engagement in help-seeking behaviors might be possibly explained by their richer clinical experiences which served as a facilitator to seek help from clinical staff whenever necessary. Besides, these experienced students were more likely to bear risks for occupational injuries and worked alone when no available aid which might be related to the busy working environment, heightened work pressures and high expectations of TUNS. Eventually, students who worked as TUNS might target on completing the assigned tasks and gradually neglecting the occupational safety. Conclusion: The findings contributed to an understanding of the level of compliance with safe work behaviors among nursing students with different clinical experiences. The results might guide the modification of current safety protocols and the introduction of multiple clinical training courses to improve nursing student’s engagement in safe work behaviors.

Keywords: Occupational safety, Safety compliance, Safe-work behavior, Nursing students

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22592 Case-Based Options Counseling Panel To Supplement An Indiana Medical School’s Pre-Clinical Family Planning and Abortion Education Curriculum

Authors: Alexandra McKinzie, Lucy Brown, Sarah Komanapalli, Sarah Swiezy, Caitlin Bernard

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Background: While 25% of US women will seek an abortion before age 45, targeted laws have led to a decline in abortion clinics, subsequently leaving 96% of Indiana counties and the 70% of Hoosier women residing in these counties without access to services they desperately need.1,2 Despite the need for a physician workforce that is educated and able to provide full-spectrum reproductive health care, few medical institutions have a standardized family planning and abortion pre-clinical curriculum. Methods: A Qualtrics survey was disseminated to students from Indiana University School of Medicine (IUSM) to evaluate (1) student interest in curriculum reform, (2) self-assessed preparedness to counsel on contraceptive and pregnancy options, and (3) preferred modality of instruction for family planning and abortion topics. Based on the pre-panel survey feedback, a case-based pregnancy options counseling panel will be implemented in the students’ pre-clinical, didactic course Endocrine, Reproductive, Musculoskeletal, Dermatologic Systems (ERMD) in February 2022. A Qualtrics post-panel survey will be disseminated to evaluate students’ perceived efficacy and quality of the panel, as well as their self-assessed preparedness to counsel on pregnancy options. Results: Participants in the pre-panel survey (n=303) were primarily female (61.72%) and White (74.43%). Across all class levels, many (60.80%) students expected to learn about family planning and abortion in their pre-clinical education. While most (84-88%) participants felt prepared to counsel about common, non-controversial pharmacotherapies (e.g. beta-blockers and diuretics), only 20% of students felt prepared to counsel on abortion options. Overall, 85.67% of students believed that IUSM should enhance its reproductive health coverage in pre-clinical, didactic courses. Traditional lectures, panels, and direct clinical exposure were the most popular instructional modalities. Expected Results: The authors predict that following the panel, students will indicate improved confidence in providing pregnancy options counseling. Additionally, students will provide constructive feedback on the structure and content of the panel for incorporation into future years’ curriculum. Conclusions: IUSM students overwhelmingly expressed interest in expanding their pre-clinical curriculum’s coverage of family planning and abortion topics. To specifically improve students’ self-assessed preparedness to provide pregnancy options counseling and address students’ self-cited learning gaps, a case-based provider panel session will be implemented in response to students’ preferred modality feedback.

Keywords: options counseling, family planning, abortion, curriculum reform, case-based panel

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22591 Security Issues and Primary School Participation in Kenya

Authors: Rose Mwanza

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This paper investigates security factors influencing primary school pupils’ school participation in Kenya. Schools, communities and the Government all have roles to play in enhancing primary school pupil’s school participation. The effective security system of a country provides the necessary avenues to facilitate improved health services protection of children and allows free movement of the country’s citizens which leads to a conducive atmosphere for school participation. Kenya is a signatory to international commitments and conventions related to security such as the National Policy on Peace Building and Conflict Management, United Nations Development Assistance Framework and Key Security Unity, which enable primary school pupils to participate in education. The paper also looks at the strategies the Government of Kenya has put in place to ensure effective pupil school participation.

Keywords: ethnicity, social media, participation in school, poverty, terrorism

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22590 A New Method to Reduce 5G Application Layer Payload Size

Authors: Gui Yang Wu, Bo Wang, Xin Wang

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Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

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22589 Iron Yoke Dipole with High Quality Field for Collector Ring FAIR

Authors: Tatyana Rybitskaya, Alexandr Starostenko, Kseniya Ryabchenko

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Collector ring (CR) of FAIR project is a large acceptance storage ring and field quality plays a major role in the magnet design. The CR will use normal conducting dipole magnets. There will be 24 H-type sector magnets with a maximum field value of 1.6 T. The integrated over the length of the magnet field quality as a function of radius is ∆B.l/B.l = ±1x10⁻⁴. Below 1.6 T the value ∆B.l/B.l can be higher with a linear approximation up to ±2.5x10⁻⁴ at the field level of 0.8 T. An iron-dominated magnet with required field quality is produced with standard technology as the quality is dominated by the yoke geometry.

Keywords: conventional magnet, iron yoke dipole, harmonic terms, particle accelerators

Procedia PDF Downloads 133
22588 Site Suitability of Offshore Wind Energy: A Combination of Geographic Referenced Information and Analytic Hierarchy Process

Authors: Ayat-Allah Bouramdane

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Power generation from offshore wind energy does not emit carbon dioxide or other air pollutants and therefore play a role in reducing greenhouse gas emissions from the energy sector. In addition, these systems are considered more efficient than onshore wind farms, as they generate electricity from the wind blowing across the sea, thanks to the higher wind speed and greater consistency in direction due to the lack of physical interference that the land or human-made objects can present. This means offshore installations require fewer turbines to produce the same amount of energy as onshore wind farms. However, offshore wind farms require more complex infrastructure to support them and, as a result, are more expensive to construct. In addition, higher wind speeds, strong seas, and accessibility issues makes offshore wind farms more challenging to maintain. This study uses a combination of Geographic Referenced Information (GRI) and Analytic Hierarchy Process (AHP) to identify the most suitable sites for offshore wind farm development in Morocco, with a particular focus on the Dakhla city. A range of environmental, socio-economic, and technical criteria are taken into account to solve this complex Multi-Criteria Decision-Making (MCDM) problem. Based on experts' knowledge, a pairwise comparison matrix at each level of the hierarchy is performed, and fourteen sub-criteria belong to the main criteria have been weighted to generate the site suitability of offshore wind plants and obtain an in-depth knowledge on unsuitable areas, and areas with low-, moderate-, high- and very high suitability. We find that wind speed is the most decisive criteria in offshore wind farm development, followed by bathymetry, while proximity to facilities, the sediment thickness, and the remaining parameters show much lower weightings rendering technical parameters most decisive in offshore wind farm development projects. We also discuss the potential of other marine renewable energy potential, in Morocco, such as wave and tidal energy. The proposed approach and analysis can help decision-makers and can be applied to other countries in order to support the site selection process of offshore wind farms.

Keywords: analytic hierarchy process, dakhla, geographic referenced information, morocco, multi-criteria decision-making, offshore wind, site suitability

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22587 Identification of Damage Mechanisms in Interlock Reinforced Composites Using a Pattern Recognition Approach of Acoustic Emission Data

Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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22586 One Species into Five: Nucleo-Mito Barcoding Reveals Cryptic Species in 'Frankliniella Schultzei Complex': Vector for Tospoviruses

Authors: Vikas Kumar, Kailash Chandra, Kaomud Tyagi

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The insect order Thysanoptera includes small insects commonly called thrips. As insect vectors, only thrips are capable of Tospoviruses transmission (genus Tospovirus, family Bunyaviridae) affecting various crops. Currently, fifteen species of subfamily Thripinae (Thripidae) have been reported as vectors for tospoviruses. Frankliniella schultzei, which is reported as act as a vector for at least five tospovirses, have been suspected to be a species complex with more than one species. It is one of the historical unresolved issues where, two species namely, F. schultzei Trybom and F. sulphurea Schmutz were erected from South Africa and Srilanaka respectively. These two species were considered to be valid until 1968 when sulphurea was treated as colour morph (pale form) and synonymised under schultzei (dark form) However, these two have been considered as valid species by some of the thrips workers. Parallel studies have indicated that brown form of schultzei is a vector for tospoviruses while yellow form is a non-vector. However, recent studies have shown that yellow populations have also been documented as vectors. In view of all these facts, it is highly important to have a clear understanding whether these colour forms represent true species or merely different populations with different vector carrying capacities and whether there is some hidden diversity in 'Frankliniella schultzei species complex'. In this study, we aim to study the 'Frankliniella schultzei species complex' with molecular spectacles with DNA data from India and Australia and Africa. A total of fifty-five specimens was collected from diverse locations in India and Australia. We generated molecular data using partial fragments of mitochondrial cytochrome c oxidase I gene (mtCOI) and 28S rRNA gene. For COI dataset, there were seventy-four sequences, out of which data on fifty-five was generated in the current study and others were retrieved from NCBI. All the four different tree construction methods: neighbor-joining, maximum parsimony, maximum likelihood and Bayesian analysis, yielded the same tree topology and produced five cryptic species with high genetic divergence. For, rDNA, there were forty-five sequences, out of which data on thirty-nine was generated in the current study and others were retrieved from NCBI. The four tree building methods yielded four cryptic species with high bootstrap support value/posterior probability. Here we could not retrieve one cryptic species from South Africa as we could not generate data on rDNA from South Africa and sequence for rDNA from African region were not available in the database. The results of multiple species delimitation methods (barcode index numbers, automatic barcode gap discovery, general mixed Yule-coalescent, and Poisson-tree-processes) also supported the phylogenetic data and produced 5 and 4 Molecular Operational Taxonomic Units (MOTUs) for mtCOI and 28S dataset respectively. These results of our study indicate the likelihood that F. sulphurea may be a valid species, however, more morphological and molecular data is required on specimens from type localities of these two species and comparison with type specimens.

Keywords: DNA barcoding, species complex, thrips, species delimitation

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22585 Open Space Use in University Campuses with User Requirements Analysis: The Case of Eskişehir Osmangazi University Meşelik Campus

Authors: Aysen Celen Ozturk, Hatice Dulger

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University may be defined as a teaching institution consisting of faculties, institutes, colleges, and units that have undergraduate and graduate education, scientific research and publications. It has scientific autonomy and public legal personality. Today, universities are not only the institutions in which students and lecturers experience education, training and scientific work. They also offer social, cultural and artistic activities that strengthen the link with the city. This also incorporates all city users into the campus borders. Thus, universities contribute to social and individual development of the country by providing science, art, socio-cultural development, communication and socialization with people of different cultural and social backgrounds. Moreover, universities provide an active social life, where the young population is the majority. This enables the sense of belonging to the users to develop, to increase the interaction between academicians and students, and to increase the learning / producing community by continuing academic sharing environments outside the classrooms. For this reason, besides academic spaces in university campuses, the users also need closed and open spaces where they can socialize, spend time together and relax. Public open spaces are the most important social spaces that individuals meet, express themselves and share. Individuals belonging to different socio-cultural structures and ethnic groups maintain their social experiences with the physical environment they are in, the outdoors, and their actions and sharing in these spaces. While university campuses are being designed for their individual and social development roles, user needs must be determined correctly and design should be realized in this direction. While considering that requirements may change over time, user satisfaction should be questioned at certain periods and new arrangements should be made in existing applications in the direction of current demands. This study aims to determine the user requirements through the case of Eskişehir Osmangazi University, Meşelik Campus / Turkey. Post Occupancy Evaluation (POE) questionnaire, cognitive mapping and deep interview methods are used in the research process. All these methods show that the students, academicians and other officials in the Meşelik Campus of Eskişehir Osmangazi University find way finding elements insufficient and are in need of efficient landscape design and social spaces. This study is important in terms of determining the needs of the users as a design input. This will help improving the quality of common space in Eskişehir Osmangazi University and in other similar universities.

Keywords: university campuses, public open space, user requirement, post occupancy evaluation

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22584 Unconventional Explorers: Gen Z Travelers Redefinding the Travel Experience

Authors: M. Panidou, F. Kilipiris, E. Christou, K. Alexandris

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This study intends to investigate the travel preferences of Generation Z (born between 1996 and 2012), focusing on their inclination towards unique and unconventional travel experiences, prioritization of authentic cultural immersion and local experiences over traditional tourist attractions, and their value for flexibility and spontaneity in travel plans. By examining these aspects, the research aims to provide insights into the preferences and behaviors of Generation Z travelers, contributing to a better understanding of their travel choices and informing the tourism industry in catering to their needs and desires. Secondary data was gathered from academic literature and industry reports to offer a thorough study of the topic. A quantitative method was used, and primary data was collected through an online questionnaire. One hundred Greek people between the ages of eighteen and twenty-seven were the study's sample. SPSS software was used to assist in the analysis of the data. The findings of the research showed that Gen Z is attracted to unusual and distinctive travel experiences, prioritizing genuine cultural immersion over typical tourist attractions, and they highly value flexibility in their travel decision-making. This research contributes to a deeper understanding of how Gen Z travelers are reshaping the travel industry. Travel companies, marketers, and destination management organizations will find the findings useful in adjusting their products to suit this influential demographic's changing demands and preferences. Considering the limitations of the sample size, future studies could expand the sample size to include individuals from different cultural backgrounds for a more comprehensive understanding.

Keywords: cultural immersion, flexibility, generation Z, travel preferences, unique experiences

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22583 Corporate Social Responsibility Practices of Local Large Firms in the Developing Economies: The Case of the East Africa Region

Authors: Lilian Kishimbo

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This study aims to examine Corporate Social Responsibility (CSR) practices of local large firms of East Africa region. In this study CSR is defined as all actions that go beyond obeying minimum legal requirements as espoused by other authors. Despite the increase of CSR literature empirical evidence clearly demonstrate an imbalance of CSR studies in the developing countries . Moreover, it is evident that most of the research on CSR in developing economies emerges from large fast-growing economies or BRICS members (i.e. Brazil, India, China and South Africa), and Indonesia and Malaysia and a further call for more research in Africa is particularly advocated. Taking Africa as an example, there are scanty researches on CSR practices, and the few available studies are mainly from Nigeria and South Africa leaving other parts of Africa for example East Africa underrepresented. Furthermore, in the face of globalization, experience shows that literature has focused mostly on multinational companies (MNCs) operating in either North-North or North-South and less on South-South indigenous local firms. Thus the existing literature in Africa shows more studies of MNCs and little is known about CSR of local indigenous firms operating in the South particularly in the East Africa region. Accordingly, this paper explores CSR practices of indigenous local large firms of East Africa region particularly Kenya and Tanzania with the aim of testing the hypothesis that do local firms of East Africa region engage in similar CSR practices as firms in other parts of the world?. To answer this question only listed local large firms were considered based on the assumption that they are large enough to engage. Newspapers were the main source of data and information collected was supplemented by business Annual Reports for the period 2010-2012. The research finding revealed that local firms of East Africa engage in CSR practices. However, there are some differences in the set of activities these firms prefers to engage in compared to findings from previous studies. As such some CSR that were given priority by firms in East Africa were less prioritized in the other part of the world including Indonesia. This paper will add knowledge to the body of CSR and experience of CSR practices of South-South indigenous firms where is evidenced to have a relative dearth of literature on CSR. Finally, the paper concludes that local firms of East Africa region engage in similar activities like other firms globally. But firms give more priority to some activities such education and health related activities. Finally, the study intends to assist policy makers at firm’s levels to plan for long lasting projects related to CSR for their stakeholders.

Keywords: Africa, corporate social responsibility, developing countries, indigenous firms, Kenya, Tanzania

Procedia PDF Downloads 398
22582 Real Time Activity Recognition Framework for Health Monitoring Support in Home Environments

Authors: Shaikh Farhad Hossain, Liakot Ali

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Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

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22581 Physical Activity Rates and Motivational Profiles of Adolescents While Keeping a Daily Leisure-Time Physical Activity Record

Authors: Matt Fullmer, Carol Wilkinson, Keven Prusak, Dennis Eggett, Todd Pennington

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Obesity and chronic health issues are linked to physical inactivity. Physical education (PE) programs in school can play a major role in combating these health-related issues. This study focused on supporting competence through keeping a leisure-time physical activity (LTPA) record as part of PE. Keeping a daily LTPA record may be an effective intervention helping students feel more competent toward exercise, and thus, self-determined (within the context of self-determination theory) to exercise. Little is known about the relationship between daily LTPA records and perceived competence, motivational profiles, and LTPA levels of students enrolled in PE. This study examined the relationship between keeping a daily, online LTPA record and adolescent (a) motivational profiles toward LTPA, (b) perceived competence toward LTPA, and (c) LTPA behaviors. Secondary students (N = 124) in physical education classes completed a baseline questionnaire which consisted of the Behavioural Regulation in Exercise Questionnaire–2, the Perceived Competence Scale, and the Godin Leisure-Time Exercise Questionnaire. For three weeks, the students were assigned to keep the Presidential Active Lifestyle Award Challenge (PALAC) as their online LTPA record. They completed the questionnaire after each week. A 2 (gender) x 4 (trials) repeated measures ANCOVA examined the relationships between recording compliance and motivation, perceived competence, and physical activity. Results showed that recording compliance was not a significant predictor of perceived competence to participate in LTPA. Examining motivational factors, a significant interaction between recording compliance and introjected regulation was found. The more students recorded the less motivated they were by guilt or obligation to exercise in their leisure-time. Also, a significant interaction was found between recording compliance and intrinsic regulation, indicating that the more students recorded the more intrinsically motivated they were to exercise in their leisure-time. Lastly, there was a significant interaction between recording compliance and LTPA. As students kept the LTPA record, girls’ LTPA levels significantly decreased and boys’ LTPA levels significantly increased. The key findings are that, as implemented in this study: a) the lack of PALAC compliance suggests that daily LTPA records may NOT be the most effective intervention for this population, b) keeping a daily LTPA record did NOT help students feel more competent to exercise in their leisure-time, c) a daily LTPA record may help students move towards being more self-determined in their feelings towards LTPA, and d) the outcome of keeping a LTPA record on LTPA behavior is statistically significant, although actual differences may not be practically important.

Keywords: behavioural regulation in exercise questionnaire–2, Godin leisure–time exercise questionnaire, online physical activity log, perceived competence scale, self-determination theory

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22580 Understanding the Impact of Resilience Training on Cognitive Performance in Military Personnel

Authors: Haji Mohammad Zulfan Farhi Bin Haji Sulaini, Mohammad Azeezudde’en Bin Mohd Ismaon

Abstract:

The demands placed on military athletes extend beyond physical prowess to encompass cognitive resilience in high-stress environments. This study investigates the effects of resilience training on the cognitive performance of military athletes, shedding light on the potential benefits and implications for optimizing their overall readiness. In a rapidly evolving global landscape, armed forces worldwide are recognizing the importance of cognitive resilience alongside physical fitness. The study employs a mixed-methods approach, incorporating quantitative cognitive assessments and qualitative data from military athletes undergoing resilience training programs. Cognitive performance is evaluated through a battery of tests, including measures of memory, attention, decision-making, and reaction time. The participants, drawn from various branches of the military, are divided into experimental and control groups. The experimental group undergoes a comprehensive resilience training program, while the control group receives traditional physical training without a specific focus on resilience. The initial findings indicate a substantial improvement in cognitive performance among military athletes who have undergone resilience training. These improvements are particularly evident in domains such as attention and decision-making. The experimental group demonstrated enhanced situational awareness, quicker problem-solving abilities, and increased adaptability in high-stress scenarios. These results suggest that resilience training not only bolsters mental toughness but also positively impacts cognitive skills critical to military operations. In addition to quantitative assessments, qualitative data is collected through interviews and surveys to gain insights into the subjective experiences of military athletes. Preliminary analysis of these narratives reveals that participants in the resilience training program report higher levels of self-confidence, emotional regulation, and an improved ability to manage stress. These psychological attributes contribute to their enhanced cognitive performance and overall readiness. Moreover, this study explores the potential long-term benefits of resilience training. By tracking participants over an extended period, we aim to assess the durability of cognitive improvements and their effects on overall mission success. Early results suggest that resilience training may serve as a protective factor against the detrimental effects of prolonged exposure to stressors, potentially reducing the risk of burnout and psychological trauma among military athletes. This research has significant implications for military organizations seeking to optimize the performance and well-being of their personnel. The findings suggest that integrating resilience training into the training regimen of military athletes can lead to a more resilient and cognitively capable force. This, in turn, may enhance mission success, reduce the risk of injuries, and improve the overall effectiveness of military operations. In conclusion, this study provides compelling evidence that resilience training positively impacts the cognitive performance of military athletes. The preliminary results indicate improvements in attention, decision-making, and adaptability, as well as increased psychological resilience. As the study progresses and incorporates long-term follow-ups, it is expected to provide valuable insights into the enduring effects of resilience training on the cognitive readiness of military athletes, contributing to the ongoing efforts to optimize military personnel's physical and mental capabilities in the face of ever-evolving challenges.

Keywords: military athletes, cognitive performance, resilience training, cognitive enhancement program

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22579 Long-Term Sitting Posture Identifier Connected with Cloud Service

Authors: Manikandan S. P., Sharmila N.

Abstract:

Pain in the neck, intermediate and anterior, and even low back may occur in one or more locations. Numerous factors can lead to back discomfort, which can manifest into sensations in the other parts of your body. Up to 80% of people will have low back problems at a certain stage of their lives, making spine-related pain a highly prevalent ailment. Roughly twice as commonly as neck pain, low back discomfort also happens about as often as knee pain. According to current studies, using digital devices for extended periods of time and poor sitting posture are the main causes of neck and low back pain. There are numerous monitoring techniques provided to enhance the sitting posture for the aforementioned problems. A sophisticated technique to monitor the extended sitting position is suggested in this research based on this problem. The system is made up of an inertial measurement unit, a T-shirt, an Arduino board, a buzzer, and a mobile app with cloud services. Based on the anatomical position of the spinal cord, the inertial measurement unit was positioned on the inner back side of the T-shirt. The IMU (inertial measurement unit) sensor will evaluate the hip position, imbalanced shoulder, and bending angle. Based on the output provided by the IMU, the data will be analyzed by Arduino, supplied through the cloud, and shared with a mobile app for continuous monitoring. The buzzer will sound if the measured data is mismatched with the human body's natural position. The implementation and data prediction with design to identify balanced and unbalanced posture using a posture monitoring t-shirt will be further discussed in this research article.

Keywords: IMU, posture, IOT, textile

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22578 Deep Neural Network Approach for Navigation of Autonomous Vehicles

Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

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22577 Efficacy of Ergonomics Ankle Support on Squatting Pushing Skills during the Second Stage of Labor

Authors: Yu-Ching Lin, Meei-Ling Gau, Ghi-Hwei Kao, Hung-Chang Lee

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Objective: To compare the pushing experiences and birth outcomes of three different pushing positions during the second stage of labor. The three positions were: semi-recumbent, squatting, and squatting with the aid of ergonomically designed ankle supports. Methods: A randomized controlled trial was conducted at a regional teaching hospital in northern Taiwan. Data were collected from 168 primiparous women in their 38th to 42nd gestational week. None of the participants received epidural analgesia during labor and all were free of pregnancy and labor-related complications. Intervention: During labor, after full cervical dilation and when the fetal head had descended to at least the +1 station and had turned to the occiput anterior position, the experimental group was asked to push in the squatting position while wearing the ergonomically designed ankle supports; comparison group A was asked to push in the squatting position without the use of these supports; and comparison group B was asked to push in a standard semi-recumbent position. Measures: The participants completed a demographic and obstetrics datasheet, the Short Form McGill Pain Questionnaire (MPQ-SF), and the Labor Pushing Experience scale within 4-hours postpartum. Conclusion: In terms of delivery time, the duration between the start of pushing to crowning for the experimental group (squatting with ankle supports) averaged 25.52 minutes less (F =6.02, p< .05) than the time for comparison group B (semi-recumbent). Furthermore, the duration between the start of pushing to infant birth averaged 25.21 minutes less for the experimental group than for comparison group B (F =6.14, p< .05). Moreover, the experimental group had a lower average VAS pain score (5.05±3.22) than comparison group B and the average McGill pain score for the experimental group was lower than both comparison groups (F=18.12, p< .001). In summary, the participants in the group that delivered from a squatting position with ankle supports had better labor pushing experiences than their peers in the comparison groups. Results: In comparison to both unsupported squatting and semi-recumbent pushing, squatting with the aid of ergonomically designed ankle supports reduced pushing times, ameliorated labor pain, and improved the pushing experience. Clinical application and suggestion: The squatting with ankle-support intervention introduced in the present study may significantly reduce tiredness and difficulties in maintaining balance as well as increase pushing efficiency. Thus, this intervention may reduce the caring needs of women during the second stage of labor. This intervention may be introduced in midwifery education programs and in clinical practice as a method to improve the care of women during the second stage of labor.

Keywords: second stage of labor, pushing, squatting with ankle supports, squatting

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22576 The Application of Fuzzy Set Theory to Mobile Internet Advertisement Fraud Detection

Authors: Jinming Ma, Tianbing Xia, Janusz Getta

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This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: mobile internet, advertisement, anti-fraud, fuzzy set theory

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22575 Research on the Correlation between College Students' Physical Fitness and Running Habits: Data Mining of Smart Phone Sports App

Authors: Mingming Guo, Xiaozan Wang

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Introduction: The purpose of this study is to examine the correlation between the physical fitness of Chinese college students and their daily running habits (RH). Methods: A total of 718 college students from East China Normal University participated in this study (385 boys and 333 girls). Each participant participated in the Chinese Students’ Physical Fitness Test during the 2018-2019 school year. In addition, each student is also required to use the app to record all their running results during each run during the 2018-2019 school year. Researchers can query and export all running records through the app's management platform. Results: (1) The total number of kilometers run by the students showed a significant negative correlation with their vital capacity (VC), sitting body flexion (SBF), and long jump (LJ) (rᵥ

Keywords: college students, physical fitness, running habits, data mining

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22574 Automated Weight Painting: Using Deep Neural Networks to Adjust 3D Mesh Skeletal Weights

Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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22573 The Use of the TRIGRS Model and Geophysics Methodologies to Identify Landslides Susceptible Areas: Case Study of Campos do Jordao-SP, Brazil

Authors: Tehrrie Konig, Cassiano Bortolozo, Daniel Metodiev, Rodolfo Mendes, Marcio Andrade, Marcio Moraes

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Gravitational mass movements are recurrent events in Brazil, usually triggered by intense rainfall. When these events occur in urban areas, they end up becoming disasters due to the economic damage, social impact, and loss of human life. To identify the landslide-susceptible areas, it is important to know the geotechnical parameters of the soil, such as cohesion, internal friction angle, unit weight, hydraulic conductivity, and hydraulic diffusivity. The measurement of these parameters is made by collecting soil samples to analyze in the laboratory and by using geophysical methodologies, such as Vertical Electrical Survey (VES). The geophysical surveys analyze the soil properties with minimal impact in its initial structure. Statistical analysis and mathematical models of physical basis are used to model and calculate the Factor of Safety for steep slope areas. In general, such mathematical models work from the combination of slope stability models and hydrological models. One example is the mathematical model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope- Stability Model) which calculates the variation of the Factor of Safety of a determined study area. The model relies on changes in pore-pressure and soil moisture during a rainfall event. TRIGRS was written in the Fortran programming language and associates the hydrological model, which is based on the Richards Equation, with the stability model based on the principle of equilibrium limit. Therefore, the aims of this work are modeling the slope stability of Campos do Jordão with TRIGRS, using geotechnical and geophysical methodologies to acquire the soil properties. The study area is located at southern-east of Sao Paulo State in the Mantiqueira Mountains and has a historic landslide register. During the fieldwork, soil samples were collected, and the VES method applied. These procedures provide the soil properties, which were used as input data in the TRIGRS model. The hydrological data (infiltration rate and initial water table height) and rainfall duration and intensity, were acquired from the eight rain gauges installed by Cemaden in the study area. A very high spatial resolution digital terrain model was used to identify the slopes declivity. The analyzed period is from March 6th to March 8th of 2017. As results, the TRIGRS model calculates the variation of the Factor of Safety within a 72-hour period in which two heavy rainfall events stroke the area and six landslides were registered. After each rainfall, the Factor of Safety declined, as expected. The landslides happened in areas identified by the model with low values of Factor of Safety, proving its efficiency on the identification of landslides susceptible areas. This study presents a critical threshold for landslides, in which an accumulated rainfall higher than 80mm/m² in 72 hours might trigger landslides in urban and natural slopes. The geotechnical and geophysics methods are shown to be very useful to identify the soil properties and provide the geological characteristics of the area. Therefore, the combine geotechnical and geophysical methods for soil characterization and the modeling of landslides susceptible areas with TRIGRS are useful for urban planning. Furthermore, early warning systems can be developed by combining the TRIGRS model and weather forecast, to prevent disasters in urban slopes.

Keywords: landslides, susceptibility, TRIGRS, vertical electrical survey

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22572 A Research and Application of Feature Selection Based on IWO and Tabu Search

Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

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Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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22571 Tip-Apex Distance as a Long-Term Risk Factor for Hospital Readmission Following Intramedullary Fixation of Intertrochanteric Fractures

Authors: Brandon Knopp, Matthew Harris

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Purpose: Tip-apex distance (TAD) has long been discussed as a metric for determining risk of failure in the fixation of peritrochanteric fractures. TAD measurements over 25 millimeters (mm) have been associated with higher rates of screw cut out and other complications in the first several months after surgery. However, there is limited evidence for the efficacy of this measurement in predicting the long-term risk of negative outcomes following hip fixation surgery. The purpose of our study was to investigate risk factors including TAD for hospital readmission, loss of pre-injury ambulation and development of complications within 1 year after hip fixation surgery. Methods: A retrospective review of proximal hip fractures treated with single screw intramedullary devices between 2016 and 2020 was performed at a 327-bed regional medical center. Patients included had a postoperative follow-up of at least 12 months or surgery-related complications developing within that time. Results: 44 of the 67 patients in this study met the inclusion criteria with adequate follow-up post-surgery. There was a total of 10 males (22.7%) and 34 females (77.3%) meeting inclusion criteria with a mean age of 82.1 (± 12.3) at the time of surgery. The average TAD in our study population was 19.57mm and the average 1-year readmission rate was 15.9%. 3 out of 6 patients (50%) with a TAD > 25mm were readmitted within one year due to surgery-related complications. In contrast, 3 out of 38 patients (7.9%) with a TAD < 25mm were readmitted within one year due to surgery-related complications (p=0.0254). Individual TAD measurements, averaging 22.05mm in patients readmitted within 1 year of surgery and 19.18mm in patients not readmitted within 1 year of surgery, were not significantly different between the two groups (p=0.2113). Conclusions: Our data indicate a significant improvement in hospital readmission rates up to one year after hip fixation surgery in patients with a TAD < 25mm with a decrease in readmissions of over 40% (50% vs 7.9%). This result builds upon past investigations by extending the follow-up time to 1 year after surgery and utilizing hospital readmissions as a metric for surgical success. With the well-documented physical and financial costs of hospital readmission after hip surgery, our study highlights a reduction of TAD < 25mm as an effective method of improving patient outcomes and reducing financial costs to patients and medical institutions. No relationship was found between TAD measurements and secondary outcomes, including loss of pre-injury ambulation and development of complications.

Keywords: hip fractures, hip reductions, readmission rates, open reduction internal fixation

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22570 Burnout in the Resident Physician and a Simple Means of Improvement

Authors: Jacob Dangerfield, Jacob Pollard, Jennifer DeCou

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Introduction: Burnout, anxiety, and depression are three conditions that are prevalent in medical providers. This is especially the case in the field of anesthesia, which has a high number of providers suffering from burnout and burnout syndrome. A major contributor to this issue is isolation in the workplace, with a perceived lack of peer support as a major risk factor for burnout. Two organizational interventions that can be done to help improve this issue are small group sessions and providing affordable mental health services. Per American College of Graduate Medical Education (ACGME) Guidelines, these affordable mental health services are a requirement of all residency programs, but for a variety of reasons, many residents do not access them. As physicians, we are often not good at asking for help. With this in mind, we hypothesized that carrying out small group resiliency sessions facilitated by Graduate Medical Education (GME) Wellness Counselors would improve both resident peer support as well as the likelihood that a resident will reach out to GME Wellness in a time of need. Methods: We held small group resiliency sessions with the GME Wellness Mental Health Professionals during protected didactic time. These sessions were small groups, including the members of one’s class (i.e., first-year residents on their own), and were facilitated by 1-2 mental health professionals. After these sessions, we surveyed residents who attended using a short Google Forms survey and using a 5-point Likert Scale, asked residents about some outcomes from the session. A “strongly agree” or “agree” was considered a positive response. Results: Results from our survey showed that the resident sessions had multiple positive outcomes. This survey was sent to 29 residents, and we had a 62% response rate. We found out through this survey that these small group sessions had a perceived positive impact on resident personal well-being, increased perceived peer support from classmates, and made residents more likely to reach out to GME Wellness in the future. Perceived positive impact on well-being was found in 83% of resident respondents, improved perceived peer support in 83% of respondents, and 78% of resident respondents stated that this session increased their likelihood of reaching out to mental health professionals. Conclusions: Through this study, we can conclude that our hypothesis was correct in that Small Group Resiliency Sessions that are facilitated by GME Wellness Counselors improve both resident peer support as well as the likelihood a resident reaches out to these mental health professionals in time of need. We believe these findings are very important as they address two important factors that can aid in decreasing a provider’s risk of experiencing burnout. Through this simple means, we believe other residency programs can help the well-being of their residents, and together, we can decrease the number of cases of burnout in anesthesia.

Keywords: anesthesiology, burnout, wellness, depression, residents, trainees, mental health

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