Search results for: adaptive random testing

Authors: Purna Prasad Acharya, Madhav Karki, Sunta B. Tamang, Uttam Basnet, Chhatra Katwal

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The paper outlines the idea behind achieving sustainable lifestyles based on the spiritual values and teachings of Lord Buddha. This objective is to be achieved by spreading the tenets and teachings of Buddhism throughout the Asia Pacific region and the world from the sacred birth place of Buddha - Lumbini, Nepal. There is an urgent need to advance the relevance of Buddhist philosophy in tackling the triple planetary crisis of climate change, nature’s decline, and pollution. Today, the world is facing an existential crisis due to the above crises, exasperated by hunger, poverty and armed conflict. To address multi-dimensional impacts, the global communities have to adopt simple life styles that respect nature and universal human values. These were the basic teachings of Gautam Buddha. Lumbini, Nepal has the moral obligation to widely disseminate Buddha’s teaching to the world and receive constant feedback and learning to develop human and ecosystem resilience by molding the lifestyles of current and future generations through adaptive learning and simplicity across the geography and nationality based on spirituality and environmental stewardship. By promoting Buddhism, Nepal has developed a pro-nature tourism industry that focuses on both its spiritual and bio-cultural heritage. Nepal is a country rich in ancient wisdom, where sages have sought knowledge, practiced meditation, and followed spiritual paths for thousands of years. It can spread the teachings of Buddha in a way people can search for and adopt ways to live, creating harmony with nature. Using tools of natural sciences and social sciences, the team will package knowledge and share the idea of community well-being within the framework of environmental sustainability, social harmony and universal respect for nature and people in a more holistic manner. This notion takes into account key elements of sustainable development such as food-energy-water-biodiversity interconnections, environmental conservation, ecological integrity, ecosystem health, community resiliency, adaptation capacity, and indigenous culture, knowledge and values. This inclusive concept has garnered a strong network of supporters locally, regionally, and internationally. The key objectives behind this concept are: a) to leverage expertise and passion of a network of global collaborators to advance research, education, and policy outreach in the areas of human sustainability based on lifestyle change using the power of spirituality and Buddha’s teaching, resilient lifestyles, and adaptive living; b) help develop creative short courses for multi-disciplinary teaching in educational institutions worldwide in collaboration with Lumbini Buddha University and other relevant partners in Nepal; c) help build local and regional intellectual and cultural teaching and learning capacity by improving professional collaborations to promote nature based and Buddhist value-based lifestyles by connecting Lumbini to Nepal’s rich nature; d) promote research avenues to provide policy relevant knowledge that is creative, innovative, as well as practical and locally viable; and e) connect local research and outreach work with academic and cultural partners in South Korea so as to open up Lumbini based Buddhist heritage and Nepal’s Karnali River basin’s unique natural landscape to Korean scholars and students to promote sustainable lifestyles leading to human living in harmony with nature.

Keywords: triple planetary crisis, spirituality, sustainable lifestyles, living in harmony with nature, resilience

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Authors: Mustafa Tekke, Nurullah Kurt

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This study examined the level of career maturity of undergraduate foreign students in a public university in Malaysia by examining on cultural aspect by using the Career Maturity Inventory. Two hundred and twenty nine (Male = 106, Female = 123) foreign students studying in various majors completed the Career Maturity Inventory and the scores of the foreign students on the CMI suggested that they had slightly higher levels than the mean level of maturity in career. Result was also supported by testing the feeling about major, consideration of changing major and planning after graduation, which indicated that foreign students had their own career decision making. However, this result should be viewed with caution within ethnic difference.

Keywords: career maturity, foreign students, career decision making, feeling about major, knowledge about major

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Authors: Şebnem Aslan, Demet Akarçay

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The objective of this study is to investigate the feelings of health employees occurred by bullying and the relationships between these feelings at work place. In this context, the relationships between bullying and the feelings of self-esteem, employee silence, anger, self- blame and shame. This study was conducted among 512 health employees in three hospitals in Konya by using survey method and simple random sampling. The scales of bullying, self-esteem, employee silence, anger, self-blame, and shame were performed within the study. The obtained data were analyzed with descriptive analysis, correlation, confirmative factor analysis, structural equation modeling and path analysis. The results of the study showed that while bullying had a positive effect on self-esteem (.61), employee silence (.41), anger (.18), a negative effect on self-blame and shame (-.26) was observed. Employee silence affected self-blame and shame (.83) as positively. Besides, self-esteem impacted on self- blame and shame (.18), employee silence (.62) positively and self-blame and shame was observed as negatively affecting on anger (-.20). Similarly, self-esteem was found as negatively affected on anger (-.13).

Keywords: bullying, self-esteem, employee silence, anger, shame and guilt, healthcare employee

Procedia PDF Downloads 297

Authors: Ruslin, R. E. Kartasasmita, M. S. Wibowo, S. Ibrahim

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An aphrodisiac is a substance contained in food or drug that can arouse sexual instinct and increase pleasure while working, these substances derived from plants, animals, and minerals. When consuming substances that have aphrodisiac activity and duration can improve the sexual instinct. The natural aphrodisiac effect can be obtained through plants, animals, and minerals. Leonurine compound has aphrodisiac activity, these compounds can be isolated from plants of Leonurus Sp, Sundanese people is known as deundereman, this plant is empirical has aphrodisiac activity and based on the isolation of active compounds from plants known to contain compounds leonurine, so that the compound is expected to have activity aphrodisiac. Leonurine compound can be isolated from plants or synthesized chemically with material dasa siringat acid. Leonurine compound can be obtained commercial and derivatives of these compounds can be synthesized in an effort to increase its activity. This study aims to obtain derivatives leonurine better aphrodisiac activity compared with the parent compound, modified the structure of the compounds in the form leonurin guanidino butyl ester group with butyl amin and bromoetanol. ArgusLab program version 4.0.1 is used to determine the binding energy, hydrogen bonds and amino acids involved in the interaction of the compound PDE5 receptor. The in vivo test leonurine compounds and derivatives as an aphrodisiac ingredients and hormone testosterone levels using 27 male rats Wistar strain and 9 female mice of the same species, ages ranged from 12 weeks rats weighing + 200 g / tail. The test animal is divided into 9 groups according to the type of compounds and the dose given. Each treatment group was orally administered 2 ml per day for 5 days. On the sixth day was observed male rat sexual behavior and taking blood from the heart to measure testosterone levels using ELISA technique. Statistical analysis was performed in this study is the ANOVA test Least Square Differences (LSD) using the program Statistical Product and Service Solutions (SPSS). Aphrodisiac efficacy of the leonurine compound and its derivatives have proven in silico and in vivo test, the in silico testing leonurine derivatives have smaller binding energy derivatives leonurine so that activity better than leonurine compounds. Testing in vivo using rats of wistar strain that better leonurine derivative of this compound shows leonurine that in silico studies in parallel with in vivo tests. Modification of the structure in the form of guanidine butyl ester group with butyl amin and bromoethanol increase compared leonurine compound for aphrodisiac activity, testosterone derivatives of compounds leonurine experienced a significant improvement especial is 1RD compounds especially at doses of 100 and 150 mg/bb. The results showed that the compound leonurine and its compounds contain aphrodisiac activity and increase the amount of testosterone in the blood. The compound test used in this study acts as a steroid precursor resulting in increased testosterone.

Keywords: aphrodisiac dysfunction erectile leonurine 1-RD 2-RD, dysfunction, erectile leonurine, 1-RD 2-RD

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Leila Najeh

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This study investigates the motivational factors influencing Tunisian university students learning English through online platforms. Using a mixed-methods approach, data were collected from 112 undergraduate students of English across universities in Tunisia. The study employed an online questionnaire to measure intrinsic and extrinsic motivation, incorporating the Learning Motivation Questionnaire (FFLLM-Q) developed by Gonzales in 2001 and semi-structured interviews to explore students’ perspectives on their online learning experiences. Quantitative analysis revealed a significant correlation between intrinsic motivation and interactive features such as gamification and adaptive content delivery, while extrinsic motivation was strongly linked to career aspirations and academic requirements. Qualitative findings highlighted challenges such as limited interaction with peers and teachers, technical constraints, and a lack of immediate feedback as demotivating factors. Participants expressed a preference for blended learning models, combining the flexibility of online education with the collaborative environment of traditional classrooms. This study underscores the need for tailored online learning solutions to enhance the motivational landscape for Tunisian students, emphasizing the importance of culturally relevant content, accessible platforms, and supportive learning communities. Further research is recommended to evaluate the long-term impact of these interventions on language proficiency and learner autonomy.

Keywords: motivational factor, online foreign language learnig, tunsian students of english, online learning platforms

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

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Authors: Simon Ayorinde Okanlawon

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This study examines residents’ assessment of with infrastructural facilities in the urban fringe of Ibadan, Nigeria. Random sampling technique was used in selecting four Local Government Areas out of the six suburban LGAs of the city. Google earth and ground trotting were used in capturing and selecting seven hundred and forty-two new houses. The questionnaires administered on house owners were harvested on the spot. The information collected includes socio-economic and demographic characteristics of residents as well as characteristics of infrastructural facilities. The study utilised both descriptive and inferential statistical analyses; Facility Availability Index (FAI) Facility Functionality Index (FFI) and Residents’ Satisfactions Index (RSI) were used to compare respectively residents’ perceived levels of availability of, the functionality of, and satisfaction with facilities across Local Government Areas. The study shows that levels of both availability of, and satisfaction with infrastructural facilities are low with respective overall FAI (0.8) and RSI (0.05), while the functionality of the facilities is generally very poor IFFI = - 0.58). Strategies were proposed to enhance the good, livable, and healthy environment.

Keywords: infrastructural facilities, infrastructural perception index, residents’ satisfaction, urban fringe of Ibadan

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Authors: Mehravar Javid, James Sexton, Farzaneh Amani, Kainaz Patravala

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Self-expansion is a procedure through which people expand the dimensions of their self-concept by incorporating novel content into their sense and experience of identity. Greater self-expansion predicts positive consequences for individuals and romantic relationships. The self-expansion questionnaire (SEQ) originally developed by Lewandowski & Aron (2002) assumes that self-expansion is constituted of key components from the self-expansion model. This study aimed to confirm the factor structure of SEQ and adapt the questions of the scale to the Iranian culture. The sample included 190 participants who responded to 14 items and were selected by simple random sampling. Using Amos-21 and SPSS-21, descriptive statistics, Pearson correlation and Confirmatory Factor Analysis (CFA) were calculated. Cronbach’s alpha coefficient for total SEQ items was 0.92. Results of CFA supported the factor structure SEQ [RMSEA=0.08, GFI=0.88 and CFI=0.92] that showed the model has a good fit and also all the items of SEQ, have a high correlation and have a direct and significant relationship. So, the SEQ demonstrated acceptable psychometric properties in Tehran University students. Looking forward, it would be interesting and exciting to see the implications of the scale as applied to romantic relationships.

Keywords: validity, reliability, confirmatory factor analysis, self-expansion questionnaire

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Zeyu Zhou, Xiaojun Bi

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Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Mirvat Shamseddine, Issam Lakkis

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We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

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Authors: Stephen V. Crowder, Jonathan W. Lane

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With short production development times, there is an increased need to demonstrate product reliability relatively quickly with minimal testing. In such cases there may be few if any observed failures. Thus it may be difficult to assess reliability using the traditional reliability test plans that measure only time (or cycles) to failure. For many components, degradation measures will contain important information about performance and reliability. These measures can be used to design a minimal test plan, in terms of number of units placed on test and duration of the test, necessary to demonstrate a reliability goal. In this work we present a case study involving an electronic component subject to degradation. The data, consisting of 42 degradation paths of cycles to failure, are first used to estimate a reliability function. Bootstrapping techniques are then used to perform power studies and develop a minimal reliability test plan for future production of this component.

Keywords: degradation measure, time to failure distribution, bootstrap, computational science

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Dana Kristalova

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

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Authors: Ngozi Nwogu, Mohammed Kajama, Emmanuel Anyanwu, Edward Gobina

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With the objective to create technologically advanced materials to be scientifically applicable, multi-layer silica alumina membranes were molecularly fabricated by continuous surface coating silica layers containing hybrid material onto a ceramic porous substrate for flue gas separation applications. The multi-layer silica alumina membrane was prepared by dip coating technique before further drying in an oven at elevated temperature. The effects of substrate physical appearance, coating quantity, the cross-linking agent, a number of coatings and testing conditions on the gas separation performance of the membrane have been investigated. Scanning electron microscope was used to investigate the development of coating thickness. The membrane shows impressive perm selectivity especially for CO2 and N2 binary mixture representing a stimulated flue gas stream

Keywords: gas separation, silica membrane, separation factor, membrane layer thickness

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Authors: Laura Sapranaviciute-Zabazlajeva, Abdonas Tamosiunas, Dalia Luksiene, Dalia Virviciute

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The cardiovascular diseases (CVD) is the leading cause of death in the EU, especially in the middle aged and elderly population. Psychological wellbeing (PWB) has been linked with better cardiovascular health and survival in the elderly. The aim of the study is to evaluate associations between CVD risk and PWB in middle-aged and elderly population. 10,940 middle aged and older Lithuanians of age 45-74 years, were invited to participate in the study. A study sample was a random and stratified by gender and age. In 2006-2008 7,087 responders participated in the survey, so the response rate was 64.8%. A follow-up study was conducted from 2006 till 2015. New CVD cases and deaths from CVD were evaluated using the Kaunas population-based CVD register and death register of Kaunas. Study results revealed that good PWB predicts longer life in female participants (Log Rank = 13.7, p < 0.001). In the fully adjusted model for socio-demographic, social and CVD risk factors, hazard ratio for CVD mortality risk was lower amongst women with good PWB (HR = 0.28, 95% CI 0.11-0.72), but not significantly for men. Our study concludes, that lower CVD mortality rates is being associated with better PWB in female aged 45-74 years.

Keywords: psychological well-being, cardiovascular disease, elderly, survival

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Authors: Fatemeh Keshavarz

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Background: Schizophrenia is a disease of the nervous system, and immune system disorders can affect its pathogenesis. Activation of microglia, proinflammatory cytokines, disruption of the blood-brain barrier (BBB) due to inflammation, activation of autoreactive B cells, and consequently the production of autoantibodies against system antigens are among the immune processes involved in neurological diseases. interleukin 32 (IL-32) a proinflammatory cytokine that important player in the activation of the innate and adaptive immune responses. This study aimed to measure the serum level of IL-32 as well as the frequency of autoantibody positivity against several nervous system antigens in patients with schizophrenia. Material and Methods: This study was conducted on 40 patients with schizophrenia and 40 healthy individuals in the control group. Serum IL-32 levels were measured by ELISA. The frequency of autoantibodies against Hu, Ri, Yo, Tr, CV2, Amphiphysin, SOX1, Zic4, ITPR1, CARP, GAD, Recoverin, Titin, and Ganglioside antigens were measured by indirect immunofluorescence method. Results: Serum IL-32 levels in patients with schizophrenia were significantly higher compared to the control group. Autoantibodies were positive in 8 patients for GAD antigen and 5 patients for Ri antigen, which showed a significant relationship compared to the control group. Autoantibodies were also positive in 2 patients for CV2, in 1 patient for Hu, and in 1 patient for CARP. Negative results were reported for other antigens. Conclusion: Our findings suggest that elevated the serum IL-32 level and autoantibody positivity against several nervous system antigens may be involved in the pathogenesis of schizophrenia.

Keywords: schizophrenia, microglia, autoantibodies, IL-32

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Authors: Jonas Colin

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Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Anita Padmanabhanunni, Labeeqah Jaffer

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Menstruation signifies the transition to biological sexual maturity and culture-bound values influence its meaning and experience for women. In South Africa there is a paucity of research specific to the topic of menstruation. This study addresses this gap in the literature by exploring the experiences of menstruation among a group of women from the ama-Xhosa ethnic group, one of the largest ethnic groups in the country. Focus group and individual interviews were conducted with ama-Xhosa woman (n= 15). Data was analyzed using thematic analysis. The study found that traditional knowledge systems and cultural practices associated with menstruation including virginity testing and intonjane (female right of passage) still exist and impact on women’s subjective experiences. The study highlights the interface of tradition and modernity in the meanings ascribed to menstruation and women’s experiences of it.

Keywords: menstruation, cultural belief systems, South Africa, ama-Xhosa

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Authors: Joshua Abraham, Craig Wales

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Abstract—SIGN Guideline 122 recommends that all patients who are admitted to hospital are assessed for venous thromboembolism risk within 24 hours of admission. NHS Greater Glasgow and Clyde provide guidance on this in the form of a proforma. Patients are then subsequently prescribed either thrombo-embolic-deterrent stockings (TEDS)/low molecular weight heparin (LMWH) for the prevention of VTE based on their score. A retrospective casenote audit of a random sample of fifty oncology and trauma inpatients at the QEUH in December 2019 was performed. 90% of patients had a risk assessment conducted as evidenced by a completed proforma. In 78% of these patients, the proforma fully completed. Overall 94% of patients had some for of thromboprophylaxis prescribed in the form of TEDS or LMWH. A lack of 100% compliance against the given standards highlighted potential implications for patient safety, but also medico-legal ramifications for staff. Clinical judgement can only be relied upon if there is written documentation as evidence. Further staff education and the suggestion of a written prompt to the clerk-in documentation will hopefully improve compliance, whilst a repeat audit should demonstrate any improvement.

Keywords: Maxillofacial , Thromboembolism, Thromboprophylaxis , Prescription

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Authors: Yuri Teraoka, Cheerawit Rattanapan, Aroonsri Mongkolchati

Abstract:

This cross sectional analytic study was carried out to determine factors related to protective behavior on indoor pollution among pregnant women in Nakhon Pathom province, Thailand. A total of 319 pregnant women were enrolled at three antenatal care clinics in community hospital. Data were collected using simple random sampling from April 2015 to May 2015 using a structured self-administration questionnaire by well-trained research assistants. The result showed that around 73% pregnant women showed low level of low protective behavior on indoor pollution. Chi-square and multiple logistic regression were used to examine the factors and protective behavior on indoor pollution. After adjusting for confounding factors, this study found that tobacco smoking before pregnancy (AOR=2.15, 95% CI: 0.78-5.95) and low environmental health hazard (AOR=1.94, 95% CI: 1.09-3.49) were significant factors related to protective behavior on indoor pollution among pregnant women (p-value < 0.05). In conclusion, this study suggested that environmental health education campaign and environmental implementation program among pregnant woman are needed.

Keywords: Thailand, environmental health, protective behavior, pregnant women

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Authors: Dewi Fatmaningrum, Ade Wiradnyani

Abstract:

Background: Optimal feeding, include optimal micronutrient intake, becomes one of the ways to overcome the long-term consequences of undernutrition. Macronutrient and micronutrient intake were important for rapid growth and development of the children. Objectives: To assess macro and micronutrient intake of children aged 12-23 months old and nutrients inadequacy from intake of children aged 12-23 months old. Methods: This survey was a cross-sectional study, simple random sampling was performed to select respondents. Total sample of this study was 83 children aged 12-23 months old in Paseban Village, Senen Sub-district, Central Jakarta. The data was collected via interview and hemoglobin measurement of children. Results: The highest prevalence of inadequacy was iron intake (52.4%) compared to other micronutrients, 11.98% children had inadequate energy intake. There were 62.6% anemic children in the study area in which divided into anemic (37.3%) and severe anemic (25.3%). Conclusion: Micronutrient inadequacy occurred more frequently than macronutrient inadequacy in the study area. The higher the percentage of iron inadequacy gets, the higher the percentage of anemia among children is observed.

Keywords: micronutrient, macronutrient, children under five, urban setting

Procedia PDF Downloads 335

Authors: Huai-Cong Liu, Tae Chul Jeong, Ju Lee

Abstract:

The aim of this study was to develop an electric circuit method (ECM) to ascertain the core loss influence on a Synchronous Reluctance Motor (SynRM) in the condition of the maximum torque per ampere (MTPA). SynRM for fan usually operates on the constant torque region, at synchronous speed the MTPA control is adopted due to current vector. However, finite element analysis (FEA) program is not sufficient exactly to reflect how the core loss influenced on the current vector. This paper proposed a method to calculate the current vector with consideration of core loss. The precision of current vector by ECM is useful for MTPA control. The result shows that ECM analysis is closer to the actual motor’s characteristics by testing with a 7.5kW SynRM drive System.

Keywords: core loss, SynRM, current vector, magnetic saturation, maximum torque per ampere (MTPA)

Procedia PDF Downloads 530

Authors: E. Rahimi, S. Shaigannia

Abstract:

Salmonella typhimurium and Salmonella enteritidis are important infectious agents causing food poisoning and food-borne gastrointestinal diseases. This study was carried out in order to investigate the distribution of virulence genes and antimicrobial resistance properties of S. typhimurium and S. enteritidis isolated from ruminant milk and dairy products in Iran. Overall 360 raw and pasteurized milk and traditional and commercial dairy products were purchased from random selected supermarkets and retail stories of Isfahan province, Iran. Samples were cultured immediately and those found positive for Salmonella were analyzed for the presence of S. typhimurium, S. enteritidis and several putative genes using PCR. Totally, 13 (3.61%), 8 (2.22%), 1 (0.27%) and 4 (1.11%) samples were found to be contaminated with Salmonella spp., S. typhimurium, S. enteritidis and other species of Salmonella, respectively. PCR results showed that invA, rfbJ, fliC and spv were the detected virulence genes in S. typhimurium and S. enteritidis positive samples. To the authors’ knowledge, the present study is the first prevalence report of virulence genes of S. typhimurium and S. enteritidis isolated from ruminant milk and traditional and commercial dairy products in Iran.

Keywords: Salmonella typhimurium, Salmonella enteritidis, virulence genes, ruminant milk, dairy products

Procedia PDF Downloads 646