Search results for: artificial life

Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Jau-Shya Lee, Rossita Shapawi, Vin Cent Pua

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Tilapia is a popular cultured fresh-water fish in Malaysia. The highly perishable nature of the fish and increasing demand for high-quality ready-to-cook fish has intensified the search for better fish preservation method. Chitosan edible coating has been evident to extend the shelf life of fish fillet. This work was attempted to explore the potential of ascorbic acid in enhancing the shelf life extension ability of chitosan coated Tilapia fillet under refrigeration condition (4 ± 1oC). A 3 2 Factorial Design which comprising of three concentrations of chitosan (1, 1.5 and 2%) and two concentrations of ascorbic acids (2.5 and 5%) was used. The fish fillets were analyzed for total viable count, thiobarbituric acid (TBA) value, pH, aw and colour changes at 3-day interval over 15-day storage. The shelf life of chitosan coated (1.5% and 2%) fillet was increased to 15 days as compared to uncoated fish fillet which can only last for nine days. The inhibition of microbial growth of fish fillet was enhanced with the addition of 5% of ascorbic acids in 2% of chitosan. The TBA value, pH and aw for chitosan coated samples were found lower than that of uncoated sample (p<0.05). The colour stability of the fish fillet was also improved by the composite coating. Overall, 2% of chitosan and 5% of ascorbic acid formed the most effective coating to enhance the quality and to lengthen the shelf life of refrigerated Tilapia fillet.

Keywords: ascorbic acid, chitosan, edible coating, fish fillet

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Authors: Saeedeh Eshkil, Seyedeh Farnaz Mousavi, Hamid Reza Kianifar, Seyed Java Sayyedi, Mehdi Sohrabi, Elham Bakhtiari, Morteza Mashoughi, Ezzat Khodashenas

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Background: The effect of the SPARK physical education program on lung function in cystic fibrosis patients is not yet determined.).SPARK is Sports, play and active recreation for kids, including moving skills, aerobic games, jogging or walking, aerobic dance and jump rope. Regarding the high prevalence of cystic fibrosis and its destructive effects on the lungs, the aim of this study is to evaluate lung function and quality of life before and after undergoing the SPARK physical education program in children with cystic fibrosis. Method: In this quasi-experimental study, all patients with cystic fibrosis aged 6-18 years referred to the cystic fibrosis clinic of Dr. Sheikh Hospital were enrolled. The patients went under 12 weeks of SPARK training program (3 sessions per week, each session 45 minutes). The quality of life questionnaire ( Cystic Fibrosis Questionnaire includes self-examination, parental ) for patients with cystic fibrosis and spirometry indices (FEV1, FVC, FEV1/FVC, FEF25-75) was filled out before and after intervention for all patients. Results The mean and standard deviation of patients' age were 9.85±2.67 years, and 65% of patients were female. The FEV1 was significantly different before and after the SPARK physical education program (P=0.03), and the respiratory component of quality of life significantly increased after intervention (P=0.002). The overall score of quality of life from parents’ point of view was 2.87 ± 0.38, which increased to 2.99 ± 0.38 after the intervention. Conclusion: The SPARK training program may improve the spirometric parameters in children with cystic fibrosis. It also had a significant effect on improving the quality of life of patients, especially in the respiratory component.

Keywords: cystic fibrosis, pediatrics, SPARK motor program, spirometry

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Authors: Zasha Romero

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This poster will detail a family oriented event which introduced individuals with visual impairments and individuals with secondary disabilities to social interaction and helped promote life-long fitness and recreational skills. Purpose: The poster will detail a workshop conducted for individuals with visual impairments, individuals with secondary disabilities and their families. Methods: Families from all over the South Texas were invited through schools and different non-profit organizations and came together for a day full recreational games in an effort to promote life-long fitness, recreational opportunities as well as social interactions. Some of the activities that participants and their families participated in were tennis, dance, swimming, baseball, etc. all activities were developed to engage the learner with visual impairments as well as secondary disabilities. Implications: This workshop was done in collaboration with different non-profit institutions to create awareness and provide opportunities for physical fitness, social interaction, and life-long fitness skills associated with the activities presented. The workshop provided collaboration amongst different entities and novel ideas to create opportunities for a typically underserved population.

Keywords: engagement, awareness, underserved population, inclusion, collaboration

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Authors: Vakhtang Nozadze, Luiza Arutinova, Khatuna Martskvishvili

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The social empowerment of most needed individuals is a challenging issue, especially for developing countries. The current study explores the effects of visual impairment on individuals’ satisfaction with different aspects of life (i.e. education, job, income, family) and coping strategies. Furthermore, the difference between groups according to health status is revealed. Other demographic variables (education, employment, and marital status) is also considered. The cross-sectional design and self-reported questionnaires were adopted. Seventy-two visually impaired males and females (age range 13-66) and seventy healthy individuals participated in the study. The results reveal the importance of health status on the accessibility of social amenities, individuals’ satisfaction with life, and a diversity of coping strategies, irrespective of the age. The research has an important implication for social integration research and policy.

Keywords: coping strategies, life satisfaction, social integration, visual impairment

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Authors: Horng-Ji Lai

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The intuitive design features and friendly interface of smartphone attract older adults. In Taiwan, many senior education institutes offer smartphone training courses for older adult learners who are interested in learning this innovative technology. It is expected that the training courses can help them to enjoy the benefits of using smartphone and increase their life satisfaction. Therefore, it is important to investigate the factors that influence older adults’ behavior of using smartphone. The purpose of the research was to develop and test a research model that investigates the factors (self-efficacy, social connection, the need to seek health information, and the need to seek financial information) affecting older adult learners’ Internet behaviour and their life satisfaction with use of smartphone. Also, this research sought to identify the relationship between the proposed variables. Survey method was used to collect research data. A Structural Equation Modeling was performed using Partial Least Squares (PLS) regression for data exploration and model estimation. The participants were 394 older adult learners from smartphone training courses in active aging learning centers located in central Taiwan. The research results revealed that self-efficacy significantly affected older adult learner’ social connection, the need to seek health information, and the need to seek financial information. The construct of social connection yielded a positive influence in respondents’ life satisfaction. The implications of these results for practice and future research are also discussed.

Keywords: older adults, smartphone, internet behaviour, life satisfaction

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Authors: Erva Akin

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– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.

Keywords: artificial intelligence, copyright, data governance, machine learning

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Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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Authors: Himansu, Bedanga Talukdar

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The aim of present study is to investigate the prevalence of various health outcomes and quality of life and analyzes the moderating role of social capital on health outcomes (i.e., self-rated good health (SRH), depression, functional health and quality of life) among elderly in India. Using WHO Study on Global AGEing and adults health (SAGE) data, with sample of 6559 elderly between 50 and above (Mage=61.81, SD=9.00) age were selected for analysis. Multivariate analysis accessed the prevalence of SRH, depression, functional limitation and quality of life among older adults. Logistic regression evaluates the effect of social capital along with other co-founders on SRH, depression, and functional limitation, whereas linear regression evaluates the effect of social capital with other co-founders on quality of life (QoL) among elderly. Empirical results reveal that (74%) of respondents were married, (70%) having low social action, (46%) medium sociability, (45%) low trust-solidarity, (58%) high safety, (65%) medium civic engagement and 37% reported medium psychological resources. The multivariate analysis, explains (SRH) is associated with age, female, having education, higher social action great trust, safety and greater psychological resources. Depression among elderly is greatly related to age, sex, education and higher wealth, higher sociability, having psychological resources. QoL is negatively associated with age, sex, being Muslim, whereas positive associated with higher education, currently married, civic engagement, having wealth, social action, trust and solidarity, safeness, and strong psychological resources.

Keywords: depressive symptom, functional limitation, older adults, quality of life, self rated health, social capital

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Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: Ek-Uma Imkome, Jintana Yunibhand, Waraporn Chaiyawat

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Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X² = 114.35, df = 92, p-value = 0.05, X² /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p<0.05). Medication use self-efficacy had a direct effect on psychotic symptoms (-0.25, p<0.01), and social support had direct effect on medication use self efficacy (0.36, p <0.01). Conclusions: Psychotic symptoms and stressful life events were the significance factors that influenced direct on social dysfunctioning. Therefore, interventions that are designed to manage these factors are crucial in order to enhance social functioning in this population.

Keywords: psychotic symptoms, methamphetamine, schizophrenia, stressful life events, social dysfunction, social support, medication use self efficacy

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Authors: Naseem Akhter, Rozina Khattak, Arshad Munir

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The Islamic social and family system is very clear concerning will, choice, consent and negation of compulsion and force in human life. Marriage is not only a civil contract but also a religious and spiritual contract between spouse (man and woman), which allows them for each other to live gladly, joyfully and legally in the society. It is an immortal and perpetual association between man and woman, which is filled with sympathetic affection, kindness, compassion and security. Islam gives specific rights to parents and guardians to set up the marriage ceremony and get done it as a respectful family occasion, confer their blessing and advice for a life partner of their children. The rights of parents and guardians are summed up in the term of "Willayah”. Islam does not permit parents, guardians and other relatives to compel their children regarding the marriage of their choice, because the groom and the bride are the real parties of the contract. Therefore, their willingness is of prime importance in order to spend whole life with each other. The Holy Prophet (peace and blessings of Allah be upon him) prohibits forcing a virgin to marriage without her permission, whether this is her father or someone else. The right of free consent to choose a life partner is the basic right for the human which is God (Allah) gifted. Unfortunately, forced marriage is a common practice in Pakistani society that has no link with Islam. This article is being written in the same context.

Keywords: choice, consent, forced marriage, Islam, parents, spouse

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Authors: Luiz Carlos Dias Lima De Oliveira

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Psychology does not have the task of being confined only to the knowledge of losses, weaknesses or diseases, because it is necessary to give analogous dedication to the investigation of human virtues, efforts and aptitudes. The reasons for living with greater constancy and expressiveness act as a protective condition for risk behaviors, but with less constancy and expressiveness they can be a viable parameter of suicidal ideation or potential suicidal initiatives. In other words, Positive Psychology scientifically studies human strengths and virtues. In the same way, we refer to the basic psychological needs of the human being, according to the Theory of Self-Determination: the need for belonging, competence and autonomy to live the best possible life or the ability to make positive decisions in life. In this sense, following the assumptions of Positive Psychology, we raise the question of what are the reasons for living, seeking a way to draw attention to positive aspects of life.

Keywords: psychology, positive, self-determination, belonging, competence, autonomy, depression, suicide.

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Authors: Dora Bianchi, Anthony Schinelli, Laura Maria Fatta, Antonia Lonigro, Fabio Lucidi, Fiorenzo Laghi

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Purpose: The role of body image in adolescent binge eating is widely confirmed, albeit the various facets of this relationship are still mostly unexplored. Within the multidimensional body image framework, this study hypothesized the indirect effects of three body image coping strategies (positive rational acceptance, appearance fixing, avoidance) in the expected relationship between the perceived impact of body image on individuals’ quality of life and binge eating symptoms. Methods: Participants were 715 adolescents aged 15-21 years (49.1% girls) recruited in Italian schools. An anonymous self-report online survey was administered. A multiple mediation model was tested. Results: A more positive perceived impact of body image on quality of life was a negative predictor of adolescents’ binge eating, controlling for individual levels of body satisfaction. Three indirect effects were found in this relationship: on one hand, the positive body image impact reduced binge eating via increasing positive rational acceptance (M1), and via reducing avoidance (M2); on the contrary, the positive body image impact also enhanced binge eating via increasing appearance fixing (M3). Conclusions: The body image impact on quality of life can be alternatively protective—when adaptive coping is solicited, and maladaptive strategies are reduced—or a risk factor, which may increase binge eating by soliciting appearance fixing.

Keywords: binge eating, body image satisfaction, quality of life, coping strategies, adolescents

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

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The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

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Authors: Stoyanka Georgieva Vladeva, Elena Kirilova Kirilova, Nikola Kirilov Kirilov

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Summary: WHO (World Health Organization) recommends the elder people a certain amount of regular physical activity in order to prevent some of the health issues. Postmenopausal osteoporosis is one of the chronic diseases which requires the maintaining of regular physical activity. The regular activity combined with an adequate medical treatment greatly improves the quality of life of the patient. Objectives: Assessment of the effect of the regular physical activity recommended by WHO on the quality of life in patients with postmenopausal osteoporosis. Material and methods: For the period of one year 68 female patients treated with Denosumab have been monitored. The bone density has been measured with the DEXA method in accordance to the T-score. No patients having any oncologic diseases and secondary osteoporosis have been included in the study. The subjects have been divided into groups by their age. The first group – women aged under 65 years (27 subjects) and the second group – women aged over 65 years (41 subjects). All patients have been advised to maintain regular physical activity included in the recommendations of the WHO in accordance with the age and the disease. The quality of life has been assessed in the beginning and at the end of the one-year period using the SF 36V2 questionnaire. Results: Only 31% of the subjects have engaged into regular increased physical activities for the whole period. Among them are mostly patients of the second group (aged over 65 years, 71%). The women from the both groups who were engaging into regular activities for this one-year period all experience an improvement of the quality of life. These results show that older patients understand the necessity of the physical activity for their health. The comparison of the output data to the scales of physical activity, durability, body pain, vitality, social activity and emotional stability has found an improvement at the end of the period in all patients. The osteodensitometry showed general improvement of the T-score. Patients with additional visits to their rheumatologist have better results. Conclusion: Combination of regular physical activity in accordance to the recommendations of WHO and medical treatment including anti-osteoporotic drugs improves the quality of life of women with postmenopausal osteoporosis.

Keywords: elderly patients, osteoporosis, physical activity, quality of life

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Authors: Abdul Rehman, Bo Liu

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Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.

Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization

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Authors: Ankur Bansal, Shashank Bishnoi

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Degradation of Sewage pipes, sewage pumping station and Sewage treatment plants(STP) is of major concern due to difficulty in their maintenance and the high cost of replacement. Most of these systems undergo degradation due to Biogenic sulphuric acid (BSA) attack. Since most of Waste water treatment system are underground, detection of this deterioration remains hidden. This paper presents a literature review, outlining the mechanism of this attack focusing on critical parameters of BSA attack, along with available models and software to predict the deterioration due to this attack. This paper critically examines the various steps and equation in various Models of BSA degradation, detail on assumptions and working of different softwares are also highlighted in this paper. The paper also focuses on the service life design technique available through various codes and method to integrate the servile life design with BSA degradation on concrete. In the end, various methods enhancing the resistance of concrete against Biogenic sulphuric acid attack are highlighted. It may be concluded that the effective modelling for degradation phenomena may bring positive economical and environmental impacts. With current computing capabilities integrated degradation models combining the various durability aspects can bring positive change for sustainable society.

Keywords: concrete degradation, modelling, service life, sulphuric acid attack

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Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

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Authors: Luana Mathias Souto

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The situation about women’s rights it’s a sensitive issue when it’s talking about human rights. More difficult its find a way to protect these rights. Aware of this problem, this article aims to analyze the women’s rights in the Brazilian context, mainly, the reproductive rights. So, to achieve this purpose, this paper through the combination of Law, philosophy, and Literature tries to rethinking why women can’t have a voice when the decisions about their rights are taken. Methodologically, it was used as an interdisciplinary bibliographical revision between Law, philosophy, and Literature. From Literature it brings the contributions from the life-narratives as an instrument to promote human rights. Besides the life-narratives theory, it’s also used the novel The Handmaid’s tale from Margaret Atwood, which became a symbol to reflect about reproductive rights. From philosophy, it’s adopted the concepts of Homo sacer and state of exception developed by the philosopher Giorgio Agamben. The contributions of these different researches fields made possible to conclude that women are Homo sacer because governments ignore their voices and opinions when they talk about abortion. The control of the human body, mainly, women bodies it’s more important than preserving some fundamental rights and because of this, it’s so difficult to preserve and promote the human rights. Based on these conclusions, it is understood that when the state is incapable or does not want to guarantee the adequate protection of human rights, it is up to society through its various means to find ways to protect them, and this is the main proposal sought by this article.

Keywords: dystopian fiction, human rights, life-narratives, state of exception

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Authors: J. Szoltysek, S. Twarog

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The happy city, as the desired effect of changes implemented by cities, involves the deliberate and purposeful evolution of material and spiritual space in which residents pursue happiness, as it is perceived collectively and individually. The quality of life (QoL) has, for many years, been researched as one of the dimensions of happiness. Both literature studies and the observation of how cities function lead to the conclusion that the happy city is the city of meetings. The importance of meeting spaces in cities for the quality of life has been confirmed also for Polish cities and, as a result, the conclusions may be drawn that public space should be planned in such a manner so as to tailor it – to the greatest possible degree – to the needs of the residents of Polish cities. The study embraced both Polish and foreign data concerning both the dimension of the quality of life in cities and the issues related to the existence of common spaces where meetings take place. Both quantitative and qualitative analytical techniques have been used to analyze and interpret the data collected. We sought the answers to the questions on the significance of the factors, identified by the respondents, which affect the QoL in a city. We identified 9 mega factors: being, work, education, recreation, health and safety, mobility, neighborhood, acceptance, agora. We established the preferences of the QoL in relation to the size of a city and the public spaces, that seem to be the cornerstone of the happy city.

Keywords: city, meetings, public spaces, social cohesion, quality of life

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Authors: K. M. Yuen

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This research examined the literature review of wedding preparation’s challenges and its developmental tasks of family transition under family life cycle. Five interviewees were invited to share their experiences on the differences with their parents in regard to wedding preparations and coping strategies. Some coping strategies and processes were highlighted for facilitating the family to achieve the developmental tasks during the wedding preparation. However, those coping strategies and processes may only act as the step and the behavior, while “concern towards parents” was found to be the essential element behind these behaviors. In addition to pre-marital counseling, a developmental group was suggested to develop under the framework of family life cycle and its related coping strategies on working with the newlyweds who encountered intergenerational differences in regard to their wedding preparations.

Keywords: wedding preparation, difference, parents, family life cycle, developmental tasks, coping strategies, process

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Pei-Yu Lee

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This study investigates the life experience and self-interpretation of female cervical cancer patients under Taiwanese cultural context. Through a Narrative Analysis Research approach, the study took six cervical cancer female patients with an average age of 58 years (ranging from 55-66 years) for an average of twice, 60 minutes each time, in-depth recorded interviews under their consent. After converting the interview recordings into transcripts, the study applied the Riessman approach to analyze the contents. The results revealed two major theme, including 1. The symbolic meaning of the cervix, and 2. Women's perseverance and compliance. Because of the illness metaphor of cervical cancer and the designation of women being family caregivers under the Chinese patriarchal culture, females with cervical cancer are not only patients but also responsible for being family and partner roles, in which contradictions of intimate relationships exist. Show the strength of perseverance and compliance in the course of life. On the other hand, they have to identify and recognize their roles in life and strive to determine the situation of coexisting with the disease to picture their life. The results showed that female cervical cancer patients not only need to combat the disease but also stand against the stigma and the traditional responsibility given to women. The researchers recommend that nurses should include cultural implications in their care of female cervical cancer patients.

Keywords: female, cervical cancer, narrative analysis research, taiwan

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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