Search results for: artificial life

Authors: Chen Xi, Liu Xuebing, Lao Xuerui, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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Climate change is a global problem facing humanity and this is now the consensus of the mainstream scientific community. In accordance with the carbon peak and carbon neutral targets and visions set out in the United Nations Framework Convention on Climate Change, the Kyoto Protocol and the Paris Agreement, this project uses the City Intelligent Model (CIM) and Artificial Intelligence Machine Vision (ICR) as the core technologies to accurately quantify low carbon behaviour into green corn, which is a means of guiding ecologically sustainable living patterns. Using individual communities as management units and blockchain as a guarantee of fairness in the whole cycle of green currency circulation, the project will form a modern resident carbon track management system based on the principle of enhancing the ecological resilience of communities and the cohesiveness of community residents, ultimately forming an ecologically sustainable smart village that can be self-organised and managed.

Keywords: urban planning, urban governance, CIM, artificial Intelligence, sustainable development

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Authors: Abas Mohsenzadeh, Tariq Bashir, Waseen Tahir, Ulf Stigh, Mikael Skrifvars, Kim Bolton

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The area of artificial muscles has received significant attention from many research domains including soft robotics, biomechanics and smart textiles in recent years. Poly(vinylidene fluoride) (PVDF) has been used to form artificial muscles since it contracts upon heating when under load. In this study, PVDF fibers were produced by melt spinning technique at different solid state draw ratios and then actuation mechanism for PVDF tie molecules within the semicrystalline region of PVDF polymer has been investigated using molecular dynamics simulations. Tie molecules are polymer chains that link two (or more) crystalline regions in semicrystalline polymers. The changes in fiber length upon heating have been investigated using a novel simulation technique. The results show that conformational changes of the tie molecules from the longer all-trans conformation at low temperature (β structure) to the shorter conformation (α structure) at higher temperature accrue by increasing the temperature. These results may be applied to understand the actuation observed for PVDF upon heating.

Keywords: poly(vinylidene fluoride), molecular dynamics, simulation, actuators, tie molecules, semicrystalline

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Authors: Cindy de Frias, Erum Whyne

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Objectives: The current study examined whether the link between stress and health-related quality of life was buffered by protective factors, namely mindfulness, in a sample of middle-aged and older adults. Method: In this cross-sectional study, 134 healthy, community-dwelling adults (aged 50–85 years) were recruited from Dallas, Texas. The participants were screened for depressive symptoms and severity (using the Patient Health Questionnaire [PHQ-9]). All participants completed measures of self-reported health status (i.e., SF-36v2: mental and physical health composites), life stress (using the Elder’s Life Stress Inventory [ELSI]), and trait mindfulness (i.e., Mindful Attention Awareness Scale). Results: Hierarchical regressions (covarying for age, gender, and education) showed that life stress was inversely related to physical and mental health. Mindfulness was positively related to mental health. The negative effect of life stress on mental health was weakened for those individuals with greater trait mindfulness. Discussion: The results suggest that mindfulness is a powerful, adaptive strategy that may protect middle-aged and older adults from the well-known harmful effects of stress on healthy aging.

Keywords: health, stress, mindfulness, aging

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Varsha Pandurang Nagargoje, K. S. James

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Background: Social participation is considered as one of the central components of successful and healthy aging. This study aimed to examine the moderating role of marital status and living arrangement in the relationship between social participation and life satisfaction and other potential factors associated with life satisfaction of Indian older adults. Method: For analyses, the nationally representative study sample of 31,464 adults aged ≥60 years old was extracted from the Longitudinal Ageing Study in India (LASI) wave 1, 2017-18. Descriptive statistics and bivariate analysis have been performed to determine the proportion of life satisfaction. The first set of multivariable linear regression analyses examined Diener’s Satisfaction with Life Scale and its association with various predictor variables, including social participation, marital status, living arrangements, socio-demographic, economic, and health-related variables. Further, the second and third sets of regression investigated the moderating role of marital status and living arrangements respectively in the association of social participation and level of life satisfaction among Indian older adults. Results: Overall, the proportion of life satisfaction among older men was relatively higher than women counterparts in most background characteristics. Regression results stressed the importance of older adults’ involvement in social participation [β = 0.39, p < 0.05], being in marital union [β = 0.68, p < 0.001] and co-residential living arrangements either only with spouse [β = 1.73, p < 0.001] or with other family members [β = 2.18, p < 0.001] for the improvement of life satisfaction. Results also showed that some factors were significant for life satisfaction: in particular, increased age, having a higher level of educational status, MPCE quintile, and caste category. Higher risk of life dissatisfaction found among Indian older adults who were exposed to vulnerabilities like consuming tobacco, poor self-rated health, having difficulty in performing ADL and IADL were of major concern. The interaction effect of social participation with marital status or with living arrangements explained that currently married older individuals, and those older adults who were either co-residing with their spouse only or with other family members irrespective of their involvement in social participation remained an important modifiable factor for life satisfaction. Conclusion: It would be crucial for policymakers and practitioners to advocate social policy programs and service delivery oriented towards meaningful social connections, especially for those Indian older adults who were staying alone or currently not in the marital union to enhance their overall life satisfaction.

Keywords: Indian, older adults, social participation, life satisfaction, marital status, living arrangement

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Authors: Abdul-Monim Batiha

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Aim: The aim of this study were to correlate Jordanian cancer patients’ quality of life and fatigue with selected variables (age, sex, religion, marital status, level of education, type of cancer, number of people living in the same household, type of radiotherapy, dose of radiotherapy, and hemoglobin level). Background: Radiotherapy and chemotherapy remain devastating agents that altered patients’ normal lives. Methods: A correlational design was used in this study to 80 cancer patients and required radiotherapy treatment using a convenience sampling procedure. Results: No significant differences were found in the relationship between quality of life scores and selected variables. A significant negative relationship was found between quality of life scores and the side effects of radiotherapy treatment. Significant positive relationships were found between fatigue scores measured by Piper Fatigue Scale and cancer complications, and radiotherapy side effects. Conclusion: Cancer patients’ quality of life and fatigue are affected by radiotherapy’s side effects and cancer complications. Implications for Nursing: Nurses should try to prevent and manage the negative side effects of radiotherapy and complications of cancer. Such an initiative would serve to design specific nursing interventions that have the potential to help patients enjoy their lives and perform their activities.

Keywords: cancer patients, piper fatigue scale, fatigue, quality of life, radiotherapy

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Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

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When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: degree of coverage, deposition of liquid, nozzle, spraying

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Authors: Ji-Won Park, Jong-Wha Kim

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Triploid L. lancifolium have a wide geographic distribution. By contrast, diploid L. lancifolium have limited distributions in the islands and coastal regions of the South and West Korean Peninsula and northern Tsushima Island, Japan. L. lancifolium diploids and triploids are not sympatrically distributed with other lily species or ploidy lines in West Sea and South Sea Islands of the Korean Peninsula. This observation raises the following questions: 'Why have autotriploid L. lancifolium never been observed in those isolated islands?', 'What mechanism excludes the occurrence of autotriploids, if they arise?'. To determine the occurrence and survival of triploid plants in natural diploid populations of tiger lily (Lilium lancifolium), ploidy analysis was conducted on natural open-pollinated seeds produced from plants grown on isolated islands, and on hybrid seeds produced by artificial crossing between plant populations originating on different Korean islands. Normal seeds were classified into five grades depending on the ratio of embryo/endosperm lengths, including 5/5, 4/5, 3/5, 2/5, and 1/5. Triploids were not observed among seedlings produced from natural open pollinations on isolated islands. Triploids were detected only in seedlings of underdeveloped seed grades(3/5 and 2/5) from artificial crosses between populations from different isolated islands. The triploid occurrence frequency was calculated as 0.0 for natural open-pollinated seedlings and 0.000582 for artificial crosses(6 triploids from 10,303 seedlings). Triploids were produced from crosses between isolated populations located at least 70 km apart; no triploids were detected in inter-population crosses of plants originating on the same islands. Triploid seedlings have very low viability in soil. We analyzed factors affecting triploid occurrence and survival in natural diploid populations of L. lancifolium. The results suggest that triploids originate from fertilization between plants that are genetically isolated due to geographical isolation and/or genotypic differences.

Keywords: Lilium lancifolium, autotriploid, natural population, genetic distance, 2n female gamete

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Authors: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Multiple sclerosis is the most common chronic disease of the central nervous system associated with demyelination of neurons and several demyelinated parts of the disease encompasses throughout the white matter and affects the sensory and motor function. This study compared the effectiveness of two methods of cognitive therapy and supportive-expressive therapy on the efficacy and quality of life in MS patients. This is an experimental project which has used developed group pretest - posttest and follow-up with 3 groups. The study included all patients with multiple sclerosis in 2013 that were members of the MS Society of Iran in Tehran. The sample included 45 patients with MS that were selected volunteerily of members of the MS society of Iran and randomly divided into three groups and pretest, posttest, and follow-up (three months) for the three groups had been done.The dimensions of quality of life in patients with multiple sclerosis scale, and general self-efficiency scale of Schwarzer and Jerusalem was used for collecting data. The results showed that there was a significant difference between the mean of quality of life scores at pretest, posttest, and follow-up of the experimental groups. There was no significant difference between the mean of quality of life of the experimental groups which means that both groups were effective and had the same effect. There was no significant difference between the mean of self-efficiency scores in control and experimental group in pretest, posttest and follow-up. Thus, by using cognitive and supportive-expressive group therapy we can improve quality of life in MS patients and make great strides in their mental health.

Keywords: cognitive group therapy, life style, MS, self-efficiency, supportive-expressive group therapy

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Authors: Arne Fagerstrom, Gary Cunningham, Fredrik Hartwig

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In this paper, a theory of sustainable enterprises, sustainable enterprise theory (SET), is developed. The sustainable enterprise theory can only be a valid theory if knowledge about life and nature is complete. Knowledge limitations should not stop enterprises from doing business with a goal of better long-term life on earth. Life demands stewardship of the resources used during one’s lifetime. This paper develops a model influenced by (the classical) enterprise theory and resource theory that includes more than money in the business activities of an enterprise. The sustainable enterprise theory is then used in an analysis of accountability and in discussions about sustainable businesses.

Keywords: sustainable business, sustainability reporting, sustainable values, theory of the firm

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Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria

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Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.

Keywords: basic life support, paediatric basic life support, web-based learning, blended learning

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Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

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The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

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Authors: Jing (Claire) LI

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The topic of corporate social responsibility (CSR) is significant for pharmaceutical companies in China at this current stage. This is because, as a rapid growth industry in China in recent years, the pharmaceutical industry in China has been undergone continuous and terrible incidents relating to CSR. However, there is limited research and practice of CSR in Chinese pharmaceutical companies. Also, there is an urgent call for more research in an international context to understand the implications of corporate life cycle on CSR performance. To respond to the research need and research call, this study examines the relationship between corporate life cycle and CSR performance of Chinese listed companies in pharmaceutical industry. This research studies Chinese listed companies in pharmaceutical industry for the period of 2010-2017, where the data is available in database. Following the literature, this study divides CSR performance with regards to CSR dimensions, including shareholders, creditors, employees, customers, suppliers, the government, and the society. This study uses CSR scores of HEXUN database and financial measures of these CSR dimensions to measure the CSR performance. This study performed regression analysis to examine the relationship between corporate life cycle stages and CSR performance with regards to CSR dimensions for pharmaceutical listed companies in China. Using cash flow pattern as proxy of corporate life cycle to classify corporate life cycle stages, this study found that most (least) pharmaceutical companies in China are in maturity (decline) stage. This study found that CSR performance for most dimensions are highest (lowest) in maturity (decline) stage as well. Among these CSR dimensions, performing responsibilities for shareholder is the most important among all CSR responsibilities for pharmaceutical companies. This study is the first to provide important empirical evidence from Chinese pharmaceutical industry on the association between life cycle and CSR performance, supporting that corporate life cycle is a key factor in CSR performance. The study expands corporate life cycle and CSR literatures and has both empirical and theoretical contributions to the literature. From perspective of empirical contributions, the findings contribute to the argument that whether there is a relationship between CSR performance and various corporate life cycle stages in the literature. This study also provides empirical evidence that companies in different corporate life cycles have difference in CSR performance. From perspective of theoretical contributions, this study relates CSR and stakeholders to corporate life cycle stages and complements the corporate life cycle and CSR literature. This study has important implications for managers and policy makers. First, the results will be helpful for managers to have an understanding in the essence of CSR, and their company’s current and future CSR focus over corporate life cycle. This study provides a reference for their actions and may help them make more wise resources allocation decisions of CSR investment. Second, policy makers (in the government, stock exchanges, and securities commission) may consider corporate life cycle as an important factor in formulating future regulations for companies. Future research can explore the "process-based" differences in CSR performance and more industries.

Keywords: China, corporate life cycle, corporate social responsibility, pharmaceutical industry

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Authors: Amina Adala, Nadra Debbache, Tahar Sehili

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Coordination polymers and uniformly {[Zn(II)(BIPY)(Pht)]n} (1), {[Zn (HYD)(Pht)]n} (2) (BIPY = 4,4’ bipyridine, Pht = terephtalic acid, HYD = 8-hydroxyquinoline) have been successfully synthesized by a hydrothermal process using aqueous zinc solution. The as-prepared compounds phases were characterized by X-ray diffraction (XRD), Fourier Transform Infrared spectroscopy, UV-visible spectroscopy, thermogravimetric analysis (TGA), and the electrochemistry study by the voltammetry cyclic. The results showed a crystalline phase for CP1 however, CP2 requires recrystallization; the FTIR showed the presence of characteristic bands of all ligands; besides that, TGA shows thermal stability up to 300°C. The electrochemistry study showed a good charge transfer between the ligands and Zn metal for the two components. UV-Vis measurement showed strong absorption in a wide range from UV to visible light with a band gap of 2.69 eV for CP1 and 2.56 eV for CP2, smaller than that of ZnO. This represents an alternative to using ZnO. The Ibuprofen IBP decomposition kinetics of 5.10⁻⁵ mol.L⁻¹ under solar and artificial light were studied for different irradiation conditions. Good photocatalytic properties were observed due to their high surface area.

Keywords: metal-organic frameworks, photocatalysis, photodegradation, organic pollutant, ibuprofen

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Authors: Zuwaira Abubakar

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Islam is the Divine religion which guides Man ways of leading a prosperous life in this life and the hereafter. This study was conducted in order to investigate the possible relationship between adherence to Islamic principles of success and academic performance of university students. Accordingly, a questionnaire based on Islamized principles of success (referred to as 'Islamic character quotient inventory (ICQi)') was correlated with CGPA (Cumulative Grade Point Averages) of 343 students of Usmanu Danfodiyo University Sokoto. The empirical testing indicates that the total score on ICQi correlated positively and significantly with academic performance of the respondent. Students with either high or medium adherence have a significantly (P<0.01) higher CGPA than their counterparts with the low-adherence level. However, the result did not show a significant relationship between the CGPA of highly adherent individuals and that of those with medium adherence level. This may suggests that Islam is not for spiritual life only but also relevant and useful for our practical life.

Keywords: academic, Islam, principles, success

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Authors: Ricky Leung

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

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Authors: Pablo M. S. Vallejos

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The article aims to analyze the autobiographical practices of users on Instagram, observing the instrumentalization of image resources in the construction of visual narratives that make up that archive and digital diary. Through bibliographical review, discourse exploration and case studies, the research also aims to present a new theoretical perception about everyday records - edited with a collage of filters and aesthetic tools - that permeate that social network, understanding it as a platform fictionalizing and an expansion of life. In this way, therefore, the work reflects on possible futures in the elaboration of representations and identities in the context of digital spaces in the 21st century.

Keywords: visual culture, social media, autobiography, image

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Huang Gui

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There can be little doubt that our world is inexorably moving towards being execution-free. However, China is still on the way until now, in other words, China is still a retentionist state in the term of capital punishment but it is developing domestic criminal law toward that goal (eventual abolition of the capital punishment). The alternative sanction to capital punishment, which would be imposed on a criminal who should have been sentenced to death by law, is a substitute for execution and it should be provided with the basis of the present criminal punishment structure and with the premise of abolishing capital punishment or limiting its use. The aim of this paper, therefore, is to explore a substitute for capital punishment in China. For the criminal sanction system in China, the death penalty with suspension, naturally, is an execution, so it wouldn’t be the substitute; life sentences without parole is out of the tune with punishment policy that promoting correction and rehabilitation; life-imprisonment, which is one of the most severe punishment measure in the sanction system, should be a suitable substitute for executing but it needs to be improved, including the term of imprisonment, the commutation and parole conditions.

Keywords: alternative sanctions, capital punishment, life imprisonment, life imprisonment without parole, China

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Joud Zagzoog, Amira Aldabbagh, Radiyah Hamidaddin

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This research aims to test out and observe whether artificial intelligence (AI) software and applications could actually be effective, useful, and time-saving for those who use them. Shaguf Bites, a web application that uses AI technology, claims to help students study and memorize information more effectively in less time. The website uses smart learning, or AI-powered bite-sized repetitive learning, by transforming documents or PDFs with the help of AI into summarized interactive smart flashcards (Bites, n.d.). To properly test out the websites’ effectiveness, both qualitative and quantitative methods were used in this research. An experiment was conducted on a number of students where they were first requested to use Shaguf Bites without any prior knowledge or explanation of how to use it. Second, they were asked for feedback through a survey on how their experience was after using it and whether it was helpful, efficient, time-saving, and easy to use for studying. After reviewing the collected data, we found out that the majority of students found the website to be straightforward and easy to use. 58% of the respondents agreed that the website accurately formulated the flashcard questions. And 53% of them reported that they are most likely to use the website again in the future as well as recommend it to others. Overall, from the given results, it is clear that Shaguf Bites have proved to be very beneficial, accurate, and time saving for the majority of the students.

Keywords: artificial intelligence (AI), education, memorization, spaced repetition, flashcards.

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Authors: Horesh Reinman Netta

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Objectives: To examine the relationship between stressful life events and recurrent major depressive disorders Methods: Three groups of 50 subjects were assessed. One group had a recurrent major depressive disorder with melancholic features; the second group met the criteria for borderline personality disorder, and the third consisted of healthy controls. The Structured Clinical Interview for AXIS I DSM-IV Disorders sand the Structured Clinical Interview for AXIS II DSM-IV Disorders were used for diagnosis. The Israel Psychiatric Epidemiology Research Interview (IPERI) Life Event Scale and the Coddington Life Events Schedule (CLES) were used to measure life events which were confirmed with a confirmatory semi-structured interview. The Beck Depression Inventory and the Satisfaction from Life scales were also administered. Results : The total number of loss-related events in childhood and in the year preceding the first episode was significantly higher in the affective disorder group than in the two control groups. Total number of LE, uncontrolled and independent events were also more common in the depressed patients in the year preceding the first episode. No category of SLE was differentiated among any of the three groups during any period of time following the first depressive episode. Conclusions: SLE play an important role in the onset of affective disorders. There appear to be specific kinds of SLE occurring in childhood and in the year preceding a first episode that have particular significance. SLE may have a lesser role in the maintenance of this illness.

Keywords: modd dosorders, recurrent depression, stress, life events

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Authors: Fatemeh Roostaee, Zahra Nikmanesh

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This study was done to investigate the role of religious coping components on occupational stress and the quality of working life of midwives. The method of study was descriptive-correlation. The sample was comprised of all midwives in maternity hospitals in Zahedan during 1393. Participants were selected through applying census method. The instruments of data collection were three questionnaires: the quality of working life, occupational stress, and religious opposition. For statistical analysis, Pearson correlation and step by step regression analysis methods were used. The results showed that there is a significant negative relationship between the component of religious activities (r=-0/454) and occupational stress, and regression analysis was also shown that the variable of religious activities has been explained 45% of occupational stress variable changes. The Pearson correlation test showed that there isn't any significant relationship between religious opposition components and the quality of life. Therefore, it is necessary to present essential trainings on (the field of) strengthening compatibility strategies and religious activities to reduce occupational stress.

Keywords: the quality of working life, occupational stress, religious, midwife

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Authors: Reena Murali, David Peter S.

Abstract:

The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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Authors: Ayşe Nihan Avcı, İpek Memikoğlu

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Lighting systems in interior architecture need to be designed according to the function of the space, the type of task within the space, user comfort and needs. Desired and comfortable lighting levels increase task efficiency. When natural lighting is inadequate in a space, artificial lighting is additionally used to support the level of light. With the technological developments, the characteristics of light are being researched comprehensively and several business segments have focused on its qualitative and quantitative characteristics. These studies have increased awareness and usage of artificial lighting systems and researchers have investigated the effects of lighting on physical and psychological aspects of human in various ways. The aim of this study is to research the effects of illuminance levels of LED lighting on user visual comfort. Eighty participants from the Department of Interior Architecture of Çankaya University participated in three lighting scenarios consisting of 200 lux, 500 lux and 800 lux that are created with LED lighting. Each lighting scenario is evaluated according to six visual comfort criteria in which a reading task is performed. The results of the study indicated that LED lighting with three different illuminance levels affect visual comfort in different ways. The results are limited to the participants and questions that are attended and used in this study.

Keywords: illuminance levels, LED lighting, reading task, visual comfort criteria

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Authors: Mohammed Russedul Islam, Shah M. Muniruzzaman, M. Kamrul-Al-Masud, Syed Sadat Morshed

Abstract:

Bangladesh is one of the most climate vulnerable countries in the world. According to scientists it is predicted that temperature will raise 1-3% and precipitation 20% by 2050 in Bangladesh. Increased temperature and precipitation will deteriorate pavement structure in an accelerated rate. The study has found that pavement life will reduce significantly due to rise in temperature and precipitation in in a coastal road in Bangladesh. It will cause to increase the maintenance cost of the road. The study has found that reduction in pavement life will be caused due the decrease in stiffness and strength parameters of the pavement material due to high temperature and precipitation. It has found that use of new material costlier than the existing one will be necessary to prevent the reduction of pavement life. Eventually it will increase the re-construction cost of the road. The study has used mechanistic-empirical analysis method with a software GAMES (General analysis on multi-layered elastic systems) to find out the effect of temperature and precipitation rise on the pavement life. The study will help to guide road engineers of Bangladesh to prepare in advance to fight with the climate change effect.

Keywords: climate change, maintenance cost, mechanistic-empirical method, pavement life

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Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

Abstract:

Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Ignitia Motjolopane

Abstract:

Small and medium enterprises (SMEs) play an important role in economies by contributing to economic growth and employment. In the fourth industrial revolution, the convergence of technologies and the changing nature of work created pressures on economies globally. Generative artificial intelligence (AI) may support SMEs in exploring, exploiting, and transforming business models to align with their growth aspirations. SMEs' growth aspirations fall into four categories: subsistence, income, growth, and speculative. Subsistence-oriented firms focus on meeting basic financial obligations and show less motivation for business model innovation. SMEs focused on income, growth, and speculation are more likely to pursue business model innovation to support growth strategies. SMEs' strategic goals link to distinct business model innovation paths depending on whether SMEs are starting a new business, pursuing growth, or seeking profitability. Integrating generative artificial intelligence in start-up SME business model innovation enhances value creation, user-oriented innovation, and SMEs' ability to adapt to dynamic changes in the business environment. The existing literature may lack comprehensive frameworks and guidelines for effectively integrating generative AI in start-up reiterative business model innovation paths. This paper examines start-up business model innovation path with generative artificial intelligence. A theoretical approach is used to examine start-up-focused SME reiterative business model innovation path with generative AI. Articulating how generative AI may be used to support SMEs to systematically and cyclically build the business model covering most or all business model components and analyse and test the BM's viability throughout the process. As such, the paper explores generative AI usage in market exploration. Moreover, market exploration poses unique challenges for start-ups compared to established companies due to a lack of extensive customer data, sales history, and market knowledge. Furthermore, the paper examines the use of generative AI in developing and testing viable value propositions and business models. In addition, the paper looks into identifying and selecting partners with generative AI support. Selecting the right partners is crucial for start-ups and may significantly impact success. The paper will examine generative AI usage in choosing the right information technology, funding process, revenue model determination, and stress testing business models. Stress testing business models validate strong and weak points by applying scenarios and evaluating the robustness of individual business model components and the interrelation between components. Thus, the stress testing business model may address these uncertainties, as misalignment between an organisation and its environment has been recognised as the leading cause of company failure. Generative AI may be used to generate business model stress-testing scenarios. The paper is expected to make a theoretical and practical contribution to theory and approaches in crafting a robust business model innovation path with generative artificial intelligence in start-up SMEs.

Keywords: business models, innovation, generative AI, small medium enterprises

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