Search results for: artificial life

Authors: Andrew Fox, Qingping Yang, Yuanhong Zhao, Tao Zhang

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Furniture is a very significant subdivision of architecture and its inherent interior design activities. The furniture industry has developed from an artisan-driven craft industry, whose forerunners saw themselves manifested in their crafts and treasured a sense of pride in the creativity of their designs, these days largely reduced to an anonymous collective mass-produced output. Although a very conservative industry, there is great potential for the implementation of collaborative digital technologies allowing a reconfigured artisan experience to be reawakened in a new and exciting form. The furniture manufacturing industry, in general, has been slow to adopt new methodologies for a design using artificial and rule-based generative design. This tardiness has meant the loss of potential to enhance its capabilities in producing sustainable, flexible, and mass customizable ‘right first-time’ designs. This paper aims to demonstrate the concept methodology for the creation of alternative and inspiring aesthetic structures for robot-based additive manufacturing (RBAM). These technologies can enable the economic creation of previously unachievable structures, which traditionally would not have been commercially economic to manufacture. The integration of these technologies with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most accomplished traditional design teams. This paper aims to address the problem by introducing generative design methodologies employing the Autodesk Fusion 360 platform. Examination of the alternative methods for its use has the potential to significantly reduce the estimated 80% contribution to environmental impact at the initial design phase. Though predominantly a design methodology, generative design combined with RBAM has the potential to leverage many lean manufacturing and quality assurance benefits, enhancing the efficiency and agility of modern furniture manufacturing. Through a case study examination of a furniture artifact, the results will be compared to a traditionally designed and manufactured product employing the Ecochain Mobius product life cycle analysis (LCA) platform. This will highlight the benefits of both generative design and robot-based additive manufacturing from an environmental impact and manufacturing efficiency standpoint. These step changes in design methodology and environmental assessment have the potential to revolutionise the design to manufacturing workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing, with the global demand for a circular economy and bespoke sustainable design at its heart.

Keywords: robot, manufacturing, generative design, sustainability, circular econonmy, product life cycle assessment, furniture

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Authors: Mandeep Saini

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The rapid advancement of Artificial Intelligence (AI) is transforming various fields, including intellectual property law. This paper explores the emerging role of AI in interpreting patent claims, a critical and highly specialized area within intellectual property rights. Patent claims define the scope of legal protection granted to an invention, and their precise interpretation is crucial in determining the boundaries of the patent holder's rights. Traditionally, this interpretation has relied heavily on the expertise of patent examiners, legal professionals, and judges. However, the increasing complexity of modern inventions, especially in fields like biotechnology, software, and electronics, poses significant challenges to human interpretation. Introducing AI into patent claim interpretation raises several legal and ethical concerns. This paper addresses critical issues such as the reliability of AI-driven interpretations, the potential for algorithmic bias, and the lack of transparency in AI decision-making processes. It considers the legal implications of relying on AI, particularly regarding accountability for errors and the potential challenges to AI interpretations in court. The paper includes a comparative study of AI-driven patent claim interpretations versus human interpretations across different jurisdictions to provide a comprehensive analysis. This comparison highlights the variations in legal standards and practices, offering insights into how AI could impact the harmonization of international patent laws. The paper proposes policy recommendations for the responsible use of AI in patent law. It suggests legal frameworks that ensure AI tools complement, rather than replace, human expertise in patent claim interpretation. These recommendations aim to balance the benefits of AI with the need for maintaining trust, transparency, and fairness in the legal process. By addressing these critical issues, this research contributes to the ongoing discourse on integrating AI into the legal field, specifically within intellectual property rights. It provides a forward-looking perspective on how AI could reshape patent law, offering both opportunities for innovation and challenges that must be carefully managed to protect the integrity of the legal system.

Keywords: artificial intelligence (ai), patent claim interpretation, intellectual property rights, algorithmic bias, natural language processing, patent law harmonization, legal ethics

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Authors: C. Han, H. Kim, S. Park

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The purpose of the present study is to analyze the effect of surface roughness on fatigue life of SCM440 steel. Two groups of specimens were made from SCM440 steel with and without surface polished after forging process and resulted in different values of surface roughness. The difference of the surface roughness between two groups was clearly distinguished even to the naked eye. Surface roughness of both groups of the specimens was quantitatively measured by a roughness measuring device, Talysurf series2 (Taylor-Hobson Co., USA). Average roughness (Ra) and maximum roughness depth (Rmax) values were obtained by scanning 45 mm with a speed of 0.25 mm/s. Fatigue tests were conducted using a three-point bending method with a cyclic sinusoidal profile of 5 Hz, stress ratio of R = 0.1 and reference life for fatigue limit of 1 × 106 cycles. Ra and Rmax without surface polished were 10.497 ± 1.721 μm and 87.936 ± 16.210 μm, respectively while those values with surface polished were much smaller (ongoing measurements). Fatigue lives of the surface-polished specimens achieved approximately 1 × 106 cycles under the maximum stress of 900 MPa, which was 10 times longer than those of the surface-untreated specimens with an average roughness of 10.082 μm. The results showed that an increase in surface roughness values led to a decrease in fatigue lives.

Keywords: surface roughness, fatigue test, fatigue life, SCM440 steel

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Authors: James V. Luisi

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Understanding consciousness requires a synthesis of ideas from multiple disciplines, including obvious ones like psychology, biology, evolution, neurology, and neuroscience, as well as less obvious ones like protozoology, botany, entomology, carcinology, herpetology, mammalogy, and computer sciences. Furthermore, to incorporate the necessary backdrop, it is best presented in a theme of Eastern philosophy, specifically leveraging the teachings of Buddhism for its relevance to early thought on consciousness. These ideas are presented as a multi-level framework that illustrates the various aspects of consciousness within a tapestry of foundational and dependent building blocks as to how living organisms evolved to understand elements of their reality sufficiently to survive, and in the case of Homo sapiens, eventually move beyond meeting the basic needs of survival, but to also achieve survival of the species beyond the eventual fate of our planet. This is not a complete system of thought, but just a framework of consciousness gathering some of the key elements regarding the evolution of consciousness and the advent of free will, and presenting them in a unique way that encourages readers to continue the dialog and thought process as an experience to enjoy long after reading the last page. Readers are encouraged to think for themselves about the issues raised herein and to question every facet presented, as much further exploration is needed. Needless to say, this subject will remain a rapidly evolving one for quite some time to come, and it is probably in the interests of everyone to at least consider attaining both an ability and willingness to participate in the dialog.

Keywords: consciousness, sentience, intelligence, artificial intelligence, Buddhism

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Authors: Fan Yang

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With the development of social economy and the popularization of quality education, the Chinese government invests more and more funding in education. Campus constructions are experiencing a great development phase. Under the trend of sustainable development, modern green campus design needs to meet new requirements of contemporary, informational and diversified education means and adapt to future education development. Educators, designers and other participants of campus design are facing new challenges. By studying and analyzing the universal unsatisfied current situations and sustainable development requirements of Chinese campuses, this paper summarizes the strategies and intentions of the whole-life-cycle campus design. In addition, a Chinese high school in Zhejiang province is added to illustrate the design cycle in an actual case. It is aimed to make all participants of campus design, especially the designers, to realize the importance of whole-life-cycle campus design and cooperate better. Sustainable campus design is expected to come true in deed instead of becoming a slogan in this way.

Keywords: campus design, green school, sustainable development, whole-life-cycle design

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Authors: Shyam, G. N. Tiwari

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Energy matrices of flate plate water collectors partially covered by PV module have been estimated in the present study. Photovoltaic thermal (PVT) water collector assembly is consisting of 5 water collectors having 2 m^2 area which are partially covered by photovoltaic module at its lower portion (inlet) and connected in series. The annual overall thermal energy and exergy are computed by using climatic data of New Delhi provided by Indian Meteorological Department (IMD) Pune, India. The Energy payback time on overall thermal and exergy basis are found to be 1.6 years and 17.8 years respectively. For 25 years of life time of system the energy production factor and life cycle conversion efficiency are estimated to be 15.8 and 0.04 respectively on overall thermal energy basis whereas for the same life time the energy production factor and life cycle conversion efficiency on exergy basis are obtained as 1.4 and 0.001.

Keywords: overall thermal energy, exergy, energy payback time, PVT water collectors

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Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

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Authors: Sevda Ddras, Fariba Mehrkhou, Remzi Atlihan, Maryam Fourouzan

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The greenhouse whitefly, Trialeurodes vaporariorum Westwood (Hemiptera: Aleyrodidae), is one of the most important pest on vegetables and ornamental host plants. In this research, the sub-lethal concentration (LC30) of thiamethoxam-lambda cyhalothrin (TLC) on the biological properties, life table parameters and population projection of T. vaporarium and its parasitoid, Encarsia formosa Gahan, were studied at controlled condition (25 ±5 ℃, R.H. 60 ±10 % and a photoperiod of 16:8 h (L:D). Bioassays were conducted by dipping tomato leaves containing third instar nymphs of the whitefly T. vaporariorum, in the obtained LC30 concentration of eforia. The life table data were analyzed using the computer program TWOSEX–MSChart based on the age-stage, two-sex life table theory. The results showed that, usage of sublethal concentration of TLC effected the biological properties and population growth parameters of greenhouse whitefly by shortening the developmentl time, adult longevity, decreasing the fecundity and population growth paramters. Also, the LC30 concentration of TLC had negative effects on life history and life table parameters of E.formosa. The obtained results illustrated that the sublethal concentration of TLC resulted in prolonging of developmental time, decreasing of adult longevity, survival rate and population growth parameters of E.formosa. Additionally, the population projection results were accordance with the population growth rate of either greenhouse whitefly or E.formosa. We conclude that, TLC should not be used in integrated pest management programs where E. formosa exists.

Keywords: greenhouse whitefly, Encarsia formosa, thiamethoxam-lambda cyhalothrin, population projection, life table parameters

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Authors: Waleed Afandi

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Artificial intelligence (AI) has rapidly transformed various sectors, including education. This paper explores the integration of AI in education, emphasizing its potential to revolutionize learning processes, enhance teaching methodologies, and personalize education. We examine the historical context of AI in education, current applications, and the potential challenges and ethical considerations associated with its implementation. By reviewing a wide range of literature, this study aims to provide a comprehensive understanding of how AI can be leveraged to improve educational outcomes and the future directions of AI-driven educational innovations. Additionally, the paper discusses the impact of AI on student engagement, teacher support, and administrative efficiency. Case studies highlighting successful AI applications in diverse educational settings are presented, showcasing the practical benefits and real-world implications. The analysis also addresses potential disparities in access to AI technologies and suggests strategies to ensure equitable implementation. Through a balanced examination of the promises and pitfalls of AI in education, this study seeks to inform educators, policymakers, and technologists about the optimal pathways for integrating AI to foster an inclusive, effective, and innovative educational environment.

Keywords: artificial intelligence, education, personalized learning, teaching methodologies, educational outcomes, AI applications, student engagement, teacher support, administrative efficiency, equity in education

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Authors: Rajkamal Kumar, Sudhir Mishra

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The connections between various elements of concrete structures play a vital role in determining the durability of structures. These connections produce discontinuities and to ensure the monolithic behavior of structures, these connections should be carefully designed. The connections between concrete layers may occur in various situations such as structure repairing and rehabilitation or construction of huge structures with cast-in-situ or pre-cast elements, etc. Bond strength at the interface of these concrete layers should be able to prevent the progressive slip from taking place and it should also ensure satisfactory performance of the structure. Different approaches to enhance the bond strength at interface have been a major area of research. Nowadays, micro-concrete is getting popular as a repair material. Under this ambit, this paper aims to present the experimental results of connections between concrete layers of different age with artificial indentation at interface with two types of repair material: Concrete with same parent concrete composition and ready-mix mortar (micro-concrete), artificial indentations (grooves and holes) were made on the old layer of concrete to increase the bond strength. Curing plays an important role in determining the bond strength. Optimum duration for curing have also been discussed for each type of repair material. Different types of failure patterns have also been mentioned.

Keywords: adhesion, cohesion, compressive stress, micro-concrete, shear stress, slant shear test

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

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The present study was aimed at developing & comparing two neural-network-based predictive models to predict shelf-life/product age of South African margarine using free fatty acid (FFA), water droplet size (D3.3), water droplet distribution (e-sigma), moisture content, peroxide value (PV), anisidine valve (AnV) and total oxidation (totox) value as input variables to the model. Brick margarine products which had varying ages ranging from fresh i.e. week 0 to week 47 were sourced. The brick margarine products which had been stored at 10 & 25 °C and were characterized. JMP and MATLAB models to predict shelf-life/ margarine age were developed and their performances were compared. The key performance indicators to evaluate the model performances were correlation coefficient (CC), root mean square error (RMSE), and mean absolute percentage error (MAPE) relative to the actual data. The MATLAB-developed model showed a better performance in all three performance indicators. The correlation coefficient of the MATLAB model was 99.86% versus 99.74% for the JMP model, the RMSE was 0.720 compared to 1.005 and the MAPE was 7.4% compared to 8.571%. The MATLAB model was selected to be the most accurate, and then, the number of hidden neurons/ nodes was optimized to develop a single predictive model. The optimized MATLAB with 10 neurons showed a better performance compared to the models with 1 & 5 hidden neurons. The developed models can be used by margarine manufacturers, food research institutions, researchers etc, to predict shelf-life/ margarine product age, optimize addition of antioxidants, extend shelf-life of products and proactively troubleshoot for problems related to changes which have an impact on shelf-life of margarine without conducting expensive trials.

Keywords: margarine shelf-life, predictive modelling, neural networks, oil oxidation

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Authors: Jacinta Ifeoma Obidile

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Teachers (vocational and technical educators inclusive) use Information and Communications Technology (ICT) for tasks outside of their normal working hours. This expansion of work duties to non-work time challenges their work-life balance. However, there has been inconsistency in the results on how these relationships correlate. This, therefore, calls for further research studies to examine the moderating mechanisms of such relationships. The present study, therefore, ascertained how vocational and technical educators’ technology acceptance relates to their work-related ICT use beyond their working hours and work-life balance, as well as how their integration affects these relationships. The population of the study comprised 320 Vocational and Technical Educators from the Southeast geopolitical zone of Nigeria. Data were collected from the respondents using the structured questionnaire. The questionnaire was validated by three experts. The reliability of the study was conducted using 20 vocational and technical educators from the South who were not part of the population. The overall reliability coefficient of 0.81 was established using Cronbach’s alpha method. The data collected was analyzed using Structural equation modeling. Findings, among others, revealed that vocational and technical educators’ work-life balance was mediated by increased digital learning environment use after work hours, although reduced by social influence.

Keywords: vocational and technical educators, digital learning environment, working hours, work-life balance, integration preference

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Authors: Yu-Yao Wang, Xiao-Meng Hu, Joanne Yeung, Xiao-Yan Li

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The high private cost and unquantified external cost limit the development of reclaimed water. In this study, an integrated framework comprising life cycle assessment (LCA), quantitative microbial risk assessment (QMRA), and life cycle costing (LCC) was developed to evaluate both costs of reclaimed water supply in water systems of various scales. LCA assesses the environmental impacts, and QMRA estimates the associated pathogenic impacts. These impacts are monetized as external costs and analyzed with the private cost by LCC to count the total life cycle cost. The framework evaluated the Hong Kong urban water system in the baseline scenario (BS) and five wastewater reuse scenarios (RS). They are RSI: substituting freshwater for toilet flushing only, RSII: substituting both freshwater and seawater for toilet flushing, RSIII: using reclaimed water for all non-potable uses, RSIV: using reclaimed water for all non-potable uses and indirect potable uses, and RSV: non-potable use and indirect potable use by conveying 100% reclaimed water to recharge the reservoirs. The results show that substituting freshwater and seawater for toilet flushing has the least total life cycle cost, exhibiting that it is the most cost-effective option for Hong Kong. Meanwhile, the evaluation results show that the external cost of each scenario is comparable to the corresponding private cost, indicating the importance of the inclusion of comprehensive external cost evaluation in private cost assessment of water systems with reclaimed water supply.

Keywords: life cycle assessment, life cycle costing, quantitative microbial risk assessment, water reclamation, reclaimed water, alternative water resources

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Authors: Anurakti Shukla, Sudhakar Srivastava

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Cyanobacteria are known for rapid growth rates, high biomass, and the ability to accumulate potentially toxic elements and contaminants. The present work was planned to develop a low-cost, feasible prototype, CyanoClean, for the growth of a cyanobacterial consortium for the removal of arsenic (As) from water. The cyanobacterial consortium consisting of Oscillatoria, Phormidiumand Gloeotrichiawas used, and the conditions for optimal growth of the consortium were standardized. A pH of 7.6, initial cyanobacterial biomass of 10 g/L, and arsenite [As(III)] and arsenate [As(V)] concentration of 400 μΜand 600 μM, respectively, were found to be suitable. The CyanoClean prototype was designed with acrylic sheet and had arrangements for optimal cyanobacterial growth in natural sunlight and also in artificial light. The As removal experiments in concentration- and duration-dependent manner demonstrated removal of up to 39-69% and 9-33% As respectively from As(III) and As(V)-contaminated water. In field testing of CyanoClean, natural As-contaminated groundwater was used, and As reduction was monitored when a flow rate of 3 L/h was maintained. In a field experiment, As concentration in groundwater was found to reduce from 102.43 μg L⁻¹ to <10 μg L⁻¹ after 6 h in natural sunlight. However, in shaded conditions under artificial light, the same result was achieved after 9 h. The CyanoClean prototype is of simple design and can be easily up-scaled for application at a small- to medium-size land and shall be affordable even for a low- to middle-income group farmer.

Keywords: cyanoclean, gloeotrichia, oscillatoria, phormidium, phycoremediation

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Authors: Binita Shah, Seema Unnikrishnan

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In the recent time, an increasing interest in the analysis and efforts to reduce the environmental impacts generated by man-made activities has been seen widely being discussed and implemented by the society. The industrial processes are expressing their concern and showing keen interest in redesigning and amending the operation process leading to better environmental performance by upgrading technologies and adjusting the financial inputs. There are various tools available for the assessment of process and production of goods on the environment. Most methods look at a particular impact on the ecosystem. Life Cycle Assessment (LCA) is one of the most widely accepted and scientifically founded methodologies to assess the overall environmental impacts of products and processes. This paper looks at the tools used in India for environmental impact assessment.

Keywords: life cycle assessment, ecological footprint, measuring sustainability, India

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Raphael Tuor, Denis Lalanne

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The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

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Authors: Fiona Lourenco, William Allen

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Dentofacial deformities are primarily surgically treated via orthognathic surgery. Health-related quality of life is concerned with aspects of quality of life that relate specifically to an individual’s health. Design and Setting: Retrospective analysis of patients who had orthognathic surgery from January 2018 - December 2022 at the trust using the previously validated Orthognathic Quality of Life questionnaire (OQoL). Materials and Methods: 32 Patient questionnaires (which included pre-operative and post-operative separate sections) were obtained via telephone survey. The data was analysed using the two-tailed paired t-test and Wilcoxon signed-rank test. Results: The change in perception post-surgery was highly significant (both tests resulted in p<0.001 for overall analysis as well as for each domain). Overall, a 74% improvement in QoL was seen following orthognathic surgery. Reports of improvement in each domain were as follows: 71% in the social aspect of the deformity domain, 76% in facial aesthetics, 60% in function, and 57% improvement in awareness of facial deformity. Conclusion: The assessment of QoL is becoming progressively imperative in clinical research. The above data shows that orthognathic surgery has a significant improvement in the QoL of patients post-operatively. The results demonstrate improvement in all domains, with perceptions in facial aesthetics seeing the highest change post-operatively.

Keywords: dentofacial, oral, facial asymmetry, orthognathic surgery, quality of life

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Muhammad Zaheer Awan, Adnan Qadir, Zeeshan Anjum

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Housefly, Musca domestica Linnaeus is ubiquitous and hazardous for Homo sapiens and livestock in sundry venerations. Musca domestica cart 100 different pathogens, such as typhoid, salmonella, bacillary dysentery, tuberculosis, anthrax and parasitic worms. The flies in rural areas usually carry more pathogens. Houseflies feed on liquid or semi-liquid substances besides solid materials which are softened by saliva. Neem botanically known as Azadirachta indica belongs to the family Meliaceae and is an indigenous tree to Pakistan. The neem tree is also one such tree which has been revered by the Pakistanis and Kashmiris for its medicinal properties. Present study showed neem seed extract has potentially toxic ability that affect Total Haemocyte Count (THC) and Differential Haemocytes Count (DHC) in insect’s blood cells, of the housefly. A significant variation in haemolymph density was observed just after application, 30 minutes and 60 minutes post treatment in term of THC and DHC in comparison with novastar. The study strappingly acclaim use of neem seed extract as insecticide as compare to artificial insecticides.

Keywords: neem, Azadirachta indica, Musca domestica, differential haemocyte count (DHC), total haemocytes count (DHC), novastar

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Louis Placido F. Lachica

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Freshman year in college, being a transition from high school to college, requires students to adjust by equipping themselves with competencies that will make them survive in college. This study conducted at in a state university in the Philippines aimed to determine the quality of school life and linguistic intelligence of 214 randomly selected college freshmen. Frequency counts and percentages were used to analyze quality of school life and linguistic intelligence. The chi-square test was utilized to determine significant relationship between quality of school life and linguistic intelligence and selected demographic variables. Results on quality of school life revealed that availability of religious books and paperbacks at home were significantly related to relationship with teachers. None of the selected demographic characteristics were significantly related to sense of achievement. Parents’ highest educational attainment was significantly related with opportunity at school. The availability of general references and song hits were significantly and highly significantly related to sense of identity which means that these promoted their sense of identity since their peers also preferred its availability. Type of high school graduated from was significantly related with students’ self-esteem. Graduates of public high schools have higher boosted self-esteem than those from private high schools. Both type of high school graduated from and reading materials available at home (religious books) had a highly significant relationship with linguistic intelligence. In addition, there was a significant relationship between time spent in reading per day and linguistic intelligence. There was a highly significant relationship between quality of school life in terms of relationship with teachers and sense of achievement with linguistic intelligence. Further, sense of identity and linguistic intelligence were significantly related.

Keywords: quality of school life, linguistic intelligence, college freshmen, state university

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Authors: Piotr Tylec, Alicja Dudek, Grzegorz Torbicz, Magdalena Mizera, Natalia Gajewska, Michael Su, Tanawat Vongsurbchart, Tomasz Stefura, Magdalena Pisarska, Mateusz Rubinkiewicz, Piotr Malczak, Piotr Major, Michal Pedziwiatr

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Introduction: Quality of life after bariatric surgery is an important factor when evaluating the final result of the treatment. Considering the vast surgical options, we tried to globally compare available methods in terms of quality of following the surgery. The aim of the study is to compare the quality of life a year after bariatric intervention using network meta-analysis methods. Material and Methods: We performed a systematic review according to PRISMA guidelines with Bayesian network meta-analysis. Inclusion criteria were: studies comparing at least two methods of weight loss treatment of which at least one is surgical, assessment of the quality of life one year after surgery by validated questionnaires. Primary outcomes were quality of life one year after bariatric procedure. The following aspects of quality of life were analyzed: physical, emotional, general health, vitality, role physical, social, mental, and bodily pain. All questionnaires were standardized and pooled to a single scale. Lifestyle intervention was considered as a referenced point. Results: An initial reference search yielded 5636 articles. 18 studies were evaluated. In comparison of total score of quality of life, we observed that laparoscopic sleeve gastrectomy (LSG) (median (M): 3.606, Credible Interval 97.5% (CrI): 1.039; 6.191), laparoscopic Roux en-Y gastric by-pass (LRYGB) (M: 4.973, CrI: 2.627; 7.317) and open Roux en-Y gastric by-pass (RYGB) (M: 9.735, CrI: 6.708; 12.760) had better results than other bariatric intervention in relation to lifestyle interventions. In the analysis of the physical aspects of quality of life, we notice better results in LSG (M: 3.348, CrI: 0.548; 6.147) and in LRYGB procedure (M: 5.070, CrI: 2.896; 7.208) than control intervention, and worst results in open RYGB (M: -9.212, CrI: -11.610; -6.844). Analyzing emotional aspects, we found better results than control intervention in LSG, in LRYGB, in open RYGB, and laparoscopic gastric plication. In general health better results were in LSG (M: 9.144, CrI: 4.704; 13.470), in LRYGB (M: 6.451, CrI: 10.240; 13.830) and in single-anastomosis gastric by-pass (M: 8.671, CrI: 1.986; 15.310), and worst results in open RYGB (M: -4.048, CrI: -7.984; -0.305). In social and vital aspects of quality of life, better results were observed in LSG and LRYGB than control intervention. We did not find any differences between bariatric interventions in physical role, mental and bodily aspects of quality of life. Conclusion: The network meta-analysis revealed that better quality of life in total score one year after bariatric interventions were after LSG, LRYGB, open RYGB. In physical and general health aspects worst quality of life was in open RYGB procedure. Other interventions did not significantly affect the quality of life after a year compared to dietary intervention.

Keywords: bariatric surgery, network meta-analysis, quality of life, one year follow-up

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Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

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In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.

Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit

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Authors: Hannah Patricia S., Louise Margarrette R., Josking Oliver L., Denisse Katrina C., Justine Kali O.

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Aims: In the Philippines, there has been an astronomical increase in the population of elderly sent to nursing home facilities which has been studied to induce despair and loss of self-worth. Nurses in institutionalized facilities generally care for the elderly. Although supportive group therapy has been explored to mend this psychological disparity, nursing research has limited published studies about this in the institutionalized setting. Hence, the study determined the effectiveness of supportive group therapy in depression, self-esteem and quality of life among institutionalized elderly. Methodology: A one-group pre-test-post-test design was conducted among 20-purposively selected institutionalized elderly after the Ethics Research Board approval. All eligible participants underwent the supportive group therapy after being subdivided into session groups. The Geriatric Depression Scale, which has a Cronbach’s alpha coefficient of 0.90; the Rosenberg Self-Esteem, which has a Cronbach’s alpha coefficient = 0.84; and the Older People Quality of Life, which has a Cronbach’s alpha coefficient =0.88, were utilized to measure depression, self-esteem, and quality of life, respectively. Descriptive statistics and Repeated Measures-Multivariate Analysis of Variance (RM-MANOVA) analyzed gathered data. Results: Results showed that the supportive group therapy significantly decreased post-test depression scores (F(1,19)=78.69,p=0.0001,partial η2=0.805), significantly improved post-test self-esteem score (F(1,19)=28.07,p=0.0001,partial η2=0.596), and significantly increased the post-test quality of life (F(1,19)=79.73,p=0.0001,partial η2=0.808) after the intervention has been rendered. Conclusion: Supportive group therapy is effective in alleviating depression and in improving self-esteem and quality of life among institutionalized elderly and can be utilized by nursing homes as an intervention to improve the over-all psychosocial status of elderly patients.

Keywords: supportive group therapy, institutionalized elderly, depression, self-esteem, quality of life

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Dike H. Ogbuagu, Etsede J. Oritsematosan

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This work investigated possible inductions of CaC₂, often misused by fruit vendors to stimulate artificial ripening, on mammalian sperm morphology and viability. Thirty isogenic strains of male albino mice, Mus musculus (age≈ 8weeks; weight= 32.5±2.0g) were acclimatized (ambient temperature 28.0±1.0°C) for 2 weeks and fed standard growers mash and water ad libutum. They were later exposed to graded toxicant concentrations (w/w) of 2.5000, 1.2500, 0.6250, and 0.3125% in 4 cages. A control cage was also established. After 5 weeks, 3 animals from each cage were sacrificed by cervical dislocation and the cauda epididymis excised. Sperm morphology and viability were determined by microscopic procedures. The ANOVA, means plots, Student’s t-test and variation plots were used to analyze data. The common abnormalities observed included Double Head, Pin Head, Knobbed Head, No Tail and With Hook. The higher toxicant concentrations induced significantly lower body weights [F(829.899) ˃ Fcrit(4.19)] and more abnormalities [F(26.52) ˃ Fcrit(4.00)] at P˂0.05. Sperm cells in the control setup were significantly more viable than those in the 0.625% (t=0.005) and 2.500% toxicant doses (t=0.018) at the 95% confidence limit. CaC₂ appeared to induced morphological abnormalities and reduced viability in sperm cells of M. musculus.

Keywords: artificial ripening, calcium carbide, fruit vendors, sperm morphology, sperm viability

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Authors: Benjamin Goldsmith, Felix Heisel

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The building industry must reduce its emissions in order to meet 2030 neutrality targets, and modular and/or offsite construction is seen as an alternative to conventional construction methods which could help achieve this goal. Modular construction has previously been shown to be less wasteful and has a lower global warming potential (GWP). While many studies have been conducted investigating the life cycle impacts of modular and conventional construction, few studies have compared different types of modular assembly and construction in order to determine which offer the greatest environmental benefits over their whole life cycle. This study seeks to investigate three different modular construction types -infill frame, core, and podium- in order to determine environmental impacts such as GWP as well as circularity indicators. The study will focus on the emissions of the production, construction, and end-of-life phases. The circularity of the various approaches will be taken into consideration in order to acknowledge the potential benefits of the ability to reuse and/or reclaim materials, products, and assemblies. The study will conduct hypothetical case studies for the three different modular construction types, and in doing so, control the parameters of location, climate, program, and client. By looking in-depth at the GWP of the beginning and end phases of various simulated modular buildings, it will be possible to make suggestions on which type of construction has the lowest global warming potential.

Keywords: modular construction, offsite construction, life cycle analysis, global warming potential, environmental impact, circular economy

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Authors: Bandana Bhattacharya

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‘Buddhism’, as such signifies the ‘ism’ that is based on Buddha’s life and teachings or that is concerned with the gospel of Buddha as recorded in the literature available in Pali, Sanskrit, Buddhist Sanskrit, Prakrit and even in the other non-Indian languages wherein it has been described a very abstruse, complex and lofty philosophy of life or ‘the way of life’ preached by Him (Buddha). It has another side too, i.e., the applicability of the tenets of Buddha according to the needs of the present society, where human life and outlook has been totally changed. Applied Buddhism signifies the applicability of the Buddha’s noble tenets. Along with the theological exposition and textual criticism of the Buddha’s discourses, it has now become almost obligatory for the Buddhist scholars to re-interpret Buddhism from modern perspectives. Basically Applied Buddhism defined a ‘way of life’ which may transform the higher quality of life or essence of life due to changed circumstances, places and time. Nowadays, if we observe the present situation of the world, we will find the current problems such as health, economic, politic, global warming, population explosion, pollution of all types including cultural scarcity essential commodities and indiscriminate use of human, natural and water resources are becoming more and more pronounced day by day, under such a backdrop of world situation. Applied Buddhism rather Buddhism may be the only instrument left now for mankind to address all such human achievements, lapses, and problems. Buddha’s doctrine is itself called ‘akālika, timeless’. On the eve of the Mahāparinibbāṇa at Kusinara, the Blessed One allows His disciples to change, modify and alter His minor teachings according to the needs of the future, although He has made some utterances, which would eternally remain fresh. Hence Buddhism has been able to occupy a prominent place in modern life, because of its timeless applicability, emanating from a set of eternal values. The logical and scientific outlook of Buddha may be traced in His very first sermon named the Dhammacakkapavattana-Sutta where He suggested to avoid the two extremes, namely, constantly attachment to sensual pleasures (Kāmasukhallikānuyoga) and devotion to self-mortification that is painful as well as unprofitable and asked to adopt Majjhimapaṭipadā, ‘Middle path’, which is very much applicable even today in every spheres of human life; and the absence of which is the root cause of all problems event at present. This paper will be a humble attempt to highlight the relevance of Buddhism in the present society.

Keywords: applied Buddhism, ecology, self-awareness, value

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