Search results for: artificial life

Authors: Phillip Garrad, Saritha Unnikrishnan

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The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Min-Woo Kim, Ok-Kyun Na, Jun-Ho Byun, Jong-Hwan Park, Seung-Hwa Yang, Joon-Hong Park, Young-Chul Park

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This study is focused on the comparative analysis and improvement to grasp the flow characteristic of the Anti-Splash Device located under the P/V Valve and new concept design models using the CFD analysis and Artificial Neural Network. The P/V valve located upper deck to solve the pressure rising and vacuum condition of inner tank of the liquid cargo ships occurred oil outflow accident by transverse and longitudinal sloshing force. Anti-Splash Device is fitted to improve and prevent this problem in the shipbuilding industry. But the oil outflow accidents are still reported by ship owners. Thus, four types of new design model are presented by study. Then, comparative analysis is conducted with new models and existing model. Mostly the key criterion of this problem is flux in the outlet of the Anti-Splash Device. Therefore, the flow and velocity are grasped by transient analysis. And then it decided optimum model and design parameters to develop model. Later, it needs to develop an Anti-Splash Device by Flow Test to get certification and verification using experiment equipment.

Keywords: anti-splash device, P/V valve, sloshing, artificial neural network

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Authors: Nuray Turan, Maria Karanika-Murray

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In working life, positive behavior and positive mood researches has given importance more and more. Increasing research on the subject sreveals this importance. In this context, positive psychological capital (PsyCap), job crafting (JC), and creativity areamongtheprominentissues in working life. However, it is noteworthy that there is not enough research on the interaction between these three concepts. Therefore, this research has been designed. The question “Does the interaction between JC and PsyCap improve creativity in working life?” has been raised, and“JobCrafting Mediating Effect Between Positive Psychological Capital and Creativity” has been questioned. A questionnaire will be applied using PsyCap, JC and Creativity scales to find answers to the aforementioned questions. Who will be the survey participants is in the process of being determined.

Keywords: positive psychological capital, job crafting, creativity, working life

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: Mohd Sarfaraz

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The objective of this study is to investigate the work-life balance and job satisfaction among women employees in a hospital in India. It is believed that balancing a successful career with a family life or personal life can be challenging. WLB impacts on persons' satisfaction in their work and personal life roles. For this purpose, a questionnaire is developed with 22 items. The data collected from women employees who are working in a hospital in Aligarh, India. The constructs considered in this study include WLB and job satisfaction. The demographic and organisational variables considered in the study are genders, age and tenure of the job. Factors of WLB are flexible working conditions, work-life balance programs, and employee intention to change/leave a job, work pressure/stress and long working hours. This paper examines the relationship between work-family conflict, policies, and job and life satisfaction. Appropriate statistical tool using SPSS will be applied to achieve the objective. The anxiety over work-life balance is progressively becoming a common talk, especially for female employees.Increasing demands from the work and family domains represent a high strain for employees which even lead to the health problems among employees. Although it is believed that work-family role strain is more common among women employees. Therefore, the study will focus on these issues of WLB and job satisfaction among female professionals.

Keywords: work-life balance, job satisfaction, work- family conflict, health

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Authors: Fateme Hadadian, Behnam Khaledi Paveh, Hosein Feizi

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Background: High number of patients with end-stage renal disease worldwide, and Iran and the patients required hemodialysis, As well as symptoms and treatment process and its impact on quality of life The researcher had to take a step towards solving these problems. Methods: In randomized clinical trial in 60 hemodialysis patients admitted to hospital hemodialysis Imam Reza (AS) were studied. Using questionnaires dialysis patients' QOL, quality of life was measured in patients and controls were divided randomly into two groups. Benson's relaxation method for the experimental group and two months at home, once per day, respectively and the control group received no special action. Immediately after the end of the period with was used for evaluating the quality of life in both the experimental and control groups were survey and data using independent t-test were used for statistical analysis. Results: The general dimensions of quality of life scores before and after intervention, there was significant difference (P=0/001). But this difference was not significant after QOL (P=0/2). Between QOL scores before and after treatment between the two groups was statistically significant (P=0/02). Conclusion: Benson relaxation has the desired effect on quality of life in hemodialysis patients and can be used as a useful method to enhance the quality of life in hemodialysis patients, implementation and training will be given.

Keywords: hemodialysis, quality of life, Benson muscle relaxation, biomedicine

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Authors: S. Silva

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Some professions had an increased risk for occupational stress and less quality of working life. Among several professions this risk is particularly preoccupant in teachers, namely high school teachers. This study aims to characterize the work stress in teachers and understand how the work stress influences their quality of working life. One hundred teachers, 60 women and 40 men with mean age of 43,2 years (SD=7,8), from North Portugal teaching in several high schools filled in the following questionnaires: Social-Demographic Questionnaire, Teacher Stress Questionnaire and the Survey of Professional Life, during January to March 2015. The results of our study show that high school teachers have several occupational stressors (M=5) and poor perceived quality of working life. They are unsatisfied with their current job and they refer to a considerable job frustration. 33% referred to no expectations about a better future in these profession and 40% have no career development. There is a strong negative correlation between stress and teacher quality of working life (r=-.775). Moderate levels of stress are related to more favorable quality of working life (r=.632). Stress, frequent in teachers, is a significant predictor of poor quality of working life. There are several stressors affecting the teachers’ performance. Career development is not considered among this professional class and it seems related to current job frustration. Considering the role of high school teacher in the development and learning of students, these results should be taken in consideration when planning the graduation and interventions with teachers.

Keywords: career, quality of working life, stress, teachers

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Authors: Thiago Fabrizio Gavilano Farje, Marcelo Patricio Herrera Malpartida

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This study examines the influence of artificial intelligence (AI) on the work efficiency of administrative employees in the financial sector of Metropolitan Lima, Peru, during the year 2024. Focusing on the relationship between AI implementation and work efficiency, it addresses specific variables such as decision-making, motivation, and employee productivity. To accomplish the analysis between AI and work efficiency within the financial sector of Metropolitan Lima, it is necessary to evaluate how AI optimizes time in administrative tasks, examine how AI impacts the agility of the process of making decisions, and investigate the influence of AI on the satisfaction and motivation of employees. The research adopts a correlational and explanatory approach, designed to establish and understand the connections between AI and work efficiency. A survey design adapted from an OECD study is used, applying questionnaires to a representative sample of administrative workers in the financial sector who incorporate AI into their functions. The target population includes administrative workers in the financial sector of Metropolitan Lima, estimated at 73,097 employees based on data from the Censo Nacional de Empresas y Establecimientos and studies by the BCRP. The sample, selected through simple random sampling, comprises 246 workers.

Keywords: business management, artificial intelligence, decision making, labor efficiency, financial sector

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Authors: Kurt S. Candilas

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This study is a critical analysis of the work of Robert Frost, 'Nothing Gold Can Stay'. It subjects the literary piece into a qualitative analysis using the critical theory of mimesis. In effect, this study is proposed to find out and shed light on the mimetic feature of the poem’s textuality. Generally, it aims to analyze the poem’s deeper meaning in the context of the reality of life from birth to death. For the most part, this critical analysis discerns, investigates, and highlights the features which present the imitation of life in detail and from a deeper view. Based on the result of analysis, it shows that Frost has portrayed the cycle of life from birth to midst life as about proving oneself to others as far as achievements and accomplishments are concerned; secondly, at some point of one’s life, successes and achievements are just one’s perfect signature of living. As Frost discloses his poem, his message of the reality of life from birth to death is clear enough, that nothing is going to last forever.

Keywords: Nothing Gold Can Stay, mimesis, birth, death

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Leonard Kabeya Mukeba Yakasham

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The theoretical machinery from singularity theory introduced by Glolubitsky, Stewart, and Schaeffer, to study equivariant bifurcation problem is completed and expanded wile generalized to the multiparameter context. In this setting the finite deterinancy theorem or normal forms, the stability of equivariant bifurcation problem, and the structural stability of universal unfolding are discussed. With Yakam Matrix the solutions are limited for some partial differential equations stochastic nonlinear of the open questions in singularity artificial intelligence for future.

Keywords: equivariant bifurcation, symmetry singularity, equivariant jets and transversality, normal forms, universal unfolding instability, structural stability

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: Muhammad Shafiq

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In accelerated life testing approaches life time data is obtained under various conditions which are considered more severe than usual condition. Classical techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, there are two types of uncertainty in data: variation among the observations and the fuzziness. Analysis techniques, which do not consider fuzziness and are only based on precise life time observations, lead to pseudo results. This study was aimed to examine the behavior of empirical acceleration functions using fuzzy lifetimes data. The results showed an increased fuzziness in the transformed life times as compare to the input data.

Keywords: acceleration function, accelerated life testing, fuzzy number, non-precise data

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Authors: Veronica Basilio, Shuting Palomo

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This research paper explores the psychological concept of coherence and wellbeing. In particular, we focus on the relationship between individual well-being and community development. The focus setting for the research is Bali, Indonesia. The major finding of our research is: a coherent life can be achieved through living a life motivated by service to others, which contributes to community development and wellbeing. Coherence occurs when values are consistent with one’s thoughts, words, and actions. According to Antonovsky’s salutogenic theory, a sense of coherence is significant to psychological well-being. The ability to cope with life’s stressors is based on how comprehensive, manageable, and meaningful one’s sense of coherence is. The methodology for the research draws on an ethnographic approach with particular attention to participant observation and in-depth interviews within the context of village and family life in Bali. The research highlights Viktor Frankl’s ideas on self-actualization that is achieved through a life of service to others. The research also focuses on the individual’s ability to shift their perspective in the face of adversity, which contributes to individual development. Through personal transformation, one can be committed to serving others, which in the end, is the foundation of a coherent life and community development.

Keywords: psychology, bali, coherence, well-being, sociology

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Authors: Syeda Faiza Gardazi, Syed Ahsan Ali Gardazi, Ajmal Waheed

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The trend of overtime is increasing among workers due to more pressure to perform workloads, job insecurity, and financial issues. Overtime work affects the work-life balance conflict negatively as well positively. Work-life balance conflict has become an important issue as traditional work and family roles have changed. The purpose of the current research was to study the impact of overtime work on work-life balance conflict along with the moderating role of job satisfaction. For this purpose, data is collected from the employees working in different public and private sectors of Pakistan using simple random sampling technique. Descriptive statistics was used for data presentation and analysis. Correlation and regression analysis were used to test four research hypotheses proposed on the basis of research framework. The findings led to the acceptance of four hypotheses. The results show that high working hours and overtime in general lead to high work-life balance conflict. Moreover, job satisfaction moderates the relationship between overtime work and work-life balance conflict.

Keywords: family to work conflict, overtime work, work to family conflict, work-life balance conflict

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Authors: Muhammad Akram, Abdurrahman Ilgan, Oyku Ozu-Cengiz

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The quality of Work life is the general state of wellbeing of employees in the workplace. The quality of work life focuses on changing climate at work so that employees can lead improved work life. This study was designed to compare the quality of work life between Turkish and Pakistani public school teachers based on their location, gender, and marital status. A 30 items scale named The Quality of School Work Life (QSWL) was used for this study. 995 teachers from 8 Turkish provinces and 716 from four Pakistani districts were conveniently selected. The overall reliability coefficient of the scale was measured as .81. Exploratory and confirmatory factor analysis yielded five subscales of the construct. The Study revealed that Turkish and Pakistani teachers significantly differed, separately, on all the five subscales of Quality of School Work Life. However, no significant differences were found between Turkish and Pakistani teachers perspectives on the composite score of the QSWL. Further, Male, married, and Single teachers did not significantly differ on their perceptions of QSWL in both countries. However, Pakistani female teachers significantly perceived better QSWL than female teachers in Turkey. The study provided initial validity and reliability evidence of the QSWL.

Keywords: developmental opportunities, fair wages, quality of work life, Pakistan

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Authors: Syed Qasim Gilani, Muhammad Umair, Muhammad Noman, Syed Bilawal Shah, Aqib Abbasi, Muhammad Waheed

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Cardiovascular Diseases(CVD's) are the major cause of death in the world. The main reason for these deaths is the unavailability of first aid for heart failure. In many cases, patients die before reaching the hospital. We in this paper are presenting innovative online health service for Cardiac Patients. The proposed online health system has two ends. Users through device developed by us can communicate with their doctor through a mobile application. This interface provides them with first aid.Also by using this service, they have an easy interface with their doctors for attaining medical advice. According to the proposed system, we developed a device called Cardiac Care. Cardiac Care is a portable device which a patient can use at their home for monitoring heart condition. When a patient checks his/her heart condition, Electrocardiogram (ECG), Blood Pressure(BP), Temperature are sent to the central database. The severity of patients condition is checked using Artificial Intelligence Algorithm at the database. If the patient is suffering from the minor problem, our algorithm will suggest a prescription for patients. But if patient's condition is severe, patients record is sent to doctor through the mobile Android application. Doctor after reviewing patients condition suggests next step. If a doctor identifies the patient condition as critical, then the message is sent to the central database for sending an ambulance for the patient. Ambulance starts moving towards patient for bringing him/her to hospital. We have implemented this model at prototype level. This model will be life-saving for millions of people around the globe. According to this proposed model patients will be in contact with their doctors all the time.

Keywords: cardiovascular disease, classification, electrocardiogram, blood pressure

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Authors: Nihan Gurel Ulusan

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It is obvious that electrical energy, which is an inseparable part of modern day’s human and also the most important power source of our age, should be generated on a level that will suffice the nation’s requirements. The electrical energy used for a sustainable architectural design should be reduced as much as possible. Designing the buildings as energy efficient systems which aim at reducing the artificial illumination loads has been a current subject of our times as a result of concepts gaining importance like conscious consumption of energy sources, environment-friendly designs and sustainability. Reducing the consumption of electrical energy regarding the artificial lighting carries great significance, especially in the volumes which are used all day long like the educational buildings. Starting out with such an aim in this paper, the educational buildings are explored in terms of energy efficient lighting. Firstly, illumination techniques, illumination systems, light sources, luminaries, illumination controls and 'efficient energy' usage in lighting are mentioned. In addition, natural and artificial lighting systems used in educational buildings and also the spaces building up these kind buildings are examined in terms of energy efficient lighting. Lastly, the illumination properties of the school sample chosen for this study, Kağıthane Anadolu Lisesi, a typical high school in Istanbul, is observed. Suggestions are made in order to improve the system by evaluating the illumination properties of the classes with the survey carried out with the users.

Keywords: educational buildings, energy efficient, illumination techniques, lighting

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Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Alò Roberta, Bottiglione Francesco, Mantriota Giacomo

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The efficiency of the actuation system of lower limb exoskeletons and of active orthoses is a significant aspect of the design of such devices because it affects their efficacy. F-IVT is an innovative actuation system to power artificial knee joint with energy recovery capabilities. Its key and non-conventional elements are a flywheel, that acts as a mechanical energy storage system, and an Infinitely Variable Transmission (IVT). The design of the F-IVT can be optimized for a certain walking condition, resulting in a heavy reduction of both the electric energy consumption and of the electric peak power. In this work, by means of simulations of level ground walking at different speeds, it is demonstrated how F-IVT is still an advantageous actuator, even when it does not work in nominal conditions.

Keywords: active orthoses, actuators, lower extremity exoskeletons, knee joint

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Authors: Marie Oldfield

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Anthropomorphism is a technique used by humans to make sense of their surroundings. Anthropomorphism is a widely used technique used to influence consumers to purchase goods or services. These techniques can entice consumers into buying something to fulfill a gap or desire in their life, ranging from loneliness to the desire to be exclusive. By manipulating belief systems, consumer behaviour can be exploited. This paper examines a series of studies to show how anthropomorphism can be used as a basis for exploitation. The first set of studies in this paper examines how anthropomorphism is used in marketing and the effects on humans engaging with this technique. The second set of studies examines how humans can be potentially exploited by artificial agents. We then discuss the consequences of this type of activity within the context of dehumanisation. This research has found potential serious consequences for society and humanity, which indicate an urgent need for further research in this area.

Keywords: anthropomorphism, ethics, human-computer interaction, AI

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Aisha Bano, Rizwan Nazir

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The present study aimed at exploring the impact of meaning in life on psychological well-being and stress among university students. Victor Frankl's paradigm provided the theoretical foundation for this study. A sample of 560 university students was drawn from Quaid-i-Azam University Islamabad. The sample was drawn using stratified random sampling technique. Data were collected using Existence Scale, Warwick-Edinburg Mental Well-Being Scale, and Stress Scale. Results of linear regression analysis reveals that high perception of meaning in life will lead to high psychological well-being and low stress among university students. Non-significant differences are found on meaning in life variable with regard to gender in the sample using t-test. Together these results suggest that meaning in life independent of gender, is a significant predictor of the levels of stress and psychological well-being being directly related to psychological well-being and inversely related to stress levels.

Keywords: existential meaning in life, psychological well-being, stress, students

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Wisdom Robert Duruji, Moses Kanayochukwu Ifoh, Efeoghene Edward Esiemunobo

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This study examines the impact of natural and artificial disasters, lackadaisical and semantic approach in risk management, and mitigation implication for sustainable development goals in Nigeria, from 2009 to 2022. The study utilizes a range of research methods to achieve its objectives. These include literature review, website knowledge, Google search, news media information, academic journals, field-work and on-site observations. These diverse methods allow for a comprehensive analysis on the impact and the implications being study. The study finds that paradigm shift from remediating seismic, flooding, environmental pollution and degradation natural disasters by Nigeria Emergency Management Agency (NEMA), to political and charity organization; has plunged risk reduction strategies to embezzling opportunities. However, this lackadaisical and semantic approach in natural disaster mitigation, invariably replicates artificial disasters in Nigeria through: Boko Haram terrorist organization, Fulani herdsmen and farmers conflicts, political violence, kidnapping for ransom, ethnic conflicts, Religious dichotomy, insurgency, secession protagonists, unknown-gun-men, and banditry. This study also, finds that some Africans still engage in self-imposed slavery through human trafficking, by nefariously stow-away to Europe; through Libya, Sahara desert and Mediterranean sea; in search for job opportunities, due to ineptitude in governance by their leaders; a perilous journey that enhanced artificial disasters in Nigeria. That artificial disaster fatality in Nigeria increased from about 5,655 in 2009 to 114,318 in 2018; and to 157,643 in 2022. However, financial and material loss of about $9.29 billion was incurred in Nigeria due to natural disaster, while about $70.59 billion was accrued due to artificial disaster; from 2009 to 2018. Although disaster risk mitigation and politics can synergistically support sustainable development goals; however, they are different entities, and need for distinct separations in Nigeria, as in reality and perception. This study concluded that referendum should be conducted in Nigeria, to ascertain its current status as a nation. Therefore it is recommended that Nigerian governments should refine its naturally endowed crude oil locally; to end fuel subsidy scam, corruption and poverty in Nigeria!

Keywords: corruption, crude oil, environmental risk analysis, Nigeria, referendum, terrorism

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Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

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