Search results for: mechanical intelligence

Authors: Ahmed Ouadah Bouakkaz, Mohamed Elmeguenni, Bel Abbes Bachir Bouiadjra, Mohamed Belhouari, Abdulmohsen Albedah

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In this study, the effect of the chemical environment on the mechanical properties of the polypropylene-talc composite was analyzed. The talc proportion was varied in order to highlight the combined effects of time of immersion in the chemical environment 'benzene' and talc concentration on the mechanical properties of the composite. Tensile test was carried out to evaluate the mechanical properties of PP-talc composite and to analyze the effect of the immersion time on the variation of these properties. The obtained results show that increasing the time of immersion has a very negative effect on the mechanical strength of the PP-talc composite, but this effect can be significantly reduced by the augmentation of the talc proportion.

Keywords: polypropylene (PP), talc, nanocomposite, degradation

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Authors: A. Mimaroglu, H. Unal

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In this study, the mechanical properties of nano filled epoxy composites were evaluated. The matrix material is epoxy. nano fillers are Al2O3, TiO2 and clay added in 2.5- 10 wt% by weight ratio. Test samples were prepared using an open mould type die. Mechanical tests were carried out. The tensile strength, elastic modulus, elongation at break and the hardness of the composite materials were obtained and evaluated. It was seen from the results that the filler content had a high influence on the level of the mechanical properties of the epoxy composites.

Keywords: nano, epoxy, composite, fillers, clay

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Authors: Rowanda Daoud Ahmed, Mansoor Abdulhak, Muhammad Azeem Afzal, Sezer Filiz, Usama Ahmad Mughal

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This paper discusses important aspects of AI in the healthcare domain. The increase of data in healthcare both in size and complexity, opens more room for artificial intelligence applications. Our focus is to review the main AI methods within the scope of the health care domain. The results of the review show that recommendations for diagnosis and recommendations for treatment, patent engagement, and administrative tasks are the key applications of AI in healthcare. Understanding the potential of AI methods in the domain of healthcare would benefit healthcare practitioners and will improve patient outcomes.

Keywords: AI in healthcare, technologies of AI, neural network, future of AI in healthcare

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Amy Gooden

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Various modes of consent have been utilized in health research, but open consent has not been explored in South Africa’s AI research context. Open consent entails the sharing of data without assurances of privacy and may be seen as an attempt to marry open science with informed consent. Because all potential uses of data are unknown, it has been questioned whether consent can be informed. Instead of trying to adapt existing modes of consent, why not adopt a new perspective? This is what open consent proposes and what this research will explore in AI health research in South Africa.

Keywords: artificial intelligence, consent, health, law, research, South Africa

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Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Ayman M. Othman, Hassan Y. Ahmed

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This paper discusses the effect of using blast furnace iron slag as a part of fine aggregate on the mechanical performance of hot mix asphalt (HMA). The mechanical performance was evaluated based on various mechanical properties that include; Marshall/stiffness, indirect tensile strength and unconfined compressive strength. The effect of iron slag content on the mechanical properties of the mixtures was also investigated. Four HMA with various iron slag contents, namely; 0%, 5%, 10% and 15% by weight of total mixture were studied. Laboratory testing has revealed an enhancement in the compressive strength of HMA when iron slag was used. Within the tested range of iron slag content, a considerable increase in the compressive strength of the mixtures was observed with the increase of slag content. No significant improvement on Marshall/stiffness and indirect tensile strength of the mixtures was observed when slag was used. Even so, blast furnace iron slag can still be used in asphalt paving for environmental advantages.

Keywords: blast furnace iron slag, compressive strength, HMA, indirect tensile strength, marshall/stiffness, mechanical performance, mechanical properties

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Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: case study, emotional intelligence, group EI, multi-method research

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Authors: Ridvan Yamanoglu, Erdinc Efendi, Ismail Daoud

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In this study, Ti-5Al-2.5Fe alloy was prepared by powder metallurgy. The elemental titanium, aluminum, and iron powders were mechanically alloyed for 10 h in a vacuum atmosphere. A stainless steel jar and stainless steel balls were used for mechanical alloying. The alloyed powders were then sintered by vacuum hot pressing at 950 °C for a soaking time of 30 minutes. Pure titanium was also sintered at the same conditions for comparison of mechanical properties and microstructural behavior. The samples were investigated by scanning electron microscopy, XRD analysis, and optical microscopy. Results showed that, after mechanical alloying, a homogeneous distribution of the elements was obtained, and desired a-b structure was determined. Ti-5Al-2.5Fe alloy was successfully produced, and the alloy showed enhanced mechanical properties compared to the commercial pure titanium.

Keywords: Ti5Al-2.5Fe, mechanical alloying, hot pressing, sintering

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Authors: Ahmed Assem Abd El Rahim

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Background: Mechanical low back pain is serious physical and social health problem. Purpose: To examine impact of shock wave therapy versus intermittent mechanical traction on mechanical LBP, and disabilities. Subjects: 60 mechanical LBP male studied cases years old 20-35 years were assigned randomly into 3 groups, Picked up from Sohag university orthopedic hospital outpatient clinic. Methods: (Study Group) A: 20 studied cases underwent shock wave therapy plus conventional physical therapy. (Study Group) B: twenty studied cases underwent intermittent mechanical traction plus conventional physical therapy. (Control Group) C: 20 patients underwent conventional physical therapy alone. Three sessions were applied weekly for four weeks. Pain was quantified using McGill Pain Questionnaire, Roland Morris Disability Questionnaire was used for measuring disability, and the ROM was evaluated by (BROM) device pre- & post-therapy. Results: Groups (A, B & C) found a reduction in pain & disability & rise in their in flexion and extension ROM after end of 4 weeks of program. Mean values of pain scale after therapy were 15.3, 9.47, and 23.07 in groups A, B, & C. mean values of Disability scale after therapy were 8.44, 4.87, 11.8in groups A, B & C. mean values of ROM of flexion were 25.53, 29.06, & 23.9 in groups A, B & C. mean values of ROM of extension were 11.73, 15.53 & 9.85 in groups A, B & C. studied cases who received intermittent mechanical traction & conventional physical therapy (group B), found reduction in pain & disability & improvement in ROM of flexion & extension value (P<0.001) after therapy program. Conclusion: Shock wave therapy and intermittent mechanical traction, as well as conventional physical treatment, can be beneficial in studied cases with mechanical LBP.

Keywords: mechanical low back pain, shock wave, mechanical, low back pain

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Authors: Viloria Marin Hermes, Paredes Santiago Maritza, Viloria Paredes Jonathan

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The aim of this study is to assess the prevalence of Burnout syndrome in a sample of 600 professors at the University of Guayaquil (Ecuador) using the Maslach Burnout Inventory (M.B.I.). In addition, assessment was made of the effects on health from professional burnout using the General Health Questionnaire (G.H.Q.-28), and the influence of Emotional Intelligence on prevention of its symptoms using the Spanish version of the Trait Meta-Mood Scale (T.M.M.S.-24). After confirmation of the underlying factor structure, the three measurement tools showed high levels of internal consistency, and specific cut-off points were proposed for the group of Latin American academics in the M.B.I. Statistical analysis showed the syndrome is present extensively, particularly on medium levels, with notably low scores given for Professional Self-Esteem. The application of Canonical Correspondence Analysis revealed that low levels of self-esteem are related to depression, with a lack of personal resources related to anxiety and insomnia, whereas the ability to perceive and control emotions and feelings improves perceptions of professional effectiveness and performance.

Keywords: burnout, academics, emotional intelligence, general health, canonical correspondence analysis

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Kiran Nair, Jincy George, Suhaib Anagreh

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Artificial intelligence (AI) in a marketing context is a form of a deterministic tool designed to optimize and enhance marketing tasks, research tools, and techniques. It is on the verge of transforming marketing roles and revolutionize the entire industry. This paper aims to explore the current dissemination of the application of artificial intelligence (AI) in the marketing mix, reviewing the scope and application of AI in various aspects of sales and distribution management. The paper also aims at identifying the areas of the strong impact of AI in factors of sales and distribution management such as distribution channel, purchase automation, customer service, merchandising automation, and shopping experiences. This is a qualitative research paper that aims to examine the impact of AI on sales and distribution management of 30 multinational brands in six different industries, namely: airline; automobile; banking and insurance; education; information technology; retail and telecom. Primary data is collected by means of interviews and questionnaires from a sample of 100 marketing managers that have been selected using convenient sampling method. The data is then analyzed using descriptive statistics, correlation analysis and multiple regression analysis. The study reveals that AI applications are extensively used in sales and distribution management, with a strong impact on various factors such as identifying new distribution channels, automation in merchandising, customer service, and purchase automation as well as sales processes. International brands have already integrated AI extensively in their day-to-day operations for better efficiency and improved market share while others are investing heavily in new AI applications for gaining competitive advantage.

Keywords: artificial intelligence, sales and distribution, marketing mix, distribution channel, customer service

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Authors: İsmail İnce

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The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Saif M. M. Obeidat

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This research investigates the impact of artificial intelligence (AI) on interior spaces within a college of Architecture and Design. Employing a qualitative approach, the study conducts in-depth interviews and reviews AI-integrated design projects within the academic setting. The key objectives include assessing AI integration in design processes, examining the influence of AI on user experience, exploring its role in architectural innovation, identifying challenges, and assessing educational implications. The study aims to provide a comprehensive understanding of AI's role in shaping interior spaces within academia. It anticipates improved efficiency in design processes, positive user feedback on functionality and experiences, the emergence of innovative design solutions, and the identification of challenges like ethical considerations and technical limitations. Additionally, the research expects insights into how educational programs may need to adapt to incorporate AI knowledge and skills, ensuring students are well-prepared for the evolving landscape of architecture and design practice. By addressing these objectives, the research contributes valuable insights into the evolving relationship between technology and the field of architecture, particularly within educational contexts.

Keywords: interior design, artificial intelligence, academic settings, technology, education

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Authors: Anand Ankush, Wani Mohammed Farooq

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A procedure based on digraph and matrix method is developed for modelling and evaluation of sustainability of Mechanical System in a concurrent engineering environment.The sustainability parameters of a Mechanical System are identified and are called sustainability attributes. Consideration of attributes and their interrelations is rudiment in modeling and evaluation of sustainability index. Sustainability attributes of a Mechanical System are modelled in termsof sustainability digraph. The graph is represented by a one-to-one matrix for sustainability expression which is based on sustainability attributes. A variable sustainability relationship permanent matrix is defined to develop sustainability expression(VPF-t) which is also useful in comparing two systems in a concurrent environment. The sustainability index of Mechanical System is obtained from permanent of matrix by substituting the numerical values of attributes and their interrelations. A higher value of index implies better sustainability of system.The ideal value of index is obtained from matrix expression which is useful in assessing relative sustainability of a Mechanical System in a concurrent engineering environment. The procedure is not only useful for evaluation of sustainability of a Mechanical System at conceptual design stage but can also be used for design and development of systems at system design stage. A step-by-step procedure for evaluation of sustainability index is also suggested and is illustrated by means of an example.

Keywords: digraph, matrix method, mechanical system, sustainability

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Authors: Thomas Rockstuhl, Soon Ang, Kok Yee Ng, Linn Van Dyne

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Intercultural interactions are often challenging and fraught with conflicts. To shed light on how to interact effectively across cultures, academics and practitioners alike have advanced a plethora of intercultural competence models. However, the majority of this work has emphasized distal outcomes, such as job performance and cultural adjustment, rather than proximal outcomes, such as how individuals resolve inevitable intercultural conflicts. As a consequence, the processes by which individuals negotiate challenging intercultural conflicts are not well understood. The current study advances theorizing on intercultural conflict resolution by exploring antecedents of how people resolve intercultural conflicts. To this end, we examine creativity – the generation of novel and useful ideas – in the context of resolving cultural conflicts in intercultural interactions. Based on the dual-identity theory of creativity, we propose that individuals with greater international experience will display greater creativity and that the relationship is accentuated by individual’s cultural intelligence. Two studies test these hypotheses. The first study comprises 84 senior university students, drawn from an international organizational behavior course. The second study replicates findings from the first study in a sample of 89 executives from eleven countries. Participants in both studies provided protocols of their strategies for resolving two intercultural conflicts, as depicted in two multimedia-vignettes of challenging intercultural work-related interactions. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded all strategies for their novelty and usefulness following scoring procedures for creativity tasks. Participants also completed online surveys of demographic background information, including their international experience, and cultural intelligence. Hierarchical linear modeling showed that surprisingly, while international experience is positively associated with usefulness, it is unrelated to novelty. Further, a person’s cultural intelligence strengthens the positive effect of international experience on usefulness and mitigates the effect of international experience on novelty. Theoretically, our findings offer an important theoretical extension to the dual-identity theory of creativity by identifying cultural intelligence as an important individual difference moderator that qualifies the relationship between international experience and creative conflict resolution. In terms of novelty, individuals higher in cultural intelligence seem less susceptible to rigidity effects of international experiences. Perhaps they are more capable of assessing which aspects of culture are relevant and apply relevant experiences when they brainstorm novel ideas. For utility, individuals high in cultural intelligence are better able to leverage on their international experience to assess the viability of their ideas because their richer and more organized cultural knowledge structure allows them to assess possible options more efficiently and accurately. In sum, our findings suggest that cultural intelligence is an important and promising intercultural competence that fosters creative resolutions to intercultural conflicts. We hope that our findings stimulate future research on creativity and conflict resolution in intercultural contexts.

Keywords: cultural Intelligence, intercultural conflict, intercultural creativity, international experience

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Authors: Moudar H. A. Zgoul, Amin Al Zamer

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Adhesive materials and adhesion have been the focal point of multiple research works related to numerous applications, particularly, aerospace, and aviation industries. To enhance the properties of conventional adhesive materials, additives have been introduced to the mix in order to enhance their mechanical and physical properties by creating a hybrid adhesive material. The evaluation of the mechanical properties of such hybrid adhesive materials is thus of an essential requirement for the purpose of properly modeling their behavior accurately. This paper presents an approach/tool to simulate the behavior such hybrid adhesives in a way that will allow researchers to better understand their behavior while in service.

Keywords: adhesive materials, analysis, hybrid adhesives, mechanical properties, simulation

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Authors: Musbah Mahfoud, Ibtisam Mustafa

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The present work highlights some of our up-to-date findings on the effect of vanadium addition on the mechanical properties and microstructure of one of the most versatile aluminum-silicon alloys, i.e., A319. In terms of microstructure, it was found that in addition to its ability to refine some of the constituent phases, vanadium also helps in retarding the formation of some of the detrimental intermetallic compounds, such as those involving Al-Fe-Si. Preliminary studies of the effect of vanadium on the mechanical properties of A319 have shown that vanadium additions up to 0.4% cause slight increase in the yield and tensile strength. However, the vanadium addition did not show a significant effect on the hardness of the alloy.

Keywords: aluminium, vanadium, intermetallic, microstructure, mechanical properties

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Authors: Mehvish Bilal, Navneet Singh, Jasir Mushtaq

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Water pollution puts people's health at risk, and it can also impact the ecology. For practitioners of integrated water resources management (IWRM), water quality modelling may be useful for informing decisions about pollution control (such as discharge permitting) or demand management (such as abstraction permitting). To comprehend the current pollutant load, movement of effective load movement of contaminants generates effective relation between pollutants, mathematical simulation, source, and water quality is regarded as one of the best estimating tools. The current study involves the Qual2k model, which includes manual simulation of the various physiochemical characteristics of water. To this end, various sensors could be installed for the automatic simulation of various physiochemical characteristics of water. An artificial intelligence model has been proposed for the automatic simulation of water quality parameters. Models of water quality have become an effective tool for identifying worldwide water contamination, as well as the ultimate fate and behavior of contaminants in the water environment. Water quality model research is primarily conducted in Europe and other industrialized countries in the first world, where theoretical underpinnings and practical research are prioritized.

Keywords: artificial intelligence, QUAL2K, simulation, physiochemical parameters

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Authors: F. Siahmed, A. Lounis, L. Faghi

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The aim of this work is to study mechanical properties of composites based on fiber natural. This material has attracted attention of the scientific community for its mechanical properties, its moderate cost and its specification as regards the protection of environment. In this study the loofah part of the family of the natural fiber has been used for these significant mechanical properties. The fiber has porous structure, which facilitates the impregnation of the resin through these pores. The matrix used in this study is the type of unsaturated polyester. This resin was chosen for its resistance to long term.The work involves: -The chemical treatment of the fibers of loofah by NaOH solution (5%) -The realization of the composite resin / fiber loofah; The preparation of samples for testing -The tensile tests and bending -The observation of facies rupture by scanning electron microscopy The results obtained allow us to observe that the values of Young's modulus and tensile strength in tension is high and open up real prospects. The improvement in mechanical properties has been obtained for the two-layer composite fiber with 7.5% (by weight).

Keywords: loofah fiber, mechanical properties, composite, loofah fiber resin

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Authors: Mahshid TalebianKiakalayeh

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As AI technologies can be used by both civilians and soldiers, it is vital to consider the consequences emanating from AI military as well as civilian use. Indeed, many of the same technologies can have a dual-use. This paper will explore the military uses of AI and assess its compliance with international legal norms. AI developments not only have changed the capacity of the military to conduct complex operations but have also increased legal concerns. The existence of a potential legal vacuum in legal principles on the military use of AI indicates the necessity of more study on compliance with International Humanitarian Law (IHL), the branch of international law which governs the conduct of hostilities. While capabilities of new means of military AI continue to advance at incredible rates, this body of law is seeking to limit the methods of warfare protecting civilian persons who are not participating in an armed conflict. Implementing AI in the military realm would result in potential issues, including ethical and legal challenges. For instance, when intelligence can perform any warfare task without any human involvement, a range of humanitarian debates will be raised as to whether this technology might distinguish between military and civilian targets or not. This is mainly because AI in fully military systems would not seem to carry legal and ethical judgment, which can interfere with IHL principles. The paper will take, as a case study, Canada’s compliance with IHL in the area of AI and the related legal issues that are likely to arise as this country continues to develop military uses of AI.

Keywords: artificial intelligence, military use, international humanitarian law, the Canadian perspective

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Alan Vaško, Juraj Belan, Lenka Hurtalová, Eva Tillová

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The aim of this study is to evaluate the influence of raw material composition on the microstructure, mechanical and fatigue properties and micromechanisms of failure of nodular cast iron. In order to evaluate the influence of charge composition, the structural analysis, mechanical and fatigue tests and micro fractographic analysis were carried out on specimens of ten melts with different charge compositions. The basic charge of individual melts was formed by a different ratio of pig iron and steel scrap and by different additive for regulation of chemical composition (silicon carbide or ferrosilicon). The results show differences in mechanical and fatigue properties, which are connected with the microstructure. SiC additive positively influences microstructure. Consequently, mechanical and fatigue properties of nodular cast iron are improved, especially in the melts with the higher ratio of steel scrap in the charge.

Keywords: nodular cast iron, silicon carbide, microstructure, mechanical properties

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Authors: Muzeyyen Balcikanli, Selma Ozaslan, Osman Sahin, Burak Uzal, Erdogan Ozbay

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In this study, the effect of nano-CaCO3 replacement with cement on the nano-mechanical properties of cement paste was investigated. Hydrophobic and hydrophilic characteristics Two types of nano CaCO3 were replaced with Portland cement at 0, 0.5 and 1%. Water to (cement+nano-CaCO3) ratio was kept constant at 0.5 for all mixtures. 36 indentations were applied on each cement paste, and the values of nano-hardness and elastic modulus of cement pastes were determined from the indentation depth-load graphs. Then, by getting the average of them, nano-hardness and elastic modulus were identified for each mixture. Test results illustrate that replacement of hydrophilic n-CaCO3 with cement lead to a significant increase in nano-mechanical properties, however, replacement of hydrophobic n-CaCO3 with cement worsened the nano-mechanical properties considerably.

Keywords: nanoindenter, CaCO3, nano-hardness, nano-mechanical properties

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Authors: Joshua Osondu

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This research explores how Artificial Intelligence (AI) can be utilized as a policy response to address teaching and learning (TL) issues in education in Ghana. The dual (AI and human) instructor model is used as a theoretical framework to examine how AI can be employed to improve teaching and learning processes and to equip learners with the necessary skills in the emerging AI society. A qualitative research design was employed to assess the impact of AI on various TL issues, such as teacher workloads, a lack of qualified educators, low academic performance, unequal access to education and educational resources, a lack of participation in learning, and poor access and participation based on gender, place of origin, and disability. The study concludes that AI can be an effective policy response to TL issues in Ghana, as it has the potential to increase students’ participation in learning, increase access to quality education, reduce teacher workloads, and provide more personalized instruction. The findings of this study are significant for filling in the gaps in AI research in Ghana and other developing countries and for motivating the government and educational institutions to implement AI in TL, as this would ensure quality, access, and participation in education and help Ghana industrialize.

Keywords: artificial intelligence, teacher, learner, students, policy response

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Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

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In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

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Authors: I. Goual, M. S. Goual, M. K. Gueddouda, Taïbi Saïd, Abou-Bekr Nabil, A. Ferhat

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This paper presents the study of hydro mechanical behavior of this optimal mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying- wetting behavior of the optimal mixture was carried out on slurry samples and compacted samples at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behavior of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

Keywords: tuff, sandy calcareous, road engineering, hydro mechanical behaviour, suction

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Authors: Paridhi Agarwal, Kusum M. George

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A cynic is someone upset about the future prematurely. In today’s highly competitive workplace, cynicism has become a prominent concern. It is a controversial issue that brings about psychological disengagement and antagonism towards the management. In organizational sciences, scientific investigation of this negative work behavior is lacking, and so there is no universal definition so far. But most commonly, Organizational Cynicism (OC) has been characterized as an unfavorable attitude towards the organization, encompassing a belief that the organization has low integrity, negative affect, and depreciative behavioral tendencies. Given its prevalence, this study aims to contribute to the existing body of knowledge on OC. This research examines the predictability of OC from two factors- Perceived Organizational Support (POS) and Emotional Intelligence (EI) among millennials in India as well as identify contradictions in today’s scenario. Standardized Organizational Cynicism Scale comprising of three components, Perceived Organizational Support Questionnaire and Goleman’s Emotional Intelligence Test are used on a convenient sample of 104 corporate sector employees in the age range 22-35 years. Correlation test elucidated the relationships, and regression analysis revealed the level of influence of the above variables on OC. Surprisingly, Emotional-Social Awareness had stronger relationships with all dimensions of OC in males as compared to females. It was also seen that EI and POS, together with predicted OC, but separately, only POS accounted for variability in OC, and this impact was much stronger for males, implying that there are other important factors that make females cynical at work. Thus, the over-emphasis on EI training for the millennial generation has also been challenged in this study. It can be said that there are avertible preconditions to the negative attitude- OC. This research has important managerial implications in areas of recruitment, training, and organizational environment.

Keywords: emotional intelligence, millennials, organizational cynicism, perceived organizational support.

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