Search results for: standardization artificial intelligence

Authors: Garg Ramneesh, Uppal Sanjeev, Mittal Rajinder, Shah Sheerin, Jain Vikas, Singla Bhupinder

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Introduction: Despite advances in trauma care, a classification system for soft tissue injuries of the face still needs to be objectively defined. Aim: To develop a classification system for soft tissue injuries of the face; that is objective, easy to remember, reproducible, universally applicable, aids in surgical management and helps to develop a structured data that can be used for future use. Material and Methods: This classification system includes those patients that need surgical management of facial injuries. Associated underlying bony fractures have been intentionally excluded. Depending upon the severity of soft tissue injury, these can be graded from 0 to IV (O-Abrasions, I-lacerations, II-Avulsion injuries with no skin loss, III-Avulsion injuries with skin loss that would need graft or flap cover, and IV-complex injuries). Anatomically, the face has been divided into three zones (Zone 1/2/3), as per aesthetic subunits. Zone 1e stands for injury of eyebrows; Zones 2 a/b/c stand for nose, upper eyelid and lower eyelid respectively; Zones 3 a/b/c stand for upper lip, lower lip and cheek respectively. Suffices R and L stand for right or left involved side, B for presence of foreign body like glass or pellets, C for extensive contamination and D for depth which can be graded as D 1/2/3 if depth is still fat, muscle or bone respectively. I is for damage to facial nerve or parotid duct. Results and conclusions: This classification system is easy to remember, clinically applicable and would help in standardization of surgical management of soft tissue injuries of face. Certain inherent limitations of this classification system are inability to classify sutured wounds, hematomas and injuries along or against Langer’s lines.

Keywords: soft tissue injuries, face, avulsion, classification

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Authors: Iris Xiaohong Quan

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The global digital health market reached 175 billion U.S. dollars in 2019, and is expected to grow at about 25% CAGR to over 650 billion USD by 2025. Different terms such as digital health, e-health, mHealth, telehealth have been used in the field, which can sometimes cause confusion. The term digital health was originally introduced to refer specifically to the use of interactive media, tools, platforms, applications, and solutions that are connected to the Internet to address health concerns of providers as well as consumers. While mHealth emphasizes the use of mobile phones in healthcare, telehealth means using technology to remotely deliver clinical health services to patients. According to FDA, “the broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.” Some researchers believe that digital health is nothing else but the cultural transformation healthcare has been going through in the 21st century because of digital health technologies that provide data to both patients and medical professionals. As digital health is burgeoning, but research in the area is still inadequate, our paper aims to clear the definition confusion and provide an overall picture of digital health companies. We further investigate how business models are designed and differentiated in the emerging digital health sector. Both quantitative and qualitative methods are adopted in the research. For the quantitative analysis, our research data came from two databases Crunchbase and CBInsights, which are well-recognized information sources for researchers, entrepreneurs, managers, and investors. We searched a few keywords in the Crunchbase database based on companies’ self-description: digital health, e-health, and telehealth. A search of “digital health” returned 941 unique results, “e-health” returned 167 companies, while “telehealth” 427. We also searched the CBInsights database for similar information. After merging and removing duplicate ones and cleaning up the database, we came up with a list of 1464 companies as digital health companies. A qualitative method will be used to complement the quantitative analysis. We will do an in-depth case analysis of three successful unicorn digital health companies to understand how business models evolve and discuss the challenges faced in this sector. Our research returned some interesting findings. For instance, we found that 86% of the digital health startups were founded in the recent decade since 2010. 75% of the digital health companies have less than 50 employees, and almost 50% with less than 10 employees. This shows that digital health companies are relatively young and small in scale. On the business model analysis, while traditional healthcare businesses emphasize the so-called “3P”—patient, physicians, and payer, digital health companies extend to “5p” by adding patents, which is the result of technology requirements (such as the development of artificial intelligence models), and platform, which is an effective value creation approach to bring the stakeholders together. Our case analysis will detail the 5p framework and contribute to the extant knowledge on business models in the healthcare industry.

Keywords: digital health, business models, entrepreneurship opportunities, healthcare

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Authors: Maria Sonto Maputle, Rhulani C. Shihundla, Rachel T. Lebese

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Background: Patients’ information must be complete and accurately documented in order to foster quality and continuity of care. The multidisciplinary health care members use patients’ documentation to communicate about health status, preventive health services, treatment, planning and delivery of care. The purpose of this study was to determine the practice of nursing documentation of patients’ information at selected Primary Health Care (PHC) facilities in Vhembe District, Limpopo Province, South Africa. Methods: The research approach adopted was qualitative while exploratory and descriptive design was used. The study was conducted at selected PHC facilities. Population included twelve professional nurses. Non-probability purposive sampling method was used to sample professional nurses who were willing to participate in the study. The criteria included participants’ whose daily work and activities, involved creating, keeping and updating nursing documentation of patients’ information. Qualitative data collection was through unstructured in-depth interviews until no new information emerged. Data were analysed through open–coding of, Tesch’s eight steps method. Results: Following data analysis, it was found that professional nurses’ had knowledge deficit related to insufficient training on updates and rendering multiple services daily had negative impact on accurate documentation of patients’ information. Conclusion: The study recommended standardization of registers, books and forms used at PHC facilities, and reorganization of PHC services into open day system.

Keywords: documentation, knowledge, patient care, patient’s information, training

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Authors: Rudolf Hela, Michala Hubertova

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The paper focuses on research of durability and lifetime of dense light-weight concrete with artificial light-weight aggregate Liapor exposed to various types of aggressive environment. Experimental part describes testing of designed concrete of various strength classes and volume weights exposed to cyclical freezing, frost and chemical de-icers and various types of chemically aggressive environment.

Keywords: aggressive environment, durability, physical-mechanical properties, light-weight concrete

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Authors: Ma. Doreen E. Candelaria, Ma. Louise Margaret A. Ramos, Dr. Jaime Y. Hernandez, Jr

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Bamboo has been introduced as a possible alternative to some construction materials nowadays. Its potential use in the field of engineering, however, is still not widely practiced due to insufficient engineering knowledge on the material’s properties and characteristics. Although there are researches and studies proving its advantages, it is still not enough to say that bamboo can sustain and provide the strength and capacity required of common structures. In line with this, a more detailed analysis was made to observe the layered structure of the bamboo, particularly the species of Kawayan Tinik. It is the main intent of this research to provide the necessary experiments to determine the tensile strength of dried bamboo samples. The test includes tensile strength parallel to fibers with samples taken at internodes only. Throughout the experiment, methods suggested by the International Organization for Standardization (ISO) were followed. The specimens were tested using 3366 INSTRON Universal Testing Machine, with a rate of loading set to 0.6 mm/min. It was then observed from the results of these experiments that dried bamboo samples recorded high layered tensile strengths, as high as 600 MPa. Likewise, along the culm’s length and across its cross section, higher tensile strength were observed at the top part and at its outer layers. Overall, the top part recorded the highest tensile strength per layer, with its outer layers having tensile strength as high as 600 MPa. The recorded tensile strength of its middle and inner layers, on the other hand, were approximately 450 MPa and 180 MPa, respectively. From this variation in tensile strength across the cross section, it may be concluded that an increase in tensile strength may be observed towards the outer periphery of the bamboo. With these preliminary investigations on the layered tensile strength of bamboo, it is highly recommended to conduct experimental investigations on the layered compressive strength properties as well. It is also suggested to conduct investigations evaluating perpendicular layered tensile strength of the material.

Keywords: bamboo strength, layered strength tests, strength test, tensile test

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Beatriz Delgado

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Although social anxiety is one of the most prevalent disorders in adolescents and causes considerable difficulties and social distress in those with the disorder, to date very few studies have explored the impact of social anxiety on academic adjustment in student populations. The aim of this study was analyze the effect of social anxiety on school functioning in Secondary Education. Specifically, we examined the relationship between social anxiety and self-concept, academic goals, causal attributions, intellectual aptitudes, and learning strategies, personality traits, and academic performance, with the purpose of creating a causal-explanatory model of academic performance. The sample consisted of 2,022 students in the seven to ten grades of Compulsory Secondary Education in Spain (M = 13.18; SD = 1.35; 51.1% boys). We found that: (a) social anxiety has a direct positive effect on internal attributional style, and a direct negative effect on self-concept. Social anxiety also has an indirect negative effect on internal causal attributions; (b) prior performance (first academic trimester) exerts a direct positive effect on intelligence, achievement goals, academic self-concept, and final academic performance (third academic trimester), and a direct negative effect on internal causal attributions. It also has an indirect positive effect on causal attributions (internal and external), learning goals, achievement goals, and study strategies; (c) intelligence has a direct positive effect on learning goals and academic performance (third academic trimester); (d) academic self-concept has a direct positive effect on internal and external attributional style. Also, has an indirect effect on learning goals, achievement goals, and learning strategies; (e) internal attributional style has a direct positive effect on learning strategies and learning goals. Has a positive but indirect effect on achievement goals and learning strategies; (f) external attributional style has a direct negative effect on learning strategies and learning goals and a direct positive effect on internal causal attributions; (g) learning goals have direct positive effect on learning strategies and achievement goals. The structural equation model fit the data well (CFI = .91; RMSEA = .04), explaining 93.8% of the variance in academic performance. Finally, we emphasize that the new causal-explanatory model proposed in the present study represents a significant contribution in that it includes social anxiety as an explanatory variable of cognitive-motivational constructs.

Keywords: academic performance, adolescence, cognitive-motivational variables, social anxiety

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Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

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AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

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Authors: Ayush Satija, Ritu Raj

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Escalating demand for elevated structures as a remedy for traffic congestion has led to a surge in the construction of viaducts and bridges predominantly employing prestressed beams. However, post-tensioned I-girder superstructures are gaining traction for their attributes like structural efficiency, cost-effectiveness, and easy construction. Recently, Ultra-high-performance fiber-reinforced concrete (UHPFRC) has emerged as a revolutionary material in reshaping conventional infrastructure engineering. UHPFRC offers exceptional properties including high compressive and tensile strength, alongside enhanced durability. Its adoption in bridges yields benefits, notably a remarkable strength-to-weight ratio enabling the design of lighter and slender structural elements, enhancing functionality and sustainability. Despite its myriad advantages, integration of UHPFRC in construction is still evolving, hindered by factors like cost, material availability, and design standardization. Consequently, there's a need to assess the feasibility of substituting ordinary concrete (OC) with UHPFRC in bridges, focusing on economic considerations. This research undertakes an efficacy study between post-tensioned I-girders fabricated from UHPFRC and OC, evaluating cost parameters associated with concrete production, reinforcement, and erection. The study reveals that UHPFRC becomes economically viable for spans exceeding 40.0m. This shift in cost-effectiveness is attributed to factors like reduced girder depth, elimination of un-tensioned steel, diminished need for shear reinforcement and decreased erection costs.

Keywords: post tensioned I girder, superstructure, ultra-high-performance fiber reinforced concrete, ordinary concrete

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Authors: José Manuel Palma, Paula Pereira, Margarida Tomás

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Foreseen the future: Human factors integration in European Horizon Projects The development of new technology as artificial intelligence, smart sensing, robotics, cobotics or intelligent machinery must integrate human factors to address the need to optimize systems and processes, thereby contributing to the creation of a safe and accident-free work environment. Human Factors Integration (HFI) consistently pose a challenge for organizations when applied to daily operations. AGILEHAND and FORTIS projects are grounded in the development of cutting-edge technology - industry 4.0 and 5.0. AGILEHAND aims to create advanced technologies for autonomously sort, handle, and package soft and deformable products, whereas FORTIS focuses on developing a comprehensive Human-Robot Interaction (HRI) solution. Both projects employ different approaches to explore HFI. AGILEHAND is mainly empirical, involving a comparison between the current and future work conditions reality, coupled with an understanding of best practices and the enhancement of safety aspects, primarily through management. FORTIS applies HFI throughout the project, developing a human-centric approach that includes understanding human behavior, perceiving activities, and facilitating contextual human-robot information exchange. it intervention is holistic, merging technology with the physical and social contexts, based on a total safety culture model. In AGILEHAND we will identify safety emergent risks, challenges, their causes and how to overcome them by resorting to interviews, questionnaires, literature review and case studies. Findings and results will be presented in “Strategies for Workers’ Skills Development, Health and Safety, Communication and Engagement” Handbook. The FORTIS project will implement continuous monitoring and guidance of activities, with a critical focus on early detection and elimination (or mitigation) of risks associated with the new technology, as well as guidance to adhere correctly with European Union safety and privacy regulations, ensuring HFI, thereby contributing to an optimized safe work environment. To achieve this, we will embed safety by design, and apply questionnaires, perform site visits, provide risk assessments, and closely track progress while suggesting and recommending best practices. The outcomes of these measures will be compiled in the project deliverable titled “Human Safety and Privacy Measures”. These projects received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND) and No 101135707 (FORTIS).

Keywords: human factors integration, automation, digitalization, human robot interaction, industry 4.0 and 5.0

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Authors: Masoud Ghaemi, MohammadJafar Hedayati, Faezeh Yousefzadeh, Hoseinali Heydarzadeh

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According to the statistics of the International Committee on Large Dams, internal erosion and piping (scour) are major causes of the destruction of earth-fill dams. If such dams are constructed in narrow valleys, the valley walls will increase the arching of the dam body due to the transfer of vertical and horizontal stresses, so the occurrence of hydraulic fracturing in these embankments is more likely. Roudbar Dam in Lorestan is a clay-core pebble earth-fill dam constructed in a relatively narrow valley in western Iran. Three years after the onset of impoundment, there has been a fall in dam behavior. Evaluation of the dam behavior based on the data recorded on the instruments installed inside the dam body and foundation confirms the occurrence of internal erosion in the lower and adjacent parts of the core on the left support (abutment). The phenomenon of hydraulic fracturing is one of the main causes of the onset of internal erosion in this dam. Accordingly, the main objective of this paper is to evaluate the validity of this hypothesis. To evaluate the validity of this hypothesis, the dam behavior during construction and impoundment has been first simulated with a three-dimensional numerical model. Then, using validated empirical equations, the safety factor of the occurrence of hydraulic fracturing phenomenon upstream of the dam score was calculated. Then, using the artificial neural network, the failure time of the given section was predicted based on the maximum stress trend created. The study results show that steep slopes of valley walls, sudden changes in coefficient, and differences in compressibility properties of dam body materials have caused considerable stress transfer from core to adjacent valley walls, especially at its lower levels. This has resulted in the coefficient of confidence of the occurrence of hydraulic fracturing in each of these areas being close to one in each of the empirical equations used.

Keywords: arching, artificial neural network, FLAC3D, hydraulic fracturing, internal erosion, pore water pressure

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Authors: K. Almi, S. Lakel, A. Benchabane, A. Kriker

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The fiber–matrix compatibility can be improved if suitable enforcements are chosen. Whenever the reinforcements have more thermal stability, they can resist to the main processes for wood–thermoplastic composites. Several researches are focused on natural resources for the production of biomaterials intended for technical applications. Date palm wood present one of the world’s most important natural resource. Its use as insulating materials will help to solve the severe environmental and recycling problems which other artificial insulating materials caused. This paper reports the results of an experimental investigation on the thermal proprieties of date palm wood from Algeria. A study of physical, chemical and mechanical properties is also carried out. The goal is to use this natural material in the manufacture of thermal insulation materials for buildings. The local natural resources used in this study are the date palm fibers from Biskra oasis in Algeria. The results have shown that there is no significant difference in the morphological proprieties of the four types of residues. Their chemical composition differed slightly; with the lowest amounts of cellulose and lignin content belong to Petiole. Water absorption study proved that Rachis has a low value of sorption whereas Petiole and Fibrillium have a high value of sorption what influenced their mechanical properties. It is seen that the Rachis and leaflets exhibit a high tensile strength values compared to the other residue. On the other hand the low value of bulk density of Petiole and Fibrillium leads to high value of specific tensile strength and young modulus. It was found that the specific young modulus of Petiole and Fibrillium was higher than that of Rachis and Leaflets and that of other natural fibers or even artificial fibers. Compared to the other materials date palm wood provide a good thermal proprieties thus, date palm wood will be a good candidate for the manufacturing efficient and safe insulating materials.

Keywords: composite materials, date palm fiber, natural fibers, tensile tests, thermal proprieties

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Authors: Amber Shahi, Ayesha Tazeen, Abdus Samad, Shama Parveen

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Nanoparticles (NPs) are tiny particles. According to the International Organization for Standardization, the size range of NPs is in the nanometer range (1-100 nm). They show distinct properties that are not shown by larger particles of the same material. NPs are currently being used in different fields due to their unique physicochemical nature. NPs are a boon for medical sciences, environmental sciences, electronics, and textile industries. However, there is growing concern about their potential adverse effects on human health. This poster presents a comprehensive review of the current literature on the pros and cons of NPs on human health. The poster will discuss the various types of interactions of NPs with biological systems. There are a number of beneficial uses of NPs in the field of health and environmental welfare. NPs are very useful in disease diagnosis, antimicrobial action, and the treatment of diseases like Alzheimer’s. They can also cross the blood-brain barrier, making them capable of treating brain diseases. Additionally, NPs can target specific tumors and be used for cancer treatment. To treat environmental health, NPs also act as catalytic converters to reduce pollution from the environment. On the other hand, NPs also have some negative impacts on the human body, such as being cytotoxic and genotoxic. They can also affect the reproductive system, such as the testis and ovary, and sexual behavior. The poster will further discuss the routes of exposure of NPs. The poster will conclude with a discussion of the current regulations and guidelines on the use of NPs in various applications. It will highlight the need for further research and the development of standardized toxicity testing methods to ensure the safe use of NPs in various applications. When using NPs in diagnosis and treatment, we should also take into consideration their safe concentration in the body. Overall, this poster aims to provide a comprehensive overview of the pros and cons of NPs on human health and to promote awareness and understanding of the potential risks and benefits associated with their use.

Keywords: disease diagnosis, human health, nanoparticles, toxicity testing

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Authors: Florina Dutt, Subhajit Das, Matthew Swartz

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Lighting design and its impact on indoor comfort conditions are an integral part of good interior design. Impact of lighting in an interior space is manifold and it involves many sub components like glare, color, tone, luminance, control, energy efficiency, flexibility etc. While other components have been researched and discussed multiple times, this paper discusses the research done to understand the glare component from an artificial lighting source in an indoor space. Consequently, the paper discusses a parametric model to convey real time glare level in an interior space to the designer/ architect. Our end users are architects and likewise for them it is of utmost importance to know what impression the proposed lighting arrangement and proposed furniture layout will have on indoor comfort quality. This involves specially those furniture elements (or surfaces) which strongly reflect light around the space. Essentially, the designer needs to know the ramification of the ‘discomfortable glare’ at the early stage of design cycle, when he still can afford to make changes to his proposed design and consider different routes of solution for his client. Unfortunately, most of the lighting analysis tools that are present, offer rigorous computation and analysis on the back end eventually making it challenging for the designer to analyze and know the glare from interior light quickly. Moreover, many of them do not focus on glare aspect of the artificial light. That is why, in this paper, we explain a novel approach to approximate interior glare data. Adding to that we visualize this data in a color coded format, expressing the implications of their proposed interior design layout. We focus on making this analysis process very fluid and fast computationally, enabling complete user interaction with the capability to vary different ranges of user inputs adding more degrees of freedom for the user. We test our proposed parametric model on a case study, a Computer Lab space in our college facility.

Keywords: computational geometry, glare impact in interior space, info visualization, parametric lighting analysis

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Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

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Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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Authors: Tomokazu Shirai, Akihiko Kondo

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Technologies of metabolic engineering or synthetic biology are essential for effective microbial bioproduction. It is especially important to develop an in silico tool for designing a metabolic pathway producing an unnatural and valuable chemical such as fossil materials of fuel or plastics. We here demonstrated two in silico tools for designing novel metabolic pathways: BioProV and HyMeP. Furthermore, we succeeded in creating an artificial metabolic pathway by enzyme engineering.

Keywords: bioinformatics, metabolic engineering, synthetic biology, genome scale model

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Diane Ghanem, Whitney Kagabo, Rebecca Engels, Uma Srikumaran, Babar Shafiq

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Hospitalist co-management of orthopaedic surgery patients is a growing trend across the country. It was created as a collaborative effort to provide overarching care to patients with the goal of improving their postoperative care and decreasing in-hospital medical complications. The aim of this project is to provide a guide for implementing and optimizing a hospitalist co-management service in orthopaedic surgery. Key leaders from the hospitalist team, orthopaedic team and quality, safety and service team were identified. Multiple meetings were convened to discuss the comanagement service and determine the necessary building blocks behind an efficient and well-designed co-management framework. After meticulous deliberation, a consensus was reached on the final service agreement and a written guide was drafted. Fundamental features of the service include the identification of service stakeholders and leaders, frequent consensus meetings, a well-defined framework, with goals, program metrics and unified commands, and a regular satisfaction assessment to update and improve the program. Identified pearls for co-managing orthopaedic surgery patients are standardization, timing, adequate patient selection, and two-way feedback between hospitalists and orthopaedic surgeons to optimize the protocols. Developing a service agreement is a constant work in progress, with meetings, discussions, revisions, and multiple piloting attempts before implementation. It is a partnership created to provide hospitals with a streamlined admission process where at-risk patients are identified early, and patient care is optimized regardless of the number or nature of medical comorbidities. A wellestablished hospitalist co-management service can increase patient care quality and safety, as well as health care value.

Keywords: co-management, hospitalist co-management, implementation, orthopaedic surgery, quality improvement

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Julio Jesus Salazar, Julio Jesus De Lama

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the fundamental objective of hydrological studies applied to the engineering field is to determine the statistically consistent volumes or water flows that, in each case, allow us to size or design a series of elements or structures to effectively manage and develop a river basin. To determine these values, there are several ways of working within the framework of traditional hydrology: (1) Study each of the factors that influence the hydrological cycle, (2) Study the historical behavior of the hydrology of the area, (3) Study the historical behavior of hydrologically similar zones, and (4) Other studies (rain simulators or experimental basins). Of course, this range of studies in a certain basin is very varied and complex and presents the difficulty of collecting the data in real time. In this complex space, the study of variables can only be overcome by collecting and transmitting data to decision centers through the Internet of things and artificial intelligence. Thus, this research work implemented the learning project of the sub-basin of the Shullcas river in the Andean basin of the Mantaro river in Peru. The sensor firmware to collect and communicate hydrological parameter data was programmed and tested in similar basins of the European Union. The Machine Learning applications was programmed to choose the algorithms that direct the best solution to the determination of the rainfall-runoff relationship captured in the different polygons of the sub-basin. Tests were carried out in the mountains of Europe, and in the sub-basins of the Shullcas river (Huancayo) and the Yauli river (Jauja) with heights close to 5000 m.a.s.l., giving the following conclusions: to guarantee a correct communication, the distance between devices should not pass the 15 km. It is advisable to minimize the energy consumption of the devices and avoid collisions between packages, the distances oscillate between 5 and 10 km, in this way the transmission power can be reduced and a higher bitrate can be used. In case the communication elements of the devices of the network (internet of things) installed in the basin do not have good visibility between them, the distance should be reduced to the range of 1-3 km. The energy efficiency of the Atmel microcontrollers present in Arduino is not adequate to meet the requirements of system autonomy. To increase the autonomy of the system, it is recommended to use low consumption systems, such as the Ashton Raggatt McDougall or ARM Cortex L (Ultra Low Power) microcontrollers or even the Cortex M; and high-performance direct current (DC) to direct current (DC) converters. The Machine Learning System has initiated the learning of the Shullcas system to generate the best hydrology of the sub-basin. This will improve as machine learning and the data entered in the big data coincide every second. This will provide services to each of the applications of the complex system to return the best data of determined flows.

Keywords: hydrology, internet of things, machine learning, river basin

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Authors: Ana Luiza Da Gama E Souza

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This article aims to discuss the problem of food insecurity in Brazil in what it refers to contamination of food by chemical substances such as herbicides, pesticides, and other contaminants. The issue will be faced by analyzing, on the one hand, the standards that guide the food system in the world and, on the other hand, human rights indicators whose purpose is to provide an effective monitoring of the State's obligations to guarantee food security, analyzing the implications of the former for the success of the latter. The methodology adopted in this article was bibliographic-documentary and consists of three moments of analysis. The first moment consists in the analysis of the reports of the Commission on Human Rights of the Organization of American States to identify the set of progress indicators developed by the Commission. This analysis will involve the new methodology used to evaluate the efficiency in monitoring food security in Brazil the case of using pesticides in the production of food at levels of toxicity not admitted by the inspection bodies. The second moment consists in evaluating the mechanism for monitoring food security in Brazil, which was initially established by the National Food Security Plan (PLANSAN) for 2012-2015 and improved by the II National Food Security Plan for 2016-2019. Those mechanisms were prepared by the Chamber (CAISAN), and have the function to compare the monitoring proposals with the results presented by CAISAN on the Indicators and Results Report of the National Plan for Food and Nutrition Security 2012-2015. The third moment was intended to understand, analyze and evaluate the standardization process of the agri-food system, especially regarding the level of toxicity standards, that is related to food safety monitoring as a guarantee of pesticide-free food. The results show the dependence between private standards of toxicity and the indicators of food safety that leads to inefficiency on monitoring that mechanism in Brazil.

Keywords: standards, indicators, human rights, food security

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Authors: Justin Byrne, Jose Ramon Cobo

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The growing importance of cross- or intercultural competencies (used here interchangeably) for the business and management professionals is now a commonplace in both academic and professional literature. This reflects two parallel developments. On the one hand, it is a consequence of the increased attention paid to a whole range of 'soft skills', now seen as fundamental in both individuals' and corporate success. On the other hand, and more specifically, the increasing demand for interculturally competent professionals is a corollary of ongoing processes of globalization, which multiply and intensify encounters between individuals and companies from different cultural backgrounds. Business schools have, for some decades, responded to the needs of the job market and their own students by providing students with training in intercultural skills, as they are encouraged to do so by the major accreditation agencies on both sides of the Atlantic. Adapting Early and Ang's (2003) formulation of Cultural Intelligence (CQ), this paper aims to help fill the lagunae in the current literature on intercultural training in three main ways. First, it offers an in-depth analysis of the CQ of a little studied group: contemporary Millenial and 'Generation Z' Business School students. The level of analysis distinguishes between the four different dimensions of CQ, cognition, metacognition, motivation and behaviour, and thereby provides a detailed picture of the strengths and weaknesses in CQ of the group as a whole, as well as of different sub-groups and profiles of students. Secondly, by crossing these individual-level findings with respondents' socio-cultural and educational data, this paper also proposes and tests hypotheses regarding the relative impact and importance of four possible antecedents of intercultural skills identified in the literature: prior international experience; intercultural training, foreign language proficiency, and experience of cultural diversity in habitual country of residence. Third, we use this analysis to suggest data-based intercultural training priorities for today's management students. These conclusions are based on the statistical analysis of individual responses of some 300 Bachelor or Masters students in a major European Business School provided to two on-line surveys: Ang, Van Dyne, et al's (2007) standard 20-question self-reporting CQ Scale, and an original questionnaire designed by the authors to collate information on respondent's socio-demographic and educational profile relevant to our four hypotheses and explanatory variables. The data from both instruments was crossed in both descriptive statistical analysis and regression analysis. This research shows that there is no statistically significant and positive relationship between the four antecedents analyzed and overall CQ level. The exception in this respect is the statistically significant correlation between international experience, and the cognitive dimension of CQ. In contrast, the results show that the combination of international experience and foreign language skills acting together, does have a strong overall impact on CQ levels. These results suggest that selecting and/or training students with strong foreign language skills and providing them with international experience (through multinational programmes, academic exchanges or international internships) constitutes one effective way of training culturally intelligent managers of tomorrow.

Keywords: business school, cultural intelligence, millennial, training

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Authors: Obadiah Nwabueze

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Bodija market is classified as Central Business District (CBD) of Ibadan North Local Government Area of Oyo State (Nigeria) because of socio economic activities, so Crime is a peculiar social issue that causes insecurity. The law enforcement agencies tasked with crime prevention and control such as the Nigerian Police have insufficient manpower, and a resultant effect is the emergence of Vigilante groups as citizen’s response to crime control and prevention (self-help). The research design adopted for this study is a case study design exploring Vigilante activities in Bodija Market. The study utilizes both quantitative and qualitative approach, sources of data includes primary and secondary sources. A sample of 127 respondents randomly picked from the 4 sections of Bodija Market through questionnaire, comprising of 50 male and 77 females which alienates issues of gender bias in addition to the 4 in-depth interview, making a total of 131 respondents. Statistical package for Social Sciences (SPSS) was used. The descriptive statistics of simple frequency, percentage, charts and graphs were computed for the analysis. Finding in the study shows that the market vigilante is able to deter and disrupt criminal activities through strategic spiritual intelligence (SSI), use of charm and juju, physical presence in strategic locations vulnerable to crime occurrence. Findings in the study also show that vigilantes collaborate with the police by assisting them in surveillance, tracking down criminals, identifying black spots, acting as informants to the police, arrest and handover criminal to police. Their challenges include poor equipment, motivation, unhealthy rivalry between the vigilante and the police. The study recommends that the government should support vigilantes with logistics and training, including patrol vehicle and radio communication. The study also recommends the integration of the informal mechanism (juju and charm) of crime detection and prevention into the formal policing strategy, an office should be created in the force commands for use of SSI.

Keywords: central business district, CBD, charm, Juju, strategic spiritual intelligence, SSI

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Authors: Mircea Pastrav, Horia Constantinescu

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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.

Keywords: modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria

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Authors: Yoon Suh Song

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Though music education can broaden one’s capacity for mathematical performance, many countries lag behind in music education. Little empirical evidence is found to identify the connection between math and music. Therefore, this research was set out to explore what music-related variables are associated with mathematical performance. The result of our analysis is as follows: A Pearson's Correlation analysis revealed that PISA math score is strongly correlated with students' Intelligence Quotient (IQ). This lays the foundation for further research as to what factors in students’ IQ lead to a better performance in math.

Keywords: music education, mathematical performance, education, IQ

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Authors: Mballa Abanda Serge, Henda Gnakate Biba, Romaric Guemno Kuate, Akono Rufine Nicole, Petfiang Sidonie, Bella Sidonie

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization, It designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and world music or variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, entanglement, langauge, science

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Authors: Nasser Salah Eldin Mohammed Salih Shebka

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Current problematic issues in AI fields are mainly due to those of knowledge representation conceptual theories, which in turn reflected on the entire scope of cognitive sciences. Knowledge representation methods and tools are driven from theoretical concepts regarding human scientific perception of the conception, nature, and process of knowledge acquisition, knowledge engineering and knowledge generation. And although, these theoretical conceptions were themselves driven from the study of the human knowledge representation process and related theories; some essential factors were overlooked or underestimated, thus causing critical methodological deficiencies in the conceptual theories of human knowledge and knowledge representation conceptions. The evaluation criteria of human cumulative knowledge from the perspectives of nature and theoretical aspects of knowledge representation conceptions are affected greatly by the very materialistic nature of cognitive sciences. This nature caused what we define as methodological deficiencies in the nature of theoretical aspects of knowledge representation concepts in AI. These methodological deficiencies are not confined to applications of knowledge representation theories throughout AI fields, but also exceeds to cover the scientific nature of cognitive sciences. The methodological deficiencies we investigated in our work are: - The Segregation between cognitive abilities in knowledge driven models.- Insufficiency of the two-value logic used to represent knowledge particularly on machine language level in relation to the problematic issues of semantics and meaning theories. - Deficient consideration of the parameters of (existence) and (time) in the structure of knowledge. The latter requires that we present a more detailed introduction of the manner in which the meanings of Existence and Time are to be considered in the structure of knowledge. This doesn’t imply that it’s easy to apply in structures of knowledge representation systems, but outlining a deficiency caused by the absence of such essential parameters, can be considered as an attempt to redefine knowledge representation conceptual approaches, or if proven impossible; constructs a perspective on the possibility of simulating human cognition on machines. Furthermore, a redirection of the aforementioned expressions is required in order to formulate the exact meaning under discussion. This redirection of meaning alters the role of Existence and time factors to the Frame Work Environment of knowledge structure; and therefore; knowledge representation conceptual theories. Findings of our work indicate the necessity to differentiate between two comparative concepts when addressing the relation between existence and time parameters, and between that of the structure of human knowledge. The topics presented throughout the paper can also be viewed as an evaluation criterion to determine AI’s capability to achieve its ultimate objectives. Ultimately, we argue some of the implications of our findings that suggests that; although scientific progress may have not reached its peak, or that human scientific evolution has reached a point where it’s not possible to discover evolutionary facts about the human Brain and detailed descriptions of how it represents knowledge, but it simply implies that; unless these methodological deficiencies are properly addressed; the future of AI’s qualitative progress remains questionable.

Keywords: cognitive sciences, knowledge representation, ontological reasoning, temporal logic

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

Procedia PDF Downloads 142