Search results for: artificial intelligence and office

Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: Maria Antonieta Erna Castillo Holly

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During the last decade, data analysis, strategic decision making, and the use of artificial intelligence (AI) tools in Latin American agriculture have been a challenge. In some countries, the availability, quality, and reliability of historical data, in addition to the current data recording methodology in the field, makes it difficult to use information systems, complete data analysis, and their support for making the right strategic decisions. This is something essential in Agriculture 4.0. where the increase in the global demand for fresh agricultural products of tropical origin, during all the seasons of the year requires a change in the production model and greater agility in the responses to the consumer market demands of quality, quantity, traceability, and sustainability –that means extensive data-. Having quality information available and updated in real-time on what, how much, how, when, where, at what cost, and the compliance with production quality standards represents the greatest challenge for sustainable and profitable agriculture in the region. The objective of this work is to present a methodological proposal for the collection of georeferenced data from the protected agriculture sector, specifically in production units (UP) with tall structures (Greenhouses), initially for Venezuela, taking the state of Mérida as the geographical framework, and horticultural products as target crops. The document presents some background information and explains the methodology and tools used in the 3 phases of the work: diagnosis, data collection, and analysis. As a result, an evaluation of the process is carried out, relevant data and dashboards are displayed, and the first satellite maps integrated with layers of information in a geographic information system are presented. Finally, some improvement proposals and tentatively recommended applications are added to the process, understanding that their objective is to provide better qualified and traceable georeferenced data for subsequent analysis of the information and more agile and accurate strategic decision making. One of the main points of this study is the lack of quality data treatment in the Latin America area and especially in the Caribbean basin, being one of the most important points how to manage the lack of complete official data. The methodology has been tested with horticultural products, but it can be extended to other tropical crops.

Keywords: greenhouses, protected agriculture, data analysis, geographic information systems, Venezuela

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Authors: Florin G. Borcan, Ramona C. Albulescu, Adela Chirita-Emandi

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pH-responsive drug delivery systems are gaining more importance because these systems deliver the drug at a specific time in regards to pathophysiological necessity, resulting in improved patient therapeutic efficacy and compliance. Polyurethane materials are well-known for industrial applications (elastomers and foams used in different insulations and automotive), but they are versatile biocompatible materials with many applications in medicine, as artificial skin for the premature neonate, membrane in the hybrid artificial pancreas, prosthetic heart valves, etc. This study aimed to obtain the physico-chemical characterization of a drug delivery system based on polyurethane microparticles. The synthesis is based on a polyaddition reaction between an aqueous phase (mixture of polyethylene-glycol M=200, 1,4-butanediol and Tween® 20) and an organic phase (lysin-diisocyanate in acetone) combined with simultaneous emulsification. Different active agents (omeprazole, amoxicillin, metoclopramide) were used to verify the release profile of the macromolecular particles in different pH mediums. Zetasizer measurements were performed using an instrument based on two modules: a Vasco size analyzer and a Wallis Zeta potential analyzer (Cordouan Technol., France) in samples that were kept in various solutions with different pH and the maximum absorbance in UV-Vis spectra were collected on a UVi Line 9,400 Spectrophotometer (SI Analytics, Germany). The results of this investigation have revealed that these particles are proper for a prolonged release in gastric medium where they can assure an almost constant concentration of the active agents for 1-2 weeks, while they can be disassembled faster in a medium with neutral pHs, such as the intestinal fluid.

Keywords: lysin-diisocyanate, nanostructures, polyurethane, Zetasizer

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Authors: Hesham Shaalan

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Senior design projects teach students many important skills. One of the major goals is to prepare students to apply effective problem-solving techniques to a problem that represents a real-world situation. This includes the ability to define the problem, compare alternative solutions, identify the best solution, and design the system. This paper describes the design of a shipboard power plant as a senior project in the Marine Engineering program at the U.S. Merchant Marine Academy. The design project was supervised by faculty members who guided a multidisciplinary group of seniors. The research project was sponsored by the Office of Naval Research. Each group of seniors focused on one of the main design aspects of the project, including the electric power system, nuclear power plant, ship hull design, and economics.

Keywords: senior design project, shipboard power system, engineering education, marine engineering

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Authors: R. Lekaviciene, D. Antiniene

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Attempts to split the construct of emotional intelligence (EI) into separate components – ability to understand own and others’ emotions and ability to control own and others’ emotions may be meaningful more theoretically than practically. In real life, a personality encounters various emotional situations that require exhibition of complex EI to solve them. Emotional situation solution tests enable measurement of such undivided EI. The object of the present study is to determine sociodemographic and other factors that are important for emotional situation solutions. The study involved 1,430 participants from various regions of Lithuania. The age of participants varied from 17 years to 27 years. Emotional social and interpersonal situation scale EI-DARL-V2 was used. Each situation had two mandatory answering formats: The first format contained assignments associated with hypothetical theoretical knowledge of how the situation should be solved, while the second format included the question of how the participant would personally resolve the given situation in reality. A questionnaire that contained various sociodemographic data of subjects was also presented. Factors, statistically significant for emotional situation solution, have been determined: gender, family structure, the subject’s relation with his or her mother, mother’s occupation, subjectively assessed financial situation of the family, level of education of the subjects and his or her parents, academic achievement, etc. The best solvers of emotional situations are women with high academic achievements. According to their chosen study profile/acquired profession, they are related to the fields in social sciences and humanities. The worst solvers of emotional situations are men raised in foster homes. They are/were bad students and mostly choose blue-collar professions.

Keywords: emotional intelligence, emotional situations, solution of situation, young people

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Authors: Jessica Kate Simonds

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The last successful hijacking perpetrated by Somali pirates in 2012 represented a critical turning point for the identity and brand of Indian Ocean (IO) insecurity, coined in this paper as the era of the post-piratical. This paper explores the broadening of the PMSC business model to account and contribute to the design of a new IO security environment that prioritises foreign and insurgency drone activity and Houthi rebel operations as the main threat to merchant shipping in the post-2012 era. This study is situated within a longer history of analysing maritime insecurity and also contributes a bespoke conceptual framework that understands the sea as a space that is produced and reproduced relative to existing and emerging threats to merchant shipping based on bespoke models of information sharing and intelligence acquisition. This paper also makes a prominent empirical contribution by drawing on a post-positivist methodology, data drawn from original semi-structured interviews with senior maritime insurers and active merchant seafarers that is triangulated with industry-produced guidance such as the BMP series as primary data sources. Each set is analysed through qualitative discourse and content analysis and supported by the quantitative data sets provided by the IMB Piracy Reporting center and intelligence networks. This analysis reveals that mechanisms such as the IGP&I Maritime Security Committee and intelligence divisions of PMSC’s have driven the exchanges of knowledge between land and sea and thus the reproduction of the maritime security environment through new regulations and guidance to account dones, rebels and bombs as the key challenges in the IO, beyond piracy. A contribution of this paper is the argument that experts who may not be in the highest-profile jobs are the architects of maritime insecurity based on their detailed knowledge and connections to vessels in transit. This paper shares the original insights of those who have served in critical decision making spaces to demonstrate that the development and refinement of industry produced deterrence guidance that has been accredited to the mitigation of piracy, have shaped new editions such as BMP 5 that now serve to frame a new security environment that prioritises the mitigation of risks from drones and WBEID’s from both state and insurgency risk groups. By highlighting the experiences and perspectives of key players on both land and at sea, the key finding of this paper is outlining that as pirates experienced a financial boom by profiteering from their bespoke business model during the peak of successful hijackings, the private security market encountered a similar level of financial success and guaranteed risk environment in which to prospect business. Thus, the reproduction of the Indian Ocean as a maritime security environment reflects a new found purpose for PMSC’s as part of the broader conglomerate of maritime insurers, regulators, shipowners and managers who continue to redirect the security consciousness and IO brand of insecurity.

Keywords: maritime security, private security, risk intelligence, political geography, international relations, political economy, maritime law, security studies

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Authors: Jillian M. Hagel, Joseph E. Tucker, Peter J. Facchini

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With the aim of establishing a holistic approach for the treatment of central nervous system (CNS) disorders, we are pursuing a drug development program rapidly progressing through discovery and characterization phases. The drug candidates identified in this program are referred to as neuroplastogens owing to their ability to mediate neuroplasticity, which can be beneficial to patients suffering from anxiety, depression, or posttraumatic stress disorder. These and other related neuropsychiatric conditions are associated with the onset of neuronal atrophy, which is defined as a reduction in the number and/or productivity of neurons. The stimulation of neuroplasticity results in an increase in the connectivity between neurons and promotes the restoration of healthy brain function. We have synthesized a substantial catalogue of proprietary indolethylamine derivatives based on the general structures of serotonin (5-hydroxytryptamine) and psychedelic molecules such as N,N-dimethyltryptamine (DMT) and psilocin (4-hydroxy-DMT) that function as neuroplastogens. A primary objective in our screening protocol is the identification of derivatives associated with a significant reduction in hallucination, which will allow administration of the drug at a dose that induces neuroplasticity and triggers other efficacious outcomes in the treatment of targeted CNS disorders but which does not cause a psychedelic response in the patient. Both neuroplasticity and hallucination are associated with engagement of the 5HT2A receptor, requiring drug candidates differentially coupled to these two outcomes at a molecular level. We use novel and proprietary artificial intelligence algorithms to predict the mode of binding to the 5HT2A receptor, which has been shown to correlate with the hallucinogenic response. Hallucination is tested using the mouse head-twitch response model, whereas mouse marble-burying and sucrose preference assays are used to evaluate anxiolytic and anti-depressive potential. Neuroplasticity is assays using dendritic outgrowth assays and cell-based ELISA analysis. Pharmacokinetics and additional receptor-binding analyses also contribute the selection of lead candidates. A summary of the program is presented.

Keywords: neuroplastogen, non-hallucinogenic, drug development, anxiety, depression, PTSD, indolethylamine derivatives, psychedelic-inspired, 5-HT2A receptor, computational chemistry, head-twitch response behavioural model, neurite outgrowth assay

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Authors: Swati Bajpai, S. P. K Jena

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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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Authors: Rebekah Granger Ellis, Richard B. Speaker, Pat Austin

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This study used two psychological scales to examine the level of social and emotional intelligence and moral judgment of over 500 gifted and talented high school students in various academic and creative arts programs in a large metropolitan area in the southeastern United States. For decades, numerous models and programs purporting to encourage socio-affective characteristics of adolescent development have been explored in curriculum theory and design. Socio-affective merges social, emotional, and moral domains. It encompasses interpersonal relations and social behaviors; development and regulation of emotions; personal and gender identity construction; empathy development; moral development, thinking, and judgment. Examining development in these socio-affective domains can provide insight into why some gifted and talented adolescents are not successful in adulthood despite advanced IQ scores. Particularly whether nonintellectual characteristics of gifted and talented individuals, such as emotional, social and moral capabilities, are as advanced as their intellectual abilities and how these are related to each other. Unique characteristics distinguish gifted and talented individuals; these may appear as strengths, but there is the potential for problems to accompany them. Although many thrive in their school environments, some gifted students struggle rather than flourish. In the socio-affective domain, these adolescents face special intrapersonal, interpersonal, and environmental problems. Gifted individuals’ cognitive, psychological, and emotional development occurs asynchronously, in multidimensional layers at different rates and unevenly across ability levels. Therefore, it is important to examine the long-term effects of participation in various gifted and talented programs on the socio-affective development of gifted and talented adolescents. This quasi-experimental longitudinal study examined students in several gifted and talented education programs (creative arts school, urban charter schools, and suburban public schools) for (1) socio-affective development level and (2) whether a particular gifted and talented program encourages developmental growth. The following research questions guided the study: (1) How do academically and artistically talented gifted 10th and 11th grade students perform on psychometric scales of social and emotional intelligence and moral judgment? Do they differ from their age or grade normative sample? Are their gender differences among gifted students? (2) Does school environment impact 10th and 11th grade gifted and talented students’ socio-affective development? Do gifted adolescents who participate in a particular school gifted program differ in their developmental profiles of social and emotional intelligence and moral judgment? Students’ performances on psychometric instruments were compared over time and by type of program. Participants took pre-, mid-, and post-tests over the course of an academic school year with Defining Issues Test (DIT-2) assessing moral judgment and BarOn EQ-I: YV assessing social and emotional intelligence. Based on these assessments, quantitative differences in growth on psychological scales (individual and school) were examined. Change scores between schools were also compared. If a school showed change, artifacts (culture, curricula, instructional methodology) provided insight as to environmental qualities that produced this difference.

Keywords: gifted and talented education, moral development, socio-affective development, socio-affective education

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Authors: Chairussyuhur Arman, Totti Tjiptosumirat, Muhammad Gunawan, Mastur, Joko Priyono, Baiq Tri Ratna Erawati

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The present study was undertaken to synchronize oestrus of bali cattle and artificially inseminated with frozen-thawed sexed-semen. The experiment was carried out at District AI Station. Four pluriparous cows and four nulliparous heifers were used in this study and they were housed in free stall barns. The heifers fed with corn silage supplemented with UMMB, while the cows fed with green fodder. All animals were given 500 mg cloprostenolum i.m. injections PGF2α twice, 11 days apart, to synchronize the occurrence of estrus. Estrus was detected by visual observation twice a day and determined if all cattle accepted mount from other females. All animals were inseminated twice with Bali sexed-semen at 72 and 76 h after observed oestrus. Results suggested that the percentage of calving rate either for pluriparous cows or nulliparous heifers were recorded to be 75 percent. One cow and one heifer did not produce calves because of embryonic lost. Regardless the sex of calves, the mean of birth weight of calves in cows was higher than that of heifers (18.50 ± 2.60 kg vs 13.83 ± 5.20 kg). One female calf from heifer with lower birth weight (8.0 kg) was dead one day after born. In pluriparous group, two cows delivered male calves and the other delivered female calf. Conversely in nulliparous group, two heifers delivered female calves and the other male calf. It is concluded that under the conditions of this preliminary trials, the sex ratio between pluriparous and nulliparous groups was found to be 50:50 (male:female).

Keywords: artificial insemination, bali cattle, calves, sexed sperm

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Authors: Elijah Cavan

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In Major League Sports (MLB, NBA, NHL, NFL), it is the Front Office Staff (FOS) who make decisions about who plays for their respective team. The FOS bear the brunt of the responsibility for acquiring players through drafting, trading and signing players in free agency while typically contesting with maximum roster salary constraints. The players themselves are volatile assets of these teams- their value fluctuates with age and performance. A simple comparison can be made when viewing players as assets. The problem here is similar to that of optimizing your investment portfolio. The The goal is ultimately to maximize your periodic returns while tolerating a fixed risk (degree of uncertainty/ potential loss). Each franchise may value assets differently, and some may only tolerate lower risk levels- these are examples of factors that introduce additional constraints into the model. In this talk, we will detail the mathematical formulation of this problem as a constrained optimization problem- which can be solved with classical machine learning methods but is also well posed as a problem to be solved on quantum computers

Keywords: optimization, financial mathematics, sports analytics, simulated annealing

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Authors: Mohammad Ashraf

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This research links the use of Building Information Modeling technology in constructions and infrastructure projects, starting from the moment when considering the establishment of a project to demolishing or renovating it, going through the design work, planning, procurement and implementation. BIM Software's which used are Revit, Navisworks and Asta Project in the case study for the Atletico Madrid Stadium project (Wanda Stadium). Also, the project improves through various phases of construction (planning - implementation - management). Besides, the level of the details managed within this project advances gradually. In addition, the construction process problems become about 30 % less than before, resulting from high coordination between designing, implementation and follow through that is done by the project management office (PMO). The current disposition in the industry is to tightly manage the detail contained within the planning and coordination phases of construction, but we miss the opportunity to manage that data as it matures and grows into the execution and commissioning phases.

Keywords: construction management, BIM technology, planning, design, procurements, critical path method

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Authors: Muna Khushaim

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Aluminum-based alloys play a key role in modern engineering, especially in the aerospace industry. Introduction of solute atoms such as Li and Cu is the main approach to improve the strength in age-hardenable Al alloys via the precipitation hardening phenomenon. Knowledge of the decomposition process of the microstructure during the precipitation reaction is particularly important for future technical developments. The objective of this study is to investigate the nano-scale chemical composition in the Al-Cu, Al-Li and Al-Li-Cu during the early stage of the precipitation sequence and to describe whether this compositional difference correlates with variations in the observed precipitation kinetics. Comparing the random binomial frequency distribution and the experimental frequency distribution of concentrations in atom probe tomography data was used to investigate the early stage of decomposition in the different binary and ternary alloys which were experienced different heat treatments. The results show that an Al-1.7 at.% Cu alloy requires a long ageing time of approximately 8 h at 160 °C to allow the diffusion of Cu atoms into Al matrix. For the Al-8.2 at.% Li alloy, a combination of both the natural ageing condition (48 h at room temperature) and a short artificial ageing condition (5 min at 160 °C) induces increasing on the number density of the Li clusters and hence increase number of precipitated δ' particles. Applying this combination of natural ageing and short artificial ageing conditions onto the ternary Al-4 at.% Li-1.7 at.% Cu alloy induces the formation of a Cu-rich phase. Increasing the Li content in the ternary alloy up to 8 at.% and increasing the ageing time to 30 min resulted in the precipitation processes ending with δ' particles. Thus, the results contribute to the understanding of Al-alloy design.

Keywords: aluminum alloy, atom probe tomography, early stage, decomposition

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Authors: Barakat Adebisi Raji

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In the workplace, Artificial Intelligence has, in recent years, emerged as a transformative technology that revolutionizes how organizations operate and perform tasks. It is a technology that has a significant impact on transportation, manufacturing, education, cyber security, robotics, agriculture, healthcare, and so many other organizations. By harnessing AI technology, workplaces can enhance productivity, streamline processes, and make more informed decisions. Given the potential of AI to change the way we work and its impact on the labor market in years to come, employers understand that it entails legal challenges and risks despite the advantages inherent in it. Therefore, as AI continues to integrate into various aspects of the workplace, understanding the legal and ethical implications becomes paramount. Also central to this study is the question of who is held liable where AI makes any defaults; the person (company) who created the AI, the person who programmed the AI algorithm or the person who uses the AI? Thus, the aim of this paper is to provide a detailed overview of how AI-related liabilities are addressed under each legal tradition and shed light on potential areas of accord and divergence between the two legal cultures. The objectives of this paper are to (i) examine the ability of Common law and Islamic law to accommodate the issues and damage caused by AI in the workplace and the legality of compensation for such injury sustained; (ii) to discuss the extent to which AI can be described as a legal personality to bear responsibility: (iii) examine the similarities and disparities between Common Law and Islamic Jurisprudence on the liability of AI in the workplace. The methodology adopted in this work was qualitative, and the method was purely a doctrinal research method where information is gathered from the primary and secondary sources of law, such as comprehensive materials found in journal articles, expert-authored books and online news sources. Comparative legal method was also used to juxtapose the approach of Islam and Common Law. The paper concludes that since AI, in its current legal state, is not recognized as a legal entity, operators or manufacturers of AI should be held liable for any damage that arises, and the determination of who bears the responsibility should be dependent on the circumstances surrounding each scenario. The study recommends the granting of legal personality to AI systems, the establishment of legal rights and liabilities for AI, the establishment of a holistic Islamic virtue-based AI ethics framework, and the consideration of Islamic ethics.

Keywords: AI, health- care, agriculture, cyber security, common law, Shari'ah

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Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

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This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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Authors: Lizhu Y. Davis, Gretchen Higginbottom, Vang Vang

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This presentation explores the adoption of library resources to engage students in a Visual Merchandising course during the 2016 spring semester. This study was a cross-disciplinary collaboration between the Fashion Merchandising Program and the Madden Library at California State University, Fresno. The goal of the project was to explore and assess the students’ use of library resources as a part of the Affordable Learning Solutions Initiative, a California State University (CSU) Office of the Chancellor Program that enables faculty to choose and provide high-quality, free or low-cost educational materials for their students. Students were interviewed afterwards and the results were generally favorable and provided insight into how students perceive and use library resources to support their research needs. This study reveals an important step in examining how open educational resources impact student learning.

Keywords: collaboration, library resources, open educational resources, visual merchandising

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Authors: M. Gil, R. Montalvo

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Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

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Authors: Jinming Du

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With the COVID-19 pandemic beginning in 2020, many higher education institutions and education systems are turning to hybrid or fully distance online courses to maintain social distance and provide a safe virtual space for learning and teaching. However, the majority of faculty members were not well prepared for the shift to blended or distance learning. Communication frustrations are prevalent in both hybrid and full-distance courses. A systematic literature review was conducted by a comprehensive analysis of 1688 publications that focused on the application of the adoption of chatbots in education. This study aimed to explore instructors' experiences with chatbots in online and blended undergraduate English courses. Language learners are overwhelmed by the variety of information offered by many online sites. The recently emerged chatbots (e.g.: ChatGPT) are slightly superior in performance as compared to those traditional through previous technologies such as tapes, video recorders, and websites. The field of chatbots has been intensively researched, and new methods have been developed to demonstrate how students can best learn and practice a new language in the target language. However, it is believed that among the many areas where chatbots are applied, while chatbots have been used as effective tools for communicating with business customers, in consulting and targeting areas, and in the medical field, chatbots have not yet been fully explored and implemented in the field of language education. This issue is challenging enough for language teachers; they need to study and conduct research carefully to clarify it. Pedagogical chatbots may alleviate the perception of a lack of communication and feedback from instructors by interacting naturally with students through scaffolding the understanding of those learners, much like educators do. However, educators and instructors lack the proficiency to effectively operate this emerging AI chatbot technology and require comprehensive study or structured training to attain competence. There is a gap between language teachers’ perceptions and recent advances in the application of AI chatbots to language learning. The results of the study found that although the teachers felt that the chatbots did the best job of giving feedback, the teachers needed additional training to be able to give better instructions and to help them assist in teaching. Teachers generally perceive the utilization of chatbots to offer substantial assistance to English language instruction.

Keywords: artificial intelligence in education, chatbots, education and technology, education system, pedagogical chatbot, chatbots and language education

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Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen

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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.

Keywords: administrative law, algorithmic decision-making, decision support, public law

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Authors: Gordon James Knowles

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Historically the Chinatown district in Sandwich Islands has been plagued with the traditional vice crimes of illegal drugs, gambling, and prostitution since the early 1800s. However, a new form of psychologically addictive arcade style table gambling machines has become the dominant form of illegal revenue made in Honolulu, Hawaii. This study attempts to document the drive, desire, or will to play and wager with arcade style video gaming and understand the role of illegal game rooms in facilitating pathological gambling addiction. Indicators of police corruption by Chinese organized crime syndicates related to protection rackets, bribery, and pay-offs were revealed. Information fusion from a police science and sociological intelligence perspective indicates insurgent warfare is being waged on the streets of Honolulu by the People’s Republic of China. This state-sponsored communist terrorism in the Hawaiian Islands used “contactless” irregular warfare entailing: (1) the deployment of psychologically addictive gambling machines, (2) the distribution of the physically addictive fentanyl drug as a lethal chemical weapon, and (3) psychological warfare by circulating pro-China anti-American propaganda newspapers targeted at the small island populace.

Keywords: Chinese and Polynesian organized crime, china daily newspaper, electronic arcade style table games, gaming technology addiction, illegal compulsive gambling, and police intelligence

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Kishen Prathivadi

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The Sewer Authority Mid-Coastside (SAM) is a Joint Powers Authority formed in 1976 and provides secondary wastewater treatment to an average flow of 2.0 million gallons per day. SAM owns and operates a Wastewater Treatment Plant (WWTP) and a sanitary sewage collection system that collects sewage from its three member agencies: the City of Half Moon Bay, the Granada Community Services District and Montara Water and Sanitary District. The Sewer Authority Mid-Coastside (SAM) partnered with Pacific Gas & Electric, and its contractor GEL America, to review and replace all inefficient lighting fixtures and bulbs at the SAM treatment plant and administrative office. The project focused on replacing old and inefficient lighting fixtures and bulbs, reducing annual operating and maintenance costs, and reducing SAM’s carbon footprint. The project resulted in a 55% overall energy reduction, higher light quality and acuity, and a total operational savings of $495,000 over ten years.

Keywords: energy savings, LED, lighting, electrical

Procedia PDF Downloads 123

Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

Procedia PDF Downloads 447

Authors: Bylhah Mugotitsa, Jim Todd, Agnes Kiragga, Jay Greenfield, Evans Omondi, Lukoye Atwoli, Reinpeter Momanyi

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The INSPIRE network aims to build an open, ethical, sustainable, and FAIR (Findable, Accessible, Interoperable, Reusable) data science platform, particularly for longitudinal mental health (MH) data. While studies have been done at the clinical and population level, there still exists limitations in data and research in LMICs, which pose a risk of underrepresentation of mental disorders. It is vital to examine the existing longitudinal MH data, focusing on how FAIR datasets are. This landscape analysis aimed to provide both overall level of evidence of availability of longitudinal datasets and degree of consistency in longitudinal studies conducted. Utilizing prompters proved instrumental in streamlining the analysis process, facilitating access, crafting code snippets, categorization, and analysis of extensive data repositories related to depression, anxiety, and psychosis in Africa. While leveraging artificial intelligence (AI), we filtered through over 18,000 scientific papers spanning from 1970 to 2023. This AI-driven approach enabled the identification of 228 longitudinal research papers meeting inclusion criteria. Quality assurance revealed 10% incorrectly identified articles and 2 duplicates, underscoring the prevalence of longitudinal MH research in South Africa, focusing on depression. From the analysis, evaluating data and metadata adherence to FAIR principles remains crucial for enhancing accessibility and quality of MH research in Africa. While AI has the potential to enhance research processes, challenges such as privacy concerns and data security risks must be addressed. Ethical and equity considerations in data sharing and reuse are also vital. There’s need for collaborative efforts across disciplinary and national boundaries to improve the Findability and Accessibility of data. Current efforts should also focus on creating integrated data resources and tools to improve Interoperability and Reusability of MH data. Practical steps for researchers include careful study planning, data preservation, machine-actionable metadata, and promoting data reuse to advance science and improve equity. Metrics and recognition should be established to incentivize adherence to FAIR principles in MH research

Keywords: longitudinal mental health research, data sharing, fair data principles, Africa, landscape analysis

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

Procedia PDF Downloads 40

Authors: Takashi Mitsuishi

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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).

Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation

Procedia PDF Downloads 342

Authors: Mballa Abanda Luc Aurelien Serge, Henda Gnakate Biba, Kuate Guemo Romaric, Akono Rufine Nicole, Zabotom Yaya Fadel Biba, Petfiang Sidonie, Bella Suzane Jenifer

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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. 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, I designed a semi-digital, semi-analog application that 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 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). The 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: language, music, sciences, quantum entenglement

Procedia PDF Downloads 60

Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

Procedia PDF Downloads 380

Authors: Alok Saini, Rajkumar Ghosh

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Water is nature's important resource for survival of all living things, but freshwater scarcity exists in some parts of world. This study has predicted that Gomti Nagar area (49.2 sq. km.) will harvest about 91110 ML of rainwater till 2051 (assuming constant and present annual rainfall). But 17.71 ML of rainwater was harvested from only 53 buildings in Gomti Nagar area in the year 2021. Water level will be increased (rise) by 13 cm in Gomti Nagar from such groundwater recharge. The total annual groundwater abstraction from Gomti Nagar area was 35332 ML (in 2021). Due to hydrogeological constraints and lower annual rainfall, groundwater recharge is less than groundwater abstraction. The recent scenario is only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. Gomti Nagar is situated in 'Zone–A' (water distribution area) and groundwater is the primary source of freshwater supply. Current scenario indicates only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. In Gomti Nagar, the difference between groundwater abstraction and recharge will be 735570 ML in 30 yrs. Statistically, all buildings at Gomti Nagar (new and renovated) could harvest 3037 ML of rainwater through RTRWHs annually. The most recent monsoonal recharge in Gomti Nagar was 10813 ML/yr. Harvested rainwater collected from RTRWHs can be used for rooftop irrigation, and residential kitchen and gardens (home grown fruit and vegetables). According to bylaws, RTRWH installations are required in both newly constructed and existing buildings plot areas of 300 sq. m or above. Harvested rainwater is of higher quality than contaminated groundwater. Harvested rainwater from RTRWHs can be considered water self-sufficient. Rooftop Rainwater Harvesting Systems (RTRWHs) are least expensive, eco-friendly, most sustainable, and alternative water resource for artificial recharge. This study also predicts about 3.9 m of water level rise in Gomti Nagar area till 2051, only when all buildings will install RTRWHs and harvest for groundwater recharging. As a result, this current study responds to an impact assessment study of RTRWHs implementation for the water scarcity problem in the Gomti Nagar area (1.36 sq.km.). This study suggests that common storage tanks (recharge wells) should be built for a group of at least ten (10) households and optimal amount of harvested rainwater will be stored annually. Artificial recharge from alternative water sources will be required to improve the declining water level trend and balance the groundwater table in this area. This over-exploitation of groundwater may lead to land subsidence, and development of vertical cracks.

Keywords: aquifer, aquitard, artificial recharge, bylaws, groundwater, monsoon, rainfall, rooftop rainwater harvesting system, RTRWHs water table, water level

Procedia PDF Downloads 70

Authors: Younis R. Elhaddad, Mohamed A. Alshaari

Abstract:

Since 2700 B.C the problem of constructing magic squares attracts many researchers. Magic squares one of most difficult challenges for mathematicians. In this work, we describe how to construct and enumerate Pan- magic squares using genetic algorithm, using new chromosome encoding technique. The results were promising within reasonable time.

Keywords: genetic algorithm, magic square, pan-magic square, computational intelligence

Procedia PDF Downloads 557