Search results for: complex plane

Authors: Anisah Ari

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Effects of organized crime permeate all facets of life, including public health, socio-economic endeavors, and human security. If any element of this is affected, it impacts large-scale national and global interest. Seeking to address terrorist networks through technical thinking is like trying to kill a weed by just cutting off its branches. It will re-develop and expand in proportions beyond one’s imagination, even in horrific ways that threaten human security. The continent of Africa has been bedeviled by this menace, with little or no solution to the problem. Nigeria is dealing with a protracted insurgency that is perpetrated by a sect against any form of westernization. Reimagining approaches to dealing with pressing issues like terrorism may require engaging the right set of people in the conversation for any sustainable change. These are people who have lived through the daily effects of the violence that ensues from the activities of terrorist activities. Effective leadership is required for an inclusive process, where spaces are created for diverse voices to be heard, and multiple perspectives are listened to, and not just heard, that supports a determination of the realistic outcome. Addressing insurgency in Nigeria has experienced a lot of disinformation and uncertainty. This may be in part due to poor leadership or an iteration of technical solutions to adaptive challenge peacemaking efforts in Nigeria has focused on behaviors, attitudes and practices that contribute to violence. However, it is important to consider the underlying issues that build-up, ignite and fan the flames of violence—looking at conflict as a complex system, issues like climate change, low employment rates, corruption and the impunity of discrimination due to ethnicity and religion. This article will be looking at an option of the more relational way of addressing insurgency through adaptive approaches that embody engagement and solutions with the people rather than for the people. The construction of a local turn in peacebuilding is informed by the need to create a locally driven and sustained peace process that embodies the culture and practices of the people in enacting an everyday peace beyond just a perennial and universalist outlook. A critical analysis that explores the socially identified individuals and situations will be made, considering the more adaptive approach to a complex existential challenge rather than a universalist frame. Case Study and Ethnographic research approach to understand what other scholars have documented on the matter and also a first-hand understanding of the experiences and viewpoints of the participants.

Keywords: terrorism, adaptive, peace, culture

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Authors: Virendra Nath, Vipin Kumar

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Background: TypeII Diabetes mellitus is a foremost health problem worldwide, predisposing to increased mortality and morbidity. Undesirable effects of the current medications have prompted the researcher to develop more potential drug(s) against the disease. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptors family and take part in a vital role in the regulation of metabolic equilibrium. They can induce or repress genes associated with adipogenesis, lipid, and glucose metabolism. Aims: Investigation of PPARα/γ agonistic hits were screened by hierarchical virtual screening followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) analysis using approved PPAR α/γ dual agonist. Methods: The PPARα/γ agonistic activity of compounds was searched by using Maestro through structure-based virtual screening and molecular dynamics (MD) simulation application. Virtual screening of nuclear-receptor ligands was done, and the binding modes with protein-ligand interactions of newer entity(s) were investigated. Further, binding energy prediction, Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit along with the structural comparative analysis of approved PPARα/γ agonists with screened hit was done for knowledge-based SAR. Results and Discussion: The silicone chip-based approach recognized the most capable nine hits and had better predictive binding energy as compared to the reference drug compound (Tesaglitazar). In this study, the key amino acid residues of binding pockets of both targets PPARα/γ were acknowledged as essential and were found to be associated in the key interactions with the most potential dual hit (ChemDiv-3269-0443). Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit and found root mean square deviation (RMSD) stabile around 2Å and 2.1Å, respectively. Frequency distribution data also revealed that the key residues of both proteins showed maximum contacts with a potent hit during the MD simulation of 20 nanoseconds (ns). The knowledge-based SAR studies of PPARα/γ agonists were studied using 2D structures of approved drugs like aleglitazar, tesaglitazar, etc. for successful designing and synthesis of compounds PPARγ agonistic candidates with anti-hyperlipidimic potential.

Keywords: computational, diabetes, PPAR, simulation

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Authors: Yari Vecchio, Margherita Masi, Jorgelina Di Pasquale

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Adoption of Precision Agriculture (PA) is involved in a multidimensional and complex scenario. The process of adopting innovations is complex and social inherently, influenced by other producers, change agents, social norms and organizational pressure. Complexity depends on factors that interact and influence the decision to adopt. Farm and operator characteristics, as well as organizational, informational and agro-ecological context directly affect adoption. This influence has been studied to measure drivers and to clarify 'bottlenecks' of the adoption of agricultural innovation. Making decision process involves a multistage procedure, in which individual passes from first hearing about the technology to final adoption. Awareness is the initial stage and represents the moment in which an individual learns about the existence of the technology. 'Static' concept of adoption has been overcome. Awareness is a precondition to adoption. This condition leads to not encountering some erroneous evaluations, arose from having carried out analysis on a population that is only in part aware of technologies. In support of this, the present study puts forward an empirical analysis among Italian farmers, considering awareness as a prerequisite for adoption. The purpose of the present work is to analyze both factors that affect the probability to adopt and determinants that drive an aware individual to not adopt. Data were collected through a questionnaire submitted in November 2017. A preliminary descriptive analysis has shown that high levels of adoption have been found among younger farmers, better educated, with high intensity of information, with large farm size and high labor-intensive, and whose perception of the complexity of adoption process is lower. The use of a logit model permits to appreciate the weight played by the intensity of labor and complexity perceived by the potential adopter in PA adoption process. All these findings suggest important policy implications: measures dedicated to promoting innovation will need to be more specific for each phase of this adoption process. Specifically, they should increase awareness of PA tools and foster dissemination of information to reduce the degree of perceived complexity of the adoption process. These implications are particularly important in Europe where is pre-announced the reform of Common Agricultural Policy, oriented to innovation. In this context, these implications suggest to the measures supporting innovation to consider the relationship between various organizational and structural dimensions of European agriculture and innovation approaches.

Keywords: adoption, awareness, complexity, precision agriculture

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Authors: Syue-Wen Lin

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Objective:This article reviews the care experience of a 40-year-old male patient who underwent a thoracoscopic right lower lobectomy following a COVID-19 infection. His complex medical history included multiple metastases (lungs, liver, spleen, and left kidney) and lung damage from COVID-19, which complicated the weaning process from mechanical ventilation. The care involved managing cancer treatment, postoperative pain, wound care, and palliative care. Methods:Nursing care was provided from August 16 to August 17, 2024. Challenges included difficulty with sputum clearance, which exacerbated the patient's anxiety and fear of reintubation. Pain management strategies combined analgesic drugs, non-drug methods, essential oil massages with family members, and playing the patient’s favorite music to reduce pain and anxiety. Progressive rehabilitation began with stabilizing vital signs, followed by assistance with sitting on the edge of the bed and walking within the ward. Strict sterile procedures and advanced wound care technology were used for daily dressing changes, with meticulous documentation of wound conditions and appropriate dressing selection. Holistic cancer care and palliative measures were integrated to address the patient’s physical and psychological needs. Results:The interdisciplinary care team developed a comprehensive plan addressing both physical and psychological aspects. Respiratory therapy, lung expansion exercises, and a high-frequency chest wall oscillation vest facilitated sputum expulsion and assisted in weaning from mechanical ventilation. The integration of cancer care, pain management, wound care, and palliative care led to improved quality of life and recovery. The collaborative approach between nursing staff and family ensured that the patient received compassionate and effective care. Conclusion: The complex interplay of emergency surgery, COVID-19, and advanced cancer required a multifaceted care strategy. The care team’s approach, combining critical care with tailored cancer and palliative care, effectively improved the patient’s quality of life and facilitated recovery. The comprehensive care plan, developed with family collaboration, provided both high-quality medical care and compassionate support for the terminally ill patient.

Keywords: multiple metastases, testicular cancer, palliative care, nursing experience

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Authors: Ilona Pavlovska, Aneka Klavina, Agris Auce, Ivars Vanadzins, Alise Silova, Laura Komarovska, Linda Paegle, Baiba Silamikele, Linda Dobkevica

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Freshwater sapropel is a common material formed by complex biological transformations of Holocene sediments in the water basement of the lakes in Latvia that has the potential to be used as medical mud. Sapropel forms over a long period in shallow waters by slowly decomposing organic sediment and has different compositions depending on the location of the source, surroundings, the water regime, etc. Official geological survey of Latvia lakes, from Latvian lake database (ezeri.lv), used in the selection of the area of the exploration. The multifunctional effect of sapropel on the whole organism explained by its complex chemical and biological structure. This unique, organic substance and its ability to maintain heat for a long time ensures deep tissue warming and has a positive effect on the treatment of various joint and skin diseases. Sapropel is a valuable resource with multiple areas of application. Investigation of sapropel sediments and survey of the five sites selected according to the criteria performed in the current study. Also, our study includes sampling at different depths and their initial treatment, evaluation of external signs, and study of physical-chemical parameters, as well as analysis of biochemical parameters and evaluation of microbiological indicators. The main selection criteria were sapropel deposits depth, hydrological regime, the history of agriculture next to the lake, and the potential exposure to industrial waste. One hundred and five sapropel samples obtained from five lakes (Audzelu, Dunakla, Ivusku, Zielu, and Mazars Kivdalova) during the wintertime. The main goal of the study is to carry out detailed and systematic research on the medical properties of sapropel to be obtained in Latvia, to promote its scientifically based use in balneology, to develop new medical procedures and services, and to promote the development of new exportable products. Latvian freshwater sapropel could be used as raw material for getting sapropel extract and use it as a remedy. All mentioned above brings us to the main question for sapropel usage in medicine, balneology, and pharmacy “how to develop quality criteria for raw sapropel and its extracts. The research was co-financed by the project "Analysis of characteristics of medical sapropel and its usage for medical purposes and elaboration of industrial extraction methods" No.1.1.1.1/16/A/165.

Keywords: balneology, extracts, freshwater sapropel, Latvian lakes, medical mud, sapropel

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Authors: Ke Zhang, Yongli Zhu

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Due to rapid load growths in today’s highly electrified societies and the requirement for green energy sources, large-scale wind farm power transmission system is constantly developing. This system is a typical multi-terminal power supply system, whose structure of the network topology of transmission lines is complex. What’s more, it locates in the complex terrain of mountains and grasslands, thus increasing the possibility of transmission line faults and finding the fault location with difficulty after the faults and resulting in an extremely serious phenomenon of abandoning the wind. In order to solve these problems, a fault location method for multi-terminal transmission line based on wind farm characteristics and improved single-ended traveling wave positioning method is proposed. Through studying the zero sequence current characteristics by using the characteristics of the grounding transformer(GT) in the existing large-scale wind farms, it is obtained that the criterion for judging the fault interval of the multi-terminal transmission line. When a ground short-circuit fault occurs, there is only zero sequence current on the path between GT and the fault point. Therefore, the interval where the fault point exists is obtained by determining the path of the zero sequence current. After determining the fault interval, The location of the short-circuit fault point is calculated by the traveling wave method. However, this article uses an improved traveling wave method. It makes the positioning accuracy more accurate by combining the single-ended traveling wave method with double-ended electrical data. What’s more, a method of calculating the traveling wave velocity is deduced according to the above improvements (it is the actual wave velocity in theory). The improvement of the traveling wave velocity calculation method further improves the positioning accuracy. Compared with the traditional positioning method, the average positioning error of this method is reduced by 30%.This method overcomes the shortcomings of the traditional method in poor fault location of wind farm transmission lines. In addition, it is more accurate than the traditional fixed wave velocity method in the calculation of the traveling wave velocity. It can calculate the wave velocity in real time according to the scene and solve the traveling wave velocity can’t be updated with the environment and real-time update. The method is verified in PSCAD/EMTDC.

Keywords: grounding transformer, multi-terminal transmission line, short circuit fault location, traveling wave velocity, wind farm

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Authors: H. Jung, N. Kim, B. Kang, J. Choe

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History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

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Authors: Hatim Elhag

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Banking and Financial Service Institutions are possibly the most advanced in terms of technology adoption and use it as a key differentiator. With high levels of business process automation, maturity in the functional portfolio, straight through processing and proven technology outsourcing benefits, Banking sector stand to benefit significantly from Cloud computing capabilities. Additionally, with complex Compliance and Regulatory policies, combined with expansive products and geography coverage, the business impact is even greater. While the benefits are exponential, there are also significant challenges in adopting this model– including Legal, Security, Performance, Reliability, Transformation complexity, Operating control and Governance and most importantly proof for the promised cost benefits. However, new architecture designed should be implemented to align this approach.

Keywords: security, cloud, banking sector, cloud computing

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Authors: Railly Hugo, Igor Aguilar-Alonso

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Software visualization is a powerful tool for understanding complex software systems. However, current visualization tools often lack features or are difficult to use, limiting their effectiveness. In this paper, we present next-viz, a proposed web-based visualization tool that addresses these challenges. We provide a literature review of existing software visualization techniques and tools and describe the architecture of next-viz in detail. Our proposed tool incorporates state-of-the-art visualization techniques and is designed to be user-friendly and intuitive. We believe next-viz has the potential to advance the field of software visualization significantly.

Keywords: software visualization, literature review, tool proposal, next-viz, web-based, architecture, visualization techniques, user-friendly, intuitive

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Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

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Authors: Imen Aouini, Lamia Ben Azzouz

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The energy need is growing rapidly due to the population growth and the large new usage of power. Several works put considerable efforts to make the electricity grid more intelligent to reduce essentially energy consumption and provide efficiency and reliability of power systems. The Smart Grid is a complex architecture that covers critical devices and systems vulnerable to significant attacks. Hence, security is a crucial factor for the success and the wide deployment of Smart Grids. In this paper, we present security issues of the Smart Grid architecture and we highlight open issues that will make the Smart Grid security a challenging research area in the future.

Keywords: smart grids, smart meters, home area network, neighbor area network

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Authors: Do-Jin Jang, Sung-Ah Kim

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In designing a kinetic façade, it is hard for the designer to make digital models due to its complex geometry with motion. This paper aims to present a methodology of converting a point cloud of a physical model into a single digital model with a certain topology and motion. The method uses a Microsoft Kinect sensor, and color markers were defined and applied to three paper folding-inspired designs. Although the resulted digital model cannot represent the whole folding range of the physical model, the method supports the designer to conduct a performance-oriented design process with the rough physical model in the reduced folding range.

Keywords: design media, kinetic facades, tangible user interface, 3D scanning

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Authors: Somayeh Akrami, Vali-Allah Mozaffarian, Habib Onsori

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The studied region in this research, watershed Kuhkamar river, is about 112.66 square kilometers, it is located between 45º 48' 9" to 45º 2' 20" N and 38º 34' 15" to 38º 40' 28" E. The gained results of the studies on flora combinations, proved 287 plant species in 190 genera and 51 families. Asteracea with 49 and Lamiaceae with 27 plant species are the major plant families. Among collected species one interesting plant was found and determined as a new record Anemone narcissiflora L. for flora of Iran. This plant is known as a complex species that shows intraspecific speciation and is classified into about 12 subspecies and 10 varieties in world. To identify the infraspecies taxons of this species, in addition to morphological characteristics, the use of appropriate molecular markers for the better isolation of the individuals were needed.

Keywords: Anemone narcissiflora, floristic Study, kuhkamar, molecular marker

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Authors: Matthew Cardeiro, Amalia D. Ardeljan, Lexi Frankel, Dianela Prado Escobar, Catalina Molnar, Omar M. Rashid

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Introduction: Enterococci comprise the natural flora of nearly all animals and are ubiquitous in food manufacturing and probiotics. However, its role in the microbiome remains controversial. The gut microbiome has shown to play an important role in immunology and cancer. Further, recent data has suggested a relationship between gut microbiota and breast cancer. These studies have shown that the gut microbiome of patients with breast cancer differs from that of healthy patients. Research regarding enterococcus infection and its sequala is limited, and further research is needed in order to understand the relationship between infection and cancer. Enterococcus may prevent the development of breast cancer (BC) through complex immunologic and microbiotic adaptations following an enterococcus infection. This study investigated the effect of enterococcus infection and the incidence of BC. Methods: A retrospective study (January 2010- December 2019) was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using a Humans Health Insurance Database. International Classification of Disease (ICD) 9th and 10th codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and enterococcus infection. Patients were matched for age, sex, Charlson Comorbidity Index (CCI), antibiotic treatment, and region of residence. Chi-squared, logistic regression, and odds ratio were implemented to assess the significance and estimate relative risk. Results: 671 out of 28,518 (2.35%) patients with a prior enterococcus infection and 1,459 out of 28,518 (5.12%) patients without enterococcus infection subsequently developed BC, and the difference was statistically significant (p<2.2x10⁻¹⁶). Logistic regression also indicated enterococcus infection was associated with a decreased incidence of BC (RR=0.60, 95% CI [0.57, 0.63]). Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 398 out of 11,523 (3.34%) patients with a prior enterococcus infection and treated with antibiotics were compared to 624 out of 11,523 (5.41%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed BC. Results remained statistically significant (p<2.2x10-16) with a relative risk of 0.57 (95% CI [0.54, 0.60]). Conclusion & Discussion: This study shows a statistically significant correlation between enterococcus infection and a decrease incidence of breast cancer. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome but also the protective mechanism(s) and impact enterococcus infection may have on breast cancer development. Ultimately, further research is needed in order to understand the complex and intricate relationship between the microbiome, immunology, bacterial infections, and carcinogenesis.

Keywords: breast cancer, enterococcus, immunology, infection, microbiome

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Authors: Adam Marks, Munir Majdalawieh, Maytha Al Ali

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While research is rich with what criteria could be included in the academic program review processes, there is rarely any mention of how this significant and complex process should be managed. This paper proposes using project management methodology in alignment with the program review criteria of the Dickeson’s Prioritizing Academic Programs model. Project management and academic program review share two distinct characteristics; one is their life cycle, and the second is the core knowledge areas they use. This aligned and structured approach offers academic administrators a step-by-step guide that can help them manage this process and effectively assess academic programs.

Keywords: project management, academic program, program review, education, higher education institution, strategic management

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Authors: Girish M. Bhatia

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Most of the important structures in refinery complex are RCC Structures for which in-depth structural monitoring and inspection is required for incessant service. Reinforced concrete structures can be under threat from a combination of insidious challenges due to environmental conditions, including temperature and humidity that lead to accelerated deterioration mechanisms like carbonation, as well as marine exposure, above and below ground structures can experience ingress from aggressive ground waters carrying chlorides and sulphates leading to unexpected deterioration that threaten the integrity of a vital structural asset. By application of health monitoring techniques like corrosion monitoring with help of sensor probes, visual inspection of high rise structures with help of drones, it is possible to establish an early warning at the onset of these destructive processes.

Keywords: concrete structures, corrosion sensors, drones, health monitoring

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Authors: Wu Peiqin

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Flexible thermoelectric devices are light and flexible, which can be in close contact with any shape of heat source surfaces to minimize heat loss and achieve efficient energy conversion. Among the wide application fields, energy harvesting via flexible thermoelectric generators can adapt to a variety of curved heat sources (such as human body, circular tubes, and surfaces of different shapes) and can drive low-power electronic devices, exhibiting one of the most promising technologies in self-powered systems. The heat flux along the cross-section of the flexible thin-film generator is limited by the thickness, so the temperature difference decreases during the generation process, and the output power is low. At present, most of the heat flow directions of the thin film thermoelectric generator are along the thin-film plane; however, this method is not suitable for attaching to the human body surface to generate electricity. In order to make the film generator more suitable for thermoelectric generation, it is necessary to apply a flexible heatsink on the air sides with the film to maintain the temperature difference. In this paper, Bismuth telluride thermoelectric paste was deposited on polyimide flexible substrate by a screen printing method, and the flexible thermoelectric film was formed after drying. There are ten pairs of thermoelectric legs. The size of the thermoelectric leg is 20 x 2 x 0.1 mm, and adjacent thermoelectric legs are spaced 2 mm apart. A phase change material-based flexible heatsink was designed and fabricated. The flexible heatsink consists of n-octadecane, polystyrene, and expanded graphite. N-octadecane was used as the thermal storage material, polystyrene as the supporting material, and expanded graphite as the thermally conductive additive. The thickness of the flexible phase change material-based heatsink is 2mm. A thermoelectric performance testing platform was built, and its output performance was tested. The results show that the system can generate an open-circuit output voltage of 3.89 mV at a temperature difference of 10K, which is higher than the generator without a heatsink. Therefore, the flexible heatsink can increase the temperature difference between the two ends of the film and improve the output performance of the flexible film generator. This result promotes the application of the film thermoelectric generator in collecting human heat for power generation.

Keywords: flexible thermoelectric generator, screen printing, PCM, flexible heatsink

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Authors: Viola Hubačová Pirová

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The assessment of psychomotor development allows us to identify children with motor delays, helps us to monitor progress in time and prepare suitable intervention programs. The foundation of psychomotor development lies in pre-school age and is crucial for child´s further cognitive and social development. Many assessment tools of psychomotor development have been developed over the years. Some of them are easy screening tools; others are more complex and sophisticated. The purpose of this review is to describe the history of psychomotor assessment, specify preschool children´s psychomotor evaluation and review eight psychomotor development assessment tools for preschool children (Denver II., DEMOST-PRE, TGMD -2/3, BOT-2, MABC-2, PDMS-2, KTK, MOT 4-6). The selection of test depends on purpose and context in which is the assessment planned.

Keywords: assessment of psychomotor development, preschool children, psychomotor development, review of assessment tools

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Authors: Triloki Nath, R. K. Gupta, L. P. Singh

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The aim of this paper is to find the new exact solution of the blast wave problem in one-dimensional unsteady adiabatic flow for generalized geometry in a compressible, inviscid ideal gas with dust particles. The density of the undisturbed region is assumed to vary according to a power law of the distance from the point of explosion. The exact solution of the problem in form of a power in the distance and the time is obtained. Further, the behaviour of the total energy carried out by the blast wave for planar, cylindrically symmetric and spherically symmetric flow corresponding to different Mach number of the fluid flow in dusty gas is presented. It is observed that the presence of dust particles in the gas yields more complex expression as compared to the ordinary Gasdynamics.

Keywords: shock wave, blast wave, dusty gas, strong shock

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Authors: Aron Witkowski, Andrzej Wodecki

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Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

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Authors: Meisam Moghadasi, Hassan Ali Ozgoli, Foad Farhani

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In this research, firstly, a commercial gas sweetening unit with methyl-di-ethanol-amine (MDEA) solution is simulated and comprised in an integrated model in accordance with Aspen HYSYS software. For evaluation purposes, in the second step, the results of the simulation are compared with operating data gathered from South Pars Gas Complex (SPGC). According to the simulation results, the considerable energy potential contributed to the pressure difference between absorber and regenerator columns causes this energy driving force to be applied in power recovery turbine (PRT). In the last step, the amount of waste hydraulic energy is calculated, and its recovery methods are investigated.

Keywords: gas sweetening unit, simulation, MDEA, power recovery turbine, waste-to-energy

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Authors: Pablo J. Valverde, Jaime E. Fernandez

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This paper shows under which conditions public corruption can emerge. The theoretical model includes variables such as the public employee wage (w), a control corruption parameter (c), and the group size of interactions (GS) between clusters of public officers and contractors. The system behavior is analyzed using phase diagrams based on combinations of such parameters (c, w, GS). Numerical simulations are implemented in order to contrast analytic results based on Nash equilibria of the theoretical model. Major findings include the functional relationship between wages and network topology, which attempts to reduce the emergence of corrupt behavior.

Keywords: public corruption, game theory, complex systems, Nash equilibrium.

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Authors: Trisha S. Malhotra

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While there exist frameworks to study the induction, manifestation, duration and general nature of emotions like shame, guilt, embarrassment and pride in humans, the same cannot be said for other species. This is because such 'complex' emotions have situational inductions and manifestations that supposedly vary due to differences between and within different species' ethology. This paper looks at the socio-adaptive functions of guilt to posit why this emotion might be observed across varying species. Primarily, the experimental paradigm of guilt-assessment in domesticated dogs is critiqued for lack of ethological consideration in its measurement and analysis. It is argued that a paradigm for guilt-assessment should measure the species-specific prosocial approach behavior instead of the immediate feedback of the 'guilty'. Finally, it is asserted that the origin of guilt is subjective and if it must be studied across a plethora of species, its definition must be tailored to fit accordingly.

Keywords: guilt, assessment, dogs, prosocial approach behavior, empathy, species, ethology

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Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

Abstract:

Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

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Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

Abstract:

The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

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Authors: Shuhua Lai, Kairui Chen

Abstract:

In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.

Keywords: coarsening, mesh clustering, shape approximation, mesh simplification

Procedia PDF Downloads 380

Authors: Pin-Ling Yin, Dung-Ying Lin

Abstract:

Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: C. Mayr, J. Periya, A. Kariminezhad

Abstract:

In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 245

Authors: Yaser E. Hawas, Md. Didarul Alam

Abstract:

Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.

Keywords: empirical, hitting barrier, in-depth crash investigation, rollover, severe crash

Procedia PDF Downloads 372

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

Procedia PDF Downloads 153