Search results for: time series fractal analysis

Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Sapan Bhatnagar

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Micron size particles emitted from different sources and produced by combustion have serious negative effects on human health and environment. They can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Cascade impactor is used to collect the atmospheric particulates and by gravimetric analysis, their concentration in the atmosphere of different size ranges can be determined. Cascade impactors have been used for the classification of particles by aerodynamic size. They operate on the principle of inertial impaction. It consists of a number of stages each having an impaction plate and a nozzle. Collection plates are connected in series with smaller and smaller cutoff diameter. Air stream passes through the nozzle and the plates. Particles in the stream having large enough inertia impact upon the plate and smaller particles pass onto the next stage. By designing each successive stage with higher air stream velocity in the nozzle, smaller diameter particles will be collected at each stage. Particles too small to be impacted on the last collection plate will be collected on a backup filter. Impactor consists of 4 stages each made of steel, having its cut-off diameters less than 10 microns. Each stage is having collection plates, soaked with oil to prevent bounce and allows the impactor to function at high mass concentrations. Even after the plate is coated with particles, the incoming particle will still have a wet surface which significantly reduces particle bounce. The particles that are too small to be impacted on the last collection plate are then collected on a backup filter (microglass fiber filter), fibers provide larger surface area to which particles may adhere and voids in filter media aid in reducing particle re-entrainment.

Keywords: aerodynamic diameter, cascade, environment, particulates, re-entrainment

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Authors: Nassereddine Attari

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Each operation to strengthen or repair requires special consideration and requires the use of methods, tools and techniques appropriate to the situation and specific problems of each of the constructs. The aim of this paper is to study the pathology of building of reinforced concrete towards the earthquake and the vulnerability assessment using a non-linear Pushover analysis and to develop curves for a medium capacity building in order to estimate the damaged condition of the building.

Keywords: pushover analysis, earthquake, damage, strengthening

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: discrete time, estimation, Kalman filter, Kalman filter gain

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Authors: Ekaterina Malova

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Type 1 diabetes (T1D) is a chronic illness requiring immense lifestyle changes to reduce the chance of life-threatening complications. Moving to a college may be the first time for a young adult with T1D to take responsibility for all the aspects of their diabetes care. In addition, people with T1D constantly face stigmatization and discrimination as a result of their health condition, which puts additional pressure on young adults with T1D. Hence, omissions in diabetes self-care often occur during the time of transition to college when both the social and physical environment of young adults changes drastically and contribute to the fact that emerging young adults remain one of the age groups with the highest hemoglobin levels and poorest diabetes control. However, despite potential severe health risks caused by a lack of proper diabetes self-care, little is known about the experiences of emerging adults embarking on a higher education journey as this population. Thus, young adults with type 1 diabetes are a 'forgotten group,' meaning that their experiences are rarely addressed by researchers. Given that self-disclosure and information-seeking can be challenging for individuals with stigmatized illnesses, online platforms like YouTube have become a popular medium of self-disclosure and information-seeking for people living with T1D. Thus, this study aims to provide an analysis of experiences that college students with T1D choose to share with the general public online and explore the nature of information being communicated by college students with T1D to the online community in personal narratives posted on YouTube. A systematic approach was used to retrieve a video sample by searching YouTube with keywords 'type 1 diabetes' and 'college,' with results ordered by relevance. A total of 18 videos were saved. Video lengths ranged from 2 to 28 minutes. The data were coded using NVivo. Video transcripts were coded and analyzed utilizing the thematic analysis method. Three key themes emerged from thematic analysis: 1) Advice, 2) Personal experience, and 3) Things I wish everyone knew about T1D. In addition, Theme 1 was divided into subtopics to differentiate between the most common types of advice: 1) Overcoming stigma and b) Seeking social support. The identified themes indicate that two groups of the population can potentially benefit from watching students’ video testimonies: 1) lay public and 2) other students with T1D. Given that students in the videos reported a lack of T1D education in the lay public, such video narratives can serve important educational purposes and reduce health stigma, while perceived similarity and identification with students in the videos may facilitate the transition of health information to other individuals with T1D and positively affect their diabetes routine. Thus, online video narratives can potentially serve both educational and persuasive purposes, empowering students with T1D to stay in control of T1D while succeeding academically.

Keywords: type 1 diabetes, college students, health communication, transition period

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Authors: Hyung-Jin Kim, Dae-Wan Kim, Moo-Yeon Lee

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The objective of this study is to experimentally investigate the heat transfer characteristics of 200 W class woofer speaker units with the input voice signals. The temperature and heat transfer characteristics of the 200 W class woofer speaker unit were experimentally tested with the several input voice signals such as 1500 Hz, 2500 Hz, and 5000 Hz respectively. From the experiments, it can be observed that the temperature of the woofer speaker unit including the voice-coil part increases with a decrease in input voice signals. Also, the temperature difference in measured points of the voice coil is increased with decrease of the input voice signals. In addition, the heat transfer characteristics of the woofer speaker in case of the input voice signal of 1500 Hz is 40% higher than that of the woofer speaker in case of the input voice signal of 5000 Hz at the measuring time of 200 seconds. It can be concluded from the experiments that initially the temperature of the voice signal increases rapidly with time, after a certain period of time it increases exponentially. Also during this time dependent temperature change, it can be observed that high voice signal is stable than low voice signal.

Keywords: heat transfer, temperature, voice coil, woofer speaker

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Authors: Iraklis Argyriou

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The transition to net-zero emission urban bus (ZEB) systems is receiving increased attention in research and policymaking throughout the globe. Most studies in this area tend to address techno-economic aspects and the perspectives of a narrow group of stakeholders, while they largely overlook analysis of current bus system dynamics. This offers limited insight into the types of ZEB governance challenges and opportunities that are encountered in real-world contexts, as well as into some of the immediate actions that need to be taken to set off the transition over the longer term. This research offers a multi-stakeholder perspective into both the technical and non-technical factors that influence ZEB transitions within a particular context, the UK. It does so by drawing from a recent transition visioning stakeholder workshop (June 2023) with key public, private and civic actors of the urban bus transportation system. Using NVivo software to qualitatively analyze the workshop discussions, the research examines the key technological and funding aspects, as well as the short-term actions (over the next five years), that need to be addressed for supporting the ZEB transition in UK cities. It finds that ZEB technology has reached a mature stage (i.e., high efficiency of batteries, motors and inverters), but important improvements can be pursued through greater control and integration of ZEB technological components and systems. In this regard, telemetry, predictive maintenance and adaptive control strategies pertinent to the performance and operation of ZEB vehicles have a key role to play in the techno-economic advancement of the transition. Yet, more pressing gaps were identified in the current ZEB funding regime. Whereas the UK central government supports greater ZEB adoption through a series of grants and subsidies, the scale of the funding and its fragmented nature do not match the needs for a UK-wide transition. Funding devolution arrangements (i.e., stable funding settlement deals between the central government and the devolved administrations/local authorities), as well as locally-driven schemes (i.e., congestion charging/workplace parking levy), could then enhance the financial prospects of the transition. As for short-term action, three areas were identified as critical: (1) the creation of whole value chains around the supply, use and recycling of ZEB components; (2) the ZEB retrofitting of existing fleets; and (3) integrated transportation that prioritizes buses as a first-choice, convenient and reliable mode while it simultaneously reduces car dependency in urban areas. Taken together, the findings point to the need for place-based transition approaches that create a viable techno-economic ecosystem for ZEB development but at the same time adopt a broader governance perspective beyond a ‘net-zero’ and ‘bus sectoral’ focus. As such, multi-actor collaborations and the coordination of wider resources and agency, both vertically across institutional scales and horizontally across transport, energy and urban planning, become fundamental features of comprehensive ZEB responses. The lessons from the UK case can inform a broader body of empirical contextual knowledge of ZEB transition governance within domestic political economies of public transportation.

Keywords: net-zero emission transition, stakeholders, transition governance, UK, urban bus transportation

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Authors: Adesoji Sodeinde

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Analytical derivatives has recently undergone an explosive growth in areas of separation techniques, likewise in detectability of certain compound/concentrated ions. The gloomy and depressing scenario which charaterized the application of analytical derivatives in areas of water analysis, water cycle and the environment should not be allowed to continue unabated. Due to technological advancement in various chemical/biochemical analysis separation techniques is widely used in areas of medical, forensic and to measure and assesses environment and social-economic impact of alternative control strategies. This technological improvement was dully established in the area of comparison between certain separation/detection techniques to bring about vital result in forensic[as Gas liquid chromatography reveals the evidence given in court of law during prosecution of drunk drivers]. The water quality analysis,pH and water temperature analysis can be performed in the field, the concentration of dissolved free amino-acid [DFAA] can also be detected through separation techniques. Some important derivatives/ions used in separation technique. Water analysis : Total water hardness [EDTA to determine ca and mg ions]. Gas liquid chromatography : innovative gas such as helium [He] or nitrogen [N] Water cycle : Animal bone charcoal,activated carbon and ultraviolet light [U.V light].

Keywords: analytical derivative, environment, water analysis, chemical/biochemical analysis

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Authors: Tania Ali Soomro

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In 1839, the British, after the annexation of the port city of Karachi, established a new urban centre consisting of various quarters and introduced new settlements there. These quarters were out of the boundaries of fortified native old area and now contain much of the oldest parts of the city and signify the colonial history of Karachi, in particular the Saddar Bazaar and the neighboring areas of Kharadar and Mithadar. These quarters bestow a mix of functional typology built in a hybrid form of construction - an adaptation of the western architectural attributes to regional requirements and characteristics. This approach is referred to as the Anglo Vernacular, Colonial or the Domestic Gothic architectural form. This research paper investigates the historical and architectural value of one such property: the Empress Market designed by then Municipal Architect, Ar. James Strachan in 1889 as a commemorative monument for the jubilee of Her Majesty the Queen Victoria; Empress of British India, at that time. This paper presents information on the present conservation status of the market building and highlights its role as a catalyst to the community interconnection. This building has survived to present day and functioned well, despite undergoing numerous transformations. A detailed analysis of the bio-degradation (Natural-Chemical dissolution of material) and the bio-deterioration (Manmade-Negative state change of the material) of the building, based on the examination of the prevailing causes of these bio-alterations is carried out, and is presented in form of a damage atlas containing both the categories of bio-alteration/ changes occurred to the building over the time. The research methodology followed in this paper starts with the available archival analysis, physical observation, photographic documentation, the statistics review and the interviews with the direct and indirect stakeholders. The results and findings of this research portray that these bio-alterations and changes are the essential part of the life cycle of Empress Market building which illustrate the historic development of the premise and therefore ought to be given due importance (depending upon their condition) while developing the conservation plan for the building.

Keywords: British colonial architecture, bio-alteration, bio-degradation, bio-deterioration, domestic gothic architectural form

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Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi

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Nowadays, athletic aggression discussion is considered as an important issue in sports psychology and sports effects have been noted by researchers from a long time ago. In this research, the amount of aggression among athletic students of different sport courses will be surveyed and compared. Statistics society in this research consists of all of boy athletic students in wrestling, taekwondo, football, and basketball of Mahmoudabad City that are 200 persons and the limitation of their ages are between 12-15 years old. Among all athletic students of different sport courses, 40 persons were chosen randomly for the sample. The method of research is a descriptive-comparative type that has been done according to field study and for measurement of examinations aggression amount, we have used Ayzank exam. In analysis step of foundations, for comparison of aggression of examined group, we have used Varian’s analysis exam. Research results show that among aggression amounts of athletic students of wrestling, taekwondo, football and basketball, there is no fundamental difference (p < 0.05). Stimulation of guest team with the host team fans, referees performance, exhaustion, physical confrontations, team position in the tournament table, and so on. There is no significant difference among aggression amount of selected sport athletic students.

Keywords: aggression, athletic, student, sports

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Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

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Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

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Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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Authors: Jurriaan Gillissen

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This work is concerned with stabilizing the numerical integration of the Navier-Stokes equation (NSE), backwards in time. Applications involve the detection of sources of, e.g., sound, heat, and pollutants. Stable reverse numerical integration of parabolic differential equations is also relevant for image de-blurring. While the literature addresses the reverse integration problem of the advection-diffusion equation, the problem of numerical reverse integration of the NSE has, to our knowledge, not yet been addressed. Owing to the presence of viscosity, the NSE is irreversible, i.e., when going backwards in time, the fluid behaves, as if it had a negative viscosity. As an effect, perturbations from the perfect solution, due to round off errors or discretization errors, grow exponentially in time, and reverse integration of the NSE is inherently unstable, regardless of using an implicit time integration scheme. Consequently, some sort of filtering is required, in order to achieve a stable, numerical, reversed integration. The challenge is to find a filter with a minimal adverse affect on the accuracy of the reversed integration. In the present work, we explore an adjoint gradient method (AGM) to achieve this goal, and we apply this technique to two-dimensional (2D), decaying turbulence. The AGM solves for the initial velocity field u0 at t = 0, that, when integrated forward in time, produces a final velocity field u1 at t = 1, that is as close as is feasibly possible to some specified target field v1. The initial field u0 defines a minimum of a cost-functional J, that measures the distance between u1 and v1. In the minimization procedure, the u0 is updated iteratively along the gradient of J w.r.t. u0, where the gradient is obtained by transporting J backwards in time from t = 1 to t = 0, using the adjoint NSE. The AGM thus effectively replaces the backward integration by multiple forward and backward adjoint integrations. Since the viscosity is negative in the adjoint NSE, each step of the AGM is numerically stable. Nevertheless, when applied to turbulence, the AGM develops instabilities, which limit the backward integration to small times. This is due to the exponential divergence of phase space trajectories in turbulent flow, which produces a multitude of local minima in J, when the integration time is large. As an effect, the AGM may select unphysical, noisy initial conditions. In order to improve this situation, we propose two remedies. First, we replace the integration by a sequence of smaller integrations, i.e., we divide the integration time into segments, where in each segment the target field v1 is taken as the initial field u0 from the previous segment. Second, we add an additional term (regularizer) to J, which is proportional to a high-order Laplacian of u0, and which dampens the gradients of u0. We show that suitable values for the segment size and for the regularizer, allow a stable reverse integration of 2D decaying turbulence, with accurate results for more then O(10) turbulent, integral time scales.

Keywords: time reversed integration, parabolic differential equations, adjoint gradient method, two dimensional turbulence

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Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

Procedia PDF Downloads 86

Authors: O. O. Sufyani, M. E. Oraiby, S. A. Qumaiy, A. I. Alaamri, Z. M. Eisa, A. M. Hakami, M. A. Attafi, O. M. Alhassan, W. M. Elsideeg, E. M. Noureldin, Y. A. Hobani, Y. Q. Majrabi, I. A. Khardali, A. B. Maashi, A. A. Al Mane, A. H. Hakami, I. M. Alkhyat, A. A. Sahly, I. M. Attafi

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According to the Food and Agriculture Organization (FAO) Pesticides Use Database, pesticide use in agriculture in Saudi Arabia has more than doubled from 4539 tons in 2009 to 10496 tons in 2019. Among pesticides, pyrethroids is commonly used in Saudi Arabia. Pesticides may increase susceptibility to a variety of diseases, particularly among pesticide workers, due to their extensive use, indiscriminate use, and long-term exposure. Therefore, analyzing blood chemo-profiles and evaluating the detected substances as biomarkers for pyrethroid pesticide exposure may assist to identify and predicting adverse effects of exposure, which may be used for both preventative and risk assessment purposes. The purpose of this study was to (a) analyze chemo-profiling by Gas Chromatography-Mass Spectrometry (GC-MS) analysis, (b) identify the most commonly detected chemicals in a time-exposure-dependent manner using a Venn diagram, and (c) identify their associated disease among pesticide workers using analyzer tools on the Comparative Toxicogenomics Database (CTD) website, (250 healthy male volunteers (20-60 years old) who deal with pesticides in the Jazan region of Saudi Arabia (exposure intervals: 1-2, 4-6, 6-8, more than 8 years) were included in the study. A questionnaire was used to collect demographic information, the duration of pesticide exposure, and the existence of chronic conditions. Blood samples were collected for biochemistry analysis and extracted by solid-phase extraction for gas chromatography-mass spectrometry (GC-MS) analysis. Biochemistry analysis reveals no significant changes in response to the exposure period; however, an inverse association between the albumin level and the exposure interval was observed. The blood chemo-profiling was differentially expressed in an exposure time-dependent manner. This analysis identified the common chemical set associated with each group and their associated significant occupational diseases. While some of these chemicals are associated with a variety of diseases, the distinguishing feature of these chemically associated disorders is their applicability for prevention measures. The most interesting finding was the identification of several chemicals; erucic acid, pelargonic acid, alpha-linolenic acid, dibutyl phthalate, diisobutyl phthalate, dodecanol, myristic Acid, pyrene, and 8,11,14-eicosatrienoic acid, associated with pneumoconiosis, asbestosis, asthma, silicosis and berylliosis. Chemical-disease association study also found that cancer, digestive system disease, nervous system disease, and metabolic disease were the most often recognized disease categories in the common chemical set. The hierarchical clustering approach was used to compare the expression patterns and exposure intervals of the chemicals found commonly. More study is needed to validate these chemicals as early markers of pyrethroid insecticide-related occupational disease, which might assist evaluate and reducing risk. The current study contributes valuable data and recommendations to public health.

Keywords: occupational, toxicology, chemo-profiling, pesticide, pyrethroid, GC-MS

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Authors: J. R. Wang, S. W. Chen, Y. Chiang, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT analysis methodology was established for Maanshan nuclear power plant (NPP). The Final Safety Analysis Report (FSAR), reports, and other data were used in this study. To evaluate the control room habitability under the CO₂ storage burst, the HABIT methodology was used to perform this analysis. The HABIT result was below the R.G. 1.78 failure criteria. This indicates that Maanshan NPP habitability can be maintained. Additionally, the sensitivity study of the parameters (wind speed, atmospheric stability classification, air temperature, and control room intake flow rate) was also performed in this research.

Keywords: PWR, HABIT, Habitability, Maanshan

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Srikanth Pandurangi, Basheer Mohammed, Nezar Al Sayegh

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In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.

Keywords: innovative methods in transportation data collection, integrated public transportation system, traffic forecasts, transportation modeling, travel behavior

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Authors: Ikram Hussain, Fuzail Ahmad, Tawseef Ahmad Bhat

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Tennis serve is characterized as one of the most prominent techniques pertaining to the success of winning a point. The study was aimed to explore the contributions of the upper body kinematics on the tennis performance during Davis Cup (Oceania Group). Four Indian International tennis players who participated in the Davis Cup held at Indore, India were inducted as the subjects for this study, with mean age 27 ± 4.79 Years, mean weight 186 ± 6.03 cm, mean weight 81.25 ± 7.41kg, respectively. The tennis serve was bifurcated into three phases viz, preparatory phase, force generation phase and follow through phase. The kinematic data for the study was recorded through the high speed canon camcorder having a shuttle speed of 1/2000, at a frame rate of 50 Hz. The data was analysed with the motion analysis software. The descriptive statistics and F-test was employed through SPSS version 17.0 for the determination of the undertaken kinematic parameters of the study, and was computed at a 0.05 level of significance with 46 degrees of freedom. Mean, standard deviation and correlation coefficient also employed to find out the relationship among the upper body kinematic parameter and performance. In the preparatory phase, the analysis revealed that no significant difference exists among the kinematic parameters of the players on the performance. However, in force generation phase, wrist velocity (r= 0.47), torso velocity (r= -0.53), racket velocity r= 0.60), and in follow through phase, torso acceleration r= 0.43), elbow angle (r= -0.48) play a significant role on the performance of the tennis serve. Therefore, players should ponder upon the velocities of the above segments at the time of preparation for the competitions.

Keywords: Davis Cup, kinematics, motion analysis, tennis serve

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Authors: Hyeondal Jeong, Yoonjung Baek

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This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: positive psychological capital , satisfaction, commitment, OCB, creativity, meta-analysis

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Authors: Merle Talvik, Taimi Tulva, Kristi Puusepp, Ulle Ernits

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Background data. This is a study in the field of health humanities. The 1930s were years of rapid cultural and economic development in Europe and in Estonia. The urban way of life the glamorous lifestyle gained popularity, although the society of Estonia in the 1930s had traditionally been agrarian. People's free time increased, which needed to be filled with activities either at home or outside the home. Therefore, the number of popular magazines aimed at housewives increased. More than 200 magazines and bulletins were published in the Republic of Estonia before the Second World War (in 1934, the population of Estonia was 1,126,000). In the 1930s, the Republic of Estonia faced several challenges in healthcare. Infectious diseases, alcoholism, prostitution and child mortality had to be dealt with. Healers without medical education operated in the villages. For the average person, medical care was quite expensive, and despite efforts, by 1940, only 20% of the population was covered by health insurance. Advice published in popular family magazines provided help in solving, understanding and preventing health problems. Aim. The aim of the study is to analyze the health counseling through magazines during the Republic of Estonia (1930-1940) in historical and cultural context. Method. In total, 420 magazine issues were processed. An extensive textual analysis, as well as an analysis of photographs and illustrations from the aspect of health advice was carried out to achieve the research objective. Results. Health counseling was written by well-known doctors of the time, leaders of the abstinence movement and others. There was advice in various areas: prevention of infectious and non-infectious diseases and their treatment with simple methods, first aid, combating sexually transmitted diseases, women's and children's health, mental health, folk medicine techniques, abstinence, healthy eating, skin care, hygiene, introducing pharmacy products. Advice was offered in both written and visual form. Photos and illustrations helped to empower the health advice. Folk heritage and health knowledge of the time were relied upon, and a scientific point of view was popularized. Aspirations towards a European lifestyle were reflected in articles and illustrations. Contribution. The article has an ethnological attitude, and its impact comes down to understanding the history of health care in its socio-cultural context. The health counseling topics of the 1930s are also applicable in today's health education and research. Health counseling builds on the legacy of the past, and it helps to understand that the past is in the future and the main principles of health counseling arise from our history and background.

Keywords: estonian republic, health counseling, lifestyle, magazines, media

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Authors: Inas Hussein

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Alice Munro is a Canadian short-story writer who has been regarded as one of the greatest writers of fiction. Owing to her great contribution to fiction, she was the first Canadian woman and the only short-story writer ever to be rewarded the Nobel Prize for Literature in 2013. Her literary works include collections of short stories and one book published as a novel. Her stories concentrate on the human condition and the human relationships as seen through the lens of daily life. The setting in most of her stories is her native Canada- small towns much similar to the one where she grew up. Her writing style is not only realistic but is also characterized by autobiographical, historical and regional features. The aim of this research is to analyze one of the key stylistic devices often adopted by Munro in her fictions: the juxtaposition of the past and the present, with reference to the title story in Munro's short story collection Too Much Happiness. The story under exploration is a brief biography of the Russian Mathematician and novelist Sophia Kovalevsky (1850 – 1891), the first woman to be appointed as a professor of Mathematics at a European University in Stockholm. Thus, the story has a historical protagonist and is set on the European continent. Munro dramatizes the severe historical and cultural constraints that hindered the career of the protagonist. A pragmatic stylistic framework is being adopted and the qualitative analysis is supported by textual reference. The stylistic analysis reveals that the juxtaposition of the past and the present is one of the distinctive features that characterize the author; in a typical Munrovian manner, the protagonist often moves between the units of time: the past, the present and, sometimes, the future. Munro's style is simple and direct but cleverly constructed and densely complicated by the presence of deeper layers and stories within the story. Findings of the research reveal that the story under investigation merits reading and analyzing. It is recommended that this story and other stories by Munro are analyzed to further explore the features of her art and style.

Keywords: Alice Munro, Too Much Happiness, style, stylistic analysis

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Authors: R. C. Sharma, Rishabh Bansal, Prajwal Menon, Manoj K. Sharma

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Silicon-air battery is highly promising for electric vehicles due to its high theoretical energy density (8470 Whkg⁻¹) and its discharge products are non-toxic. For the first time, pure silicon and germanium powders are used as anode material. Nickel wire meshes embedded with charcoal and manganese dioxide powder as cathode and concentrated potassium hydroxide is used as electrolyte. Voltage-time curves have been presented in this study for pure silicon and germanium powder and 5% and 10% germanium with silicon powder. Silicon powder cell assembly gives a stable voltage of 0.88 V for ~20 minutes while Si-Ge provides cell voltage of 0.80-0.76 V for ~10-12 minutes, and pure germanium cell provides cell voltage 0.80-0.76 V for ~30 minutes. The cell voltage is higher for concentrated (10%) sodium hydroxide solution (1.08 V) and it is stable for ~40 minutes. A sharp decrease in cell voltage beyond 40 min may be due to rapid corrosion.

Keywords: Silicon-air battery, Germanium-air battery, voltage-time curve, open circuit voltage, Anodic corrosion

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Authors: Yen-Luan Chen

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Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

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Authors: Iveta Řepková

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The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: data envelopment analysis, efficiency, Slovak banking sector, window analysis

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Authors: Asfaw Gezae Daful, Mohsen Alimandagari, Kathleen Haigh, Somayeh Farzad, Eugene Van Rensburg, Johann F. Görgens

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The sugar industry has to 're-invent' itself to ensure long-term economic survival and opportunities for job creation and enhanced community-level impacts, given increasing pressure from fluctuating and low global sugar prices, increasing energy prices and sustainability demands. We propose biorefineries for re-vitalisation of the sugar industry using low value lignocellulosic biomass (sugarcane bagasse, leaves, and tops) annexed to existing sugar mills, producing a spectrum of high value platform chemicals along with biofuel, bioenergy, and electricity. Opportunity is presented for greener products, to mitigate climate change and overcome economic challenges. Xylose from labile hemicellulose remains largely underutilized and the conversion to value-add products a major challenge. Insight is required on pretreatment and/or extraction to optimize production of cellulosic ethanol together with lactic acid, furfural or biopolymers from sugarcane bagasse, leaves, and tops. Experimental conditions for alkaline and pressurized hot water extraction dilute acid and steam explosion pretreatment of sugarcane bagasse and harvest residues were investigated to serve as a basis for developing various process scenarios under a sugarcane biorefinery scheme. Dilute acid and steam explosion pretreatment were optimized for maximum hemicellulose recovery, combined sugar yield and solids digestibility. An optimal range of conditions for alkaline and liquid hot water extraction of hemicellulosic biopolymers, as well as conditions for acceptable enzymatic digestibility of the solid residue, after such extraction was established. Using data from the above, a series of energy efficient biorefinery scenarios are under development and modeled using Aspen Plus® software, to simulate potential factories to better understand the biorefinery processes and estimate the CAPEX and OPEX, environmental impacts, and overall viability. Rigorous and detailed sustainability assessment methodology was formulated to address all pillars of sustainability. This work is ongoing and to date, models have been developed for some of the processes which can ultimately be combined into biorefinery scenarios. This will allow systematic comparison of a series of biorefinery scenarios to assess the potential to reduce negative impacts on and maximize the benefits of social, economic, and environmental factors on a lifecycle basis.

Keywords: biomass, biorefinery, green economy, sustainability

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Authors: Rupali, Anil Kumar Jaiswal

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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model

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Authors: Ebru Turgal, Beyza Doganay Erdogan

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Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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Authors: Biswanath Swain

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Ethical relativism, as an ethical perspective, holds that moral worth of a course of action is dependent on a particular space and time. Moral rightness or wrongness of a course of action varies from space to space and from time to time. In short, ethical relativism holds that morality is relative to the context. If we reflect conscientiously on the scope of this perspective, we will find that it is wide-spread amongst the marketers involved in the offshore business. However, the irony is that most of the marketers gone along with ethical relativism in their offshore business have been found to be unsuccessful in terms of loss in market-share and bankruptcy. The upshot is purely self-defeating in nature for the marketers. GSK in China and Nestle Maggi in India are some of the burning examples of that sort. The paper argues and recommends that a marketer, as an alternative, should have recourse to Kantian ethical perspective to deliberate courses of action sensitive to offshore business as Kantian ethical perspective is logically and methodologically sound in nature.

Keywords: business, course of action, Kant, morality, offshore, relativism

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