Search results for: cuckoo search optimization

Authors: Aleksander Mendoza

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Glushkov's construction has many interesting properties, and they become even more evident when applied to transducers. This article strives to show the vast range of possible extensions and optimisations for this algorithm. Special flavour of regular expressions is introduced, which can be efficiently converted to e-free functional subsequential weighted finite state transducers. Produced automata are very compact, as they contain only one state for each symbol (from input alphabet) of original expression and only one transition for each range of symbols, no matter how large. Such compactified ranges of transitions allow for efficient binary search lookup during automaton evaluation. All the methods and algorithms presented here were used to implement open-source compiler of regular expressions for multitape transducers.

Keywords: weighted automata, transducers, Glushkov, follow automata, regular expressions

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Authors: Okorowo Cyril Agochi

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The main challenge of present world is to harness the energy source which is environment friendly and ecologically balanced. This need has forced to search for other alternate source of energy. But unfortunately the new alternative energy sources like the solar, hydro, wind etc. require huge economical value and technical power to operate, which seem to be very difficult for the developing countries like Nigeria. In the present moment biogas energy can be one and only reliable, easily available and economically feasible source of alternative and renewable source which can be managed by locally available sources and simple technology for secondary schools, tertiary institution and rural villages. This paper is aimed at boosting the energy generation for developing of rural Nigeria, through Biogas.

Keywords: bio-gas, energy, environment, nigeria, technology

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Authors: Sharon K. O'Kelley

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At the heart of mathematics education is the concept of communication which many teachers envision as the influential dialogue they conduct with their students. However, communication in the mathematics classroom operates in different forms at different levels, both externally and internally. Specifically, it can be a central component in the building of critical thinking skills that requires students not only to know how to communicate their solutions to others but that they also be able to navigate their own thought processes in search of those solutions. This paper provides a review of research on the role of communication in the building of critical thinking skills in mathematics with a focus on the problem-solving process and the implications this interplay has for the teaching and learning of mathematics.

Keywords: communication in mathematics, critical thinking skills, mathematics education, problem-solving process

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Authors: Anne Prip, Kirsten Alling Møller, Dorte Lisbet Nielsen, Mary Jarden, Marie-Helene Olsen, Anne Kjaergaard Danielsen

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Background: The development in cancer care has shifted towards shorter hospital stays and more outpatient treatment. Today, cancer care and treatment predominantly takes place in outpatient settings where encounters between patients and health care professionals are often brief. This development will probably continue internationally as the global cancer burden seems to be growing significantly. Furthermore, the number of patients who require ambulatory treatments such as chemotherapy is increasing. Focusing on the encounters between health care professionals and patients during oncology treatment has thus become increasingly important due to a growing trend in outpatient cancer management. Objective: The aim of the systematic review was to summarize the literature from the perspective of the patient, on experiences of and the need for communication and relationships with the health care professional during chemotherapy treatment in an outpatient setting. Method: The review was designed and carried out according to the PRISMA guidelines and PICO framework. The systematic search was conducted in Medline, CINAHL, The Cochrane Library and Joanna Briggs Institute Evidence Based Practice Database. Results: In all, 1174 studies were identified by literature search. After duplicates were removed, the remaining studies (n = 1053) were screened for inclusion. Nine studies were included; qualitative (n = 5) and quantitative (n = 4) as they met the inclusions criteria. The review identified that communication and relationships between health care professionals and patients were important for the patients’ ability to cope with cancer and also had an impact on patients’ satisfaction with care in the outpatient clinic. Furthermore, the review showed that hope and positivity was a need and strategy for patients with cancer and was facilitated by health care professionals. Finally, it revealed that outpatient clinic visits framed and influenced communication and relationships. Conclusions: This review identified the significance of communication and the relationships between patients and health care professionals in the outpatient setting as it supports patients’ ability to cope with cancer. The review showed the need for health care professionals to pay attention to the relational aspects of communication in an outpatient clinic as encounters are often brief. Furthermore, the review helps to specify which elements of the communication are central in the patient-health care professional interaction from the patients' perspective. Finally, it shows a need for more research to investigate which type of interaction and intervention would be the most effective in supporting patients’ coping during chemotherapy in an outpatient clinic.

Keywords: ambulatory chemotherapy, communication, health care professional-patient relation, nurse-patient relation, outpatient care, systematic review

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Authors: Parul Khanna, Pavol Zavarsky, Dale Lindskog

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Doxing is a term derived from documents, and hence consists of collecting information on an organization or individual through social media websites, search engines, password cracking methods, social engineering tools and other sources of publicly displayed information. The main purpose of doxing attacks is to threaten, embarrass, harass and humiliate the organization or individual. Various tools are used to perform doxing. Tools such as Maltego visualize organization’s architecture which helps in determining weak links within the organization. This paper discusses limitations of Maltego Chlorine CE 3.6.0 and suggests measures as to how organizations can use these tools to protect themselves from doxing attacks.

Keywords: advanced persistent threat, FOCA, OSINT, PII

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Authors: Daniil Karzanov

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This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: Gianvito Colucci, Valeria Di Cosmo, Matteo Nicoli, Orsola Maria Robasto, Laura Savoldi

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The hydrogen value chain deployment is likely to be boosted in the near term by the energy security measures planned by European countries to face the recent energy crisis. In this context, some countries are recognized to have a crucial role in the geopolitics of hydrogen as importers, consumers and exporters. According to the European Hydrogen Backbone Initiative, Italy would be part of one of the 5 corridors that will shape the European hydrogen market. However, the set targets are very ambitious and require large investments to rapidly develop effective hydrogen policies: in this regard, scenario analysis is becoming increasingly important to support energy planning, and energy system optimization models appear to be suitable tools to quantitively carry on that kind of analysis. The work aims to assess the competitiveness of hydrogen in contributing to the Italian energy security in the coming years, under different price and import conditions, using the energy system model TEMOA-Italy. A wide spectrum of hydrogen technologies is included in the analysis, covering the production, storage, delivery, and end-uses stages. National production from fossil fuels with and without CCS, as well as electrolysis and import of low-carbon hydrogen from North Africa, are the supply solutions that would compete with other ones, such as natural gas, biomethane and electricity value chains, to satisfy sectoral energy needs (transport, industry, buildings, agriculture). Scenario analysis is then used to study the competition under different price and import conditions. The use of TEMOA-Italy allows the work to catch the interaction between the economy and technological detail, which is much needed in the energy policies assessment, while the transparency of the analysis and of the results is ensured by the full accessibility of the TEMOA open-source modeling framework.

Keywords: energy security, energy system optimization models, hydrogen, natural gas, open-source modeling, scenario analysis, TEMOA

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Authors: Ruhollah Basatnia, Ali Reza Aghababa, Mehrdad Anbarian, Sara Akbari, Mohammad Khazaee

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Introduction: The investigation of brain activity in sports has become a subject of interest for researchers. Several studies have examined the patterns or differences in brain activity during different sports situations. Previous studies have suggested that the pattern of cortical activity may differ between different football positions, such as goalkeepers and other players. This study aims to investigate the differences in electroencephalographic (EEG) activity between the positions of goalkeeper and forward in professional football players. Methods: Fourteen goalkeepers and twelve forwards, all males between 19-28 years old, participated in the study. EEG activity was recorded while participants were sitting with their eyes closed for 5 minutes. The mean relative power of EEG activity for each frequency band was compared between the two groups using independent samples t-test. Findings: The study found significant differences in the relative power of EEG activity between different frequency bands and electrodes. Notably, significant differences were observed in the mean relative power of EEG activity between the two groups for certain frequency bands and electrodes. These findings suggest that EEG activity can serve as a sensory indicator for cognitive and performance differences between goalkeepers and forwards in football players. Discussion: The results of this study suggest that EEG activity can be used to identify cognitive and performance differences between goalkeepers and forwards in football players. However, further research is needed to establish the relationship between EEG activity and actual performance in the field. Future studies should investigate the potential influence of other factors, such as fatigue and stress, on the EEG activity of football players. Additionally, the use of real-time EEG feedback could be explored as a tool for training and performance optimization in football players. Further research is required to fully understand the potential of EEG activity as a sensory indicator for cognitive and performance differences between football player positions and to explore its potential applications for training and performance optimization in football and other sports.

Keywords: football, brain activity, EEG, goalkeepers, forwards

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Authors: Zouhour Neji Ben Salem

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Microscopic evacuation focuses on the evacuee behavior and way of search of safety place in an egress situation. In recent years, several models handled microscopic evacuation problem. Among them, we have proposed Artificial Neural Network (ANN) as an alternative to mathematical models that can deal with such problem. In this paper, we present two ANN models: SOM map and Hopfield Network used to predict the evacuee behavior in a disaster situation. These models are tested in a real case, the second floor of Tunisian children hospital evacuation in case of fire. The two models are studied and compared in order to evaluate their performance.

Keywords: artificial neural networks, self-organization map, hopfield network, microscopic evacuation, fire building evacuation

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Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: Jesus David Argueta Moreno, Justa Rufina Martel, Edith Gabriela Carrasco

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The Central American Coffee small, medium, and large corporations search for excellence, sustainability, and continuous improvement, triggers in a still unknown scale the Local expansion, crusading, and franchising strategies towards a more suitable commercial opportunity, where the dynamics of the Central American business displacement can be explained through the markets permeability traits. By considering the previously mentioned, the present study aims to evaluate the franchising potentialities offered by Central American Coffee business scenario, in order to explain dynamics of the business demography phenomena and its relevance on the Central American competitiveness landscape.

Keywords: competitiveness, franchising, business demography, Central American Coffee

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Authors: Rianne Voet

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This paper uses a literature review to search for keys of success for entrepreneurial regional media collaborations in the Netherlands and elsewhere. It specifies keys on general aspects: a digital-first strategy, innovation, a particular journalistic mission and a new role for the public. It outlines keys in practicalities: competencies, revenue model, legal structure, communication structure and organization structure. The paper elaborates on a new public function and a new concept of citizenship which, according to several authors in the literature, are required in order to be successful. Finally, it offers a model of keys for success in regional entrepreneurial media collaboration.

Keywords: media collaboration, factors of success, keys of success, regional media cooperation

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Authors: Muhammad Isa Khan, Jalil Ur Rehman, Muhammad Afzal Khan Rao, James Chow

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Purpose: This study investigates the dose-volume variations in planning target volume (PTV) and organs-at-risk (OARs) using different collimator angles for smart arc prostate volumetric modulated arc therapy (VMAT). Awareness of the collimator angle for PTV and OARs sparing is essential for the planner because optimization contains numerous treatment constraints producing a complex, unstable and computationally challenging problem throughout its examination of an optimal plan in a rational time. Materials and Methods: Single arc VMAT plans at different collimator angles varied systematically (0°-90°) were performed on a Harold phantom and a new treatment plan is optimized for each collimator angle. We analyzed the conformity index (CI), homogeneity index (HI), gradient index (GI), monitor units (MUs), dose-volume histogram, mean and maximum doses to PTV. We also explored OARs (e.g. bladder, rectum and femoral heads), dose-volume criteria in the treatment plan (e.g. D30%, D50%, V30Gy and V38Gy of bladder and rectum; D5%,V14Gy and V22Gy of femoral heads), dose-volume histogram, mean and maximum doses for smart arc VMAT at different collimator angles. Results: There was no significance difference found in VMAT optimization at all studied collimator angles. However, if 0.5% accuracy is concerned then collimator angle = 45° provides higher CI and lower HI. Collimator angle = 15° also provides lower HI values like collimator angle 45°. It is seen that collimator angle = 75° is established as a good for rectum and right femur sparing. Collimator angle = 90° and collimator angle = 30° were found good for rectum and left femur sparing respectively. The PTV dose coverage statistics for each plan are comparatively independent of the collimator angles. Conclusion: It is concluded that this study will help the planner to have freedom to choose any collimator angle from (0°-90°) for PTV coverage and select a suitable collimator angle to spare OARs.

Keywords: VMAT, dose-volume histogram, collimator angle, organs-at-risk

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Authors: Basavaraj R. Endigeri, S. G. Sarganachari

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Steel is widely used in machine parts, structural equipment and many other applications. In many steel structural elements, holes of different shapes and orientations are made with a view to satisfy the design requirements. The presence of holes in steel elements creates stress concentration, which eventually reduce the mechanical strength of the structure. Therefore, it is of great importance to investigate the state of stress around the holes for the safety and properties design of such elements. By literature survey, it is known that till date, there is no analytical solution to reduce the stress concentration by providing auxiliary holes at a definite location and radii in a steel plate. The numerical method can be used to determine the optimum location and radii of auxiliary holes. In the present work plate with an elliptical hole, for a steel material subjected to uniaxial load is analyzed and the effect of stress concentration is graphically represented .The introduction of auxiliary holes at a optimum location and radii with its effect on stress concentration is also represented graphically. The finite element analysis package ANSYS 11.0 is used to analyse the steel plate. The analysis is carried out using a plane 42 element. Further the ANSYS optimization model is used to determine the location and radii for optimum values of auxiliary hole to reduce stress concentration. All the results for different diameter to plate width ratio are presented graphically. The results of this study are in the form of the graphs for determining the locations and diameter of optimal auxiliary holes. The graph of stress concentration v/s central hole diameter to plate width ratio. The Finite Elements results of the study indicates that the stress concentration effect of central elliptical hole in an uniaxial loaded plate can be reduced by introducing auxiliary holes on either side of the central circular hole.

Keywords: finite element method, optimization, stress concentration factor, auxiliary holes

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Authors: Giovanna Grosso, Martien A. Hulsen, Arash Sarhangi Fard, Andrew Overend, Patrick. D. Anderson

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In many industrial applications and, in particular in polymer industry, the quality of mixing between different materials is fundamental to guarantee the desired properties of finished products. However, properly modelling and understanding polymer mixing often presents noticeable difficulties, because of the variety and complexity of the physical phenomena involved. This is the case of the Cavity Transfer Mixer (CTM), for which a clear understanding of mixing mechanisms is still missing, as well as clear guidelines for the system optimization. This device, invented and patented by Gale at Rapra Technology Limited, is an add-on to be mounted downstream of existing extruders, in order to improve distributive mixing. It consists of two concentric cylinders, the rotor and stator, both provided with staggered rows of hemispherical cavities. The inner cylinder (rotor) rotates, while the outer (stator) remains still. At the same time, the pressure load imposed upstream, pushes the fluid through the CTM. Mixing processes are driven by the flow field generated by the complex interaction between the moving geometry, the imposed pressure load and the rheology of the fluid. In such a context, the present work proposes a complete and accurate three dimensional modelling of the CTM and results of a broad range of simulations assessing the impact on mixing of several geometrical and functioning parameters. Among them, we find: the number of cavities per row, the number of rows, the size of the mixer, the rheology of the fluid and the ratio between the rotation speed and the fluid throughput. The model is composed of a flow part and a mixing part: a finite element solver computes the transient velocity field, which is used in the mapping method implementation in order to simulate the concentration field evolution. Results of simulations are summarized in guidelines for the device optimization.

Keywords: Mixing, non-Newtonian fluids, polymers, rheology.

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Authors: Mustafa Alshawaqfeh, Bilal Wajidy, Echin Serpedin, Jan Suchodolski

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Inflammatory Bowel disease (IBD) is a disease of the colon with characteristic inflammation. Clinically IBD is detected using laboratory tests (blood and stool), radiology tests (imaging using CT, MRI), capsule endoscopy and endoscopy. There are two variants of IBD referred to as Ulcerative Colitis (UC) and Crohn’s disease. This study employs a hybrid feature selection method that combines a correlation-based variable ranking approach with exhaustive search wrapper methods in order to find potential biomarkers for UC. The proposed biomarkers presented accurate discriminatory power thereby identifying themselves to be possible ingredients to UC therapeutics.

Keywords: ulcerative colitis, biomarker detection, feature selection, inflammatory bowel disease (IBD)

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Authors: Thomas S. Abia II, Citlali Garcia-Saucedo

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A continuous copper precipitation treatment (CCPT) system was conceived at Intel Chandler Site to serve as a first-of-kind (FOK) facility-scale waste copper (Cu), nickel (Ni), and manganese (Mn) co-precipitation facility. The process was designed to treat highly variable wastewater discharged from a substrate packaging research factory. The paper discusses metals co-precipitation induced by internal changes for manufacturing facilities that lack the capacity for hardware expansion due to real estate restrictions, aggressive schedules, or budgetary constraints. Herein, operating parameters such as pH and oxidation reduction potential (ORP) were examined to analyze the ability of the CCPT System to immobilize various waste metals. Additionally, influential factors such as influent concentrations and retention times were investigated to quantify the environmental variability against system performance. A total of 2,027 samples were analyzed and statistically evaluated to measure the performance of CCPT that was internally retrofitted for Mn abatement to meet environmental regulations. In order to enhance the consistency of the influent, a separate holding tank was cannibalized from another system to collect and slow-feed the segregated Mn wastewater from the factory into CCPT. As a result, the baseline influent Mn decreased from 17.2+18.7 mg¹L^-1 at pre-pilot to 5.15+8.11 mg¹L^-1 post-pilot (70.1% reduction). Likewise, the pre-trial and post-trial average influent Cu values to CCPT were 52.0+54.6 mg¹L^-1 and 33.9+12.7 mg¹L^-1, respectively (34.8% reduction). However, the raw Ni content of 0.97+0.39 mg¹L^-1 at pre-pilot increased to 1.06+0.17 mg¹L^-1 at post-pilot. The average Mn output declined from 10.9+11.7 mg¹L^-1 at pre-pilot to 0.44+1.33 mg¹L^-1 at post-pilot (96.0% reduction) as a result of the pH and ORP operating setpoint changes. In similar fashion, the output Cu quality improved from 1.60+5.38 mg¹L^-1 to 0.55+1.02 mg¹L^-1 (65.6% reduction) while the Ni output sustained a 50% enhancement during the pilot study (0.22+0.19 mg¹L^-1 reduced to 0.11+0.06 mg¹L^-1). pH and ORP were shown to be significantly instrumental to the precipitative versatility of the CCPT System.

Keywords: copper, co-precipitation, industrial wastewater treatment, manganese, optimization, pilot study

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Authors: Patchara Pedpradab, Kietisak Yoksang, Kosin Pattanamanee

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In our ongoing search for pharmacological significant of compounds from marine organisms, we investigated the active constituents of two sponges (Xestospongia sp., Halichondria sp.) and a gorgonian coral (Juncella sp.) from the Andaman Sea, Thailand. Several compounds were isolated from those of marine organisms. A marine sponge, Xestospongia sp. contained an isoqinoline compound namely aureol and cytotoxic thiophenen sesterterpene while Halichondria sp. produced C-28 sterols. The white gorgonian coral, Juncella sp. contained anti-tuberculosis diterpenes namely, junceellin and praelolide. All of the isolated compounds were analyzed by spectroscopic methods, extensively.

Keywords: Xestospongia sp., Halichondria sp., gorgonian, Juncella sp. biological activity

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Authors: C. Patrascioiu, V. Matei, N. Nicolae

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The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: hydrofining, kinetic, modeling, optimization

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Authors: Yu Chen Su

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Introduction: Gestational diabetes mellitus (GDM) refers to impaired glucose tolerance in pregnant women, impacting both the mother and newborn with short and long-term effects. It increases risks of preeclampsia, hypertension, type 2 diabetes, cesarean section, and preterm birth. GDM is associated with fetal macrosomia, shoulder dystocia, neonatal hypoglycemia, and future type 2 diabetes risk. A study on 6,421 pregnant women found 12% experienced high stress, linked to maladaptive coping and depressive emotions. Women with high-risk pregnancies may experience greater stress and depression. Research suggests GDM increases depression prevalence. A study on 632 Hispanic women with GDM showed severe stress and depression tendencies. Involving 95 women with GDM, 33.4% exhibited depression symptoms. Another study compared 180 GDM women to 186 with normal glucose levels, revealing higher depression levels in GDM women. They found GDM women were 1.85 times more likely to receive antidepressants during pregnancy and 1.69 times more likely to experience postpartum depression. Maternal stress and depressive symptoms during pregnancy are significant factors. Early identification by healthcare professionals can greatly benefit GDM women, their infants, and their families. Objectives: The purpose of this study was to investigate the association between gestational diabetes mellitus (GDM) and the risk of depression. Methods: This study reviewed and analyzed relevant literature on gestational diabetes mellitus (GDM) and depression in 6,876 patients. The literature search followed PRISMA guidelines and included databases like Embase, PubMed, MEDLINE, CINAHL, and Cochrane Library. Prospective or retrospective studies with relevant risk ratios and estimates were included, using a random-effects model for the analysis of depression risk correlation. Studies without depression data or relevant risks were excluded. The search period extended until October 2022. Results: Systematic review of 7 studies (6,876 participants) found a significant association (OR = 8.77, CI: 7.98-9.64, p < 0.05) between gestational diabetes mellitus (GDM) and higher depression risk compared to healthy pregnant women. Conclusions: Pregnancy is a significant life transition involving physiological, psychological, and social changes. Gestational diabetes poses challenges to women's physical and mental well-being. Sensitive healthcare professionals identifying issues early can greatly benefit women, babies, and the family.

Keywords: gestational diabetes, depression, systematic review, neta-analysis

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Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

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Authors: Jeffrey A. Lavarias, Jessie C. Elauria, Arnold R. Elepano, Engelbert K. Peralta, Delfin C. Suministrado

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Shelling process is one of the primary processes and critical steps in the processing of chocolate or any product that is derived from cocoa beans. It affects the quality of the cocoa nibs in terms of flavor and purity. In the Philippines, small-scale food processor cannot really compete with large scale confectionery manufacturers because of lack of available postharvest facilities that are appropriate to their level of operation. The impact of this study is to provide the needed intervention that will pave the way for cacao farmers of engaging on the advantage of value-adding as way to maximize the economic potential of cacao. Thus, provision and availability of needed postharvest machines like mechanical cacao sheller will revolutionize the current state of cacao industry in the Philippines. A mechanical cacao sheller was developed, fabricated, and evaluated to establish optimum shelling conditions such as moisture content of cocoa beans, clearance where of cocoa beans passes through the breaker section and speed of the breaking mechanism on shelling recovery, shelling efficiency, shelling rate, energy utilization and large nib recovery; To establish the optimum level of shelling parameters of the mechanical sheller. These factors were statistically analyzed using design of experiment by Box and Behnken and Response Surface Methodology (RSM). By maximizing shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization, the optimum shelling conditions were established at moisture content, clearance and breaker speed of 6.5%, 3 millimeters and 1300 rpm, respectively. The optimum values for shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization were recorded at 86.51%, 99.19%, 21.85kg/hr, 89.75%, and 542.84W, respectively. Experimental values obtained using the optimum conditions were compared with predicted values using predictive models and were found in good agreement.

Keywords: cocoa beans, optimization, RSM, shelling parameters

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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The number of inpatient admissions in the UK has been significantly increasing over the past decade. These increases cause bed occupancy rates to exceed the target level (85%) set by the Department of Health in England. Therefore, hospital service managers are struggling to better manage key resource such as beds. On the other hand, this severe demand pressure might lead to confusion in wards. For example, patients can be admitted to the ward of another inpatient specialty due to lack of resources (i.e., bed). This study aims to develop a simulation-optimization model to reallocate the available number of beds in a mid-sized hospital in the UK. A hospital simulation model was developed to capture the stochastic behaviours of the hospital by taking into account the accident and emergency department, all outpatient and inpatient services, and the interactions between each other. A couple of outputs of the simulation model (e.g., average length of stay and revenue) were generated as inputs to be used in the optimization model. An integer linear programming was developed under a number of constraints (financial, demand, target level of bed occupancy rate and staffing level) with the aims of maximizing number of admitted patients. In addition, a sensitivity analysis was carried out by taking into account unexpected increases on inpatient demand over the next 12 months. As a result, the major findings of the approach proposed in this study optimally reallocate the available number of beds for each inpatient speciality and reveal that 74 beds are idle. In addition, the findings of the study indicate that the hospital wards will be able to cope with 14% demand increase at most in the projected year. In conclusion, this paper sheds a new light on how best to reallocate beds in order to cope with current and future demand for healthcare services.

Keywords: bed occupancy rate, bed reallocation, discrete event simulation, inpatient admissions, integer linear programming, projected usage

Procedia PDF Downloads 130

Authors: Wisdom Robert Duruji, Moses Kanayochukwu Ifoh, Efeoghene Edward Esiemunobo

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This study examines the impact of natural and artificial disasters, lackadaisical and semantic approach in risk management, and mitigation implication for sustainable development goals in Nigeria, from 2009 to 2022. The study utilizes a range of research methods to achieve its objectives. These include literature review, website knowledge, Google search, news media information, academic journals, field-work and on-site observations. These diverse methods allow for a comprehensive analysis on the impact and the implications being study. The study finds that paradigm shift from remediating seismic, flooding, environmental pollution and degradation natural disasters by Nigeria Emergency Management Agency (NEMA), to political and charity organization; has plunged risk reduction strategies to embezzling opportunities. However, this lackadaisical and semantic approach in natural disaster mitigation, invariably replicates artificial disasters in Nigeria through: Boko Haram terrorist organization, Fulani herdsmen and farmers conflicts, political violence, kidnapping for ransom, ethnic conflicts, Religious dichotomy, insurgency, secession protagonists, unknown-gun-men, and banditry. This study also, finds that some Africans still engage in self-imposed slavery through human trafficking, by nefariously stow-away to Europe; through Libya, Sahara desert and Mediterranean sea; in search for job opportunities, due to ineptitude in governance by their leaders; a perilous journey that enhanced artificial disasters in Nigeria. That artificial disaster fatality in Nigeria increased from about 5,655 in 2009 to 114,318 in 2018; and to 157,643 in 2022. However, financial and material loss of about $9.29 billion was incurred in Nigeria due to natural disaster, while about $70.59 billion was accrued due to artificial disaster; from 2009 to 2018. Although disaster risk mitigation and politics can synergistically support sustainable development goals; however, they are different entities, and need for distinct separations in Nigeria, as in reality and perception. This study concluded that referendum should be conducted in Nigeria, to ascertain its current status as a nation. Therefore it is recommended that Nigerian governments should refine its naturally endowed crude oil locally; to end fuel subsidy scam, corruption and poverty in Nigeria!

Keywords: corruption, crude oil, environmental risk analysis, Nigeria, referendum, terrorism

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

Procedia PDF Downloads 91

Authors: Suresh Vanguri, Suresh Palla, K. V. Kalyani, S. K. Chaturvedi, B. N. Mohapatra

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Enhancing the fly ash utilization in the manufacture of cement is identified as one of the key areas to mitigate the Green House Gas emissions from the cement industry. Though increasing the fly ash content in cement has economic and environmental benefits, it results in a decrease in the compressive strength values, particularly at early ages. Quality of clinker and fly ash were identified as predominant factors that govern the extent of absorption of fly ash in the manufacturing of cement. This paper presents systematic investigations on the effect of clinker and fly ash quality on the properties of resultant cement. Since mechanical activation alters the physicochemical properties such as particle size distribution, surface area, phase morphology, understanding the variation of these properties with activation is required for its applications. The effect of mechanical activation on fly ash surface area, specific gravity, flow properties, lime reactivity, comparative compressive strength (CCS), reactive silica and mineralogical properties were also studied. The fineness of fly ash was determined by Blaine’s method, specific gravity, lime reactivity, CCS were determined as per the method IS 1727-1967. The phase composition of fly ash was studied using the X-ray Diffraction technique. The changes in the microstructure and morphology with activation were examined using the scanning electron microscope. The studies presented in this paper also include evaluation of Portland Pozzolana Cement (PPC), prepared using high volume fly ash. Studies are being carried out using clinker from cement plants located in different regions/clusters in India. Blends of PPC containing higher contents of activated fly ash have been prepared and investigated for their chemical and physical properties, as per Indian Standard procedures. Changes in the microstructure of fly ash with activation and mechanical properties of resultant cement containing high volumes of fly ash indicated the significance of optimization of the quality of clinker and fly ash fineness for better techno-economical benefits.

Keywords: flow properties, fly ash enhancement, lime reactivity, microstructure, mineralogy

Procedia PDF Downloads 445

Authors: L. Matlawe, E. S. Idemudia

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The stability is an important topic to plan and manage the energy in the microgrids as the same as the conventional power systems. The voltage and frequency stability is one of the most important issues recently studied in microgrids. The objectives of this paper are the modeling and designing of the components and optimal controllers for the voltage and frequency control of the AC/DC hybrid microgrid under the different disturbances. Since the PI controllers have the advantages of simple structure and easy implementation, so they were designed and modeled in this paper. The harmony search (HS) algorithm is used to optimize the controllers’ parameters. According to the achieved results, the PI controllers have a good performance in voltage and frequency control of the microgrid.

Keywords: emotional abuse, employees, mental health, self-concept

Procedia PDF Downloads 236

Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

Procedia PDF Downloads 97