Search results for: objective function

Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

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Authors: Abhishek Oswal

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Background: Inconsistencies between the guidelines for childhood asthma can pose a diagnostic challenge to clinicians. NICE guidelines are the most commonly followed guidelines in primary care in the UK; they state that to be diagnosed with asthma, a child must be more than 5 years old and must have objective evidence of the disease. When diagnoses are coded in general practice (GP), these guidelines may be superseded by communications from secondary care. Hence it is imperative that diagnoses are correct, as per up to date guidelines and evidence, as this affects follow up and management both in primary and secondary care. Methods: A snapshot audit at a general practice surgery was undertaken of children (less than 16 years old) with a coded diagnosis of 'asthma', to review the age at diagnosis and whether any objective evidence of asthma was documented at diagnosis. 50 cases of asthma in children presenting to the emergency department (ED) were then audited to review the age at presentation, whether there was evidence of previous asthma diagnosis and whether the patient was discharged from ED. A repeat audit is planned in ED this winter. Results: In a GP surgery, there were 83 coded cases of asthma in children. 51 children (61%) were diagnosed under 5, with 9 children (11%) who had objective evidence of asthma documented at diagnosis. In ED, 50 cases were collected, of which 4 were excluded as they were referred to the other services, or for incorrect coding. Of the 46 remaining, 27 diagnoses confirmed to NICE guidelines (59%). 33 children (72%) were discharged from ED. Discussion: The most likely reason for the apparent low rate of a correct diagnosis is the significant challenge of obtaining objective evidence of asthma in children. There were a number of patients who were diagnosed from secondary care services and then coded as 'asthma' in GP, without having objective documented evidence. The electronic patient record (EPR) system used in our emergency department (ED) did not allow coding of 'suspected diagnosis' or of 'viral induced wheeze'. This may have led to incorrect diagnoses coded in primary care, of children who had no confirmed diagnosis of asthma. We look forward to the re-audit, as the EPR system has been updated to allow suspected diagnoses. In contrast to the NICE guidelines used here, British Thoracic Society (BTS) guidelines allow for a trial of treatment and subsequent confirmation of diagnosis without objective evidence. It is possible that some of the cases which have been classified as incorrect in this audit may still meet other guidelines. Conclusion: The diagnosis of asthma in children is challenging. Incorrect diagnoses may be related to clinical pressures and the provision of services to allow compliance with NICE guidelines. Consensus statements between the various groups would also aid the decision-making process and diagnostic dilemmas that clinicians face, to allow more consistent care of the patient.

Keywords: asthma, diagnosis, primary care, emergency department, guidelines, audit

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Authors: Vince Macri, Jakub Petioky, Paul Zilber

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Virtual-reality-based technology, i.e. video-game-like simulations (collectively, VRSims) are used in therapy for a variety of medical conditions. The purpose of this paper is to contribute to a discussion on criteria for selecting VRSims to augment treatment of survivors of acquired brain injury. Specifically, for treatments to improve or restore brain motor function in upper extremities affected by paresis or paralysis. Six uses of virtual reality are reviewed video games for entertainment, training simulations, unassisted or device-assisted movements of affected or unaffected extremities displayed in virtual environments and virtual anatomical interactivity.

Keywords: acquired brain injury, brain-motor function, virtual anatomical interactivity, therapeutic simulations

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Authors: Anderson dos Santos Ananias, Matheus Yuji Shigueoka, Roberto Saverio Souza Costa

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Soil and water conservation can be conceptualized as a combination of management and use methods, which have the function of protecting them against deterioration induced by anthropogenic or natural factors. Thus, the objective of this research was to evaluate the rural extension work in soil conservation carried out at Sítio do Alto in Jaboticabal-SP, through the analysis of planimetric data (latitude and longitude coordinates) and altimetric differences of the empirically constructed terraces by the rural producer and with technical guidance from CATI (Coordination of Integral Technical Assistance). A data collection procedure was carried out in the field, with GPS L1/L2, before the construction of five (5) terraces technically level and after their construction. The results showed that the greatest differences were found on terrace one (1), with a maximum latitude difference of 57 meters, the longitude of 23 m, and altitude of 2 m. These results corroborate the observations in the field, in which the presence of a great erosion caused by the incorrect construction of terrace 1 was verified rainwater to the side of the rural property, where the largest erosion furrows with the beginning of gully formation were found.

Keywords: GPS, mechanical pratice, surface runoff, erosion

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Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

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The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

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Authors: Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

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The main aim of this article is to investigate the statistical convergence of the summation of integral type operators and to obtain the weighted statistical convergence. The rate of statistical convergence by means of modulus of continuity and function belonging to the Lipschitz class are also studied. We discuss the convergence of the defined operators by graphical representation and put a better rate of convergence than the Szasz-Mirakjan-Kantorovich operators. In the last section, we extend said operators into bivariate operators to study about the rate of convergence in sense of modulus of continuity and by means of Lipschitz class by using function of two variables.

Keywords: The Szasz-Mirakjan-Kantorovich operators, statistical convergence, modulus of continuity, Peeters K-functional, weighted modulus of continuity

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Reham Hajomer, Ikram Elsiddig, Amna Hamad

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Lepidium sativum (Garden Cress) belonging to Brassicaceae family is an annual herb locally known as El-rshad. In Ayurveda it is an important medicinal plant, traditionally used for the treatment of jaundice, liver problems, spleen diseases, gastrointestinal disorders, menstrual problems, fracture, arthritis, inflammatory conditions and for treatment of hypothyroidism. Hypothyroidism is a condition in which the thyroid gland does not produce enough thyroid hormones (Triiodithyronine T3 and Thyroxine T4) which are commonly caused by iodine deficiency. It’s divided into primary and secondary hypothyroidism, the primary caused by failure of thyroid function and secondary due to the failure of adequate thyroid-stimulating hormone (TSH) secretion from the pituitary gland or thyroid -releasing hormone (TRH) from the hypothalamus. The disease is most common in women over age 60. The objective regarding this study is to know whether Lepidium sativum would affect the level of thyroid hormones. The extract was prepared with 96% ethanol using Soxhlet apparatus. The anti-hypothyroidism activity was tested by using thirty male Wistar rats weighing (100-140 g) were used in the experiment. They were grouping into five groups, Group 1: Normal group= Administered only distilled water. Then 10 mg/kg Propylthiouracil was added to the drinking water of all other groups to induce hypothyroidism. Group 2: Negative control without any treatment; Group 3: Test group= treated with oral administration of 500mg/kg extract; Group 4: treated with oral administration of 250mg/kg of the extract; Group 5: Standard group (positive control) = treated with intraperitoneal Levothyroxine. All rats were incubated for 20 days at animal house with room temperature of proper ventilation provided with standard diet. The result show that the Lepidium sativum extract was found to increases the T3 and T4 in the propylthiouracil induced rats with values (0.29 ng/dl T3 and 0.57 U T4) for the 500mg/kg and (0.27 ng/dl T3 and 0.517 U T4) for the 250mg/kg in comparison with standard with values (0.241 ng/dl T3 and 0.516 U T4) so that Lepidium sativum can be stimulatory to thyroid function and possess significant anti-hypothyroidism effect with p-values ranges from (0.000006*-0.893472). In conclusion, from results obtained, Lepidium sativum plant extract was found to posses anti-hypothyroidism effects so its act as an agent that stimulates thyroid hormone secretion.

Keywords: anti-hypothyroidism, extract, lepidium, sativum

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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Authors: Biplab Singha, Mausumi Sen, Nidul Sinha

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In order to deal with the impreciseness and uncertainty of a system, D. Molodtsov has introduced the concept of ‘Soft Set’ in the year 1999. Since then, a number of related definitions have been conceptualized. This paper includes a study on various forms of Soft Sets with examples. The paper contains the concepts of domain and co-domain of a soft set, conversion to one-one and onto function, matrix representation of a soft set and its relation with one-one function, upper and lower triangular matrix, transpose and Kernel of a soft set. This paper also gives the idea of the extension of soft sets in medical diagnosis. Here, two soft sets related to disease and symptoms are considered and using AND operation and OR operation, diagnosis of the disease is calculated through appropriate examples.

Keywords: kernel of a soft set, soft set, transpose of a soft set, upper and lower triangular matrix of a soft set

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola

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In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.

Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity

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Authors: Vishal Bhatnagar

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The objective of this study is to compare the efficacy of epidural analgesia of two amide local anesthetics, ropivacaine and levobupivacaine, with fentanyl for postoperative analgesia in major abdominal surgery CRS+HIPEC. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS+HIPEC) are done for primary peritoneal malignancies or peritoneal spread of malignant neoplasm. CRS and HIPEC are considered one of the most painful surgery among all major abdominal surgeries. Poorly managed postoperative pain elevates stress, increases anxiety, causes prolonged Hospital stay, increases opioid requirement and side effects, increases the cost of treatment and psychological effects on patient and family. It affects the quality of life of patients. The epidural technique provides better postoperative analgesia, earlier recovery of bowel function, fewer side effects, higher patient satisfaction, and an improvement in life quality in the postoperative days after abdominal surgery than other analgesic techniques.

Keywords: HIPEC, postoperative analgesia, cytoreductive surgery, VAS score, rescue analgesia

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Authors: Joseph P. Mandala

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This paper examines the legal and medical ethics concerns, which proponents of human head transplantation continue to defy since the procedure was first attempted on dogs in 1908. Despite recent bioethical objections, proponents have proceeded with radical experimentation, claiming transplantation would treat incurable diseases and improve patients’ quality of life. In 2018, Italian neurosurgeon, Sergio Canavero, and Dr. Xiaoping Ren claimed to have performed a head transplant on a corpse in China. Content analysis of literature shows that the procedure failed to satisfy scientific, legal, and bioethical elements because, unlike humans, corpses cannot coordinate function. Putting a severed head onto a body that has been dead for several days is not equivalent to a transplant which would require successfully reconnecting and restoring function to a spinal cord. While reconnection without restoration of bodily function is not transplantation, the publicized procedure on animals and corpses could leapfrog to humans, sparking excitement in society likely to affect organ donors and recipients from territorial jurisdictions with varying legal and ethical regimes. As neurodiscoveries generate further excitement, the need to preemptively address the legal and medical ethics impact of head transplantation in our society cannot be overstated. A preemptive development of methods to address the impact of head transplantation will help harmonizing national and international laws on organ donations, advance directives, and laws affecting end of life.

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Authors: Zarine Avetisyan

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Both in language and literature there exists the theory of recurrence of text and talk chunks which brings us to the notion of precedence. It must be stated that precedence as a pragma-linguistic phenomenon is yet underknown and it is the main objective of the present research to revisit and reveal it thoroughly. In line with the main research objective, analysis of political text and talk provides abundant relevant data for the illustration of the phenomenon of precedence. The analysis focuses on certain pragmatic universals (e.g. intention) and categories (e.g. speech techniques) which lead to the disclosure of the present object of study.

Keywords: intention, precedence, political discourse, pragmatic universals

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Authors: D. F. Coetzee, M. M. Campbell

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The urban environment is constantly expanding and the optimal use of centrally located land is important in terms of sustainable development. Bloemfontein has expanded and this affects land-use functions. The purpose of the study is to examine the possible shift in location of the Bloemfontein show grounds to utilize the space of the grounds more effectively in context of spatial planning. The research method used is qualitative case study research with the case study on the Bloemfontein show grounds. The purposive sample consisted of planners who work or consult in the Bloemfontein area and who are registered with the South African Council for Planners (SACPLAN). Interviews consisting of qualitative open-ended questionnaires were used. When considering relocation the social and economic aspects need to be considered. The findings also indicated a majority consensus that the property can be utilized more effectively in terms of mixed land use. The showground development trust compiled a master plan to ensure that the property is used to its full potential without the relocation of the showground function itself. This Master Plan can be seen as the next logical step for the showground property itself, and it is indeed an attempt to better utilize the land parcel without relocating the show function. The question arises whether the proposed Master Plan is a permanent solution or whether it is merely delaying the relocation of the core showground function to another location. For now, it is a sound solution, making the best out of the situation at hand and utilizing the property more effectively. If the show grounds were to be relocated the researcher proposed a recommendation of mixed-use development, in terms an expansion on the commercial business/retail, together with a sport and recreation function. The show grounds in Bloemfontein are well positioned to capitalize on and to meet the needs of the changing economy, while complimenting the future economic growth strategies of the city if the right plans are in place.

Keywords: centrally located land, spatial planning, show grounds, central business district

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Authors: Fernanda Gonçalves, Karla Alcântara, Vanessa Moura, Patrícia Nolasco, Jorge Kalil, Maristela Hernandez

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Introduction: Atherosclerosis is a chronic disease where two striking features are observed: retention of lipids and inflammation. Understanding the interaction between immune cells and lipoproteins involved in atherogenesis are urgent challenges, since cardiovascular diseases are the leading cause of death worldwide. Macrophages are critical to the development of atherosclerotic plaques and in the perpetuation of inflammation in these lesions. These cells are also directly involved in unstable plaque rupture. Recently different populations of macrophages are being identified in atherosclerotic lesions. Although the presence of M2 macrophages (macrophages activated by the alternative pathway, eg. The IL-4) has been identified, the function of these cells in atherosclerosis is not yet defined. M2 macrophages have a high endocytic capacity, they promote remodeling of tissues and to have anti-inflammatory activity. However, in atherosclerosis, especially unstable plaques, severe inflammatory reaction, accumulation of cellular debris and intense degradation of the tissue is observed. Thus, it is possible that the M2 macrophages have altered function (phenotype) in atherosclerosis. Objective: Our aim is to evaluate if the presence of oxidized LDL alters the phenotype and function of M2 macrophages in vitro. Methods: For this, we will evaluate whether the addition of lipoprotein in M2 macrophages differentiated in vitro with IL -4 induces 1) a reduction in the secretion of anti-inflammatory cytokines (CBA and ELISA), 2) secretion of inflammatory cytokines (CBA and ELISA), 3) expression of cell activation markers (Flow cytometry), 4) alteration in gene expression of molecules adhesion and extracellular matrix (Real-Time PCR) and 5) Matrix degradation (confocal microscopy). Results: In oxLDL stimulated M2 macrophages cultures we did not find any differences in the expression of the cell surface markers tested, including: HLA-DR, CD80, CD86, CD206, CD163 and CD36. Also, cultures stimulated with oxLDL had similar phagocytic capacity when compared to unstimulated cells. However, in the supernatant of these cultures an increase in the secretion of the pro-inflammatory cytokine IL-8 was detected. No significant changes where observed in IL-6, IL-10, IL-12 and IL-1b levels. The culture supernatant also induced massive extracellular matrix (produced by mouse embryo fibroblast) filaments degradation. When evaluating the expression of 84 extracellular matrix and adhesion molecules genes, we observed that the stimulation of oxLDL in M2 macrophages decreased 47% of the genes and increased the expression of only 3% of the genes. In particular we noted that oxLDL inhibit the expression of 60% of the genes constituents of extracellular matrix and collagen expressed by these cells, including fibronectin1 and collagen VI. We also observed a decrease in the expression of matrix protease inhibitors, such as TIMP 2. On the opposite, the matricellular protein thrombospondin had a 12 fold increase in gene expression. In the presence of native LDL 90% of the genes had no altered expression. Conclusion: M2 macrophages stimulated with oxLDL secrete the pro-inflammatory cytokine IL-8, have an altered extracellular matrix constituents gene expression, and promote the degradation of extracellular matrix. M2 macrophages may contribute to the perpetuation of inflammation in atherosclerosis and to plaque rupture.

Keywords: atherosclerosis, LDL, macrophages, m2

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Authors: I. Muslih, A. Alkhalailah, A. Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: dust effect, MENA, solar energy, PV system

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Authors: Estrella C. Damaris, Ingrid A. Olais, Gloria P. Uicab

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This study explores the relationship between the level of functionality and cognitive impairment in older adult women from the south-east of Mexico. It is a descriptive, cross-sectional study; performed with 172 participants in total who attended a health institute and live in Merida, Yucatan Mexico. After a non-probabilistic sampling, Barthel and Pfeiffer scales were applied. The results show statistically significant correlation between the cognitive impairment (Pfeiffer) and the levels of independence and function (Barthel) (r =0.489; p =0.001). Both determine a dependence level so they need either a little or a lot of help. Society needs that the older woman be healthy and that the professionals of mental health develop activities to prevent and rehabilitate because cognitive impairment and function are directly related with the quality of life.

Keywords: functionality, cognition, routine activities, cognitive impairment

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Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

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Authors: Serge B. Provost, Yishan Zhang

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A moment-based adjustment to the saddlepoint approximation is introduced in the context of density estimation. First applied to univariate distributions, this methodology is extended to the bivariate case. It then entails estimating the density function associated with each marginal distribution by means of the saddlepoint approximation and applying a bivariate adjustment to the product of the resulting density estimates. The connection to the distribution of empirical copulas will be pointed out. As well, a novel approach is proposed for estimating the support of distribution. As these results solely rely on sample moments and empirical cumulant-generating functions, they are particularly well suited for modeling massive data sets. Several illustrative applications will be presented.

Keywords: empirical cumulant-generating function, endpoints identification, saddlepoint approximation, sample moments, density estimation

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Authors: Sheetla Prasad

Abstract:

The focus issue of this article is to determine the mechanism of mind with geometrical analysis of human face. Research paradigm has been designed for study of spatial dynamic of face and it was found that different shapes of face have their own function for determine the action of mind. The functional ratio (FR) of face has determined the behaviour operation of human beings. It is not based on the formulistic approach of prediction but scientific dogmatism and mathematical analysis is the root of the prediction of behaviour. For analysis, formulae were developed and standardized. It was found that human psyche is designed in three forms; manipulated, manifested and real psyche. Functional output of the psyche has been determined by degree of energy flow in the psyche and reserve energy for future. Face is the recipient and transmitter of energy but distribution and control is the possible by mind. Mind directs behaviour. FR indicates that the face is a power house of energy and as per its geometrical domain force of behaviours has been designed and actions are possible in the nature of individual. The impact factor of this study is the promotion of human capital for job fitness objective and minimization of criminalization in society.

Keywords: functional ratio, manipulated psyche, manifested psyche, real psyche

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Srijanani Anurag Prasad

Abstract:

The Coalescence Hidden-variable Fractal Interpolation Surface (CHFIS) was built by combining interpolation data from the Iterated Function System (IFS). The interpolation data in a CHFIS comprises a row and/or column of uncertain values when a single point is entered. Alternatively, a row and/or column of additional points are placed in the given interpolation data to demonstrate the node added CHFIS. There are three techniques for inserting new points that correspond to the row and/or column of nodes inserted, and each method is further classified into four types based on the values of the inserted nodes. As a result, numerous forms of node insertion can be found in a CHFIS.

Keywords: fractal, interpolation, iterated function system, coalescence, node insertion, knot insertion

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Authors: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

Abstract:

Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

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Authors: Chia-Yu Yao

Abstract:

This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: pulse-shaping filters, FIR filters, jittering, QAM

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Authors: Yasmin Tantawi, Mary Beth Rosson

Abstract:

In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

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