Search results for: non negative integer sampling

Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

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This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

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Authors: Soheil Behdarvandirad

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The relationship between depression and self-focused language has been well documented. The more depressed a person is, the more "I"s, "me"s, and "my"s they will use. The present study attempted to factor in the impact of mood and examine whether negative mood has self-focused impacts similar to those of depression. For this purpose, 160 Iranian native speakers of Farsi were divided into three experimental groups of negative, neutral, and positive groups. After completing the BDI-II inventory and depression measurement, they were presented with pretested mood stimuli (3 separate videos to induce the target moods). Finally, they were asked to write between 10 to 20 minutes about a topic that asked them to freely write about their state of life, how you feel about it and the reasons that had shaped their current life circumstances. While the significant correlation between depression and I-talk was observed, negative mood led to more we-talk in general and seemed to even push the participants away from self-rumination. It seems that it is an emotion-regulatory strategy that participants subconsciously adopt to distract themselves from the disturbing mood. However, negative mood intensified the self-focused language among depressed participants. Such results can be further studied by examining brain areas that are more involved in self-perception and particularly in precuneus.

Keywords: self-focused language, depression, mood, precuneus

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Authors: Mahsa Oroojeni Mohammad Javad

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Globalization of economic activity and rapid growth of information technology has resulted in shorter product lifecycles, reduced transport capacity, dynamic and changing customer behaviors, and an increased focus on supply chain design in recent years. The design of the supply chain network is one of the most important supply chain management decisions. These decisions will have a long-term impact on the efficacy and efficiency of the supply chain. In this paper, a two-objective mixed-integer linear programming (MILP) model is developed for designing and optimizing a closed-loop green supply chain network that, to the greatest extent possible, includes all real-world assumptions such as multi-level supply chain, the multiplicity of production technologies, and multiple modes of transportation, with the goals of minimizing the total cost of the chain (first objective) and minimizing total emissions of emissions (second objective). The ε-constraint and CPLEX Solver have been used to solve the problem as a single-objective problem and validate the problem. Finally, the sensitivity analysis is applied to study the effect of the real-world parameters’ changes on the objective function. The optimal management suggestions and policies are presented.

Keywords: closed-loop supply chain, multi-level green supply chain, mixed-integer programming, transportation modes

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Authors: Naheed Malik, Waheed Akhtar

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An introduction to the Islamic move towards the managing human resource is a preliminary attempt to provide managers with a useful way of managing and accepting employees. This knowledge would be helpful to even non-Muslim managers. Muslim managers are required not to know only the Islamic HR but also it is expected from them to apply the Islamic approach in managing the employees. Human resource is considered the most substantial asset of organizations. Studies have recommended that successful human resource management (HRM) leads to positive attitudes and behaviors at the workplace. On the contrary, unproductive use of human resources results in negative penalty in the form of lower job satisfaction, lower commitment, or even high employee turnover and even poor workforce quality.The study examined the Impact of Islamic HR practices on job satisfaction. Islamic HR variables encompass the aspects of performance appraisal, training and development, selection and recruitment. Data was obtained via self –administered questionnaires distributed among the employees of Banks in Pakistan which are practicing Islamic Banking. The sampling method employed was purposive sampling.Based on 240 responses obtained ,the study revealed that Islamic HRM deliberates the 40per cent of the variances in Job satisfaction .All variables excluding recruitment were found to be substantially pertinent to the dependent variable. The study also meditated the implications for future studies.

Keywords: islamic HRM, job satisfaction, islamic and conventional banks, Pakistan

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Authors: Hashem Sazegar

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Legendre’s conjecture states that there is a prime number between n^2 and (n + 1)^2 for every positive integer n. In this paper we prove that every composite number between n2 and (n + 1)2 can be written u^2 − v^2 or u^2 − v^2 + u − v that u > 0 and v ≥ 0. Using these result as well as induction and residues (modq) we prove Legendre’s conjecture.

Keywords: bertrand-chebyshev theorem, landau’s problems, goldbach’s conjecture, twin prime, ramanujan proof

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Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

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The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient. In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake

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Authors: Małgorzata Osowiecka

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Negative emotions are rather seen as creativity inhibitor. On the other hand, it is worth noting that negative emotions may be good for our functioning. Negative emotions enhance cognitive resources and improve evaluative processes. Moreover maintaining a negative emotional state allow for cognitive reinterpretation of the emotional stimuli, what is good for our creativity, especially cognitive flexibility. Writing a diary or writing about difficult emotional experiences in general can be the way to not only improve psychical health, but also – enhance creative behaviors. Thanks to translating difficult emotions to the verbal level and giving them ‘a name’ or ‘a label’, we can get easier access to both emotional content of an experience and to the semantic content, without the need of speaking out loud. Expressive writing improves academic results and the efficiency of working memory. The classical method of writing about emotions consists in a long-term process of describing negative experiences. Present research demonstrate the efficiency of this process over a shorter period of time - one writing session, on school children sample. Participants performed writing task. Writing task had two different topics: emotions connected with their negative emotions (expressive writing) and content not connected with negative emotional state (writing about one’s typical day). Creativity was measured by Guilford’s Alternative Uses Task. Results have shown that writing about negative emotions results in the higher level of divergent thinking in all three parameters: fluency, flexibility and originality. After the writing task mood of expressive writing participants remained negative more than the mood of the controls. Taking an expressive action after a difficult emotional experience can support functioning, which can be observed in enhancement of divergent thinking. Writing about emotions connected with negative experience makes one more creative, than writing about something unrelated with difficult emotional moments. Research has shown that young people should not demonize negative emotions. Sometimes, properly applied, negative emotions can be the basis of creation. Preparation was supported by a The Young Scientist University grant titled ‘Dynamics of emotions in the creative process’ from The Polish Ministry of Science and Higher Education.

Keywords: creativity, divergent thinking, emotions, expressive writing

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Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

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This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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Authors: Hamidreza Sharifan, Audra Morse

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Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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Authors: S. Suman, G. N. Singh

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This research work is an effort to analyse the consequences of scrambled response technique to estimate the current population mean in two-occasion successive sampling when the characteristic of interest is sensitive in nature. The generalized estimation procedures have been proposed using sensitive auxiliary variables under additive and multiplicative scramble models. The properties of resultant estimators have been deeply examined. Simulation, as well as empirical studies, are carried out to evaluate the performances of the proposed estimators with respect to other competent estimators. The results of our studies suggest that the proposed estimation procedures are highly effective under the presence of non-response situation. The result of this study also suggests that additive scrambled response model is a better choice in the perspective of cost of the survey and privacy of the respondents.

Keywords: scrambled response, sensitive characteristic, successive sampling, optimum replacement strategy

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Authors: Dmytro O. Plutenko, Alexei D. Kiselev, Mikhail V. Vasnetsov

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We present the results of our analytical and computational study of Laguerre-Gaussian (LG) beams scattering by spherical homogeneous isotropic particles located on the axis of the beam. We consider different types of scatterers (dielectric, metallic and double negative metamaterials) and different polarizations of the LG beams. A possibility to generate photonic nanojets using metallic and double negative metamaterial Mie scatterers is shown. We have studied the properties of such nonclassical nanojets and discovered new types of the nanojets characterized by zero on-axes magnetic (or electric) field with the electric (or magnetic) field polarized along the z-axis.

Keywords: double negative metamaterial, Laguerre-Gaussian beam, Mie scattering, optical vortices, photonic nanojets

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Authors: Dzatur Rizqi Fathienah Syarifuddin, Isharyah Sunarno, Eddy Hartono, Siti Maisuri T. Chalid

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Introduction: The potential impact of coronavirus disease 2019 (COVID-19) on the health of expectant mothers and fetuses has strained attention. Pregnant women are considered a vulnerable category to respiratory infections. Moreover, several inflammatory cytokines are 2-100 times more abundant in COVID-19 with cytokine storms than in normal individuals; interleukin 6 (IL-6) exhibits much higher elevations. Investigating potential relationships between IL-6 serum levels and the severity of COVID-19 symptoms in pregnant women is the aim of this study. Material and Methods: Sixty-two eligible pregnant women were divided into a positive COVID-19 group (n=31) and a negative COVID-19 group (n=31) in this cross-sectional study. The research subjects were selected using consecutive sampling. The IL-6 was measured from a vein blood specimen using ELISA methods. Results: The COVID-19 positive group had a higher median IL-6 serum level (45.35 (35.15- 153.99) vs. 38.86 ± 11.43 (15.02-59.52), p=0.03) than the negative group. On the other hand, the IL-6 serum level had comparable value according to the COVID-19 symptoms severity (88.35 ± 36.14 ng/mL vs. 51.09 ± 25.48 ng/mL vs. 56.02 ± 33.20 ng/mL in moderate symptoms, mild symptoms, and asymptomatic, respectively; p=0.152). Conclusion: Although the IL-6 serum levels are not related to COVID-19 symptoms severity, an elevated of this biomarker was found in pregnant women with affected diagnoses.

Keywords: interleukin-6, pregnancy, COVID-19, several inflammatory

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Authors: Chaghoub Soraya, Zhang Xiaoyan

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This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.

Keywords: approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median

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Authors: Zs. Csanádi, A. Szabó Nagy, J. Szabó, J. Erdős

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Atmospheric aerosols have several important environmental impacts and health effects in point of air quality. Monitoring the PM10-bound polycyclic aromatic hydrocarbons (PAHs) could have important environmental significance and health protection aspects. Benzo(a)pyrene (BaP) is the most relevant indicator of these PAH compounds. In Hungary, the Hungarian Air Quality Network provides air quality monitoring data for several air pollutants including BaP, but these data show only the annual mean concentrations and maximum values. Seasonal variation of BaP concentrations comparing the heating and non-heating periods could have important role and difference as well. For this reason, the main objective of this study was to assess the annual concentration and seasonal variation of BaP associated with PM10 in the ambient air of Northwestern Hungary seven different sampling sites (six urban and one rural) in the sampling period of 2008–2013. A total of 1475 PM10 aerosol samples were collected in the different sampling sites and analyzed for BaP by gas chromatography method. The BaP concentrations ranged from undetected to 8 ng/m3 with the mean value range of 0.50-0.96 ng/m3 referring to all sampling sites. Relatively higher concentrations of BaP were detected in samples collected in each sampling site in the heating seasons compared with non-heating periods. The annual mean BaP concentrations were comparable with the published data of the other Hungarian sites.

Keywords: air quality, benzo(a)pyrene, PAHs, polycyclic aromatic hydrocarbons

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Madjid Nancy, Rakinaung Natalia, Lumowa Fresy

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Background: Bullying becomes one of the problems that concern the world of education, especially in adolescents, which has a negative impact on learning achievement, psychology, and physical health. The psychological impact is shame, depression, distress, fear, sadness, and anxiety, so that if prolonged leave can lead to depression in the victim. While the impact on physical health in the form of bruises on the hit area, blisters, swelling and in more severe cases will lead to death. Objectives: This study aims to explore the perception of bullying in adolescent students Sekolah Menengah Kejuruan (SMK) Negeri 1 Manado and the people associated with that adolescent students. Methods: This research uses descriptive qualitative research design and using thematic analysis, and supported by Urie Bronfenbrenner Ecological Framework. The data collection that will be used is by in-depth interview. Sampling using purposive sampling and snowball techniques. This research was conducted at SMK Negeri 1 Manado. Result: From the analysis obtained three themes with the categories: 1) the perception of bullying with categories are: Understanding of Bullying and The Impact of Bullying, 2) the originator of bullying with categories are: Fulfillment of Youth Development Tasks and Needs, Peers Influence, and Family Communication; 3) the effort to handle bullying with categories are: the Individual Coping and Teacher Role. Conclusion: This research get three themes, those are perception of bullying, bullying’s originator and the effort of handling bullying.

Keywords: adolscent, students, bullying, perception

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Authors: Eric Granholm, Christophe Delay, Jason Holden, Peter Link

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Negative symptoms are an important unmet treatment needed for schizophrenia. We conducted an open trial of a novel blended intervention called mobile-assisted cognitive behavior therapy for negative symptoms (mCBTn). mCBTn is a weekly group therapy intervention combining in-person and smartphone-based CBT (CBT2go app) to improve experiential negative symptoms in people with schizophrenia. Both the therapy group and CBT2go app included recovery goal setting, thought challenging, scheduling of pleasurable activities and social interactions, and pleasure savoring interventions to modify defeatist attitudes, a target mechanism associated with negative symptoms, and improve experiential negative symptoms. We tested whether participants with schizophrenia or schizoaffective disorder (N=31) who met prospective criteria for persistent negative symptoms showed improvement in experiential negative symptoms. Retention was excellent (87% at 18 weeks) and severity of defeatist attitudes and motivation and pleasure negative symptoms declined significantly in mCBTn with large effect sizes. We also tested whether pupillary responses, a measure of cognitive effort, predicted improvement in negative symptoms mCBTn. Pupillary responses were recorded at baseline using a Tobii pupillometer during the digit span task with 3-, 6- and 9-digit spans. Mixed models showed that greater dilation during the task at baseline significantly predicted a greater reduction in experiential negative symptoms. Pupillary responses may provide a much-needed prognostic biomarker of which patients are most likely to benefit from CBT. Greater pupil dilation during a cognitive task predicted greater improvement in experiential negative symptoms. Pupil dilation has been linked to motivation and engagement of executive control, so these factors may contribute to benefits in interventions that train cognitive skills to manage negative thoughts and emotions. The findings suggest mCBTn is a feasible and effective treatment for experiential negative symptoms and justify a larger randomized controlled clinical trial. The findings also provide support for the defeatist attitude model of experiential negative symptoms and suggest that mobile-assisted interventions like mCBTn can strengthen and shorten intensive psychosocial interventions for schizophrenia.

Keywords: cognitive-behavioral therapy, mobile interventions, negative symptoms, pupillometry schizophrenia

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Authors: Milica Lazic, Jovana Jestrovic

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The aim of this research is to examine moderating role of positive and negative affect, defined as traits, in relationship between a number of stressful life events to which an individual is exposed and life satisfaction. The tendency to experience positive and negative emotions is considered as relatively independent, and life satisfaction depends on presence and intensity of emotions of different valence. However, the role of positive and negative affect can be much more complex. It can change the direction and/or intensity of correlation between a number of stressful life events and life satisfaction. Thus, this question is important for two reasons, (I) better comprehension of inconsistent result of correlation intensity between stressful events and life satisfaction (II) verification on what conditions positive and negative affect have a protective role, and on what conditions the positive and/or negative affect is vulnerability factor. Longitudinal data were collected in two waves from 660 adolescents. Firstly, participants completed the Positive and Negative Affect Schedule. A year later, Life events questionnaire, which measures the number of stressful events in the past six months and Satisfaction with Life Scale were administered. The data were analyzed using hierarchical regression analyses: three-way interaction. The results show that number of life events, positive and negative effect contribute to the level of life satisfaction. The check of moderation role shows the significant three-way interaction of number of life event, and both, positive and negative affect. Individuals who report high level of positive affect, estimate to be moderate to highly satisfied with their lives, regardless of number of stressors to which they are exposed and also how often they experience negative emotions. Individuals, who often experience negative emotions and rarely positive, report the lowest level of life satisfaction. It doesn't change despite the number of stressors they were exposed to. Individuals who report that rarely experience not only positive than also negative emotions estimate different level of life satisfaction depending on number of stressors they were exposed to. Under the influence of numerous stressors, their level of life satisfaction is low, and it's equal to life satisfaction level of individuals who often experience negative and rarely positive emotions. The result of this research shows that tendency to often experience positive emotions is the protective factor in situation when individuals are exposed to high number of stressors. On the other hand, tendency to rarely experience positive emotions present vulnerability factor. Conclusions and practical implications are further discussed.

Keywords: life events, life satisfaction, subjective well-being, positive and negative affect

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Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

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The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

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Authors: Reza Moslemi, Sebastien Perrier

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Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Liaquat Ahmad, Muhammad Aslam, Muhammad Azam

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In this article, we propose a control chart based on repetitive group sampling scheme for the location parameter. This charting scheme is based on the regression estimator; an estimator that capitalize the relationship between the variables of interest to provide more sensitive control than the commonly used individual variables. The control limit coefficients have been estimated for different sample sizes for less and highly correlated variables. The monitoring of the production process is constructed by adopting the procedure of the Shewhart’s x-bar control chart. Its performance is verified by the average run length calculations when the shift occurs in the average value of the estimator. It has been observed that the less correlated variables have rapid false alarm rate.

Keywords: average run length, control charts, process shift, regression estimators, repetitive group sampling

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Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

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With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: electrical market prices, electricity market, energy storage optimization, mixed integer linear programming (MILP) optimization

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Authors: Sana Tahir, Haya Fatimah

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Sexuality is a social construct which is considered as the most confidential affair among individuals where women tend to refrain themselves more from sexually explicit behavior than men. Patriarchy has an elevated influence on the expression of female sexuality. While women’s sexual experiences are suppressed men are entitled to pleasure themselves according to their desire. The purpose of this study is to explore how the internalization of patriarchy affects women’s sexuality. Similarly, it was investigated how women sexuality is associated with psychological distress. The sample consisted of 100(age 20-40) married women. Participants were selected through a combination of convenient and snowball sampling. Women were asked to provide data regarding patriarchal beliefs, sexual awareness and DAS (depression, anxiety, and stress). Pearson Product Moment Correlation Analyze was conducted to examine the nature of the relationship between patriarchal beliefs, sexual awareness and psychological distress in married women. There is a significant negative relation between sexual awareness and patriarchal beliefs (r=-.391, p<.001). There also lies a significant negative relation between sexual awareness and depression, anxiety, stress (r=-.359, p<.001) (r=.301, p=.002) (r=-.221, p=.027). The results reveal that women with strong patriarchal beliefs have less sexual awareness in terms of sexual consciousness, sexual monitoring, sexual assertiveness and sexual appeal consciousness. Similarly, women with strong patriarchal beliefs and less sexual awareness have high levels of depression, anxiety, and stress.

Keywords: female sexuality, patriarchy, psychological distress, sexual awareness

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Authors: Onur Kaya, Ilknur Tukenmez

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In this study, we consider vehicle routing problems on networks with alternative direct links between nodes, and we analyze a multi-objective problem considering the financial, environmental and social objectives in this context. In real life, there might exist several alternative direct roads between two nodes, and these roads might have differences in terms of their lengths and durations. For example, a road might be shorter than another but might require longer time due to traffic and speed limits. Similarly, some toll roads might be shorter or faster but require additional payment, leading to higher costs. We consider such alternative links in our problem and develop a mixed integer linear programming model that determines which alternative link to use between two nodes, in addition to determining the optimal routes for different vehicles, depending on the model objectives and constraints. We consider the minimum cost routing as the financial objective for the company, minimizing the CO2 emissions and gas usage as the environmental objectives, and optimizing the driver working conditions/working hours, and minimizing the risks of accidents as the social objectives. With these objective functions, we aim to determine which routes, and which alternative links should be used in addition to the speed choices on each link. We discuss the results of the developed vehicle routing models and compare their results depending on the system parameters.

Keywords: vehicle routing, alternative links between nodes, mixed integer linear programming, triple bottom line accounting

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Abhigna Bhatt, Arnab Banerjee

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A periodic system with only a single coupling degree of freedom is called a monocoupled system. Monocoupled systems with mechanisms like mass in the mass system generates effective negative mass, mass connected with rigid links generates inertial amplification, and spring-mass connected with a rigid link generateseffective negative stiffness. In this paper, the representative unit cell is introduced, considering all three mechanisms combined. Further, the dynamic stiffness matrix of the unit cell is constructed, and the dispersion relation is obtained by applying the Bloch theorem. The frequency response function is also calculated for the finite length of periodic unit cells. Moreover, the input displacement signal is given to the finite length of periodic structure and using inverse Fourier transform to visualize the wave propagation in the time domain. This visualization explains the sudden attenuation in metamaterial due to energy dissipation by an embedded resonator at the resonance frequency. The visualization created for wave propagation is found necessary to understand the insights of physics behind the attenuation characteristics of the system.

Keywords: mono coupled system, negative effective mass, negative effective stiffness, inertial amplifier, fourier transform

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Shih Yu Pan, Pao Chen Hung, Chuan Yao Lin, Charles C.-K. Chou, Yu Chi Lin, Kai Hsien Chi

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This study analyzed 16 atmospheric PAHs species which were controlled by USEPA and IARC. To measure the concentration of PAHs, four rural sampling sites and two urban sampling sites were selected in Central Taiwan during spring and summer. In central Taiwan, the rural sampling stations were located in the downstream of Da-An River, Da-Jang River, Wu River and Chuo-shui River. On the other hand, the urban sampling sites were located in Taichung district and close to the roadside. Ambient air samples of both vapor phase and particle phase of PAHs compounds were collected using high volume sampling trains (Analitica). The sampling media were polyurethane foam (PUF) with XAD2 and quartz fiber filters. Diagnostic ratio, Principal component analysis (PCA), Positive Matrix Factorization (PMF) models were used to evaluate the apportionment of PAHs in the atmosphere and speculate the relative contribution of various emission sources. Because of the high temperature and low wind speed, high PAHs concentration in the atmosphere was observed. The total PAHs concentration, especially in vapor phase, had significant change during summer. During the sampling periods the total PAHs concentration of atmospheric at four rural and two urban sampling sites in spring and summer were 3.70±0.40 ng/m3,3.40±0.63 ng/m3,5.22±1.24 ng/m3,7.23±0.37 ng/m3,7.46±2.36 ng/m3,6.21±0.55 ng/m3　; 15.0± 0.14 ng/m3,18.8±8.05 ng/m3,20.2±8.58 ng/m3,16.1±3.75 ng/m3,29.8±10.4 ng/m3,35.3±11.8 ng/m3, respectively. In order to identify PAHs sources, we used diagnostic ratio to classify the emission sources. The potential sources were diesel combustion and gasoline combustion in spring and summer, respectively. According to the principal component analysis (PCA), the PC1 and PC2 had 23.8%, 20.4% variance and 21.3%, 17.1% variance in spring and summer, respectively. Especially high molecular weight PAHs (BaP, IND, BghiP, Flu, Phe, Flt, Pyr) were dominated in spring when low molecular weight PAHs (AcPy, Ant, Acp, Flu) because of the dominating high temperatures were dominated in the summer. Analysis by using PMF model found the sources of PAHs in spring were stationary sources (34%), vehicle emissions (24%), coal combustion (23%) and petrochemical fuel gas (19%), while in summer the emission sources were petrochemical fuel gas (34%), the natural environment of volatile organic compounds (29%), coal combustion (19%) and stationary sources (18%).

Keywords: PAHs, source identification, diagnostic ratio, principal component analysis, positive matrix factorization

Procedia PDF Downloads 241