Search results for: gaussian selection operator

Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

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his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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Authors: Stylianos Kampakis

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This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features.

Keywords: neural networks, feature selection, regularization, aggressive reweighting

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Authors: Amit Kumar Dwivedi, Priyanko Ghosh

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Data Envelopment analysis (DEA) has been used to calculate the technical and scale efficiency measures of the public and private sugar manufacturing firms of the Indian Sugar Industry (2006 to 2010). Within DEA framework, the input & Output oriented Variable Returns to Scale (VRS) & Constant Return to Scale (CRS) model is employed for the study of Decision making units (DMUs). A representative sample of 43 firms which account for major portion of the total market share is studied. The selection criterion for the inclusion of a firm in the analysis was the total sales of INR 5,000 million or more in the year 2010. After reviewing the literature it is found that no study has been conducted in the context of Indian sugar manufacturing firms in the Post-liberalization era which motivates us to initiate the study.

Keywords: technical efficiency, Indian sugar manufacturing units, DEA, input output oriented

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Authors: Nancy Chun Feng, Janet S. Greenlee

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Nonprofit empirical research has grown substantially in recent years. In this paper, the authors provide a detailed review of a selection of representative recent empirical nonprofit research, organized chronologically within each accounting topic in major accounting areas (i.e. auditing, compensation, financial accounting, governance, managerial accounting, and taxation). The authors also include in the appendix an annotated bibliography of nonprofit accounting empirical research that has been published in major journals since 2016, also organized by major accounting areas. This appendix includes not only references but also their major findings. This paper should be of interest for researchers who are keen to learn recent findings of nonprofit empirical research in these major accounting areas.

Keywords: nonprofit accounting, nonprofit auditing, nonprofit financial performance, nonprofit governance

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Authors: Youn-Sung Kim, Jin-Ho Jo, Mi-Sung Kim, Jae-Kun Lee

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Accelerated life cycle test is applied to various products or components in order to reduce the time of life cycle test in industry. It must be considered for many test conditions according to the product characteristics for the test and the selection of acceleration parameter is especially very important. We have carried out the general life cycle test and the accelerated life cycle test by applying the acceleration factor (AF) considering the characteristics of brushless DC (BLDC) motor for washing machine. The final purpose of this study is to verify the validity by analyzing the results of the general life cycle test and the accelerated life cycle test. It will make it possible to reduce the life test time through the reasonable accelerated life cycle test.

Keywords: accelerated life cycle test, reliability test, motor for washing machine, brushless dc motor test

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Authors: Daniel Tarrazó-Serrano, Sergio Pérez-López, Sergio Castiñeira-Ibáñez, Pilar Candelas, Constanza Rubio

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Zone Plates (ZPs) are used in many areas of physics where planar fabrication is advantageous in comparison with conventional curved lenses. There are several types of ZPs, such as the well-known Fresnel ZPs or the more recent Fractal ZPs and Fibonacci ZPs. The material selection of the lens plays a very important role in the beam modulation control. This work presents a comparison between two Fresnel ZP made from different materials in the ultrasound domain: Polylactic Acid (PLA) and brass. PLA is the most common material used in commercial 3D-printers due to its high design flexibility and low cost. Numerical simulations based on Finite Element Method (FEM) and experimental results are shown, and they prove that the focusing capabilities of brass ZPs and PLA ZPs are similar. For this reason, PLA is proposed as a Magnetic Resonance Imaging (MRI) compatible material with great potential for therapeutic ultrasound focusing applications.

Keywords: FZP, PLA, focus, ultrasound, MRI

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Authors: Astrid Rivera, Diego Villatoro

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The world population increases at an accelerated pace, and it is essential to find solutions to feed the population. Nevertheless, crop diversity has significantly decreased in the last years, and the increase in food production is not the optimal solution. It is essential to consider the origin of the food, the nutriment contributions, among other dimensions. In this regard, biodiversity plays an indispensable role when designing an effective strategy to face the actual food security problems. Consequently, the purpose of this work is to analyze biodiversity in the Mexican national food production and suggest a proper crop selection based on companion plants, for which empirical and experimental knowledge shows a better scenery than current efforts. As a result, we get a set of crop recommendations to increase production in sustainable and nutritive planning. It is essential to explore more feasible options to advance sustainable development goals beyond an economic aspect.

Keywords: biodiversity, food security, companion plats, nutrition

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Authors: Heather Warfield, Brad Genereux

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Military personnel encounter a number of challenges when separating from military service to include career uncertainty, relational/family dynamics, trauma as a result of military experiences, reconceptualization of identity, and existential issues related to purpose, meaning making and framing of the military experience(s). Embedded within military culture are well-defined rites of passage and a significant sense of belonging. Consequently, transition out of the military can result in the loss of such rites of passage and belongingness. However, a pilgrimage journey can provide the time and space to engage in a new rite of passage, to construct a new pilgrim identity, and a to develop deep social relationships that lead to a sense of belongingness to a particular pilgrim community as well as to the global community of pilgrims across numerous types of pilgrimage journeys. The aims of the current paper are to demonstrate the rationale for why pilgrimage journeys are particularly significant for military veterans, provide an overview of an innovative program that facilitates the Camino de Santiago pilgrimage for military veterans, and discusses the lessons learned from the initial pilot project of a recently established program. Veterans on the Camino (VOC) is an emerging nongovernmental organization in the USA. Founded by a military veteran, after leaving his military career, the primary objective of the organization is to facilitate healing for veterans via the Camino de Santiago pilgrimage journey. As part of the program, participants complete a semi-structured interview at three time points – pre, during, and post journey. The interview items are based on ongoing research by the principal investigator and address such constructs as meaning-making, wellbeing, therapeutic benefits and transformation. In addition, program participants complete The Sources of Meaning and Meaning in Life Questionnaire (SoMe). The pilot program occurred in the spring of 2017. Five participants were selected after an extensive application process and review by a three-person selection board. The selection criteria included demonstrated compatibility with the program objectives (i.e., prior military experience, availability for a 40 day journey, and awareness of the need for a transformational intervention). The participants were connected as a group through a private Facebook site and interacted with one another for several months prior to the pilgrimage. Additionally, the participants were interviewed prior to beginning the pilgrimage, at one point during the pilgrimage and immediately following the conclusion of the pilgrimage journey. The interviews yielded themes related to loss, meaning construction, renewed hope in humanity, and a commitment to future goals. The lessons learned from this pilot project included a confirmation of the need for such a program, a need for greater focus on logistical details, and the recognition that the pilgrimage experience needs to continue in some manner once the veterans return home.

Keywords: pilgrimage, healing, military veterans, Camino de Santiago

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Authors: Robin Molinier

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Industrial symbiosis (I.S) rely on two modes of cooperation that are infrastructure sharing and resource substitution to obtain economic and environmental benefits. The former consists in the intensification of use of an asset while the latter is based on the use of waste, fatal energy (and utilities) as alternatives to standard inputs. Both modes, in fact, rely on the shift from a business-as-usual functioning towards an alternative production system structure so that in a business point of view the distinction is not clear. In order to investigate the way those cooperation modes can be distinguished, we consider the stakeholders' interplay in the business model structure regarding their resources and requirements. For infrastructure sharing (following economic engineering literature) the cost function of capacity induces economies of scale so that demand pooling reduces global expanses. Grassroot investment sizing decision and the ex-post pricing strongly depends on the design optimization phase for capacity sizing whereas ex-post operational cost sharing minimizing budgets are less dependent upon production rates. Value is then mainly design driven. For resource substitution, synergies value stems from availability and is at risk regarding both supplier and user load profiles and market prices of the standard input. Baseline input purchasing cost reduction is thus more driven by the operational phase of the symbiosis and must be analyzed within the whole sourcing policy (including diversification strategies and expensive back-up replacement). Moreover, while resource substitution involves a chain of intermediate processors to match quality requirements, the infrastructure model relies on a single operator whose competencies allow to produce non-rival goods. Transaction costs appear higher in resource substitution synergies due to the high level of customization which induces asset specificity, and non-homogeneity following transaction costs economics arguments.

Keywords: business model, capacity, sourcing, synergies

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Authors: Huy Q. Tran, Bac V. Nguyen, Choonghyun Kang, Jungwon Huh

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Jumbo container crane is an important part of port structures that needs to be designed properly, even when the port locates in low seismicity zone such as in Korea. In this paper, 30 artificial ground motions derived from the elastic response spectra of Korean Building Code (2005) are used for time history analysis. It is found that the uplift might not occur in this analysis when the crane locates in the low seismic zone. Therefore, a selection of a pinned or a gap element for base supporting has not much effect on the determination of the total base shear. The relationships between the total base shear and peak ground acceleration (PGA) and the relationships between the portal drift and the PGA are proposed in this study.

Keywords: jumbo container crane, portal drift, time history analysis, total base shear

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Authors: Devendra Kumar Pandey, Debabrata Chakraborty

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The advancement in various concrete ingredients like plasticizers, additives and fibers, etc. has enabled concrete technologists to develop many viable varieties of special concretes in recent decades. Such various varieties of concrete have significant enhancement in green as well as hardened properties of concrete. A prudent selection of appropriate type of concrete can resolve many design and application issues in construction projects. This paper focuses on usage of self-compacting concrete, high early strength concrete, structural lightweight concrete, fiber reinforced concrete, high performance concrete and ultra-high strength concrete in the structures. The modified properties of strength at various ages, flowability, porosity, equilibrium density, flexural strength, elasticity, permeability etc. need to be carefully studied and incorporated into the design of the structures. The paper demonstrates various mixture combinations and the concrete properties that can be leveraged. The selection of such products based on the end use of structures has been proposed in order to efficiently utilize the modified characteristics of these concrete varieties. The study involves mapping the characteristics with benefits and savings for the structure from design perspective. Self-compacting concrete in the structure is characterized by high shuttering loads, better finish, and feasibility of closer reinforcement spacing. The structural design procedures can be modified to specify higher formwork strength, height of vertical members, cover reduction and increased ductility. The transverse reinforcement can be spaced at closer intervals compared to regular structural concrete. It allows structural lightweight concrete structures to be designed for reduced dead load, increased insulation properties. Member dimensions and steel requirement can be reduced proportionate to about 25 to 35 percent reduction in the dead load due to self-weight of concrete. Steel fiber reinforced concrete can be used to design grade slabs without primary reinforcement because of 70 to 100 percent higher tensile strength. The design procedures incorporate reduction in thickness and joint spacing. High performance concrete employs increase in the life of the structures by improvement in paste characteristics and durability by incorporating supplementary cementitious materials. Often, these are also designed for slower heat generation in the initial phase of hydration. The structural designer can incorporate the slow development of strength in the design and specify 56 or 90 days strength requirement. For designing high rise building structures, creep and elasticity properties of such concrete also need to be considered. Lastly, certain structures require a performance under loading conditions much earlier than final maturity of concrete. High early strength concrete has been designed to cater to a variety of usages at various ages as early as 8 to 12 hours. Therefore, an understanding of concrete performance specifications for special concrete is a definite door towards a superior structural design approach.

Keywords: high performance concrete, special concrete, structural design, structural lightweight concrete

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Authors: Maya Irjayanti

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Local creativity utilization has been a strategic investment to be expanded as a creative industry due to its significant contribution to the national gross domestic product. Many developed and developing countries look toward creative industries as an agenda for the economic growth. This study aims to identify the role of local potential for creative industries from various empirical studies. The method performed in this study will involve a peer-reviewed journal articles and conference papers review addressing local potential and creative industries. The literature review analysis will include several steps: material collection, descriptive analysis, category selection, and material evaluation. Finally, the outcome expected provides a creative industries clustering based on the local potential of various nations. In addition, the finding of this study will be used as future research reference to explore a particular area with well-known aspects of local potential for creative industry products.

Keywords: business, creativity, local potential, local wisdom

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Authors: Chris Cadman, Marcel Strauss

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Background: In 2020, the University Hospital Wishaw in the United Kingdom became the centre for trauma and orthopaedics within its health board. This resulted in the majority of patients with suspected cauda equina syndrome (CES) being assessed and imaged at this site, putting an increased demand on MR imaging and displacing other previous activity. Following this transition, imaging requests for CES did not always follow national guidelines and would often be missing important clinical and safety information. There also appeared to be a very low positive scan rate compared with previously reported studies. In an attempt to improve patient selection and reduce the burden of CES imaging at this site clinical audit was performed. Methods: A total of 250 consecutive patients imaged to assess for CES were evaluated. Patients had to have presented to either the emergency or orthopaedic department acutely with a presenting complaint of suspected CES. Patients were excluded if they were not admitted acutely or were assessed by other clinical specialities. In total, 233 patients were included. Requests were assessed for appropriate clinical history, accurate and complete clinical assessment and MRI safety information. Clinical assessment was allocated a score of 1-6 based on information relating to history of pain, level of pain, dermatomes/myotomes affected, peri-anal paraesthesia/anaesthesia, anal tone and post-void bladder volume with each element scoring one point. Images were assessed for positive findings of CES, acquired spinal stenosis or nerve root compression. Results: Overall, 73% of requests had a clear clinical history of CES. The urgency of the request for imaging was given in 23% of cases. The mean clinical assessment score was 3.7 out of a total of 6. Overall, 2% of scans were positive for CES, 29% had acquired spinal stenosis and 30% had nerve root compression. For patients with CES, 75% had acute neurological signs compared with 68% of the study population. CES patients had a mean clinical history score of 5.3 compared with 3.7 for the study population. Overall, 95% of requests had appropriate MRI safety information. Discussion: it study included 233 patients who underwent specialist assessment and referral for MR imaging for suspected CES. Despite the serious nature of this condition, a large proportion of imaging requests did not have a clear clinical query of CES and the level of urgency was not given, which could potentially lead to a delay in imaging and treatment. Clinical examination was often also incomplete, which can make triaging of patients presenting with similar symptoms challenging. The positive rate for CES was only 2%, much below other studies which had positive rates of 6–40% with a large meta-analysis finding a mean positive rate of 19%. These findings demonstrate an opportunity to improve the quality of imaging requests for suspected CES. This may help to improve patient selection for imaging and result in a positive rate for CES imaging that is more in line with other centres.

Keywords: cauda equina syndrome, acute back pain, MRI, spine

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Authors: Roberta Martino, Viviana Ventre

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Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

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Authors: L. Pigon, S. Kot, J. K. Grabara

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Nowadays, with organizations facing the challenges of increasing competitiveness, human capital accumulated by the organization is one of the elements that strongly differentiate between companies. Efficient management in the competition area requires to manage the competencies of their employees to be suitable to the market fluctuations. The aim of the paper was to determine how employee training to improve their competencies is verified. The survey was conducted among 37 respondents involved in selection of training providers and training programs in their enterprises. The results showed that all organizations use training survey as a basic method for evaluation of training effectiveness. Depending on the training contents and organization, the questionnaires contain various questions. Most of these surveys are composed of the three basic blocks: the trainer's assessment, the evaluation of the training contents, the assessment of the materials and the place of the organisation. None of the organization surveys conducted regular job-related observations or examined the attitudes of the training participants.

Keywords: human capital, competencies, training effectiveness, sale department

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Authors: Shahram Nanekarani, Majid Goodarzi, Majid Khosravi

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The present study aimed at analyzing of ovine major histocompatibility complex class II (Ovar II) DRB1 gene second exon in Lori Sheep breed. The MHC plays a central role in the control of disease resistance and immunological response. Genomic DNA from blood samples of 124 sheep was extracted and a 296 bp MHC exon 2 fragment was amplified using polymerase chain reaction. PCR products were characterized by the restriction fragment length polymorphism technique using Hin1I restriction enzyme. The PCRRFLP patterns showed three genotypes, AA, AB and BB with frequency of 0.282, 0.573 and 0.145, respectively. There was no significant (P > 0.05) deviation from Hardy–Weinberg equilibrium for this locus in this population. The results of the present study indicate that exon 2 of the Ovar-DRB1 gene is highly polymorphic in Lori sheep and could be considered as an important marker assisted selection, for improvement of immunity in sheep.

Keywords: MHC-DRB1 gene, polymorphism, PCR-RFLP, lori sheep

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Dora Martins, Susana Silva, Cândida Silva

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Human Resources Management (HRM) has been recognized by academics and practitioners as an important element in organizations. Therefore, this paper explores the best practices of HRM and seeks to understand the level of participation in the development of these practices by human resources managers in the hospitality industry and compare it with other industries. Thus, the study compared the HRM practices of companies in the hospitality sector with HRM practices of companies in other sectors, and identifies the main differences between their HRM practices. The results show that the most frequent HRM practices in all companies, independently of its sector of activity, are hiring and training. When comparing hospitality sector with other sectors of activity, some differences were noticed, namely in the adoption of the practices of communication and information sharing, and of recruitment and selection. According to these results, the paper discusses the major theoretical and practical implications. Suggestions for future research are also presented.

Keywords: exploratory study, human resources management practices, human resources manager, hospitality companies, Portuguese companies

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

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Authors: Piotr Muzyk, Beata Morawiec, Mariusz Opara, Andrzej Tomasik, Brygida Przywara-Chowaniec, Wojciech Jachec, Ewa Nowalany-Kozielska, Damian Kawecki

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Background: Coronary bifurcation is one of the most complex lesion in patients with coronary ar-tery disease. Provisional T-stenting is currently one of the recommended techniques. The aim was to assess optimal methods of treatment in the era of drug-eluting stents (DES). Methods: The regis-try consisted of data from 1916 patients treated with coronary percutaneous interventions (PCI) using either first- or second-generation DES. Patients with bifurcation lesion entered the analysis. Major adverse cardiac and cardiovascular events (MACCE) were assessed at one year of follow-up and comprised of death, acute myocardial infarction (AMI), repeated PCI (re-PCI) of target ves-sel and stroke. Results: Of 1916 registry patients, 204 patients (11%) were diagnosed with bifurcation lesion >50% and entered the analysis. The most commonly used technique was provi-sional T-stenting (141 patients, 69%). Optimization with kissing-balloons technique was performed in 45 patients (22%). In 59 patients (29%) second-generation DES was implanted, while in 112 pa-tients (55%), first-generation DES was used. In 33 patients (16%) both types of DES were used. The procedure success rate (TIMI 3 flow) was achieved in 98% of patients. In one-year follow-up, there were 39 MACCE (19%) (9 deaths, 17 AMI, 16 re-PCI and 5 strokes). Provisional T-stenting resulted in similar rate of MACCE to other techniques (16% vs. 5%, p=0.27) and similar occurrence of re-PCI (6% vs. 2%, p=0.78). The results of post-PCI kissing-balloon technique gave equal out-comes with 3% vs. 16% of MACCE in patients in whom no optimization technique was used (p=0.39). The type of implanted DES (second- vs. first-generation) had no influence on MACCE (4% vs 14%, respectively, p=0.12) and re-PCI (1.7% vs. 51% patients, respectively, p=0.28). Con-clusions: The treatment of bifurcation lesions with PCI represent high-risk procedures with high rate of MACCE. Stenting technique, optimization of PCI and the generation of implanted stent should be personalized for each case to balance risk of the procedure. In this setting, the operator experience might be the factor of better outcome, which should be further investigated.

Keywords: coronary bifurcation, drug eluting stents, long-term follow-up, percutaneous coronary interventions

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Authors: Darius Jakimavicius

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Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: E. Botchway, C. Godfrey, V. Anderson, C. Catroppa

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Introduction: Sleep disturbances are common after childhood traumatic brain injury (TBI). This systematic review aimed to assess the prevalence, types, and predictors of sleep disturbances in childhood TBI. Methods: Medline, Pubmed, PsychInfo, Web of Science, and EMBASE databases were searched. Out of the 547 articles assessed, 15 met selection criteria for this review. Results: Sleep disturbances were common in children and adolescents with TBI, irrespective of injury severity. Excessive daytime sleepiness and insomnia were the most common sleep disturbances reported. Sleep disturbance was predicted by sex, injury severity, pre-existing sleep disturbances, younger age, pain, and high body mass index. Conclusions: Sleep disturbances are highly prevalent in childhood TBI, regardless of the injury severity. Routine assessment of sleep in survivors of childhood TBI is recommended.

Keywords: traumatic brain injury, sleep diatiurbances, childhood, systematic review

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: Kajingulu Malandala, Ranganai Edmore

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The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

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Authors: Maisa Sales Gama Tobias, Humberto de Paiva Junior, Luciano Silva Brito, Rui António Rodrigues Ramos

Abstract:

Waterway transport in the Amazon was the first means of access and occupation in the region. For the economic and social matter of high importance, still nowadays one of the main transport modes to several places in the region. To some places, still the only transport mode. With the advent of the pandemic, transport companies that already faced management challenges began to experience unprecedented structural changes and trends in trade and global supply chains. Thus, companies need operational reorganization to maintain the sustainability of the service under the penalty of loss of demand. Allied to this fact, it was observed that the demand presented behavior changes to adapt to this new moment. However, the lack of information about these changes makes it difficult to find solutions to maintain the quality of service. This work aimed to characterize the changes in the demand of waterway passengers through an empirical study with field research involving interviews with users and crew, on-board journeys, and visits to the waterway service company. The case study is the route Belém-Camara, on Marajó Island, in the state of Pará. This line is traditionally the only means of transport for this route, besides air transport on a much smaller scale. The collected data had a descriptive and analytical statistical treatment presented in this work. As the main result, the COVID-19 pandemic has caused significant changes, mainly in trip time and motives and, in the perception itself on service quality by part of the demand, with the increase of trip time and the feeling of insecurity. In conclusion, the service operator must review cost management and business survival strategies and tactics. The viability of the service and the social guarantee of transport proved to be threatened, putting at risk the service to the riverside populations.

Keywords: demand of waterway transport passengers, data analysis, COVID-19, amazonia

Procedia PDF Downloads 113

Authors: Xia Chen, Hua-Quan Yang, Shi-Hua Zhou

Abstract:

Alkali-active sandstone aggregate was ground by vertical and ball mill into particles with residue over 45 μm less than 12%, and investigations have been launched on particles distribution and characterization of ground sandstone powder, fluidity, heat of hydration, strength as well as hydration products morphology of pastes with incorporation of ground sandstone powder. Results indicated that ground alkali-active sandstone powder with residue over 45 μm less than 8% was easily obtainable, and specific surface area was more sensitive to characterize its fineness with extension of grinding length. Incorporation of sandstone powder resulted in higher water demand and lower strength, advanced hydration of C₃A and C₂S within 3days and refined pore structure. Based on its manufacturing, characteristics and influence on properties of pastes, it was concluded that sandstone powder was a good selection for use in concrete as mineral admixture.

Keywords: concrete, mineral admixture, hydration, structure

Procedia PDF Downloads 326

Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

Abstract:

The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

Procedia PDF Downloads 290

Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

Abstract:

Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

Procedia PDF Downloads 125

Authors: Amir Azaron

Abstract:

In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

Procedia PDF Downloads 295