Search results for: Maximum Entropy Bootstrapping approach

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: Sevcan Ozturk

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The overall aim of this paper is to present a Kierkegaardian approach to Iqbal’s use of literature as a form of communication. Despite belonging to different historical, cultural, and religious backgrounds, the philosophical approaches of Soren Kierkegaard, ‘the father of existentialism,' and Muhammad Iqbal ‘the spiritual father of Pakistan’ present certain parallels. Both Kierkegaard and Iqbal take human existence as the starting point for their reflections, emphasise the subject of becoming genuine religious personalities, and develop a notion of the self. While doing these they both adopt parallel methods, employ literary techniques and poetical forms, and use their literary works as a form of communication. The problem is that Iqbal does not provide a clear account of his method as Kierkegaard does in his works. As a result, Iqbal’s literary approach appears to be a collection of contradictions. This is mainly because despite he writes most of his works in the poetical form, he condemns all kinds of art including poetry. Moreover, while attacking on Islamic mysticism, he, at the same time, uses classical literary forms, and a number of traditional mystical, poetic symbols. This paper will argue that the contradictions found in Iqbal’s approach are actually a significant part of Iqbal’s way of communicating his reader. It is the contention of this paper that with the help of the parallels between the literary and philosophical theories of Kierkegaard and Iqbal, the application of Kierkegaard’s method to Iqbal’s use of poetry as a communicative act will make it possible to dispel the seeming ambiguities in Iqbal’s literary approach. The application of Kierkegaard’s theory to Iqbal’s literary method will include an analysis of the main principles of Kierkegaard’s own literary technique of ‘indirect communication,' which is a crucial term of his existentialist philosophy. Second, the clash between what Iqbal’s says about art and poetry and what he does will be highlighted in the light of Kierkegaardian theory of indirect communication. It will be argued that Iqbal’s literary technique can be considered as a form of ‘indirect communication,' and that reading his technique in this way helps on dispelling the contradictions in his approach. It is hoped that this paper will cultivate a dialogue between those who work in the fields of comparative philosophy Kierkegaard studies, existentialism, contemporary Islamic thought, Iqbal studies, and literary criticism.

Keywords: comparative philosophy, existentialism, indirect communication, intercultural philosophy, literary communication, Muhammad Iqbal, Soren Kierkegaard

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Authors: Peter Sabev, Katalina Grigorova

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Test automation allows performing difficult and time consuming manual software testing tasks efficiently, quickly and repeatedly. However, development and maintenance of automated tests is expensive, so it needs a proper prioritization what to automate first. This paper describes a simple yet efficient approach for such prioritization of test cases based on the effort needed for both manual execution and software test automation. The suggested approach is very flexible because it allows working with a variety of assessment methods, and adding or removing new candidates at any time. The theoretical ideas presented in this article have been successfully applied in real world situations in several software companies by the authors and their colleagues including testing of real estate websites, cryptographic and authentication solutions, OSGi-based middleware framework that has been applied in various systems for smart homes, connected cars, production plants, sensors, home appliances, car head units and engine control units (ECU), vending machines, medical devices, industry equipment and other devices that either contain or are connected to an embedded service gateway.

Keywords: automated testing, manual testing, test automation, software testing, test prioritization

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Authors: Monalisa Pradhan, Ajana Dutta, Irshad Kariyattuparamb Abbas, Boby Joseph, T. N. Guru Row, Diptikanta Swain, Gopal K. Pradhan

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Compounds with the Vanthoffite crystal structure having general formula Na6M(SO₄)₄ (M= Mg, Mn, Ni , Co, Fe, Cu and Zn) display a variety of intriguing physical properties intimately related to their structural arrangements. The compound Na6Mn(SO4)4 shows antiferromagnetic ordering at low temperature where the in-plane Mn-O•••O-Mn interactions facilitates antiferromagnetic ordering via a super-exchange interaction between the Mn atoms through the oxygen atoms . The inter-atomic bond distances and angles can easily be tuned by applying external pressure and can be probed using high resolution X-ray diffraction. Moreover, because the magnetic interaction among the Mn atoms are super-exchange type via Mn-O•••O-Mn path, the variation of the Mn-O•••O-Mn dihedral angle and Mn-O bond distances under high pressure inevitably affects the magnetic properties. Therefore, it is evident that high pressure studies on the magnetically ordered materials would shed light on the interplay between their structural properties and magnetic ordering. This will indeed confirm the role of buckling of the Mn-O polyhedral in understanding the origin of anti-ferromagnetism. In this context, we carried out the pressure dependent X-ray diffraction measurement in a diamond anvil cell (DAC) up to a maximum pressure of 17 GPa to study the phase transition and determine equation of state from the volume compression data. Upon increasing the pressure, we didn’t observe any new diffraction peaks or sudden discontinuity in the pressure dependences of the d values up to the maximum achieved pressure of ~17 GPa. However, it is noticed that beyond 12 GPa the a and b lattice parameters become identical while there is a discontinuity in the β value around the same pressure. This indicates a subtle transition to a pseudo-monoclinic phase. Using the third order Birch-Murnaghan equation of state (EOS) to fit the volume compression data for the entire range, we found the bulk modulus (B0) to be 44 GPa. If we consider the subtle transition at 12 GPa, we tried to fit another equation state for the volume beyond 12 GPa using the second order Birch-Murnaghan EOS. This gives a bulk modulus of ~ 34 GPa for this phase.

Keywords: mineral, structural phase transition, high pressure XRD, spectroscopy

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Authors: Sifeddine Abderrahmani, Sonia Bouafia

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The finite element method is the most practical tool for the analysis of structures, whatever the geometrical shape and behavior. It is extensively used in many high-tech industries, such as civil or military engineering, for the modeling of bridges, motor bodies, fuselages, and airplane wings. Additionally, experience demonstrates that engineers like modeling their structures using the most basic finite elements. Numerous models of finite elements may be utilized in the numerical analysis depending on the interpolation field that is selected, and it is generally known that convergence to the proper value will occur considerably more quickly with a good displacement pattern than with a poor pattern, saving computation time. The method for creating finite elements using the strain approach (S.B.A.) is presented in this presentation. When the results are compared with those provided by equivalent displacement-based elements, having the same total number of degrees of freedom, an excellent convergence can be obtained through some application and validation tests using recently developed membrane elements, plate bending elements, and flat shell elements. The effectiveness and performance of the strain-based finite elements in modeling structures are proven by the findings for deflections and stresses.

Keywords: finite elements, plate bending, strain approach, displacement formulation, shell element

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Authors: Majid Pourahmadi

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The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: microwave imaging, time reversal, MUSIC algorithm, minimum description length (MDL)

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Authors: Johannes Atug, Stefan Braunreuther, Gunther Reinhart

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Volatile markets, as well as increasing global competition in manufacturing, lead to a high demand of flexible and agile production systems. These advanced production systems in turn conduct to high capital expenditure along with high investment risks. Developments in production regarding digitalization and cyber-physical systems result to a merger of informational- and operational technology. The approach of this paper is to benefit from this merger and present a framework of a production network with scalable production capacity and low capital expenditure by adaptation of the IT concept 'everything as a service' into the production environment.

Keywords: digital manufacturing system, everything as a service, reconfigurable production, value network

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Authors: Abid Kousay

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Appeared and developed essentially in large companies and multinationals, Talent Management (TM) in Small and Medium-Sized Enterprises (SMEs) has remained an under-explored subject till today. Although the literature on TM in the Anglo-Saxon context is developing, it remains monopolized in non-European contexts, especially in France. Therefore, this article aims to address these shortcomings through contributing to TM issues, by adopting a multilevel approach holding the goal of reaching a global holistic vision of interactions between various levels, while applying TM. A qualitative research study carried out within 12 SMEs in France, built on the methodological perspective of grounded theory, will be used in order to go beyond description, to generate or discover a theory or even a unified theoretical explanation. Our theoretical contributions are the results of the grounded theory, the fruit of context considerations and the dynamic of the multilevel approach. We aim firstly to determine the perception of talent and TM in SMEs. Secondly, we formalize TM in SME through the empowerment of all 3 levels in the organization (individual, collective, and organizational). And we generate a multilevel dynamic system model, highlighting the institutionalization dimension in SMEs and the managerial conviction characterized by the domination of the leader's role. Thirdly, this first study shed the light on the importance of rigorous implementation of TM in SMEs in France by directing CEO and HR and TM managers to focus on elements that upstream TM implementation and influence the system internally. Indeed, our systematic multilevel approach policy reminds them of the importance of the strategic alignment while translating TM policy into strategies and practices in SMEs.

Keywords: French context, institutionalization, talent, multilevel approach, talent management system

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Authors: Christos Konstantopoulos, Thomas Ussmueller

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Digital low drop-out regulators, in contrast to analog counterparts, provide an architecture of sub-1 V regulation with low power consumption, high power efficiency, and system integration. Towards an optimized integration in the ultra-low-power system-on-chip Internet of Things architecture that is operated through a radio frequency energy harvesting scheme, the D-LDO regulator should constitute the main regulator that operates the master-clock and rest loads of the SoC. In this context, we present a D-LDO with linear search coarse regulation and asynchronous fine regulation, which incorporates an in-regulator clock generation unit that provides an autonomous, self-start-up, and power-efficient D-LDO design. In contrast to contemporary D-LDO designs that employ ring-oscillator architecture which start-up time is dependent on the frequency, this work presents a fast start-up burst oscillator based on a high-gain stage with wake-up time independent of coarse regulation frequency. The design is implemented in a 55-nm Global Foundries CMOS process. With the purpose to validate the self-start-up capability of the presented D-LDO in the presence of ultra-low input power, an on-chip test-bench with an RF rectifier is implemented as well, which provides the RF to DC operation and feeds the D-LDO. Power efficiency and load regulation curves of the D-LDO are presented as extracted from the RF to regulated DC operation. The D-LDO regulator presents 83.6 % power efficiency during the RF to DC operation with a 3.65 uA load current and voltage regulator referred input power of -27 dBm. It succeeds 486 nA maximum quiescent current with CL 75 pF, the maximum current efficiency of 99.2%, and 1.16x power efficiency improvement compared to analog voltage regulator counterpart oriented to SoC IoT loads. Complementary, the transient performance of the D-LDO is evaluated under the transient droop test, and the achieved figure-of-merit is compared with state-of-art implementations.

Keywords: D-LDO, Internet of Things, RF energy harvesting, voltage regulators

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Authors: Benmansour Nassima, Benmansour Souheyla

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The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

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Authors: Maria L. Ulloa, Ruth M. Crawford, Stephanie Kelly, Joey Domdom

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In recent decades health and social service delivery have become more collaborative and interdisciplinary. Emerging trends suggest the need for an integrative and interprofessional approach to meet the challenges faced by professionals navigating the complexities of health and social service practice environments. Terms such as multidisciplinary practice, interprofessional collaboration, interprofessional education and transprofessional practice have become the common language used across a range of social services and health providers in western democratic systems. In Aotearoa New Zealand, one example of an interprofessional collaborative approach to curriculum design and delivery in health and social service is the development of an innovative Masters of Professional Practice programme. This qualification is the result of a strategic partnership between two tertiary institutions – Whitireia New Zealand (NZ) and the Wellington Institute of Technology (Weltec) in Wellington. The Master of Professional Practice programme was designed and delivered from the perspective of a collaborative, interprofessional and relational approach. Teachers and students in the programme come from a diverse range of cultural, professional and personal backgrounds and are engaged in courses using a blended learning approach that incorporates the values and pedagogies of interprofessional education. Students are actively engaged in professional practice while undertaking the programme. This presentation describes the themes of exploratory qualitative formative observations of engagement in class and online, student assessments, student research projects, as well as qualitative interviews with the programme teaching staff. These formative findings reveal the development of critical practice skills around the common themes of the programme: research and evidence based practice, education, leadership, working with diversity and advancing critical reflection of professional identities and interprofessional practice. This presentation will provide evidence of enhanced learning experiences in higher education and learning in multi-disciplinary contexts.

Keywords: diversity, exploratory research, interprofessional education, professional identity

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Victor Manuel Alcántara Alza

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The way in which the application of the deep cryogenic treatment DCT(-196°C) affects, applied with subsequent aging, was investigated, regarding the mechanical properties of hardness, toughness and microstructure, applied to martensitic stainless steels, with the aim of establishing a different methodology compared to the traditional DCT cryogenic treatment with subsequent tempering. For this experimental study, a muffle furnace was used, first subjecting the specimens to deep cryogenization in a liquid Nitrogen bath/4h, after being previously austenitized at the following temperatures: 1020-1030-1040-1050 (°C) / 1 hour; and then tempered in oil. A first group of cryogenic samples were subjected to subsequent aging at 150°C, with immersion times: 2.5 -5- 10 - 20 - 50 – 100 (h). The next group was subjected to subsequent tempering at temperatures: 480-500-510-520-530-540 (°C)/ 2h. The hardness tests were carried out under standards, using a Universal Durometer, and the readings were made on the HRC scale. The Impact Resistance tests were carried out in a Charpy machine following the ASTM E 23 – 93ª standard. Measurements were taken in joules. Microscopy was performed at the optical level using a 1000X microscope. It was found: For the entire aging interval, the samples austenitized at 1050°C present greater hardness than austenitized at 1040°C, with the maximum peak aged being at 30h. In all cases, the aged samples exceed the hardness of the tempered samples, even in their minimum values. In post-tempered samples, the tempering temperature hardly have effect on the impact strength of material. In the Cryogenic Treatment: DCT + subsequent aging, the maximum hardness value (58.7 HRC) is linked to an impact toughness value (54J) obtained with aging time of 39h, which is considered an optimal condition. The higher hardness of steel after the DCT treatment is attributed to the transformation of retained austenite into martensite. The microstructure is composed mainly of lath martensite; and the original grain size of the austenite can be appreciated. The choice of the combination: Hardness-toughness, is subject to the required service conditions of steel.

Keywords: deep cryogenic treatment; aged precipitation; martensitic steels;, mechanical properties; martensitic steels, hardness, carbides precipitaion

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

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Authors: B. Petrović, L. Rutonjski, M. Baucal, M. Teodorović, O. Čudić, B. Basarić

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Radiotherapy treatment planning computers use CT data of the patient. For the computation of a treatment plan, treatment planning system must have an information on electron densities of tissues scanned by CT. This information is given by the conversion curve CT (CT number) to ED (electron density), or simply calibration curve. Every treatment planning system (TPS) has built in default CT to ED conversion curves, for the CTs of different manufacturers. However, it is always recommended to verify the CT to ED conversion curve before actual clinical use. Objective of this study was to check how the default curve already provided matches the curve actually measured on a specific CT, and how much it influences the calculation of a treatment planning computer. The examined CT scanners were from the same manufacturer, but four different scanners from three generations. The measurements of all calibration curves were done with the dedicated phantom CIRS 062M Electron Density Phantom. The phantom was scanned, and according to real HU values read at the CT console computer, CT to ED conversion curves were generated for different materials, for same tube voltage 140 kV. Another phantom, CIRS Thorax 002 LFC which represents an average human torso in proportion, density and two-dimensional structure, was used for verification. The treatment planning was done on CT slices of scanned CIRS LFC 002 phantom, for selected cases. Interest points were set in the lungs, and in the spinal cord, and doses recorded in TPS. The overall calculated treatment times for four scanners and default scanner did not differ more than 0.8%. Overall interest point dose in bone differed max 0.6% while for single fields was maximum 2.7% (lateral field). Overall interest point dose in lungs differed max 1.1% while for single fields was maximum 2.6% (lateral field). It is known that user should verify the CT to ED conversion curve, but often, developing countries are facing lack of QA equipment, and often use default data provided. We have concluded that the CT to ED curves obtained differ in certain points of a curve, generally in the region of higher densities. This influences the treatment planning result which is not significant, but definitely does make difference in the calculated dose.

Keywords: Computation of treatment plan, conversion curve, radiotherapy, electron density

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Authors: Nejah Ben Mabrouk, Bassem Jarboui, Habib Chabchoub

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Production and distribution planning is the most important part in supply chain management. In this paper, a NP-hard production-distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize the sum of costs of three items: production setups, inventories and distribution, while determining, for each period, the amount produced, the inventory levels and the delivery trips. To solve this difficult problem, we propose a bi-phase approach based on a Variable Neighbourhood Search (VNS). This heuristic is tested on 90 randomly generated instances from the literature, with 20 periods and 50, 100, 200 customers. Computational results show that our approach outperforms existing solution procedures available in the literature

Keywords: logistic, production, distribution, variable neighbourhood search

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Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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Authors: Lloyd A. Taylor

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An increase in the prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) highlights the need to consider factors that may be exacerbating symptom presentation. Traditional diagnostic criteria provide a little framework for healthcare providers to consider as they attempt to diagnose and treat children with behavioral problems. In fact, aside from exclusion criteria, limited alternative considerations are available, and approaches fail to consider the impact of outside factors that could increase or decrease the likelihood of appropriate diagnosis and success of interventions. This paper will consider specific systems-based factors that influence behavior and intervention successes that, when not considered, could account for the upsurge of diagnoses. These include understanding (1) challenges in the healthcare system, (2) the influence and impact of educators and the educational system, (3) technology use, and (4) patient and parental attitudes about the diagnosis of ADHD. These factors must be considered both individually and as a whole when considering both the increase in diagnoses and the subsequent increases in prescriptions for psychostimulant medication. A theoretical model based on a risk management approach will be presented. Finally, data will be presented that demonstrates pediatric provider satisfaction with this approach to diagnoses and treatment of ADHD as it relates to practice trends.

Keywords: ADHD, diagnostic criteria, risk management model, pediatricians

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Authors: Marzieh Zarei

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Well instability is one of the most fundamental challenges faced by the oil and gas industry. Well wall stability analysis is a gap to be filled in the oil industry. The collection of static data such as well logging leads to the construction of a geomechanical numerical model, which will help in assessing the probable risks in future drilling. In this paper, geomechanical model was designed, and mechanical properties of the rock was determined at all points of the model. It was found the safe mud window was determined and the minimum and maximum mud pressures were determined in the ranges of 70-60 MPa and 110-100 MPa, respectively.

Keywords: geomechanics, numerical model, well stability, in-situ stress, underbalanced drilling

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Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian

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Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.

Keywords: optical flow, variational methods, computer vision, anisotropic operator

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Authors: Michał Gęca, Konrad Pietrykowski, Grzegorz Barański

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The water pump in the compression-ignition internal combustion engine transports a hot coolant along a system of ducts from the engine block to the radiator where coolant temperature is lowered. This part needs to maintain a constant volumetric flow rate. Its power should be regulated to avoid a significant drop in pressure if a coolant flow decreases. The internal combustion engine cooling system uses centrifugal pumps for suction. The paper investigates 4 constructions of engine pumps. The pumps are from diesel engine of a maximum power of 75 kW. Each of them has a different rotor shape, diameter and width. The test stand was created and the geometry inside the all 4 engine blocks was mapped. For a given pump speed on the inverter of the electric engine motor, the valve position was changed and volumetric flow rate, pressure, and power were recorded. Pump speed was regulated from 1200 RPM to 7000 RPM every 300 RPM. The volumetric flow rates and pressure drops for the pump speeds and efficiencies were specified. Accordingly, the operations of each pump were mapped. Our research was to select a pump for the aircraft compression-ignition engine. There was calculated a pressure drop at a given flow on the block and radiator of the designed aircraft engine. The water pump should be lightweight and have a low power demand. This fact shall affect the shape of a rotor and bearings. The pump volumetric flow rate was assumed as 3 kg/s (previous AVL BOOST research model) where the temperature difference was 5°C between the inlet (90°C) and outlet (95°C). Increasing pump speed above the boundary flow power defined by pressure and volumetric flow rate does not increase it but pump efficiency decreases. The maximum total pump efficiency (PCC) is 45-50%. When the pump is driven by low speeds with a 90% closed valve, its overall efficiency drops to 15-20%. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft engine, diesel engine, flow, water pump

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Authors: H. Hajimolahoseini, J. Hashemi, D. Redfearn

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Background: Catheter ablation is an effective therapy for symptomatic atrial fibrillation (AF). The intracardiac electrocardiogram (IEGM) collected during this procedure contains precious information that has not been explored to its full capacity. Novel processing techniques allow looking at these recordings from different perspectives which can lead to improved therapeutic approaches. In our previous study, we showed that variation in amplitude measured through Shannon Entropy could be used as an AF recurrence risk stratification factor in patients who received Ibutilide before the electrograms were recorded. The aim of this study is to further investigate the effect of Ibutilide on characteristics of the recorded signals from the left atrium (LA) of a patient with persistent AF before and after administration of the drug. Methods: The IEGMs collected from different intra-atrial sites of 12 patients were studied and compared before and after Ibutilide administration. First, the before and after Ibutilide IEGMs that were recorded within a Euclidian distance of 3 mm in LA were selected as pairs for comparison. For every selected pair of IEGMs, the Probability Distribution Function (PDF) of the amplitude in time domain and magnitude in frequency domain was estimated using the regression analysis. The PDF represents the relative likelihood of a variable falling within a specific range of values. Results: Our observations showed that in time domain, the PDF of amplitudes was fitted to a Gaussian distribution while in frequency domain, it was fitted to a Rayleigh distribution. Our observations also revealed that after Ibutilide administration, the IEGMs would have significantly narrower short-tailed PDFs both in time and frequency domains. Conclusion: This study shows that the PDFs of the IEGMs before and after administration of Ibutilide represents significantly different properties, both in time and frequency domains. Hence, by fitting the PDF of IEGMs in time domain to a Gaussian distribution or in frequency domain to a Rayleigh distribution, the effect of Ibutilide can easily be tracked using the statistics of their PDF (e.g., standard deviation) while this is difficult through the waveform of IEGMs itself.

Keywords: atrial fibrillation, catheter ablation, probability distribution function, time-frequency characteristics

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Authors: Misagh Faezipour

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System dynamics is a systems engineering approach that can help address the complex challenges in different systems. Little is known about how the brain represents people to predict behavior. This work is based on how the brain simulates different personal behavior and responds to them in the case of young children ages one to five. As we know, children’s minds/brains are just as clean as a crystal, and throughout time, in their surroundings, families, and education center, they grow to develop and have different kinds of behavior towards the world and the society they live in. Hence, this work aims to identify how young children respond to various personality behavior and observes their reactions towards them from a system dynamics perspective. We will be exploring the Big Five personality traits in young children. A causal model is developed in support of the system dynamics approach. These models graphically present the factors and factor relationships that contribute to the big five personality traits and provide a better understanding of the entire behavior model. A simulator will be developed that includes a set of causal model factors and factor relationships. The simulator models the behavior of different factors related to personality traits and their impacts and can help make more informed decisions in a risk-free environment.

Keywords: personality traits, systems engineering, system dynamics, causal model, behavior model

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Authors: Sarojini Imran, Riza Firmansyah, Aula Ramadhan, Chudamul Furqon, Achfriyatama Oktariflandi

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This article delves into the participatory approach in formulating a master plan for the development of pioneer village tourism in Cibubuan, Sumedang. We explore the process of participatory mapping that involves the active participation of the local community in planning and envisioning the future of village tourism. This research considers the positive impact that arises when the community takes an active role in designing a master plan that benefits the local economy while preserving culture and the environment. The results of this research reveal that the participatory approach can create a more accurate and community-responsive mapping that aligns with the aspirations of the people in Cibubuan Village. It also provides a deep insight into how community-developed mapping can guide the development of sustainable tourism. By offering a deeper understanding of the participatory role in village tourism development planning, this article provides essential insights for stakeholders and researchers in this field. We hope this article will inspire more communities to adopt a participatory approach in planning the future of their village tourism.

Keywords: participatory masterplan, pioneer village tourism, sustainable tourism, community engagement, Cibubuan Village

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Hassan Almoslim

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Background: The machine resistance training is an exercise that uses the equipment as loads to strengthen and condition the musculoskeletal system and improving muscle tone. The machine resistance training is easy to use, allow the individual to train with heavier weights without assistance, useful for beginners and elderly populations and specific muscle groups. Purpose: The purpose of this study was to examine the impact of nine weeks of machine resistance training on maximum strength among lean and normal weight male college students. Method: Thirty-six male college students aged between 19 and 21 years from King Fahd University of petroleum & minerals participated in the study. The subjects were divided into two an equal groups called Lean Group (LG, n = 18) and Normal Weight Group (NWG, n = 18). The subjects whose body mass index (BMI) is less than 18.5 kg / m2 is considered lean and who is between 18.5 to 24.9 kg / m2 is normal weight. Both groups performed machine resistance training nine weeks, twice per week for 40 min per training session. The strength measurements, chest press, leg press and abdomen exercises were performed before and after the training period. 1RM test was used to determine the maximum strength of all subjects. The training program consisted of several resistance machines such as leg press, abdomen, chest press, pulldown, seated row, calf raises, leg extension, leg curls and back extension. The data were analyzed using independent t-test (to compare mean differences) and paired t-test. The level of significance was set at 0.05. Results: No change was (P ˃ 0.05) observed in all body composition variables between groups after training. In chest press, the NWG recorded a significantly greater mean different value than the LG (19.33 ± 7.78 vs. 13.88 ± 5.77 kg, respectively, P ˂ 0.023). In leg press and abdomen exercises, both groups revealed similar mean different values (P ˃ 0.05). When the post-test was compared with the pre-test, the NWG showed significant increases in the chest press by 47% (from 41.16 ± 12.41 to 60.49 ± 11.58 kg, P ˂ 001), abdomen by 34% (from 45.46 ± 6.97 to 61.06 ± 6.45 kg, P ˂ 0.001) and leg press by 23.6% (from 85.27 ± 15.94 to 105.48 ± 21.59 kg, P ˂ 0.001). The LG also illustrated significant increases by 42.6% in the chest press (from 32.58 ± 7.36 to 46.47 ± 8.93 kg, P ˂ 0.001), the abdomen by 28.5% (from 38.50 ± 7.84 to 49.50 ± 7.88 kg, P ˂ 0.001) and the leg press by 30.8% (from 70.2 ± 20.57 to 92.01 ± 22.83 kg, P ˂ 0.001). Conclusion: It was concluded that the lean and the normal weight male college students can benefit from the machine resistance-training program remarkably.

Keywords: body composition, lean, machine resistance training, normal weight

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Ashwani Kumar, Jitender Kumar

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In this paper, an optimal power flow based approach has been applied for multi-transactions deregulated environment for ATC determination with SVC and STATCOM. The main contribution of the paper is (i) OPF based approach for evaluation of ATC with multi-transactions, (ii) ATC enhancement with FACTS devices viz. SVC and STATCOM for intact and line contingency cases, (iii) impact of ZIP load on ATC determination and comparison of ATC obtained with SVC and STATCOM. The results have been determined for intact and line contingency cases taking simultaneous as well as single transaction cases for IEEE 24 bus RTS.

Keywords: available transfer capability, FACTS devices, line contingency, multi-transactions, ZIP load model

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Authors: Michael Heuer, Ayoub Al-Hamadi, Alexander Rain, Marc-Michael Meinecke

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Vulnerable road users, e.g. pedestrians, have a high impact on fatal accident numbers. To reduce these statistics, car manufactures are intensively developing suitable safety systems. Hereby, fast and reliable environment recognition is a major challenge. In this paper we describe a tracking approach that is only based on a 24 GHz radar sensor. While common radar signal processing loses much information, we make use of a track-before-detect filter to incorporate raw measurements. It is explained how the Range-Doppler spectrum can help to indicated pedestrians and stabilize tracking even in occultation scenarios compared to sensors in series.

Keywords: radar, pedestrian detection, active safety, sensor

Procedia PDF Downloads 530