Search results for: time-dependent linear potential

Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

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Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

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Authors: B. S Kaith, K. Sharma, V. Kumar, S. Kalia

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Superabsorbent are three-dimensional networks of linear or branched polymeric chains which can uptake large volume of biological fluids. The ability is due to the presence of functional groups like –NH2, -COOH and –OH. Such cross-linked products based on natural materials, such as cellulose, starch, dextran, gum and chitosan, because of their easy availability, low production cost, non-toxicity and biodegradability have attracted the attention of Scientists and Technologists all over the world. Since natural polymers have better biocompatibility and are non-toxic than most synthetic one, therefore, such materials can be applied in the preparation of controlled drug delivery devices, biosensors, tissue engineering, contact lenses, soil conditioning, removal of heavy metal ions and dyes. Gums are natural potential antioxidants and are used as food additives. They have excellent properties like high solubility, pH stability, non-toxicity and gelling characteristics. Till date lot of methods have been applied for the synthesis and modifications of cross-linked materials with improved properties suitable for different applications. It is well known that ion beam irradiation can play a crucial role to synthesize, modify, crosslink or degrade polymeric materials. High energetic heavy ions irradiation on polymer film induces significant changes like chain scission, cross-linking, structural changes, amorphization and degradation in bulk. Various researchers reported the effects of low and heavy ion irradiation on the properties of polymeric materials and observed significant improvement in optical, electrical, chemical, thermal and dielectric properties. Moreover, modifications induced in the materials mainly depend on the structure, the ion beam parameters like energy, linear energy transfer, fluence, mass, charge and the nature of the target material. Ion-beam irradiation is a useful technique for improving the surface properties of biodegradable polymers without missing the bulk properties. Therefore, a considerable interest has been grown to study the effects of SHIs irradiation on the properties of synthesized semi-IPNs and IPNs. The present work deals with the preparation of semi-IPNs and IPNs and impact of SHI like O7+ and Ni9+ irradiation on optical, chemical, structural, morphological and thermal properties along with impact on different applications. The results have been discussed on the basis of Linear Energy Transfer (LET) of the ions.

Keywords: adsorbent, gel, IPNs, semi-IPNs

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Authors: Deepak Singh

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AI technology is rapidly being integrated into the healthcare system, bringing many ethical and social implications. This literature review examines the various aspects of this phenomenon, focusing on the ethical considerations of using AI in healthcare, such as how it might affect patient autonomy, privacy, and doctor-patient relationships. Furthermore, the review considers the potential social implications of AI in Healthcare, such as the potential for automation to reduce the availability of healthcare jobs and the potential to widen existing health inequalities. The literature suggests potential benefits and drawbacks to using AI in healthcare, and it is essential to consider the ethical and social implications before implementation. It is concluded that more research is needed to understand the full implications of using AI in healthcare and that ethical regulations must be in place to ensure patient safety and the technology's responsible use.

Keywords: AI, healthcare, telemedicine, telehealth, ethics, security, privacy, patient, rights, safety

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

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Authors: Terry Lucas

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Calculations are performed to quantify the potential contribution of each greenhouse gas emission reduction strategy. This approach facilitates the visualisation of the relative benefits of each, and it provides a potential baseline for the development of a plan of action that is rooted in quantitative evaluation. Emissions reductions are converted to potential de-escalation of global average temperature. A comprehensive plan is then presented which shows the potential benefits all the way out to year 2100. A target temperature de-escalation of 2oC was selected, but the plan shows a benefit of only 1.225oC. This latter disappointing result is in spite of new and powerful technologies introduced into the equation. These include nuclear fusion and alternative nuclear fission processes. Current technologies such as wind, solar and electric vehicles show surprisingly small constributions to the whole.

Keywords: climate change, emissions, drawdown, energy

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Authors: Zipeng Zhang, Yat C. Wong, Arul Arulrajah

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Since automobiles became widely popular around the early 20th century, end-of-life tyres have been one of the major types of waste humans encounter. Every minute, there are considerable quantities of tyres being disposed of around the world. Most end-of-life tyres are simply landfilled or simply stockpiled, other than recycling. To address the potential issues caused by tyre waste, incorporating it into construction materials can be a possibility. This research investigated the viability of manufacturing bricks using mill waste and tyre crumb by alkali-activation at a relatively low temperature. The mill waste was extracted from a brick factory located in Melbourne, Australia, and the tyre crumbs were supplied by a local recycling company. As the main precursor, the mill waste was activated by the alkaline solution, which was comprised of sodium hydroxide (8m) and sodium silicate (liquid). The introduction ratio of alkaline solution (relative to the solid weight) and the weight ratio between sodium hydroxide and sodium silicate was fixed at 20 wt.% and 1:1, respectively. The tyre crumb was introduced to substitute part of the mill waste at four ratios by weight, namely 0, 5, 10 and 15%. The mixture of mill waste and tyre crumbs were firstly dry-mixed for 2 min to ensure the homogeneity, followed by a 2.5-min wet mixing after adding the solution. The ready mixture subsequently was press-moulded into blocks with the size of 109 mm in length, 112.5 mm in width and 76 mm in height. The blocks were cured at 50°C with 95% relative humidity for 2 days, followed by a 110°C oven-curing for 1 day. All the samples were then placed under the ambient environment until the age of 7 and 28 days for testing. A series of tests were conducted to evaluate the linear shrinkage, compressive strength and water absorption of the samples. In addition, the microstructure of the samples was examined via the scanning electron microscope (SEM) test. The results showed the highest compressive strength was 17.6 MPa, found in the 28-day-old group using 5 wt.% tyre crumbs. Such strength has been able to satisfy the requirement of ASTM C67. However, the increasing addition of tyre crumb weakened the compressive strength of samples. Apart from the strength, the linear shrinkage and water absorption of all the groups can meet the requirements of the standard. It is worth noting that the use of tyre crumbs tended to decrease the shrinkage and even caused expansion when the tyre content was over 15 wt.%. The research also found that there was a significant reduction in compressive strength for the samples after water absorption tests. In conclusion, the tyre crumbs have the potential to be used as a filler material in brick manufacturing, but more research needs to be done to tackle the durability problem in the future.

Keywords: bricks, mill waste, tyre crumbs, waste recycling

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Authors: M. Khouil, N. Saber, M. Mestari

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This study aimed to propose, a different architecture of a Path Planning using the NECMOP. where several nonlinear objective functions must be optimized in a conflicting situation. The ability to detect and avoid collision is very important for mobile intelligent machines. However, many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons linear and threshold logic, which simplified the actual implementation of all the networks proposed. This article represents a comprehensive algorithm that determine through the AMAXNET network a measure (a mini-maximum point) in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: path planning, collision detection, convex polyhedron, neural network

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Authors: Min Wei

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The traditional prediction methods of the forecast for tourism market are paid more attention to the accuracy of the forecasts, ignoring the results of the feasibility of forecasting and predicting operability, which had made it difficult to predict the results of scientific testing. With the application of Linear Regression Model, this paper attempts to construct a scientific evaluation system for predictive value, both to ensure the accuracy, stability of the predicted value, and to ensure the feasibility of forecasting and predicting the results of operation. The findings show is that a scientific evaluation system can implement the scientific concept of development, the harmonious development of man and nature co-ordinate.

Keywords: linear regression model, tourism market, forecast, tourism economics

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Othmane Boughazi, Abdelmadjid Boumedienne, Hachemi Glaoui

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This work treats the modeling and simulation of non-linear system behavior of an induction motor using backstepping sliding mode control. First, the direct field oriented control IM is derived. Then, a sliding for direct field oriented control is proposed to compensate the uncertainties, which occur in the control.Finally, the study of Backstepping sliding controls strategy of the induction motor drive. Our non linear system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.

Keywords: induction motor, proportional-integral, sliding mode control, backstepping sliding mode control

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

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Authors: Phan Thi Song Thuong

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This paper uses data from a survey on the green consumption behavior of Hanoi residents in October 2022. Data was gathered from a survey conducted in ten districts in the center of Hanoi, with 393 respondents. The hypothesis focuses on understanding the factors that may affect green consumption behavior, such as demographic characteristics, concerns about the environment and health, people living around, self-efficiency, and mass media. A number of methods, such as the T-test, exploratory factor analysis, and a linear regression model, are used to prove the hypotheses. Accordingly, the results show that gender, age, and education level have separate effects on the green consumption behavior of respondents.

Keywords: green consumption, urban residents, environment, sustainable, linear regression

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Authors: Brahim Fares Zaidi

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech based on the Hidden Models of Markov and the Hidden Markov Model Toolkit to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients and Perceptual Linear Prediction and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: ARSDS, HTK, HMM, MFCC, PLP

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Authors: Mohamad Saberi, Arash Sohrabi

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Tuned liquid damper is one the passive structural control ways which has been used since mid-1980 decade for seismic control in civil engineering. This system is made of one or many tanks filled with fluid, mostly water that installed on top of the high raised structure and used to prevent structure vibration. In this article we will show how to make seismic table contain TLD system and analysis the result of using this system in our structure. Results imply that when frequency ratio approaches 1 this system can perform its best in both dissipate energy and increasing structural damping. And also results of these serial experiments are proved compatible with Hunzer linear theory behaviour.

Keywords: TLD, seismic table, structural system, Hunzer linear behaviour

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Tahani Salman Alangari

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Student success can be impacted by internal factors such as their emotional well-being and external factors such as organizational support and instructional support in the classroom. This study is to identify at least one factor that forecasts student engagement. It is a cross-sectional, conducted on 6206 teachers and encompassed three years of data collection and observations of math instruction in approximately 50 schools and 300 classrooms. A multiple linear regression revealed that a model predicting student engagement from emotional support, classroom organization, and instructional support was significant. Four linear regression models were tested using hierarchical regression to examine the effects of independent variables: emotional support was the highest predictor of student engagement while instructional support was the lowest.

Keywords: student engagement, emotional support, organizational support, instructional support, well-being

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Authors: Sharib Ahmed, Mansoor Rafi, Kamran Ali Awan, Faraz Khaskhali, Amir Maqbool, Altaf Hashmi

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Medical linear accelerators (LINAC’s) used in radiotherapy treatments produce undesired neutrons when they are operated at energies above 8 MeV, both in electron and photon configuration. Neutrons are produced by high-energy photons and electrons through electronuclear (e, n) a photonuclear giant dipole resonance (GDR) reactions. These reactions occurs when incoming photon or electron incident through the various materials of target, flattening filter, collimators, and other shielding components in LINAC’s structure. These neutrons may reach directly to the patient, or they may interact with the surrounding materials until they become thermalized. A work has been set up to study the effect of different parameter on the production of neutron around the room by photonuclear reactions induced by photons above ~8 MeV. One of the commercial available neutron detector (Ludlum Model 42-31H Neutron Detector) is used for the detection of thermal and fast neutrons (0.025 eV to approximately 12 MeV) inside and outside of the treatment room. Measurements were performed for different field sizes at 100 cm source to surface distance (SSD) of detector, at different distances from the isocenter and at the place of primary and secondary walls. Other measurements were performed at door and treatment console for the potential radiation safety concerns of the therapists who must walk in and out of the room for the treatments. Exposures have taken place from Elekta Synergy® linear accelerators for two different energies (10 MV and 18 MV) for a given 200 MU’s and dose rate of 600 MU per minute. Results indicates that neutron doses at 100 cm SSD depend on accelerator characteristics means jaw settings as jaws are made of high atomic number material so provides significant interaction of photons to produce neutrons, while doses at the place of larger distance from isocenter are strongly influenced by the treatment room geometry and backscattering from the walls cause a greater doses as compare to dose at 100 cm distance from isocenter. In the treatment room the ambient dose equivalent due to photons produced during decay of activation nuclei varies from 4.22 mSv.h−1 to 13.2 mSv.h−1 (at isocenter),6.21 mSv.h−1 to 29.2 mSv.h−1 (primary wall) and 8.73 mSv.h−1 to 37.2 mSv.h−1 (secondary wall) for 10 and 18 MV respectively. The ambient dose equivalent for neutrons at door is 5 μSv.h−1 to 2 μSv.h−1 while at treatment console room it is 2 μSv.h−1 to 0 μSv.h−1 for 10 and 18 MV respectively which shows that a 2 m thick and 5m longer concrete maze provides sufficient shielding for neutron at door as well as at treatment console for 10 and 18 MV photons.

Keywords: equivalent doses, neutron contamination, neutron detector, photon energy

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Authors: Pravin Kumar, Rajendra K. Singh, Prabhakar Singh

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A widespread research work on Mo-based double perovskite systems has been reported as a potential application for electrode materials of solid oxide fuel cells. Mo-based double perovskites studied in form of B-site ordered double perovskite materials, with general formula A₂B′B″O₆ structured by alkaline earth element (A = Sr, Ca, Ba) and heterovalent transition metals (B′ = Fe, Co, Ni, Cr, etc. and B″ = Mo, W, etc.), are raising a significant interest as potential mixed ionic-electronic conductors in the temperature range of 500-800 °C. Such systems reveal higher electrical conductivity, particularly those assigned in form of Sr₂CoMoO₆₋δ (M = Mg, Mn, Fe, Co, Ni, Zn etc.) which were studied in different environments (air/H₂/H₂-Ar/CH₄) at an intermediate temperature. Among them, the Sr₂CoMoO₆₋δ system is a potential candidate as an anode material for solid oxide fuel cells (SOFCs) due to its better electrical conductivity. Therefore, Sr₂CoMoO₆₋δ (SCM) system with La-doped on Sr site has been studied to discover the structural and electrical properties. The double perovskite system Sr₂CoMoO₆₋δ (SCM) and doped system Sr₂-ₓLaₓCoMoO₆₋δ (SLCM, x=0.04) were synthesized by the citrate-nitrate combustion synthesis route. Thermal studies were carried out by thermo-gravimetric analysis. Phase justification was confirmed by powder X-ray diffraction (XRD) as a tetragonal structure with space group I4/m. A minor phase of SrMoO₄ (s.g. I41/a) was identified as a secondary phase using JCPDS card no. 85-0586. Micro-structural investigations revealed the formation of uniform grains. The average grain size of undoped (SCM) and doped (SLCM) compositions was calculated by a linear intercept method and found to be ⁓3.8 μm and 2.7 μm, respectively. The electrical conductivity of SLCM is found higher than SCM in the air within the temperature range of 200-600 °C. SLCM system was also measured in reducing atmosphere (pure H₂) in the temperature range 300-600 °C. SLCM has been showed the higher conductivity in the reducing atmosphere (H₂) than in air and therefore it could be a promising anode material for SOFCs.

Keywords: double perovskite, electrical conductivity, SEM, XRD

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Authors: M. Akhlaque Ahmed, Maliha Afshan

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Solar energy potential of Capital city Islamabad and five major cities Peshawar, Lahore, Multan, Quetta and Karachi have been analyzed by using sun shine hour data of the area. Global and diffused solar radiation on horizontal surfaces has been assessed to see the feasibility of solar energy utilization. The result obtained shows 70% direct and 30% diffuse solar radiation for five cities throughout the year except Karachi which shows large variation in direct and diffuse component of solar radiation 57% direct and 43% diffuse in the month of July and August. The cloudiness index were also calculated which lies between 60 to 70% for all the cities except for Karachi which shows 37% clear sky in monsoon month July and August. All the cities show high solar potential throughout the year except Karachi which shows low solar potential during July and August months.

Keywords: global and diffuse solar radiations, Pakistan, power generation, solar potential, sunshine hour

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Authors: Ibrahim Ali, Adamu Danlami Ahmed

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This study examines the impact of depreciation on taxable income and financial performance of consumer goods companies quoted on the Nigerian stock exchange. The study adopts ex-post factor research design. Data were collected using a secondary source. The findings of the study suggest that, method of depreciation adopted in any organization influence the taxable profit. Depreciation techniques can either be: depressive, accelerative and linear depreciation. It was also recommended that consumer goods should adjust their method of depreciation to make sure an appropriate method is adopted. This will go a long way to revitalize their taxable profit.

Keywords: accelerated, linear, depressive, depreciation

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Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

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This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges

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Authors: Prasannakumar Palaniappan, Dong Ho Shin, Chul Gyu Song

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The photoacoustic images are obtained from a custom developed linear array photoacoustic tomography system. The biological specimens are imitated by conducting phantom tests in order to retrieve a fully functional photoacoustic image. The acquired image undergoes the active region based contour filtering to remove the noise and accurately segment the object area for further processing. The universal back projection method is used as the image reconstruction algorithm. The active contour filtering is analyzed by evaluating the signal to noise ratio and comparing it with the other filtering methods.

Keywords: contour filtering, linear array, photoacoustic tomography, universal back projection

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Authors: Prachi Bhatt

Abstract:

Motivated workforce is an important asset of an organisation. Intrinsic motivation is one of the key aspects of people operations and performance. Researches have emphasized the significance of internal factors in individuals’ motivation. In the changing business scenario, it is a challenge for the organizations’ leaders to inspire and motivate their workforce. The present study deals with the intrinsic motivation potential of an individual which govern the innate capability of an individual driving him or her to behave or perform in the changing work environment, tasks, teams. Differences at individual level significantly influence differences in levels of motivation. In the above context, the present research attempts to explore behavioral trait dimensions which influence motivational potential of an individual. The present research emphasizes the significance of intrinsic motivational potential and the significance of exploring the differences in the intrinsic motivational potential levels of individuals at work places. Thus, this paper empirically tests the framework of behavioral traits which affects motivational potential of an individual. With the help of two studies i.e., Study 1 and Study 2, exploratory factor analysis and confirmatory factor analysis, respectively, indicated a reliable measure assessing intrinsic motivational potential of an individual. Given the variety of challenges of motivating contemporary workforce, and with increasing importance of intrinsic motivation, the paper discusses the relevance of the findings and of the measure assessing intrinsic motivational potential. Assessment of such behavioral traits would assist in the effective realization of intrinsic motivational potential of individuals. Additionally, the paper discusses the practical implications and furnishes scope for future research.

Keywords: behavioral traits, individual differences, intrinsic motivational potential, intrinsic motivation, motivation, workplace motivation

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Authors: Mehdi Ghatei, Masoomeh Lorestani

Abstract:

Upstream Tailings Storage Facilities (TSFs) may experience slope instabilities due to soil liquefaction, especially in regions known to be seismically active. In this study, liquefaction susceptibility of an upstream-raised TSF in Western Australia was assessed using two different approaches. The first approach assessed liquefaction susceptibility using Cone Penetration Tests with pore pressure measurement (CPTu) as described by the National Centre for Earthquake Engineering Research (NCEER). This assessment was based on the four CPTu tests that were conducted on the perimeter embankment of the TSF. The second approach used the Finite Element (FE) method with application of an equivalent linear model to predict the undrained cyclic behavior, the pore water pressure and the liquefaction of the materials. The tailings parameters were estimated from the CPTu profiles and from the laboratory tests. The cyclic parameters were estimated from the literature where test results of similar material were available. The results showed that there was a good agreement, in the liquefaction susceptibility of the tailings material, between the NCEER and FE methods with equivalent linear model.

Keywords: liquefaction , CPTU, NCEER, finite element method, equivalent linear model

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Authors: Kumar Shashvat, Amol P. Bhondekar

Abstract:

In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: Amiel Satvedi, Richard Pyne

Abstract:

Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

Procedia PDF Downloads 151

Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah

Abstract:

This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.

Keywords: damage mechanics, 3-D numerical analysis, RC, slab with opening

Procedia PDF Downloads 153