Search results for: finite state method
Commenced in January 2007
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Edition: International
Paper Count: 25287

Search results for: finite state method

14457 Markov Random Field-Based Segmentation Algorithm for Detection of Land Cover Changes Using Uninhabited Aerial Vehicle Synthetic Aperture Radar Polarimetric Images

Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

Abstract:

The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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14456 Effect of Compaction Energy on the Compaction of Soils with Low Water Content in the Semi-arid Region of Chlef

Authors: Obeida Aiche, Mohamed Khiatine, Medjnoun Amal, Ramdane Bahar

Abstract:

Soil compaction is one of the most challenging tasks in the construction of road embankments, railway platforms, and earth dams. Stability and durability are mainly related to the nature of the materials used and the type of soil in place. However, nature does not always offer the engineer materials with the right water content, especially in arid and semi-arid regions where obtaining the optimum Proctor water content requires the addition of considerable quantities of water. The current environmental context does not allow for the rational use of water, especially in arid and semi-arid regions, where it is preferable to preserve water resources for the benefit of the local population. Low water compaction can be an interesting approach as it promotes the reuse of earthworks materials in their dry or very dry state. Thanks to techniques in the field of soil compaction, such as vibratory compactors, which have made it possible to increase the compaction energy considerably, it is possible for some materials to obtain a satisfactory quality by compacting at low water contents or at least lower than the optimum determined by the Proctor test. This communication deals with the low water content compaction of soils in the semi-arid zone of the Chlef region in Algeria by increasing the compaction energy.

Keywords: compaction, soil, low water content, compaction energy

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14455 Multi-Model Super Ensemble Based Advanced Approaches for Monsoon Rainfall Prediction

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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14454 Providing a Proposed Framework for the Copyright of Library Resources in Iran: A Comparative Study of the Copyright Laws of Iran, Australia and U.S.

Authors: Zeinab Papi

Abstract:

This study was aimed at analyzing the copyright laws of Iran, Australia, the U.S., and library portals, thereby providing a proposed framework for the copyright of library resources for the NLAI and other Iranian libraries while considering the current situation and the internal Iranian laws. This is an applied study falling in the category of qualitative approach research. Documentary analysis method and comparative method were used to resolve the problem and answer the questions of the research. The two National Library of Australia (NLA) and Library of Congress (LC), together with the NLAI formed the research community. In addition, the Iranian Law for the Protection of Authors, Composers and Artists Rights (1970); the Australian Copyright Act (1968), and the U.S. Copyright Law (1976) were purposefully selected as three main resources among other documents and resources. Findings revealed that the dimensions of fair and non-profit use, duration of copyright, license, and agreement, copyright policy, moral rights, economic rights, and infringement of copyright were the main dimensions that, along with 49 main components, formed the proposed framework for the copyright of information resources for the NLAI and other Iranian libraries. It should be acknowledged that there are some differences in different copyright fields between countries' laws, and each country takes into account its internal conditions to compile and revise the laws. By following the laws of other countries, it is possible to effectively improve and develop copyright laws. The researcher hopes that this research can have its effects in creating awareness and ability among librarians, formulating a copyright policy in Iranian libraries, and helping legislators in revising copyright laws regarding library exceptions and exemptions.

Keywords: copyright, library resources, National Library and Archives of the I.R. of Iran, National Library of Australia, Library of Congress, copyright law

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14453 Impact of Infrastructural Development on Socio-Economic Growth: An Empirical Investigation in India

Authors: Jonardan Koner

Abstract:

The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

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14452 Subjective Well-Being through Coaching Process

Authors: Pendar Fazel

Abstract:

Well-being is a good or satisfactory condition of existence; a state characterized by health, happiness, and prosperity. Well-being of people is correlated with, the cognitive, social, emotional, and physical aspect of their personality. Subjective well-being, people’s emotional and cognitive evaluations of their lives, includes what lay people call happiness, peace, fulfillment, and life satisfaction. Unfortunately in this period of time people are under the pressure of financial, social problems, and other stress factors which made them vulnerable, and their well-being is threatened. Personal Coaching as a holistic orientation and novel approach is ideal for the present century which help people, to find balance, enjoyment and meaning in their lives as well as improving performance, skills and effectiveness. The aim of the present article besides introducing the personal coaching is determining how personal coaching can positively effects on subjective well-being, under this aim we tend to describe how coaching impact on the cognitive and emotional reconstruction. Present qualitative research is descriptive analytic study, which data gathered by manual library research and search within authentic article through internet; analyzed personal coaching which integrated different views into an operational one helps people promote self-awareness as well as evaluate, emotional and cognitive aspect of their personality and provide appropriate subjective well-being.

Keywords: subjective well-being, coaching, well-being, positive psychology, personal growth

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14451 Contact Toxicity Effects of Different Formulations of Artemisia Absinthium Extracts on Rose Aphid

Authors: Maryam Atapour

Abstract:

Chemical pesticides, which are widely used in agriculture, cause problems such as soil and water pollution, reducing biodiversity and creating pest resistance. These problems have led to increased attention to alternative and more sustainable methods such as natural-based pesticides. Herbal pesticides have been developed based on essential oils or extracts from different parts of plants, such as leaves, roots, and flowers. Herbal pesticides are compatible with the environment and can be used in integrated pest management programs. Despite the many benefits, herbal pesticides, especially essential oil-based compounds, have low durability in the environment, and their production costs are high, so the use of herbal extracts with appropriate formulations is more justified in all aspects. In the current study and based on the results of previous studies, aqueous and 70% ethanolic extract of Artemisia absinthium L. was prepared by the percolation method and formulated as an emulsion and water-soluble powder. To produce powder formulation, 20% maltodextrin was used with the spray-dryer method. Different concentrations of these compounds were sprayed on bushes infected with rose aphid Macrosiphum rosae (L.). Sampling was done randomly and the percentage of aphids’ mortality was checked. The results showed that the use of different concentrations of ethanolic extracts created a significant difference in the mortality rate of aphids, while water-soluble powder formulation caused less mortality. The current results showed that the extract of this plant has practical usability to control aphids, and with the appropriate formulation, it can be used as a good alternative to chemical pesticides.

Keywords: contact toxicity, formulation, extract, aphid, Artemisia absinthium.

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14450 Selecting the Best Sub-Region Indexing the Images in the Case of Weak Segmentation Based on Local Color Histograms

Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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14449 Labor Legislation and Female Economic Empowerment: Evidence from Night Work, Regulatory and Seating Laws

Authors: Lamis Kattan, Joanne Haddad

Abstract:

This paper examines the impact of gender focused labor legislation on women's labor force participation and economic empowerment. We rely on historical legislative acts passed by state legislatures and exploit whether or not states passed regulatory laws regulating overall and industry specific employment and work conditions for women, night work laws and labor laws requiring provision of seats for working women. We exploit the fact that not all states enacted these laws as well as the variation in the timing of enactment of such laws. Our results show that women in comparison to men in treated states are more likely to be in the labor force post introduction of night work laws in comparison to control states. We also document the effect of industry-specific labor policies on women's likelihood to be employed in the affected industry and in higher-wage occupations within the industry of interest. Policy implications of our findings endorse the adoption of labor laws in favor of women to advocate their empowerment through a higher involvement in the labor market and financial independence.

Keywords: female employment, labor laws, marriage, fertility

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14448 Development of a Direct Immunoassay for Human Ferritin Using Diffraction-Based Sensing Method

Authors: Joel Ballesteros, Harriet Jane Caleja, Florian Del Mundo, Cherrie Pascual

Abstract:

Diffraction-based sensing was utilized in the quantification of human ferritin in blood serum to provide an alternative to label-based immunoassays currently used in clinical diagnostics and researches. The diffraction intensity was measured by the diffractive optics technology or dotLab™ system. Two methods were evaluated in this study: direct immunoassay and direct sandwich immunoassay. In the direct immunoassay, human ferritin was captured by human ferritin antibodies immobilized on an avidin-coated sensor while the direct sandwich immunoassay had an additional step for the binding of a detector human ferritin antibody on the analyte complex. Both methods were repeatable with coefficient of variation values below 15%. The direct sandwich immunoassay had a linear response from 10 to 500 ng/mL which is wider than the 100-500 ng/mL of the direct immunoassay. The direct sandwich immunoassay also has a higher calibration sensitivity with value 0.002 Diffractive Intensity (ng mL-1)-1) compared to the 0.004 Diffractive Intensity (ng mL-1)-1 of the direct immunoassay. The limit of detection and limit of quantification values of the direct immunoassay were found to be 29 ng/mL and 98 ng/mL, respectively, while the direct sandwich immunoassay has a limit of detection (LOD) of 2.5 ng/mL and a limit of quantification (LOQ) of 8.2 ng/mL. In terms of accuracy, the direct immunoassay had a percent recovery of 88.8-93.0% in PBS while the direct sandwich immunoassay had 94.1 to 97.2%. Based on the results, the direct sandwich immunoassay is a better diffraction-based immunoassay in terms of accuracy, LOD, LOQ, linear range, and sensitivity. The direct sandwich immunoassay was utilized in the determination of human ferritin in blood serum and the results are validated by Chemiluminescent Magnetic Immunoassay (CMIA). The calculated Pearson correlation coefficient was 0.995 and the p-values of the paired-sample t-test were less than 0.5 which show that the results of the direct sandwich immunoassay was comparable to that of CMIA and could be utilized as an alternative analytical method.

Keywords: biosensor, diffraction, ferritin, immunoassay

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14447 Comparative Analysis of Effect of Capital Structure to Profitability in Manufacturing Sector in Indonesia and Malaysia in 2009 - 2014

Authors: Hatane Semuel, Hartmann H. Ngono, Sautma R. Basana

Abstract:

The effect of capital structure on profitability is often debated by many financial investigators. The application of the trade-off theory and pecking order theory to analyze this relationship may generate different views. Each company has its own strategies to achieve its objectives and the external environment, such as state policy has a broad impact on the relationship with the capital structure of the company's profitability. Malaysia is the country closest to Indonesia that had a similar growth rate of GDP and industrial production with Indonesia, but Malaysia has lower inflation rate than Indonesia. This study was conducted to compare the performance of manufacturing sector between two countries when entering the era of the ASEAN Economic Community (AEC). The samples for this study were 69 companies in Indonesia and 242 companies in Malaysia that engaged in manufacturing sector. The study uses panel data analysis. The study found that the capital structure have positive effect on profitability of manufacturing company in Indonesia, and it turns to negative effect on manufacturing companies in Malaysia. The results also showed that there are significant differences in short-term debt towards profitability of manufacturing companies in the two countries Indonesia and Malaysia.

Keywords: capital structure, Indonesia, Malaysia, manufacturing, profitability

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14446 An Optimized Approach to Generate the Possible States of Football Tournaments Final Table

Authors: Mouslem Damkhi

Abstract:

This paper focuses on possible states of a football tournament final table according to the number of participating teams. Each team holds a position in the table with which it is possible to determine the highest and lowest points for that team. This paper proposes an optimized search space based on the minimum and maximum number of points which can be gained by each team to produce and enumerate the possible states for a football tournament final table. The proposed search space minimizes producing the invalid states which cannot occur during a football tournament. The generated states are filtered by a validity checking algorithm which seeks to reach a tournament graph based on a generated state. Thus, the algorithm provides a way to determine which team’s wins, draws and loses values guarantee a particular table position. The paper also presents and discusses the experimental results of the approach on the tournaments with up to eight teams. Comparing with a blind search algorithm, our proposed approach reduces generating the invalid states up to 99.99%, which results in a considerable optimization in term of the execution time.

Keywords: combinatorics, enumeration, graph, tournament

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14445 Numerical Simulation of Phase Transfer during Cryosurgery for an Irregular Tumor Using Hybrid Approach

Authors: Rama Bhargava, Surabhi Nishad

Abstract:

The infusion of nanofluids has dramatically enhanced the heat-carrying capacity of the fluids, applicable to many engineering and medical process where the temperature below freezing is required. Cryosurgery is an efficient therapy for the treatment of cancer, but sometimes the excessive cooling may harm the nearby healthy cells. Efforts are therefore done to develop a model which can cause to generate the low temperature as required. In the present study, a mathematical model is developed based on the bioheat transfer equation to simulate the heat transfer from the probe on a tumor (with irregular domain) using the hybrid technique consisting of element free Galerkin method with αα-family of approximation. The probe is loaded will nano-particles. The effects of different nanoparticles, namely Al₂O₃, Fe₃O₄, Au on the heat-producing rate, is obtained. It is observed that the temperature can be brought to (60°C)-(-30°C) at a faster freezing rate on the infusion of different nanoparticles. Besides increasing the freezing rate, the volume of the nanoparticle can also control the size and growth of ice crystals formed during the freezing process. The study is also made to find the time required to achieve the desired temperature. The problem is further extended for multi tumors of different shapes and sizes. The irregular shape of the frozen domain and the direction of ice growth are very sensitive issues, posing a challenge for simulation. The Meshfree method has been one of the accurate methods in such problems as a domain is naturally irregular. The discretization is done using the nodes only. MLS approximation is taken in order to generate the shape functions. Sufficiently accurate results are obtained.

Keywords: cryosurgery, EFGM, hybrid, nanoparticles

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14444 Incidence of Anaemia in Female Breast Cancer Patients

Authors: Fatima Abu Baker Hamad

Abstract:

Anaemia is a public health problem that affects population in both rich and poor countries. Although the primary cause is iron deficiency, it is seldom present in isolation. More frequently it coexists with a number of other causes, such as malaria, parasitic infection, nutritional deficiencies and hemoglobin apathies. That was the people in Sudan suffered from it .Anaemia has a high prevalence in patients with cancer. The aim of this study was to find the incidence of anaemia in new cases of Sudanese female breast patients attending the National Cancer Institute (NCI), Gezira University, Sudan. The study was performed on 250 female breast cancer patients, the age range was (20-70) years and the mean age was 45.99±0.82. The hemoglobin level was measured by SYSMEX-KX2lM.As result 144(58.8) of patients presented with anaemia, between moderate to severe. Forty four (17.6%) of the patients were found to be under weight, 31 of them were anaemic. While 105(42%) of the patients were overweight and obese, 52 of them were anaemic. The incidence of anaemia in newly diagnosed Sudanese female breast cancer patients presented at NCI is association presentation with advance disease stage. Also it is related to age, state of nutrition and social economic factors. Early cancer detection which leads to effective treatment and reduced complication of diseases included anaemia is recommended.

Keywords: anaemia, breast cancer, stages of disease, malaria

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14443 Differential Terrain: A Spectrum in Capitalism Transformation

Authors: Sibo Lu, Zhongkai Qian

Abstract:

This study endeavors to articulate a spectrum of capitalist transformation from a politico-economic perspective, categorizing the development of capitalism into pre-modern, modern, and post-modern stages while examining the transitions between these states. It critically engages with the concepts of pre-modernity, modernity, and post-modernity, typically aligned with cultural studies, to shed light on their objective changes in the politico-economic realm. Post-modernity, in this context, is associated with the transition to high-value-added services and economic growth in ‘developed’ countries amidst globalization, framing a ‘neoliberal’ economic transformation. The paper scrutinizes the neoliberal economic shifts in the latter half of the 20th century as part of the post-modern state, arguing against viewing post-modernity merely as a cultural or subjective interpretative stance. Instead, it is posited as a concrete politico-economic phase marked by the dominance of post-Fordist systems. Through integrating insights from the political economy with continental philosophy, this research provides a nuanced analysis of capitalism's evolution, challenging conventional class analyses under the capitalist system and fostering a broader understanding of socio-economic paradigms.

Keywords: post marxism, critical theory, political economy, capitalism transformation

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14442 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation

Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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14441 Automated End of Sprint Detection for Force-Velocity-Power Analysis with GPS/GNSS Systems

Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

Abstract:

Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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14440 Application of Bayesian Model Averaging and Geostatistical Output Perturbation to Generate Calibrated Ensemble Weather Forecast

Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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14439 An Approach to Correlate the Statistical-Based Lorenz Method, as a Way of Measuring Heterogeneity, with Kozeny-Carman Equation

Authors: H. Khanfari, M. Johari Fard

Abstract:

Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

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14438 Homogenization of a Non-Linear Problem with a Thermal Barrier

Authors: Hassan Samadi, Mustapha El Jarroudi

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In this work, we consider the homogenization of a non-linear problem in periodic medium with two periodic connected media exchanging a heat flux throughout their common interface. The interfacial exchange coefficient λ is assumed to tend to zero or to infinity following a rate λ=λ(ε) when the size ε of the basic cell tends to zero. Three homogenized problems are determined according to some critical value depending of λ and ε. Our method is based on Γ-Convergence techniques.

Keywords: variational methods, epiconvergence, homogenization, convergence technique

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14437 State of Play for the World’s Largest Greenhouse Gas Emitters

Authors: Olivia Meeschaert

Abstract:

The Conference of the Parties (COP) refers to the countries that signed on to the United Nations Framework Convention on Climate Change. This annual conference provides a platform for countries to voice their major climate concerns, negotiate on a number of global issues, and come to agreements with the world’s largest emitters on how to make incremental changes that will achieve global climate goals. Historically, the outcome of COP includes major climate pledges and international agreements. COP27 will take place in Egypt at the beginning of November 2022. The 197 parties will come together to develop solutions to the dire consequences of climate change that many people around the world are already experiencing. The war in Ukraine will require a different tone from last year’s COP, particularly given that major impacts of the war are being felt throughout Europe and have had a detrimental effect on the region’s progress in achieving the benchmarks set in their climate pledges. Last year’s COP opened with many climate advocates feeling optimistic but the commitments made in Glasgow have so far remained empty promises, and the main contributors to climate change – China, the European Union, and the United States of America – have not moved fast enough.

Keywords: environment, law and policy, climate change, greenhouse gas, conference of the parties, China, United States, European Union

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14436 Corporate Female Entrepreneurship, Moving Boundaries

Authors: Morena Paulisic, Marli Gonan Bozac

Abstract:

Business organization and management in theory are typically presented as gender- neutral. Although in practice female contribution to corporation is not questionable, gender diversity in top management of corporation is and that especially in emerging countries like Croatia. This paper brings insights into obstacles and problems which should be overcome. Furthermore, gives an introspective view on the most important promotion and motivation factors of powerful female CEOs in Croatia. The goal was to clarify perception and performance of female CEOs that contributed to their success and to determine mutual characteristics of women in corporate entrepreneurship regarding the motivation. For our study we used survey instrument that was developed for this research. The research methods used were: table research, field research, generalization method, comparative method, and statistical method (descriptive statistics and Pearson’s Chi-square test). Some result showed us that today even more women in corporations are not likely to accept more engagement at work if it harms their families (2003 – 31.9% in 2013 – 33.8%) although their main motivating factor is still interested job (2003 – 95.8%; in 2013-100%). It is also significant that 78.8 % of Croatian top managers (2013) think that women managers in Croatia are insufficiently spoken and written about, and that the reasons for this are that: (1) the society underestimates their ability (37.9%); (2) women underestimate themselves (22.4%); (3) the society still mainly focuses on male managers (20.7%) and (4) women managers avoid interviews and appearing on front pages (19%). The environment still “blocks” the natural course of advancement of women managers in organisations (entrepreneurship in general) and the main obstacle is that women must always or almost always be more capable than men in order to succeed (96.6%). Based on survey results on longitudinal research conducted in 2003 (return rate 30,8%) and 2013 (return rate 29,2%) in Croatia we expand understanding of determination indicators of corporate female entrepreneurship. Theoretically in practice gender structure at the management level (executive management, management board and supervisory board) throw years (2011- 2014) have positive score but still women remain significantly underrepresented at those positions. Findings from different sources have shown that diversity at the top of corporations’ correlates with better performance. In this paper, we have contributed to research on gender in corporate entrepreneurship by offering experiences from successful female CEOs and explanation why in social responsible society women with their characteristics can support needed changes and construct different way forward for corporations. Based on research result we can conclude that in future underrepresentation of female in corporate entrepreneurship should be overcome.

Keywords: Croatia, female entrepreneurship, glass ceiling, motivation

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14435 Ultrasound-Assisted Extraction of Carotenoids from Tangerine Peel Using Ostrich Oil as a Green Solvent and Optimization of the Process by Response Surface Methodology

Authors: Fariba Tadayon, Nika Gharahgolooyan, Ateke Tadayon, Mostafa Jafarian

Abstract:

Carotenoid pigments are a various group of lipophilic compounds that generate the yellow to red colors of many plants, foods and flowers. A well-known type of carotenoids which is pro-vitamin A is β-carotene. Due to the color of citrus fruit’s peel, the peel can be a good source of different carotenoids. Ostrich oil is one of the most valuable foundations in many branches of industry, medicine, cosmetics and nutrition. The animal-based ostrich oil could be considered as an alternative and green solvent. Following this study, wastes of citrus peel will recycle by a simple method and extracted carotenoids can increase properties of ostrich oil. In this work, a simple and efficient method for extraction of carotenoids from tangerine peel was designed. Ultrasound-assisted extraction (UAE) showed significant effect on the extraction rate by increasing the mass transfer rate. Ostrich oil can be used as a green solvent in many studies to eliminate petroleum-based solvents. Since tangerine peel is a complex source of different carotenoids separation and determination was performed by high-performance liquid chromatography (HPLC). In addition, the ability of ostrich oil and sunflower oil in carotenoid extraction from tangerine peel and carrot was compared. The highest yield of β-carotene extracted from tangerine peel using sunflower oil and ostrich oil were 75.741 and 88.110 (mg/L), respectively. Optimization of the process was achieved by response surface methodology (RSM) and the optimal extraction conditions were tangerine peel powder particle size of 0.180 mm, ultrasonic intensity of 19 W/cm2 and sonication time of 30 minutes.

Keywords: β-carotene, carotenoids, citrus peel, ostrich oil, response surface methodology, ultrasound-assisted extraction

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14434 Rain Gauges Network Optimization in Southern Peninsular Malaysia

Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

Abstract:

Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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14433 Describing Cognitive Decline in Alzheimer's Disease via a Picture Description Writing Task

Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

Abstract:

For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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14432 Characterization of Calcined Clay Blended Self Compacting Concrete-Correlation between Super-Plasticizer Dosage and Self Compacting Concrete Properties

Authors: Kumator Josiphiah Taku

Abstract:

Sustainability in construction is essential to the economic construction and can be achieved by the use of locally available construction materials. This research work, thus, uses locally available materials –calcined clay and Sandcrete SPR-300 superplasticizer in the production of Self Compacting Concrete (SCC) by investigating the correlation between the superplasticizer dosage and the fresh and hardened states properties of a grade 50 SCC made by incorporating a Calcined Clay (CC) – Portland Limestone Cement (PLC) blend as the cementitious matter at 20% replacement of PLC with CC and using CC as filler. The superplasticizer dosage was varied from 0.4 to 3.0% by weight of cementitious material and the slump, v-funnel, L-box and strength parameters investigated. The result shows a positive correlation between the increased dosage of the superplasticizer and the fresh and hardened states properties of the SCC up to 2% dosage. The J¬Spread¬, t¬500J¬, Slump flow, L-box H¬2¬/H¬1 ¬ratio and strength, all increases with SP dosage while the V-funnel flow decreased with SP dosage. Overall, SP ratio of 0.5 to 2.0 can be used in improving the properties of SCC produced using calcined clay both as filler and cementitious material.

Keywords: calcined clay, compressive strength, fresh-state properties of SCC, self compacting concrete, superplasticizer dosage

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14431 Evaluating the Potential of Microwave Treatment as a Rock Pre-Conditioning Method in Achieving a More Sustainable Mining

Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

Abstract:

Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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14430 Dynamic Effects of Charitable Giving in a Ramsey Model

Authors: Riham Barbar

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This paper studies the dynamic effects of charitable giving in a Ramsey model à la Becker and Foias (1994), such that heterogeneity is reduced to two types of agents: rich and poor. It is assumed that rich show a great concern for poor and enjoy giving. The introduction of charitable giving in this paper is inspired from the notion of Zakat (borrowed from the Islamic Economics) and is defined according to the warm-glow of Andreoni (1990). In this framework, we prove the existence of a steady state where only the patient agent holds capital. Furthermore, we show that local indetermincay appears. While moderate values of charitable-giving elasticity makes the appearance of endogenous fluctuations due to self-fulfilling expectations more likely, high values of this elasticity stabilizes endogenous fluctuations, by narrowing down the range of parameter values compatible with local indeterminacy and may rule out expectations-driven fluctuations if it exceeds certain threshold. Finally, cycles of period two emerge. However, charitable-giving makes it less likely for these cycles to emerge.

Keywords: charitable giving, warm-glow, bifurcations, heterogeneous agents, indeterminacy, self-fulfilling expectations, endogenous fluctuations

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14429 A Deep Learning Approach to Detect Complete Safety Equipment for Construction Workers Based on YOLOv7

Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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14428 Development of Method for Recovery of Nickel from Aqueous Solution Using 2-Hydroxy-5-Nonyl- Acetophenone Oxime Impregnated on Activated Charcoal

Authors: A. O. Adebayo, G. A. Idowu, F. Odegbemi

Abstract:

Investigations on the recovery of nickel from aqueous solution using 2-hydroxy-5-nonyl- acetophenone oxime (LIX-84I) impregnated on activated charcoal was carried out. The LIX-84I was impregnated onto the pores of dried activated charcoal by dry method and optimum conditions for different equilibrium parameters (pH, adsorbent dosage, extractant concentration, agitation time and temperature) were determined using a simulated solution of nickel. The kinetics and adsorption isotherm studies were also evaluated. It was observed that the efficiency of recovery with LIX-84I impregnated on charcoal was dependent on the pH of the aqueous solution as there was little or no recovery at pH below 4. However, as the pH was raised, percentage recovery increases and peaked at pH 5.0. The recovery was found to increase with temperature up to 60ºC. Also it was observed that nickel adsorbed onto the loaded charcoal best at a lower concentration (0.1M) of the extractant when compared with higher concentrations. Similarly, a moderately low dosage (1 g) of the adsorbent showed better recovery than larger dosages. These optimum conditions were used to recover nickel from the leachate of Ni-MH batteries dissolved with sulphuric acid, and a 99.6% recovery was attained. Adsorption isotherm studies showed that the equilibrium data fitted best to Temkin model, with a negative value of constant, b (-1.017 J/mol) and a high correlation coefficient, R² of 0.9913. Kinetic studies showed that the adsorption process followed a pseudo-second order model. Thermodynamic parameter values (∆G⁰, ∆H⁰, and ∆S⁰) showed that the adsorption was endothermic and spontaneous. The impregnated charcoal appreciably recovered nickel using a relatively smaller volume of extractant than what is required in solvent extraction. Desorption studies showed that the loaded charcoal is reusable for three times, and so might be economical for nickel recovery from waste battery.

Keywords: charcoal, impregnated, LIX-84I, nickel, recovery

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