Search results for: probability of return

Authors: Andrii Natochii

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We are currently presenting the recent results from the CERN accelerator facilities obtained in the frame of the UA9 Collaboration. The UA9 experiment investigates how a tiny silicon bent crystal (few millimeters long) can be used for various high-energy physics applications. Due to the huge electrostatic field (tens of GV/cm) between crystalline planes, there is a probability for charged particles, impinging the crystal, to be trapped in the channeling regime. It gives a possibility to steer a high intensity and momentum beam by bending the crystal: channeled particles will follow the crystal curvature and deflect on the certain angle (from tens microradians for LHC to few milliradians for SPS energy ranges). The measurements at SPS, performed in 2017 and 2018, confirmed that the protons deflected by the first crystal, inserted in the primary beam halo, can be caught and channeled by the second crystal. In this configuration, we measure the single pass deflection efficiency of the second crystal and prove our opportunity to perform the fixed target experiment at SPS accelerator (LHC in the future).

Keywords: channeling, double-crystal setup, fixed target experiment, Timepix detector

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Authors: Ghorbanali Mohammadi

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Background: The objectives of this study were the association between physical and psychological risk factors for occupational lower back and neck pain among industrial workers. Methods: We conducted a cross-sectional study among 400 male workers of an industrial company over the previous 7days and 12 months. Data were collected using Nordic and third version of COPSOO questionnaires and QEC method for assessment of postures during the work. Results: The prevalence of LB and NP in the last 12 months is 58% and 52% respectively. The relationship between risk factors and low back/ neck pain in the last 12 months were cognitive demands (OR 995% CI 1.65) and (OR 995% CI 1.75); Influence at work (OR 995% CI 2.21) and (OR 995% CI 1.85); quality of leadership (OR 995% CI 2.42) and (OR 995% CI 2.09) was strongly correlated with complaints of low back and neck pains. Conclusion: Data of this study showed a higher prevalence of LBP and NP in the subjects. The results revealed that workers with work experience of more than 12 yrs. and who work more than 8 hrs. days with smoking habits had more probability to develop both LBP and NP.

Keywords: low back pain, neck pain, physical risk factors, psychological risk factors, QEC, COPSOQ III

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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Authors: Charles Amoatey

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The issue of risk in the mining industry is a global phenomenon and the Ghanaian mining industry is not exempted. The main purpose of this study is to identify the critical risk factors affecting the mining industry. The study takes an integrated view of the mining industry by examining the contribution of various risk factors to mining project failure in Ghana. A questionnaire survey was conducted to solicit the critical risk factors from key mining practitioners. About 80 respondents from 11 mining firms participated in the survey. The study identified 22 risk factors contributing to mining project failure in Ghana. The five most critical risk factors based on both probability of occurrence and impact were: (1) unstable commodity prices, (2) inflation/exchange rate, (3) land degradation, (4) high cost of living and (5) government bureaucracy for obtaining licenses. Furthermore, the study found that risk assessment in the mining sector has a direct link with mining project sustainability. Mitigation measures for addressing the identified risk factors were discussed. The key findings emphasize the need for a comprehensive risk management culture in the entire mining industry.

Keywords: risk, assessment, mining, Ghana

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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The performance of wireless communication systems is affected mainly by the environment of its associated channel, which is characterized by dynamic and unpredictable behavior. In this paper, different statistical earth-satellite channel models are studied with emphasize on two main models, first is the Rice-Log normal model, due to its representation for the environment including shadowing and multi-path components that affect the propagated signal along its path, and a three-state model that take into account different fading conditions (clear area, moderate shadow and heavy shadowing). The provided models are based on AWGN, Rician, Rayleigh, and log-normal distributions were their Probability Density Functions (PDFs) are presented. The transmission system Bit Error Rate (BER), Peak-Average-Power Ratio (PAPR), and the channel capacity vs. fading models are measured and analyzed. These simulations are implemented using MATLAB tool, and the results had shown the performance of transmission system over different channel models.

Keywords: fading channels, MIMO communication, RNS scheme, statistical modeling

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Authors: H. Hammoudi, S. Bendenia, I. Batonneau-Gener, J. Comparot, K. Marouf-Khelifa, A. Khelifa

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X zeolites were prepared by ion-exchange with Cu2+ and/or Zn2+ cations, at different concentrations of the exchange solution, and characterised by thermal analysis and nitrogen adsorption. The acidity of the samples was investigated by pyridine adsorption–desorption followed by in situ Fourier transform infrared (FTIR) spectroscopy. Desorption was carried out at 150, 250 and 350 °C. The objective is to estimate the nature and concentration of acid sites. A comparison between the binary (Cu(x)X, Zn(x)X) and ternary (CuZn(x)X) exchanges was also established (x = level of exchange) through the Cu(43)X, Zn(48)X and CuZn(50)X samples. Lewis acidity decreases overall with desorption temperature and the level of exchange. As the latter increases, there is a conversion of some Lewis sites into those of Brønsted during thermal treatment. In return, the concentration of Brønsted sites increases with the degree of exchange. The Brønsted acidity of CuZn(50)X at 350 °C is more important than the sum of those of Cu(43)X and Zn(48)X. The found values were 73, 32 and 15 μmol g-1, respectively. Besides, the concentration of Brønsted sites for CuZn(50)X increases with desorption temperature. These features indicate the presence of a synergistic effect amplifying the strength of these sites when Cu2+ and Zn2+ cations compete for the occupancy of sites distributed inside zeolitic cavities.

Keywords: acidity, adsorption, pyridine, zeolites

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Authors: Maharjan Shree Kumar

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Climate change impacts are observed in all livelihood sectors primarily in agriculture and forestry. Multiple factors have influenced the climate vulnerabilities and adaptations in agricultural at the household level. This study focused on the factors affecting adaptation in agriculture in Madi and Deukhuri valleys of Central and Western Nepal. The systematic random sampling technique was applied to select 154 households in Madi and 150 households in Deukhuri. The main purpose of the study was to analyze the socio-economic factors that either influence or restrain the farmers’ adaptation to climate change at the household level by applying the linear probability model. Based on the analysis, it is revealed that crop diversity, education, training and total land holding (acre) were positively significant for adaptation choices the study sites. Rest of the variables were not significant though indicated positive as expected except age, occupation, ethnicity, family size, and access to credit.

Keywords: adaptation, agriculture, climate, factors, Nepal

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Authors: Bibi Asma, Rokonozzaman Reza, Majharul Islam, Muhammad Foyez Ahmed, Mohammad Tayub

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Since the beginning of human civilization, natural dyes have been adored in textile coloration due to their non-hazardous nature compared to commercial dyes, recyclability, safety and a plethora of congenial attributes. Henna is an herb leaf that is used to color hands in Muslim fes-tivals, hence it is a part of tradition. In this study, Henna (Lawsoniainermis L.) has been used to dye nylon fabric with and without mordants. In the case of the mordanting process, metal chela-tion of Ferrous Sulphate (FeSO₄) and Copper Sulphate (CuSO₄) was used. The dyeing behavior of natural dye Henna with or without mordant was examined by analysis of colorimetric properties of color, depth of shade measurement and colorfastness properties of dyed fabric sample was also assessed as well. The study shows dye absorption of fiber has considerably increased by using mordants which in return exhibits a greater depth of shade, also the dyed samples demonstrated excellent fastness ratings in wash fastness, rubbing fastness, and Perspiration fastness with little to no change in color obtained.

Keywords: sustainable dyeing, henna, mordanting, metal chelation

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Chisom N. Nwaigwe, Blessing N. Egbulefu, Angela Uwakwem

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A study on Stress and its’ effect on the health of workers in Federal Medical Centres in Nigeria is presented. The aim is to evaluate how much stress related hazards health workers in our tertiary health institutions are exposed to and to create awareness and reduce the rate at which stress affect the health of the working population in Nigeria, using workers in Federal Medical Centre, Umuahia as a case study. The descriptive survey design was adopted with the aid of 100 questionnaires delivered to the respondents in order to obtain first-hand information. From the findings, the major causes of stress were identified as inadequate staffing, unresolved family problems and psychological/cultural factors like the return of a lactating mother to work after three months post-delivery. The effects of stress on the workers were identified as hypertension, poor job performances, depression, asthma, and peptic ulcers. The study recommended instituting counseling units for stress management, holding seminars on stress management and increasing the salary scale (remuneration) and proper roster planning as solutions to stress reduction in our hospitals. This study is important to management in planning staffing, roaster, and a rehabilitation programme for her staff.

Keywords: stress, causes, effects, workers

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Authors: Fu Jinyu, Lin Jinguan

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This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

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Authors: Y. Rae, A. Benaarbia, J. Hughes, Wei Sun

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This paper describes an elasto-visco-plastic computational modelling method which can be used to assess the cyclic plasticity responses of high temperature structures operating under thermo-mechanical loadings. The material constitutive equation used is an improved unified multi-axial Chaboche-Lemaitre model, which takes into account non-linear kinematic and isotropic hardening. The computational methodology is a three-dimensional framework following an implicit formulation and based on a radial return mapping algorithm. The associated user material (UMAT) code is developed and calibrated across isothermal hold-time low cycle fatigue tests for a typical turbine rotor steel for use in finite element (FE) implementation. The model is applied to a realistic industrial gas turbine rotor, where the study focuses its attention on the deformation heterogeneities and critical high stress areas within the rotor structure. The potential improvements of such FE visco-plastic approach are discussed. An integrated life assessment procedure based on R5 and visco-plasticity modelling, is also briefly addressed.

Keywords: unified visco-plasticity, thermo-mechanical, turbine rotor, finite element modelling

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Authors: Raed El-Khalil, Hussein Zeaiter

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Managing and improving efficiency in the current highly competitive global automotive industry demands that companies adopt leaner and more flexible systems. During the past 20 years the domestic automotive industry in North America has been focusing on establishing new management strategies in order to meet market demands. 98The lean management process also known as Toyota Manufacturing Process (TPS) or lean manufacturing encompasses tools and techniques that were established in order to provide the best quality product with the fastest lead time at the lowest cost. The following paper presents a study that focused on improving labor efficiency at one of the Big Three (Ford, GM, Chrysler LLC) domestic automotive facility in North America. The objective of the study was to utilize several lean management tools in order to optimize the efficiency and utilization levels at the “Pre-Marriage” chassis area in a truck manufacturing and assembly facility. Utilizing three different lean tools (i.e. Standardization of work, 7 Wastes, and 5S) this research was able to improve efficiency by 51%, utilization by 246%, and reduce operations by 14%. The return on investment calculated based on the improvements made was 284%.

Keywords: lean manufacturing, standardized work, operation efficiency, utilization

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Authors: G. Mattia, A. Di Leo, L. Principato

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The purchase impulsiveness is preceded by a lack of self-control: consequently, it is legitimate to believe that a consumer with a low level of self-control can result in a higher probability of cognitive dissonance. Moreover, the process of purchase is influenced by the pre-existing affective state in a considerable way. With reference to on-line purchases, digital behavior cannot be merely ascribed to the rational sphere, given the speed and ease of transactions and the hedonistic dimension of purchases. To our knowledge, this research is among the first cases of verification of the effect of moderation exerted by the positive affective state in the on-line impulse purchase of products with a high expressive value such as a smartphone on the occurrence of cognitive dissonance. To this aim, a moderation analysis was conducted on a sample of 212 impulsive millennials buyers. Three scales were adopted to measure the constructs of interest: IBTS for impulsivity, PANAS for the affective state, Sweeney for cognitive dissonance. The analysis revealed that positive affective state does not affect the onset of cognitive dissonance.

Keywords: cognitive dissonance, impulsive buying, online shopping, online consumer behavior

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Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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Authors: Robert Grzeszczak, Magdalena Gniadzik

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The article deals with one of the most significant issues concerning the functioning of the internal market of the European Union – the free movement of workers and free movement of persons. The purpose is to identify the political and legal effects of the “renationalisation process” on the EU and its Member States. The concept of renationalisation is expressed through Member States’ aim to verify the relationship with the EU. The tendency is more visible in the public opinion of several MS’s of the ‘EU core’ and may be confirmed by the changes applied by the regulatory body. The thesis for the article is the return of renationalisation tendencies in the area of the Single Market, which is supported by, among others, an open criticism of the foundations of EU integration or considerations on withdrawal from the EU by some MS. This analysis will focus primarily on the effects that renationalisation may have on the free movement of persons. The free movement of persons is one of the key issues for the development of the European integration. It is still subject to theoretical reflections, new doubts and practical issues. The latest developments in politics, law and jurisprudence demonstrate the need to reflect on the attempts to redefine certain principles regarding migrant EU workers and their protection against nationality-based discrimination.

Keywords: European Union, Singel Market, free movement of persons, posting of workers

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Naime Boudemagh, Zoheir Hammoudi

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The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.

Keywords: parameters estimation, method of moments, automatic censoring, K distribution

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Authors: Muhammad Haitham Albahnassi, Adnan Malki, Shokri Almekdad

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In this paper, a method for reconfiguring bandwidth in a circular dual-mode resonator is presented. The method concerns the optimized geometry of a structure that may be used to host the tuning elements, which are typically RF (Radio Frequency) switches. The tuning elements themselves, and their performance during tuning, are not the focus of this paper. The designed resonator is able to reconfigure its fractional bandwidth by adjusting the inter-coupling level between the degenerate modes, while at the same time improving its response by adjusting the external-coupling level and keeping the center frequency fixed. The inter-coupling level has been adjusted by changing the dimensions of the perturbation element, while the external-coupling level has been adjusted by changing one of the feeder dimensions. The design was arrived at via optimization. Agreeing simulation and measurement results of the designed and implemented filters showed good improvements in return loss values and the stability of the center frequency.

Keywords: dual-mode resonators, perturbation theory, reconfigurable filters, software defined radio, cognitine radio

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Authors: Chandranath Chatterjee, Amina Khatun, Bhabagrahi Sahoo

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With the changing climate, precipitation events are intensified in the tropical river basins. Since these river basins are significantly influenced by the monsoonal rainfall pattern, critical impacts are observed on the agricultural practices in the downstream river reaches. This study analyses the crop damage and associated flood risk in terms of net benefit in the paddy-dominated tropical Indian delta of the Mahanadi River. The Mahanadi River basin lies in eastern part of the Indian sub-continent and is greatly affected by the southwest monsoon rainfall extending from the month of June to September. This river delta is highly flood-prone and has suffered from recurring high floods, especially after the 2000s. In this study, the lumped conceptual model, Nedbør Afstrømnings Model (NAM) from the suite of MIKE models, is used for rainfall-runoff modeling. The NAM model is laterally integrated with the MIKE11-Hydrodynamic (HD) model to route the runoffs up to the head of the delta region. To obtain the precipitation-derived future projected discharges at the head of the delta, nine Global Climate Models (GCMs), namely, BCC-CSM1.1(m), GFDL-CM3, GFDL-ESM2G, HadGEM2-AO, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM and NorESM1-M, available in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) archive are considered. These nine GCMs are previously found to best-capture the Indian Summer Monsoon rainfall. Based on the performance of the nine GCMs in reproducing the historical discharge pattern, three GCMs (HadGEM2-AO, IPSL-CM5A-MR and MIROC-ESM-CHEM) are selected. A higher Taylor Skill Score is considered as the GCM selection criteria. Thereafter, the 10-year return period design flood is estimated using L-moments based flood frequency analysis for the historical and three future projected periods (2010-2039, 2040-2069 and 2070-2099) under Representative Concentration Pathways (RCP) 4.5 and 8.5. A non-dimensional hydrograph analysis is performed to obtain the hydrographs for the historical/projected 10-year return period design floods. These hydrographs are forced into the calibrated and validated coupled 1D-2D hydrodynamic model, MIKE FLOOD, to simulate the flood inundation in the delta region. Historical and projected flood risk is defined based on the information about the flood inundation simulated by the MIKE FLOOD model and the inundation depth-damage-duration relationship of a normal rice variety cultivated in the river delta. In general, flood risk is expected to increase in all the future projected time periods as compared to the historical episode. Further, in comparison to the 2010s (2010-2039), an increased flood risk in the 2040s (2040-2069) is shown by all the three selected GCMs. However, the flood risk then declines in the 2070s as we move towards the end of the century (2070-2099). The methodology adopted herein for flood risk assessment is one of its kind and may be implemented in any world-river basin. The results obtained from this study can help in future flood preparedness by implementing suitable flood adaptation strategies.

Keywords: flood frequency analysis, flood risk, global climate models (GCMs), paddy cultivation

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

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Authors: Feddal Imene, Boumediene Youssra, Mimanne Goussem

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The history of the environment and its chemistry is above all the history of its pollution. For a large part, it is the changes made in the air, water and soil by human beings. From there, we can define that pollution is an unfavorable modification of the natural environment that appears as a by-product of human action, through direct and indirect effects. The protection and preservation of the environment is one of the pillars of sustainable development, which is currently a major issue for the future of man and the planet. Currently, humanity is facing an alarming increase in the pollution of the natural environment by various organic or inorganic materials. The objective of our work is to study the adsorption of a textile dye which is known in the industrial environment, methyl green, on raw calcic clay. Our material was characterized by X-ray diffraction (XRD) Fourier transform infrared (FTIR), we also determined its cation exchange capacity (CEC), pHzc and specific surface by Methylene Blue method. The kinetic and thermodynamic study of the adsorption of methyl green was studied, these experiments resulted that the adsorption of the dye follows pseudo second order kinetics, and according to the thermodynamic study and the study of the probability we can say that we have a physisorption.

Keywords: calcic clay, dye, materials, environment

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Authors: Arnaud Deshais

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The supply chain industry has integrated the need for supplier Diversity and Inclusion (D&I), mostly from an ethical and moral argument. In addition, in some countries, it is also a legal requirement for companies reaching a certain size. As a matter of fact, a lot of successful companies have developed a Corporate Social Responsibility Program that encourages diversity and inclusion in the supply chain, such as building strong relationships with minority owned businesses (women, LGBT, veterans, etc.). Outside ethical and legal perspectives, it is also worth researching the economic and financial benefits of pursuing such efforts. Through surveys of purchasing and supply chain managers in their current roles as well as review of some case studies on supplier based D&I programs, it becomes apparent that a financial return on investment is to be expected as well for companies who make a concerted effort to grow their D&I programs. The study explores the levers to increase shareholder value and business efficiencies. Finally, the research highlights the competitive advantage related to a broad minority based supplier network. The benefits manifest themselves in the areas of competitiveness, innovation, and collaboration. The economic reward ends up being at the forefront of those programs while being an opportunity for organizations to become 'a good citizen'.

Keywords: diversity, inclusion, purchasing, supplier

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Authors: Rizwana Amin, Afshan Afroze Bhatti

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The study was a quasi-experimental pre-post test design including two groups. Data was collected from 127 students through non-probability random sampling from Bahaudin Zakariya University Multan. The groups were given pre-test using perceived stress scale and information about academic achievement was taken by self-report. After screening, 27 participants didn’t meet the criterion. Remaining 100 participants were divided into two groups (experimental and control). Further, 4 students of experimental group denied taking intervention. Then 46 understudies were separated into three subgroups (16, 15 and 15 in each) for training. The experimental groups were given the stress management training, each of experimental group attended one 3-hour training sessions separately while the control group was only given pre-post assessment. The data were analyzed using ANCOVA method (analysis of covariance) t–test. Results of the study indicate that stress training will lead to increased emotional intelligence and academic achievement of students.

Keywords: stress, stress management, academic achievement, students

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Authors: Amar Danial Abd Azis, Shipun Anuar Hamzah, Mohd Noh Dalimin, Khairun Nidzam Ramli, Mohd Sani Yahya, Fauziahanim Che Seman

Abstract:

This paper discusses the design, simulation results, and testing of a compact dual-band printed dipole antenna operating at frequencies of 916 MHz and 1.57 GHz for LoRa and GPS applications, respectively. The basic design of this antenna uses a linear dipole that operates at 916 MHz and 2.7 GHz. A small triangular-shaped linear balun has been developed as the matching network. Parasitic elements are employed to tune the second frequency to 1.57 GHz through a parametric study. Meanwhile, a stub is used to suppress the undesired 2.6 GHz frequency. This antenna is capable of operating on dual-frequency bands simultaneously with high efficiency in suppressing the unwanted frequency. The antenna exhibits the following parameters: return loss of -18.5 dB at 916 MHz and -14 dB at 1.57 GHz, VSWR of 1.25 at 868 MHz and 1.5 at 1.57 GHz, and gain of 2 dBi at 916 MHz and 2.75 dBi at 1.57 GHz. The radiation pattern of the antenna shows a directional E-plane and an omnidirectional H-plane at both frequencies. With its compact size and dual-band capability, this antenna demonstrates great potential for use in IoT applications that require both LoRa and GPS communication, particularly in applications where a small yet efficient form factor is essential.

Keywords: dual band, dipole antenna, parasitic elements, harmonic suppression, LoRa and Gps

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Authors: Ahmad Saad, Shuja Abbas, Breanna Marine

Abstract:

Introduction: This study explores the potential applications of autologous pedal fat pad grafting as a minimally invasive therapeutic strategy for addressing pedal fat pad loss. Without adequate shock absorbing tissue, a patient can experience functional deficits, ulcerations, loss of quality of life, and significant limitations with ambulation. This study details a novel technique involving autologous adipose grafting from the abdomen to enhance plantar fat pad thickness in a patient involved in a severe motor vehicle accident which resulted in total fat pad loss of the heel. Autologous adipose grafting (AAG) was used following adipose allografting in an effort to recreate a normal shock absorbing surface to allow return to activities of daily living and painless ambulation. Methods: A 46-year-old male sustained multiple open pedal fractures and necrosis to the heel fat pad after a motorcycle accident, which resulted in complete loss of the calcaneal fat pad. The patient underwent serial debridement’s, utilization of wound vac therapy and split thickness skin grafting to accomplish complete closure, despite complete loss of adipose to area. Patient presented with complaints of pain on ambulation, inability to bear weight on the heel, recurrent ulcerations, admitted had not been ambulating for two years. Clinical exam demonstrated complete loss of the plantar fat pad with a thin layer of epithelial tissue overlying the calcaneal bone, allowing visibility of the osseous contour of the calcaneus. Scar tissue had formed in place of the fat pad, with thickened epithelial tissue extending from the midfoot to the calcaneus. After conservative measures were exhausted, the patient opted for initial management by adipose allograft matrix (AAM) injections. Post operative X-ray imaging revealed noticeable improvement in calcaneal fat pad thickness. At 1 year follow up, the patient was able to ambulate without assistive devices. The fat pad at this point was significantly thicker than it was pre-operatively, but the thickness did not restore to pre-accident thickness. In order to compare the take of allograft versus autografting of adipose tissue, the decision to use adipose autograft through abdominal liposuction harvesting was deemed suitable. A general surgeon completed harvesting of adipose cells from the patient’s abdomen via liposuction, and a podiatric surgeon performed the AAG injection into the heel. Total of 15 cc’s of autologous adipose tissue injected to the calcaneus. Results: There was a visual increase in the calcaneal fat pad thickness both clinically and radiographically. At the 6-week follow up, imaging revealed retention of the calcaneal fat pad thickness. Three months postop, patient returned to activities of daily living and increased quality of life due to their increased ability to ambulate. Discussion: AAG is a novel treatment for pedal fat pad loss. These treatments may be viable and reproducible therapeutic choices for patients suffering from fat pad atrophy, fat pad loss, and/or plantar ulcerations. Both treatments of AAM and AAG exhibited similar therapeutic results by providing pain relief for ambulation and allowing for patients to return to their quality of life.

Keywords: podiatry, wound, adipose, allograft, autograft, wound care, limb reconstruction, injection, limb salvage

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

Abstract:

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 237

Authors: M. Kosandi, V. Susanti, N. I. Subono, E. Kartini

Abstract:

This paper discusses the risk of glorification trap in combating human trafficking, as it is shown in the case of Indonesia. Based on a research on Indonesian combat against trafficking in 2017-2018, this paper shows the tendency of misinterpretation and misapplication of the Indonesian anti-trafficking law into misusing the law for glorification, to create an image of certain extent of achievement in combating human trafficking. The objective of this paper is to explain the persistent occurrence of human trafficking crimes despite the significant progress of anti-trafficking efforts of Indonesian government. The research was conducted in 2017-2018 by qualitative approach through observation, depth interviews, discourse analysis, and document study, applying the three-dimensional model for analyzing human trafficking in the source country. This paper argues that the drive for glorification of achievement in the combat against trafficking has trapped Indonesian government in the loop of misinterpretation, misapplication, and misuse of the anti-trafficking law. In return, the so-called crime against humanity remains high and tends to increase in Indonesia.

Keywords: human trafficking, anti-trafficking policy, transnational crime, source country, glorification trap

Procedia PDF Downloads 172