Search results for: hand function

Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

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Authors: Mimeche Leila, Debabeche Mahmoud

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It is question to study and to value the possibility of settling the process of purification by plants (constructed wetland) to treat the domestic waste water of Biskra, city in a semi-arid environment with grave problems of. According to the bibliography, the process of treatment by plants is considered as more advantageous than the classic techniques. It is the use of beds with macrophytes where the purification is made by the combined action of plants and micro-organisms in a filtering bed. The micro-organisms which are aerobic bacteria and\or anaerobic have for main function to degrade the polluting materials. Plants in the macrophytes beds have for function to serve as support in the development of bacteria and to favour also their development. In this study, we present a preliminary experimental analysis of the potentialities of treatment of some macrpohytes plants, implanted in basins filled of gravel. Analyses physico chemical and bacteriological of the waste water indicate a good elimination of the polluting materials, and put in evidence the purifier power of these plants, in association with bacteria. The obtained results seem to be interesting and encourage deepening the study for other types of plants in other conditions.

Keywords: constructed wetlands, macrophytes, sewage treatment, wastewater

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Authors: Liliane Ventura, Mauro Masili

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Ultraviolet (UV) protection is critical for sunglasses, and mydriasis, as well as miosis, are relevant parameters to consider. The literature reports that for sunglasses, ultraviolet protection is critical because sunglasses can cause the opposite effect if the lenses do not provide adequate UV protection due to the greater dilation of the pupil when wearing sunglasses. However, the scientific literature does not properly quantify to support this rationale. The reasoning may be misleading by ignoring not only the inherent absorption of UV by the sunglass lens materials but also by ignoring the absorption of the anterior structures of the eye, i.e., the cornea and aqueous humor. Therefore, we estimate the pupil diameter and calculate the solar ultraviolet influx through the pupil of the human eye for two situations of an individual wearing and not wearing sunglasses. We quantify the dilation of the pupil as a function of the luminance of the surrounding. Therefore, we calculate the influx of solar UV through the pupil of the eye for two situations for an individual wearing sunglass and for the eyes free of shade. A typical boundary condition for the calculation is an individual in an upright position wearing sunglasses, staring at the horizon as if the sun is in the zenith. The calculation was done for the latitude of the geographic center of the state of São Paulo (-22º04'11.8'' S) from sunrise to sunset. A model from the literature is used for determining the sky luminance. The initial approach is to obtain pupil diameter as a function of luminance. Therefore, as a preliminary result, we calculate the pupil diameter as a function of the time of day, as the sun moves, for a particular day of the year. The working range for luminance is daylight (10⁻⁴ – 10⁵ cd/m²). We are able to show how the pupil adjusts to brightness change (~2 - ~7.8 mm). At noon, with the sun higher, the direct incidence of light on the pupil is lower if compared to mid-morning or mid-afternoon, when the sun strikes more directly into the eye. Thus, the pupil is larger at midday. As expected, the two situations have opposite behaviors since higher luminance implies a smaller pupil. With these results, we can progress in the short term to obtain the transmittance spectra of sunglasses samples and quantify how light attenuation provided by the spectacles affects pupil diameter.

Keywords: sunglasses, UV protection, pupil diameter, solar irradiance, luminance

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Authors: Latha V. Prabhu, B.V. Murlimanju, P.J. Jiji, Mangala M. Pai

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Background: The capitate is the largest among the carpal bones. There exists no literature about the vascular foramina of the capitate bone. The objective of the present study was to investigate the morphology and number of the nutrient foramina in the cadaveric dried capitate bones of the Indian population. Methods: The present study included 59 capitate bones (25 right sided and 34 left sided) which were obtained from the gross anatomy laboratory of our institution. The bones were macroscopically observed for the nutrient foramina and the data was collected with respect to their number. The tabulation of the data and analysis were done. Results: All of our specimens (100%) exhibited the nutrient foramina over the non-articular and articular surfaces. The foramina were observed at the medial, lateral, palmar and dorsal surfaces of the capitate bones. The foramina were ranged from 6 to 23 in each capitate bone. In the medial surface, the foramina ranged from 1 to 6, lateral surface from 0 to 7, the foramina ranged between 0 and 5 in the palmar surface. However most of the foramina were located at the dorsal surface which ranged from 3 to 11. Conclusion: We believe that the present study has provided additional data about the nutrient foramina of the capitate bones. The data is enlightening to the orthopedic surgeon and would help in the hand surgeries. The knowledge about the foramina is also important to the radiologists to prevent the misinterpretation of the findings in the x ray and computed tomogram scan films. The foramina may mimick like erosions and ossicles. The morphological knowledge of the vasculature, their foramina of entry and number is required to understand the concepts in the avascular necrosis of the capitate.

Keywords: avascular necrosis, capitate, morphology, nutrient foramen

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Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

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Authors: Goodness Thandi Ntuli

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Some cultural aspects in the African context have a tendency of uplifting women while some thrust them into the worst denigration scenarios; hence African Women Theologians refer to culture as a ‘double edged sword. Through socialization and internalization of social norms, some women become custodians of life, denying aspects of the culture that are against them and hand them down to the next generation. This indirectly contributes to the perpetuation of patriarchal tendencies wherein women themselves uphold and endorse such tendencies to their own detriment. One of the findings of the empirical research study conducted among the Zulu young women in the South African context was that, on the one hand, lobola (the bride-price) is one of the cultural practices that contribute a great deal in the vilification of women. On the other hand, a woman whose lobola has been paid is highly esteemed in the cultural context not only by society at large but also by the implicated woman who takes pride in it. Consequently, lobola becomes an ambiguous cultural practice. Thus from the postcolonial feminist perspective, this paper examines and critiques lobola practice while also disclosing and exposing its deep seated cultural reinforcement that is life denying to women. The paper elucidates the original lobola as a cultural practice before colonization and how it became commercialized during colonial times. With commercialization in the modern world, lobola has completely lost its preliminary meaning and ceased to be a life-giving cultural practice, particularly for women. It turned out to be the worst cultural practice that demeans women to the extent that it becomes suicidal to women dignity because, in marriage, they become objects or property to the men who purchased them. Women objectification in marriage does not only leave them culturally trapped in what was perceived to be a good practice, but it also leads to women abuse and gender based or domestic violence. The research has indicated that this kind of violence is escalating and has become so pervasive in the South African context that the country is rated as one of the capital cities of violence against women in the world. Therefore, this paper demonstrates how cultural practices at times indirectly contribute to this national scourge that needs to be condemned, disparaged and rejected. Women in the African context where such cultural activities are still viewed as a norm are in desperate need for true liberation from such ambiguous cultural practices that leave them in the margins in spite of the earned social status they might have achieved.

Keywords: african, ambiguity, critique, culture, feminist, lobola, postcolonial, society

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Authors: Vedant Subhash

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This paper discusses the physics of the detection of thermal neutrons using thin-film coated semiconductor detectors. The thermal neutron detection efficiency as a function of film thickness is calculated for the front and back irradiation detector devices coated with ¹⁰B, ⁶LiF, and pure Li thin films. The detection efficiency for back irradiation devices is 4.15% that is slightly higher than that for front irradiation detectors, 4.0% for ¹⁰B films of thickness 2.4μm. The theoretically calculated thermal neutron detection efficiency using ¹⁰B film thickness of 1.1 μm for the back irradiation device is 3.0367%, which has an offset of 0.0367% from the experimental value of 3.0%. The detection efficiency values are compared and proved consistent with the given calculations.

Keywords: detection efficiency, neutron detection, semiconductor detectors, thermal neutrons

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Authors: Rabia Khaliala, Adi Vitman-Schorr

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Background: The increase in longevity of people on one hand, and on the other hand the fact that the social networks in later life become increasingly narrower, highlight the importance of Internet use to enhance quality of life (QoL). However, whether Internet use increases or decreases social networks, loneliness and quality of life is not clear-cut. Purposes: To explore the direct and/or indirect effects of Internet use on QoL, and to examine whether ethnicity and time the elderly spent with family moderate the mediation effect of Internet use on quality of life throughout loneliness. Methods: This descriptive-correlational study was carried out in 2016 by structured interviews with a convenience sample of 502 respondents aged 50 and older, living in northern Israel. Bootstrapping with resampling strategies was used for testing mediation a model. Results: Use of the Internet was found to be positively associated with QoL. However, this relationship was mediated by loneliness, and moderated by the time the elderly spent with family members. In addition, respondents' ethnicity significantly moderated the mediation effect between Internet use and loneliness. Conclusions: Internet use can enhance QoL of older adults directly or indirectly by reducing loneliness. However, these effects are conditional on other variables. The indirect effect moderated by ethnicity, and the direct effect moderated by the time the elderly spend with their families. Researchers and practitioners should be aware of these interactions which can impact loneliness and quality of life of older persons differently.

Keywords: internet use, loneliness, quality of life, social contacts

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Authors: A. Raj Kumar, A. Okunseinde, P. Raghavan, V. Kapila

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Stroke is the leading cause of adult disability worldwide. With recent advances in immediate post-stroke care, there is an increasing number of young stroke survivors, under the age of 65 years. While most stroke survivors will regain the ability to walk, they often experience long-term arm and hand motor impairments. Long term upper limb rehabilitation is needed to restore movement and function, and prevent deterioration from complications such as learned non-use and learned bad-use. We have developed a novel virtual coach, a wearable instrumented rehabilitation jacket, to motivate individuals to participate in long-term skill re-learning, that can be personalized to their impairment profile. The jacket can estimate the movements of an individual’s arms using embedded off-the-shelf sensors (e.g., 9-DOF IMU for inertial measurements, flex-sensors for measuring angular orientation of fingers) and a Bluetooth Low Energy (BLE) powered microcontroller (e.g., RFduino) to non-intrusively extract data. The 9-DOF IMU sensors contain 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer to compute the quaternions, which are transmitted to a computer to compute the Euler angles and estimate the angular orientation of the arms. The data are used in a gaming environment to provide visual, and/or haptic feedback for goal-based, augmented-reality training to facilitate re-learning in a cost-effective, evidence-based manner. The full paper will elaborate the technical aspects of communication, interactive gaming environment, and physical aspects of electronics necessary to achieve our stated goal. Moreover, the paper will suggest methods to utilize the proposed system as a cheaper, portable, and versatile system vis-à-vis existing instrumentation to facilitate post-stroke personalized arm rehabilitation.

Keywords: feedback, gaming, Euler angles, rehabilitation, augmented reality

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Authors: A. G. Margaryan

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Aims and Objectives: Assessment of health status and detection disorders of external respiration functions (ERF) during preventative medical examination among physicians of Armenia. Subjects and Methods: Overall, fifty-nine physicians (17 men and 42 women) were examined and spirometry was carried out. The average age of the physicians was 50 years old. The studies were conducted on the Micromedical MicroLab 3500 Spirometer. Results: 25.4% among 59 examined physicians are overweight; 22.0% of them suffer from obesity. Two physicians are currently smokers. About half of the examined physicians (50.8%) at the time of examination were diagnosed with some diseases and had different health-related problems (excluding the problems related to vision and hearing). FVC was 2.94±0.1, FEV1 – 2.64±0.1, PEF – 329.7±19.9, and FEV₁%/FVC – 89.7±1.3. Pathological changes of ERF are identified in 23 (39.0%) cases. 28.8% of physicians had first degree of restrictive disorders, 3.4% – first degree of combined obstructive/ restrictive disorders, 6.8% – second degree of combined obstructive/ restrictive disorders. Only three physicians with disorders of the ERF were diagnosed with chronic bronchitis and bronchial asthma. There were no statistically significant changes in ERF depending on the severity of obesity (P> 0.05). Conclusion: The study showed the prevalence of ERF among physicians, observing mainly mild and moderate changes in ERF parameters.

Keywords: Armenia, external respiration function, health status, physicians

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Authors: Alina Beraudi, Simona Catalani, Dalila De Pasquale, Eva Bianconi, Umberto Santoro, Susanna Stea, Pietro Apostoli

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Recently the European Community, in line with the international scientific community such as with the Consensus Statement, has determined to stop the use of metal-on-metal big head stemmed hip prosthesis. Among the factors accounted as responsible for the high failure rates of these hip implants are the release and accumulation of metal ions. Many studies have correlated the presence of these ions, besides other factors, with the induction of oxidative stress response. In our study on 12 subjects, we observed the patient specific capability to eliminate metal ions after revision surgery. While for cobalt all the patients were able to completely excrete cobalt ions within 5-7 months after metal-on-metal bearing removal, for chromium ions it didn’t happen. If on the one hand the toxicokinetic differences between the two types of ions are confirmed by toxicological and occupational studies, on the other hand, this peculiar way of exposition represents a novel and important point of view. Thus, two different approaches were performed to better understand the subject specific capability to transport metal ions (albumin study) and to manage the response to them (heme-oxygenase-1 study): - a mutational screening of ALBUMIN gene was conducted in 30 MoM prosthetic patients resulting in the absence of nucleotidic changes compared with the ALB reference sequence. To this study was also added the analysis of expression of modified albumin protein; - a gene and protein expression study on 44 patients of heme-oxygenase-1, that is one of the most important antioxidant enzyme induced by metallic ions, was performed. This study resulted in no statistically significant differences in the expression of the gene and protein heme-oxygenase-1 between prosthetic and non-prosthetic patients, as well as between patients with high and low ions levels. Our results show that the protein studied (albumin and heme-oxygenase-1) seem to be not involved in determining chromium and cobalt ions level. On the other hand, achromium and cobalt elimination rates are different, but similar in all patients analyzed, suggesting that this process could be not patient-related. We support the importance of researching more about ions transport within the organism once released by hip prosthesis, about the chemical species involved, the districts where they are contained and the mechanisms of elimination, not excluding the existence of a subjective susceptibility to these metals ions.

Keywords: chromium, cobalt, hip prosthesis, individual susceptibility

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Omer Oral, Y. Emre Yilmaz

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Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.

Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization

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Authors: Jaime R. Silva, Gabriel E. Reyes, Marianne Krause

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Background: The two-polarity model of the depressive personality argues that experience is organized around two axes: interpersonal relatedness and self-definition. Differential emphasis on one of these poles defines three types of depressive experience: Anaclitic, Introjective or Mixed pattern. On the one hand, Anaclitic pattern has been conceptually related with exaggerated biological stress sensitivity. On the other hand, the Introjective pattern was linked with anhedonic symptomatology. The general aim of the study was to find empirical support for this relationship. Methods: 101 non-clinical individuals participated in two experimental sessions. During the first session, the biological stress reactivity (cortisol concentration in saliva) and the subjective stress perceived (self-reported) during the Trier Social Stress Test (TSST), were investigated. In the second session, a visual discrimination task with a specific reward system, to study the reinforcement sensitivity (anhedonia), was performed. Results: Results evidenced that participants with Introjective depressive symptoms showed a higher interpersonal sensitivity and a diminished sensitivity to reinforcement. In addition, results also indicated that such a group has a poor psychological detection of its exacerbated reactivity to stress, which is the opposite pattern evidenced amongst the Anaclitic group. Conclusions: In perspective, these results empirically support the two-polarity of the depressive personality model. Clinical implications are discussed.

Keywords: depression, interpersonal stress, personality, trier social stress test

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Dalal Alghawas, Jetty Lee, Kaisa Poutanen, Hani El-Nezami

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Oat β-glucan a water soluble non starch linear polysaccharide has been approved as a cholesterol lowering agent by various food safety administrations and is commonly used to reduce the risk of heart disease. The molecular weight of oat β-glucan can vary depending on the extraction and fractionation methods. It is not clear whether the molecular weight has a significant impact at reducing the acceleration of atherosclerosis. The aim of this study was to investigate three different oat β-glucan fractionations on the development of atherosclerosis in vivo. With special focus on plaque stability and the intestinal barrier function. To test this, ApoE-/- female mice were fed a high fat diet supplemented with oat bran, high molecular weight (HMW) oat β-glucan fractionate and low molecular weight (LMW) oat β-glucan fractionate for 16 weeks. Atherosclerosis risk markers were measured in the plasma, heart and aortic tree. Plaque size was measured in the aortic root and aortic tree. ICAM-1, VCAM-1, E-Selectin, P-Selectin, protein levels were assessed from the aortic tree to determine plaque stability at 16 weeks. The expression of p22phox at the aortic root was evaluated to study the NADPH oxidase complex involved in nitric oxide bioavailability and vascular elasticity. The tight junction proteins E-cadherin and beta-catenin from western blot analyses were analysed as an intestinal barrier function test. Plasma LPS, intestinal D-lactate levels and hepatic FMO gene expression were carried out to confirm whether the compromised intestinal barrier lead to endotoxemia. The oat bran and HMW oat β-glucan diet groups were more effective than the LMW β-glucan diet group at reducing the plaque size and showed marked improvements in plaque stability. The intestinal barrier was compromised for all the experimental groups however the endotoxemia levels were higher in the LMW β-glucan diet group. The oat bran and HMW oat β-glucan diet groups were more effective at attenuating the development of atherosclerosis. Reasons for this could be due to the LMW oat β-glucan diet group’s low viscosity in the gut and the inability to block the reabsorption of cholesterol. Furthermore the low viscosity may allow more bacterial endotoxin translocation through the impaired intestinal barrier. In future food technologists should carefully consider how to incorporate LMW oat β-glucan as a health promoting food.

Keywords: Atherosclerosis, beta glucan, endotoxemia, intestinal barrier function

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Authors: Thomas Heffernan, Nick Neave, Colin Hamilton, Gill Case

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Hoarding is the acquisition of and failure to discard possessions, leading to excessive clutter and significant psychological/emotional distress. From a cognitive-behavioural approach, excessive hoarding arises from information-processing deficits, as well as from problems with emotional attachment to possessions and beliefs about the nature of possessions. In terms of information processing, hoarders have shown deficits in executive functions, including working memory, planning, inhibitory control, and cognitive flexibility. However, this previous research is often confounded by co-morbid factors such as anxiety, depression, or obsessive-compulsive disorder. The current study adopted a cognitive-behavioural approach, specifically assessing executive deficits and working memory in a non-clinical sample of hoarders, compared with non-hoarders. In this study, a non-clinical sample of 40 hoarders and 73 non-hoarders (defined by The Savings Inventory-Revised) completed the Adult Executive Functioning Inventory, which measures working memory and inhibition, Dysexecutive Questionnaire-Revised, which measures general executive function and the Hospital Anxiety and Depression Scale, which measures mood. The participant sample was made up of unpaid young adult volunteers who were undergraduate students and who completed the questionnaires on a university campus. The results revealed that, after observing no differences between hoarders and non-hoarders on age, sex, and mood, hoarders reported significantly more deficits in inhibitory control and general executive function when compared with non-hoarders. There was no between-group difference on general working memory. This suggests that non-clinical hoarders have a specific difficulty with inhibition-control, which enables you to resist repeated, unwanted urges. This might explain the hoarder’s inability to resist urges to buy and keep items that are no longer of any practical use. These deficits may be underpinned by general executive function deficiencies.

Keywords: hoarding, memory, executive, deficits

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Authors: Manar Y. Abd El-Aziz, Alyaa E. Morgham, Amira A. El-Fallal, Heba Tolla E. Abo El Naga

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Different textile materials are usually used in upholstery. However, upholstery parts may become unhealthy when dust accrues and bacteria raise on the surface, which negatively affects the user's health. Also, leather and artificial leather were used in upholstery but, leather has a high cost and artificial leather has a potential chemical risk for users. Researchers have advanced vegie leather made from bacterial cellulose a symbiotic culture of bacteria and yeast (SCOBY). SCOBY remains a gelatinous, cellulose biofilm discovered floating at the air-liquid interface of the container. But this leather still needs some enhancement for its mechanical properties. This study aimed to prepare SCOBY, produce bamboo rib knitted fabrics with two different stitch densities, and cotton woven fabric then laminate these fabrics with the prepared SCOBY film to enhance the mechanical properties of the SCOBY leather at the same time; add anti-microbial function to the prepared fabrics. Laboratory tests were conducted on the produced samples, including tests for function properties; anti-microbial, thermal conductivity and light transparency. Physical properties; thickness and mass per unit. Mechanical properties; elongation, tensile strength, young modulus, and peel force. The results showed that the type of the fabric affected significantly SCOBY properties. According to the test results, the bamboo knitted fabric with higher stitch density laminated with SCOBY was chosen for its tensile strength and elongation as the upholstery of a bed model with antimicrobial properties and comfortability in the headrest design. Also, the single layer of SCOBY was chosen regarding light transparency and lower thermal conductivity for the creation of a lighting unit built into the bed headboard.

Keywords: anti-microbial, bamboo, rib, SCOPY, upholstery

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Ghada Mahmoud El Kassas, Maged Atta El Wakeel

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Background: Environmental enteric dysfunction (EED) is impending trouble that flared up in the last decades to be pervasive in infants and children. EED is asymptomatic villous atrophy of the small bowel that is prevalent in the developing world and is associated with altered intestinal function and integrity. Evidence has suggested that supplementary zinc might ameliorate this damage by reducing gastrointestinal inflammation and may also benefit cognitive development. Objective: We tested whether zinc supplementation improves intestinal integrity, growth, and cognitive function in stunted children predicted to have EED. Methodology: This case–control prospective interventional study was conducted on 120 Egyptian Stunted children aged 1-10 years who recruited from the Nutrition clinic, the National research center, and 100 age and gender-matched healthy children as controls. At the primary phase of the study, Full history taking, clinical examination, and anthropometric measurements were done. Standard deviation score (SDS) for all measurements were calculated. Serum markers as Zonulin, Endotoxin core antibody (EndoCab), highly sensitive C-reactive protein (hsCRP), alpha1-acid glycoprotein (AGP), Tumor necrosis factor (TNF), and fecal markers such as myeloperoxidase (MPO), neopterin (NEO), and alpha-1-anti-trypsin (AAT) (as predictors of EED) were measured. Cognitive development was assessed (Bayley or Wechsler scores). Oral zinc at a dosage of 20 mg/d was supplemented to all cases and followed up for 6 months, after which the 2ry phase of the study included the previous clinical, laboratory, and cognitive assessment. Results: Serum and fecal inflammatory markers were significantly higher in cases compared to controls. Zonulin (P < 0.01), (EndoCab) (P < 0.001) and (AGP) (P < 0.03) markedly decreased in cases at the end of 2ry phase. Also (MPO), (NEO), and (AAT) showed a significant decline in cases at the end of the study (P < 0.001 for all). A significant increase in mid-upper arm circumference (MUAC) (P < 0.01), weight for age z-score, and skinfold thicknesses (P< 0.05 for both) was detected at end of the study, while height was not significantly affected. Cases also showed significant improvement of cognitive function at phase 2 of the study. Conclusion: Intestinal inflammatory state related to EED showed marked recovery after zinc supplementation. As a result, anthropometric and cognitive parameters showed obvious improvement with zinc supplementation.

Keywords: stunting, cognitive function, environmental enteric dysfunction, zinc

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Authors: Shin-Ku Lee, Ming-Tsu Ho

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A newly proposed antireflective selector with shuffled structure is reported in this paper. The proposed idea is made of two different quarter wavelength (QW) slabs and numerically supported by the one-dimensional simulation results provided by the method of characteristics (MOC) to function as an antireflective selector. These two QW slabs are characterized by dielectric constants εᵣA and εᵣB, uniformly divided into N and N+1 pieces respectively which are then shuffled to form an antireflective plate with B(AB)N structure such that there is always one εᵣA piece between two εᵣB pieces. Another is A(BA)N structure where every εᵣB piece is sandwiched by two εᵣA pieces. Both proposed structures are numerically proved to function as QW plates. In order to allow maximum transmission through the proposed structures, the two dielectric constants are chosen to have the relation of (εᵣA)² = εᵣB > 1. The advantages of the proposed structures over the traditional anti-reflection coating techniques are two components with two thicknesses and to shuffle to form new QW structures. The design wavelength used to validate the proposed idea is 71 mm corresponding to a frequency about 4.225 GHz. The computational results are shown in both time and frequency domains revealing that the proposed structures produce minimum reflections around the frequency of interest.

Keywords: method of characteristics, quarter wavelength, anti-reflective plate, propagation of electromagnetic fields

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Authors: Walid Hassairi, Moncef Bousselmi, Mohamed Abid

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Functional verification is a major part of today’s system design task. Several approaches are available for verification on a high abstraction level, where designs are often modeled using MATLAB/Simulink. However, different approaches are a barrier to a unified verification flow. In this paper, we propose a co-simulation interface between SystemC and MATLAB and Simulink to enable functional verification of multi-abstraction levels designs. The resulting verification flow is tested on JPEG compression algorithm. The required synchronization of both simulation environments, as well as data type conversion is solved using the proposed co-simulation flow. We divided into two encoder jpeg parts. First implemented in SystemC which is the DCT is representing the HW part. Second, consisted of quantization and entropy encoding which is implemented in Matlab is the SW part. For communication and synchronization between these two parts we use S-Function and engine in Simulink matlab. With this research premise, this study introduces a new implementation of a Hardware SystemC of DCT. We compare the result of our simulation compared to SW / SW. We observe a reduction in simulation time you have 88.15% in JPEG and the design efficiency of the supply design is 90% in SDR.

Keywords: hardware/software, co-design, co-simulation, systemc, matlab, s-function, communication, synchronization

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Authors: Valerii Dashuk

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The usage of the confidence intervals in economics and econometrics is widespread. To be able to investigate a random variable more thoroughly, joint tests are applied. One of such examples is joint mean-variance test. A new approach for testing such hypotheses and constructing confidence sets is introduced. Exploring both the value of the random variable and its deviation with the help of this technique allows checking simultaneously the shift and the probability of that shift (i.e., portfolio risks). Another application is based on the normal distribution, which is fully defined by mean and variance, therefore could be tested using the introduced approach. This method is based on the difference of probability density functions. The starting point is two sets of normal distribution parameters that should be compared (whether they may be considered as identical with given significance level). Then the absolute difference in probabilities at each 'point' of the domain of these distributions is calculated. This measure is transformed to a function of cumulative distribution functions and compared to the critical values. Critical values table was designed from the simulations. The approach was compared with the other techniques for the univariate case. It differs qualitatively and quantitatively in easiness of implementation, computation speed, accuracy of the critical region (theoretical vs. real significance level). Stable results when working with outliers and non-normal distributions, as well as scaling possibilities, are also strong sides of the method. The main advantage of this approach is the possibility to extend it to infinite-dimension case, which was not possible in the most of the previous works. At the moment expansion to 2-dimensional state is done and it allows to test jointly up to 5 parameters. Therefore the derived technique is equivalent to classic tests in standard situations but gives more efficient alternatives in nonstandard problems and on big amounts of data.

Keywords: confidence set, cumulative distribution function, hypotheses testing, normal distribution, probability density function

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Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: Achsania Hendratmi, Nisful Laila, Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum

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This study aims to compare and see the differences between Islamic bank in Indonesia and Islamic bank in Malaysia using RGEC method (Risk Profile, Good Corporate Governance, Earnings, and Capital). This study examines the comparison in business and social performance of eleven Islamic banks in Indonesia and fifteen Islamic banks in Malaysia. This research used quantitative approach and the collections of data was done by collecting all the annual reports of banks that has been created as a sample over the period 2011-2015. The test result of the Independent Samples T-test and Mann-Whitney Test showed there were differences in the business performance of Islamic Bank in Indonesia and Malaysia as seen from the aspect of Risk profile (FDR), GCG, and Earnings (ROA). Also, there were differences of business and social performance as seen from Earnings (ROE), Capital (CAR), and Sharia Conformity Indicator (PSR and ZR) aspects.

Keywords: business performance, Islamic banks, RGEC, social performance

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Nazli Uren, Ayse Okur

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Tactile comfort of a textile product is an essential property and a major concern when it comes to customer perceptions and preferences. The subjective nature of comfort and the difficulties regarding the simulation of human hand sensory feelings make it hard to establish a well-accepted link between tactile comfort and objective evaluations. On the other hand, shear behavior of a fabric is a mechanical parameter which can be measured by various objective test methods. The principal aim of this study is to determine the tactile comfort of commercially available denim fabrics by subjective measurements, create a tactile score database for denim fabrics and investigate the relations between tactile comfort and shear behavior. In-plane shear behaviors of 17 different commercially available denim fabrics with a variety of raw material and weave structure were measured by a custom design shear frame and conventional bias extension method in two corresponding diagonal directions. Tactile comfort of denim fabrics was determined via subjective customer evaluations as well. Aforesaid relations were statistically investigated and introduced as regression equations. The analyses regarding the relations between tactile comfort and shear behavior showed that there are considerably high correlation coefficients. The suggested regression equations were likewise found out to be statistically significant. Accordingly, it was concluded that the tactile comfort of denim fabrics can be estimated with a high precision, based on the results of in-plane shear behavior measurements.

Keywords: denim fabrics, in-plane shear behavior, linear regression estimation, tactile comfort

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

Procedia PDF Downloads 195