Search results for: data loss

Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: Taehan Bae

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In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

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Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho

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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.

Keywords: ganoderma, oil palm, regression model, yield loss, economic loss

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Authors: Wu Xiaoguang, Liu Jiaxin, Fang Miaomiao, Wei Saidong

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There are many prestressed concrete prefabricated girder Bridges with small and medium span and the damage is serious. This paper mainly study the effect of prestress loss of prefabricated bridge bearing performance, through the establishment of ANSYS finite element model, from the condition of different prestress loss research, get the stress and strain data, draw curve, finally get the following conclusion: loss of prestress can reduce the ultimate bearing capacity of Bridges, the side span across the deflection value than the influence of times side span, the influence of the deflection in the midspan cross value. Therefore, the prestress loss and the effective prestress should be strictly considered in the design and construction process.

Keywords: across the deflection, loss of prestress, prefabricated girder bridge, the main tensile stress

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Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

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Authors: Sai Chand, Ashish Dhamaniya, Satish Chandra

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Curbside bus stops are provided on urban roads when sufficient land is not available to construct bus bays. The present study demonstrates the effect of curbside bus stops on midblock capacity of an urban arterial road. Data were collected on seven sections of 6-lane urban arterial roads in New Delhi. Three sections were selected without any side friction to estimate the base value of capacity. Remaining four sections were with curbside bus stop. Speed and volume data were collected in field and these data were used to estimate the capacity of a section. The average base midblock capacity of a 6–lane divided urban road was found to be 6314 PCU/hr which was further referred as base capacity. Effect of curbside bus stop on midblock capacity of urban road was evaluated by comparing the capacity of a section with curbside bus stop with that of the base capacity. Finally, a mathematical relation has been developed between bus frequency and capacity loss. Also a relation has been suggested between dwell time and capacity loss. The developed relations would be very useful for practising engineers to estimate capacity loss due to bus stop.

Keywords: bus frequency, bus stops, capacity loss, urban arterial

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

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Authors: Abdulrazaq O. Raji, Abba Mohammed, Ibrahim D. Mohammed

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This study was conducted to investigate foetal loss among slaughtered livestock species at the Maiduguri abattoir from 2009 to 2013. Record of animals slaughtered monthly and fetuses recovered were collected from the management of the Maiduguri abattoir. Data was subjected to Analysis of Variance using the General Linear Model of SPSS 13.0 with Season, Species and their interaction as fixed factors. Average yearly slaughter at the Maiduguri abattoir was 63,225 animals with cattle, camel, goat and sheep accounting for 19737, 7374, 19281 and 17540 of the total. The corresponding number of those pregnant were 3117, 839, 2281 and 2432 out of a total of 8522 animals. Thus, cattle, camel, goat and sheep accounted for 30.87, 11.53, 30.16 and 27.44%, respectively of the animals slaughtered at the Abattoir and 35.96, 9.68, 26.31 and 28.05% of the foetal loss. The effect of season and species on foetal loss was significant (P < 0.05). The number of pregnant animals slaughtered and foetal loss were higher during wet than dry season. Similarly, foetal loss at the abattoir was higher in the month of May in respect of camel, goat and sheep, and August for cattle. Camel was the least slaughtered animal and had the least number of pregnant females. Foetal loss (%) was higher (P < 0.05) for cattle compared to other species. The interaction showed that camel was the least slaughtered species in both seasons and cattle in the wet season had the highest foetal loss.

Keywords: abattoir, foetal loss, season, species

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Authors: Sumit Banerjee, Chandan Kumar Chanda

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The paper presents allocation of active power losses and energy losses to consumers connected to radial distribution networks in a deregulated environment for loads of composite types. A detailed comparison among four algorithms, namely quadratic loss allocation, proportional loss allocation, pro rata loss allocation and exact loss allocation methods are presented. Quadratic and proportional loss allocations are based on identifying the active and reactive components of current in each branch and the losses are allocated to each consumer, pro rata loss allocation method is based on the load demand of each consumer and exact loss allocation method is based on the actual contribution of active power loss by each consumer. The effectiveness of the proposed comparison among four algorithms for composite load is demonstrated through an example.

Keywords: composite type, deregulation, loss allocation, radial distribution networks

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Suhib A. Abu-Seini, Kyung-Doo Kim

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A heat loss model for ATLAS facility was introduced using SPACE code predefined correlations and various dialing factors. As all previous simulations were carried out using a heat loss free input; the facility was considered to be completely insulated and the core power was reduced by the experimentally measured values of heat loss to compensate to the account for the loss of heat, this study will consider heat loss throughout the simulation. The new heat loss model will be affecting SPACE code simulation as heat being leaked out of the system throughout a transient will alter many parameters corresponding to temperature and temperature difference. For that, a Station Blackout followed by a multiple Steam Generator Tube Rupture accident will be simulated using both the insulated system approach and the newly introduced heat loss input of the steady state. Major parameters such as system temperatures, pressure values, and flow rates to be put into comparison and various analysis will be suggested upon it as the experimental values will not be the reference to validate the expected outcome. This study will not only show the significance of heat loss consideration in the processes of prevention and mitigation of various incidents, design basis and beyond accidents as it will give a detailed behavior of ATLAS facility during both processes of steady state and major transient, but will also present a verification of how credible the data acquired of ATLAS are; since heat loss values for steady state were already mismatched between SPACE simulation results and ATLAS data acquiring system. Acknowledgement- This work was supported by the Korean institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea.

Keywords: ATLAS, heat loss, simulation, SPACE, station blackout, steam generator tube rupture, verification

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Authors: Aleema Rahman

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Introduction: This study aims to estimate the prevalence of long-term otitis media with effusion (OME) and hearing loss in a prospective longitudinal cohort studyand to study the relationship between the condition and educational and psychosocial outcomes. Methods: Analysis of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) will be undertaken. ALSPAC is a longitudinal birth cohort study carried out in the UK, which has collected detailed measures of hearing on ~7000 children from the age of seven. A descriptive analysis of the data will be undertaken to estimate the prevalence of OME and hearing loss (defined as having average hearing levels > 20dB and type B tympanogram) at 7, 9, 11, and 15 years as well as that of long-term OME and hearing loss. Logistic and linear regression analyses will be conducted to examine associations between long-term OME and hearing loss and educational outcomes (grades obtained from standardised national attainment tests) and psychosocial outcomes such as anxiety, social fears, and depression at ages 10-11 and 15-16 years. Results: Results will be presented in terms of the prevalence of OME and hearing loss in the population at each age. The prevalence of long-term OME and hearing loss, defined as having OME and hearing loss at two or more time points, will also be reported. Furthermore, any associations between long-term OME and hearing loss and the educational and psychosocial outcomes will be presented. Analyses will take into account demographic factors such as sex and social deprivation and relevant confounders, including socioeconomic status, ethnicity, and IQ. Discussion: Findings from this study will provide new epidemiological information on the prevalence of long-term OME and hearing loss. The research will provide new knowledge on the impact of OME for the small group of children who do not grow out of condition by age 7 but continue to have hearing loss and need clinical care through later childhood. The study could have clinical implications and may influence service delivery for this group of children.

Keywords: educational attainment, hearing loss, otitis media with effusion, psychosocial development

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Authors: Kaushika Vinotheeswaran

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The Greater Toronto Area (GTA), located in Ontario, Canada, is among the fastest-growing metropolitan areas in North America. Rapid urbanization within the GTA has led to increased imperviousness and surface runoff, contributing to wetland loss. Wetland cover and land cover data from the Southern Ontario Land Resource Information System were analyzed to characterize wetland loss to built-up areas and land conversions between 2005 and 2015, evaluating the extent of urbanization-induced wetland loss. Spatial analysis revealed a significant increase in the number of wetlands lost from 2005 to 2011 compared to the period from 2011 to 2015, with these losses attributed to increased urban expansions within the GTA. Non-wetland conversions, such as agricultural and impervious built-up uses to support urban expansions, played a significant role in wetland loss. Current approaches to wetland policy implementation and land-use planning strategies do not effectively identify or mitigate damage to wetlands in advance of development, resulting in significant wetland loss. Therefore, wetland conservation policies must be re-evaluated to address gaps in policy practice and focus on minimizing wetland loss.

Keywords: wetland loss, urbanization, impervious, pervious, wetland conservation

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Authors: Md. Rashidul Hasan, Atikur Rahman Baizid

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The Bayesian estimation approach is a non-classical estimation technique in statistical inference and is very useful in real world situation. The aim of this paper is to study the Bayes estimators of the parameter of exponential distribution under different loss functions and then compared among them as well as with the classical estimator named maximum likelihood estimator (MLE). In our real life, we always try to minimize the loss and we also want to gather some prior information (distribution) about the problem to solve it accurately. Here the gamma prior is used as the prior distribution of exponential distribution for finding the Bayes estimator. In our study, we also used different symmetric and asymmetric loss functions such as squared error loss function, quadratic loss function, modified linear exponential (MLINEX) loss function and non-linear exponential (NLINEX) loss function. Finally, mean square error (MSE) of the estimators are obtained and then presented graphically.

Keywords: Bayes estimator, maximum likelihood estimator (MLE), modified linear exponential (MLINEX) loss function, Squared Error (SE) loss function, non-linear exponential (NLINEX) loss function

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Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal

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Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.

Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer

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Authors: Pitak Keawbunsong, Sathaporn Promwong

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This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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Authors: Masica Jordan Alston, Angela N. Bullock, Angela S. Henderson, Stephanie Strianse, Sade Dunn, Joseph Hackett, Alaysia Black Hackett, Marcus Mason

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The Energy Model of Cumulative Grief was created in 2018. The Energy Model of Cumulative Grief utilizes historic models of grief stage theories. The innovative model is additionally unique due to its focus on cultural responsiveness. The Energy Model of Cumulative Grief helps to train practitioners who work with clients dealing with grief and loss. This paper assists in introducing the world to this innovative model and exploring how this model positively impacted a convenience sample of 140 practitioners and individuals experiencing grief and loss. Respondents participated in Webinars provided by the National Grief and Loss Center of America (NGLCA). Participants in this cross-sectional research design study completed one of three Grief and Loss Surveys created by the Grief and Loss Centers of America. Data analysis for this study was conducted via SPSS and Survey Hero to examine survey results for respondents. Results indicate that the Energy Model of Cumulative Grief was an effective resource for participants in addressing grief and loss. The majority of participants found the Webinars to be helpful and a conduit to providing them with higher levels of hope. The findings suggest that using The Energy Model of Cumulative Grief is effective in providing culturally responsive grief and loss resources to practitioners and clients. There are far reaching implications with the use of technology to provide hope to those suffering from grief and loss worldwide through The Energy Model of Cumulative Grief.

Keywords: grief, loss, grief energy, grieving brain

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Rickard Grassman, Carl Cederström

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In this paper, Lacanian theory will be used to illustrate the way discourses interact with the material by way of reifying antagonisms to shape our sense of identities in and around organizations. The ability to ‘sustain the loss’ is, in this view, the common structure here discerned in the very texture of a discourse, which reifies ‘lack’ as an ontological condition into something contingently absent (loss) that the subject hopes to overcome (desire). These fundamental human tendencies of identification are illustrated in the paper by examples drawn from history, cinema, and literature. Turning to a select sample of empirical accounts from a management consultancy firm, it is argued that this ‘sustaining the loss’ operates in discourse to enact identification in an organizational context.

Keywords: Lacan, identification, discourse, desire, loss

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Authors: Fatma Abidi, Taoufik Harizi, Slah Msahli, Faouzi Sakli

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Nine different Tunisian handmade carpets were used for the investigation. The raw material of the carpet pile yarns was wool. The influence of the different structure parameters (linear density and pile height) on the carpet compression was investigated. Carpets were tested under dynamic loading in order to evaluate and observe the thickness loss and carpet behavior under dynamic loads. To determine the loss of pile height under dynamic loading, the pile height carpets were measured. The test method was treated according to the Tunisian standard NT 12.165 (corresponds to the standard ISO 2094). The pile height measurements are taken and recorded at intervals up to 1000 impacts (measures of this study were made after 50, 100, 200, 500, and 1000 impacts). The loss of pile height is calculated using the variation between the initial height and those measured after the number of reported impacts. The experimental results were statistically evaluated using Design Expert Analysis of Variance (ANOVA) software. As regards the deformation, results showed that both of the structure parameters of the pile yarn and the pile height have an influence. The carpet with the higher pile and the less linear density of pile yarn showed the worst performance. Results of a polynomial regression analysis are highlighted. There is a good correlation between the loss of pile height and the impacts number of dynamic loads. These equations are in good agreement with measured data. Because the prediction is reasonably accurate for all samples, these equations can also be taken into account when calculating the theoretical loss of pile height for the considered carpet samples. Statistical evaluations of the experimen¬tal data showed that the pile material and number of impacts have a significant effect on mean thickness and thickness loss variations.

Keywords: Tunisian handmade carpet, loss of pile height, dynamic loads, performance

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Authors: N. E. Gallagher, C. E. Neville, N. Lyner, J. Yarnell, C. C. Patterson, J. E. Gallacher, Y. Ben-Shlomo, A. Fehily, J. V. Woodside

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Hearing loss is highly prevalent in older people and can reduce quality of life substantially. Emerging research suggests that potentially modifiable risk factors, including risk factors previously related to cardiovascular disease risk, may be associated with a decreased or increased incidence of hearing loss. This has prompted investigation into the possibility that certain nutrients, foods or dietary patterns may also be associated with incidence of hearing loss. The aim of this study was to determine any associations between dietary patterns and hearing loss in men enrolled in the Caerphilly study. The Caerphilly prospective cohort study began in 1979-1983 with recruitment of 2512 men aged 45-59 years. Dietary data was collected using a self-administered, semi-quantitative, 56-item food frequency questionnaire (FFQ) at baseline (1979-1983), and 7-day weighed food intake (WI) in a 30% sub-sample, while pure-tone unaided audiometric threshold was assessed at 0.5, 1, 2 and 4 kHz, between 1984 and 1988. Principal components analysis (PCA) was carried out to determine a posteriori dietary patterns and multivariate linear and logistic regression models were used to examine associations with hearing level (pure tone average (PTA) of frequencies 0.5, 1, 2 and 4 kHz in decibels (dB)) for linear regression and with hearing loss (PTA>25dB) for logistic regression. Three dietary patterns were determined using PCA on the FFQ data- Traditional, Healthy, High sugar/Alcohol avoider. After adjustment for potential confounding factors, both linear and logistic regression analyses showed a significant and inverse association between the Healthy pattern and hearing loss (P<0.001) and linear regression analysis showed a significant association between the High sugar/Alcohol avoider pattern and hearing loss (P=0.04). Three similar dietary patterns were determined using PCA on the WI data- Traditional, Healthy, High sugar/Alcohol avoider. After adjustment for potential confounding factors, logistic regression analyses showed a significant and inverse association between the Healthy pattern and hearing loss (P=0.02) and a significant association between the Traditional pattern and hearing loss (P=0.04). A Healthy dietary pattern was found to be significantly inversely associated with hearing loss in middle-aged men in the Caerphilly study. Furthermore, a High sugar/Alcohol avoider pattern (FFQ) and a Traditional pattern (WI) were associated with poorer hearing levels. Consequently, the role of dietary factors in hearing loss remains to be fully established and warrants further investigation.

Keywords: ageing, diet, dietary patterns, hearing loss

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Authors: Dchieche Amina, Aboulaich Rajae

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Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Jonathan A. Mikhail, Arsenio Paez

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It is not uncommon for a viral infection to cause hearing loss. Many viral infections are associated with sudden-onset, often unilateral, idiopathic sensorineural hearing loss. We conducted an exploratory study with thirty patients with pre-existing hearing loss between 50 and 64 to evaluate if COVID-19 was associated with exacerbated hearing loss. We hypothesized that hearing loss would be exacerbated by COVID-19 infection in patients with pre-existing hearing loss. A statistically significant paired T-test between pure tone averages (PTAs) at the patient’s original diagnosis and a current, updated audiometric assessment indicated a regression in hearing (p-value < .001) sensitivity following the contraction of COVID-19. Speech reception thresholds (SRTs) and word recognition scores (WRSs) were also considered, as well as the participants' gender. SRTs between each ear exhibited a statistically significant change (p-value of .002 and p-value < .001). WRSs did not show statistically significant differences (p-value of .290 and p-value of .098). A non-statistically significant Two-Way ANOVA was performed to evaluate gender’s potential role in exacerbated hearing loss and proved to be statistically insignificant (p-value of .214). This study discusses practical implications for clinical and educational pursuits in understanding COVID-19's effect on the auditory system and the need to evaluate the deadly virus further.

Keywords: audiology, COVID-19, sensorineural hearing loss, otology, auditory research

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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Authors: Marzieh Amiri, Zahra Iranpour Mobarakeh, Fatemeh Mehrbakhsh, Mehran Amiri

Abstract:

Introduction: Early diagnosis and intervention of congenital hearing loss is necessary to minimize the adverse effects of hearing loss. The aim of the present study was to report the results of newborn hearing screening in a centerin the south part of Iran, Fasa. Material and methods: In this study, the data related to 6,144 newbornsduring September 2018 up to September2021, was analyzed. Hearing screening was performed using transient evoked otoacoustic emissions (TEOAEs) and automated auditory brainstem response (AABR) tests. Results: From all 6144 newborns,3752 and 2392referred to the center from urban and rural part of Fasa, respectively. There were 2958 female and 3186 male in this study. Of 6144 newborns, 6098 ones passed the screening tests, and 46 neonates were referred to a diagnostic audiology clinic. Finally, nine neonates were diagnosed with congenital hearing loss (seven with sensorineural hearing loss and two with conductive hearing loss). The severity of all the hearing impaired neonates was moderate and above. The most important risk factors were family history of hearing loss, low gestational age, NICU hospitalization, and hyperbilirubinemia. Conclusion: Our results showed that the prevalence of hearing loss was 1.46 per 1000 infants. Boosting public knowledge by providing families with proper education appears to be helpful in preventing the negative effects of delayed implementation of health screening programs.

Keywords: newborn hearing screening, hearing loss, risk factor, prevalence

Procedia PDF Downloads 121

Authors: Filipa Cortez, Vanessa Pereira

Abstract:

Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

Procedia PDF Downloads 118