Search results for: diagnostic accuracy

Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Bharti Arora, Michael Chen, Steven Lun

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Plasmacytoid urothelial carcinoma (PUC) of the bladder is a rare and aggressive subtype of urothelial carcinoma that usually presents at an advanced clinical stage, has a predilection for early metastatic potential and is associated with poor prognosis. The first reported case of PUC was in 1991 and approximately 100 cases were reported in the literature worldwide. We present a case of a 43 year old female presenting with a 3-month history of urgency and frequency. Failing medical management of her urinary symptoms with anticholinergic medication, she underwent a diagnostic cystoscopy which revealed an erythematous and indurated bladder. Bladder biopsies of these regions revealed plasmacytoid urothelial carcinoma. Pre-operative staging scans were clear of any metastatic disease and the patient subsequently underwent a radical cystectomy and pelvic clearance with the formation of ileal conduit for urinary diversion. Histology confirmed plasmacytoid urothelial carcinoma with involvement of right upper vagina and focally positive margins in soft tissue at right and left sides of bladder. She received adjuvant chemotherapy but passed away within a year from disease progression. PUC can present atypically and our case highlights the role of cystoscopy in patients with persistent urinary symptoms. By reviewing the literature on PUC, we aim to raise awareness and improve understanding of this rare bladder cancer subtype amongst urologists.

Keywords: urology, bladder cancer, plasmacytoid urothelial cancer, literature review

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Authors: J. B. Sharma, Vivek Kakkar, Sunesh Kumar, K. K. Roy, Rajesh Kumari, Kavita Pandey, Smriti Hari

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Background: Stress urinary incontinence (SUI) is a common problem affecting the quality of life of women. Methods: It is a prospective study conducted over 40 women of SUI by endovaginal ultrasound on rest and Valsalva preoperatively and six months postoperatively for levator hiatus, pubovisceral thickness, urethral length, and bladder neck position. A 24-hour pad test was also performed on all women at the same time for grading of SUI. Treatment given was medical in 4 (10%), Burch colposuspension in 18 (45%), and tension-free obturator tape in 18 (45%). Results: Mean age, parity, and body mass index in the study were 41.60 years, 2.73, and 24.2 kg/m², respectively. All 40 (100%) patients had SUI, with the mean duration of symptoms being 4.04 years. On the 24-hour pad test, mild SUI was in 4 (10%), moderate SUI in 33 (82.5%), and severe SUI in 3 (7.5%), with mean preoperative 24-hour pad test being 36.69 gm which significantly reduced to 9.79 gm postoperatively (p 0.001). There was a significant change in levator hiatus and pubovisceral thickness with the treatment of SUI. Overall urethral length increased, but there was a significant decrease in urethral length on Valsalva after the treatment (0.40 versus 0.28 cm, p 0.04) and a significant reduction in bladder neck descent after Valsalva after treatment (0.41 cm versus 0.27 cm, p 0.001). Conclusion: Endovaginal ultrasound and 24-hour pad test are useful diagnostic modalities for SUI diagnosis and to see the impact of treatment.

Keywords: stress urinary incontinence, endovaginal ultrasound, 24-hours pad test, pubovisceral muscle thickness

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Authors: S. A. Gayvoronsky, T. A. Ezangina

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The robust control system objects with interval-undermined parameters is considers in this paper. Initial information about the system is its characteristic polynomial with interval coefficients. On the basis of coefficient estimations of quality indices and criterion of the maximum stability degree, the methods of synthesis of a robust regulator parametric is developed. The example of the robust stabilization system synthesis of the rope tension is given in this article.

Keywords: interval polynomial, controller synthesis, analysis of quality factors, maximum degree of stability, robust degree of stability, robust oscillation, system accuracy

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Authors: Kwok W. Cheung

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A scientific interpretation of creation reconciling the beliefs of six literal days of creation and a 13.7-billion-year-old universe currently perceived by most modern cosmologists is proposed. We hypothesize that the reference timeframe of God’s creation is associated with some cosmic time different from the earth's time. We show that the scale factor of earth time to cosmic time can be determined by the solution of the Friedmann equations. Based on this scale factor and some basic assumptions, we derive a Cosmic Time Dilation model that harmonizes the literal meaning of creation days and scientific discoveries with remarkable accuracy.

Keywords: cosmological expansion, time dilation, creation, genesis, relativity, Big Bang, biblical hermeneutics

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Authors: Jake Tempo, Stephen Brough

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Introduction and Objectives: Urine cytology has a role in the diagnosis of urothelial cancer when used alongside cystoscopy and imaging, according to the European Association of Urology guidelines. It also has a role in the surveillance post-treatment of urothelial carcinoma. Collecting and analysing urine cytology is costly and time-consuming. We investigated the use of urine cytology in an Australian regional hospital to determine whether clinicians are following international guidelines. Materials and Methods: We analysed all urine cytology requests performed in an Australian regional hospital between 1st January 2017 and 31st December 2018. We reviewed the indication for urine cytology and the patients’ case notes to determine whether urine cytology changed management. Results: During the two-year study period, 153 patients had urine cytology analysed for a variety of indications. In no cases did cytology change the outcome of patient management significantly. In total, 69 of 153 (41%) urine cytology requests were not supported by urological society guidelines. Fifty requests were for haematuria, and twenty requests were for urothelial cancer surveillance. Seven were analysed for follow-up from previous urological investigations. Nine samples were sent for ureteric obstruction of unknown origin. Conclusion: Urine cytology, even when positive, did not significantly change management for the investigation of potential urothelial cancer, and therefore, its use as a diagnostic tool for this purpose should be reconsidered. Many cytology tests are expensive, unnecessary, and not supported by urological society guidelines.

Keywords: cytology, bladder cancer, urine, urothelial carcinoma

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Authors: Javad Nosratabadi

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This paper investigates the difference between firms' actual and expected employment along with the amount of loans invested by them. In addition, it examines the relationship between the amount of loans received by firms and wages. Empirically, using a causal effect estimation and firm-level data from a province in Iran between 2004 and 2011, the results show that there is a range of the loan amount for which firms' expected employment meets their actual one. In contrast, there is a gap between firms' actual and expected employment for any other loan amount. Furthermore, the result shows that there is a positive and significant relationship between the amount of loan invested by firms and wages.

Keywords: expected employment, actual employment, wage, loan

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Authors: Gaohuizi Guo, Ning Zhang

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Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: firefly algorithm, hybrid algorithm, multi-objective optimization, sine cosine algorithm

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Authors: H. İmrek, O. Corumluoglu, B. Akdemir, I. Sanlioglu

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It is important to be able to determine the heading direction of a moving vehicle with respect to a distant location. Additionally, it is important to be able to direct a rotating platform on a moving vehicle towards a distant position or location on the earth surface, especially for applications such as determination of the Kaaba direction for daily Muslim prayers. GNNS offers some reasonable solutions. In this study, a functional model of such a directing system supported by GNNS is discussed, and an appropriate system is designed for these purposes. An application for directing system is done by using RTK and DGNSS. Accuracy estimations are given for this system.

Keywords: GNNS, orientation of rotating platform, vehicle orientation, prayer aid device

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Authors: I. Caldas, T. Duarte

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Avoidant Restrictive Food Intake Disorder (ARFID) was included for the first time in DSM-5, replacing the old diagnosis of DSM-4 'Early Childhood Eating Disorder'. An ARFID is characterized by a restrictive/avoidant eating pattern that can lead to severe nutritional deficiency, weight loss, nutritional supplementation dependence, and poor psychosocial functioning. This eating pattern is associated with decreased interest in food, worries about food characteristics or the act of ingestion, and lack of concern with weight or body image. This paper aims to understand the impact of this new diagnosis in other Eating Disorders (ED) prevalence, as well as to compare their therapeutic approaches. Methodology: Literature reviewed by PubMed with the following keywords: 'ARFID', 'Prevalence', and 'Eating Disorders'. We selected articles related to this theme, written since 2016. Results: In a population of children hospitalized with ED, 5% to 14% was diagnosed with ARFID, and, as outpatient treatment, the prevalence was 22%. People diagnosed with ARFID have more prevalence of other comorbidities, especially autism spectrum, are younger, and are more often male. Regarding the treatment of ARFID, it most often required nasogastric feeding, and with less suffering associated with this procedure, compared to AN. Despite these differences, 12% of patients diagnosed with ARFID transited to AN during treatment, suggesting that the first pathology may be a risk factor for the development of AN. Conclusions: The differences identified between ARFID and the other EDs are important when analyzed as differential diagnostic hypotheses and therapeutic approaches. Further study is necessary regarding its prevalence, risk factors, and treatment.

Keywords: avoidant restrictive food intake disorder, ARFID, differential diagnoses, eating disorders, prevalence

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Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

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Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: accelerometer, AdaBoost, GPS, mode prediction, support vector machine

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Authors: Long Kim Vu, Ban Dang Nguyen

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In this paper, the finite element method (FEM) is utilized to simulate the comprehensive process including tightening, releasing and self-loosening of a bolt joint under transverse vibration. Following to the accurate geometry of helical threads, an absolutely hexahedral meshing is implemented. The accuracy of simulation process is verified and validated by comparison with the experimental results on clamping force-vibration relationship, which shows the sufficient correlation. Further analysis with different amplitude and frequency of transverse vibration is done to determine the dominant factor inducing the failure.

Keywords: bolt self-loosening, contact state, finite element method, FEM, helical thread modeling

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Authors: Prachi Choudhary, Jai Gopal Sharma

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Microbial cultures determine the type of organism, its abundance in the tested sample, or both. It is one of the primary diagnostic methods of microbiology. It is used to determine the cause of infectious disease by letting the agent multiply in a predetermined medium. Different bacteria produce colonies that may be very distinct from the bacterial species that produced them. To culture any pathogen or microorganism, we should first know about the types of media used in microbiology for culturing. Sometimes sub culturing is also done in various microorganisms if some mixed growth is seen in culture. Nearly 3 types of culture media based on consistency – solid, semi-solid, and liquid (broth) media; are further explained in the report. Then, The Five I's approach is a method for locating, growing, observing, and characterizing microorganisms, including inoculation and incubation. Isolation, inspection, and identification. For identification of bacteria, we have to culture the sample like urine, sputum, blood, etc., on suitable media; there are different methods of culturing the bacteria or microbe like pour plate method, streak plate method, swabbing by needle, pipetting, inoculation by loop, spreading by spreader, etc. After this, we see the bacterial growth after incubation of 24 hours, then according to the growth of bacteria antibiotics susceptibility test is conducted; this is done for sensitive antibiotics or resistance to that bacteria, and also for knowing the name of bacteria. Various methods like the dilution method, disk diffusion method, E test, etc., do antibiotics susceptibility tests. After that, various medicines are provided to the patients according to antibiotic sensitivity and resistance.

Keywords: inoculation, incubation, isolation, antibiotics suspectibility test, characterizing

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Authors: Brock Buckingham, Zhe Lin, Wenxuan Guo

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Accurate elevation data is critical in deriving topographic attributes for the precision management of crop inputs, especially water and nutrients. Traditional ground-based elevation data acquisition is time consuming, labor intensive, and often inconvenient at the field scale. Various unmanned aerial systems (UAS) provide the capability of generating digital elevation data from high-resolution images. The objective of this study was to compare the performance of two UAS with different global positioning system (GPS) receivers in determining elevation at the field scale. A DJI Phantom 4 Pro and a DJI Phantom 4 RTK(real-time kinematic) were applied to acquire images at three heights, including 40m, 80m, and 120m above ground. Forty ground control panels were placed in the field, and their geographic coordinates were determined using an RTK GPS survey unit. For each image acquisition using a UAS at a particular height, two elevation datasets were generated using the Pix4D stitching software: a calibrated dataset using the surveyed coordinates of the ground control panels and an uncalibrated dataset without using the surveyed coordinates of the ground control panels. Elevation values for each panel derived from the elevation model of each dataset were compared to the corresponding coordinates of the ground control panels. The coefficient of the determination (R²) and the root mean squared error (RMSE) were used as evaluation metrics to assess the performance of each image acquisition scenario. RMSE values for the uncalibrated elevation dataset were 26.613 m, 31.141 m, and 25.135 m for images acquired at 120 m, 80 m, and 40 m, respectively, using the Phantom 4 Pro UAS. With calibration for the same UAS, the accuracies were significantly improved with RMSE values of 0.161 m, 0.165, and 0.030 m, respectively. The best results showed an RMSE of 0.032 m and an R² of 0.998 for calibrated dataset generated using the Phantom 4 RTK UAS at 40m height. The accuracy of elevation determination decreased as the flight height increased for both UAS, with RMSE values greater than 0.160 m for the datasets acquired at 80 m and 160 m. The results of this study show that calibration with ground control panels improves the accuracy of elevation determination, especially for the UAS with a regular GPS receiver. The Phantom 4 Pro provides accurate elevation data with substantial surveyed ground control panels for the 40 m dataset. The Phantom 4 Pro RTK UAS provides accurate elevation at 40 m without calibration for practical precision agriculture applications. This study provides valuable information on selecting appropriate UAS and flight heights in determining elevation for precision agriculture applications.

Keywords: unmanned aerial system, elevation, precision agriculture, real-time kinematic (RTK)

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Authors: Anisul Islam

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The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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Authors: Bin Li, Mei Liu

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Arrival time information is a crucial component of advanced public transport system (APTS). The advertisement of arrival time at stops can help reduce the waiting time and anxiety of passengers, and improve the quality of service. In this research, an experiment was conducted to compare the performance on prediction accuracy and precision between the link-based and the path-based historical travel time based model with the automatic vehicle location (AVL) data collected from an actual bus route. The research results show that the path-based model is superior to the link-based model, and achieves the best improvement on peak hours.

Keywords: bus transit, arrival time prediction, link-based, path-based

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Authors: Adaour Mohamed Amine, Bachene Mohamed Sadek, Fortassi Mosaab, Siouda Wafaa

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Foot infections are responsible for a significant number of hospitalizations and amputations in diabetic patients. The objective of our study is to analyze and evaluate the management of diabetic foot in a surgical setting. A retrospective study was conducted based on a selected case of suspected diabetic foot infections of osteitis treated at the Mohamed Boudiaf hospital in Medea. The case was reiterated as a therapeutic charge, consisting of treating first the infection of the soft tissues, then the osteitis: biopsy after at least 15 days of cessation of antibiotic therapy. Successful treatment of osteitis was defined at the end of a follow-up period of complete wound healing, lack of bone resection/amputation surgery at the initial bone site during follow-up , Instead, biopsies are prescribed in the treatment of soft tissue infection. The mean duration of treatment for soft tissue infection was 2-3 weeks, the duration of the antibiotic-free window of therapy prior to bone biopsy was 2-4 weeks. This patient received medical management without surgical resection. The success rate for treating osteitis at one year was 73% and healing at one year was 88%.It is often limited to a sausage of the foot at the cost of repeated amputations. The best management remains prevention, which necessarily involves setting up a specialized and adapted centre.

Keywords: osteitis, antibiotic therapy, bone biopsy, diabetic foot

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Authors: Ibrahim Mahamid, A. Al-Ghonamy, M. Aichouni

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This study is conducted to identify causes of cost deviations in public construction projects in Saudi Arabia from contractors’ perspective. 41 factors that might affect cost estimating accuracy were identified through literature review and discussion with some construction experts. The factors were tabulated in a questionnaire form and a field survey included 51 contractors from the Northern Province of Saudi Arabia was performed. The results show that the top five important causes are: wrong estimation method, long period between design and time of implementation, cost of labor, cost of machinary and absence of construction-cost data.

Keywords: cost deviation, public construction, cost estimating, Saudi Arabia, contractors

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Authors: Alok Raghav, Jamal Ahmad

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Background: Serum albumin glycation and advanced glycation end products (AGE) formation correlates in diabetes and its associated complications. Extensive modified human serum albumin is used to study the biochemical, electrochemical and functional properties in hyperglycemic environment with relevance to diabetes. We evaluate Spectroscopic, side chain modifications, amino acid analysis, biochemical and functional group properties in four glucose modified samples. Methods: A series four human serum albumin samples modified with glucose was characterized in terms of amino acid analysis, spectroscopic properties and side chain modifications. The diagnostic technique employed incorporates UV Spectroscopy, Fluorescence Spectroscopy, biochemical assays for side chain modifications, amino acid estimations, electrochemical and optical characterstic of glycated albumin. Conclusion: Glucose modified human serum albumin confers AGEs formation alters biochemical, electrochemical, optical, and functional property that depend on the reactivity of glucose and its concentration used for in-vitro glycation. A biochemical, electrochemical, optical, and functional characterization of modified albumin in-vitro produced AGE product that will be useful to interpret the complications and pathophysiological significance in diabetes.

Keywords: human serum albumin, glycated albumin, adavanced glycation end products, associated pathologies

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Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: Johnson Oladele Fatokun, I. P. Akpan

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In this paper, the one-dimensional time dependent Schrödinger equation is discretized by the method of lines using a second order finite difference approximation to replace the second order spatial derivative. The evolving system of stiff ordinary differential equation (ODE) in time is solved numerically by an L-stable trapezoidal-like integrator. Results show accuracy of relative maximum error of order 10-4 in the interval of consideration. The performance of the method as compared to an existing scheme is considered favorable.

Keywords: Schrodinger’s equation, partial differential equations, method of lines (MOL), stiff ODE, trapezoidal-like integrator

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Authors: Anita, Sari Septiani Tangke, Rusdina Bte Ladju, Nasrum Massi

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New diagnostic tools are urgently needed to interrupt the transmission of tuberculosis and multidrug-resistant tuberculosis. The microscopic-observation drug-susceptibility (MODS) assay is a rapid, accurate and simple liquid culture method to detect multidrug-resistant tuberculosis (MDR-TB). MODS were evaluated to determine a lower and same concentration of isoniazid and rifampin for detection of MDR-TB. Direct drug-susceptibility testing was performed with the use of the MODS assay. Drug-sensitive control strains were tested daily. The drug concentrations that used for both isoniazid and rifampin were at the same concentration: 0.16, 0.08 and 0.04μg per milliliter. We tested 56 M. tuberculosis clinical isolates and the control strains M. tuberculosis H37RV. All concentration showed same result. Of 53 M. tuberculosis clinical isolates, 14 were MDR-TB, 38 were susceptible with isoniazid and rifampin, 1 was resistant with isoniazid only. Drug-susceptibility testing was performed with the use of the proportion method using Mycobacteria Growth Indicator Tube (MGIT) system as reference. The result of MODS assay using lower concentration was significance (P<0.001) compare with the reference methods. A lower and same concentration of isoniazid and rifampin can be used to detect MDR-TB. Operational cost and application can be more efficient and easier in resource-limited environments. However, additional studies evaluating the MODS using lower and same concentration of isoniazid and rifampin must be conducted with a larger number of clinical isolates.

Keywords: isoniazid, MODS assay, MDR-TB, rifampin

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

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Authors: Leili Iranirad, Mohammad Saleh Sadeghi, Seyed Fakhreddin Hejazi, Negar Vakili Razlighi

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Objective: Contrast-induced nephropathy (CIN) or contrast-induced acute kidney injury (CI-AKI) is an unknown acute kidney injury (AKI) occurring after exposure to contrast media (CM). Contrast agents are most often used for diagnostic procedures or therapeutic angiographic interventions. Recently, Na/K citrate as a urine alkalinization has been evaluated for the prevention of CIN. We conducted this experiment to evaluate the efficiency of Na/K citrate on CIN in high-risk patients treated with cardiac catheterization. Methods: A prospective randomized clinical trial was conducted on 400 patients having moderate to high-risk factors for CIN treated with elective percutaneous coronary intervention (PCI) and were assigned randomly to the control group or the Na/K citrate group. The Na/K citrate group (n=200) received 5 g Na/K citrate solution, which was diluted in 200 mL water two h before and four hours after the first administration and intravenous hydration for two h prior to and six h after the procedure, while the control group (n=200) only received intravenous hydration. Serum creatinine (SCr) was calculated prior to the contrast exposure and after 48 h. CIN was described as a 25% increase in creatinine of serum (SCr) or >0.5 mg/dl 48 h after contrast administration. Results: CIN was observed in 33 patients (16.5%) in the control group and in 6 patients (3%) in the Na/K citrate group. A significant variation was recorded in the CIN incidence between the two groups 48 h after the radiocontrast agent administration (p < 0.001). Conclusion: Our results show that Na/K citrate is useful and substantially reduces the incidence of CIN.

Keywords: contrast media, citrate, PCI

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Authors: Mehrshad Khosraviani, Faramarz Abbaspour Leyl Abadi

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The fundamental component of the computer network of modern information society will be considered. These networks are connected to the network of the internet generally. Due to the fact that the primary purpose of the Internet is not designed for, in recent decades, none of these networks in many of the attacks has been very important. Today, for the provision of security, different security tools and systems, including intrusion detection systems are used in the network. A common diagnosis system based on artificial immunity, the designer, the Adhasaz Foundation has been evaluated. The idea of using artificial safety methods in the diagnosis of abnormalities in computer networks it has been stimulated in the direction of their specificity, there are safety systems are similar to the common needs of m, that is non-diagnostic. For example, such methods can be used to detect any abnormalities, a variety of attacks, being memory, learning ability, and Khodtnzimi method of artificial immune algorithm pointed out. Diagnosis of the common system of education offered in this paper using only the normal samples is required for network and any additional data about the type of attacks is not. In the proposed system of positive selection and negative selection processes, selection of samples to create a distinction between the colony of normal attack is used. Copa real data collection on the evaluation of ij indicates the proposed system in the false alarm rate is often low compared to other ir methods and the detection rate is in the variations.

Keywords: artificial immune system, abnormality detection, intrusion detection, computer networks

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Authors: J. R. Ashrapov, G. A. Alihodzhaeva, D. E. Abdullaev, N. R. Kadirbekov

Abstract:

Diagnosis of brain tumors is one of the challenges, as several central nervous system diseases run the same symptoms. Modern diagnostic techniques such as CT, MRI helps to significantly improve the surgery in the operating period, after surgery, after allowing time to identify postoperative complications in neurosurgery. Purpose: To study the MRI characteristics and localization of brain tumors in children and to detect the postoperative complications in the postoperative period. Materials and methods: A retrospective study of treatment of 62 children with brain tumors in age from 2 to 5 years was performed. Results of the review: MRI scan of the brain of the 62 patients 52 (83.8%) case revealed a brain tumor. Distribution on MRI of brain tumors found in 15 (24.1%) - glioblastomas, 21 (33.8%) - astrocytomas, 7 (11.2%) - medulloblastomas, 9 (14.5%) - a tumor origin (craniopharyngiomas, chordoma of the skull base). MRI revealed the following characteristic features: an additional sign of the heterogeneous MRI signal of hyper and hypointensive T1 and T2 modes with a different perifocal swelling degree with involvement in the process of brain vessels. The main objectives of postoperative MRI study are the identification of early or late postoperative complications, evaluation of radical surgery, the identification of the extended-growing tumor that (in terms of 3-4 weeks). MRI performed in the following cases: 1. Suspicion of a hematoma (3 days or more) 2. Suspicion continued tumor growth (in terms of 3-4 weeks). Conclusions: Magnetic resonance tomography is a highly informative method of diagnostics of brain tumors in children. MRI also helps to determine the effectiveness and tactics of treatment and the follow up in the postoperative period.

Keywords: brain tumors, children, MRI, treatment

Procedia PDF Downloads 140

Authors: Morteza Esfandiari, Shabnam Jabari, Heather MacGrath, David Coleman

Abstract:

Flood is a severe issue in different places in the world as well as the city of Fredericton, New Brunswick, Canada. The downtown area of Fredericton is close to the Saint John River, which is susceptible to flood around May every year. Recently, the frequency of flooding seems to be increased, especially after the fact that the downtown area and surrounding urban/agricultural lands got flooded in two consecutive years in 2018 and 2019. In order to have an explicit vision of flood span and damage to affected areas, it is necessary to use either flood inundation modelling or satellite data. Due to contingent availability and weather dependency of optical satellites, and limited existing data for the high cost of hydrodynamic models, it is not always feasible to rely on these sources of data to generate quality flood maps after or during the catastrophe. Height Above the Nearest Drainage (HAND), a state-of-the-art topo-hydrological index, normalizes the height of a basin based on the relative elevation along with the stream network and specifies the gravitational or the relative drainage potential of an area. HAND is a relative height difference between the stream network and each cell on a Digital Terrain Model (DTM). The stream layer is provided through a multi-step, time-consuming process which does not always result in an optimal representation of the river centerline depending on the topographic complexity of that region. HAND is used in numerous case studies with quite acceptable and sometimes unexpected results because of natural and human-made features on the surface of the earth. Some of these features might cause a disturbance in the generated model, and consequently, the model might not be able to predict the flow simulation accurately. We propose to include a previously existing stream layer generated by the province of New Brunswick and benefit from culvert maps to improve the water flow simulation and accordingly the accuracy of HAND model. By considering these parameters in our processing, we were able to increase the accuracy of the model from nearly 74% to almost 92%. The improved model can be used for generating highly accurate flood maps, which is necessary for future urban planning and flood damage estimation without any need for satellite imagery or hydrodynamic computations.

Keywords: HAND, DTM, rapid floodplain, simplified conceptual models

Procedia PDF Downloads 146

Authors: Sevil Igit, Merve Meric, Sarp Erturk

Abstract:

In this paper, it is proposed to improve Daisy descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.

Keywords: face recognition, Daisy descriptor, One-Bit Transform, image registration

Procedia PDF Downloads 358