Search results for: statistical methods

Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 87

Authors: Behnam Tavakkol

Abstract:

Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.

Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data

Procedia PDF Downloads 215

Authors: Sayaka Ono, Ryutaro Imai, Tomoko Ehara, Tetsuya Matsumoto, Hajime Matsumura

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Background: Wound pH affects a number of important factors in wound healing. We previously measured the pH value of the exudates collected from second-degree burns and found that the increase in pH was observed in the burn wounds in which colonized by Staphylococcus spp., and the increase in pH was evident prior to the clinical findings of local infection. To investigate the relationship between the changes of pH value and bacterial growth, we performed in vitro study using Pseudomonas aeruginosa and liquid medium as a locally infected wound equivalent model. Methods: Pseudomonas aeruginosa standard strain (ATCCR 10145TM) was cultured at 37 °C environment in Luria Broth Miller medium. The absorbance rate which means the amount of bacteria was measured by a microplate reader 2300EnSpireTM). The pH was measured using pH-indicator strips (MColorpHastTM). The statistical analysis was performed using the product-moment correlation coefficient of Pearson's. Results: The absorbance rate and pH value were increased along with culture period. There was a positive correlation between pH value and absorbance rate (n = 27, Pearson's r = 0.985). Moreover, there was a positive correlation between pH value and the culture period (n = 18, Pearson's r = 0.901). The bacteria was well growth in the media from pH 6.6 to pH 8.0 and the pH of culture media converged at 8 -9 along with the bacterial growth. Conclusion: From these results, we conclude that pH value of the wound is correlated with the number of viable bacteria and bacterial growth periods.

Keywords: colonization, potential of hydrogen, Pseudomonas aeruginosa, wound

Procedia PDF Downloads 278

Authors: M. Crozet, D. Roudil, T. Branger, S. Boden, P. Peerani, B. Russell, M. Herranz, L. Aldave de la Heras

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The EURATOM work program project INSIDER (Improved Nuclear Site Characterization for Waste minimization in Decommissioning under Constrained Environment) was launched in June 2017. This 4-year project has 18 partners and aims at improving the management of contaminated materials arising from decommissioning and dismantling (D&D) operations by proposing an integrated methodology of characterization. This methodology is based on advanced statistical processing and modelling, coupled with adapted and innovative analytical and measurement methods, with respect to sustainability and economic objectives. In order to achieve these objectives, the approaches will be then applied to common case studies in the form of Inter-laboratory comparisons on matrix representative reference samples and benchmarking. Work Package 6 (WP6) ‘Performance analysis and overall uncertainty’ is in charge of the analysis of the benchmarking on real samples, the organisation of inter-laboratory comparison on synthetic certified reference materials and the establishment of overall uncertainty budget. Assessment of the outcome will be used for providing recommendations and guidance resulting in pre-standardization tests.

Keywords: decommissioning, sampling strategy, research and development, characterization, European project

Procedia PDF Downloads 362

Authors: Mohamed Taher Eldesoky, Enas Elsayed Abutaleb

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Background: The changes in foot posture possibly generate changes in the pelvic alignment, although, there is lack of evidence about the effects of bilateral and unilateral flatfoot on possible changes in pelvic alignment. The purpose of this study was to investigate the effect of flatfoot on the sagittal and frontal planes of pelvic postures. Materials and Methods: 56 subjects, aged 18–40 years, were assigned into three groups. 20 healthy subjects, 19 subjects with bilateral flexible second-degree flat foot, and 17 subjects with unilateral flexible second-degree flat foot. 3D assessment of the pelvis using the formetric-II device was used to evaluate pelvic alignment in the frontal and sagittal planes by measuring pelvic inclination and pelvic tilt angles. Results: ANOVA test with LSD test were used for statistical analysis. Both Unilateral and bilateral second degree flatfoot produced significant (P < 0.05) pelvic anteversion in comparison to the healthy subjects (P < 0.05), but the bilateral flatfoot subjects seemed to have more anteversion than the unilateral subjects. Unilateral flatfoot caused a significant (P<0.05) lateral pelvic tilt in the direction of the affected side in comparison to the healthy and bilateral flatfoot subjects. Conclusion: The bilateral and unilateral second degree flatfoot changed pelvic alignment. Both of them led to increases of pelvic anteversion while the unilateral one caused lateral pelvic tilt toward the affected side. Thus, foot posture should be considered when assessing patients with pelvic misalignment and disorders.

Keywords: bilateral flatfoot, unilateral flatfoot, pelvic alignment, foot posture

Procedia PDF Downloads 360

Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang

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In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.

Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning

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Authors: Orkide Donma, Mustafa M. Donma

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Morbid obesity is a health threatening condition particularly in children. Generally, it leads to the development of metabolic syndrome (MetS) characterized by central obesity, elevated fasting blood glucose (FBG), triglyceride (TRG), blood pressure values and suppressed high density lipoprotein cholesterol (HDL-C) levels. However, some ambiguities exist during the diagnosis of MetS in children below 10 years of age. Therefore, clinicians are in the need of some surrogate markers for the laboratory assessment of pediatric MetS. In this study, the aim is to develop an index, which will be more helpful during the evaluation of further risks detected in morbid obese (MO) children. A total of 235 children with normal body mass index (N-BMI), with varying degrees of obesity; overweight (OW), obese (OB), MO as well as MetS participated in this study. The study was approved by the Institutional Ethical Committee. Informed consent forms were obtained from the parents of the children. Obesity states of the children were classified using BMI percentiles adjusted for age and sex. For the purpose, tabulated data prepared by WHO were used. MetS criteria were defined. Systolic and diastolic blood pressure values were measured. Parameters related to glucose and lipid metabolisms were determined. FBG, insulin (INS), HDL-C, TRG concentrations were determined. Diagnostic Obesity Notation Model Assessment Laboratory (DONMA_LAB) Index [ln TRG/HDL-C*INS] was introduced. Commonly used insulin resistance (IR) indices such as Homeostatic Model Assessment for IR (HOMA-IR) as well as ratios such as TRG/HDL-C, TRG/HDL-C*INS, HDL-C/TRG*INS, TRG/HDL-C*INS/FBG, log, and ln versions of these ratios were calculated. Results were interpreted using statistical package program (SPSS Version 16.0) for Windows. The data were evaluated using appropriate statistical tests. The degree for statistical significance was defined as 0.05. 35 N, 20 OW, 47 OB, 97 MO children and 36 with MetS were investigated. Mean ± SD values of TRG/HDL-C were 1.27 ± 0.69, 1.86 ± 1.08, 2.15 ± 1.22, 2.48 ± 2.35 and 4.61 ± 3.92 for N, OW, OB, MO and MetS children, respectively. Corresponding values for the DONMA_LAB index were 2.17 ± 1.07, 3.01 ± 0.94, 3.41 ± 0.93, 3.43 ± 1.08 and 4.32 ± 1.00. TRG/HDL-C ratio significantly differed between N and MetS groups. On the other hand, DONMA_LAB index exhibited statistically significant differences between N and all the other groups except the OW group. This index was capable of discriminating MO children from those with MetS. Statistically significant elevations were detected in MO children with MetS (p < 0.05). Multiple parameters are commonly used during the assessment of MetS. Upon evaluation of the values obtained for N, OW, OB, MO groups and for MO children with MetS, the [ln TRG/HDL-C*INS] value was unique in discriminating children with MetS.

Keywords: children, index, laboratory, metabolic syndrome, obesity

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Authors: O. Acan, Y. Keskin

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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.

Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method

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Authors: Praveena Sinha

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Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

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Authors: Ugbajah Maryjane

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The study examined the production of grass cutter and the constraints in Anambra state, Nigeria. Specifically, it described socio-economic characteristics of the respondents, determinants of net farm income and constraints to grass cutter production. Multistage and random sampling methods were used to select 50 respondents for this study. Primary data were collected by means of structured questionnaire. Non-parametric and parametric statistical tools including frequency percentage mean ranking counts, cost and returns and returns and multiple regression were deployed for data analysis. Majority 84% produce on small scale, 64 % had formal education 68% had 3-4 years of farming experience hence small scaled production were common. The income (returns) on investment was used as index of profitability, gross margin (#5,972,280), net farm income (#5,327,055.2) net return on investment (2.5) and return on investment 3.1. Net farm income was significantly influence by stock size and years of farming experience. Grass cutter farmers production problem would be ameliorated by the expression of extension education awareness campaigns to discourage unhealthy practices such as indiscriminant bush burning, use of toxic chemicals as baits, and provision of credits to the farmers.

Keywords: socio-economic factors, profitability, awareness, toxic chemicals, credits

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

Procedia PDF Downloads 127

Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

Procedia PDF Downloads 108

Authors: Asma Dill

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The aim of this study is to explore the role of HRM practices in SMEs success. The role of HRM practices in large enterprises is relatively known, on the other hand, small and medium enterprises (SMEs) companies have not been greatly studied in relation to the HRM practices in the past. Although, there is a lack of literature and empirical research in this area, several studies in the recent years emphasized on the importance of the HRM practices for the success of the SMEs. This study finds out relationship of HRM practices and SMESs performances. The objective is to analyze significant impacts of HRM practices (training, performance appraisal, compensation and employee development) on SMEs success, to determine whether SMEs recognize the importance of HRM practices in their businesses. To carry out this research a survey research strategy was followed. The sample frame for this study consisted of firms that belong to the services and commerce sector, employing at least 50 employees. The final research sample consisted of questionnaires. Descriptive statistical methods have been used during quantitative analysis to explore the relations. The findings of the study revealed that HRM practices have a significant influence on the performance of SMEs, and the better the HRM practice, the higher the performance of the SMEs. HRM practices, including, training, compensation, performance appraisal and employee development, have been found to be significantly and positively related to business success. Outcome of the study will provide useful guidelines to the business organizations. This study contributes to knowledge by providing insights on the impact of HRM practices on SMEs performance.

Keywords: compensation, employee performance, HRM practices, training

Procedia PDF Downloads 176

Authors: Michael A. Kraus, Navid Pourmoghaddam, Martin Botz, Jens Schneider, Geralt Siebert

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Fragmentation analysis of tempered glass gives insight into the quality of the tempering process and defines a certain degree of safety as well. Different standard such as the European EN 12150-1 or the American ASTM C 1048/CPSC 16 CFR 1201 define a minimum number of fragments required for soda-lime safety glass on the basis of fragmentation test results for classification. This work presents an approach for the glass breakage pattern prediction using a Voronoi Tesselation over Random Fields. The random Voronoi tessellation is trained with and validated against data from several breakage patterns. The fragments in observation areas of 50 mm x 50 mm were used for training and validation. All glass specimen used in this study were commercially available soda-lime glasses at three different thicknesses levels of 4 mm, 8 mm and 12 mm. The results of this work form a Bayesian framework for the training and prediction of breakage patterns of tempered soda-lime glass using a Voronoi Random Field Tesselation. Uncertainties occurring in this process can be well quantified, and several statistical measures of the pattern can be preservation with this method. Within this work it was found, that different Random Fields as basis for the Voronoi Tesselation lead to differently well fitted statistical properties of the glass breakage patterns. As the methodology is derived and kept general, the framework could be also applied to other random tesselations and crack pattern modelling purposes.

Keywords: glass breakage predicition, Voronoi Random Field Tessellation, fragmentation analysis, Bayesian parameter identification

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.

Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Leonor Varandas, Pedro D. Gaspar, Martim L. Aguiar

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One of the biggest concerns in the field of agriculture is around the energy efficiency of robots that will perform agriculture’s activity and their charging methods. In this paper, two different charging methods for agricultural standalone docking stations are shown that will take into account various variants as field size and its irregularities, work’s nature to which the robot will perform, deadlines that have to be respected, among others. Its features also are dependent on the orchard, season, battery type and its technical specifications and cost. First charging base method focuses on wireless charging, presenting more benefits for small field. The second charging base method relies on battery replacement being more suitable for large fields, thus avoiding the robot stop for recharge. Existing many methods to charge a battery, the CC CV was considered the most appropriate for either simplicity or effectiveness. The choice of the battery for agricultural purposes is if most importance. While the most common battery used is Li-ion battery, this study also discusses the use of graphene-based new type of batteries with 45% over capacity to the Li-ion one. A Battery Management Systems (BMS) is applied for battery balancing. All these approaches combined showed to be a promising method to improve a lot of technical agricultural work, not just in terms of plantation and harvesting but also about every technique to prevent harmful events like plagues and weeds or even to reduce crop time and cost.

Keywords: agricultural mobile robot, charging methods, battery replacement method, wireless charging method

Procedia PDF Downloads 147

Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Munirah Alaboudi

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This paper discusses a research project carried out with 12 first-year graduate students enrolled in research methods course prior to undertaking a graduate thesis during the academic year 2019. The research was designed for the objective of creating research methods course structure that embraces an individualized and activity-based approach to learning in a highly engaging group environment. This approach targeted innovating the traditional research methods lecture-based, theoretical format where students reported less engagement and limited learning. This study utilized action research methodology in developing a different approach to research methods course instruction where student performance indicators and feedback were periodically collected to assess the new teaching method. Student learning was achieved through utilizing the flipped classroom approach where students learned the material at home and classroom activities were designed to implement and experiment with the newly acquired information, with the guidance of the course instructor. Student learning in class was practiced through a series of activities based on different research methods. With the goal of encouraging student engagement, a wide range of activities was utilized including workshops, role play, mind-mapping, presentations, peer evaluations. Data was collected through an open-ended qualitative questionnaire to establish whether students were engaged in the material they were learning, and to what degree were they engaged, and to test their mastery level of the concepts discussed. Analysis of the data presented positive results as around 91% of the students reported feeling more engaged with the active learning experience and learning research by “actually doing research, not just reading about it”. The students expressed feeling invested in the process of their learning as they saw their research “gradually come to life” through peer learning and practice during workshops. Based on the results of this study, the research methods course structure was successfully remodeled and continues to be delivered.

Keywords: research methods, higher education instruction, flipped classroom, graduate education

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Authors: Fadi Awawdeh

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In this work, we highlight the key concepts in using semigroup theory as a methodology used to construct efficient formulas for solving inverse problems. The proposed method depends on some results concerning integral equations. The experimental results show the potential and limitations of the method and imply directions for future work.

Keywords: identification problems, semigroup theory, methods for inverse problems, scientific computing

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Authors: Klaudia Chmielewska, Krystyna Dzierzbicka, Iwona Inkielewicz-Stepniak

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Carnosine, an endogenous peptide consisting of β-alanine and L-histidine has a variety of functions to mention: antioxidant, antiglycation, and reducing the toxicity of metal ions. It has therefore been proposed to act as a therapeutic agent for many pathological states, although its therapeutic index is limited by quick enzymatic cleavage. To overcome this limitation, there’s an urge to create new derivatives which might become less potent to hydrolysis, while preserving the therapeutic effect. The poster summarizes the efficiency of two peptide synthesis methods, which were: (1) the mixed anhydride with isobutyl chloroformate and N-methylmorpholine (NMM) and (2) carbodiimide - mediated coupling method via appropriate reagent condensing, here – CDI. The methods were used to obtain dipeptides which were the derivatives of carnosine. Obtained dipeptides were made in the form of methyl esters and their structures will be confirmed 1H NMR, 13C NMR, MS and elemental analysis techniques. Later on, they will be analyzed for their antioxidant properties, in comparison to carnosine.

Keywords: carnosine, method, peptide, synthesis

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Authors: Fatemeh Rezaei, Afsaneh Amouei, Iman Bakouei, Mahdi Sharif, Shahabeddin Sarvi, Mohammad Taghi Rahimi, Ahmad Daryani

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Background: Rodents act as reservoir host and important potential source for many zoonotic pathogens which pose a public health risk to humans. Therefore, it is necessary to investigate the prevalence of gastrointestinal and ectoparasites among rodents. Materials and Methods: 118 Rattus rattus were captured using snap live traps. Each rat was combed with a fine tooth comb to dislodge ectoparasite and studied. Various samples were collected from feces, examined wet smear, formalin-ether method and stained with modified acid-fast staining and trichrome. Result: The overall prevalence of gastrointestinal parasites of examined rats was 75.4%. Cryptosporidium 30.5%, was the most prevalent protozoan which was followed by Giardia 20.3% and Entamoeba muris 13.5%, Trichomonas muris 10.1% and Spironucleus muris 3.3%. The prevalence of helminth egg was as following Syphacia obvelata 24.5%, Hymenolepis diminuta 10.1% and Trichuris muris 9.3%. 86.4% rodents were found to be infested with ectoparasites including mite 35.6%, flea 28.4%, and lice 42.7%. A significant statistical difference was observed between prevalence and gender of infected individuals. Conclusions: The prevalence of gastrointestinal and ectoparasites of collected rats in studied area is remarkably high. In addition, Rattus rattus can be considered as potential risk for human health.

Keywords: prevalence, rodent, intestinal parasites, ecto-parasites, zoonose

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Authors: Muhammad Ridho Fakhrin, Leni Sagita Riantini, Yusuf Latief

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Based on the 2015-2019 RPJMN data, the realization of toll road infrastructure development in Indonesia experienced a delay of 49% or 904 km of the total plan. One of the major causes of delays in development is caused by institutional factors. The case study taken in this research is the construction of the Trans Sumatra Toll Road (JTTS). The purpose of this research is to identify the institutional forms, functions, roles, duties, and responsibilities of each stakeholder and the risks that occur in the Trans Sumatra Toll Road Infrastructure Development. Risk analysis is implemented on functions, roles, duties, responsibilities of each existing stakeholder and is carried out at the Funding Stage, Technical Planning Stage, and Construction Implementation Stage in JTTS. This research is conducted by collecting data through a questionnaire survey, then processed using statistical methods, such as homogeneity, data adequacy, validity, and reliability test, continued with risk assessment based on a risk matrix. The results of this study are the evaluation and development of institutional functions in risk-based JTTS development can improve time performance and minimize delays in the construction process.

Keywords: institutional, risk management, time performance, toll road

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Authors: P. O. Ughachukwu, P. O. Okonkwo, P. C. Unekwe, J. O. Ogamba

Abstract:

Background: The prevalence of hepatitis B viral infection is high worldwide with liver cirrhosis and hepatocellular carcinoma as important complications. Cases of poor antibody response to hepatitis B vaccination abound. Immunosuppression, especially from glucocorticoids, is often cited as a cause of poor antibody response and there are documented evidences of irrational administration of glucocorticoids to children and adults. The study was, therefore, designed to find out if administration of glucocorticoids affects immune response to vaccination against hepatitis B in mice. Methods: Mice of both sexes were randomly divided into 2 groups. Daily intramuscular methylprednisolone injections, (15 mg kg-1), were given to the test group while sterile deionized water (0.1ml) was given to control mice for 30 days. On day 6 all mice were given 2 μg (0.1ml) hepatitis B vaccine and a booster dose on day 27. On day 34, blood samples were collected and analyzed for anti-HBs titres using enzyme-linked immunosorbent assay (ELISA). Statistical analysis was done using Graph Pad Prism 5.0 and the results taken as statistically significant at p value < 0.05. Results: There were positive serum anti-HBs responses in all mice groups but the differences in titres were not statistically significant. Conclusions: At the dosages and length of exposure used in this study, methylprednisolone injection did not significantly inhibit anti-HBs response in mice following immunization against hepatitis B virus. By extrapolation, methylprednisolone, when used in the usual clinical doses and duration of therapy, is not likely to inhibit immune response to hepatitis B vaccinations in man.

Keywords: anti-HBs, hepatitis B vaccine, immune response, methylprednisolone, mice

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Authors: Nicolas Zufferey

Abstract:

Ant algorithms are well-known metaheuristics which have been widely used since two decades. In most of the literature, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. Generally, at each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (also called the visibility, the short term profit or the heuristic information) and the trail system (central memory which collects historical information of the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed, namely SMART (for Solution Methods with Ants Running by Types). It relies on the use of different population of ants, where each population has its own personality.

Keywords: ant algorithms, evolutionary procedures, metaheuristics, optimization, population-based methods

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Authors: Taleb L., Benarbia M., Brahmi M., Belmiloud H., Boukerche A.

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Introduction and purpose of the study: Cavum cancer in children and adolescents is rare and represents 8% of all nasopharyngeal cancers treated in our department. Our objective is to study its epidemiological, clinical, therapeutic, and evolutionary particularities. Material and methods: Retrospective study of 39 patients under 20 years old, treated for undifferentiated non-metastatic carcinoma of the nasopharynx at the Emir Abdelkader Cancer Center between 2014 and 2020. Results and statistical analysis: Median age was 14 years [7-19 years], with a sex ratio of 2.9. The median time to diagnosis was 5.6 months [1 to 14 months], the circumstances of the discovery of which were dominated by lymph node syndrome in 43.6% of cases (n=17) followed by a rhinological syndrome in 30.8% of cases (n=13). The tumor stage was T1 for two patients (5.1%), T2 for 8 (20.5%), T3 for 9 (23.1%), T4 for 20 (51.3%), N0 for 2 (5 .1%) N1 for 4 (10.3%), N2 for 28 (71.8%) and N3 for 5 (12.8%). All patients received induction chemotherapy followed by concomitant radiotherapy with cisplatin. The dose of irradiation delivered to the cavum and adenopathies was 66 Gy with fractionation of 2 Gy per session in 69.2% of cases (n=27) and 1.8 Gy in 30.8% of cases (n=12). With a median follow-up of 51 months (15 to 97 months), the locoregional, metastatic, specific, and overall relapse-free survival rates at five years were 91.1%, 73.5%, 66.1%, and 68.4, respectively. Conclusion: Chemotherapy and radiotherapy treatment of cavum cancer in children and adolescents has allowed excellent locoregional control despite the advanced stage of the disease. However, the frequency of metastatic relapses could justify the possible use of systemic maintenance treatment.

Keywords: cancer, nasopharynx, radiotherapy, chemotherapy, survival

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Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: V. Verma, Syed Riyaz-ul-Hassan

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Staphylococcus aureus is one of the most commonly found pathogenic bacteria and is hard to eliminate from the human environment. It is responsible for many nosocomial infections, besides being the main causative agent of food intoxication by virtue of its variety of enterotoxins. Routine detection of S. aureus in food is usually carried out by traditional methods based on morphological and biochemical characterization. These methods are time-consuming and tedious. In addition, misclassifications with automated susceptibility testing systems or commercially available latex agglutination kits have been reported by several workers. Consequently, there is a need for methods to specifically discriminate S. aureus from other staphylococci as quickly as possible. Data on protocols developed using molecular means like PCR technology will be presented for rapid and specific detection of this pathogen in food, clinical and environmental samples, especially milk.

Keywords: food Pathogens, PCR technology, rapid and specific detection, staphylococcus aureus

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Authors: Ilaria Lucrezia Amerise

Abstract:

The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: generalized extreme values, likelihood estimation, precipitation data, Wakeby distribution

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

Abstract:

Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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