Search results for: time series data mining

Authors: Shieh Shiow-fang

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Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interview to collect their experiences about sport superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awareness, learning norms, competitive athlete

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Authors: Rahim Shahrokhi, Junboum Park

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Per- and Polyfluoroalkyl Substances (PFASs) are environmentally persistent halogenated hydrocarbons that have been widely used in many industrial and commercial applications. Recently, contaminating the soil and groundwater due to the ubiquity of PFAS in environments has raised great concern. Adsorption technology is one of the most promising methods for PFAS removal. Chitosan is a biopolymer substance with abundant amine and hydroxyl functional groups, which render it a good adsorbent. This study has tried to enhance the adsorption capacity of chitosan by grafting more amine functional groups on its surface for the removal of two long (PFOA and PFOS) and two short-chain (PFBA, PFBS) PFAS substances from the aqueous phase. A series of batch adsorption tests have been performed to evaluate the adsorption capacity of the used sorbent. Also, the sorbent was analyzed by SEM, FT-IR, zeta potential, and XRD tests. The results demonstrated that both chitosan beads have good potential for adsorbing short and long-chain PFAS from the aqueous phase.

Keywords: PFAS, chitosan beads, adsorption, grafted chitosan

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

Procedia PDF Downloads 238

Authors: Wilfred Jeyatheese Jeyaraj

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Education is a key determinant of future success, and every person deserves non-discriminant access to information for educational inevitabilities in any case. Analysing and understanding complex information is a crucial learning tool, especially for students. In order to compete equally with sighted students, visually impaired students require the unhinged access to access to all the available information resources. When the education of visually impaired students comes to a focal point, it can be stated that visually impaired students encounter several obstacles and barriers before they enter the university and during their time there as students. These obstacles and barriers are spread across technical, organizational and social arenas. This study reveals the possible approaches to absorb and benefit from the information provided by the Sri Lankan University Libraries for visually impaired students. Purposive sampling technique was used to select sample visually impaired students attached to the Sri Lankan National universities. There are 07 National universities which accommodate the visually impaired students and with the identified data, they were selected for this study and 80 visually impaired students were selected as the sample group. Descriptive type survey method was used to collect data. Structured questionnaires, interviews and direct observation were used as research instruments. As far as the Sri Lankan context spread is concerned, visually impaired students are able to finish their courses through their own determination to overcome the barriers they encounter on their way to graduation, through moral and practical support from their own friends and very often through a high level of creativity. According to the findings there are no specially trained university librarians to serve visually impaired users and less number of assistive technology equipment are available at present. This paper enables all university libraries in Sri Lanka to be informed about the social isolation of visually compromised students at the Sri Lankan universities and focuses on the rectification issues by considering their distinct case for interaction.

Keywords: information access, Sri Lanka, university libraries, visual impairment

Procedia PDF Downloads 222

Authors: Maria Korman, Carmit Gal, Ella Gabitov, Avi Karni

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The main question addressed in this study was whether the time-of-day wherein training is afforded is a significant factor for motor skill ('how-to', procedural knowledge) acquisition and consolidation into long term memory in the healthy elderly population. Twenty-nine older adults (60-75 years) practiced an explicitly instructed 5-element key-press sequence by repeatedly generating the sequence ‘as fast and accurately as possible’. Contribution of three parameters to acquisition, 24h post-training consolidation, and 1-week retention gains in motor sequence speed was assessed: (a) time of training (morning vs. evening group) (b) sleep quality (actigraphy) and (c) chronotype. All study participants were moderately morning type, according to the Morningness-Eveningness Questionnaire score. All participants had sleep patterns typical of age, with average sleep efficiency of ~ 82%, and approximately 6 hours of sleep. Speed of motor sequence performance in both groups improved to a similar extent during training session. Nevertheless, evening group expressed small but significant overnight consolidation phase gains, while morning group showed only maintenance of performance level attained at the end of training. By 1-week retention test, both groups showed similar performance levels with no significant gains or losses with respect to 24h test. Changes in the tapping patterns at 24h and 1-week post-training were assessed based on normalized Pearson correlation coefficients using the Fisher’s z-transformation in reference to the tapping pattern attained at the end of the training. Significant differences between the groups were found: the evening group showed larger changes in tapping patterns across the consolidation and retention windows. Our results show that morning-oriented older adults effectively acquired, consolidated, and maintained a new sequence of finger movements, following both morning and evening practice sessions. However, time-of-training affected the time-course of skill evolution in terms of performance speed, as well as the re-organization of tapping patterns during the consolidation period. These results are in line with the notion that motor training preceding a sleep interval may be beneficial for the long-term memory in the elderly. Evening training should be considered an appropriate time window for motor skill learning in older adults, even in individuals with morning chronotype.

Keywords: time-of-day, elderly, motor learning, memory consolidation, chronotype

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

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This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script which is a series of texts including directions and dialogues. The other is blogposts which possesses relatively abstracted contents, stories and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. In order to improve the quality of topics, it needs a method to consider the word difference. In this paper, we introduce a semantic vocabulary expansion method to solve the word difference. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can learn more salient topics for broadcasting contents.

Keywords: broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec

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Authors: Mishell Vaca, Gema Gonzales, Francisco Quiroz

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Heavy metals present in wastewater constitute a danger for living beings in general. In Ecuador, one of the sources of contamination is artisanal mining whose liquid effluents, in many of the cases without prior treatment, are discharged to the surrounding rivers. Lead is a pollutant that accumulated in the body causes severe health effects. Nowadays, there are several treatment methods to reduce this pollutant. The aim of this study is to reduce the concentration of lead II through the use of a porous material formed by a matrix of chitosan, in which hydroxyapatite and moringa particles smaller than 53 um are suspended. These materials are not toxic to the environment, and each one adsorbs metals independently, so the synergic effect between them will be evaluated. The synthesized material has a cylindrical design that allows increasing the surface area, which is expected to have greater capacity of adsorption. It has been determined that the best conditions for its preparation are to dissolve the chitosan in 1% v/v acetic acid with a pH = 5, then the hydroxyapatite and moringa are added to the mixture with magnetic stirring. This suspension is frozen, lyophilized and finally dried. In order to evaluate the performance of the synthesized material, synthetic solutions of lead are prepared at different concentrations, and the percentage of removal is evaluated. It is expected to have an effluent whose lead content is less than 0.2 mg/L which is the limit maximum allowable according to established environmental standards.

Keywords: adsorption, chitosan, hydroxyapatite, lead, moringa, water treatment

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Authors: Laroussi Chaabane, Amel El Ghali, Emmanuel Beyou, Mohamed Hassen V. Baouab

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In this research, the functionalization of graphene oxide sheets by ethylenediamine (EDA) was accomplished and followed by the grafting of bis(2-pyridylmethyl) amino group (BPED) onto the activated graphene oxide sheets in the presence of chloroacetylchloride (CAC) and then combined with magnetic nanoparticles (Fe₃O₄NPs) to produce a magnetic graphene-based composite [(Go-EDA-CAC)@Fe₃O₄NPs-BPED]. The physicochemical properties of [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] composites were investigated by Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA). Additionally, the catalysts can be easily recycled within ten seconds by using an external magnetic field. Moreover, [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] was used for removing Cu(II) ions from aqueous solutions using a batch process. The effect of pH, contact time and temperature on the metal ions adsorption were investigated, however weakly dependent on ionic strength. The maximum adsorption capacity values of Cu(II) on the [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] at the pH of 6 is 3.46 mmol.g⁻¹. To examine the underlying mechanism of the adsorption process, pseudo-first, pseudo-second-order, and intraparticle diffusion models were fitted to experimental kinetic data. Results showed that the pseudo-second-order equation was appropriate to describe the Cu (II) adsorption by [(Go-EDA-CAC)@Fe₃O₄NPs-BPED]. Adsorption data were further analyzed by the Langmuir, Freundlich, and Jossens adsorption approaches. Additionally, the adsorption properties of the [(Go-EDA-CAC)@Fe₃O₄NPs-BPED], their reusability (more than 6 cycles) and durability in the aqueous solutions open the path to removal of Cu(II) from water solution. Based on the results obtained, we report the activity of Cu(II) supported on [(Go-EDA-CAC)@Fe₃O₄NPs-BPED] as a catalyst for the cross-coupling of symmetric alkynes.

Keywords: graphene, magnetic nanoparticles, adsorption kinetics/isotherms, cross coupling

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: Hyery Kang, Dong-Yeun Koh, Yun-Ho Ahn, Huen Lee

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Determination of the behavior of clathrate hydrate with inhibitor in the THz region will provide useful information about hydrate plug control in the upstream of the oil and gas industry. In this study, terahertz time-domain spectroscopy (THz-TDS) revealed the inhibition of the THF clathrate hydrate system with dosage of polyvinylpyrrolidone (PVP) with three different molecular weights. Distinct footprints of phase transition in the THz region (0.4–2.2 THz) were analyzed and absorption coefficients and real part of refractive indices are obtained in the temperature range of 253 K to 288 K. Along with the optical properties, ring breathing and stretching modes for different molecular weights of PVP in THF hydrate are analyzed by Raman spectroscopy.

Keywords: clathrate hydrate, terahertz spectroscopy, tetrahydrofuran, inhibitor

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Authors: Ravi Kiran Jaladi, Ezz I. El-Masry

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Emerging technologies such as ultra-wide band wireless access technology that operate at ultra-low power present several challenges due to their inherent design that limits the use of voltage-mode filters. Therefore, Continuous-time current-mode (CTCM) filters have become very popular in recent times due to the fact they have a wider dynamic range, improved linearity, and extended bandwidth compared to their voltage-mode counterparts. The goal of this research is to develop analog filters which are suitable for the current scaling CMOS technologies. Bulk-driven MOSFET is one of the most popular low power design technique for the existing challenges, while other techniques have obvious shortcomings. In this work, a CTCM Gate-driven (GD) differentiator has been presented with a frequency range from dc to 100MHz which operates at very low supply voltage of 0.7 volts. A novel CTCM Bulk-driven (BD) differentiator has been designed for the first time which reduces the power consumption multiple times that of GD differentiator. These GD and BD differentiator has been simulated using CADENCE TSMC 65nm technology for all the bilinear and biquadratic band-pass frequency responses. These basic building blocks can be used to implement the higher order filters. A 6th order cascade CTCM Chebyshev band-pass filter has been designed using the GD and BD techniques. As a conclusion, a low power GD and BD 6th order chebyshev stagger-tuned band-pass filter was simulated and all the parameters obtained from all the resulting realizations are analyzed and compared. Monte Carlo analysis is performed for both the 6th order filters and the results of sensitivity analysis are presented.

Keywords: bulk-driven (BD), continuous-time current-mode filters (CTCM), gate-driven (GD)

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Authors: İkbal Eski

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This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

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Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

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This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

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Authors: Haythem Barrak, Gaetan Laroche, Adel M’nif, Ahmed Hichem Hamzaoui

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The use of semiconductor oxides, as chemical or biological, requires their functionalization with appropriate dependent molecules of the substance to be detected. generally, the support materials used are TiO2 and SiO2. In the present work, we used zinc oxide (ZnO) known for its interesting physical properties. The synthesis of nano scale ZnO was performed by co-precipitation at low temperature (60 ° C).To our knowledge, the obtaining of this material at this temperature was carried out for the first time. This shows the low cost of this operation. On the other hand, the surface functionalization of ZnO was performed with (3-aminopropyl) triethoxysilane (APTES) by using a specific method using ethanol for the first time. In addition, the duration of this stage is very low compared to literature. The samples obtained were analyzed by XRD, TEM, DLS, FTIR, and TGA shows that XPS that the operation of grafting of APTES on our support was carried out with success.

Keywords: functionalization, nanoparticle, ZnO, APTES, caractérisation

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: Farhina Haque, Chanyeop Park

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The high efficiency, high field, and high power density provided by wide bandgap (WBG) semiconductors and advanced power electronic converter (PEC) topologies enabled the dynamic control of power in medium to high voltage systems. Although WBG semiconductors outperform the conventional Silicon based devices in terms of voltage rating, switching speed, and efficiency, the increased voltage handling properties, high dv/dt, and compact device packaging increase local electric fields, which are the main causes of partial discharge (PD) in the advanced medium and high voltage applications. PD, which occurs actively in voids, triple points, and airgaps, is an inevitable dielectric challenge that causes insulation and device aging. The aging process accelerates over time and eventually leads to the complete failure of the applications. Hence, it is critical to mitigating PD. Sharp edges, airgaps, triple points, and bubbles are common defects that exist in any medium to high voltage device. The defects are created during the manufacturing processes of the devices and are prone to high-electric-field-induced PD due to the low permittivity and low breakdown strength of the gaseous medium filling the defects. A contemporary approach of mitigating PD by neutralizing electric fields in high power density applications is introduced in this study. To neutralize the locally enhanced electric fields that occur around the triple points, airgaps, sharp edges, and bubbles, electrets are developed and incorporated into high voltage applications. Electrets are electric fields emitting dielectric materials that are embedded with electrical charges on the surface and in bulk. In this study, electrets are fabricated by electrically charging polyvinylidene difluoride (PVDF) films based on the widely used triode corona discharge method. To investigate the PD mitigation performance of the fabricated electret films, a series of PD experiments are conducted on both the charged and uncharged PVDF films under square voltage stimuli that represent PWM waveform. In addition to the use of single layer electrets, multiple layers of electrets are also experimented with to mitigate PD caused by higher system voltages. The electret-based approach shows great promise in mitigating PD by neutralizing the local electric field. The results of the PD measurements suggest that the development of an ultimate solution to the decades-long dielectric challenge would be possible with further developments in the fabrication process of electrets.

Keywords: electrets, high power density, partial discharge, triode corona discharge

Procedia PDF Downloads 191

Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: Armanul Hoque Shaon, Md Baizid Mahmud, Askander Nobi, Md. Raju Ahmed, Md. Jiabul Hoque

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In the Internet of Things (IoT), devices are linked to the internet through a wireless network, allowing them to collect and transmit data without the need for a human operator. Agriculture relies heavily on wireless sensors, which are a vital component of the Internet of Things (IoT). This kind of wireless sensor network monitors physical or environmental variables like temperatures, sound, vibration, pressure, or motion without relying on a central location or sink and collaboratively passes its data across the network to be analyzed. As the primary source of plant nutrients, the soil is critical to the agricultural industry's continued growth. We're excited about the prospect of developing an Internet of Things (IoT) solution. To arrange the network, the sink node collects groundwater levels and sends them to the Gateway, which centralizes the data and forwards it to the sensor nodes. The sink node gathers soil moisture data, transmits the mean to the Gateways, and then forwards it to the website for dissemination. The web server is in charge of storing and presenting the moisture in the soil data to the web application's users. Soil characteristics may be collected using a networked method that we developed to improve rice production. Paddy land is running out as the population of our nation grows. The success of this project will be dependent on the appropriate use of the existing land base.

Keywords: IoT based agriculture monitoring, intelligent irrigation, communicating network, rice production

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Authors: V. Benedico, C. Anacleto, A. Bearzi, L. Brice, V. Delahaye

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The aim in present paper is to construct an affordable and reliable commodity prices based on a recalculation of its cost through time which allows visualize the potential risks and thus, take more appropriate decisions regarding forecasts. Here attention has been focused on Levy model, more reliable and realistic than classical random Gaussian one as it takes into consideration observed abrupt jumps in case of sudden price variation. In application to Energy Trading sector where it has never been used before, equations corresponding to Levy model have been written for electricity pricing in European market. Parameters have been set in order to predict and simulate the price and its evolution through time to remarkable accuracy. As predicted by Levy model, the results show significant spikes which reach unconventional levels contrary to currently used Brownian model.

Keywords: commodity pricing, Lévy Model, price spikes, electricity market

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Authors: F. A. Saracoglu Varol, H. Agaccıoglu

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Experimental studies to investigate the depth of the scour conducted at a side-weir intersection located at the 1800 curved flume which located Hydraulic Laboratory of Yıldız Technical University, Istanbul, Turkey. Side weirs were located at the middle of the straight part of the main channel. Three different lengths (25, 40 and 50 cm) and three different weir crest height (7, 10 and 12 cm) of the side weir placed on the side weir station. There is no scour when the material is only kaolin. Therefore, the cohesive bed was prepared by properly mixing clay material (kaolin) with 31% sand in all experiments. Following 24h consolidation time, in order to observe the effect of flow intensity on the scour depth, experiments were carried out for five different upstream Froude numbers in the range of 0.33-0.81. As a result of this study the relation between scour depth and upstream flow intensity as a function of time have been established. The longitudinal velocities decreased along the side weir; towards the downstream due to overflow over the side-weirs. At the beginning, the scour depth increases rapidly with time and then asymptotically approached constant values in all experiments for all side weir dimensions as in non-cohesive sediment. Thus, the scour depth reached equilibrium conditions. Time to equilibrium depends on the approach flow intensity and the dimensions of side weirs. For different heights of the weir crest, dimensionless scour depths increased with increasing upstream Froude number. Equilibrium scour depths which formed 7 cm side-weir crest height were obtained higher than that of the 12 cm side-weir crest height. This means when side-weir crest height increased equilibrium scour depths decreased. Although the upstream side of the scour hole is almost vertical, the downstream side of the hole is inclined.

Keywords: clay-sand mixed sediments, scour, side weir, hydraulic structures

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Authors: Mohamed H. El-Newehy, Sameh M. Osman, Moamen S. Refat, Salem S. Al-Deyab, Ayman El-Faham

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The two copolymers itaconic acid-methyl methacrylate and itaconic acid-acrylamide have been prepared in different ratio by radical copolymerization in the presence of azobisisobutyronitrile (AIBN) as initiator and using 2-butanone as reaction medium using microwave irradiation. The microwave technique is safe, fast, and gives high yield of the products with high purity in an optimum time, comparing to the traditional conventional heating. All the prepared copolymers were characterized by FT-IR, thermal analysis and elemental microanalysis. The itaconic acid-based copolymers showed a good sensitivity in alkaline media for scavenging Cu (II) and Pb (II). The chelation behavior of both Cu (II) and Pb (II) complexes were checked using FT-IR, thermogravimetric analysis (TGA), and differential scanning calorimetery (DSC). The infrared data are in a good agreement with the coordination through carboxylate-to-metal, in which the copolymers acting as a bidentate ligand.

Keywords: microwave synthesis, itaconic acid, copolymerization, scavenging, thermal stability

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

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The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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Authors: R. Ziaie Moayed, A. Mahigir

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Stone column technique has been successfully employed to improve the load-settlement characteristics of foundations. A series of finite element numerical analyses of harmonic dynamic loading have been conducted on strengthened raft footing to study the effects of single and group stone columns on settlement of circular footings. The settlement of circular raft footing that improved by single and group of stone columns are studied under harmonic dynamic loading. This loading is caused by heavy machinery foundations. A detailed numerical investigation on behavior of single column and group of stone columns is carried out by varying parameters like weight of machinery, loading frequency and period. The result implies that presence of single and group of stone columns enhanced dynamic behavior of the footing so that the maximum and residual settlement of footing significantly decreased. 

Keywords: finite element analysis, harmonic loading, settlement, stone column

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Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

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Authors: Ergun Sakalar, Kubra Bilgic

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Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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Authors: Londeka Ntuli, Frasia Oosthuizen

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Background: Tenefovir disiproxil fumarate (TDF) is a nephrotoxic drug and has been proven to contribute to renal insufficiency necessitating intensive monitoring and management of adverse effects arising from prolonged exposure to the drug. TDF is one of the preferred first-line drugs used in combination therapy in most regions. There are estimated 300 000 patients being initiated on the Efavirenz/TDF/Emtricitabine first-line regimen annually in South Africa. It is against this background that this study aims to investigate the effects of TDF on renal sufficiency of HIV positive patients. Methodology: A retrospective quantitative study was conducted, analysing clinical charts of HIV positive patient’s older than 18 years of age and on a TDF-containing regimen for more than 1 year. Data were obtained from the analysis of patient files and was transcribed into Microsoft® Excel® spreadsheet. Extracted data were coded, categorised and analysed using STATA®. Results: A total of 275 patient files were included in this study. Renal function started decreasing after 3 months of treatment (with 93.5% patients having a normal EGFR), and kept on decreasing as time progressed with only 39.6% normal renal function at year 4. Additional risk factors for renal insufficiency included age below 25, female gender, and additional medication. Conclusion: It is clear from this study that the use of TDF necessitates intensive monitoring and management of adverse effects arising from prolonged exposure to the drug. The findings from this study generated pertinent information on the safety profile of the drug TDF in a resource-limited setting of a public health institution. The appropriate management is of tremendous importance in the South African context where the majority of HIV positive individuals are on the TDF containing regimen; thus it is beneficial to ascertain the possible level of toxicities these patients may be experiencing.

Keywords: renal insufficiency, tenefovir, HIV, risk factors

Procedia PDF Downloads 108

Authors: Matt Fullmer, Carol Wilkinson, Keven Prusak, Dennis Eggett, Todd Pennington

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Obesity and chronic health issues are linked to physical inactivity. Physical education (PE) programs in school can play a major role in combating these health-related issues. This study focused on supporting competence through keeping a leisure-time physical activity (LTPA) record as part of PE. Keeping a daily LTPA record may be an effective intervention helping students feel more competent toward exercise, and thus, self-determined (within the context of self-determination theory) to exercise. Little is known about the relationship between daily LTPA records and perceived competence, motivational profiles, and LTPA levels of students enrolled in PE. This study examined the relationship between keeping a daily, online LTPA record and adolescent (a) motivational profiles toward LTPA, (b) perceived competence toward LTPA, and (c) LTPA behaviors. Secondary students (N = 124) in physical education classes completed a baseline questionnaire which consisted of the Behavioural Regulation in Exercise Questionnaire–2, the Perceived Competence Scale, and the Godin Leisure-Time Exercise Questionnaire. For three weeks, the students were assigned to keep the Presidential Active Lifestyle Award Challenge (PALAC) as their online LTPA record. They completed the questionnaire after each week. A 2 (gender) x 4 (trials) repeated measures ANCOVA examined the relationships between recording compliance and motivation, perceived competence, and physical activity. Results showed that recording compliance was not a significant predictor of perceived competence to participate in LTPA. Examining motivational factors, a significant interaction between recording compliance and introjected regulation was found. The more students recorded the less motivated they were by guilt or obligation to exercise in their leisure-time. Also, a significant interaction was found between recording compliance and intrinsic regulation, indicating that the more students recorded the more intrinsically motivated they were to exercise in their leisure-time. Lastly, there was a significant interaction between recording compliance and LTPA. As students kept the LTPA record, girls’ LTPA levels significantly decreased and boys’ LTPA levels significantly increased. The key findings are that, as implemented in this study: a) the lack of PALAC compliance suggests that daily LTPA records may NOT be the most effective intervention for this population, b) keeping a daily LTPA record did NOT help students feel more competent to exercise in their leisure-time, c) a daily LTPA record may help students move towards being more self-determined in their feelings towards LTPA, and d) the outcome of keeping a LTPA record on LTPA behavior is statistically significant, although actual differences may not be practically important.

Keywords: behavioural regulation in exercise questionnaire–2, Godin leisure–time exercise questionnaire, online physical activity log, perceived competence scale, self-determination theory

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Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

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

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

Procedia PDF Downloads 95

Authors: Noga Bregman

Abstract:

Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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