Search results for: sampling algorithms

Authors: Sefa Aksu, Ünal Kızıl

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For this study, a town based soil database created in Gümüşçay District of Biga Town, Çanakkale, Turkey. Crop and livestock production are major activities in the district. Nutrient management is mainly based on commercial fertilizer application ignoring the livestock manure. Within the boundaries of district, 122 soil sampling points determined over the satellite image. Soil samples collected from the determined points with the help of handheld Global Positioning System. Labeled samples were sent to a commercial laboratory to determine 11 soil parameters including salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium, iron, manganese, copper and zinc. Based on the test results soil maps for mentioned parameters were developed using remote sensing, GIS, and geostatistical analysis. In this study we developed a GIS database that will be used for soil nutrient management. Methods were explained and soil maps and their interpretations were summarized in the study.

Keywords: geostatistics, GIS, nutrient management, soil mapping

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Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

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This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: matrix minimization algorithm, decoding sequential search algorithm, image compression, DCT, DWT

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Authors: Gianni Jacucci

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Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial intelligence methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while straight AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability

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Authors: Henok Biruk Alemayehu, Kalkidan Berhane Tsegaye, Fozia Seid Ali, Nebiyat Feleke Adimassu, Getasew Alemu Mersha

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Background: Strabismus is a visual disorder where the eyes are misaligned and point in different directions. Untreated strabismus can lead to amblyopia, loss of binocular vision, and social stigma due to its appearance. Since it is assumed that knowledge is pertinent for early screening and prevention of strabismus, the main objective of this study was to assess knowledge and attitudes toward strabismus in Woreta town, Northwest Ethiopia. Providing data in this area is important for planning health policies. Methods: A community-based cross-sectional study was done in Woreta town from April–May 2020. The sample size was determined using a single population proportion formula by taking a 50% proportion of good knowledge, 95% confidence level, 5% margin of errors, and 10% non- response rate. Accordingly, the final computed sample size was 424. All four kebeles were included in the study. There were 42,595 people in total, with 39,684 adults and 9229 house holds. A sample fraction ’’k’’ was obtained by dividing the number of the household by the calculated sample size of 424. Systematic random sampling with proportional allocation was used to select the participating households with a sampling fraction (K) of 21 i.e. each household was approached in every 21 households included in the study. One individual was selected ran- domly from each household with more than one adult, using the lottery method to obtain a final sample size. The data was collected through a face-to-face interview with a pretested and semi-structured questionnaire which was translated from English to Amharic and back to English to maintain its consistency. Data were entered using epi-data version 3.1, then processed and analyzed via SPSS version- 20. Descriptive and analytical statistics were employed to summarize the data. A p-value of less than 0.05 was used to declare statistical significance. Result: A total of 401 individuals aged over 18 years participated, with a response rate of 94.5%. Of those who responded, 56.6% were males. Of all the participants, 36.9% were illiterate. The proportion of people with poor knowledge of strabismus was 45.1%. It was shown that 53.9% of the respondents had a favorable attitude. Older age, higher educational level, having a history of eye examination, and a having a family history of strabismus were significantly associated with good knowledge of strabismus. A higher educational level, older age, and hearing about strabismus were significantly associated with a favorable attitude toward strabismus. Conclusion and recommendation: The proportion of good knowledge and favorable attitude towards strabismus were lower than previously reported in Gondar City, Northwest Ethiopia. There is a need to provide health education and promotion campaigns on strabismus to the community: what strabismus is, its’ possible treatments and the need to bring children to the eye care center for early diagnosis and treatment. it advocate for prospective research endeavors to employ qualitative study design.Additionally, it suggest the exploration of studies that investigate causal-effect relationship.

Keywords: strabismus, knowledge, attitude, Woreta

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Authors: F. Fakheri Raof, F. Zobeidizadeh

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The present study examined the potential capability of Spirogyra algae remove heavy metals Zn, Pb, Cu, and Cr from the water. For this purpose, the water treatment No. 3 of Ahvaz County in Khuzestan Province of Iran was selected as a case study. From 8 sampling stations, 4 stations were dedicated to the water samples and 4 stations to the algae samples. According to the obtained results, the concentration of the heavy metals Cr, Cu, Pb, and Zn in water samples were within the ranges of 1.98-19.53, 0.67-13.45, 1-23.18, and 2.12-83.04 µg/L. Besides, the concentration of heavy metal Cr, Pb, Cu, and Zn in spirogyra algae samples varied between the ranges 2.30-3.61, 2.06-3.43, 2.29-2.56, and 9.88-10.84 µg/L. The highest amount of metal absorption in spirogyra algae samples was related to the zinc. The obtained results also indicated that the last spirogyra algae sample which was at the inlet of Tank 4 absorbed the lowest concentration of metals. This would be due to the treatment process along the course of ponds resulted in completely pure water at the outlet without the existence of algae on the sides. The paper also provides some useful recommendations on this issue.

Keywords: absorption, Ahvaz, heavy metal, spirogyra algae, water treatment plants

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Authors: Kaushikk Iyer, Richard M Hall, David Keeling

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Hardware-in-the-loop (HIL) simulation is an advanced technique for developing and testing complex real-time control systems. This paper presents the benefits of HIL simulation and how it can be implemented and used effectively to develop, test, and validate advanced control algorithms used in a spinal joint Wear simulator for the Tribological testing of spinal disc prostheses. spinal wear simulator is technologically the most advanced machine currently employed For the in-vitro testing of newly developed spinal Discimplants. However, the existing control techniques, such as a simple position control Does not allow the simulator to test non-sinusoidal waveforms. Thus, there is a need for better and advanced control methods that can be developed and tested Rigorouslybut safely before deploying it into the real simulator. A benchtop HILsetupis was created for experimentation, controller verification, and validation purposes, allowing different control strategies to be tested rapidly in a safe environment. The HIL simulation aspect in this setup attempts to replicate similar spinal motion and loading conditions. The spinal joint wear simulator containsa four-Barlinkpowered by electromechanical actuators. LabVIEW software is used to design a kinematic model of the spinal wear Simulator to Validatehow each link contributes towards the final motion of the implant under test. As a result, the implant articulates with an angular motion specified in the international standards, ISO-18192-1, that define fixed, simplified, and sinusoid motion and load profiles for wear testing of cervical disc implants. Using a PID controller, a velocity-based position control algorithm was developed to interface with the benchtop setup that performs HIL simulation. In addition to PID, a fuzzy logic controller (FLC) was also developed that acts as a supervisory controller. FLC provides intelligence to the PID controller by By automatically tuning the controller for profiles that vary in amplitude, shape, and frequency. This combination of the fuzzy-PID controller is novel to the wear testing application for spinal simulators and demonstrated superior performance against PIDwhen tested for a spectrum of frequency. Kaushikk Iyer is a Ph.D. Student at the University of Leeds and an employee at Key Engineering Solutions, Leeds, United Kingdom, (e-mail: [email protected], phone: +44 740 541 5502). Richard M Hall is with the University of Leeds, the United Kingdom as a professor in the Mechanical Engineering Department (e-mail: [email protected]). David Keeling is the managing director of Key Engineering Solutions, Leeds, United Kingdom (e-mail: [email protected]). Results obtained are successfully validated against the load and motion tolerances specified by the ISO18192-1 standard and fall within limits, that is, ±0.5° at the maxima and minima of the motion and ±2 % of the complete cycle for phasing. The simulation results prove the efficacy of the test setup using HIL simulation to verify and validate the accuracy and robustness of the prospective controller before its deployment into the spinal wear simulator. This method of testing controllers enables a wide range of possibilities to test advanced control algorithms that can potentially test even profiles of patients performing various dailyliving activities.

Keywords: Fuzzy-PID controller, hardware-in-the-loop (HIL), real-time simulation, spinal wear simulator

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Ali Abojassim, Nabeel Kadhim, Adil Jaber, Ali Hussein

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Water quality index (WQI) is valuable and unique rating to depict the total water quality status in a single term that is helpful for the selection of appropriate treatment technique to meet the concerned issues. Fifteen surface water samples were collected from the Euphrates river within AlHaydria is sub district of AL-Najaf (Iraq). The quality of surface water were evaluated by testing various physicochemical parameters such as pH, Total Dissolved Solid (TDS), , Calcium, Chloride, Sulphate and Electrical conductivity. The WQI for all samples were found in the range of 25.92 to 47.22. The highest value of WQI was observed in the Ali Hajj Hassan(SW4,SW8), El Haj Abdel Sayed (SW 10 to SW 12)and Hasan alsab(SW 14) sampling locations. Most of the water samples within study area were found good to moderate categories. most of the water samples for study area were found good as well as moderate categories

Keywords: water quality index, GIS, physicochemical parameters, Iraq Standards for irrigation purpose 2012

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Authors: Mohammad Khamoushi, Reza Mirmahdi

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The aim of this research was the effect of sensory integration in reduction of stereotype behaviors in autistic children. The statistical population included 55 children with the age range 2/8 – 14 in Esfahan Ordibehesht autistic center. Purposive sampling was used for selecting the sample group and 20 children with random assignment were designated in two group; experimental and control . Research project was quasi-experimental two-group with pretest and posttest. Data collection tools included repetitive behavior scale-revised with six sub-scales: stereotype behavior, self-injurious behavior, compulsive behavior, ritualistic behavior, sameness behavior, restricted behavior. Analysis of covariance was used for analyzing hypotheses. Result show that sensory integration procedure was effective in reduction of stereotype behavior, compulsive behavior and self-injurious behavior in autistic children. According to the findings, it is suggested that effect sensory integration procedure in stereotype behavior of autism children should be studied and used for treatment of other disabilities of this children.

Keywords: autism, sensory integration procedure, stereotype behavior, compulsive behavior

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Authors: Baqir Khawari

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This study has been undertaken to investigate the impact of remittances on household poverty and inequality using OLS and Logit Models with a strictly multi-random sampling method. The result of the OLS model reveals that if the per capita international remittances increase by 1%, then it is estimated that the per capita income will increase by 0.071% and 0.059% during 2019/20 and 2020/21, respectively. In addition, a 1% increase in external remittances results in a 0.0272% and 0.025% reduction in per capita depth of poverty and a 0.0149% and 0.0145% decrease in severity of poverty during 2019/20 and 2020/21, respectively. It is also shown that the effect of external remittances on poverty is greater than internal remittances. In terms of inequality, the result represents that remittances reduced the Gini coefficient by 2% and 7% during 2019/20 and 2020/21, respectively. Further, it is bold that COVID-19 negatively impacts the amount of received remittances by households, thus resulting in a reduction in the size of the effect of remittances. Therefore, a concerted effort of effective policies and governance and international assistance is imperative to address this prolonged problem.

Keywords: migration, remittances, poverty, inequality, COVID-19, Afghanistan

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Authors: Rais Yusoh, Rosli Saad, Mokhtar Saidin, Fauzi Andika, Sabiu Bala Muhammad

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Resistivity and seismic refraction profiling have become a common method in pre-investigations for visualizing subsurface structure. The integration of the methods could reduce an interpretation ambiguity. Both methods have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was existed and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both methods by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the ancient river. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis provides an additional technique for interpretation such as an alluvium, which can have strong influence on the ancient river findings.

Keywords: ancient river, combine inversion, resistivity, seismic refraction

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Authors: Ziyad Alghamdi

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This research investigates how issues concerning Saudi women have been represented in selected U.S. and Saudi publications. Saudi Vision 2030 is the Kingdom of Saudi Arabia's development strategy, which was revealed on April 25, 2016. This study used 115 news items across selected newspapers as its sampling. The New York Times and the Washington Post were chosen to represent U.S. newspapers and picked two Saudi newspapers, Al Jazirah, and Al Watan. This research examines how these issues were covered before and during the implementation of Saudi Vision 2030. The news pieces were analyzed using both quantitative and qualitative methodologies. The qualitative study employed an inductive technique to uncover frames. Furthermore, this work looked at how American and Saudi publications had framed Saudi women depicted in images by reviewing the photographs used in news reports about Saudi women's issues. The primary conclusion implies that the human-interest frame was more prevalent in American media, whereas the economic frame was more prevalent in Saudi publications. A variety of diverse topics were considered.

Keywords: Saudi newspapers, Saudi Vision 2030, framing theory, Saudi women

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Authors: Reysand Mae A. Abapial, Christine Claire Z. Agra, Quenna Lyn V. De Guzman, Marielle Arianne Joyce Q. Hojilla, John Joseph A. Tiangco

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The study focused on the assessment of the tourists’ satisfaction on the local gastronomy in Pagudpud, Ilocos Norte as a tourist destination as perceived by 100 tourists visiting the tourist destination, which is determined through convenient random sampling. Mean, percentage frequency and Wilcoxon rank sum test were used in the collection of data. The results revealed that the tourists agree that the local establishments offering local cuisines are accessible in terms of the location, internet visibility and facilities for persons-with-disabilities. The tourist are also willing to pay for the local food because it is attainable, budget-friendly, worthy for an expensive price, satisfies the cravings, reflects the physical appearance of the establishment and its quantity is reasonable based on the price. However, the tourists disagree that the local food completes their overall experience as tourists and it does not have the potential to satisfy all types of tourists. Recommendations for the enhancement of the local cuisine and implications for future research are discussed.

Keywords: gastronomy, local gastronomy, tourist satisfaction, Pagudpud

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Authors: E. Dehghan, R. Dehghan

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Generally, the slender structural walls have flexural behavior. Since behavior of bending members can be explained by moment–curvature relation, therefore, an analytical model is proposed based on moment–curvature relation for slender structural walls. The moment–curvature relationships of RC sections are constructed through section analysis. Governing equations describing the bond-slip behavior in walls are derived and applied to moment–curvature relations. For the purpose of removing the imprecision in analytical results, the plastic hinge length is included in the finite element modeling. Finally, correlation studies between analytical and experimental results are conducted with the objective to establish the validity of the proposed algorithms. The results show that bond-slip effect is more significant in walls subjected to larger axial compression load. Moreover, preferable results are obtained when ultimate strain of concrete is assumed conservatively.

Keywords: nonlinear analysis, slender structural walls, moment-curvature relation, bond-slip, plastic hinge length

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Authors: Tathiana Yesenia Coy Mondragón, Jossitt William Vargas Cruz, Cristian Leonardo Gutiérrez Gómez

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The study of cosmic rays is based on two fundamental pillars: the detection of secondary cosmic rays on the Earth's surface and the detection of the source and origin of the cascade. In addition, the constant flow of RC generates a lot of interest for study due to the incidence of various natural phenomena, which makes it relevant to characterize their incidence parameters to determine their effect not only at subsoil or terrestrial surface levels but also throughout the atmosphere. To determine the physical parameters of the primary cosmic ray, the implementation of robust algorithms capable of reconstructing the cascade from the measured values is required, with a high level of reliability. Therefore, it is proposed to build a machine learning system that will be fed from the cosmic ray simulations in CORSIKA at different energies that lie in a range [10⁹-10¹²] eV. in order to generate a trained particle and pattern recognition system to obtain greater efficiency when inferring the nature of the origin of the cascade for EAS in the atmosphere considering atmospheric models.

Keywords: CORSIKA, cosmic rays, eas, Colombia

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Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Elmahdi Elgharbaoui, Tamou Nasser, Ahmed Essadki

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In the era of sustainable development, photovoltaic (PV) technology has shown significant potential as a renewable energy source. Photovoltaic generators (GPV) have a non-linear current-voltage characteristic, with a maximum power point (MPP) characterized by an optimal voltage, and depends on environmental factors such as temperature and irradiation. To extract each time the maximum power available at the terminals of the GPV and transfer it to the load, an adaptation stage is used, consisting of a boost chopper controlled by a maximum power point tracking technique (MPPT) through a stage of pulse width modulation (PWM). Our choice has focused on three techniques which are: the perturbation and observation method (P&O), the incremental conductance method (InCond) and the last is that of control using the fuzzy logic. The implementation and simulation of the system (photovoltaic generator, chopper boost, PWM and MPPT techniques) are then performed in the Matlab/Simulink environment.

Keywords: photovoltaic generator, technique MPPT, boost chopper, PWM, fuzzy logic, P&O, InCond

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Authors: Osifeko Olalekan Remigious, Adesanya Adebisi Joseph, Omolade Akinmade Olatunde

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The focus of this study was to determine the factors associated with the use of substances for sport performance of youth in Lagos state sport. Questionnaire was the instrument used for the study. Descriptive research method was used. The estimated population for the study was 2000 sport men and women. The sample size was 200 respondents for purposive sampling techniques were used. The instrument was validated in it content and constructs value. The instrument was administered with the assistance of the coaches. Same 200 copies administered were returned. The data obtained was analysed using simple percentage and chi-square (x2) for stated hypothesis at 0.05 level of significance. The finding reveal that sport injuries exercise induced and anaphylaxis and asthma and feeling of loss of efficacy associated with alcohol used on sport performance among the users of substances. Alcohol users are recommended to partake in sport like swimming, basketball and volleyball because they have space of time for resting while at play. Government should be fully in charge of the health of sport men and women.

Keywords: implications, Lagos state, substances, sports performance, youth

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Authors: Nadeen Felemban, Hamsa Banjer, Rabaah Jaafari

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One of the most common hazards in the pharmaceutical industry is the chemical hazard, which can cause harm or develop occupational health diseases/illnesses due to chronic exposures to hazardous substances. Therefore, a chemical agent management system is required, including hazard identification, risk assessment, controls for specific hazards and inspections, to keep your workplace healthy and safe. However, routine management monitoring is also required to verify the effectiveness of the control measures. Moreover, Betamethasone Valerate and Clobetasol Propionate are some of the APIs (Active Pharmaceutical Ingredients) with highly hazardous classification-Occupational Hazard Category (OHC 4), which requires a full containment (ECA-D) during handling to avoid chemical exposure. According to Safety Data Sheet, those chemicals are reproductive toxicants (reprotoxicant H360D), which may affect female workers’ health and cause fatal damage to an unborn child, or impair fertility. In this study, qualitative (chemical Risk assessment-qCRA) was conducted to assess the chemical exposure during handling of Betamethasone Valerate and Clobetasol Propionate in pharmaceutical laboratories. The outcomes of qCRA identified that there is a risk of potential chemical exposure (risk rating 8 Amber risk). Therefore, immediate actions were taken to ensure interim controls (according to the Hierarchy of controls) are in place and in use to minimize the risk of chemical exposure. No open handlings should be done out of the Steroid Glove Box Isolator (SGB) with the required Personal Protective Equipment (PPEs). The PPEs include coverall, nitrile hand gloves, safety shoes and powered air-purifying respirators (PAPR). Furthermore, a quantitative assessment (personal air sampling) was conducted to verify the effectiveness of the engineering controls (SGB Isolator) and to confirm if there is chemical exposure, as indicated earlier by qCRA. Three personal air samples were collected using an air sampling pump and filter (IOM2 filters, 25mm glass fiber media). The collected samples were analyzed by HPLC in the BV lab, and the measured concentrations were reported in (ug/m3) with reference to Occupation Exposure Limits, 8hr OELs (8hr TWA) for each analytic. The analytical results are needed in 8hr TWA (8hr Time-weighted Average) to be analyzed using Bayesian statistics (IHDataAnalyst). The results of the Bayesian Likelihood Graph indicate (category 0), which means Exposures are de "minimus," trivial, or non-existent Employees have little to no exposure. Also, these results indicate that the 3 samplings are representative samplings with very low variations (SD=0.0014). In conclusion, the engineering controls were effective in protecting the operators from such exposure. However, routine chemical monitoring is required every 3 years unless there is a change in the processor type of chemicals. Also, frequent management monitoring (daily, weekly, and monthly) is required to ensure the control measures are in place and in use. Furthermore, a Similar Exposure Group (SEG) was identified in this activity and included in the annual health surveillance for health monitoring.

Keywords: occupational health and safety, risk assessment, chemical exposure, hierarchy of control, reproductive

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Authors: Chirag Kothawade, Gourie Jagtap, PreetKaur Relusinghani, Vedang Chavan, Smitha S. Bhosale

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Psychological research has proven that music relieves stress, elevates mood, and is responsible for the release of “feel-good” chemicals like oxytocin, serotonin, and dopamine. It comes as no surprise that music has been a popular tool in rehabilitation centers and therapy for various disorders, thus with the interminably rising numbers of people facing mental health-related issues across the globe, addressing mental health concerns is more crucial than ever. Despite the existing music recommendation systems, there is a dearth of holistically curated algorithms that take care of the needs of users. Given that, an undeniable majority of people turn to music on a regular basis and that music has been proven to increase cognition, memory, and sleep quality while reducing anxiety, pain, and blood pressure, it is the need of the hour to fashion a product that extracts all the benefits of music in the most extensive and deployable method possible. Our project aims to ameliorate our users’ mental state by building a comprehensive mood-based music recommendation system called “Viby”.

Keywords: language, communication, speech recognition, interaction

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Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

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Authors: Po-Chun Wang, Yan-Ru Lai, Sophia I. C. Lin, Alvin W. Y. Su

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The Generative Theory of Tonal Music (GTTM) provides systematic approaches to recognizing local boundaries of music. The rules have been implemented in some automated melody segmentation algorithms. Besides, there are also deep learning methods with GTTM features applied to boundary detection tasks. However, these studies might face constraints such as a lack of or inconsistent label data. The GTTM database is currently the most widely used GTTM database, which includes manually labeled GTTM rules and local boundaries. Even so, we found some problems with these labels. They are sometimes discrepancies with GTTM rules. In addition, since it is labeled at different times by multiple musicians, they are not within the same scope in some cases. Therefore, in this paper, we examine this database with musicians from the aspect of classical music and relabel the scores. The relabeled database - GTTM Database v2.0 - will be released for academic research usage. Despite the experimental and statistical results showing that the relabeled database is more consistent, the improvement in boundary detection is not substantial. It seems that we need more clues than GTTM rules for boundary detection in the future.

Keywords: dataset, GTTM, local boundary, neural network

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Authors: L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead

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Cognitive decline and frailty is apparent in older adults leading to an increased likelihood of the risk of falling. Currently health care professionals have to make professional decisions regarding such risks, and hence make difficult decisions regarding the future welfare of the ageing population. This study uses health data from The Irish Longitudinal Study on Ageing (TILDA), focusing on adults over the age of 50 years, in order to analyse health risk factors and predict the likelihood of falls. This prediction is based on the use of machine learning algorithms whereby health risk factors are used as inputs to predict the likelihood of falling. Initial results show that health risk factors such as long-term health issues contribute to the number of falls. The identification of such health risk factors has the potential to inform health and social care professionals, older people and their family members in order to mitigate daily living risks.

Keywords: classification, falls, health risk factors, machine learning, older adults

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Authors: Fanqiang Kong, Chending Bian

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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means

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Authors: A. H. Paul, L. J. Gizaki, E. P. Ejimbi

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The study was carried out to determine the level of knowledge and adoption of agricultural biotechnology in Taraba state. Purposive and simple sampling techniques were used to select respondents. Questionnaires were administered to 90 respondents. Data were analyzed using descriptive and inferential statistics. The results showed that the majority (73.3%) of the respondents were small-scale farmers, whereas 24.4 percent were engaged in secondary occupations. The mean farm size was 1-5 ha. The majority (72.2%) had one form of formal education or another. About 84 percent (84.4%) had been farming for at least 10 years. There was a mean household size of 6-10 persons. Many (97.8%) of the respondents were knowledgeable about biotechnology, and about 70.0 percent (70.1%) reported that the biotechnology products which they had adopted were very good for animals and human consumption. The result of Pearson’s correlation (r = 0.699) was significant at the 0.01 alpha level. Therefore, the hypothesis that there is no significant relationship between knowledge and adoption of agricultural biotechnology was rejected. It was concluded that the agricultural biotechnologies that were adopted were very safe for animals, humans, and the environment. It was recommended that the government should employ more extension agents to help educate farmers about agricultural biotechnology.

Keywords: agricultural, adoption, biotechnology, knowledge

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

Abstract:

The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

Abstract:

This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: Ariel Barel, Rotem Manor, Alfred M. Bruckstein

Abstract:

We present a probabilistic gathering algorithm for agents that can only detect the presence of other agents in front of or behind them. The agents act in the plane and are identical and indistinguishable, oblivious, and lack any means of direct communication. They do not have a common frame of reference in the plane and choose their orientation (direction of possible motion) at random. The analysis of the gathering process assumes that the agents act synchronously in selecting random orientations that remain fixed during each unit time-interval. Two algorithms are discussed. The first one assumes discrete jumps based on the sensing results given the randomly selected motion direction, and in this case, extensive experimental results exhibit probabilistic clustering into a circular region with radius equal to the step-size in time proportional to the number of agents. The second algorithm assumes agents with continuous sensing and motion, and in this case, we can prove gathering into a very small circular region in finite expected time.

Keywords: control, decentralized, gathering, multi-agent, simple sensors

Procedia PDF Downloads 165

Authors: Katie Hudson

Abstract:

A growing body of scholarship is dedicated to the concept of imperial nationalism, denoting a nostalgia for empire amongst former imperial powers and a yearning to recapture the grandeur of the imperial ‘golden age.’ Much research within this field has focused on Brexit, arguing that Britain’s imperialist identity has spawned Euroscepticism. However, the interaction between imperial nationalism and foreign policy remains underdeveloped and thus far has failed to consider cases outside of the UK. Using maximum variation sampling across post-2000 Britain, Spain and the Netherlands, this comparative analysis aims to explore the discursive invocation of empire in foreign policy framing, under which circumstances and in what ways imperial nationalism emerges. Preliminary findings demonstrate that empire is most often cited when there is a perceived threat to the sovereignty of the nation and that all cases frame foreign policy options according to their acute concerns with regaining the prestige associated with empire. This is present to a lesser extent in Spain, whose earlier period of decolonisation affected the extent to which imperialism has permeated their national psyche. This, therefore, provides an alternative lens through which we can view both Euroscepticism and international relations, conditioned by an imperial legacy.

Keywords: empire, nationalism, foreign policy, IR

Procedia PDF Downloads 96

Authors: Utkan Caliskan

Abstract:

Two types of numerical codes based on finite volume method are developed in order to solve compressible Euler equations to simulate the flow through forward facing step channel. Both algorithms have AUSM+- up (Advection Upstream Splitting Method) scheme for flux splitting and two-stage Runge-Kutta scheme for time stepping. In this study, the flux calculations differentiate between the algorithm based on OpenFOAM mesh format which is called 'face-based' algorithm and the basic algorithm which is called 'element-based' algorithm. The face-based algorithm avoids redundant flux computations and also is more flexible with hybrid grids. Moreover, some of OpenFOAM’s preprocessing utilities can be used on the mesh. Parallelization of the face based algorithm for which atomic operations are needed due to the shared memory model, is also presented. For several mesh sizes, 2.13x speed up is obtained with face-based approach over the element-based approach.

Keywords: cell centered finite volume method, compressible Euler equations, OpenFOAM mesh format, OpenMP

Procedia PDF Downloads 320