Search results for: data quality filtering

Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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Authors: Sara D. Garduno-Diaz, Philippe Y. Garduno-Diaz

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To date, one of the few comprehensive indicators for the measurement of food security is the Global Food Security Index. This index is a dynamic quantitative and qualitative bench marking model, constructed from 28 unique indicators, that measures drivers of food security across both developing and developed countries. Whereas the Global Food Security Index has been calculated across a set of 109 countries, in this paper we aim to present and compare, for the Middle East and North Africa (MENA), 1) the Food Security Index scores achieved and 2) the data available on affordability, availability, and quality of food. The data for this work was taken from the latest (2014) report published by the creators of the GFSI, which in turn used information from national and international statistical sources. According to the 2014 Global Food Security Index, MENA countries rank from place 17/109 (Israel, although with resent political turmoil this is likely to have changed) to place 91/109 (Yemen) with household expenditure spent in food ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food as a share of household consumption in most countries and better food safety net programs in the MENA have contributed to a notable increase in food affordability. The region has also however experienced a decline in food availability, owing to more limited food supplies and higher volatility of agricultural production. In terms of food quality and safety the MENA has the top ranking country (Israel). The most frequent challenges faced by the countries of the MENA include public expenditure on agricultural research and development as well as volatility of agricultural production. Food security is a complex phenomenon that interacts with many other indicators of a country’s well-being; in the MENA it is slowly but markedly improving.

Keywords: diet, food insecurity, global food security index, nutrition, sustainability

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Authors: Jonathan N. Nayga, Emelita B. Valdez, Mila R. Andres, Beulah B. Estrada, Emelina A. Lopez, Rogelio B. Tamayo, Aubrey Joy M. Balbin

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Goat production is one of the activities included in integrated farming in the Philippines. Goats are raised for its meat and regardless of breed the animal is slaughtered for this purpose. In order to document the carcass yield of different goats slaughtered, five (5) different breeds of goats to include Purebred Boer and Anglo-nubian, Crossbred Boer and Anglo-nubian and Philippine Native goat were used in the study. Data on slaughter parameters, carcass characteristics, and sensory evaluation were gathered and analyzed using Complete Random Design (CRD) at 5% level of significance and the results of carcass conformation were assessed descriptively. Results showed that slaughter data such as slaughter/live weight, hot and chilled carcass weights, dressing percentage and percentage drip loss were significantly different (P>0.05) among breeds. On carcass and meat characteristics, pure breed and upgraded Boer were found to be moderately muscular while Native goat was rated as thin muscular. The color of the carcass also revealed that Purebred and crossbred Boer were described dark red, while Native goat was noted to be slightly pale. On sensory evaluation, the results indicated that there was no significant difference (P>0.05) among breeds evaluated. It is therefore concluded that purebred goat has heavier carcass, while both purebred Boer and upgrade are rated slightly muscular. It is further confirms that regardless of breed, goat will have the same sensory characteristics. Thus, it is recommended to slaughter heavier goats to obtain more carcasses with better conformation and quality.

Keywords: carcass quality, goat, sensory evaluation, slaughter

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Yumei Wu, Xiaoyan Dang, Shenglong Yang, Shengmao Zhang

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The East China Sea is one of four main seas in China, where there are many fishery resources. Some important fishing grounds, such as Zhousan fishing ground important to society. But the eco-environment is destroyed seriously due to the rapid developing of industry and economy these years. In this paper, about twenty-year satellite data from MODIS and the statistical information of marine environment from the China marine environmental quality bulletin were applied to do the research. The chlorophyll-a concentration data from MODIS were dealt with in the East China Sea and then used to analyze the features and variations of plankton biomass in recent years. The statistics method was used to obtain their spatial and temporal features. The plankton biomass in the Yangtze River estuary and the Taizhou region were highest. The high phytoplankton biomass usually appeared between the 88th day to the 240th day (end-March - August). In the peak time of phytoplankton blooms, the Taizhou islands was the earliest, and the South China Sea was the latest. The intensity and period of phytoplankton blooms were connected with the global climate change. This work give us confidence to use satellite data to do more researches about the China Sea, and it also provides some help for us to know about the eco-environmental variation of the East China Sea and regional effect from global climate change.

Keywords: the East China Sea, phytoplankton biomass, temporal and spatial variation, phytoplankton bloom

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Authors: Mst. Nilufa Sultana, Shatirah Akib, Muhammad Aqeel Ashraf, Mohamed Roseli Zainal Abidin

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Most people today are aware that global Climate change, is not just a scientific theory but also a fact with worldwide consequences. Global climate change is due to rapid urbanization, industrialization, high population growth and current vulnerability of the climatic condition. Water is becoming scarce as a result of global climate change. To mitigate the problem arising due to global climate change and its drought effect, harvesting rainwater from green roofs, an environmentally-friendly and versatile technology, is becoming one of the best assessment criteria and gaining attention in Malaysia. This paper addresses the sustainability of green roofs and examines the quality of water harvested from green roofs in comparison to rainwater. The factors that affect the quality of such water, taking into account, for example, roofing materials, climatic conditions, the frequency of rainfall frequency and the first flush. A green roof was installed on the Humid Tropic Centre (HTC) is a place of the study on monitoring program for urban Stormwater Management Manual for Malaysia (MSMA), Eco-Hydrological Project in Kualalumpur, and the rainwater was harvested and evaluated on the basis of four parameters i.e., conductivity, dissolved oxygen (DO), pH and temperature. These parameters were found to fall between Class I and Class III of the Interim National Water Quality Standards (INWQS) and the Water Quality Index (WQI). Some preliminary treatment such as disinfection and filtration could likely to improve the value of these parameters to class I. This review paper clearly indicates that there is a need for more research to address other microbiological and chemical quality parameters to ensure that the harvested water is suitable for use potable water for domestic purposes. The change in all physical, chemical and microbiological parameters with respect to storage time will be a major focus of future studies in this field.

Keywords: Green roofs, INWQS, MSMA-SME, rainwater harvesting, water treatment, water quality parameter, WQI

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Authors: Domingo Planes Meseguer, Raffaele Danilo Esposito, Maria Del Pilar Dorado Rodriguez

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Monthly quality control checks for a Radiation Therapy Linac may be performed is a simple and efficient way once they have been standardized and protocolized. On the other hand this checks, in spite of being imperatives, require a not negligible execution times in terms of machine time and operators time. Besides it must be taken into account the amount of disposable material which may be needed together with the use of commercial software for their performing. With the aim of optimizing and standardizing mechanical-geometric checks and multi leaves collimator checks, we decided to implement a protocol which makes use of the Electronic Portal Imaging Device (EPID) available on our Linacs. The user is step by step guided by the software during the whole procedure. Acquired images are automatically analyzed by our programs all of them written using only free software.

Keywords: quality control checks, linac, radiation oncology, medical physics, free software

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Authors: Wei-Hsuan Hsu, Yi-Xuan Huang

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Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.

Keywords: electrowetting, mold filling, nano-imprint, surface modification

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Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

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Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

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Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

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Authors: Ernest Gyan Bediako, Petra Dancova, Tomas Vit

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Flow boiling heat transfer remains an important area of research due to its relevance in thermal management systems and other applications. Despite the enormous work done in the field of flow boiling heat transfer over the years to understand how flow parameters such as mass flux, heat flux, saturation conditions and tube geometries influence the characteristics of flow boiling heat transfer, there are still many contradictions and lack of agreement on the actual mechanisms controlling heat transfer and how flow parameters impact the heat transfer. This work thus seeks to experimentally investigate the heat transfer characteristics and flow patterns at low mass fluxes, low heat fluxes and low saturation pressure conditions which are of less attention in literature but prevalent in refrigeration, air-conditioning and heat pump applications. In this study, flow boiling experiment was conducted for R134a working fluid in a 5 mm internal diameter stainless steel horizontal smooth tube with mass flux ranging from 80- 100 kg/m2 s, heat fluxes ranging from 3.55kW/m2 - 25.23 kW/m2 and saturation pressure of 460 kPa. Vapor quality ranged from 0 to 1. A well-known flow pattern map created by Wojtan et al. was used to predict the flow patterns noticed during the study. The experimental results were correlated with well-known flow boiling heat transfer correlations in literature. The findings show that, heat transfer coefficient was influenced by both mass flux and heat fluxes. However, for an increasing heat flux, nucleate boiling was observed to be the dominant mechanism controlling the heat transfer especially at low vapor quality region. For an increasing mass flux, convective boiling was the dominant mechanism controlling the heat transfer especially in the high vapor quality region. Also, the study observed an unusual high heat transfer coefficient at low vapor qualities which could be due to periodic wetting of the walls of the tube due to slug flow pattern and stratified wavy flow patterns. The flow patterns predicted by Wojtan et al. flow pattern map were mixture of slug and stratified wavy, purely stratified wavy and dry out. Statistical assessment of the experimental data with various well-known correlations from literature showed that, none of the correlations reported in literature could predicted the experimental data with enough accuracy.

Keywords: flow boiling, heat transfer coefficient, mass flux, heat flux.

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Authors: Toru Shionoya, Yosuke Kurihara, Takashi Kaburagi, Kajiro Watanabe

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Mass-produced bidirectional microphones have attractive characteristics. They work as a microphone as well as a sensor with high gain over a wide frequency range; they are also highly reliable and economical. We present novel multiple functional uses of the microphones. A mathematical model for explaining the high-pass-filtering characteristics of bidirectional microphones was presented. Based on the model, the characteristics of the microphone were investigated, and a novel use for the microphone as a sensor with a wide frequency range was presented. In this study, applications for using the microphone as a security sensor and a human biosensor were introduced. The mathematical model was validated through experiments, and the feasibility of the abovementioned applications for security monitoring and the biosignal monitoring were examined through experiments.

Keywords: bidirectional microphone, low-frequency, mathematical model, frequency response

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

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The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC

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Authors: Güler Duru Aşiret

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Introduction: Poor sleep quality is a common problem among the older people living in nursing homes. Our study aimed at assessing the effect of individual reminiscence therapy on the sleep quality of the elderly living in nursing homes. Methods: The study had 22 people in the intervention group and 24 people in the control group. The intervention group had reminiscence therapy once a week for 12 weeks in the form of individual sessions of 25-30 minutes. In our study, we first determined the dates suitable for the intervention group and researcher and planned the date and time of individual reminiscence therapies, which would take 12 weeks. While preparing this schedule, we considered subjects’ time schedules for their regular visits to health facilities and the arrival of their visitors. At this stage, the researcher informed the participants that their regular attendance in sessions would affect the intervention outcome. One topic was discussed every week. Weekly topics included: introduction in the first week; childhood and family life, school days, starting work and work life (a day at home for housewives), a fun day out of home, marriage (friendship for the singles), plants and animals they loved, babies and children, food and cooking, holidays and travelling, special days and celebrations, assessment and closure, in the following weeks respectively. The control group had no intervention. Study data was collected by using an introductory information form and the Pittsburgh Sleep Quality Index (PSQI). Results: In our study, participants’ average age was 76.02 ± 7.31. 58.7% of them were male and 84.8% were single. All of them had at least one chronic disease. 76.1% did not need help for performing their daily life activities. The length of stay in the institution was 6.32 ± 3.85 years. According to the participants’ descriptive characteristics, there was no difference between groups. While there was no statistically significant difference between the pretest PSQI median scores (p > 0.05) of both groups, PSQI median score had a statistically significant decrease after 12 weeks of reminiscence therapy (p < 0.05). There was no statistically significant change in the median scores of the subcomponents of sleep latency, sleep duration, sleep efficiency, sleep disturbance and use of sleep medication before and after reminiscence therapy. After the 12-weeks reminiscence therapy, there was a statistically significant change in the median scores for the PSQI subcomponents of subjective sleep quality (p<0.05). Conclusion: Our study found that reminiscence therapy increased the sleep quality of the elderly living in nursing homes. Acknowledgment: This study (project no 2017-037) was supported by the Scientific Research Projects Coordination Unit of Aksaray University. We thank the elderly subjects for their kind participation.

Keywords: nursing, older people, reminiscence therapy, sleep

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Roswati Md. Amin, Nurul Asmera Mudiman, Muhammad Faisal Abd. Rahman, Md-Suffian Idris, Noor Hazwani Mohd Azmi

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Distribution of picophytoplankton from two genera, Synechococcus and Prochlorococcus at the surface water (0.5m) were observed from coastal to offshore area of the southeastern coast of Peninsular Malaysia, for a six day cruise in August 2014 during SouthWest monsoon. The picophytoplankton was divided into two different size fractions (0.7-2.7μm and <0.7 μm) by filtering through GF/D (2.7 μm) and GF/F (0.7 μm) filter papers and counted by using flow cytometer. Synechococcus and Prochlorococcus contribute higher at 0.7-2.7μm size range (ca. 90% and 95%, respectively) compared to <0.7 μm (ca. 10% and 5%, respectively). Synechococcus (>52%) dominated the total picophytoplankton compared to Prochlorococcus (<26%) for both size fractions in southeastern coast of Peninsular Malaysia. Total density (<2.7 μm) of Synechococcus was ranging between 1.72 x104 and 12.57 x104 cells ml-1, while Prochlorococcus varied from 1.50 x104 to 8.62 x104. Both Synechococcus and Prochlorococcus abundance showed a decreasing trend from coastal to offshore.

Keywords: Peninsular Malaysia, prochlorococcus, South China Sea, synechococcus

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Authors: Ahmed A. Al-Mudhafar, Ali A. Abduljabar, Hayder Jawad Albattat

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This work suggests a new microwave resonator sensor (MRS) device for measuring the oil’s breakdown voltage of high voltage transformers. A precise high-sensitivity sensor is designed and manufactured based on a microstrip split ring resonator (SRR). To improve the sensor sensitivity, a RF amplifier of 30 dB gain is linked through a transmission line of 50Ω.The sensor operates at a microwave band (L) with a quality factor of 1.35x105 when it is loaded with an empty tube. In this work, the sensor has been tested with three samples of high voltage transformer oil of different ages (new, middle, and damaged) where the quality factor differs with each sample. A mathematical model was built to calculate the breakdown voltage of the transformer oils and the accuracy of the results was higher than 90%.

Keywords: active resonator sensor, oil breakdown voltage, transformers oils, quality factor

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Authors: Rameshwor Pudasaini

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An experiment was conducted to study the effect of pollination quality of rapeseed seed in Chitwan during 2012-2013. The experiment was designed in Randomized Complete Block with four replications and five pollination treatments. The rapeseed plots were caged with mosquito nets at 10% flowering except natural pollination. Two-framed colonies of Apis mellifera L. and Apis cerana F. were introduced separately for pollination, and control plot caged without pollinators. The highest germination percent was observed on Apis cerana F. pollinated plot seeds (90.50% germination) and lowest on control plots (42.00% germination) seeds. Similarly, seed test weight of Apis cerana F. pollinated plots (3.22 gm/ 1000 seed) and Apis mellifera L. pollinated plots (2.93 gm/1000 seed) were and control plots (2.26 gm/ 1000 seed) recorded respectively. However, oil content was recorded highest on pollinated by Apis cerana F. (36.1 %) and lowest on control plots (32.8%). This study clearly indicated pollination increases the seed quality of rapeseed and therefore, management of honeybee is necessary for higher quality of rapeseed under Chitwan condition.

Keywords: apis cerana, apis mellifera, rapeseed pollination, rapeseed quality

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Authors: Debi Konukcu Onal, Tarkan Cavusoglu

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In modern societies, the costs of public goods and services are shared through taxes paid by citizens. However, taxation has always been a frictional issue, as tax obligations are perceived to be a financial burden for taxpayers rather than being merit that fulfills the redistribution, regulation and stabilization functions of the welfare state. The tax compliance literature evolves into discussing why people still pay taxes in systems with low costs of legal enforcement. Related empirical and theoretical works show that a wide range of socially oriented behavioral factors can stimulate voluntary compliance and subversive effects as well. These behavioral motivations are argued to be driven by self-enforcing rules of informal institutions, either independently or through interactions with legal orders set by formal institutions. The main focus of this study is to investigate empirically whether institutional particularities have a significant role in explaining the cross-country differences in the tax noncompliance levels. A part of the controversy about the driving forces behind tax noncompliance may be attributed to the lack of empirical evidence. Thus, this study aims to fill this gap through regression estimates, which help to trace the link between institutional quality and noncompliance on a cross-country basis. Tax evasion estimates of Buehn and Schneider is used as the proxy measure for the tax noncompliance levels. Institutional quality is quantified by three different indicators (percentile ranks of Worldwide Governance Indicators, ratings of the International Country Risk Guide, and the country ratings of the Freedom in the World). Robust Least Squares and Threshold Regression estimates based on the sample of the Organization for Economic Co-operation and Development (OECD) countries imply that tax compliance increases with institutional quality. Moreover, a threshold-based asymmetry is detected in the effect of institutional quality on tax noncompliance. That is, the negative effects of tax burdens on compliance are found to be more pronounced in countries with institutional quality below a certain threshold. These findings are robust to all alternative indicators of institutional quality, supporting the significant interaction of societal values with the individual taxpayer decisions.

Keywords: institutional quality, OECD economies, tax compliance, tax evasion

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Gabriela-Andreea Despescu, Mădălina Mavrodin, Gheorghe Lăzăroiu, S. Nacu, R. Băstinaş

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The Monitoring of Surface Water Bodies (Rivers) from Tisa Catchment Area - Maramureş County in 2014. This study is focused on the monitoring and evaluation of river’s water bodies from Maramureş County, using the methodology associated with the EU Water Framework Directive 60/2000. Thus, in the first part are defined the theoretical terms of monitoring activities related to the water bodies’ quality and the specific features of those we can find in the studied area. There are presented the water bodies’ features, quality indicators and the monitoring frequencies for the rivers situated in the Tisa catchment area. The results have shown the actual ecological and chemical state of those water bodies, in relation with the standard values mentioned through the Water Framework Directive.

Keywords: monitoring, surveillance, water bodies, quality

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Authors: Supriyono, Sumardiyono

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Biodiesel is one of the alternative fuels that promising for substituting petrodiesel as energy source which is have advantage on sustainability and eco-friendly. Due to the raw material that tend to decompose during storage, biodiesel also have the same characteristic that tend to decompose and formed higher acid value which is the result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could prevent by introduce a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. The quality degradation on biodiesel could evaluated by measuring iodine value and acid number of biodiesel. Biodiesel made from High Fatty Acid Jatropha curcas oil equality by using esterification and esterification process will stand on the quality by introduce 90 ppm pyrogallol powder on the biodiesel, which could extend the quality from 2 hours to more than 6 hours in rancimat test evaluation.

Keywords: biodiesel, antioxidant, iodine number, acid value

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil

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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.

Keywords: interpolation, MSE, PSNR, SSIM, super resolution

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

Procedia PDF Downloads 402

Authors: Shuaili Ji

Abstract:

The correct use of verbs is an important element of high-quality research articles, and thus for Chinese EFL learners, it is significant to master characteristics of verbs and to precisely use verbs. However, some researches have shown that there are differences in using verbs between learners and native speakers and learners have difficulty in using English verbs. This corpus-based quantitative research can enhance learners’ knowledge of English verbs and promote the quality of research article abstracts even of the whole academic writing. The aim of this study is to find the differences between learners’ and native speakers’ use of verbs and to study the factors that contribute to those differences. To this end, the research question is as follows: What are the differences between most frequently used verbs by learners and those by native speakers? The research question is answered through a study that uses corpus-based data-driven approach to analyze the verbs used by learners in their abstract writings in terms of collocation, colligation and semantic prosody. The results show that: (1) EFL learners obviously overused ‘be, can, find, make’ and underused ‘investigate, examine, may’. As to modal verbs, learners obviously overused ‘can’ while underused ‘may’. (2) Learners obviously overused ‘we find + object clauses’ while underused ‘nouns (results, findings, data) + suggest/indicate/reveal + object clauses’ when expressing research results. (3) Learners tended to transfer the collocation, colligation and semantic prosody of shǐ and zuò to make. (4) Learners obviously overused ‘BE+V-ed’ and used BE as the main verb. They also obviously overused the basic forms of BE such as be, is, are, while obviously underused its inflections (was, were). These results manifested learners’ lack of accuracy and idiomatic property in verb usage. Due to the influence of the concept transfer of Chinese, the verbs in learners’ abstracts showed obvious transfer of mother language. In addition, learners have not fully mastered the use of verbs, avoiding using complex colligations to prevent errors. Based on these findings, the present study has implications for English teaching, seeking to have implications for English academic abstract writing in China. Further research could be undertaken to study the use of verbs in the whole dissertation to find out whether the characteristic of the verbs in abstracts can apply in the whole dissertation or not.

Keywords: academic writing abstracts, Chinese EFL learners, corpus-based, data-driven, verbs

Procedia PDF Downloads 339

Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

Abstract:

The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

Procedia PDF Downloads 117

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Xiaofang Wei

Abstract:

Harmful Algal Blooms are a recurrent disturbing occurrence in Lake Erie that has caused significant negative impacts on water quality and aquatic ecosystem around Great Lakes areas in the United States. Targeting the recent HAB events in western Lake Erie, this paper utilizes satellite imagery and hydrological modeling to monitor HAB cyanobacteria blooms and analyze the impacts of agricultural activities from Maumee watershed, the biggest watershed of Lake Erie and agriculture dominant.SWAT (Soil & Water Assessment Tool) Model for Maumee watershed was established with DEM, land use data, crop data layer, soil data, and weather data, and calibrated with Maumee River gauge stations data for streamflow and nutrients. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) was applied to remove atmospheric attenuation and cyanobacteria Indices were calculated from Landsat OLI imagery to study the intensity of HAB events in the years 2015, 2017, and 2019. The agricultural practice and nutrients management within the Maumee watershed was studied and correlated with HAB cyanobacteria indices to study the relationship between HAB intensity and nutrient loadings. This study demonstrates that hydrological models and satellite imagery are effective tools in HAB monitoring and modeling in rivers and lakes.

Keywords: harmful algal bloom, landsat OLI imagery, SWAT, HAB cyanobacteria

Procedia PDF Downloads 180