Search results for: Scalable performance testing

Authors: Mahmoud A. Abdulhamid

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Poly(ether-ether-ketone) (PEEK) has received increased attention due to its outstanding performance in different membrane applications including gas and liquid separation. However, it suffers from a semi-crystalline morphology, bad solubility and low porosity. To fabricate membranes from PEEK, the usage of harsh acid such as sulfuric acid is essential, regardless its hazardous properties. In this work, we report the molecular design of poly(ether-ether-ketones) (iPEEKs) with intrinsic porosity character, by incorporating kinked units into PEEK backbone such as spirobisindane, Tröger's base, and triptycene. The porous polymers were used to fabricate stable membranes for organic solvent nanofiltration application. To better understand the mechanism, we conducted molecular dynamics simulations to evaluate the possible interactions between the polymers and the solvents. Notable enhancement in separation performance was observed confirming the importance of molecular engineering of high-performance polymers. The iPEEKs demonstrated good solubility in polar aprotic solvents, a high surface area of 205–250 m² g⁻¹, and excellent thermal stability. Mechanically flexible nanofiltration membranes were prepared from N-methyl-2-pyrrolidone dope solution at iPEEK concentrations of 19–35 wt%. The molecular weight cutoff of the membranes was fine-tuned in the range of 450–845 g mol⁻¹ displaying 2–6 fold higher permeance (3.57–11.09 L m⁻² h⁻¹ bar⁻¹) than previous reports. The long-term stabilities were demonstrated by a 7 day continuous cross-flow filtration.

Keywords: molecular engineering, polymer synthesis, membrane fabrication, liquid separation

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Authors: Assiya Madenovna Borsynbayeva, Kairat Altynbekovich Turgenbayev, Nikolay Petrovich Ivanov

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In this article presents the results of rapid diagnostics of tuberculosis in comparison with classical bacteriological method. The proposed method of rapid diagnosis of tuberculosis than bacteriological method allows shortening the time of diagnosis to 7 days, to visualize the growth of mycobacteria in the semi-liquid medium and differentiate the type of mycobacterium. Fast definition of Mycobacterium tuberculosis and its derivatives in the culture medium is a new and promising direction in the diagnosis of tuberculosis.

Keywords: animal diagnosis of tuberculosis, bacteriological diagnostics, antigen, specific antibodies, immunological reaction

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Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

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This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Kambiz Rasoulkhani, Jeanne Cole, Sybil Sharvelle, Ali Mostafavi

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Dual water distribution systems have been proposed as solutions to enhance the sustainability and resilience of urban water systems by improving performance and decreasing energy consumption. The objective of this study was to evaluate the long-term resilience and robustness of dual water distribution systems versus singular water distribution systems under various stressors such as demand fluctuation, aging infrastructure, and funding constraints. To this end, the long-term dynamics of these infrastructure systems was captured using a simulation model that integrates institutional agency decision-making processes with physical infrastructure degradation to evaluate the long-term transformation of water infrastructure. A set of model parameters that varies for dual and singular distribution infrastructure based on the system attributes, such as pipes length and material, energy intensity, water demand, water price, average pressure and flow rate, as well as operational expenditures, were considered and input in the simulation model. Accordingly, the model was used to simulate various scenarios of demand changes, funding levels, water price growth, and renewal strategies. The long-term resilience and robustness of each distribution infrastructure were evaluated based on various performance measures including network average condition, break frequency, network leakage, and energy use. An ecologically-based resilience approach was used to examine regime shifts and tipping points in the long-term performance of the systems under different stressors. Also, Classification and Regression Tree analysis was adopted to assess the robustness of each system under various scenarios. Using data from the City of Fort Collins, the long-term resilience and robustness of the dual and singular water distribution systems were evaluated over a 100-year analysis horizon for various scenarios. The results of the analysis enabled: (i) comparison between dual and singular water distribution systems in terms of long-term performance, resilience, and robustness; (ii) identification of renewal strategies and decision factors that enhance the long-term resiliency and robustness of dual and singular water distribution systems under different stressors.

Keywords: complex systems, dual water distribution systems, long-term resilience performance, multi-agent modeling, sustainable and resilient water systems

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Authors: A. Y. Purnama, N. Yasufuku

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The bridge structure is a building that has to be maintained, especially for the elastomeric bearing. The girder of the bridge needs to be lifted upward to maintain this elastomeric bearing, that needs high cost. Nowadays, integral abutment bridges are becoming popular. The integral abutment bridge is less costly because the elastomeric bearings are eliminated, which reduces the construction cost and maintenance costs. However, when this elastomeric bearing removed, the girder movement due to environmental thermal forces directly support by pile foundation, and it needs to be considered in the design. In case of pile foundation in a stiff soil, in the top area of the pile cannot move freely due to the fixed condition by soil stiffness. Pre-bored pile system can be used to increase the flexibility of pile foundation using a pre-bored hole that filled with elastic materials, but the behavior of soil-pile interaction and soil response due to this system is still rarely explained. In this paper, an experimental study using small-scale laboratory model test conducted in a half size model. Single flexible pile model embedded in sandy soil with the pre-bored ring, which filled with the filler material. The testing box made from an acrylic glass panel as observation area of the pile shaft to monitor the displacement of the pile during the lateral loading. The failure behavior of the soil inside the pre-bored ring and around the pile shaft was investigated to determine the point of pile rotation and the movement of this point due to the pre-bored ring system along the pile shaft. Digital images were used to capture the deformations of the soil and pile foundation during the loading from the acrylic glass on the side of the testing box. The results were presented in the form of lateral load resistance charts against the pile shaft displacement. The failure pattern result also established due to the cyclic lateral loading. The movement of the rotational point was measured due to the pre-bored system filled with appropriate filler material. Based on the findings, design considerations for pre-bored pile system due to cyclic lateral loading can be introduced.

Keywords: failure behavior, pre-bored pile system, cyclic lateral loading, sandy soil

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Authors: Saeed Ahmed, Tamoor Abbas, M. Amir, M. S. Iqbal, D. Hussain

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This study was conducted to evaluate the effect of supplementation of different levels of yeast culture (Saccharomyces cerevisiae) in Beetal male goats diets on growth performance, digestibility of nutrients and selected blood metabolites. Another objective was to determine the inclusion level of yeast culture for optimal growth performance of Beetal male goats. Eighteen (n=18) Beetal male goats were randomly assigned to three total mixed ration treatments (n=6 goats/treatment): T1, T2 and T3 containing 0gm, 3gm and 6gm/day yeast culture (YC) mixed with total mixed ration (TMR). The diets were iso-nitrogenous and iso-caloric having crude protein 15.2% and ME 2.6Mcal/kg. The total duration of the experiment was 8 weeks. Beetal bucks were fed on TMR diets (T1, T2 and T3) having blend of oat silage, Lucerne hay and concentrate mixed with yeast culture (YC). Bucks were housed individually and feed was offered @ 4% of body weight on dry matter basis. Samples of fresh feed and refusal were collected twice weekly of moisture percentage using hot air oven. Data for daily dry matter intake, body weight gain, nutrient digestibility and selected blood metabolites were analyzed through one-way ANOVA technique under Complete randomised design (SAS Institute Inc, 2002-03). Results were declared significant at P≤0.05. Overall, DMI was not affected (P≥0.05) by dietary treatments. Body weight gain, digestibility of crude protein and crude fibre were improved. Blood glucose concentration was detected higher in the group having supplementation of yeast culture (YC) 6gm/day compared to other two dietary treatments. This study suggested the positive impact of inclusion of yeast culture (YC) up to 6gm/day in the TMR diet for optimal growth performance and digestibility of nutrients in Beetal male goats.

Keywords: yeast culture, growth performance, digestibility, beetle goat

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Authors: Meng-Fei Cheng, Wei Fneg

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New Taiwan high school standards emphasize employing scientific models and modeling practices in physics learning. However, to our knowledge. Few studies address how scientific models and modeling are approached in current science teaching, and they do not examine the views of scientific models portrayed in the textbooks. To explore the views of scientific models and modeling in textbooks, this study investigated the atomic unit in different textbook versions as an example and provided suggestions for modeling curriculum. This study adopted a quantitative analysis of qualitative data in the atomic units of four mainstream version of Taiwan high school physics textbooks. The models were further analyzed using five dimensions of the views of scientific models (nature of models, multiple models, purpose of the models, testing models, and changing models); each dimension had three levels (low, medium, high). Descriptive statistics were employed to compare the frequency of describing the five dimensions of the views of scientific models in the atomic unit to understand the emphasis of the views and to compare the frequency of the eight scientific models’ use to investigate the atomic model that was used most often in the textbooks. Descriptive statistics were further utilized to investigate the average levels of the five dimensions of the views of scientific models to examine whether the textbooks views were close to the scientific view. The average level of the five dimensions of the eight atomic models were also compared to examine whether the views of the eight atomic models were close to the scientific views. The results revealed the following three major findings from the atomic unit. (1) Among the five dimensions of the views of scientific models, the most portrayed dimension was the 'purpose of models,' and the least portrayed dimension was 'multiple models.' The most diverse view was the 'purpose of models,' and the most sophisticated scientific view was the 'nature of models.' The least sophisticated scientific view was 'multiple models.' (2) Among the eight atomic models, the most mentioned model was the atomic nucleus model, and the least mentioned model was the three states of matter. (3) Among the correlations between the five dimensions, the dimension of 'testing models' was highly related to the dimension of 'changing models.' In short, this study examined the views of scientific models based on the atomic units of physics textbooks to identify the emphasized and disregarded views in the textbooks. The findings suggest how future textbooks and curriculum can provide a thorough view of scientific models to enhance students' model-based learning.

Keywords: atomic models, textbooks, science education, scientific model

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Authors: Thierry Sammour Sawaya, Heikki Deschacht

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In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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Authors: Bin Li, Mei Liu

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

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

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Shadab Shishegar, Sophie Duchesne, Genevieve Pelletier

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Sustainability as one of the key elements of Smart cities, can be realized by employing Real Time Control Strategies for city’s infrastructures. Nowadays Stormwater management systems play an important role in mitigating the impacts of urbanization on natural hydrological cycle. These systems can be managed in such a way that they meet the smart cities standards. In fact, there is a huge potential for sustainable management of urban stormwater and also its adaptability to global challenges like climate change. Hence, a dynamically managed system that can adapt itself to instability of the environmental conditions is desirable. A Global Predictive Real Time Control approach is proposed in this paper to optimize the performance of stormwater management basins in terms of flooding prevention. To do so, a mathematical optimization model is developed then solved using Genetic Algorithm (GA). Results show an improved performance at system-level for the stormwater basins in comparison to static strategy.

Keywords: environmental sustainability, optimization, real time control, storm water management

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Authors: Benjamin Mugisha Bugingo

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Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Leong Tatt Loh, Ming Kun Yew, Ming Chian Yew, Lip Huat Saw, Jing Han Beh, Siong Kang Lim, Foo Wei Lee

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Oil palm shell (OPS) is the solid waste product from the palm oil sector of the agricultural industry and can be used as alternative coarse aggregates to substitute depleting conventional raw materials. This research aims to investigate the incorporation of various high-performance polypropylene (HPP) fibres with different geometry to enhance the mechanical properties and thermal conductivity of OPS lightweight concrete. The effect of different volume fractions (Vf) (0.05%, 0.10% and 0.15%) were studied for each fibre. The results reveal that the effectiveness of HPP fibres to increase the compressive strength at later ages was more pronounced than at early age. It is found that the use of HPP fibres reinforced OPS lightweight concrete (LWC) induced the advantageous of improving mechanical properties (compressive strength, flexural strength and splitting tensile strength) and thermal conductivity. Hence, this HPP fibres is a promising alternative solution to compensate lower mechanical properties as well as contribute to energy efficiency building material in the construction industry.

Keywords: oil palm shell, high performance polypropylene fibre, lightweight concrete, mechanical properties, thermal conductivity

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Authors: H. Boucheloukh, N. Aoun, M. Denni, A. Mahrouk, T. Sehili

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Perovskite materials with strontium alkaline earth metal have attracted researchers in photocatalysis. Thus, nanocomposite-based strontium has been synthesized by the sol-gel method, calciened at 700 °C, and characterized by different methods such as X-ray difraction (DRX), Fourier transformed infrared (FTIR), and diffuse relectance spectroscopy (DRS). After that, the photocatlytic performance of SrNO3/SnO2 has been tested under sunlight in an aqueous solution for two dyes methylene blue and congo-red. The results reveal that 70% of methylene blue has already been degraded after 45 minutes of exposure to sun light, while 80% of Congo red has been eliminated by adsorption on SrSnO₃/SnO₂ in 120 minutes of contact.

Keywords: congo-red, methylene blue, photocatalysis, perovskite

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Authors: Ormal Lishi

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This research presents a computationally efficient probabilistic method to assess the performance of compartmentation walls with similar Fire Resistance Levels (FRL) but varying complexity. Specifically, a masonry brick wall and a light-steel framed (LSF) wall with comparable insulation performance are analyzed. A Monte Carlo technique, employing Latin Hypercube Sampling (LHS), is utilized to quantify uncertainties and determine the probability of failure for both walls exposed to standard and parametric fires, following ISO 834 and Eurocodes guidelines. Results show that the probability of failure for the brick masonry wall under standard fire exposure is estimated at 4.8%, while the LSF wall is 7.6%. These probabilities decrease to 0.4% and 4.8%, respectively, when subjected to parametric fires. Notably, the complex LSF wall exhibits higher variability in predicting time to failure for specific criteria compared to the less complex brick wall, especially at higher temperatures. The proposed approach highlights the need for Probabilistic Risk Assessment (PRA) to accurately evaluate the reliability and safety levels of complex designs.

Keywords: design complexity, probability of failure, monte carlo analysis, compartmentation walls, insulation

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Authors: I. Gusti Agung Aditya Surya Wibawa, Andri Syafriya, Beiruny Syam

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Gumai Formation which acts as regional seal for Talang Akar Formation becomes one of the most prolific reservoir in South Sumatra Basin and the primary exploration target in this area. Marine conditions were eventually established during the continuation of transgression sequence leads an open marine facies deposition in Early Miocene. Marine clastic deposits where calcareous shales, claystone and siltstones interbedded with fine-grained calcareous and glauconitic sandstones are the domination of lithology which targeted as the hydrocarbon reservoir. All this time, the main objective of PetroChina’s exploration and production in Betara area is only from Lower Talang Akar Formation. Successful testing in some exploration wells which flowed gas & condensate from Gumai Formation, opened the opportunity to optimize new reservoir objective in Betara area. Limitation of conventional wireline logs data in Gumai interval is generating technical challenge in term of geological approach. A utilization of Gas While Drilling indicator initiated with the objective to determine the next Gumai reservoir candidate which capable to increase Jabung hydrocarbon discoveries. This paper describes how Gas While Drilling indicator is processed to generate potential and non-potential zone by cut-off analysis. Validation which performed by correlation and comparison with well logs, Drill Stem Test (DST), and Reservoir Performance Monitor (RPM) data succeed to observe Gumai reservoir in Betara Complex. After we integrated all of data, we are able to generate a Betara Complex potential map and overlaid with reservoir characterization distribution as a part of risk assessment in term of potential zone presence. Mud log utilization and geophysical data information successfully covered the geological challenges in this study.

Keywords: Gumai, gas while drilling, classification, reservoir, potential

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Authors: Kristel Faye Tandog

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The State Owned Enterprise (SOE) or also called Public Enterprise (PE) has been playing a vital role in a country’s social and economic development. Following this idea, this study focused on the Factor Structures of Financial Performance of the Local Economic Enterprises (LEEs) namely: Food Court, Market, Slaughterhouse, and Terminal in Matalam, Cotabato. It aimed to determine the profile of the LEEs in terms of organizational structure, manner of creation, years in operation, source of initial operating requirements, annual operating budget, geographical location, and size or description of the facility. This study also included the different financial ratios of LEE that covered a five year period from Calendar Year 2009 to 2013. Primary data using survey questionnaire was administered to 468 respondents and secondary data were sourced out from the government archives and financial documents of the said LGU. There were 12 dominant factors identified namely: “management”, “enforcement of laws”, “strategic location”, “existence of non-formal competitors”, “proper maintenance”, “pricing”, “customer service”, “collection process”, “rentals and services”, “efficient use of resources”, “staffing”, and “timeliness and accuracy”. On the other hand, the financial performance of the LEE of Matalam, Cotabato using financial ratios needs reformatting. This denotes that refinement as to the following ratios: Cash Flow Indicator, Activity, Profitability and Growth is necessary. The cash flow indicator ratio showed difficulty in covering its debts in successive years. Likewise, the activity ratios showed that the LEE had not been effective in putting its investment at work. Moreover, profitability ratios revealed that it had operated in minimum capacity and had incurred net losses and thus, it had a weak profit performance. Furthermore, growth ratios showed that LEE had a declining growth trend particularly in net income.

Keywords: factor structures, financial performance, financial ratios, state owned enterprises

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Authors: Nishitha Chowdary, Prabhav Dwivedi

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Solar radiation (or insolation) is responsible for 174 petawatts (PW) of energy reaching the Earth's atmosphere. About one-third of this is reflected in space. Solar energy is by far the most abundant source of energy on Earth. In this study to use solar energy to the fullest in a solar air heater, An analysis of a solar air heater duct roughened with fixed cylindrical ribs in 3-D has been done using CFD. These fixed cylindrical ribs have a uniform circular cross-section and are placed in transverse in-line and staggered arrangements. The orientation of ribs has been fixed and is perpendicular to the in-flow direction. Cylindrical ribs are arranged periodically with fixed pitch; therefore, one pitch length is only considered in the present study. Validation has been done with smooth as well as with roughened duct and is matched perfectly with the developed correlations. Geometric parameters, namely rib height (e), ranges from 1 to 2 mm and pitch ranges from 10 to 40 mm are used in the present investigation. Thermo-hydraulic performance parameters in terms of average Nusselt number and friction factor have been extracted for Reynolds number ranging 5000—18000 to optimize the performance of roughened duct.

Keywords: cylindrical ribs, solar air heater, thermo-hydraulic performance factor, roughened duct

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Authors: Aniketh Ravukutam, Rajath Rao M., Pradyumna S. A.

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In the past few decades there has been great advancement in use of aerodynamics in cars. Now its use has been evident from commercial cars to race cars for achieving higher speeds, stability and efficiency. This paper focusses on studying the effects of aerodynamics in Formula Student car. These cars weigh around 200kgs with an average speed of 60kmph. With increasing competition every year, developing a competitive car is a herculean task. The race track comprises mostly of tight corners and little or no straights thus testing the car’s cornering capabilities. Higher cornering speeds can be achieved by increasing traction at the tires. Studying the aerodynamics helps in achieving higher traction without much addition in overall weight of car. The main focus is to develop an aerodynamic package involving front wing, under tray and body to obtain an optimum value of down force. The initial process involves the detail study of geometrical constraints mentioned in the rule book and calculating the limiting value of drag as per the engine specifications. The successive steps involve conduction of various iterations in ANSYS for selection of airfoils, deciding the number of elements, designing the nose for low drag, channelizing the flow under the body and obtain an optimum value of down force within the limits defined in the initial process. The final step involves design of model using these results in Virtual environment called OptimumLap® for detailed study of performance with and without the presence of aerodynamics. The CFD analysis results showed an overall down force of 377.44N with a drag of 164.08N. The corresponding parameters of the last model were applied in OptimumLap® and an improvement of 3.5 seconds in lap times was observed.

Keywords: aerodynamics, formula student, traction, front wing, undertray, body, rule book, drag, down force, virtual environment, computational fluid dynamics (CFD)

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Authors: Rute Faria, Digo Moraes, Amanda Santos, Dione Morais, Maria Sartori

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Seed vigor is a fundamental component for the good performance of the entire soybean production process. Seeds with mechanical damage at harvest time will be more susceptible to fungal and insect attack during storage, which will invariably reduce their vigor to the field, compromising uniformity and final stand performance. Harvesters, even the most modern ones, when not properly regulated or operated, can cause irreversible damages to the seeds, compromising even their commercialization. Therefore, the control of an efficient harvest is necessary in order to guarantee a good quality final product. In this work, the damage caused by two different harvesters (one rented, and another one) was evaluated, traveling in two speeds (4 and 8 km / h). The design was completely randomized in 2 x 2 factorial, with four replications. To evaluate the physiological quality seed germination and vigor tests were carried out over a period of six months. A multivariate analysis of Principal Components (PCA) and clustering allowed us to verify that the leased machine had better performance in the incidence of immediate damages in the seeds, but after a storage period of 6 months the vigor of these seeds reduced more than own machine evidencing that such a machine would bring more damages to the seeds.

Keywords: Glycine max (L.), cluster analysis, PCA, vigor

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: Joseph Osodo, Motsa Thobekani Phila

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The study investigated the impact of e-learning on the performance of history learners in Eswatini general certificate of secondary education in the Manzini region of Eswatini. The study was guided by the theory of connectivism. The study had three objectives which were to find out the significance of e-learning during the COVID-19 era in learning History subject; challenges faced by history teachers’ and learners’ in e-learning; and how the challenges were mitigated. The study used a qualitative research approach and descriptive research design. Purposive sampling was used to select eight History teachers and eight History learners from four secondary schools in the Manzini region. Data were collected using face to face interviews. The collected data were analyzed and presented in thematically. The findings showed that history teachers had good knowledge on what e-learning was, while students had little understanding of e-learning. Some of the forms of e-learning that were used during the pandemic in teaching history in secondary schools included TV, radio, computer, projectors, and social media especially WhatsApp. E-learning enabled the continuity of teaching and learning of history subject. The use of e-learning through the social media was more convenient to the teacher and the learners. It was concluded that in some secondary school in the Manzini region, history teacher and learners encountered challenges such as lack of finances to purchase e-learning gadgets and data bundles, lack of skills as well as access to the Internet. It was recommended that History teachers should create more time to offer additional learning support to students whose performance was affected by the COVID-19 pandemic effects.

Keywords: e-learning, performance, COVID-19, history, connectivism

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Authors: Xiaoqin Wang, Li Yin

Abstract:

Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

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Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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Authors: Polina Prokopovich

Abstract:

Despite the well-established dependence of cartilage mechanical properties on the frequency of the applied load, most research in the field is carried out in either load-free or constant load conditions because of the complexity of the equipment required for the determination of time-dependent properties. These simpler analyses provide a limited representation of cartilage properties thus greatly reducing the impact of the information gathered hindering the understanding of the mechanisms involved in this tissue replacement, development and pathology. More complex techniques could represent better investigative methods, but their uptake in cartilage research is limited by the highly specialised training required and cost of the equipment. There is, therefore, a clear need for alternative experimental approaches to cartilage testing to be deployed in research and clinical settings using more user-friendly and financial accessible devices. Frequency dependent material properties can be determined through rheometry that is an easy to use requiring a relatively inexpensive device; we present how a commercial rheometer can be adapted to determine the viscoelastic properties of articular cartilage. Frequency-sweep tests were run at various applied normal loads on immature, mature and trypsinased (as model of osteoarthritis) cartilage samples to determine the dynamic shear moduli (G*, G′ G″) of the tissues. Moduli increased with increasing frequency and applied load; mature cartilage had generally the highest moduli and GAG depleted samples the lowest. Hydraulic permeability (KH) was estimated from the rheological data and decreased with applied load; GAG depleted cartilage exhibited higher hydraulic permeability than either immature or mature tissues. The rheometer-based methodology developed was validated by the close comparison of the rheometer-obtained cartilage characteristics (G*, G′, G″, KH) with results obtained with more complex testing techniques available in literature. Rheometry is relatively simpler and does not require highly capital intensive machinery and staff training is more accessible; thus the use of a rheometer would represent a cost-effective approach for the determination of frequency-dependent properties of cartilage for more comprehensive and impactful results for both healthcare professional and R&D.

Keywords: tissue, rheometer, biomaterial, cartilage

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Authors: Konstantinos G. Papaioannou, Panagiotis K. Serdaris

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This study, examines the level of implementation of Human Resource Management (HRM) activities in law enforcement agencies in Greece. Recognizing that HRM is crucial for maximizing organizational performance, the study aims to evaluate its application within Greek law enforcement. A quantitative-descriptive survey was conducted, involving 996 executives from Greek Law Enforcement Agencies (477 from the Hellenic Police and 519 from the Hellenic Coast Guard), through random sampling. The survey, revealed significant concerns regarding the minimal implementation of HRM practices, in both agencies. The findings indicate that HRM practices, such as HR planning, recruitment, job position, selection, training and development, personnel management, compensation, labor relations and health and safety, are minimally applied. Neither the Hellenic Police nor the Hellenic Coast Guard appears to follow a comprehensive HRM plan. The study, contributes both theoretically and practically by highlighting the lack of HRM implementation in these agencies. The data suggest that by adopting strategic HRM practices, these organizations can enhance personnel performance and better fulfill their societal roles. Future research should extend to law enforcement agencies in other countries to draw more representative conclusion.

Keywords: coastguard, human resources management, law enforcement agencies, performance management, police

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Authors: Junaid Bin Aamir, Ma Fanhua

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Methanol and hydrogen are the most suitable alternative fuel resources for the existing and future internal combustion engines. This paper experimentally examined the effects of hydrogen addition on the performance and emission characteristics of a spark-ignition engine fueled with methanol at part load conditions. The experiments were carried out for various engine speeds and loads. Hydrogen-rich syngas was used to enhance the performance of the test engine. It was formed by catalytic dissociation of methanol itself, and volumetric hydrogen fraction in syngas was about 67%. A certain amount of syngas dissociated from methanol was injected into the intake manifold in each engine cycle, and the low heating value (LHV) of hydrogen-rich syngas used was 4% of methanol in each cycle. Both the fuels were injected separately using port fuel injectors. The results showed that brake thermal efficiency of the engine was enhanced by 3-5% with hydrogen addition, while brake specific fuel consumption and exhaust gas temperature were reduced. There was a significant reduction (90-95%) in THC and (35-50%) in CO emissions at the exhaust. NOx emissions from hydrogen blended methanol increased slightly (10-15%), but they can be reduced by using lean fuel-air mixture to keep the cylinder temperature low.

Keywords: hydrogen, methanol, alternative fuel, emissions, spark ignition engines

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Authors: Toni Raurich-Marcet, Joan Llonch-Andreu

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This research is focused on the relationship between Search Engine Marketing (SEM) and traditional advertising. The dominant assumption is that SEM does not help brand awareness and only does it in session as if it were the cost of manufacturing the product being sold. The study is methodologically developed using an experiment where the effects were determined to analyze the billboard effect. The research allowed the cross-linking of theoretical and empirical knowledge on digital marketing. This paper has validated this marketing generates retention as traditional advertising would by measuring brand awareness and its improvements. This changes the way performance and brand campaigns are split within marketing departments, effectively rebalancing budgets moving forward.

Keywords: attribution, performance marketing, SEM, marketplaces

Procedia PDF Downloads 125