Search results for: sensing performance

Authors: N. Chayaopas, W. Assawinchaichote

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In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: doubly fed induction generator, H-infinity fuzzy integral control, linear matrix inequality, wind energy system

Procedia PDF Downloads 347

Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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Cloud computing and virtualization technology have brought an innovative way for people to develop and use software nowadays. However, conventional virtualization comes at the expense of performance loss for applications. Container-based virtualization could be an option as it potentially reduces overhead and minimizes performance decline of the service platform. In this paper, we introduce a system framework and present an implementation of resource broker for dynamic cloud service deployment on the container-based platform to facilitate the efficient execution and improve the utilization. We target the load-aware service deployment approach for task ranking scenario. This proposed effort can collaborate with resource management system to adaptively deploy services according to the different requests. In particular, our approach relies on composing service immediately onto appropriate container according to user’s requirement in order to conserve the waiting time. Our evaluation shows how efficient of the service deployment is and how to expand its applicability to support the variety of cloud service.

Keywords: cloud computing, container-based virtualization, resource broker, service deployment

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Authors: Jinjoo Jung, Hayeon Won, Doyeong Jeong, Do Hyung Kim

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We present the electrochemical and electrochromic performance of the novel crystalline tungsten oxide and tungsten-molybdenum oxide nanostructures synthesized by utilizing solvo-thermal method with hexacarbonyl tungsten, hexacarbonyl molybdenum, and ethyl alcohol. The morphology and phase of the prepared products were highly dependent on the synthesis conditions such as synthesis and annealing temperature, synthesis time, and precursor ratio. The tungsten oxide nanostructures (TCNs) have urchin-like or spherical nanostructure with different phase of W18O49 and WO3. The morphology of tungsten-molybdenum oxide nanostructures (TMONs) is basically similar to that of TCNs. However, the morphology and phase of TMONs are more diverse and are strongly dependent on the composition ratios of W/Mo in the precursor. The electrochemical properties depending on their morphologies and phases of TCNs and TMONs are compared using cyclic voltammetry and galvanostatic charge/discharge tests. The relationship between the electrochromic performance and phase structures/morphologies of nanostructured TCNs and TMONs are systematically investigated.

Keywords: electrochemical, electrochromic, tungsten oxide, tungsten-molybdenum oxide

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Authors: Umamaheswari Shanmugam, Silvia Ronchi, Radu Vornicu

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that are able to use the large amount and variety of data generated during healthcare services every day. As we read the news, over 500 machine learning or other artificial intelligence medical devices have now received FDA clearance or approval, the first ones even preceding the year 2000. One of the big advantages of these new technologies is the ability to get experience and knowledge from real-world use and to continuously improve their performance. Healthcare systems and institutions can have a great benefit because the use of advanced technologies improves the same time efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and also to protect patients’ safety. The evolution and the continuous improvement of software used in healthcare must take into consideration the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device approval, but they are necessary to ensure performance, quality, and safety, and at the same time, they can be a business opportunity if the manufacturer is able to define in advance the appropriate regulatory strategy. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems.

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Authors: Sadaf Zahra Usman

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Business Incubation has become a pervasive phenomenon in numerous parts of the world and is seen as a tool for creating a startup ecosystem. The reason for greatest barriers to the advancement of business incubation centers is the need for an entrepreneurial ecosystem and underdeveloped financial assistance and angel investor networks for startup firms. Business incubation helps in creating successful startup ventures by providing administrative support services and assistance in creating their ventures. We identify incubators into three categories: University incubation centers (UICs), Private incubators (PICs), and Government incubator centers (GICs) to measure the influence of different types of business incubation practices and their performance by using a survey questionnaire from incubation managers across Pakistan. The analysis is conducted on eight Business incubators. Results suggest that the quality of incubation centers is extremely important in this regard. The research anticipated helping policymakers, government officials, and incubation management to utilize business incubation more effectively to “hatch” innovation-based entrepreneurial development.

Keywords: entrepreneurship, unemployment, startups, economy, business incubation practice

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Authors: Hisham Mousa Mohammed Ahmed, Ahmed Wali Mohamed Salad, Yousif Hamed Dldom Gomaa

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A drip or Trickle irrigation system is designed to apply a precise amount of water near the plant with a certain degree of uniformity. This study was conducted at the Experimental Farm of the Faculty of Agricultural Sciences, University of Gezira, in March 2018. The study aimed to design and evaluate the hydraulic performance of three drip emitter types using: average discharge (Qavg), discharge variation (Qvar %), coefficient of uniformity (CU %), coefficient of manufacturer variation (CV %), distribution uniformity (DU %), statistical uniformity (Us %), clogging (%) wetted diameter (cm) and wetted depth (cm). The emitter types used are regular gauges (RG), high compensating pressure (HCP) and low compensating pressure (LCP). The treatments were laid out in a randomized complete block design (RCBD) with four replications. Results showed that there were significant differences (P≤0.05) in all tested parameters except clogging, wetted diameter and wetted depth. Discharge variation (Qvar %) values were 12.71, 15.57 and 19.17 for RG, LCP, and HCP, respectively. The variation is quite good and within the acceptable range. Results of coefficient of manufacture variation (CV %) were 10.9, 27.8 and 52.7 for RG, LCP and HCP, respectively. It is considered within the unacceptable range except for RG type, which is excellent. Statistical uniformity (Us %) values were 89.1, 72.2 and 45.7 for RG, LCP and HCP, respectively. It is considered good, acceptable and unacceptable, respectively. Results of the coefficient of uniformity (CU %) were 91.3, 77.7 and 56.7 for RG, LCP and HCP, respectively. It is considered excellent, fair and unacceptable, respectively. Distribution uniformity (DU %) was 90.2, 67.9 and 36.5 for RG, LCP and HCP, respectively. It is considered excellent, poor and poor, respectively. The study recommended regular gauges (RG) type emitters under the heavy clay soil conditions of the Gezira State, Sudan.

Keywords: drip irrigation, uniformity, clogging, coefficient, performance

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Authors: Huseyi̇n Das, Bülent Tarim, Sunay Demi̇r, Nurçi̇n Küçükkent, Sevi̇l Cengi̇z, Engi̇n Tülek, Veci̇hi̇ Aksakal

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Atak-S laying hens are a high-performance strain obtained by crossing of the Rhode Island Red (RIR) X the Barred Plymouth Rock (BR) and are being produced in the Ankara Poultry Research Institute since 1997. Phenotypic and genetic improving studies are continued for this strain. In this study, 2 from IGF and 1 from IGFBP2, totally 3 different SNP polymorphisms were examined in 200 Atak-S chickens. Genotypes of SNPs were compared using ANOVA to body weight and egg number thorough 32 weeks of age, body weight at sexual maturity, age at sexual maturity and also egg quality traits such as egg shell breaking strength, shell thickness, Haugh unit, albumen index, yolk index, shape index. Only IGF(a) locus was in agreement with Hardy-Weinberg equilibrium, while, the other loci were not. As a result of the performance comparisons to the 3 SNP loci, it was determined that there has a significant association (P<0.05) between only TC genotypes of the IGF(b) locus and body weight at 32 weeks of age, but there was not any association to the other traits.

Keywords: Atak-S, Igf, Igfbp2, single nucleotide polymorphism

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Authors: Mangana B. Rampheri, Timothy Dube, Farai Dondofema, Tatenda Dalu

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Identifying and delineating groundwater-dependent ecosystems (GDEs) is critical to the well understanding of the GDEs spatial distribution as well as groundwater allocation. However, this information is inadequately understood due to limited available data for the most area of concerns. Thus, this study aims to address this gap using remotely sensed, analytical hierarchy process (AHP) and in-situ data to identify and delineate GDEs in Khakea-Bray Transboundary Aquifer. Our study developed GDEs index, which integrates seven explanatory variables, namely, Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Land-use and landcover (LULC), slope, Topographic Wetness Index (TWI), flow accumulation and curvature. The GDEs map was delineated using the weighted overlay tool in ArcGIS environments. The map was spatially classified into two classes, namely, GDEs and Non-GDEs. The results showed that only 1,34 % (721,91 km2) of the area is characterised by GDEs. Finally, groundwater level (GWL) data was used for validation through correlation analysis. Our results indicated that: 1) GDEs are concentrated at the northern, central, and south-western part of our study area, and 2) the validation results showed that GDEs classes do not overlap with GWL located in the 22 boreholes found in the given area. However, the results show a possible delineation of GDEs in the study area using remote sensing and GIS techniques along with AHP. The results of this study further contribute to identifying and delineating priority areas where appropriate water conservation programs, as well as strategies for sustainable groundwater development, can be implemented.

Keywords: analytical hierarchy process (AHP), explanatory variables, groundwater-dependent ecosystems (GDEs), khakea-bray transboundary aquifer, sentinel-2

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Authors: Hamid Aslani, Ahmed Radwan

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In this paper, a single element microstrip antenna is presented for UWB applications by using techniques as partial ground plane and modified the shape of the patch. The antenna is properly designed to have a compact size and constant gain against frequency. The simulated results have done using two EM software and show good agreement with the measured results for the fabricated antenna. Then a designing of two elements patch antenna array for UWB in the frequency band of 3.1-10 GHz is presented in this paper. The array is constructed by means of feeding two omni-directional modified circular patch elements with a modified power divider. Experimental results show that the array has a stable radiation pattern and low return loss over a broad bandwidth of 64% (3.1–10 GHz). Due to its planar profile, physically compact size, wide impedance bandwidth, directive performance over a wide bandwidth proposed antenna is a good candidate for portable UWB applications and other UWB integrated circuits.

Keywords: ultra wide band, radiation performance, microstrip antenna, size miniaturized antenna

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Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

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In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

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Authors: Leila Ayat, Afak Meftah

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Amorphous-silicon alloys have great promise as low cost solar cell materials. They have excellent photo-conductivity and high optical absorption to sunlight. Now PIN a-Si:H based solar cells are widely used in power generation modules. However, to improve the performance of these cells further, a better fundamental under-standing of the factors limiting cell performance in the homo junction PIN structure is necessary. In this paper we discuss the sensitivity of light J-V characteristics to various device and material parameters in PIN homo junction solar cells. This work is a numerical simulation of the output parameters of a PIN a-Si:H solar cell under AM1.5 spectrum. These parameters are the short circuit current (Jsc), the open circuit voltage (Voc), the fill factor (FF), the conversion efficiency. The simulation was performed with SCAPS-1D software version 3.3 developed at ELIS in Belgium by Marc Burgelman et al. The obtained results are in agreement with experiment. In addition, the effect of the thickness, doping density, capture cross sections of the gap states and the band microscopic mobilities on the output parameters of the cell are also presented.

Keywords: amorphous silicon p-i-n junctions, thin film, solar cells, sensitivity

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Authors: Maomao Cao

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Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer.

Keywords: liver cancer, ctDNA methylation, detection, diagnostic performance

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Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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Authors: Hong Lu, Wei Fan, Yongquan Zhang, Junbo Zhang

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A cross coupling sliding synchronization control strategy is proposed for the dual-driving feed system. This technology will minimize the position error oscillation and achieve the precise synchronization performance in the high speed and high precision drive system, especially some high speed and high precision machine. Moreover, a cross coupling compensation matrix is provided to offset the mismatched disturbance and the disturbance observer is established to eliminate the chattering phenomenon. Performance comparisons of proposed dual-driving cross coupling sliding mode control (CCSMC), normal cross coupling control （CCC） strategy with PID control, and electronic virtual main shaft control (EVMSC) strategy with SMC control are investigated by simulation and a dual-driving control system; the results show the effectiveness of the proposed control scheme.

Keywords: cross coupling matrix, dual motors, synchronization control, sliding mode control

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Chun-Han Li, Tien-Fu Yang, Chen-Yu Chen, Wei-Mon Yan

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The conventional dehumidification method in air-conditioning system mostly utilizes a cooling coil to remove the moisture in the air via cooling the supply air down below its dew point temperature. During the process, it needs to reheat the supply air to meet the set indoor condition that consumes a considerable amount of energy and affect the coefficient of performance of the system. If the processes of dehumidification and cooling are separated and operated respectively, the indoor conditions will be more efficiently controlled. Therefore, decoupling the dehumidification and cooling processes in heating, ventilation and air conditioning system is one of the key technologies as membrane dehumidification processes for the next generation. The membrane dehumidification method has the advantages of low cost, low energy consumption, etc. It utilizes the pore size and hydrophilicity of the membrane to transfer water vapor by mass transfer effect. The moisture in the supply air is removed by the potential energy and driving force across the membrane. The process can save the latent load used to condense water, which makes more efficient energy use because it does not involve heat transfer effect. In this work, the performance measurements including the permeability and selectivity of water vapor and air with the composite and commercial membranes were conducted. According to measured data, we can choose the suitable dehumidification membrane for designing the flow channel length and components of the planar dehumidifier. The vacuum membrane dehumidification system was set up to examine the effects of temperature, humidity, vacuum pressure, flow rate, the coefficient of performance and other parameters on the dehumidification efficiency. The results showed that the commercial Nafion membrane has better water vapor permeability and selectivity. They are suitable for filtration with water vapor and air. Meanwhile, Nafion membrane has promising potential in the dehumidification process.

Keywords: vacuum membrane dehumidification, planar membrane dehumidifier, water vapour and air permeability, air conditioning

Procedia PDF Downloads 147

Authors: Farzana Esmailkassam, Usakorn Kunanuvat, Zahraa Mohammed Ali

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Objective: The key barrier in Clozapine treatment of treatment-resistant schizophrenia (TRS) includes frequent bloods draws to monitor neutropenia, the main drug side effect. WBC and ANC monitoring must occur throughout treatment. Accurate WBC and ANC counts are necessary for clinical decisions to halt, modify or continue clozapine treatment. The CSAN Pronto point-of-care (POC) analyzer generates white blood cells (WBC) and absolute neutrophils (ANC) through image analysis of capillary blood. POC monitoring offers significant advantages over central laboratory testing. This study evaluated the performance of the CSAN Pronto against the Beckman DxH900 Hematology laboratory analyzer. Methods: Forty venous samples (EDTA whole blood) with varying concentrations of WBC and ANC as established on the DxH900 analyzer were tested in duplicates on three CSAN Pronto analyzers. Additionally, both venous and capillary samples were concomitantly collected from 20 volunteers and assessed on the CSAN Pronto and the DxH900 analyzer. The analytical performance including precision using liquid quality controls (QCs) as well as patient samples near the medical decision points, and linearity using a mix of high and low patient samples to create five concentrations was also evaluated. Results: In the precision study for QCs and whole blood, WBC and ANC showed CV inside the limits established according to manufacturer and laboratory acceptability standards. WBC and ANC were found to be linear across the measurement range with a correlation of 0.99. WBC and ANC from all analyzers correlated well in venous samples on the DxH900 across the tested sample ranges with a correlation of > 0.95. Mean bias in ANC obtained on the CSAN pronto versus the DxH900 was 0.07× 109 cells/L (95% L.O.A -0.25 to 0.49) for concentrations <4.0 × 109 cells/L, which includes decision-making cut-offs for continuing clozapine treatment. Mean bias in WBC obtained on the CSAN pronto versus the DxH900 was 0.34× 109 cells/L (95% L.O.A -0.13 to 0.72) for concentrations <5.0 × 109 cells/L. The mean bias was higher (-11% for ANC, 5% for WBC) at higher concentrations. The correlations between capillary and venous samples showed more variability with mean bias of 0.20 × 109 cells/L for the ANC. Conclusions: The CSAN pronto showed acceptable performance in WBC and ANC measurements from venous and capillary samples and was approved for clinical use. This testing will facilitate treatment decisions and improve clozapine uptake and compliance.

Keywords: absolute neutrophil counts, clozapine, point of care, white blood cells

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

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Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Sheela Tiwari, R. Naresh, R. Jha

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The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Suitable low global warming potential (GWP) refrigerants that conform to F-gas regulations are required to extend the operational envelope of high-temperature heat pumps (HTHPs) used for industrial waste heat recovery processes. The thermophysical properties and characteristics of these working fluids need to be assessed to provide a comprehensive understanding of operational effectiveness in HTHP applications. This paper presents the results of a theoretical simulation to investigate a range of low-GWP refrigerants and their suitability to supersede refrigerants HFC-245fa and HFC-365mfc. A steady-state thermodynamic model of a single-stage HTHP with an internal heat exchanger (IHX) was developed to assess system cycle characteristics at temperature ranges between 50 to 80 °C heat source and 90 to 150 °C heat sink. A practical approach to maximize the operational efficiency was examined to determine the effects of regulating minimum superheat within the process and subsequent influence on energetic and exergetic efficiencies. A comprehensive map of minimum superheat across the HTHP operating variables were used to assess specific tipping points in performance at 30 and 70 K temperature lifts. Based on initial results, the refrigerants HCFO-1233zd(E) and HFO-1336mzz(Z) were found to be closely aligned matches for refrigerants HFC-245fa and HFC-365mfc. The overall results show effective performance for HCFO-1233zd(E) occurs between 5-7 K minimum superheat, and HFO-1336mzz(Z) between 18-21 K dependant on temperature lift. This work provides a method to optimize refrigerant selection based on operational indicators to maximize overall HTHPs system performance.

Keywords: high-temperature heat pump, minimum superheat, energy & exergy efficiency, low GWP refrigerants

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Iyad Al-Attar

Abstract:

Air filters installed in HVAC equipment and gas turbine for power generation confront several atmospheric contaminants with various concentrations while operating in different environments (tropical, coastal, hot). This leads to engine performance degradation, as contaminants are capable of deteriorating components and fouling compressor assembly. Compressor fouling is responsible for 70 to 85% of gas turbine performance degradation leading to reduction in power output and availability and an increase in the heat rate and fuel consumption. Therefore, filter design must take into account face velocities, pleat count and its corresponding surface area; to verify filter performance characteristics (Efficiency and Pressure Drop). The experimental work undertaken in the current study examined two groups of four filters with different pleating densities were investigated for the initial pressure drop response and fractional efficiencies. The pleating densities used for this study is 28, 30, 32 and 34 pleats per 100mm for each pleated panel and measured for ten different flow rates ranging from 500 to 5000 m3/h with increment of 500m3/h. This experimental work of the current work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase in face velocity and pleat density. The reasons that led to surface area losses of filtration media are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. It is evident from entire array of experiments that as the particle size increases, the efficiency decreases until the MPPS is reached. Beyond the MPPS, the efficiency increases with increase in particle size. The MPPS shifts to a smaller particle size as the face velocity increases, while the pleating density and orientation did not have a pronounced effect on the MPPS. Throughout the study, an optimal pleat count which satisfies initial pressure drop and efficiency requirements may not have necessarily existed. The work has also suggested that a valid comparison of the pleat densities should be based on the effective surface area that participates in the filtration action and not the total surface area the pleat density provides.

Keywords: air filters, fractional efficiency, gas cleaning, glass fibre, HEPA filter, permeability, pressure drop

Procedia PDF Downloads 135

Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Lucas Caldas, Pablo Paulse, Karla Hora

Abstract:

Shipping containers are present in different Brazilian cities, firstly used for transportation purposes, but which become waste materials and an environmental burden in their end-of-life cycle. In the last decade, in Brazil, some buildings made partly or totally from shipping containers started to appear, most of them for commercial and office uses. Although the use of a reused container for buildings seems a sustainable solution, it is very important to measure the thermal and energy aspects when they are used as such. In this context, this study aims to evaluate the thermal and energy performance of an office building totally made from a 12-meter-long, High Cube 40’ shipping container in different Brazilian Bioclimatic Zones. Four different constructive solutions, mostly used in Brazil were chosen: (1) container without any covering; (2) with internally insulated drywall; (3) with external fiber cement boards; (4) with both drywall and fiber cement boards. For this, the DesignBuilder with EnergyPlus was used for the computational simulation in 8760 hours. The EnergyPlus Weather File (EPW) data of six Brazilian capital cities were considered: Curitiba, Sao Paulo, Brasilia, Campo Grande, Teresina and Rio de Janeiro. Air conditioning appliance (split) was adopted for the conditioned area and the cooling setpoint was fixed at 25°C. The coefficient of performance (CoP) of air conditioning equipment was set as 3.3. Three kinds of solar absorptances were verified: 0.3, 0.6 and 0.9 of exterior layer. The building in Teresina presented the highest level of energy consumption, while the one in Curitiba presented the lowest, with a wide range of differences in results. The constructive option of external fiber cement and drywall presented the best results, although the differences were not significant compared to the solution using just drywall. The choice of absorptance showed a great impact in energy consumption, mainly compared to the case of containers without any covering and for use in the hottest cities: Teresina, Rio de Janeiro, and Campo Grande. This study brings as the main contribution the discussion of constructive aspects for design guidelines for more energy-efficient container buildings, considering local climate differences, and helps the dissemination of this cleaner constructive practice in the Brazilian building sector.

Keywords: bioclimatic zones, Brazil, shipping containers, thermal and energy performance

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Authors: Meghan E. Murray, Carri R. Tolmie

Abstract:

This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

Procedia PDF Downloads 127

Authors: Shamsulhaq Amin

Abstract:

Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agriculture, hydrological

Procedia PDF Downloads 41

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

Abstract:

Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

Procedia PDF Downloads 176

Authors: Van Diem Thi, Mourad Khelifa, Mohammed El Ganaoui, Yann Rogaume

Abstract:

An efficient numerical method has been developed to incorporate the effects of heat transfer in timber panels on partition walls exposed to real building fires. The procedure has been added to the software package Abaqus/Standard as a user-defined subroutine (UMATHT) and has been verified using both time-and spatially dependent heat fluxes in two- and three-dimensional problems. The aim is to contribute to the development of simulation tools needed to assist structural engineers and fire testing laboratories in technical assessment exercises. The presented method can also be used under the developmental stages of building components to optimize performance in real fire conditions. The accuracy of the used thermal properties and the finite element models was validated by comparing the predicted results with three different available fire tests in literature. It was found that the model calibrated to results from standard fire conditions provided reasonable predictions of temperatures within assemblies exposed to real building fire.

Keywords: Timber panels, heat transfer, thermal properties, standard fire tests

Procedia PDF Downloads 342

Authors: Jatinder Kumar, Ajay Bansal

Abstract:

Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

Procedia PDF Downloads 585