Search results for: optimal bias techniques

Authors: Mustafa Ural, Can Bayseferogulari

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In this work, radio frequency (RF) coupling between two HF antennas on a shipboard platform is minimized by determining an optimal antenna placement. Unlike the other works, the coupling is minimized not only at single frequency but over the whole frequency band of operation. Similarly, GAO and PSO, are used in order to determine optimal antenna placement. Throughout this work, outputs of two optimization techniques are compared with each other in terms of antenna placements and coupling results. At the end of the work, far-field radiation pattern performances of the antennas at their optimal places are analyzed in terms of directivity and coverage in order to see that.

Keywords: electromagnetic compatibility, antenna placement, optimization, genetic algorithm optimization, particle swarm optimization

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Authors: Ahmad Al-Omari, Osama Khreis, Ahmad M. K. Dagamseh, Abdullah Ababneh, Kevin Lear

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High-speed infrared vertical-cavity surface-emitting laser diodes (VCSELs) with Cu-plated heat sinks were fabricated and tested. VCSELs with 10 mm aperture diameter and 4 mm of electroplated copper demonstrated a -3dB modulation bandwidth (f_-3dB) of 14 GHz and a resonance frequency (f_R) of 9.5 GHz at a bias current density (J_bias) of only 4.3 kA/cm², which corresponds to an improved f_-3dB²/J_bias ratio of 44 GHz²/kA/cm². At higher and lower bias current densities, the f_-3dB²/ J_bias ratio decreased to about 30 GHz²/kA/cm² and 18 GHz²/kA/cm², respectively. Examination of the analogue modulation response demonstrated that the presented VCSELs displayed a steady f_-3dB/ f_R ratio of 1.41±10% over the whole range of the bias current (1.3I_th to 6.2I_th). The devices also demonstrated a maximum modulation bandwidth (f_{-3dB max}) of more than 16 GHz at a bias current less than the industrial bias current standard for reliability by 25%.

Keywords: current density, high-speed VCSELs, modulation bandwidth, small-signal characteristics, thermal impedance, vertical-cavity surface-emitting lasers

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Authors: Koustav Pal, Indranil Das

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In recent times, perovskite and double perovskite (DP) systems attracts lot of interest as they provide a rich material platform for studying emergent functionalities like near-room-temperature ferromagnetic (FM) insulators, exchange bias (EB), magnetocaloric effects, colossal magnetoresistance, anisotropy, etc. These interesting phenomena emerge because of complex couplings between spin, charge, orbital, and lattice degrees of freedom in these systems. Various magnetic phenomena such as exchange bias, spin glass, memory effect, colossal magneto-resistance, etc. can be modified and controlled through antisite (B-site) disorder or controlling oxygen concentration of the material. By controlling oxygen concentration in SrFe0.5Co0.5O3 – δ (SFCO) (δ ∼ 0.3), we achieve intrinsic exchange bias effect with a large exchange bias field (∼1.482 Tesla) and giant coercive field (∼1.454 Tesla). Now we modified the B-site by introducing 10% iridium in the system. This modification give rise to the exchange bias field as high as 1.865 tesla and coercive field 1.863 tesla. Our work aims to investigate the effect of oxygen deficiency and B-site effect on exchange bias in oxide materials for potential technological applications. Structural characterization techniques including X-ray diffraction, scanning tunneling microscopy, and transmission electron microscopy were utilized to determine crystal structure and particle size. X-ray photoelectron spectroscopy was used to identify valence states of the ions. Magnetic analysis revealed that oxygen deficiency resulted in a large exchange bias due to a significant number of ionic mixtures. Iridium doping was found to break interaction paths, resulting in various antiferromagnetic and ferromagnetic surfaces that enhance exchange bias.

Keywords: coercive field, disorder, exchange bias, spin glass

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Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

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This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

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Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder bias voltage, switching voltage, radio-over-fiber, RF gain

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Authors: Jou-An Chung

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The purpose of this study is to investigate the verb bias of the Mandarin verbs in children’s reading materials and provide the criteria for categorization. Verb bias varies cross-linguistically. As Mandarin and English are typological different, this study hopes to shed light on Mandarin verb bias with the use of corpus and provide thorough and detailed criteria for analysis. Moreover, this study focuses on children’s reading materials since it is a significant issue in understanding children’s sentence processing. Therefore, investigating verb bias of Mandarin verbs in children’s reading materials is also an important issue and can provide further insights into children’s sentence processing. The small corpus is built up for this study. The corpus consists of the collection of school textbooks and Mandarin Daily News for children. The files are then segmented and POS tagged by JiebaR (Chinese segmentation with R). For the ease of analysis, the one-word character verbs and intransitive verbs are excluded beforehand. The total of 20 high frequency verbs are hand-coded and are further categorized into one of the three types, namely DO type, SC type and other category. If the frequency of taking Other Type exceeds the threshold of 25%, the verb is excluded from the study. The results show that 10 verbs are direct object bias verbs, and six verbs are sentential complement bias verbs. The paired T-test was done to assure the statistical significance (p = 0.0001062 for DO bias verb, p=0.001149 for SC bias verb). The result has shown that in children’s reading materials, the DO biased verbs are used more than the SC bias verbs since the simplest structure of sentences is easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child's reading materials but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context. Sentences are easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child corpus, but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context.

Keywords: corpus linguistics, verb bias, child language, psycholinguistics

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Authors: Sumachaya Harnsukworapanich, Tetsuo Ichimori

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The apportionment method is used by many countries, to calculate the distribution of seats in political bodies. For example, this method is used in the United States (U.S.) to distribute house seats proportionally based on the population of the electoral district. Famous apportionment methods include the divisor methods called the Adams Method, Dean Method, Hill Method, Jefferson Method and Webster Method. Sometimes the results from the implementation of these divisor methods are unfair and include errors. Therefore, it is important to examine the optimization of this method by using a bias measurement to figure out precise and fair results. In this research we investigate the bias of divisor methods in the U.S. Houses of Representatives toward large and small states by applying the Stolarsky Mean Method. We compare the bias of the apportionment method by using two famous bias measurements: The Balinski and Young measurement and the Ernst measurement. Both measurements have a formula for large and small states. The Third measurement however, which was created by the researchers, did not factor in the element of large and small states into the formula. All three measurements are compared and the results show that our measurement produces similar results to the other two famous measurements.

Keywords: apportionment, bias, divisor, fair, measurement

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Authors: Katie Strong, Brian P. O'Connor, Jacqueline M. Kanippayoor

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To date, self-report measures of psychopathy have largely been conceptualized with a male-focused understanding of the disorder, with the presumption that psychopathy expression is uniform across genders. However, generalizing this understanding to the female population may be misleading. The objective of this research was to explore gender differences in the expression of psychopathy and to assess current self-report psychopathy measures for gender bias. It was hypothesized that some items in commonly used measures of psychopathy may show gender bias and that existing measures may not contain enough items that are relevant to the manifestation of psychopathy in women. An exploratory investigation was conducted on statistical bias in common measures of psychopathy, and novel, relevant, but previously neglected items and measures were included in a new data collection. The participant pool included a sample of 403 university students and 354 participants recruited using Amazon Mechanical Turk. Item Response Theory methods - including Differential Item Functioning - were used to assess for the item- and test- level bias across several common self-report measures of psychopathy. Analyses indicated occasional and modest levels of item-level bias, and that some additional female-relevant items merit consideration for inclusion in measures of psychopathy. These findings suggest that current self-report measures of psychopathy may be demonstrating gender-bias and warrant further examination.

Keywords: gender, measurement bias, personality, psychopathy

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Kellina Craig-Henderson

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Today, there is increased attention to the role of social perceptions in the selection, hiring, and management of employees and the evaluation and promotion of students. In some contexts, where women or members of certain social groups have been historically underrepresented there is evidence that these perceptions reflect the implicit biases people harbor. Research in the social and psychological sciences reveals that implicit biases against women unfairly disadvantage them in academic and work settings. This presentation will provide an overview of the current state of knowledge on an implicit bias as well as the problems associated with it. How employers, educators and other evaluators can inoculate themselves from the pernicious effects of these biases will be considered.

Keywords: gender equity, implicit bias, social psychology, unconscious bias

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Abdelaziz Rabehi

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The current–voltage (I–V) characteristics of Au/GaN Schottky diodes were measured at room temperature. In addition, capacitance–voltage–frequency (C–V–f) characteristics are investigated by considering the interface states (Nss) at frequency range 100 kHz to 1 MHz. From the I–V characteristics of the Schottky diode, ideality factor (n) and barrier height (Φb) values of 1.22 and 0.56 eV, respectively, were obtained from a forward bias I–V plot. In addition, the interface states distribution profile as a function of (Ess − Ev) was extracted from the forward bias I–V measurements by taking into account the bias dependence of the effective barrier height (Φe) for the Schottky diode. The C–V curves gave a barrier height value higher than those obtained from I–V measurements. This discrepancy is due to the different nature of the I–V and C–V measurement techniques.

Keywords: Schottky diodes, frequency dependence, barrier height, interface states

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks

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Authors: Adriana Avila Zuniga Nordfjeld

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This paper provides a literature review to document the state of the art with respect to handling 'human bias' in decision making within the established quality management systems (QMS) and LEAN theory, in the context of shipbuilding. Previous research shows that in shipbuilding there is a huge deviation from the planned man-hours under the project management to the actual man-hours used because of errors in planning and reworks caused by human bias in the information flows among others. This reduces the efficiency and increases operational costs. Thus, the research question is how QMS and LEAN handle biases. The findings show the gap in studying the integration of methods to handle human bias in decision making into QMS and lean, not only within shipbuilding but also in general. Theoretical and practical implications are discussed for researchers and practitioners in the areas of decision making QMS, LEAN, and future research is suggested.

Keywords: human bias, decision making, LEAN shipbuilding, quality management systems

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Authors: Reza Aghayan

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This paper illustrates that numerically invariant joint signatures suffer biases in the resulting signatures. Next, we classify the arising biases as Bias Type 1 and Bias Type 2 and show how they can be removed.

Keywords: Euclidean and affine geometries, differential invariant signature curves, numerically invariant joint signatures, numerical analysis, numerical bias, curve analysis

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Authors: Amir Mahdavi

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In this paper a highly linear CMOS low noise amplifier (LNA) for ultra-wideband (UWB) applications is proposed. The proposed LNA uses a linearization technique to improve second and third-order intercept points (IIP3). The linearity is cured by repealing the common-mode section of all intermodulation components from the cascade topology current with optimization of biasing current use symmetrical and asymmetrical circuits for biasing. Simulation results show that maximum gain and noise figure are 6.9dB and 3.03-4.1dB over a 3.1–10.6 GHz, respectively. Power consumption of the LNA core and IIP3 are 2.64 mW and +4.9dBm respectively. The wideband input impedance matching of LNA is obtained by employing a degenerating inductor (|S11|<-9.1 dB). The circuit proposed UWB LNA is implemented using 0.18 μm based CMOS technology.

Keywords: highly linear LNA, low-power LNA, optimal bias techniques

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Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

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The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

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Authors: Sang Wook Park, Se Woon Choi, Yousok Kim, Byung Kwan Oh, Hyo Seon Park

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Various retrofit techniques for reinforced concrete frame with infill wall have been steadily developed. Among those techniques, strengthening methodology based on diagonal FRP strips (FRP bracings) has numerous advantages such as feasibility of implementing without interrupting the building under operation, reduction of cost and time, and easy application. Considering the safety of structure and retrofit cost, the most appropriate retrofit solution is needed. Thus, the objective of this study is to suggest pareto-optimal solution for existing building using FRP bracings. To find pareto-optimal solution analysis, NSGA-II is applied. Moreover, the seismic performance of retrofit building is evaluated. The example building is 5-storey, 3-bay RC frames with infill wall. Nonlinear static pushover analyses are performed with FEMA 356. The criterion of performance evaluation is inter-story drift ratio at the performance level IO, LS, CP. Optimal retrofit solutions is obtained for 32 individuals and 200 generations. Through the proposed optimal solutions, we confirm the improvement of seismic performance of the example building.

Keywords: retrofit, FRP bracings, reinforced concrete frame with infill wall, seismic performance evaluation, NSGA-II

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Authors: Helen J. Spray, Karina J. Linnell

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Local-global bias in adulthood is strongly dependent on environmental factors and a global bias is not the universal characteristic of adult perception it was once thought to be: whilst Western adults typically demonstrate a global bias, Namibian adults living in traditional villages possess a strong local bias. Furthermore, environmental effects on local-global bias have been shown to be highly gender-specific; whereas urbanisation promoted a global bias in urbanised Namibian women but not men, education promoted a global bias in urbanised Namibian men but not women. Adult populations, however, provide only a snapshot of the gene-environment interactions which shape perceptual bias. Yet, to date, there has been little work on the development of local-global bias across environmental settings. In the current study, local-global bias was assessed using a similarity-matching task with Navon figures in children aged between 4 and 15 years from across three populations: traditional Namibians, urban Namibians, and urban British. For the two Namibian groups, measures of urbanisation and education were obtained. Data were subjected to both between-group and within-group analyses. Between-group analyses compared developmental trajectories across population and gender. These analyses revealed a global bias from even as early as 4 in the British sample, and showed that the developmental onset of a global bias is not fixed. Urbanised Namibian children ultimately developed a global bias that was indistinguishable from British children; however, a global bias did not emerge until much later in development. For all populations, the greatest developmental effects were observed directly following the onset of formal education. No overall gender effects were observed; however, there was a significant gender by age interaction which was difficult to reconcile with existing biological-level accounts of gender differences in the development of local-global bias. Within-group analyses compared the effects of urbanisation and education on local-global bias for traditional and urban Namibian boys and girls separately. For both traditional and urban boys, education mediated all effects of age and urbanisation; however, this was not the case for girls. Traditional Namibian girls retained a local bias regardless of age, education, or urbanisation, and in urbanised girls, the development of a global bias was not attributable to any one factor specifically. These results are broadly consistent with aforementioned findings that education promoted a global bias in urbanised Namibian men but not women. The development of local-global bias does not follow a fixed trajectory but is subject to environmental control. Understanding how variability in the development of local-global bias might arise, particularly in the context of gender, may have far-reaching implications. For example, a number of educationally important cognitive functions (e.g., spatial ability) are known to show consistent gender differences in childhood and local-global bias may mediate some of these effects. With education becoming an increasingly prevalent force across much of the developing world it will be important to understand the processes that underpin its effects and their implications.

Keywords: cross-cultural, development, education, gender, local-global bias, perception, urbanisation, urbanization

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Authors: X. L. Zhou, S. Tunmee, I. Toda, K. Komatsu, S. Ohshio, H. Saitoh

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Hydrogenated amorphous carbon (a-C:H) films have been synthesized by a radio frequency plasma enhanced chemical vapor deposition (rf-PECVD) technique with different bias voltage from 0.0 to -0.5 kV. The Raman spectra displayed the polymer-like hydrogenated amorphous carbon (PLCH) film with 0.0 to -0.1 and a-C:H films with -0.2 to -0.5 kV of bias voltages. The surface chemical information of all films were studied by X-ray photo electron spectroscopy (XPS) technique, presented to C-C (sp2 and sp3) and C-O bonds, and relative carbon (C) and oxygen (O) atomics contents. The O contamination had affected on structure and optical properties. The true density of PLCH and a-C:H films were characterized by X-ray refractivity (XRR) method, showed the result as in the range of 1.16-1.73 g/cm3 that depending on an increasing of bias voltage. The hardness was proportional to the true density of films. In addition, the optical properties i.e. refractive index (n) and extinction coefficient (k) of these films were determined by a spectroscopic ellipsometry (SE) method that give formation to in 1.62-2.10 (n) and 0.04-0.15 (k) respectively. These results indicated that the optical properties confirmed the Raman results as presenting the structure changed with applied bias voltage increased.

Keywords: negative bias voltage, a-C:H film, oxygen contamination, optical properties

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Authors: Sedigheh Samimian, Sadra Ashrafi, Tahereh Khaleghdoost Mohammadi, Mohammad Reza Yeganeh, Ali Ashraf, Hamideh Hakimi, Maryam Dehghani

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Introduction: The recommended position for measuring Intra-Abdominal Pressure (IAP) is the supine position. However, patients put in this position are prone to Ventilator-associated pneumonia. This study was done to evaluate the relationship between bed head angle and IAP measurements of intubated patients in the intensive care unit. Methods: In this clinical trial, seventy-six critically ill patients under mechanical ventilation were enrolled. IAP measurement was performed every 8 hours for 24 hours using the KORN method in three different degrees of the head of bed (HOB) elevation (0°, 15°, and 30°). Bland-Altman analysis was performed to identify the bias and limits of agreement among the three HOBs. According to World Society of the Abdominal Compartment Syndrome (WSACS), we can consider two IAP techniques equivalent if a bias of <1 mmHg and limits of agreement of - 4 to +4 were found between them. Data were analyzed using SPSS statistical software (v. 19), and the significance level was considered as 0.05. Results: The prevalence of intra-abdominal hypertension was 18.42%. Mean ± standard deviation (SD) of IAP were 8.44 ± 4.02 mmHg for HOB angle 0°, 9.58 ± 4.52 for HOB angle 15°, and 11.10 ± 4.73 for HOB angle 30o (p = 0.0001). The IAP measurement bias between HOB angle 0◦ and HOB angle 15° was 1.13 mmHg. This bias was 2.66 mmHg between HOB angle 0° and HOB angle 30°. Conclusion: Elevation of HOB angle from 0 to 30 degree significantly increases IAP. It seems that the measurement of IAP at HOB angle 15° was more reliable than 30°.

Keywords: pressure, intra-abdominal hypertension, head of bed, critical care, compartment syndrome, supine position

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Authors: Susanna Menis

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‘Unconscious’ bias is widespread, affecting society on all levels of decision-making and beyond. Placed in the law context, this study will explore the direct effect of the psycho-social and cultural evolution of unconscious bias on how a judicial decision was made. The aim of this study is to contribute to socio-legal scholarship by examining the formation of unconscious bias and its influence on the creation of legal rules that judges believe reflect social solidarity and protect against violence. The study seeks to understand how concepts like criminalization and unlawfulness are constructed by the common law. The study methodology follows two theoretical approaches: historical genealogy and emotions as sociocultural phenomena. Both methods have the ‘tracing back’ of the original formation of a social way of seeing and doing things in common. The significance of this study lies in the importance of reflecting on the ways unconscious bias may be formed; placing judges’ decisions under this spotlight forces us to challenge the status quo, interrogate justice, and seek refinement of the law.

Keywords: legal geneology, emotions, disgust, criminal law

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Authors: Nelson Bii, Christopher Ouma, John Odhiambo

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Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

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Authors: Zain Ul Abideen

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The study examines the potentially dark and bright parts of behavioral biases in investors’ investment decisions in the Pakistani equity market. These biases, directly and indirectly, play a comprehensive role in controlling and deciding the investor’s investment decisions. Stock market anomalies are used as a mediator, while financial literacy is used as a moderator to check the mentioned relationship. The sample consisted of investors who have trading experience of more than two years in the stock market. The result indicates that calendar anomalies do not mediate between overconfidence bias and investment decisions. However, the study investigates the mediating role of fundamental and technical anomalies between overconfidence bias and investment decisions. Furthermore, calendar anomalies play a significant role between the disposition effect and investment decisions. Calendar anomalies also mediate between herding bias and investment decisions. Financial literacy significantly moderates between behavioral biases and stock market anomalies. This research would be beneficial for individual and professional investors in their investment decisions. They should be financially literate, consequently less biased and have no market anomalies. Investors in emerging and developed economies can make optimal decisions in their respective stock markets.

Keywords: behavioral biases, financial literacy, stock market anomalies, investment decision

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Authors: Arnab Majumdar, Srimani Sen

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In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p⁺pnn⁺ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×10⁸ A/m². The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×10⁸ A/m².

Keywords: cubic ZnB-GaN, hexagonal 4H-SiC, double drift impatt diode, millimetre wave, optimised bias current density, wide band gap semiconductor

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Authors: Kittipob Kondee, Chutima Prommak

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In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

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Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

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Authors: M. Moradi Dalini, M. R. Talebi

Abstract:

This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.

Keywords: econometrics, multiobjective optimization, management problem, optimization

Procedia PDF Downloads 47

Authors: Keyao Li, Sai On Cheung

Abstract:

Incorporation of alternative dispute resolution (ADR) mechanism has been the main feature of current trend of construction project dispute resolution (CPDR). ADR approaches have been identified as efficient mechanisms and are suitable alternatives to litigation and arbitration. Moreover, the use of ADR in this multi-tiered dispute resolution process often leads to repeated evaluations of a same dispute. Multi-tiered CPDR may become a breeding ground for cognitive biases. When completed knowledge is not available at the early tier of construction dispute resolution, disputing parties may form preconception of the dispute matter or the counterpart. This preconception would influence their information processing in the subsequent tier. Disputing parties tend to search and interpret further information in a self-defensive way to confirm their early positions. Their imbalanced information collection would boost their confidence in the held assessments. Their attitudes would be hardened and difficult to compromise. The occurrence of cognitive bias, therefore, impedes efficient dispute settlement. This study aims to explore ways to minimize bias in CPDR. Based on a comprehensive literature review, three types of bias minimizing approaches were collected: strategy-based, attitude-based and process-based. These approaches were further operationalized into bias minimizing measures. To verify the usefulness and practicability of these bias minimizing measures, semi-structured interviews were conducted with ten CPDR third party neutral professionals. All of the interviewees have at least twenty years of experience in facilitating settlement of construction dispute. The usefulness, as well as the implications of the bias minimizing measures, were validated and suggested by these experts. There are few studies on cognitive bias in construction management in general and in CPDR in particular. This study would be the first of its type to enhance the efficiency of construction dispute resolution by highlighting strategies to minimize the biases therein.

Keywords: bias, construction project dispute resolution, minimization, multi-tiered, semi-structured interview

Procedia PDF Downloads 154