Search results for: patch-based similarity metric

Authors: D. B. Gohil

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Closed die forging is a very complex process, and measurement of actual forces for real material is difficult and time consuming. Hence, the modelling technique has taken the advantage of carrying out the experimentation with the proper model material which needs lesser forces and relatively low temperature. The results of experiments on the model material then may be correlated with the actual material by using the theory of similarity. There are several methods available to resolve the complexity involved in the closed die forging process. Finite Element Method (FEM) and Finite Difference Method (FDM) are relatively difficult as compared to the slab method. The slab method is very popular and very widely used by the people working on shop floor because it is relatively easy to apply and reasonably accurate for most of the common forging load requirement computations.

Keywords: experimentation, forging, process modeling, strain distribution

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Authors: Wei Zhang, Lifen Zhao

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The present study aims to translate and validate the Career Motivation Scale among Chinese university and vocational college teachers. Exploratory factor analysis supported a three-factor structure that was consistent with the original structure of career motivation: career insight, career identity, and career resilience. Confirmatory factor analysis showed that a second-order three-factor model with correlated measurement errors best fit the data. Configural, metric, and scalar invariance models were tested, demonstrating that the Chinese version of the Career Motivation Scale did not differ across groups of school type, educational level, and working years in current institutions. The concurrent validity of the Chinese Career Motivation Scale was confirmed by its significant correlations with work engagement, career adaptability, career satisfaction, job crafting, and intention to quit. The results of the study indicated that the Chinese Career Motivation Scale was a valid and reliable measure of career motivation among university and vocational college teachers in China.

Keywords: career motivation scale, Chinese University, vocational college teachers, measurement invariance, validation

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

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Authors: Luv Sharma

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Sex determination has been the most intriguing puzzle for forensic pathologists and anthropologists, for which efforts have been made for a long. Sexual dimorphism is well established in the adult pelvis, and it is known to provide the highest level of information about sexual dimorphism. This study was conducted to know whether this dimorphism exists in fetal bones or not. A total of 34 pairs of fetal pelvis bones (22 males and 12 Females), ages ranging from 4 months to full term, were collected from unidentified dead fetuses brought to the Department of Forensic Medicine for routine medicolegal autopsies to study for sexual dimorphism in the Department of Anatomy, Pt. BD Sharma PGIMS, Rohtak. Samples were divided into 2 age groups, and various metric parameters were recorded with the help of a digital vernier caliper. Data obtained was subjected to descriptive and discriminant functional analysis. Results of Descriptive and Discriminant Functional Analysis showed that sex determination can be done with 100% accuracy by using different combinations of parameters of fetal ilium. This study illustrates that sexual dimorphism exists from early fetal life after mid-pregnancy; it can be clearly established by discriminant functional analysis.

Keywords: Ilium, fetus, sex determination, morphometric

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Authors: Mohamad Sakizadeh, Fatemeh Mehrabi Sharafabadi, Hadi Ghorbani

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Concentrations of Cr and Ni in 97 plant samples (belonged to eight different plant species) and the associated soil groups were considered in this study. The amounts of Ni in soil groups fluctuated between 26.8 and 36.8 mgkg⁻¹ whereas the related levels of chromium ranged from 67.7 to 94.3mgkg⁻¹. The index of geoaccumulation indicated that 87 percents of the studied soils for chromium and 98.8 percents for nickel are located in uncontaminated zone. The results of Mann-Whitney U-test proved that agricultural practices have not significantly influenced the values of Ni and Cr. In addition, tillage had also little impact on the Ni and Cr transfer in the surface soil. Ni showed higher accumulation and soil-to-plant transfer factor compared with that of chromium in the studied plants. There was a high similarity between the accumulation pattern of Cr and Fe in most of the plant species.

Keywords: bioconcentration factor, chromium, geoaccumulation index, nickel

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Authors: William Wong Xiu Shun, Yoonjin Hyun, Mingyu Kim, Seongi Choi, Namgyu Kim

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Recently, the demand of extracting the R&D keywords from the issues and using them in retrieving R&D information is increasing rapidly. But it is hard to identify the related issues or to distinguish them. Although the similarity between the issues cannot be identified, but with the R&D lexicon, the issues that always shared the same R&D keywords can be determined. In details, the R&D keywords that associated with particular issue is implied the key technology elements that needed to solve the problem of the particular issue. Furthermore, the related issues that sharing the same R&D keywords can be showed in a more systematic way through the issue clustering constructed from the perspective of R&D. Thus, sharing of the R&D result and reusable of the R&D technology can be facilitated. Indirectly, the redundancy of investment on the same R&D can be reduce as the R&D information can be shared between those corresponding issues and reusability of the related R&D can be improved. Therefore, a methodology of constructing an issue clustering from the perspective of common R&D keywords is proposed to satisfy the demands mentioned.

Keywords: clustering, social network analysis, text mining, topic analysis

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Authors: Pia I. Hautamäki

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Sales has changed. Selling has taken on aspects of relationship marketing and sales force play a critical role in developing long-term relationships between buyers and sellers which is seen to serve the company’s targets and create success for a long run. The purpose of this study was to examine what really matters in buyer-seller encounters and determine what expectations business buyers have. We studied 17 business buyers by a qualitative interview. We found that buyers appreciate encounters where the salesperson face the buyer as a way he or she is as a person, identificate the real needs to improve buyers’ business and build up cooperation for long-term relationship. This study show that personality matters are a key elements when satisfying business buyers’ expectations.

Keywords: business buyer-seller encounters, customer expectations, perceived similarity, personal selling, personality types

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Authors: N. Zarikian

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Comparative analysis of the fauna of two families of butterflies (Lepidoptera: Rhopalocera) – Hesperiidae and Nymphalidae were carried out. In general, 122 species of the families are recorded. among these 33 species belong to Hesperiidae and 89 to Nymphalidae. The numbers by countries are as follows: 72 species are found in Syria (including 24 Hesperiidae and 48 Nymphalidae) and 97 in Armenia (26 and 71 species, respectively). Two species of Hesperiidae are reported for Syrian fauna for the first time and one species is newly recorded for Armenia. From the species above mentioned 38 are common both for Syria and Armenia. For estimation of the similarity of faunas studied were used the Jaccard index. By families the index is rather different, consisting for Hesperiidae 0.5151 and for Nymphalidae 0.337.

Keywords: Armenia, fauna, Hesperiidae, Nymphalidae, (Rhopalocera: Lepidoptera), Syria

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Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: L. Todorovska, E. Sivevska, B. Dejanova, J. Pluncevic, S. Petrovska, V. Antevska, S. Mancevska, I. Karadjozova

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Objective: The aim of this longitudinal study was to describe anthropometric and performance characteristics and to explore their differences between senior football (F) and basketball (B) players. Subjects and methods: 25 F (aged 23±2.5 y) and 25 B (aged 22±4.2 y) from Macedonian national teams and elite sport clubs were annually tested during 2 consecutive years. Full anthropometric profiles (stature, weight, five circumferences, four bone diameters, seven skin-folds and nine calculated parameters with standard formulas) were collected. Body composition was determined with InBody720 System. Physical capacity was tested with ergo metric test of Bruce (Custo med GmbH, Germany). Results: B were taller (p<0.001) and heavier (p<0.01), but leaner (p<0.001). F had higher percentage of muscle mass (p<0.01) and body fat (p< 0.001). F had higher VO2max (p<0.05) and lower hard rate (p<0.01). The differences in physical performance were not significant (p>0.05) within the groups during the 2-years period. Conclusions: These results suggest that there are distinct differences in anthropometric profile between Macedonian senior football and basketball players during the two competitive seasons.

Keywords: anthropometry, basketball players, football players, Macedonia

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Authors: Jamal A. Gledan, Othman A. Azzeidani

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During the last decade, Libya established a new Geodetic Datum called Libyan Geodetic Datum 2006 (LGD 2006) by using GPS, whereas the ground traversing method was used to establish the last Libyan datum which was called the Europe Libyan Datum 79 (ELD79). The current research paper introduces ELD79 to LGD2006 coordinate transformation technique, the accurate comparison of transformation between multiple regression equations and the three-parameters model (Bursa-Wolf). The results had been obtained show that the overall accuracy of stepwise multi regression equations is better than that can be determined by using Bursa-Wolf transformation model.

Keywords: geodetic datum, horizontal control points, traditional similarity transformation model, unconventional transformation techniques

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Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Ashkan Golgoon, Souhayl Sadik, Arash Yavari

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Eigenstrains in nonlinear solids are created due to anelastic effects such as non-uniform temperature distributions, growth, remodeling, and defects. Eigenstrains understanding is indispensable, as they can generate residual stresses and strongly affect the overall response of solids. Here, we study the residual stress and deformation fields of an incompressible isotropic infinite wedge with a circumferentially-symmetric distribution of finite eigenstrains. We construct a material manifold, whose Riemannian metric explicitly depends on the eigenstrain distribution, thereby we turn the problem into a classical nonlinear elasticity problem, where we find an embedding of the Riemannian material manifold into the ambient Euclidean space. In particular, we find exact solutions for the residual stress and deformation fields of a neo-Hookean wedge having a symmetric inclusion with finite radial and circumferential eigenstrains. Moreover, we numerically solve a similar problem when a symmetric Mooney-Rivlin inhomogeneity with finite eigenstrains is placed in a neo-Hookean wedge. Generalization of the eigenstrain problem to other geometries are also discussed.

Keywords: finite eigenstrains, geometric mechanics, inclusion, inhomogeneity, nonlinear elasticity

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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Authors: Abhijith Asok

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This paper presents a generalized approach for the simple linear data transformation, Y=bX, through an integration of multidimensional coordinate geometry, vector space theory and polygonal geometry. The scaling is performed by adding an additional ’Dummy Dimension’ to the n-dimensional data, which helps plot two dimensional component-wise straight lines on pairs of dimensions. The end result is a set of scaled extensions of observations in any of the 2n spatial divisions, where n is the total number of applicable dimensions/dataset variables, created by shifting the n-dimensional plane along the ’Dummy Axis’. The derived scaling factor was found to be dependent on the coordinates of the common point of origin for diverging straight lines and the plane of extension, chosen on and perpendicular to the ’Dummy Axis’, respectively. This result indicates the geometrical interpretation of a linear data transformation and hence, opportunities for a more informed choice of the factor ’b’, based on a better choice of these coordinate values. The paper follows on to identify the effect of this transformation on certain popular distance metrics, wherein for many, the distance metric retained the same scaling factor as that of the features.

Keywords: data transformation, dummy dimension, linear transformation, scaling

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Authors: Hamad Almohamadi, Abdulrahman AlKassem, Majed Alamoudi

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Dumping Aluminum (Al) waste into landfills causes several health and environmental problems. The pyrolysis process could treat Al waste to produce AlCl₃ and H₂. Using the Aspen Plus software, a techno-economic and feasibility assessment has been performed for Al waste pyrolysis. The Aspen Plus simulation was employed to estimate the plant's mass and energy balance, which was assumed to process 100 dry metric tons of Al waste per day. This study looked at two cases of Al waste treatment. The first case produces 355 tons of AlCl₃ per day and 9 tons of H₂ per day without recycling. The conversion rate must be greater than 50% in case 1 to make a profit. In this case, the MSP for AlCl₃ is $768/ton. The plant would generate $25 million annually if the AlCl₃ were sold at $1000 per ton. In case 2 with recycling, the conversion has less impact on the plant's profitability than in case 1. Moreover, compared to case 1, the MSP of AlCl₃ has no significant influence on process profitability. In this scenario, if AlCl₃ were sold at $1000/ton, the process profit would be $58 million annually. Case 2 is better than case 1 because recycling Al generates a higher yield than converting it to AlCl₃ and H₂.

Keywords: aluminum waste, aspen plus, process modelling, fast pyrolysis, techno-economic assessment

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Authors: Mustapha Rilwan Adewale, Salau Ayobami Muhammed

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This study focuses on the heat transfer analysis of magneto-hydrodynamics (MHD) squeezing flow between parallel disks, considering a viscous incompressible fluid. The upper disk exhibits both upward and downward motion, while the lower disk remains stationary but permeable. By employing similarity transformations, a system of nonlinear ordinary differential equations is derived to describe the flow behavior. To solve this system, a numerical approach, namely the Chebyshev collocation method, is utilized. The study investigates the influence of flow parameters and compares the obtained results with existing literature. The significance of this research lies in understanding the heat transfer characteristics of MHD squeezing flow, which has practical implications in various engineering and industrial applications. By employing the similarity transformations, the complex governing equations are simplified into a system of nonlinear ordinary differential equations, facilitating the analysis of the flow behavior. To obtain numerical solutions for the system, the Chebyshev collocation method is implemented. This approach provides accurate approximations for the nonlinear equations, enabling efficient computations of the heat transfer properties. The obtained results are compared with existing literature, establishing the validity and consistency of the numerical approach. The study's major findings shed light on the influence of flow parameters on the heat transfer characteristics of the squeezing flow. The analysis reveals the impact of parameters such as magnetic field strength, disk motion amplitude, fluid viscosity on the heat transfer rate between the disks, the squeeze number(S), suction/injection parameter(A), Hartman number(M), Prandtl number(Pr), modified Eckert number(Ec), and the dimensionless length(δ). These findings contribute to a comprehensive understanding of the system's behavior and provide insights for optimizing heat transfer processes in similar configurations. In conclusion, this study presents a thorough heat transfer analysis of magneto-hydrodynamics squeezing flow between parallel disks. The numerical solutions obtained through the Chebyshev collocation method demonstrate the feasibility and accuracy of the approach. The investigation of flow parameters highlights their influence on heat transfer, contributing to the existing knowledge in this field. The agreement of the results with previous literature further strengthens the reliability of the findings. These outcomes have practical implications for engineering applications and pave the way for further research in related areas.

Keywords: squeezing flow, magneto-hydro-dynamics (MHD), chebyshev collocation method(CCA), parallel manifolds, finite difference method (FDM)

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Authors: Worrapol Koranuntachai, Tonkid Chantrasmi, Udomkiat Nontakaew

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Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

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This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1^st January, 1997 to 28^th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: detrended fluctuation analysis, generalized hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis

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Authors: Muhammad Mufakkar, Ghulam Hussain Bhatti, Maryem Rana

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The study of the coordination behavior of thiones is of considerable interest due to the similarity of their binding sites to those in living systems. The complexation of thiones towards Copper(I) has also received considerable attraction in view of their variable bonding modes, structural diversity and promising biological implications. Copper (I) complexes of thioureas of the general formula: CuLCl, CuL2Cl and CuL3Cl [where L= Thiourea and its N- and N, N/- mono and di alkyl and phenyl derivatives] have been prepared using Cu(I)CN in the presence of HCl. The complexes have been characterized by thermal, IR and NMR(1H and 13C) spectroscopy. An upfield shift in 13C NMR and downfield shifts in 1H NMR are consistent with the sulfur coordination to Copper(I). The disappearance of a band around 2200 cm⁻¹ in IR and a resonance around 146 ppm in 13C NMR indicates that during the course of reaction the cyanide group of the Copper(I) salt has been replaced by chloride leading to the formation of chlorido complexes.

Keywords: Thiones, complexation, spectra, TGA, thermogram, chemical shifts, deshielding, resonance

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Authors: Eunice Oluwakemi Chukwuma-Nwuba

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Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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Authors: Ying Zhao, Xingyan Bin

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Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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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: Hyunbin Choi, Jihyeon Noh, Changwon Lim

Abstract:

In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Waraporn Wimuktalop

Abstract:

This research will select regions which are vulnerable to flooding in different level. Mathematical principles will be systematically and rationally utilized as a tool to solve problems of selection the regions. Therefore the method called Multiple Criteria Decision Making (MCDM) has been chosen by having two analysis standards, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytic Hierarchy Process). There are three criterions that have been considered in this research. The first criterion is climate which is the rainfall. The second criterion is geography which is the height above mean sea level. The last criterion is the land utilization which both forest and agriculture use. The study found that the South has the highest risk of flooding, then the East, the Centre, the North-East, the West and the North, respectively.

Keywords: multiple criteria decision making, TOPSIS, analytic hierarchy process, flooding

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Authors: Motahar Reza, Rajni Chahal, Neha Sharma

Abstract:

This article addresses the boundary layer flow and heat transfer of Casson fluid over a nonlinearly permeable stretching surface with chemical reaction in the presence of variable magnetic field. The effect of thermal radiation is considered to control the rate of heat transfer at the surface. Using similarity transformations, the governing partial differential equations of this problem are reduced into a set of non-linear ordinary differential equations which are solved by finite difference method. It is observed that the velocity at fixed point decreases with increasing the nonlinear stretching parameter but the temperature increases with nonlinear stretching parameter.

Keywords: boundary layer flow, nonlinear stretching, Casson fluid, heat transfer, radiation

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

Abstract:

In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

Procedia PDF Downloads 118