Abstract The quality of Neural Machine Translation (NMT), as a data-driven approach, massively depends on quantity, quality and relevance of the training dataset. Such approaches have achieved promising results for bilingually high-resource scenarios but are inadequate for low-resource conditions. Generally, the NMT systems learn from millions of words from bilingual training dataset. However, human labeling process is very costly and time consuming. In this paper, we describe a round-trip training approach to bilingual low-resource NMT that takes advantage of monolingual datasets to address training data bottleneck, thus augmenting translation quality. We conduct detailed experiments on English-Spanish as a high-resource language pair as well as Persian-Spanish as a low-resource language pair. Experimental results show that this competitive approach outperforms the baseline systems and improves translation quality.

/pdf/augmenting-neural-machine-translation-through-round-trip-132d97o22g.pdf

Augmenting Neural Machine Translation through Round-Trip Training Approach

This study develops a new map matching algorithm targeting off-line applications. The algorithm takes a holistic view of the entire GPS trajectory and finds its match by first dividing it into several segments. This segmentation is made possible through creating a multi-layer road index system for the original road network. For each segment, a global map matching strategy is employed to identify the best match. The algorithm is compared against three state-of-the-art map matching algorithms from the literature. To get ground truth data, we design and perform numerous test drives with predefined paths that have a total length of 234 km. GPS trajectories recorded during the test drives are used to evaluate the algorithms. Our numerical experiments show the proposed algorithm improves match efficiency by up to two order of magnitude compared to the benchmark algorithms. Importantly, it achieves this remarkable speedup with negligible losses in matching accuracy.

Map matching based on multi-layer road index

There is growing evidence on positive effects of physical activity (PA) on mental health. However, the focus of previous research on this relationship has typically been on mental health from the perspective of mental health problems rather than from the perspective of mental wellbeing. Further, previous research has commonly focused rather on leisure time PA without evidence on the role of other domains of PA. The aim of the present cross-sectional study was to investigate the relationship between positive mental health (PMH) and different domains of PA in young Finnish men. The secondary aim was to examine the reasons for physical inactivity among individuals with a low level of PMH. Positive mental health (measured with Short Warwick-Edinburgh Mental Wellbeing Scale, SWEMWBS), self-reported leisure time, occupational and commuting PA as well as reasons for physical inactivity were measured using questionnaires (n = 456, mean age 29 years) among young Finnish males. Logistic regression modelling was used to generate odds for low and high levels of positive mental health for different levels of PA and sociodemographic variables. A weak positive association between leisure time PA and PMH was found in men with a low level of PMH (OR = 0.33, 95% CI 0.13–0.86). No association was found in the domains of commuting and occupational PA. Multivariate logistic regression analysis showed lower level of leisure time PA, unemployment and being single independently predicting low level of PMH. No associations were found between any domains of PA and high level of PMH. The most common reasons for physical inactivity among men with a low level of PMH were lack of interest (28%) and unwillingness to practise sports alone (27%). The relationship between physical activity and positive mental health seems to vary between different domains of physical activity. The findings highlight the important role of leisure time physical activity, particularly in men with a low level of positive mental health. Strategies aimed at increasing physical activity for mental health benefits should focus particularly on providing opportunities for leisure time physical activity involving social interactions for men with lower mental wellbeing.

/pdf/relationship-between-different-domains-of-physical-activity-1qa14r2wzq.pdf

Relationship between different domains of physical activity and positive mental health among young adult men.

This research has suggested a quadrature rule based iterative method for the solution of non-linear algebraic and transcendental equations. The proposed iterated method is derived from Quadrature Formula and Numerical Technique. The quadrature rule based iterative method is converged quadratically, and it is free from pitfall. Few of physical non-linear problems to demonstrate the competency of proposed iterative method with the assessment of Steffensen Method and Newton Raphson Method. C++ and EXCEL have been used to examine the numerical results and graphical illustration of quadrature rule based iterative method. Hence, from several examples illustrate that the convergence and efficiency of the quadrature rule based iterative method is better than Steffensen Method and Newton Raphson Method.

Quadrature Rule Based Iterative Method for the Solution of Non-Linear Equations: Quadrature Rule for the Solution of Non-Linear Equations

Obtaining an approximation for the majority of sparse linear systems found in engineering and applied sciences requires efficient iteration approaches. Solving such linear systems using iterative techniques is possible, but the number of iterations is high. To acquire approximate solutions with rapid convergence, the need arises to redesign or make changes to the current approaches. In this study, a modified approach, termed the “third refinement” of the Gauss–Seidel algorithm, for solving linear systems is proposed. The primary objective of this research is to optimize for convergence speed by reducing the number of iterations and the spectral radius. Decomposing the coefficient matrix using a standard splitting strategy and performing an interpolation operation on the resulting simpler matrices led to the development of the proposed method. We investigated and established the convergence of the proposed accelerated technique for some classes of matrices. The efficiency of the proposed technique was examined numerically, and the findings revealed a substantial enhancement over its previous modifications. 

/pdf/an-accelerated-iterative-technique-third-refinement-of-gauss-tq21a7os.pdf

An Accelerated Iterative Technique: Third Refinement of Gauss–Seidel Algorithm for Linear Systems

This study towards the Map-Matching process that is useful to align a location of Global Positioning System (GPS) of vehicles on the digital road networks. Today’s GPS-enabled vehicles in developed countries generate a big volume of GPS data. On the other hand, the development of new roads in the city enables the road network very complex and difficult to match the vehicles’ location. So therefore, different techniques (i.e., pre-processing techniques) may be applied before the map-matching process is a recent concern of the Intelligent Transport System (ITS) research community. In this paper, we introduce the pre-processing technique; splitting the road network graph and processing the Single Source Shortest Path (SSSP) in synchronize parallel processing in the Hadoop environment. The proposed technique enables the map-matching schemes efficient to align the GPS points on the digital road networks. In the experimental work, the results of the map-matching schemes (i.e., found in the literature review) incorporated with our proposed pre-processing technique shows better performance in aspect to the response time.

/pdf/a-study-of-pre-processing-technique-for-map-matching-schemes-10sovmleeq.pdf

A Study of Pre-Processing Technique for Map-Matching Schemes of GPS-Enabled Vehicles

The present research aims to find the relationship between quality of life in the context of mental health among sports participants and non-participants. This is a correlational study that seeks to find the strength of relationship between two characteristics viz. Quality of Life and Mental wellbeing among sports participants and non- participants at university level. Quality of Life Inventory (QOLI), The Warwick-Edinburgh Mental Well-being Scale (WEMWBS) instruments was applied to the participants. 98 male and female graduates and post graduates from University of Sindh, Jamshoro (age range from 18 to 30 years) were selected through simple random sampling technique. The results indicated that the total QLI score is significantly correlated with total scores of WEMWBS for sports participants and non-participants (r= .661, p< .01). An association has also been recorded in different subscales of QLI and WEMWBS. Significant differences were found between the total scores of Quality of Life Inventory (QLI) among sports participants and sports non- participants (t=3.801, p=.000). The same results have been recorded on almost all subscales of QLI except Social Support and Money where the score indicates (t=1.334, p=.185) and (t=-.779, p=.438) the value of t is 3.801, p=.0000 among sports participants and sports non-participants.

/pdf/quality-of-life-and-mental-health-among-university-students-5fqyvxt13g.pdf

Quality Of Life And Mental Health Among University Students: A Comparison Of Sports Participants And Non-Participants

The fundamental problem of linear algebra is to solve the system of linear equations (SOLE’s). To solve SOLE’s, is one of the most crucial topics in iterative methods. The SOLE’s occurs throughout the natural sciences, social sciences, engineering, medicine and business. For the most part, iterative methods are used for solving sparse SOLE’s. In this research, an improved iterative scheme namely, ‘’a new improved classical iterative algorithm (NICA)’’ has been developed. The proposed iterative method is valid when the co-efficient matrix of SOLE’s is strictly diagonally dominant (SDD), irreducibly diagonally dominant (IDD), M-matrix, Symmetric positive definite with some conditions and H-matrix. Such types of SOLE’s does arise usually from ordinary differential equations (ODE’s) and partial differential equations (PDE’s). The proposed method reduces the number of iterations, decreases spectral radius and increases the rate of convergence. Some numerical examples are utilized to demonstrate the effectiveness of NICA over Jacobi (J), Gauss Siedel (GS), Successive Over Relaxation (SOR), Refinement of Jacobi (RJ), Second Refinement of Jacobi (SRJ), Generalized Jacobi (GJ) and Refinement of Generalized Jacobi (RGJ) methods. 

A New Improved Classical Iterative Algorithm for Solving System of Linear Equations

This paper aims to construct a numerical iterated method of open methods to find a single root of application problems. The proposed numerical iterated method is the sixth order of convergence, and which is based on Steffensen Method and Newton Raphson Method. The proposed sixth-order numerical iterated method is compared with the Modified Efficient Iterative Method and Generalize Newton Raphson Method [16-17]. C++/MATLAB is used on a few examples for justification of the proposed method based on the number of evolutions, accuracy, and iterations. From numerical results, it has been observed that the sixth order numerical iterated method is good accuracy with good convergence criteria as the assessment of existing methods for solving the root of nonlinear applications problems.

Sixth Order Numerical Iterated Method of Open Methods for Solving Nonlinear Applications Problems: Sixth Order Numerical Iterated Method of Open Methods for Solving Nonlinear Applications

The aim of this research article is to develop a three-step optimal iterative technique using Hermite interpolation for the solution of nonlinear algebraic and transcendental equation arises in chemical engineering models. In this connection, we proposed an optimal three-step eight-order technique without derivative and, has a high efficiency index. The convergence analysis of the proposed method is also discussed. For this demonstration, we apply the new technique to certain nonlinear problems in chemical engineering, such as, the conversion in a chemical reactor, a chemical equilibrium problem, azeotropic point of a binary solution and Continuous Stirred Tank Reactor (CSTR). And the study of dynamics is also used to demonstrate the performance of the presented scheme. It’s observed from the Comparison tables and dynamics, the proposed technique is more efficient compared to other existing methods.

/pdf/solution-of-chemical-engineering-models-and-their-dynamics-3qu8j17c.pdf

Zubair Ahmed Kalhoro

Papers

A Study of Pre-Processing Technique for Map-Matching Schemes of GPS-Enabled Vehicles

Quality Of Life And Mental Health Among University Students: A Comparison Of Sports Participants And Non-Participants

A New Improved Classical Iterative Algorithm for Solving System of Linear Equations

Sixth Order Numerical Iterated Method of Open Methods for Solving Nonlinear Applications Problems: Sixth Order Numerical Iterated Method of Open Methods for Solving Nonlinear Applications

Solution of Chemical Engineering Models and Their Dynamics Using a New Three-Step Derivative Free Optimal Method