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Birth weight is a key public health indicator that needs to be monitored regularly. However, in the United Arab and worldwide, there is currently no systematic procedure for monitoring shifts or trends in the mean and variability of birth weight at a national level. For this purpose, it is proposed to use statistical process control charts (SPC). This is illustrated through developing SPC charts for monitoring the birth weight of UAE nationals. The developed control charts indicated that the birth weight of UAE nationals is in statistical control. The national mean birth weight, standard deviation of birth weights, percentage of low birth weight, and percentage of high birth weight were estimated to be 3.208 kg, 0.445 kg, 5.59%, and 0.19%, respectively.

Today's intense competition forces organizations to examine how they can improve performance as they seek to enhance their competitiveness. In order to design and implement an effective program for performance improvement, the interrelations among performance criteria and factors affecting them need to be understood. For this purpose, this study used interpretive structural modeling to represent the interrelationships among seven performance criteria and 19 factors in a simple, hierarchical structure model. The bottom level of this structure contains 12 factors, namely employee selection, employee training , work environment, employee incentives, organizational culture, leadership style, efficiency, size of organization, organizational/commercial resources, product life cycle, internationalization, and employee satisfaction. This mean that any action improving performance must start from these factors. This study's findings will be beneficial for organizations that are planning to enhance their performance.

The traveling salesman problem, an NP-hard problem in combinatorial optimization, is solved in several studies by decomposing the problem into subproblems using a clustering technique. The subproblems are then solved individually. To overcome some of the limitations of the clustering technique, this paper proposes a two-stage approach for decomposing the cities into groups. In the first phase, the groups of cities are identified using a marginally modified version of factor analysis. In the second phase, the cities are assigned to groups using an integer-programming model. The proposed approach has the flexibility to allow the user to either identify the required number of groups in advance or consider it as a dependent variable. Using algorithms that are available in many commercial software packages is another advantage of the proposed approach.