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This study aims to validate a model for estimating platoon delay due to pedestrian crossing for use in Kuwait City.

The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically. Using video footage to observe the site, several variables were collected, and a model was used to calculate the delays suffered by the vehicles because of pedestrian crossing. The model was validated using the actual footage and manual observation to measure the delays.

The model showed a good match fit to the observed data, as the average delays differed by 22.5% between the two methods. Following the comparison, a sensitivity analysis was made on three variables: the acceleration rate, deceleration rate, as well as the pedestrian walking time. The analysis has shown that deceleration rate has approximately twice the effect on the model than the acceleration rate has. It has also shown that the pedestrian walking time has a major effect on the model, in an almost one-to-one correlation. A 50% change of the pedestrian walking time is associated with approximately 50% change in the model’s output delay.

A model for estimating platoon delay because of pedestrian crossing was validated for use in Kuwait City. The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically.

The purpose of this paper is to achieve intelligent superstore site selection. Yonghui Superstores partnered with Cardinal Operations to incorporate a tremendous amount of site-related information (e.g. points of interest, population density and features, distribution of competitors, transportation, commercial ecosystem, existing own-store network) into its store site optimization.

This paper showcases the integration of regression, optimization and machine learning approaches in site selection, which has proven practical and effective.

The result was the development of the “Yonghui Intelligent Site Selection System” that includes three modules: business district scoring, intelligent site engine and precision sales forecasting. The application of this system helps to significantly reduce the labor force required to visit and investigate all potential sites, circumvent the pitfalls associated with possibly biased experience or intuition-based decision making and achieve the same population coverage as competitors while needing only half the number of stores as its competitors.

To our knowledge, this project is among the first to integrate regression, optimization and machine learning approaches in site selection. There is innovation in optimization techniques.

There has been almost no scholarly work on the challenges of money laundering in sovereign states that use the US dollar as their currency of choice. This study aims to break the silence by highlighting how money laundering thrives in these situations mainly due to lack of or weak regulation of the US dollar by both the adopting states and the USA.

The research depended on various secondary data sources. It is an adapted academic version of a shorter piece for a professional magazine for professionals in the Anti-Money Laundering (AML) Field.

Preliminary findings show that due to the lack of regulation of the US dollar in dollarized economies, unscrupulous politicians, organized criminal gangs and multinational corporations among others can use a variation of the Black Market Peso Exchange (BMPE) to counteract money laundering controls and launder ill-gotten gains from crimes such as corruption, transnational crimes and tax evasion. Furthermore, ordinary citizens, migrant workers and small businesses avoiding stringent exchange rates are also using the black market, posing a further challenge to the law enforcement authorities.

The practical implications of this paper relate to how the mutations of money laundering techniques, as they are adopted by criminals, to operate in different conditions are making it difficult not only to dictate but also to address using traditional AML techniques.

BMPE has far reaching social consequences. Hence, this study is significant to instigate a search for solutions and for further detailed studies into the money laundering techniques in countries that do not have a sovereign currency.

To the best of the authors’ knowledge, this is the first paper to discuss the unique challenges faced by countries that have adopted the US dollar for domestic use. The paper also shows how dollarization is a modest reminder that money laundering technique such as the BMPE can evolve to counter the legislative and regulatory environment of the various jurisdictions in which they are laundered.