A smart city is rising as an approach and strategy to reduce the troubles produced by rapid urbanization and the growth of urban population. Although, cities continue to develop and purify their social, economic and environmental goals along with the strategies to achieve them, this phenomenon has been discussed by little research yet. However, due to the requiring immediate action or attention for practical application of the principles of smart cities, city authorities, stakeholders and local communities need to know the current reality of their city and where development is being attained in their systems. Therefore, constructing a framework for smart cities assessment will help share or exchange the newcomer strong and weak points, and emphasize where actual development is taking place and update a plan for future developments. Moreover, this assessment is able to assist cities prioritizes actions. This paper developed a guiding assessment framework for smart cites that will help the creating, carefully choosing and priorities of crucial indicators. These indicators can then show the way to the smart cites performance assessment and monitoring. Drawing on the investigation of an extensive and wide collection of literature from a variety of disciplinary areas and based on the conceptual literature on smart cities, in addition to interviews this study identify a good tool to help recognizing of virtual achievement of smart city. Furthermore, it is significant to be taken into consideration in assessing smart city smartness level.

To assist in making Middle Eastern cities more sustainable a guiding methodological framework for local sustainability assessment is key to achieving a sustainable future. This paper investigates available frameworks and develops an approach to local sustainability assessment (LSA), by constructing a methodological framework utilising a combination of (bottom-up) and (top-down) approaches. This facilitates the formulation, selection and prioritisation of key indicators, which can then guide the assessment of a city’s sustainability at a local level in the Middle East. The paper finally applies the LSA methodological framework to the Iraqi city of Hilla and succeeds in formulating and ranking 57 useful and valid sustainability indicators.

The drilling, completion, and stimulation of multiple fractured horizontal wells has proven to be an effective means of extracting hydrocarbons from unconventional resources. Since the first application of this technology by Maersk in the Dan Field in the mid-1980's oil and gas reservoirs have seen improved productivity and profitability. However, identifying the key drivers for success of multiple fractured horizontal well technology has proven difficult especially in unconventional reservoirs where data is limited. With few vertical wells, logs and core data typically used for building a basis of completion and stimulation design are often lacking. As a result, other methods of identifying success drivers must be developed and utilized.To this end, this paper utilizes a data-mining and statistical analysis of well, completion, fracture stimulation, and production data to establish the important parameters for success in horizontal wells in the Montney Formation of Alberta and British Columbia, Canada. In this study more than 3,300 horizontal wells were characterized with respect to lateral length, completion type, number of stages, fracture fluids pumped, proppant loading, costs, and production. The study utilized the statistical software JMP to identify key relationships between well data. The software system allowed standard screening and more advanced graphical methods to be applied to validate the dataset. From the quality assured dataset various additional parameters were calculated and used in the analysis.Both regression analysis and statistical 'heat maps' were used to correlate and visualize data trends. Heat maps are shown as a useful tool for visualizing strongly trending data. Another finding from this study is that cased and cemented horizontal wells in the Montney Formation had significantly better initial productivity (ϩ31%) and first year cumulatives (ϩ42%) than open hole external packer completion systems even though the cased and cemented wellbores had fewer stages (-40%), larger stimulations (ϩ390%), and increased costs (ϩ14%).While additional completed stages may increase cumulative recovery in the Montney Formation, statistical analysis demonstrates the recovery per stage decreases after a certain stage density. This conclusion is consistent with recent findings (VISAGE and Jim Gouveia 2014). Results of the study clearly demonstrate that wells with the smallest frac fluid load recovery have the best cumulative gas recovery with time, and spending more for the completion translates into higher production. This work is important as it identifies relevant completion trends in the Montney Formation and completion and stimulation practices linked to higher recovery and well success. This is also the first field-wide statistical review of wells completed in the Montney Formation using more advanced data mining and statistical analysis. The work lays a foundation for application of these techniques to more unconventional and tight oil and gas reservoirs.

Introduction: To improve current practices and create the most effective healthcare waste treatment system, solid medical waste composition needs to be analyzed. This  study aims to develop models to predict the rate of medical waste production in hospitals in Hilla city, Iraq. Predictive mode can be used to set standards, evaluate current methods for treating and disposing medical waste, and optimize healthcare solid waste management systems. Materials and Methods: Predictive models and long-term data on the composition and rate of solid medical waste generation were developed using a longitudinal study design. A standardized questionnaire and weighted scale were used to measure solid medical waste generated from the five public hospitals. Statistics were used to create models predicting the amount of waste generated at each hospital. Results: These models demonstrated a significant correlation between inpatient and outpatient numbers and waste generation. Different hospitals treat different numbers of inpatients and outpatients. Different models have been created based on various types of hospitals. Conclusion: Linear rule-based models accurately represent the weights of variables, identify the sources and implications of solid medical waste, and control waste levels by using a variety of parameters. The research model can help in the development of an effective strategic plan for setting up a medical solid waste (MSW) management system.

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