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Geological disasters in mines, ecological environment and geology and geomorphology are closely bound up with each other. To reduce or avoid economic loss and to decrease the threat degree of geological disasters to life safety, the protection of geological environment are formulated in this study. Specifically, this includes taking mines that are dominated by thin bedded carbonate as the research objects. The goals of this study include prevention and control of geological disasters and protection of geological environment. The data are based on characteristics of geological strata in mines collected by the exploration, and combined with the characteristics of geomorphic environment, relevant rules aiming at the prevention and control of geological disasters. Then, pursuant to the selection of indicators, an evaluation system is constructed to verify the effectiveness of measures and strategies proposed, in which the score value is converted into the corresponding level to test the implementation effect of the measures and strategies proposed. Through comparing the changes of the utility levels before and after the implementation of measures and strategies proposed, it can be seen that the geological disaster levels of the five mining areas in the study region are respectively improved from the non-ideal levels V, IV, V, V, IV to II, I, I, II, II, with the tailings pond leakage times less than 4 times and collapse volume less than 5m3. And, the levels of geological environment are upgraded from levels IV, IV, IV, V, V to ideal levels II, II, II, I, II, accomplished by the vegetation coverage rate of the mine reaching more than 35%, as well as the recovery rate of exploitation and utilization rate of tailings both exceeding 85%, which indicates that the protection strategy proposed in this paper has good practicality and feasibility.

With the governmental sectors imitating the reformation of enterprises stressing on Knowledge, Contracting Out and Deregulation have become the core policies. Contracting Out is not based on the arbitrariness of an administrator, but the selective efficiency and competition. Connecting the resources between Public and Private Sectors is a concern of Contracting Out, while Knowledge Outsourcing is an innovation to enhance organizational knowledge and the reduction of organizational ignorance. Based on a Knowledge Outsourcing Investigation by the Kaohsiung City Government (Taiwan) in the past few years, Data Envelopment Analysis (DEA) and Sensitivity Analysis are integrated for measuring the total efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) of Knowledge Outsourcing of the sectors in the Kaohsiung City Government for the improvement reference of other counties and cities. From the message acquired from the efficiency and variables with the DEA, one DMU (Data Management Unit), or about 5% of all DMUs, appears to have strong Knowledge Outsourcing efficiency 1, showing favorable Knowledge Outsourcing efficiency. Two DMUs, comprising about 10% of all DMUs, reveal the marginal Knowledge Outsourcing inefficiency between 0.9 and 1. This implies that such sectors could better enhance the Knowledge Outsourcing efficiency. 17 DMUs, representing about 85% of all DMUs, exhibit an obvious Knowledge Outsourcing inefficiency of less than 0.9, so that the Finance and Transportation Bureaus present the lowest Knowledge Outsourcing efficiency. ; En la medida en que el sector público imita la reforma de aquellas empresas que ponen el acento en el conocimiento, la subcontratación y la desregulación se han convertido en las principales políticas. La subcontratación no se basa en la arbitrariedad de un gestor público, sino en la eficacia selectiva y la competencia. El interés de la subcontratación consiste en poner en contacto los recursos del sector público y privado, mientras que la externalización del conocimiento supone una innovación para incrementar el conocimiento organizativo y reducir la ignorancia organizativa. Basándose en una investigación sobre externalización de conocimiento llevada a cabo por el Ayuntamiento de Kaohsiung (Taiwan) en los últimos años, se ha integrado el Análisis Envolvente de Datos (DEA) y el Análisis de Sensibilidad para medir la eficiencia total (TE), la eficiencia técnica pura (PTE) y la eficiencia del tamaño (SE) en la externalización del conocimiento en del Ayuntamiento de Kaohsiung, lo que puede servir para otros países y ciudades. De las variables sobre eficiencia del DEA se obtiene que un DMU (Data Management Unit), esto es, en torno al 5% de todos los DMU, cuenta con una robusta eficiencia de 1 en la externalización del conocimiento, lo que muestra una favorable eficiencia en la externalización de conocimiento. Dos DMU, lo que supone alrededor del 10% de todos los DMU, revela ineficiencia marginal en la externalización de conocimiento entre 0,9 y 1. Ello supone que esos sectores podrían incrementar la eficiencia en la externalización del conocimiento. Diecisiete DMU, que representan el 85% de todos los DMU, muestran una obvia ineficiencia en la externalización de conocimiento menor de 0,9, por lo que el sector de las finanzas y el de transporte presenta la menor eficiencia en la externalización de conocimiento.

AbstractThe Keelung River is one of the major branches of the Danshuei River estuarine system, which runs the metropolitan capital city of Taipei, Taiwan, and receives a large of amount of wastewater. The dissolved oxygen (DO) concentration is generally low in the tidal portion of the Keelung River. Hypoxia/anoxia occurs often, particularly during a low‐flow period. The sediment oxygen demand (SOD) amounts to a significant value, hence increasing the total oxygen demand load of the river. The present work reports on laboratory SOD made on grab sediment core samples in situ that are undisturbed. The results reveal that SOD values fluctuate with variations in seasons and are higher in summer due to a high‐temperature effect. It was found in the laboratory tests that the average SOD (at 20 °C) value is 0.76 g/m2/day and the maximum SOD (at 20 °C) value reaches 1.58 g/m2/day. The mean values of measured SOD at each station were adopted in the vertical two‐dimensional water quality model to simulate the DO distribution along the tidal Keelung River. The simulated results are in reasonable agreement with the measured DO distribution in the river. Model sensitivity analyses were also conducted with increasing and decreasing SOD. It reveals that SOD is an important parameter that affects the DO distribution in the tidal estuary.