The integration of medical images is the process of registering and fusing them to obtain a greater amount of diagnostic information. In this work an analysis is performed for the integration of images obtained through computed axial tomography and magnetic resonance imaging, for which a tool was developed in the Matlab program, where the registration is implemented through equivalent features; in addition, the pairs of images are compared by several fusion rules, with a view to identify the best algorithm in which the resulting fused image contains the most information from the original representations.

Map is the basic language of geography and an indispensable tool for spatial analysis. But for a long time, maps have been regarded as an objective and neutral scientific achievement. Inspired by critical geography, critical cartography/GIS came into being with the goal of clarifying the discourse embedded in cartographic practice. Power relationship challenges the untested assumption in map representation that is taken for granted. After more than 40 years of debate and running in, this research field has initially shown an outline, and critical cartography/GIS has roughly formed two research directions: the deconstruction path mainly starts from the identity of cartography subject and the process of map knowledge production, and analyzes the inseparable relationship between cartography and national governance and its internal power mechanism respectively; the construction path mainly relies on cooperative mapping and anti-mapping to realize the reproduction of map data. Domestic critical cartography/GIS research has just started, and it is necessary to continue to absorb the achievements of critical geography and carry out research in different historical periods. The deconstruction research of different types of maps also needs to strengthen the in-depth bridging between the construction path and the deconstruction path, and to be more open to the public. Impartial map application research, and actively apply the research results to social practice.

The study evaluates to what extent logistics performance and its components impact Vietnam’s bilateral export value. The augmented Gravity model is applied on panel data in the period from 2010 to 2018. Logistics efficiency is measured by Logistic performance index (LPI) and its sub-indices developed by the World Bank. A variety of diagnostic tests and estimation methods are employed to ensure the stability of the results. The main findings confirm that all explanatory variables demonstrate the expected signs, and aggregate logistics performance and its sub-indices have positive impacts on Vietnam’s export flows, with the magnitude of logistics impacts is greater than other factors in the research model. Among LPI components of Vietnam, Ease of arranging shipments index is the most influential factor on exports, followed by Infrastructure, Timeliness, and Quality of logistics services. These export’s effects are also identified by partners’ LPI indicators namely Quality of logistics services, Customs, Infrastructure, and Tracking and tracing.

Mapping land use and land cover (LULC) is essential for comprehending changes in the environment and promoting sustainable planning. To achieve accurate and effective LULC mapping, this work investigates the integration of Geographic Information Systems (GIS) with Machine Learning (ML) methodology. Different types of land covers in the Lucknow district were classified using the Random Forest (RF) algorithm and Landsat satellite images. Since the research area consists of a variety of landforms, there are issues with classification accuracy. These challenges are met by combining supplementary data into the GIS framework and adjusting algorithm parameters like selection of cloud free images and homogeneous training samples. The result demonstrates a net increase of 484.59 km² in built-up areas. A net decrement of 75.44 km² was observed in forest areas. A drastic net decrease of 674.52 km² was observed for wetlands. Most of the wastelands have been converted into urban areas and agricultural land based on their suitability with settlements or crops. The classifications achieved an overall accuracy near 90%. This strategy provides a reliable way to track changes in land cover, supporting resource management, urban planning, and environmental preservation. The results highlight how sophisticated computational methods can enhance the accuracy of LULC evaluations.

A logistics service company in Batam faces challenges related to warehouse load fulfillment and sorting inaccuracies. This study aims to identify proposed efficiency improvements to the goods distribution system using the cross-docking method. The research method chosen is cross-docking, a technique that eliminates the storage process in the warehouse, thus saving time and cost. The research findings show significant benefits, especially in achieving zero inventory efficiency. Data processing and discussion revealed that efficiencies were apparent by increasing the sorting tables from 1 to 6, with an output of 90,000 kg during aircraft loading and unloading (compared to approximately 77,000 kilograms). This efficiency arises from the larger output of the sorting tables compared to the input, eliminating the need for warehousing and adding ten trucks. As a result, the shipment can be completed in one trip, with no goods stored in the warehouse. The analysis shows that implementing cross-docking in the company increases efficiency in distributing goods to forwarding partners.

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.