Strategic Planning for Avoidance of Catastrophic Flood Consequences

The present study is to deal with the strategic planning in avoidance of all catastrophic consequences of major flood in West Attica region in 2017 and is divided into three main sections.The first one comprises the study of the internal and external environment of the Regional Unit of West Attica with analysis of resources,procedures,culture that governs the internal environment,external bodies and mapping through PESTEL(Political,Economic,Socio-Cultural and Technological)analysis as components of the external environment.The second section comprises the vision and mission of this strategic plan and specializes in reporting and analyzing the strategic objectives as well as the actions that characterize them in order to complete the mission that has been set and to achieve the vision that has been planned.The last section focuses on the feasibility of the above proposals formulated in the midst of actions and strategic objectives with the help of SWOT(Strength,Weakness,Opportunity,and Threat)analysis and concludes with a proposal for the implementation of strategic planning with the implementation of the Integrated Spatial Investment tool.

Utilization of Agricultural Waste for Production of Soil Conditioner-Case Study

In the present study,reference is made to a pigsty with an estimated total animal weight of 500,000 kg.The quantities and quality(typical characteristics)of the generated waste are calculated.The total waste occurs after the cleaning washes in the premises of the breeding unit.Semi-liquid waste is treated in solid-liquid phase mechanical separation plants.The resulting solids,waste(reduced humidity),go to storage areas,manure.These areas are shaped concrete basins,in which there is aerobic digestion“composting”.This process results in odorless organochumic material which is further used as a soil conditioner.

Nesting and Berth Allocation by an Expert System Using Heuristic Search

Nesting is a common problem in industries such as shipbuilding, auto-maker, clothing, shoe-making, and furniture, in which various parts are cut off from a stock or stocks while minimizing the wastes or maximizing the utilization of the stock. Berth allocation at seaside is also considered one form of two dimensional nesting problems, in which a ship is assigned a location for service during a certain time slot. This paper presents an expert system using a heuristic search method for nesting problems. The parts and stocks are represented by pixels with which utility function is used to evaluate current state in search tree. The system is developed in CLIPS, an expert system shell and applied to various example problems with different constraints and to a berth allocation example to illustrate its applicability under different conditions.

FEATURE NETWORK-DRIVEN QUADRANT MAPPING FOR SUMMARIZING CUSTOMER REVIEWS

With the rapid growth of e-commerce, customers increasingly write online reviews of the product they purchase. These customer reviews are one of the most valuable sources of information affecting selection of products or services. Summarizing these customer reviews is becoming an interesting area of research, inspiring researchers to develop a more condensed, concise summarization for users. However, most of the current efforts at summarization are based on general product features without feature＇s relationship. As a result, these summaries either ignore feedback from customers or do a poor job of reflecting the opinions expressed in customer reviews. To remedy this summarization shortcoming, we propose a feature network-driven quadrant mapping that captures and incorporates opinions from customer reviews. Our focus is on construction of a feature network, which is based on co-occurrence and sematic similarities, and a quadrant display showing the opinions polarity of feature groups. Moreover, the proposed approach involves clustering similar product features, and thus, it is different from standard text summarization based on abstraction and extraction. The summarized results can help customers better understand the overall opinions about a product.

Apply neural network for improving production planning at Samarang petrol mine

Purpose-Artificial neural network(ANN)is considered a good solution for building non-linear relationship between input and output parameters,which is suitable for solving production back allocation,which is the most important step for production planning of petroleum mine.The purpose of this paper is to suggest a solution for solving production back allocation problem at Samarang petrol mine based on ANN approach.Design/methodology/approach-In this study,well operational parameters’surveillance was conducted and ANN was used to build relationships between operation parameters and production rates.Experimental method is used for testing and evaluating the possibility of using ANN for supporting production planning at Samarang mine.Findings-Consequently,the proposed ANN solution can increase the accuracy of predicted values and could be used for supporting production planning at Samarang mine.Because ANN uses well test data for training and predicting(without adding new devices),it could be a feasible and cheap solution.Research limitations/implications-There is a need for applying other methods,such as:support machine vector,non-linear autoregressive models,etc.for better evaluation of ANN solution.Practical implications-The ANN models helped operation engineers to understand well production performance and make decision to improve production plan in timely manner.This solution could be generalized for the whole mine or to similar petroleum mines in practice.Originality/value-This paper aims to propose a solution based on ANN for solving production back allocation problem of petroleum industry.The solution is tested at Samarang mine.