scholarly journals Risk Assessment of Critical Solid Waste Points in Lima, Peru, using the Grey Clustering Method

2019 ◽  
Vol 8 (12) ◽  
pp. 4988-4993
Keyword(s):  
Solid Waste ◽  
Critical Points ◽  
Risk Evaluation ◽  
Social Impact ◽  
Limited Information ◽  
Clustering Method ◽  
Landscape Characteristics ◽  
Grey Clustering ◽  
High Level ◽  
Regional Authorities

The district of Comas in Lima, Peru, is considered one of the districts with the highest number of critical points due to the accumulation of solid waste, causing the proliferation of vectors and the generation of bad smells, producing in this way a negative environmental and social impact on the population and on the landscape characteristics of the environment. The objective of this investigation is to evaluate the risk produced by the critical points of solid waste identified in Tupac Amaru Avenue, in the district of Comas, using the Grey Clustering method. This method allows to consider the uncertainty in the analysis being an adequate methodology for the evaluation of the risk of critical points since it is an issue of high level of uncertainty due to the limited information. The criteria for the evaluation of the risk of the critical points are according to the methodology of the Risk Evaluation Guide of the Ministry of the Environment. Five critical points of solid waste identified in the corresponding Tupac Amaru Avenue in all Zone 1 of the district of Comas were evaluated during 3 days. The results revealed that the three of the monitoring points present moderate risk and two slight risk. This study could be a useful tool for decision making by local and regional authorities to prioritize critical points for eradication and prevention

scholarly journals OPTIMIZATION ASSIGNMENT OF WESTERN PATROL UNIT (KRI) ELEMENT IN SEA SECURITY OPERATIONS IN RIAU ISLANDS WATER AREAS USING SET COVERING MODEL

JOURNAL ASRO ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 42
Author(s):  
Agus Setiadji ◽  
Didit Herdiawan ◽  
Benny Sukandari ◽  
Muksin Muksin
Keyword(s):  
Critical Points ◽  
Set Covering ◽  
Limited Information ◽  
Location Selection ◽  
Operational Costs ◽  
Discrete Approach ◽  
Covering Method ◽  
Security Operations ◽  
Covering Model ◽  
High Level

The territorial waters of Riau Islands are one of the locations with a high level of vulnerability to violations in thesea in Indonesia, because this region is directly adjacent to neighboring countries and is an international tradeand shipping route. One of the roles of the Indonesian Navy is to maintain the security of national jurisdictions,including in the territorial waters of Riau Islands, which are then realized in Operation Sea Security, where theimplementation still has several constraints, namely budget constraints, technical capabilities, number of ships,limited information, and limitations supporting facilities, so that the implementation of Marine SecurityOperations is not optimal. The main reason is the placement of patrol boats during operations is not wellorganized. With these problems, a study was conducted using the set covering method to get the most optimallocation for patrol boat placement with as few ships as possible but still be able to reach the entire waters of theRiau Islands and minimize operational costs. In this study a discrete approach was taken, namely thedetermination of the critical points, which numbered 37 vulnerable points. All these points must be affordable bythe ship on duty.Keywords: Set Covering, Location Selection, Marine Security Operations, Riau Islands Waters Region

scholarly journals Social Impact Assessment in La Oroya, Peru Applying the Grey Clustering Method

2019 ◽  
Vol 9 (1) ◽  
pp. 4772-4775
Keyword(s):  
Decision Making ◽  
Social Impact ◽  
Social Conflict ◽  
Social Impact Assessment ◽  
Correct Decision ◽  
Clustering Method ◽  
Subjective Evaluations ◽  
The Social ◽  
Grey Clustering ◽  
The City

The social conflict presented in the city of La Oroya, of a national government issue type, is considered by the Ombudsman's Office as a latent social conflict during the month of April 2019; therefore, analyses, agreements, meetings and dialogue tables are presented, which allow subjective evaluations of the problematic reality, complicating the correct decision making. For which, the application of the Grey Clustering method is proposed to quantify the social impact presented in the city of La Oroya; the surveys were conducted on Sunday, June 2, 2019, containing 08 questions (same number of criteria to evaluate) that were answered by 20 settlers, such answers were evaluated with the Grey Clustering method obtaining as a result that the social impact in the city of La Oroya is of normal level.

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

scholarly journals Spatial Analysis of the Drivers, Characteristics, and Effects of Forest Fragmentation

2021 ◽  
Vol 13 (6) ◽  
pp. 3246
Author(s):  
Zoe Slattery ◽  
Richard Fenner
Keyword(s):  
Forest Fragmentation ◽  
Forest Fires ◽  
Geographical Information ◽  
Agricultural Expansion ◽  
Forest Patches ◽  
Mato Grosso ◽  
Remote Imaging ◽  
Landscape Characteristics ◽  
High Level

Building on the existing literature, this study examines whether specific drivers of forest fragmentation cause particular fragmentation characteristics, and how these characteristics can be linked to their effects on forest-dwelling species. This research uses Landsat remote imaging to examine the changing patterns of forests. It focuses on areas which have undergone a high level of a specific fragmentation driver, in particular either agricultural expansion or commodity-driven deforestation. Seven municipalities in the states of Rondônia and Mato Grosso in Brazil are selected as case study areas, as these states experienced a high level of commodity-driven deforestation and agricultural expansion respectively. Land cover maps of each municipality are created using the Geographical Information System software ArcGIS Spatial Analyst extension. The resulting categorical maps are input into Fragstats fragmentation software to calculate quantifiable fragmentation metrics for each municipality. To determine the effects that these characteristics are likely to cause, this study uses a literature review to determine how species traits affect their responses to forest fragmentation. Results indicate that, in areas that underwent agricultural expansion, the remaining forest patches became more complex in shape with longer edges and lost a large amount of core area. This negatively affects species which are either highly dispersive or specialist to core forest habitat. In areas that underwent commodity-driven deforestation, it was more likely that forest patches would become less aggregated and create disjunct core areas. This negatively affects smaller, sedentary animals which do not naturally travel long distances. This study is significant in that it links individual fragmentation drivers to their landscape characteristics, and in turn uses these to predict effects on species with particular traits. This information will prove useful for forest managers, particularly in the case study municipalities examined in this study, in deciding which species require further protection measures. The methodology could be applied to other drivers of forest fragmentation such as forest fires.

scholarly journals Pain Standards for Accredited Healthcare Organizations (ACDON Project): A Mixed Methods Study

2021 ◽  
Vol 11 (2) ◽  
pp. 102
Author(s):  
Concepción Pérez ◽  
Jimmy Martin-Delgado ◽  
Mercedes Vinuesa ◽  
Pedro J. Ibor ◽  
Mercedes Guilabert ◽  
...  
Keyword(s):  
Mixed Methods ◽  
Pain Management ◽  
Cancer Pain ◽  
Delphi Technique ◽  
Social Impact ◽  
Poor Quality ◽  
Nominal Group ◽  
Cancer Pain Management ◽  
Healthcare Organizations ◽  
High Level

Up to 50% of cancer patients and up to 90% of those in terminal stages experience pain associated with disease progression, poor quality of life, and social impact on caregivers. This study aimed to establish standards for the accreditation of oncological pain management in healthcare organizations. A mixed methods approach was used. First, a pragmatic literature review was conducted. Second, consensus between professionals and patients was reached using the Nominal Group and Delphi technique in a step that involved anesthesiologists, oncologists, family physicians, nurses, psychologists, patient representatives, and caregivers. Third, eight hospitals participated in a pilot assessment of the level of fulfillment of each standard. A total of 37 standards were extracted. The Nominal Group produced additional standards, of which 60 were included in Questionnaire 0 that was used in the Delphi Technique. Two Delphi voting rounds were performed to reach a high level of consensus, and involved 64 and 62 participants with response rates of 90% and 87%, respectively. Finally, 39 standards for the management of cancer pain were agreed upon. In the self-evaluation, the average range of compliance was between 56.4% and 100%. The consensus standards of the ACDON Project might improve the monitoring of cancer pain management. These standards satisfied the demands of professionals and patients and could be used for the accreditation of approaches in cancer pain management.

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