APPLICATION OF TOPSIS METHOD TO ANALYZE CAUSES OF SUICIDE THOUGHT IN DOMESTIC VIOLENCE
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Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is the best method to find out the ideal solution of the problem. In recent years, TOPSIS has been widely applied to many fields with good results such as marketing strategy selection, mechatronic system optimization, network security management, location planning for urban distribution centers, business competition evaluation, irrigation water pricing decision making, emergency management, low carbon development evaluation, spaceflight mission planning, Environmental Science. This is the first time we study the causes of suicidal thought in domestic violence using TOPSIS Method. This paper has four sections. Section one gives the introduction to the suicide thought. Second section gives the Algorithm of TOPSIS method is explained. In section three we derive the framework of the research topic. Final section gives the conclusion based on our study.
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T OWARDS A S YSTEM D YNAMICS M ODELING M E- THOD B ASED ON DEMATEL
If System Dynamics (SD) models are constructed based
solely on decision makers' mental models and u
n-
derstanding of the context subject to study, then the resulting systems must necessarily bear some d
e
gree of
deficiency due to the subjective, limited, and internally inconsistent mental models which led to t
he conce
p-
tion of these systems. As such, a systematic method for constructing SD models could be esse
n
tially helpful
in overcoming the biases dictated by the human mind's limited understanding and conceptualization of
complex systems. This paper proposes a
novel combined method to su
p
port SD model construction. The
classical Dec
i
sion Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define causal
relationships among variables of a system, and to construct the corresponding Impact Relatio
n Maps
(IRMs). The novelty of this paper stems from the use of the resulting total influence m
a
trix to derive the
system dynamic's Causal Loop Diagram (CLD) and then define variable weights in the stock
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Insider threat has been recognized as one of the most dangerous security threats and become a much more complex issue. Insider threat is resulted from the legitimate users abusing their privileges and cause tremendous damage or losses. Not always being friends, insiders can be main threats to the organization. Currently, there is no equivalent prevention solution for insider threat to an intrution prevention system or vulnerability scanner. From the survey of literature of insider threat studies, we conclude that the system dynamics (SD) is an effective tool to analyze the root causes of insider threat incidents and evaluate mitigation strategies from people, process, and technology perspectives. A generized case based SD model can be tailored and applied to analyze and evaluate specific insider threat incidents. We
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Running head CRIME ANALYSIS TECHNOLOGY .docx
Running head: CRIME ANALYSIS TECHNOLOGY 1
CRIME ANALYSIS TECHNOLOGY 9
Crime Analysis Technology
Student’s Name
Institutional Affiliation
Crime Analysis Technology
Peer-Reviewed Article Analysis
Technology has evolved over the years in various sectors, with new technological innovations being developed. One of the areas that has witnessed great applications of technological evolution is in the detection and prevention of crime. This article will analyze the various technologies that are used to prevent and detect crime.
Byrne and Marx (2011) in their article reviews the topic in detail and gives insight in the role of technology in combating crime.
The key data that will be used in this research is secondary data from various peer-reviewed sources that review the topic of Crime Analysis Technology from various perspectives. Byrne and Marx (2011) presents various data on crime and the use of Information Technology in crime detection and prevention. For instance, it highlights that the percentage of schools in the United States that deploy metal detectors is approximately 2%. The article also approximates that as of 2006, one million CCTV cameras had been deployed in the United States, although the article does not provide current estimates on the same.
The article plays a great role in my final research. It gives a highlight of the various technological applications for crime prevention and detection. This can provide a background for further research, especially the technological innovations that are currently being developed. The article also presents figures about various elements of technology in crime prevention and detection such as the number of CCTV cameras, the crime rates such as the registered sex offenders, among others. Projections can therefore be made to the future.
The article mentions several significant facts. First, it classifies technological innovations in criminal justice as hard technology versus soft technology. Hard technology innovations include hardware and materials while soft technology innovations include information systems and computer software. Examples of hard technology is the CCTV cameras, metal detectors, and security systems at homes and schools. Examples of soft technology include predictive policing technology, crime analysis techniques, software, and data sharing techniques, among others. Both of the two categories of technological innovations are important in criminal justice. Another fact is the new technology of policing. The article identifies hard policing technological tools such as non-lethal weaponry and technologies for officer safety. It highlights soft policing technologies such as data-driven policies in policing and information sharing. Another important fact that the article mentions is the issues that should be con ...
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Technology has evolved over the years in various sectors, with new technological innovations being developed. One of the areas that has witnessed great applications of technological evolution is in the detection and prevention of crime. This article will analyze the various technologies that are used to prevent and detect crime.
Byrne and Marx (2011) in their article reviews the topic in detail and gives insight in the role of technology in combating crime.
The key data that will be used in this research is secondary data from various peer-reviewed sources that review the topic of Crime Analysis Technology from various perspectives. Byrne and Marx (2011) presents various data on crime and the use of Information Technology in crime detection and prevention. For instance, it highlights that the percentage of schools in the United States that deploy metal detectors is approximately 2%. The article also approximates that as of 2006, one million CCTV cameras had been deployed in the United States, although the article does not provide current estimates on the same.
The article plays a great role in my final research. It gives a highlight of the various technological applications for crime prevention and detection. This can provide a background for further research, especially the technological innovations that are currently being developed. The article also presents figures about various elements of technology in crime prevention and detection such as the number of CCTV cameras, the crime rates such as the registered sex offenders, among others. Projections can therefore be made to the future.
The article mentions several significant facts. First, it classifies technological innovations in criminal justice as hard technology versus soft technology. Hard technology innovations include hardware and materials while soft technology innovations include information systems and computer software. Examples of hard technology is the CCTV cameras, metal detectors, and security systems at homes and schools. Examples of soft technology include predictive policing technology, crime analysis techniques, software, and data sharing techniques, among others. Both of the two categories of technological innovations are important in criminal justice. Another fact is the new technology of policing. The article identifies hard policing technological tools such as non-lethal weaponry and technologies for officer safety. It highlights soft policing technologies such as data-driven policies in policing and information sharing. Another important fact that the article mentions is the issues that should be con.
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deal with this problem, in this paper a meta-heuristic algorithm is used that we have called
MOCANAR. The MOCANAR is a Pareto based multi-objective cuckoo search algorithm which
extracts high quality association rules from numeric datasets. The support, confidence,
interestingness and comprehensibility are the objectives that have been considered in the
MOCANAR. The MOCANAR extracts rules incrementally, in which, in each run of the algorithm, a
small number of high quality rules are made. In this paper, a comprehensive taxonomy of metaheuristic
algorithm have been presented. Using this taxonomy, we have decided to use a Cuckoo
Search algorithm because this algorithm is one of the most matured algorithms and also, it is simple
to use and easy to comprehend. In addition, until now, to our knowledge this method has not been
used as a multi-objective algorithm and has not been used in the association rule mining area. To
demonstrate the merit and associated benefits of the proposed methodology, the methodology has
been applied to a number of datasets and high quality results in terms of the objectives were
extracted
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Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
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APPLICATION OF TOPSIS METHOD TO ANALYZE CAUSES OF SUICIDE THOUGHT IN DOMESTIC VIOLENCE
- 1. International Journal of Computing Algorithm, Vol 2(2), December 2013 ISSN(Print):2278-2397 Website: www.ijcoa.com Application of Topsis Method to Analyze Causes of Suicide Thought in Domestic Violence M.Clement Joe Anand, A.Victor Devadoss Department of Mathematics, Loyola College, Chennai Email: rarjoemi@gmail.com Abstract Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is the best method to find out the ideal solution of the problem. In recent years, TOPSIS has been widely applied to many fields with good results such as marketing strategy selection, mechatronic system optimization, network security management, location planning for urban distribution centers, business competition evaluation, irrigation water pricing decision making, emergency management, low carbon development evaluation, spaceflight mission planning, Environmental Science. This is the first time we study the causes of suicidal thought in domestic violence using TOPSIS Method. This paper has four sections. Section one gives the introduction to the suicide thought. Second section gives the Algorithm of TOPSIS method is explained. In section three we derive the framework of the research topic. Final section gives the conclusion based on our study.