149 resultados para Network Centric Warfare
Resumo:
Finnish Defence Studies is published under the auspices of the National Defence College, and the contributions reflect the fields of research and teaching of the College. Finnish Defence Studies will occasionally feature documentation on Finnish Security Policy. Views expressed are those of the authors and do not necessarily imply endorsement by the National Defence College.
Resumo:
The purpose of this work was to describe and compare sourcing practices and challenges in different geographies, to discuss possible options to advance sustainability of global sourcing, and to provide examples to answer why sourcing driven by sustainability principles is so challenging to implement. The focus was on comparison between Europe & Asia & South-America from the perspective of sustainability adoption. By analyzing sourcing practices of the case company it was possible to describe main differences and challenges of each continent, available sourcing options, supplier relationships and ways to foster positive chance. In this qualitative case study gathered theoretical material was compared to extensive sourcing practices of case company in a vast supplier network. Sourcing specialist were interviewed and information provided by them analyzed in order to see how different research results and theories are reflecting reality and to find answers to proposed research questions.
Resumo:
Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.
Resumo:
The goal of the master’s thesis was to develop a model to build a service quality centric customer reference portfolio for a software as a service company. The case company is Meltwater Finland Oy that leverages customer references externally but there is no systematic model to produce good quality customer references that are in line with the company strategy. The project was carried out as a case study, where the primary source of information were seventeen internal interviews with the employees of the case company. The theory part focuses on customer references as assets and service quality in software as a service industry. In the empirical part the research problem is solved. As a result of the case study, the model to build a service quality centric customer reference portfolio was created and further research areas were suggested.
Resumo:
The purpose of this Master’s thesis is to study value co-creation in emerging value network. The main objective is to examine how value is co-created in bio-based chemicals value network. The study provides insights to different actors’ perceived value in the value network and enlightens their motivations to commit to the collaborative partnerships with other actors. Empirical study shows that value co-creation is creation of mutual value for both parties of the relationship by combining their non-competing resources to achieve a common goal. Value co-creation happens in interactions, and trust, commitment and information sharing are essential prerequisites for value co-creation. Value co-creation is not only common value creation, but it is also value that emerges for each actor because of the co-operation with the other actor. Even though the case companies define value mainly in economic terms, the other value elements like value of the partnership, knowledge transfer and innovation are more important for value co-creation.
Resumo:
Production of a new system in any range is expanding dramatically and new ideas are there upon introduced, the logic stands behind the matter is the growth of application of the internet and granting web-based systems. Before producing a system and distribute to the customer, various aspects should be studied which multiple the profit of the system. The process of productizing a new system from being unprocessed idea until delivers to the final user has been unambiguous. In this thesis, the systematize service in a way that benefits both the customer and provider, along with an effort to establish trust and diminish customer’s risk and increase service productivity are in detail presented. Characteristics of Servitization and Productization as two faces of one coin have been interpreted. Apart from the abovementioned issues state of art, service-oriented architecture (SOA) and New Service Development (NSD) has been included in this report for solving the problem of gradually decline in value of companies.
Resumo:
This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.
Resumo:
In this study, an infrared thermography based sensor was studied with regard to usability and the accuracy of sensor data as a weld penetration signal in gas metal arc welding. The object of the study was to evaluate a specific sensor type which measures thermography from solidified weld surface. The purpose of the study was to provide expert data for developing a sensor system in adaptive metal active gas (MAG) welding. Welding experiments with considered process variables and recorded thermal profiles were saved to a database for further analysis. To perform the analysis within a reasonable amount of experiments, the process parameter variables were gradually altered by at least 10 %. Later, the effects of process variables on weld penetration and thermography itself were considered. SFS-EN ISO 5817 standard (2014) was applied for classifying the quality of the experiments. As a final step, a neural network was taught based on the experiments. The experiments show that the studied thermography sensor and the neural network can be used for controlling full penetration though they have minor limitations, which are presented in results and discussion. The results are consistent with previous studies and experiments found in the literature.