PENGARUH COGNITIVE DISSONANCE BIAS DAN MENTAL ACCOUNTING DALAM PENGAMBILAN KEPUTUSAN INVESTASI ASSET CRYPTOCURRENCY

Penelitian ini bertujuan untuk menguji apakah terdapat pengaruh antara cognitive dissonance bias dan mental accounting dalam pengambilan keputusan investasi asset cryptocurrency. Metode penelitian yang digunakan adalah penelitian eksperimen dengan desain faktorial 2x2. Pengujian dalam penelitian ini menggunakan uji regresi logistik dengan subjek penelitian investor asset cryptocurrency yang tergabung dalam sebuah komunitas Lern2TradeID dengan teknik pengambilan sampel menggunakan simple random sampling. Hasil penelitian berdasarkan kuesioner yang telah disebarkan menunjukan bahwa cognitive dissonance bias tidak berpengaruh secara signifikan dalam pengambilan keputusan investasi asset cryptocurrency, sedangkan mental accounting berpengaruh signifikan dalam pengambilan keputusan investasi asset cryptocurrency. Hasil penelitian ini juga menunjukan bahwa tidak terdapat pengaruh interaksi antara cognitive dissonance bias dan mental accounting dalam pengambilan keputusan investasi asset cryptocurrency. Kata Kunci: Cognitive Dissonance Bias, Mental Accounting, Keputusan Investasi, Asset Cryptocurrency. This study aims to examine whether there is an influence between cognitive dissonance bias and mental accounting in making cryptocurrency investment decisions. The research method used is experimental research with a 2x2 factorial design. The test in this study uses a logistic regression test with the research subject of cryptocurrency asset investors who are members of the Lern2TradeID community with a sampling technique using simple random sampling. The results of the research based on the questionnaires that have been distributed show that cognitive dissonance bias has no significant effect on cryptocurrency asset investment decisions, while mental accounting has a significant effect on cryptocurrency asset investment decisions. The results of this study also show that there is no interaction effect between cognitive dissonance bias and mental accounting in making cryptocurrency investment decisions. Keywords: Cognitive Dissonance Bias, Mental Accounting, Investment Decision Making, Asset Cryptocurrenc

Measures of Critical Infrastructure Vulnerability to Destructive Events

RÉSUMÉ : Les infrastructures critiques sont les actifs physiques qui fournissent aux sociétés modernes les services et besoins nécessaires pour le bon fonctionnement d’activités sociales et économiques essentielles. L'importance de ces infrastructures complexes est largement reconnue et la nécessité de protéger ces réseaux contre des événements destructifs—intentionnels ou accidentels—attire l'attention de plusieurs chercheurs et experts en sécurité. Il est également bien reconnu que le coût et les efforts associés à la protection totale représentent un énorme défi. La société réalisera son plus grand retour sur investissement en identifiant, en priorisant et en protégeant stratégiquement les actifs les plus vulnérables de son portefeuille d'infrastructures. Cela implique la nécessité d'une méthodologie de sélection permettant de cibler les actifs les plus cruciaux et de mesurer efficacement la vulnérabilité globale d'un réseau donné, ce qui nous permettra d'évaluer les niveaux de risque actuels et d'évaluer les améliorations techniques proposés. Le travail à suivre tente de mesurer la robustesse des systèmes d'infrastructures critiques en utilisant une approche basée sur les conséquences, évaluant la fonctionnalité de ces réseaux suite à la survenance d'un événement destructeur. Pour ce faire, des applications empiriques de deux approches différentes—une première utilisant la méthodologie fondée sur la théorie des réseaux et une deuxième méthodologie, proposé pour la première fois, fondée sur l'entropie—ont été réalisées sur les réseaux de transport d'électricité des quatre plus grandes provinces canadiennes en utilisant l'information disponible dans le domaine public. Notre enquête sur les similitudes entre ces deux méthodologies distinctes n’a fourni aucune similarité définitive lors de la comparaison de la vulnérabilité des provinces, mesurée selon les différentes approches, mais a éclairée des avenues prometteuses pour de la recherche future.----------ABSTRACT : Critical infrastructure systems are the physical assets that provide modern societies with the fundamental resources required to conduct essential economic and social operations, from power and electricity to drinking water and telecommunications. The crucial importance of these vast, complex and ubiquitous infrastructures is widely acknowledged and as such, the necessity to protect these networks from destructive events—both intentional and accidental—has garnered the attention of researchers and security experts alike. Similarly, it is also well recognized that the cost and effort associated with total protection presents an enormous challenge. Society will achieve its greatest return on investment by correctly identifying, prioritizing and protecting the most vulnerable assets in its infrastructure portfolio. This implies the need for a screening methodology by which we can target the most crucial assets, and effective metrics with which to gauge the vulnerability of a given network as a whole, allowing us to assess risk levels and evaluate proposed or completed engineering changes. The following work studies the robustness of critical infrastructure systems using a consequence-based framework, assessing the functionality of networks conditional on some destructive event having taken place. In order to do so, empirical applications of two different approaches—the network theory-based methodology and a novel entropy-based methodology—were carried out on the electrical transmission networks of the four largest Canadian provinces, using information available in the public domain. Our attempt to investigate the similarities between the separate methodologies failed to provide any meaningful consistencies when comparing provinces’ robustness according to the different grading schemes, but did provide promising avenues for future research

PRNU pattern alignment for images and videos based on scene content

This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics application

A vision-based fully automated approach to robust image cropping detection

The definition of valid and robust methodologies for assessing the authenticity of digital information is nowadays critical to contrast social manipulation through the media. A key research topic in multimedia forensics is the development of methods for detecting tampered content in large image collections without any human intervention. This paper introduces AMARCORD (Automatic Manhattan-scene AsymmetRically CrOpped imageRy Detector), a fully automated detector for exposing evidences of asymmetrical image cropping on Manhattan-World scenes. The proposed solution estimates and exploits the camera principal point, i.e., a physical feature extracted directly from the image content that is quite insensitive to image processing operations, such as compression and resizing, typical of social media platforms. Robust computer vision techniques are employed throughout, so as to cope with large sources of noise in the data and improve detection performance. The method leverages a novel metric based on robust statistics, and is also capable to decide autonomously whether the image at hand is tractable or not. The results of an extensive experimental evaluation covering several cropping scenarios demonstrate the effectiveness and robustness of our approac

Early use of abiraterone and radium-223 in metastatic prostate cancer

[No abstract available