bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recognising Cyber Blockades as Crimes Against Humanity: Can International Criminal Law Keep Up?
Authors: Velenczei Dora Vanda 
Published: March 2024

As a result of the heavily digitalised world on top of our increasing online presence and interconnectedness, states and civilian populations are becoming more and more vulnerable to cyber attacks. It is thus imperative to examine the dangers large scale cyber attacks pose with respect to their contribution to potential human suffering. As such, these large scale cyber attacks, especially a cyber blockade, may be able to constitute an international crime. The Prosecutor of the International Criminal Court announced at the Digital Front Lines conference that his office is willing to investigate cyber operations as potential war crimes given that they are capable of causing severe consequences akin to kinetic warfare. (Yoon Onn, 2023) This is the first significant step towards recognising the harmful effects of malicious cyber operations as international crimes. However, not only is the Rome Statute itself silent on cyber operations as potential international crimes, the ICC has not yet seen a case concerning malicious cyber activities as either a war crime or as a crime against humanity. As such, the central question the paper seeks to answer is whether the Rome Statute could potentially encompass cyber blockades as the crime against humanity of “other inhumane acts” under Article 7(1)(k) of the Rome Statute. The paper looks at crimes against humanity for three reasons: firstly, Karim Khan KC has already touched on cyber attacks potentially prosecuted as war crimes, as mentioned above, thus the knowledge gap is gradually being bridged with respect to war crimes. Secondly, there is an absence of any regulatory framework should a cyber blockade be unleashed in peacetime, where international humanitarian principles do not apply. Thirdly, establishing a cyber blockade as a crime against humanity would lead to greater individual criminal responsibility as opposed to a war crimes conviction. This, in turn, would send a strong deterrent message in both war and peace.
Analysis of Media Influence on Military Decision-Making
Authors: Rushing Bonnie 
Published: March 2024

Information warfare challenges, including the "CNN Effect," are increasing in quantity and complexity as the internet saturates modern life. Media communications, reliable or not, are constantly injected into American life, affecting opinions, decision-making, and actions—which may result in terrifying and permanent consequences when the media influences military members and government leaders. This research focuses on the immersive learning environment—an engaging, simulation-based educational experience with realistic conflict scenarios where students apply lesson objectives through hands-on activities. Instructors conduct immersive learning in the US Air Force Academy's (USAFA) Multi-Domain Laboratory. Traditionally, students were taught military strategy in a classroom where they engaged in wargaming by rolling dice using a board game. Now, the Military & Strategic Studies (MSS) Department uses hands-on, real-time wargaming with unique hardware and software to teach future leaders how to apply classroom concepts using experiential learning. Wargames are critical for meeting the priorities of the Joint Chiefs of Staff—specifically, preparing leaders to conduct joint operations in all domains by integrating experiential learning. The guidance explains that "curricula should leverage live, virtual, constructive, and gaming methodologies with wargames… to develop deeper insight and ingenuity." The wargame with media provides external influences like news and information from various sources, which may influence students' decision-making process, resulting in "The CNN Effect." "The CNN Effect" is a short-hand way to explain how news reports drive government leaders' responses, including military decision-making. This project builds upon existing research uniquely because this study examines decision-making from multiple leaders based on the same simulated media in USAFA's immersive learning environment. This research uses mixed methods analysis to explore how students act based on the wargame media inputs and compare course outcome differences after receiving enhanced Information Operations education or when exposed to different quantities of broadcasts. The Information Warfare (news literacy) module enhances education on the media's influence on decision-making and trust for students. Students learned to identify and research information sources, analyze biases, opinion versus fact-based reporting, and compare news reports from various outlets.
Teenagers: A Social Media Threat Vector
Authors: Collier Henry , Morton Charlotte 
Published: March 2024

Social media has grown significantly since the early days. During this time, social media has grown to be a mainstay in most teenagers’ lives. Whether they are on Facebook, Snapchat, X (formerly Twitter), or TikTok, teenagers have fully integrated social media into their lives. Teens tend to post the ins and outs of their lives, sharing sensitive information about themselves to people they know, but also to strangers. Although social media can be used for good, it can also be used by nefarious threat actors to take advantage of teenagers. Social engineers count on their subject's desire to increase the number of virtual connections, which may increase the endorphin response received when they get “likes”. As such, social engineers create targeting accounts and then try to get as many people to accept them as possible. This increased footprint levitates the chances of a successful social engineering attack. Add to this, when someone shares an abundance of information about themselves, social engineers use this information to target individuals with spear phishing attacks. To further exacerbate the situation, social media uses algorithms to target its users and feed them with a significant amount of information that is not always vetted as being truthful. When someone is influenced by disinformation, it increases their susceptibility by taking away their desire to verify the truth, but rather accept that what they are being told is the truth. This case study examines the dynamics associated with teenagers and their susceptibility to becoming a victim of cybercrime and how social media perpetuates this situation.
Theory-Guided Feature Selection in Cybercrime Data Science
Authors: Naidoo Shiven , Naidoo Rennie 
Published: March 2024

Cybercrime data science is being significantly hampered by the presence of 'noisy' features within vast and complex datasets. We draw from the theoretical insights of the behavioural sciences to propose a feature selection model to enrich and improve the value and interpretability of cybercrime intelligence datasets. We piloted our theory-guided feature selection approach on a subset of intelligence datafeeds provided by a global fraud and cybercrime tracking firm. The results of the proposed social influence feature selection model show significant improvement in the interpretability of the machine learning-based exploratory analysis and advanced visualization techniques in an experimental setting. The feature selection model yielded rich insights about cybercriminal psychological tactics from social engineering scam data and has potential applicability in the areas of cyberthreat response and cybersecurity awareness training. Our study shows the value of an interdisciplinary theory-guided approach to cybercrime data analytics that integrates scientific knowledge from the behavioural sciences and data science expertise. Our paper concludes by suggesting avenues for future research on theory-guided feature selection seeking to incorporate behavioural science knowledge in cybercrime data science. We intend to refine, automate, evaluate, and scale our model in future research to assess its effectiveness in producing insights about cybercriminal activities and informing decision-making in a naturalistic and real-time setting. In future research efforts, we aim to automate the encoding of features and apply a wider range of machine learning tools and evaluation metrics to extract more meaningful insights into cybercriminal psychological tactics. We also intend to refine our model on larger datasets to enhance its efficiency and responsiveness to real-time cybercrime data. We call on data scientists and cybercrime domain experts to work together to apply theory-guided feature selection to improve processes of knowledge discovery that enhance our cybersecurity capabilities.
Deepfakes: The Legal Implications
Authors: Ramluckan Trishana 
Published: March 2024

The development of deepfakes began in 2017, when a software developer on the Reddit online platform began posting his creations in which he swapped the faces of Hollywood celebrities onto the faces of adult film artists, while in 2018, the comedic actor Jordan Peele posted a deepfake video of former U.S. President Obama insulting former U.S. President Trump and warning of the dangers of deepfake media. With the viral use of deepfakes by 2019, the U.S. House Intelligence Committee began hearings on the potential threats to U.S. security posed by deepfakes. Unfortunately, deepfakes have become even more sophisticated and difficult to detect. With easy accessibility to the applications of deepfakes, its usage has increased drastically over the last five years. Deepfakes are now designed to harass, intimidate, degrade, and threaten people and often leads to the creation and dissemination of misinformation as well as creating confusion about important state and non-state issues. A deepfake may also breach IP rights e.g., by unlawfully exploiting a specific line, trademark or label. Furthermore, deepfakes may cause more severe problems such as violation of the human rights, right of privacy, personal data protection rights apart from the copyright infringements. While just a few governments have approved AI regulations, the majority have not due to concerns around the freedom of speech. And while most online platforms such as YouTube have implemented a number of legal mechanisms to control the content posted on their platforms, it remains a time consuming and costly affair. A major challenge is that deep fakes often remain indetectable by the unaided human eye, which lead to the development by governments and private platform to develop deep-fake detecting technologies and regulations around their usage. This paper seeks to discuss the legal and ethical implications and responsibilities of the use of deepfake technologies as well as to highlight the various social and legal challenges which both regulators and the society face while considering the potential role of online content dissemination platforms and governments in addressing deep fakes.
Cyber Resilience, Dependability and Security
Authors: Davies Gareth , Mison Angela , Eden Peter 
Published: March 2024

There is a continuing skills shortage associated with digital security and DevSecOps (World Economic Forum, 2023), but this paper argues that is due to non-recognition that it is time for cyber security and/or digital security to be defined, and a further separation of specialisms in computing to be made apparent. This has become increasingly important when considering Artificial Intelligence. The problem is not new. This paper presents a refinement of the principles suggested by Milner (2007) of using a model to describe behaviour and organise software, grappling with seemingly intractable and complex problems which cross boundaries between different systems: engineering, technological, social, economic, legal, and political, each with a distinct perspective and goal. It emphasises Hoare’s (1996) assertion that system failures are largely due to failed analysis impacting development of resilient systems. It argues that there are dichotomies between resilience – a system security/safety perspective, dependability – a user/consumer perspective, and security – a technology perspective. Many proposed systems to date have conflated these perspectives in the secure by design paradigm which requires a depth of knowledge and expertise. Unicorns are rare. This paper suggests how to overcome the skills shortage utilising the skill sets that are available in a manner that maximises the contribution to digital security. Recognising that not everyone and everything needs to communicate with the world reduces complexity and can increase trust. Concentration on the operational purpose of a system, resulting in an Operational Design Domain (ODD) reduces complexity further. Additional reduction in complexity is achieved by placing resilience in an engineering and programming development context, grounded in acceptable behaviours, while accepting dependability as a user expectation of system behaviour, and cyber security as a separate specialism addressing access to systems and infrastructure. Much of this paper is a reversion to defensive programming through the ODD. There is a need for any solution to the skills shortage be scalable and economic, and this paper suggests how that can be achieved using existing skill sets targeted at their specialisms.
Pemberdayaan Perempuan Melalui Program Sekolah Perempuan Capai Impian dan Cita-cita (Sekoper Cinta) di Kota Tasikmalaya
Authors: Sri Wahyuni Santi , Supriatna Popon , Andriani Dian 
Published: March 2024

Program Sekoper Cinta merupakan program unggulan Pemerintah Jawa Barat yang dilaksanakan oleh Pemerintah Kota Tasikmalaya yaitu DPPKBP3A Kota Tasikmalaya. Program ini berdasarkan Keputusan Gubernur Jawa Barat Nomor:420.05/Kep.1224/Yanbangsos/2018 tentang Tim Penyelenggara Sekolah Perempuan Capai Impian dan Cita-cita. Penelitian yang berjudul Pemberdayaan Perempuan Melalui Program Sekolah Perempuan Capai Impian dan Cita-cita (Sekoper Cinta) Di Kota Tasikmalaya ini bertujuan untuk menganalisa pemberdayaan perempuan yang dilakukan DPKBP3A Kota Tasikmalaya, dalam menangani masalah ini melalui teori Adisasmita yang difokuskan terhadap aspek input, aspek proses dan aspek output. Metode penelitian yang digunakan adalah Deskriptif dengan pendekatan Kualitatif atau Deskriptif Kualitatif. Dengan menggunakan teknik snowball sampling, data yang berhasil diperoleh dari hasil observasi, wawancara dan dokumentasi. Hasil penelitian menunjukkan bahwa Pemberdayaan Perempuan Melalui Program Sekoper Cinta Di Kota Tasikmalaya sudah dijalankan namun belum optimal, karena sarana dan prasarana yang sangat minim, kurangnya pengawasan pemerintah setelah pelaksanaan program Sekoper Cinta, belum adanya tindak lanjut setelah pelaksanaan program.

Kata kunci: Pemberdayaan Perempuan, Sekoper Cinta
Gerakan Lingkungan Masyarakat Terhadap Pembangunan Pembangkit Listrik Tenaga Sampah (PLTSa) di Kecamatan Gedebage
Authors: Ghaisani Jihan Auliana 
Published: March 2024

Penelitian ini bertujuan untuk menganalisis kajian terkait dinamika Gerakan Sosial dalam proses Penolakan Pembangunan PLTSa Gedebage. Penelitian ini menggunakan teori Gerakan Sosial yang dikemukakan oleh Sydney Tarrow dengan fokus gerakan lingkungan. Penelitian ini menganalisis bagaimana suatu kebijakan menjadi perhatian masyarakat hingga kemudian terjadi interaksi yang dilakukan berupa gerakan sosial dikarenakan adanya ketidaksesuaian jalannya pemerintahan yang dijalankan. Metode penelitian yang digunakan dalam penelitian ini adalah metode penelitian kualitatif. Dalam hal memperoleh sumber penelitian, peneliti memperoleh data primer yang berasal dari wawancara langsung salah satu tokoh masyarakat di Kecamatan Gedebage, setelahnya untuk data sekunder sendiri, berasal dari beragam aneka studi kepustakaan serta juga media massa. Hasil penelitian ini menunjukkan bahwa terdapat polemik antara pemangku kebijakan yakni Pemerintah Kota Jawa Barat dengan masyarakat. Hal ini dikarenakan masyarakat merasa tidak adanya sistem yang berjalan dengan baik, sehingga terjadi maladministrasi dalam pembangunan PLTSa Gedebage. Maka dari itu masyarakat Gedebage melakukan suatu gerakan sosial agar pemerintah lebih memperhatikan jalannya roda pemerintahan berdasarkan demokrasi partisipatif.
Near-infrared phosphorescent OLEDs exhibiting over 10% external quantum efficiency and extremely long lifetime using resonant energy transfer with a phosphorescent assist dopant
Authors: Hanayama Takanori , Sano Takeshi , Saito Yu , Nakamura Takeru , Okuyama Yutaka , Sasabe Hisahiro , Kido Junji 
Published: March 2024

Abstract
We have introduced a three-component light-emitting layer consisting of a host, a phosphorescent assist dopant, and a phosphorescent emitter to simultaneously realize high efficiency and long lifetime in NIR organic LEDs. An efficient energy transfer between the two phosphorescent materials was observed with 1 wt% doping ratio of the NIR emitter, significantly enhancing the external quantum efficiency reaching 10.5% with an emission peak at 769 nm. The device showed a low drive voltage and a long operational lifetime, with a luminance decay of less than 11% from the initial value after 4800 h under accelerated conditions of 100 mA cm−2.
BAYESIAN SOFTWARE HEALTH MANAGEMENT FOR AIRCRAFT GUIDANCE, NAVIGATION, AND CONTROL
Authors: Schumann Johann , Mbaya Timmy , Mengshoel Ole 
Published: March 2024

Modern aircraft—both piloted fly-by-wire commercial aircraft as well as UAVs—more and more depend on highly complex safety critical software systems with many sensors and computer-controlled actuators. Despite careful design and V&V of the software, severe incidents have happened due to malfunctioning software. In this paper, we discuss the use of Bayesian networks to monitor the health of the on-board software and sensor system, and to perform advanced on-board diagnostic reasoning. We focus on the development of reliable and robust health models for combined software and sensor systems, with application to guidance, navigation, and control (GN&C). Our Bayesian network-based approach is illustrated for a simplified GN&C system implemented using the open source real-time operating system OSEK/Trampoline. We show, using scenarios with injected faults, that our approach is able to detect and diagnose faults in software and sensor systems.
Online Estimation of Lithium-Ion Battery State-of-Charge and Capacity with a Multiscale Filtering Technique
Authors: Hu Chao , D. Youn Byeng , Kim Taejin , Chung Jaesik 
Published: March 2024

Real-time prediction of state-of-charge (SOC), state-of-health (SOH) and state-of-life (SOL) plays an essential role in many battery energy storage applications, such as electric vehicle (EV), hybrid electric vehicle (HEV) and smart power grid. However, among these three quantities, only the SOC has been thoroughly studies while there is still lack of rigorous research efforts onthe other two quantities, SOH and SOL. Specially, real- time estimation of the SOH-relevant cell capacity by tracking readily available measurements (e.g., voltage,current and temperature) is still an open problem. Commonly used joint/dual extended Kalman filter(EKF) suffers from the lack of accuracy in the capacity estimation since (i) the cell voltage is the only measurable data for the SOC and capacity estimation and updates and (ii) the capacity is very weakly linked to the cell voltage. Furthermore, although the capacity is a slowly time-varying quantity that indicates cell state-of-health (SOH), the capacity estimation is generally performed on the same time-scale as the quickly time-varying SOC, resulting in high computational complexity. To resolve these difficulties, this paper proposes a multiscale framework with EKF for SOC and capacity estimation. The proposed framework comprises two ideas: (i) a multiscale framework to estimate SOC and capacity that exhibit time-scale separation and (ii) a state projection scheme for accurate and stable capacity estimation. Simulation and experimental results verify the effectiveness of our framework.
Identifying NOx Sensor Failure for Predictive Maintenance of Diesel Engines using Explainable AI
Authors: Mckinley Thomas , Somwanshi Meghana , Bhave Devawrat , Verma Sandeep 
Published: March 2024

The automotive industry is being transformed by the application of artificial intelligence and big data analysis. In particular, predictive analytics is becoming a powerful tool for anticipating component failure. This key area of research provides automotive industry manufacturers with lower warranty expenses and incremental service parts revenue while rewarding customers with higher uptime. These benefits are particularly important for commercial vehicles operations such as bus and truck fleets, since analytics led predictive maintenance can prevent inconvenient and costly interruptions of vehicle mission. Accurate prediction models for component failures are especially challenging. This paper describes one such effort for failure prediction of transit bus NOx (Nitrogen Oxides) sensors.
Stringent emissions regulations have made diesel exhaust aftertreatment systems mandatory in nearly all global markets, and NOx sensors play a critical role in control and diagnostic algorithms used by these systems. NOx is measured before and after the SCR (Selective Catalytic Reduction) system with two different components namely Engine out (EO) NOx and System out (SO) NOx. Due to differences in operating conditions and failure rates these two components were studied separately. The results of different Machine Learning algorithms were obtained and compared to get the optimal predictions. Moreover, early life and late life failures were also studied separately to differentiate between random and wear-out failure modes. Highlights of the paper are: - the data collection process, feature engineering and feature selection process, as well as explainable AI (Artificial Intelligence) built on top of the machine learning model. Efforts were also taken to keep the approach generic and not become too component specific so that it can easily be replicated for predicting other failures on other product lines or of different components.
PERANCANGAN VIDEO DOKUMENTER UBI CILEMBU SEBAGAI MEDIA PROMOSI BUDAYA MASYARAKAT CILEMBU
Authors: Khoirul Rizal Ari Muhamad 
Published: March 2024

Ubi jalar Cilembu sudah seperti ikonik bagi masyarakat Cilembu, karena sebagian besar tanah di sana merupakan perkebunan ubi, dan mayoritas masyarakat berprofesi sebagai petani, tetapi karena minimnya kesadaran akan urgensi publikasi, pengelolaan terhadap media komunikasi dan sarana iklan dari produk yang dihasilkan pun masih kurang maksimal. Padahal, apabila penduduk mampu mengelola sumber daya desa khususnya keunikan dari ubi jalar Cilembu dan mampu memperkenalkan kepada masyarakat luas tentunya akan lebih menguntungkan untuk masyarakat.
Video dokumenter ini mengangkat tema agribisnis yang akan menyuguhkan seorang petani ubi Cilembu dengan segala informasi mengenai aktivitas, filosofi dan cerita mengenai ubi Cilembu itu sendiri. Segala informasi yang terkandung harus tersampaikan dengan baik, oleh sebab itu format video dokumenter menjadi pilihan untuk mengemasnya karena dinilai lebih efektif dan efisien, selain itu pendekatan dokumenter membuat penulis mempunyai ruang lebih luas dan lugas untuk menyampaikan ide-ide dan konsep demi tercapainya tujuan awal pembuatan video ini. Segala aspek informasi yang disampaikan diulik secara mendalam dengan menggunakan metode wawancara dan observasi dengan petani ubi Cilembu.