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关键词： Turing machines  

摘要： We have defined the Conscious Turing Machine (CTM) for the purpose of investigating a Theoretical Computer Science (TCS) approach to consciousness. For this, we have hewn to the TCS demand for simplicity and understandability. The CTM is consequently and intentionally a simple machine. It is not a model of the brain, though its design has greatly benefited - and continues to benefit - from neuroscience and psychology. The CTM is a model of and for consciousness. Although it is developed to understand consciousness, the CTM offers a thoughtful and novel guide to the creation of an Artificial General Intelligence (AGI). For example, the CTM has an enormous number of powerful processors, some with specialized expertise, others unspecialized but poised to develop an expertise. For whatever problem must be dealt with, the CTM has an excellent way to utilize those processors that have the required knowledge, ability, and time to work on the problem, even if it is not aware of which ones these may be. © 2023, CC BY.

关键词： Gene expression  

摘要： Metastatic prostate cancer is one of the most common cancers in men. In the advanced stages of prostate cancer, tumours can metastasise to other tissues in the body, which is fatal. In this thesis, we performed a genetic analysis of prostate cancer tumours at different metastatic sites using data science, machine learning and topological network analysis methods. We presented a general procedure for pre-processing gene expression datasets and pre-filtering significant genes by analytical methods. We then used machine learning models for further key gene filtering and secondary site tumour classification. Finally, we performed gene co-expression network analysis and community detection on samples from different prostate cancer secondary site types. In this work, 13 of the 14,379 genes were selected as the most metastatic prostate cancer related genes, achieving approximately 92% accuracy under cross-validation. In addition, we provide preliminary insights into the co-expression patterns of genes in gene co-expression networks. Project code is available at https://***/zcablii/Master_cancer_project. © 2023, CC BY.

关键词： Philosophical aspects  

摘要： Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers in various CS sub-disciplines to identify whether and how they consider potential unintended consequences of their research innovations. We show that considering unintended consequences is generally seen as important but rarely practiced. Principal barriers are a lack of formal process and strategy as well as the academic practice that prioritizes fast progress and publications. Drawing on these findings, we discuss approaches to support researchers in routinely considering unintended consequences, from bringing diverse perspectives through community participation to increasing incentives to investigate potential consequences. We intend for our work to pave the way for routine explorations of the societal implications of technological innovations before, during, and after the research process. © 2023, CC BY.

关键词： Computer science   Engineering   Machine learning   Technology  

摘要： Collecting training data by focusing on dangerous scenarios offers an efficient way for artificial intelligence to improve the safety of autonomous vehicles. Augmented reality allows the approach to be tested without risking lives. AI tests self-driving vehicles by collating dangerous scenarios.

关键词： Computer science   Industry   Society   Software  

摘要： A virtual world filled with bad AI drivers can be used to test autonomous vehicles.

关键词： Computer science   Information technology  

摘要： Recent advances in artificial intelligence technology have significantly improved facial image manipulation, which is known as Deepfake. Facial image manipulation synthesizes or replaces a region of the face in an image with that of another face. The techniques for facial image manipulation are classified into four categories: (1) entire face synthesis, (2) identity swap, (3) attribute manipulation, and (4) expression swap. Out of them, we focus on expression swap because it effectively manipulates only the expression of the face in the images or videos without creating or replacing the entire face, having advantages for the real-time application. In this study, we propose an evaluation framework of the expression swap models targeting the real-time online class environments. For this, we define three kinds of scenarios according to the portion of the face in the entire image considering actual online class situations: (1) attendance check (Scenario 1), (2) presentation (Scenario 2), and (3) examination (Scenario 3). Considering the manipulation on the online class environments, the framework receives a single source image and a target video and generates the video that manipulates a face of the target video to that in the source image. To this end, we select two models that satisfy the conditions required by the framework: (1) first order model and (2) GANimation. We implement these models in the framework and evaluate their performance for the defined scenarios. Through the quantitative and qualitative evaluation, we observe distinguishing properties of the used two models. Specifically, both models show acceptable results in Scenario 1, where the face occupies a large portion of the image. However, their performances are significantly degraded in Scenarios 2 and 3, where the face occupies less portion of the image;the first order model causes relatively less loss of image quality than GANimation in the result of the quantitative evaluation. In contrast, GANimatio

关键词： non-small cell lung cancer   radiotherapy   machine learning   computer science   bibliometric analysis  

摘要： BackgroundMachine learning is now well-developed in non-small cell lung cancer (NSCLC) radiotherapy. But the research trend and hotspots are still unclear. To investigate the progress in machine learning in radiotherapy NSCLC, we performed a bibliometric analysis of associated research and discuss the current research hotspots and potential hot areas in the future. MethodsThe involved researches were obtained from the Web of Science Core Collection database (WoSCC). We used R-studio software, the Bibliometrix package and VOSviewer (Version 1.6.18) software to perform bibliometric analysis. ResultsWe found 197 publications about machine learning in radiotherapy for NSCLC in the WoSCC, and the journal Medical Physics contributed the most articles. The University of Texas MD Anderson Cancer Center was the most frequent publishing institution, and the United States contributed most of the publications. In our bibliometric analysis, "radiomics" was the most frequent keyword, and we found that machine learning is mainly applied to analyze medical images in the radiotherapy of NSCLC. ConclusionThe research we identified about machine learning in NSCLC radiotherapy was mainly related to the radiotherapy planning of NSCLC and the prediction of treatment effects and adverse events in NSCLC patients who were under radiotherapy. Our research has added new insights into machine learning in NSCLC radiotherapy and could help researchers better identify hot research areas in the future.

关键词： Authentication   Vehicular ad hoc networks   Security   Protocols   Public key   Privacy   Computer science   certificateless signature   provable security   revocation   vehicular ad hoc network (VANET)  

摘要： In the vehicular ad hoc network (VANET), the communication between the vehicle and other nodes is performed in an open channel, which puts forward the requirements for its privacy security and message integrity. Most previous protocols either frequently verify identities before accepting traffic information or do not involve identity revocation mechanisms, and they may assume that third parties are fully trusted. To further solve the above problem, a certificateless-based anonymous and revocable authentication protocol for vehicle-to-vehicle communications is proposed in this article. Our construction separates the identity authentication process from the traffic message verification, which not only avoids the disadvantage of a frequent identity revocation list (IRL) checking but also reduces the overhead in communication and message authentication. These features can make "identity authentication once, broadcast efficiency " really happen. In addition, since our authentication process is based on certificateless signature, it can resist malicious key generation centers (KGCs) and road-side units (RSUs), which is very necessary for privacy-sensitive application scenarios. Finally, the performance analyses show that our proposal is superior to the existing schemes in terms of authentication speed and communication overhead.

关键词： Computer Science   Computer Forensics   Cybersecurity   Malware Detection   Fileless Malware Prevention  

摘要： The rapid advancements in cyber-attack strategies are in parallel with the measures for detection, analysis, and prevention. Attackers have recently developed fileless malware that can simply bypass existing security mech-anisms. Researchers publish reports to help discover fileless malware and to better understand the threat's scope to counteract it. However, with the lack of studies on fileless malware regarding the classification and the scale of the threat, they have not been thoroughly analyzed. As a result, in this research, we explored the most recent advancements in fileless malware prevention and detection and highlighted future research challenges. We also propose an analytical approach based on the attack strategies and attributes of the selected sample. Our method simplifies feature extraction and reduces processing load. Furthermore, compared to the static analysis we do not need for decompression and unpacking for the analysis. We applied the proposed method on a real case example. It has been seen that information about fileless malware detection, working mechanism, attack method and attacker named "Kovter" can be accessed. Our approach is advantageous and can be applied as a new technique for fileless malware detection to protect systems from cyber threats. This paper also presents an insight to the fileless malware threat and provides a basic review of the methods and techniques used in the detection and analysis of fileless malware attacks.