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This research addresses the complex challenge of recognizing hand gestures irrespective of the user's body posture, a crucial issue in medical treatment for people with speech impairments and human-machine interfaces where precise gesture interpretation is vital. The aim is to engineer an advanced hand gesture recognition system, effective across various body positions and camera viewpoints. A novel flexible camera arrangement was employed, integrating a CNN-Transformer hybrid model, leveraging the strengths of Convolutional Neural Networks and the self-attention mechanism of Transformers. Developed using Python and the PyTorch deep learning framework, the system focuses on sophisticated image processing techniques. A thorough literature review on gesture recognition systems and multi-view analysis was conducted to inform the development. The system demonstrated exceptional accuracy in recognizing hand gestures in diverse body postures and from multiple camera perspectives, significantly outperforming existing methods. It marked a significant advancement in decoding complex gestures, a key aspect for medical applications and intricate human-machine is primarily interactions. This beneficial for people with speech impairments, rehabilitation, and in human-machine interfaces, poised to revolutionize patient care and enhance interaction with advanced machinery and computer systems.

This study addresses the vulnerabilities of traditional monocular camera-based face recognition systems, emphasizing the need for improved security and reliability in biometric authentication under varying environmental conditions, lighting, and human poses. To counteract the risk of spoofing attacks using masks or static images, we introduce a multi-angle stereo camera system. This system is strategically designed to capture facial imagery from multiple perspectives, thereby enhancing depth perception and spatial accuracy, crucial for high-security authentication. Employing a novel image processing approach, the study integrates a Convolutional Neural Networks (CNN) with a simple Boolean operation to differentiate the landmarks detected on each camera. This method exploits CNN’s robust feature extraction capabilities and the effective usage of stereo camera, enabling precise detection and analysis of 3D facial landmarks. Such an approach significantly bolsters the system’s ability to differentiate between genuine faces and deceptive representations like masks or static images. Empirical results demonstrate that the stereo camera configuration substantially improves recognition accuracy, reducing both false positives and negatives, especially in controlled spoofing scenarios. The advanced 3D facial landmark detection further reinforces the system ’ s security. With its enhanced robustness and security, the developed system shows great potential for applications in areas requiring stringent identity verification, such as banking, public facilities, and smart home technologies.

Attribute-based encryption () is a cryptographic framework that provides flexible access control by allowing encryption based on user attributes. is widely applied in cloud storage, file sharing, e-Health, and digital rights management. schemes rely on hard cryptographic assumptions such as pairings and others (pairing-free) to ensure their security against external and internal attacks. Internal attacks are carried out by authorized users who misuse their access to compromise security with potentially malicious intent. One common internal attack is the attribute collusion attack, in which users with different attribute keys collaborate to decrypt data they could not individually access. This paper focuses on the ciphertext-policy (-), a type of where ciphertexts are produced with access policies. Our first work is to carry out the attribute collusion attack against several existing pairing-free - schemes. As a main contribution, we introduce a novel attack, termed the anonymous key-leakage attack, concerning the context in which users could anonymously publish their secret keys associated with certain attributes on public platforms without the risk of detection. This kind of internal attack has not been defined or investigated in the literature. We then show that several prominent pairing-based - schemes are vulnerable to this attack. We believe that this work will contribute to helping the community evaluate suitable - schemes for secure deployment in real-life applications.

In the manufacture of integrated circuits (ICs), copper is used primarily as the multilevel interconnect material, which is manufactured with a dual damascene technique utilizing chemical mechanical polishing (CMP) to planarize overburdened materials. However, there are many challenges for copper CMP technique to produce a surface with a superior planarity and local device surface finish with minimal dishing and erosion while achieving uniform copper blanket film under specific thickness. Considering these challenges, this study pioneered the development of a three-dimensional microstructural model for polishing pads, which is based on image processing algorithms to construct the porous feature structure of polishing pad in conjunction with generating a layer of surface asperities, allowing for an accurate assessment of the effect of downward pressure during CMP on the microstructure of polishing pads. Moreover, this study also develop the new calibration method based on finite element simulation method for determining the mechanism of material removal by abrasive particles as well as the passivation of thin copper blanket film in polishing slurry. Results of this study include not only investigations of the copper blanket wafer’s surface roughness after CMP process but also the development of a new methodology of calibrating the material removal rates (MRRs) validated through comparison with CMP experiments. These findings can be further applied for developing CMP process model, and for advanced applications.

1.8 micrometer-thick magnesium hydride films were synthesized in a single-step process by reactive plasma-assisted sputtering. The MgH2 thin films, which were deposited on two types of flexible surfaces (namely graphite and polyimide foils) were found to adhere on both substrates. In all cases, XRD analysis revealed an as-deposited thin film consisting of alpha-MgH2, a tetragonal, rutile-type crystal structure (space group \\#136). The hydrogen sorption capacities of the uncapped films were studied over successive desorption/absorption cycles performed at 350 {\\textdegree}C. The first desorption always shows a slow kinetics that can be explained by a superficial oxidation of the films. However, once the passivating layer is removed, the following dehydrogenations occur faster. Multiple cycling of the film deposited on polyimide resulted in delamination of the film and its conversion into loose powder. As for MgH2 deposited on the flexible graphite substrate, a fully reversible capacity was observed over 28 cycles with no delamination of the film. Upon cycling, the microstructure of the film has evolved from homogeneous fibrous to an untextured morphology with a higher degree of crystallinity.

The accomplishments that 2003 Peace Prize Laureate Shirin Ebadi has achieved have come from her concern not only about her country, or solely the role of women in Islamic countries and the world, but also for universal human rights. Committed to protecting human rights, she feels they are the foundation for creating a more just and free world for all. Quoc-Benjamin details Ebadi's lecture on human rights connection to peace and social development entitled Women, Democracy, and Islam in June 2004 at UN Headquarters in New York.

On May 26, 2004, Sec Gen Kofi Annan delegates, UN staff and members of civil society affiliated with the UN to a lecture entitled \"Who Is Afraid of Human Rights?,\" part of the Secretary-General's Lecture Series. Here, Quoc-Benjamin details the lecture series, which was followed with a question-and-answer session.

Dr Hans Rosling, a professor of international health at the Karolinska Institute in Stockholm, envisions the role of Gapminder's software as the crucial transmitter linking the statistical sources provided by the UN, Governments and non-governmental organizations to a civil society that needs to make use of such information. Equipped with educational tools such as those by Gapminder, both the public and policy makers could convert multiple databases with numerical statistics into an attractive garden filled with blooming flowers of accomplished global goals, which he has always dreamed about.

Quoc-Benjamin discusses the border dispute between Nigeria and Cameroon. Among other things, the UN has employed a host of measures, ranging from diplomatic mediation to financial incentives, to ensure both countries abide by it.

At CRYPTO 2017, Rosca, Sakzad, Stehle and Steinfeld introduced the Middle--Product LWE (MPLWE) assumption which is as secure as Polynomial-LWE for a large class of polynomials, making the corresponding cryptographic schemes more flexible in choosing the underlying polynomial ring in design while still keeping the equivalent efficiency. Recently at TCC 2019, Lombardi, Vaikuntanathan and Vuong introduced a variant of MPLWE assumption and constructed the first IBE scheme based on MPLWE. Their core technique is to construct lattice trapdoors compatible with MPLWE in the same paradigm of Gentry, Peikert and Vaikuntanathan at STOC 2008. However, their method cannot directly offer a Hierachical IBE construction. In this paper, we make a step further by proposing a novel trapdoor delegation mechanism for an extended family of polynomials from which we construct, for the first time, a Hierachical IBE scheme from MPLWE. Our Hierachy IBE scheme is provably secure in the standard model.