Search Results (8)

Product safety is a significant issue, and leading industrialized nations, which are largely based on manufacturing, invest considerable time and resources to address product safety-related challenges. The social issues surrounding product safety can directly impact consumers’ health and safety, and failing to comply with product safety standards or providing inaccurate information to consumers can infringe on consumer rights. Therefore, product safety must be approached as a social issue with broad societal implications, necessitating government efforts to manage and oversee these concerns. Simplifying the complexities of product safety management and developing a systematic evaluation framework at the government level are essential. Product safety is a socially significant issue, and leading industrialized nations, which are largely based on manufacturing, invest considerable time and resources to address product safety-related challenges. This study developed a product safety evaluation framework for manufacturing companies based on Korean consumers’ awareness of product safety. It was designed to comprehensively assess manufacturing companies’ technological, procedural, and perceptual levels from a product safety perspective. A total of 101 companies participated, categorized into 43 electrical product manufacturers, 22 daily goods manufacturers, and 36 children’s product manufacturers. The primary goal of this evaluation framework is to enable companies to conduct self-assessments and ultimately promote a culture of product safety. Additionally, the framework aims to assist the government in establishing a systematic product safety evaluation system. Full article

With the continuous advancement of information technology, a growing number of works, including articles, paintings, and music, are being digitized. Digital content can be swiftly shared and disseminated via the Internet. However, it is also vulnerable to malicious plagiarism, which can seriously infringe upon the rights of creators and dampen their enthusiasm. To protect creators’ rights and interests, a sophisticated method is necessary to authenticate digital intellectual property rights. Traditional authentication methods rely on centralized, trustworthy organizations that are susceptible to single points of failure. Additionally, these methods are prone to network attacks that can lead to data loss, tampering, or leakage. Moreover, the circulation of copyright information often lacks transparency and traceability in traditional systems, which leads to information asymmetry and prevents creators from controlling the use and protection of their personal information during the authentication process. Blockchain technology, with its decentralized, tamper-proof, and traceable attributes, addresses these issues perfectly. In blockchain technology, each node is a peer, ensuring the symmetry of information. However, the transparent feature of blockchains can lead to the leakage of user privacy data. Therefore, this study designs and implements an Ethereum blockchain-based intellectual property authentication scheme with privacy protection. Firstly, we propose a method that combines elliptic curve cryptography (ECC) encryption with digital signatures to achieve selective encryption of user personal information. Subsequently, an authentication algorithm based on Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) is adopted to complete the authentication of intellectual property ownership while encrypting personal privacy data. Finally, we adopt the InterPlanetary File System (IPFS) to store large files, solving the problem of blockchain storage space limitations. Full article

This paper presents a two-stage hierarchical neural network using image classification and object detection algorithms as key building blocks for a system that automatically detects a potential design right infringement. This neural network is trained to return the Top-N original design right records that highly resemble the input image of a counterfeit. This work proposes an ensemble neural network (ENN), an artificial neural network model that aims to deal with a large amount of counterfeit data and design right records that are frequently added and deleted. First, we performed image classification and objection detection learning per design right using acclaimed existing models with high accuracy. The distributed models form the backbone of the ENN and yield intermediate results aggregated at a master neural network. This master neural network is a deep residual network paired with a fully connected network. This ensemble layer is trained to determine the sub-models that return the best result for a given input image of a product. In the final stage, the ENN model multiplies the inferred similarity coefficients to the weighted input vectors produced by the individual sub-models to assess the similarity between the test input image and the existing product design rights to see any sign of violation. Given 84 design rights and the sample product images taken meticulously under various conditions, our ENN model achieved average Top-1 and Top-3 accuracies of 98.409% and 99.460%, respectively. Upon introducing new design rights data, a partial update of the inference model was performed an order of magnitude faster than the single model. The ENN maintained a high level of accuracy as it was scaled out to handle more design rights. Therefore, the ENN model is expected to offer practical help to the inspectors in the field, such as customs at the border that deal with a swarm of products. Full article

With the advent of the digital age, traditional lifestyle activities, such as reading books, referencing recipes, and enjoying music, have progressively transitioned from offline to online. However, numerous issues plague the conventional approach to digital copyright protection. This is especially true in the realm of recipe protection, where the rights and interests of original creators are inadequately safeguarded due to the widespread dissemination of a large number of recipes on the Internet. This primarily stems from the high costs of gathering evidence, incomplete coverage of evidence collection, and the inability to identify and halt infringement activities in a timely manner during the process of traditional digital copyright protection. Therefore, this study designs and implements a blockchain-based digital recipe copyright protection scheme to address the issues of insufficient legal evidence and cumbersome processes in traditional digital copyright protection. First, we enhance standard short text similarity calculation method SimHash, boosting the accuracy of text similarity detection. We then utilize the decentralization, immutability, time-stamping, traceability, and smart contract features of blockchain technology for data privacy protection. We employ the Interplanetary File System (IPFS) to store raw data, thereby ensuring user privacy and security. Lastly, we improve the proxy voting node selection in the existing delegated proof of stake (DPOS) consensus mechanism. According thorough evaluation and empirical analysis, the scheme effectively improves the accuracy of text similarity detection. Simultaneously, the enhanced DPOS mechanism effectively rewards nodes with excellent performance and penalizes nodes exhibiting malicious behavior. In this study, we successfully designed and implemented an innovative digital recipe copyright protection scheme. This scheme effectively enhances the accuracy of text similarity detection; ensures the privacy and security of user data; and, through an enhanced DPOS mechanism, rewards well-performing nodes while penalizing those exhibiting malicious behavior. Full article

Integrating artificial intelligence (AI) technologies into law enforcement has become a concern of contemporary politics and public discourse. In this paper, we qualitatively examine the perspectives of AI technologies based on 20 semi-structured interviews of law enforcement professionals in North Carolina. We investigate how integrating AI technologies, such as predictive policing and autonomous vehicle (AV) technology, impacts the relationships between communities and police jurisdictions. The evidence suggests that police officers maintain that AI plays a limited role in policing but believe the technologies will continue to expand, improving public safety and increasing policing capability. Conversely, police officers believe that AI will not necessarily increase trust between police and the community, citing ethical concerns and the potential to infringe on civil rights. It is thus argued that the trends toward integrating AI technologies into law enforcement are not without risk. Policymaking guided by public consensus and collaborative discussion with law enforcement professionals must aim to promote accountability through the application of responsible design of AI in policing with an end state of providing societal benefits and mitigating harm to the populace. Society has a moral obligation to mitigate the detrimental consequences of fully integrating AI technologies into law enforcement. Full article

High-voltage transmission technology has advanced quickly with the overall development and increased use of renewable energy. More demands on the insulating system are made when high-voltage power systems evolve. One of the significant factors is the sharp rise in population density, which led to the high demand for electricity. Right-of-way infringement is a problem that frequently occurs these days. Transmission is done over a rated capacity; as a result, the transmission line heats up, the insulation ages, and the electric field becomes distorted. The insulating system is prone to fail too soon when the operating voltage inverses or when there is a significant temperature differential. Environmentally friendly insulating materials have received much attention recently. A synergistic optimisation of heat resistance properties, mechanical properties, and dielectric properties must be accomplished before these materials can be used in high-voltage transmission systems. They must also withstand harsh electrical and thermal shocks such as overvoltage and short-circuit faults. One of the developments that has become a popular research topic is the constantly evolving tower design. This review article presents advancements in cross-arm technology in high-voltage transmission systems to elaborate on the limitations and contributions of different research work. Full article

In recent years, the wide application of deep neural network models has brought serious risks of intellectual property rights infringement. Embedding a watermark in a network model is an effective solution to protect intellectual property rights. Although researchers have proposed schemes to add watermarks to models, they cannot prevent attackers from adding and overwriting original information, and embedding rates cannot be quantified. Therefore, aiming at these problems, this paper designs a high embedding rate and tamper-proof watermarking scheme. We employ wet paper coding (WPC), in which important parameters are regarded as wet blocks and the remaining unimportant parameters are regarded as dry blocks in the model. To obtain the important parameters more easily, we propose an optimized probabilistic selection strategy (OPSS). OPSS defines the unimportant-level function and sets the importance threshold to select the important parameter positions and to ensure that the original function is not affected after the model parameters are changed. We regard important parameters as an unmodifiable part, and only modify the part that includes the unimportant parameters. We selected the MNIST, CIFAR-10, and ImageNet datasets to test the performance of the model after adding a watermark and to analyze the fidelity, robustness, embedding rate, and comparison schemes of the model. Our experiment shows that the proposed scheme has high fidelity and strong robustness along with a high embedding rate and the ability to prevent malicious tampering. Full article

Online copyright infringement is one of the toughest challenges the content industry has faced in the twenty first century. Article 8(3) of the Information Society Directive, implemented under section 97A of the UK Copyright, Designs and Patents Act, 1988, provides an injunctive remedy in response to such online infringement. Given the elusive nature of the website operators and the sheer number of their users, rights owners have turned to the Internet Service Providers (ISPs) to implement the injunctions granted under section 97A to block websites with infringing content. In their battle to keep pace with online infringers, the UK courts have permitted significant compromises to the procedures while granting these injunctive blocking orders. One of the pioneers in this line of cases in the UK is the Pirate Bay case (TPB case), which ruled as a matter of law that the procedure under Section 97A does not require the alleged infringers to be made parties to those proceedings. TPB case also marks the trend of the ISPs consenting to an order of injunction, and not defending the proceedings. This has resulted in the absence of any adverse party in the proceedings under section 97A. This threatens the basic tenets of procedural fairness and propriety, having adverse consequences on both the substantive and procedural aspects, evident in the cases that followed TPB case. This article examines the aspects of the judgment in TPB case that led to these procedural compromises, whether it had any basis in the pre-existing case law, what the nature of an injunction under section 97A is and how the subsequent line of cases have followed TPB case as a precedent. It further explores the adverse consequences of the procedural compromises and whether any safeguards are available against such compromises. Full article