Search Results (47)

The economic and legal framework is transforming with the change in the globalization paradigm, accompanied by structural and quantitative changes in intellectual property assessment. This study aims to justify commercialization and analyze the innovation management of intellectual property as a fundamental socio-economic institution and improve theoretical perspectives on its current development processes. This study surveyed 100 companies to identify the factors determining intellectual property use and its commercialization. The analysis of the structure of intellectual property revealed a 14% decrease in trademark applications and a 2% increase in patent applications. This research highlights the specifics of intellectual property generation through machine learning: mass creation of new objects, reduction in innovation product development cycles, increased accuracy of market demand forecasting, and adaptive problem solving. An analysis of budget expenditures on intellectual property in the EU based on the specific value of patent activity identified five classification groups (ranging from 0.17 to 0.23% to 1.23–2.26% of GDP), each exhibiting different economic activities and innovation intensity. Full article

This paper critically analyses the application of the trademark dilution doctrine under Jordanian trademark law, exposing fundamental deficiencies arising from statutory ambiguity and inconsistent judicial interpretation. The indeterminate definition of a “well-known” trademark in the second section has led to an indiscriminate classification of foreign marks as inherently well-known, resulting in courts extending automatic dilution protection without a rigorous evidentiary assessment. This practice fosters an implicit presumption favouring foreign trademark holders, potentially disadvantaging domestic marks that may not receive commensurate protection, thereby undermining the principle of equitable trademark enforcement. This paper argues for a systematic recalibration of Jordan’s dilution framework. A comparative analysis of the well-established dilution doctrines in the United States and European Union identifies jurisprudential best practices that could enhance the doctrinal coherence and judicial application of dilution protection in Jordan. Furthermore, drawing on the WIPO Joint Recommendation as a normative foundation, the paper proposes legal reforms to rectify inconsistencies, ensuring a more balanced and principled approach to trademark dilution. We argue that aligning Jordan’s legal framework with international standards strengthens the discourse on harmonising intellectual property law and ensuring equitable trademark protection in emerging markets. Full article

As emerging economies play a pivotal role in global growth, understanding the impact of environmental factors, especially air pollution, on innovation is crucial. This study empirically examines the relationship between air pollution and innovation performance in EAGLE (emerging and growth leading economies) using a 20-year dataset (2000–2019) and employing 2SLS (two-stage least square) and FMOLS (fully modified ordinary least square) estimation techniques. The key findings of the study reveal that air pollution hampers R&D activities and patent applications by weakening human capital, diverting resources, and creating an unfavorable research environment. The results remain robust across multiple control variables and alternative estimation techniques. These findings highlight the urgent need for pollution control policies to mitigate its adverse effects on innovation, offering valuable insights for policymakers striving to enhance innovation resilience amid environmental challenges. This study uniquely explores the causal impact of air pollution on the macro-level innovation performance of a country. Full article

This study analyzes the patent landscape of Saudi Arabia from the announcement of Saudi Vision 2030 in late April 2016 to September 2024, utilizing the Patsnap database to evaluate patent grants across various organizations. The findings reveal a gradual increase in patent registrations, with Saudi Aramco leading in patent grants, followed by King Faisal University (KFU), King Fahd University of Petroleum and Minerals (KFUPM), King Abdullah University of Science and Technology (KAUST), and King Abdulaziz University (KAU). SABIC, a prominent industry player in Saudi Arabia, has registered most of its patents using its European Head Office address and holds extensive collaborations with international partners, generating numerous patents. The analysis identifies the top patent offices where KSA organizations seek protection, including the United States Patent and Trademark Office (USPTO), Saudi Authority for Intellectual Property (SAIP), European Patent Office (EPO), the China National Intellectual Property Administration (CNIPA), and the German Patent and Trade Mark Office. However, the limited number of registrations at the SAIP highlights a need for improvement. The primary application domains encompass borehole/well accessories, measurement devices, organic chemistry, computing, and chemical/physical processes. The landscape reveals that Saudi Aramco and KFUPM focus predominantly on upstream and downstream technologies, while KAU, KFU, and KAUST concentrate on life sciences. Key findings indicate a significant increase in patent activity since the vision announcement, suggesting a growing focus on innovation within Saudi Arabia. However, the concentration of patents among a few major players (Saudi Aramco and SABIC) and the underrepresentation of patents filed with the Saudi Authority of Intellectual Property (SAIP) highlight areas for improvement. This study emphasizes the necessity to support small and medium enterprises (SMEs) and healthcare research institutions to foster broader participation in innovation and protect novel technologies. This research contributes valuable insights into the current state of patenting activities in Saudi Arabia and outlines opportunities for enhancing the country’s innovation ecosystem. Full article

This study presents an in-depth molecular and structural characterization of novel biopolyesters developed under the trademark Bluepha^®. The primary aim was to elucidate the relationship between chemical structure, chain architecture, and material properties of these biopolyesters to define their potential applications across various sectors. Proton nuclear magnetic resonance (¹H NMR) analysis identified the biopolyesters as poly[(R)-3-hydroxybutyrate-co-(R)-3-hydroxyhexanoate] (PHBH) copolymers, containing 4% and 10% molar content of hydroxyhexanoate (HH) units, respectively. Mass spectrometry analysis of PHBH oligomers, produced via controlled thermal degradation, further confirmed the chemical structure and molecular architecture of the PHBH samples. Additionally, multistage electrospray ionization mass spectrometry (ESI-MS/MS) provided insights into the chemical homogeneity and arrangement of comonomer units within the copolyester chains, revealing a random distribution of hydroxyhexanoate (HH) and hydroxybutyrate (HB) units along the PHBH chains. X-ray diffraction (XRD) patterns demonstrated partial crystallinity in the PHBH samples. The thermal properties, including glass transition temperature (T_g), melting temperature (T_m), and melting enthalpy (ΔH_m), were found to be lower in PHBH than in poly(R)-3-hydroxybutyrate (PHB), suggesting a broader application potential for the tested PHBH biopolyesters. Full article

The task of trademark text recognition is a fundamental component of scene text recognition (STR), which currently faces a number of challenges, including the presence of unordered, irregular or curved text, as well as text that is distorted or rotated. In applications such as trademark infringement detection and analysis of brand effects, the diversification of artistic fonts in trademarks and the complexity of the product surfaces where the trademarks are located pose major challenges for relevant research. To tackle these issues, this paper proposes a novel recognition framework named SwinCornerTR, which aims to enhance the accuracy and robustness of trademark text recognition. Firstly, a novel feature-extraction network based on SwinTransformer with EFPN (enhanced feature pyramid network) is proposed. By incorporating SwinTransformer as the backbone, efficient capture of global information in trademark images is achieved through the self-attention mechanism and enhanced feature pyramid module, providing more accurate and expressive feature representations for subsequent text extraction. Then, during the encoding stage, a novel feature point-retrieval algorithm based on corner detection is designed. The OTSU-based fast corner detector is presented to generate a corner map, achieving efficient and accurate corner detection. Furthermore, in the encoding phase, a feature point-retrieval mechanism based on corner detection is introduced to achieve priority selection of key-point regions, eliminating character-to-character lines and suppressing background interference. Finally, we conducted extensive experiments on two open-access benchmark datasets, SVT and CUTE80, as well as a self-constructed trademark dataset, to assess the effectiveness of the proposed method. Our results showed that the proposed method achieved accuracies of 92.9%, 92.3% and 84.8%, respectively, on these datasets. These results demonstrate the effectiveness and robustness of the proposed method in the analysis of trademark data. Full article

The traditional approach of single-word brand names faces constraints due to trademarks, prompting a shift towards fusing two or more words to craft unique and memorable brands, exemplified by brands such as SalesForce^© or SnapChat^©. Furthermore, brands such as Kodak^©, Xerox^©, Google^©, Häagen-Dazs^©, and Twitter^© have become everyday names although they are not real words, underscoring the importance of brandability in the naming process. However, manual evaluation of the vast number of possible combinations poses challenges. Artificial intelligence (AI), particularly natural language processing (NLP), is emerging as a promising solution to address this complexity. Existing online brand name generators often lack the sophistication to comprehensively analyze meaning, sentiment, and semantics, creating an opportunity for AI-driven models to fill this void. In this context, the present document reviews AI, NLP, and text-to-speech tools that might be useful in innovating the brand name generation and evaluation process. A systematic search on Google Scholar, IEEE Xplore, and ScienceDirect was conducted to identify works that could assist in generating and evaluating brand names. This review explores techniques and datasets used to train AI models as well as strategies for leveraging objective data to validate the brandability of generated names. Emotional and semantic aspects of brand names, which are often overlooked in traditional approaches, are discussed as well. A list with more than 75 pivotal datasets is presented. As a result, this review provides an understanding of the potential applications of AI, NLP, and affective computing in brand name generation and evaluation, offering valuable insights for entrepreneurs and researchers alike. Full article

A registered trademark represents one of a company’s most valuable intellectual assets, acting as a safeguard against possible reputational damage and financial losses resulting from infringements of this intellectual property. To be registered, a mark must be unique and distinctive in relation to other trademarks which are already registered. In this paper, we describe the CMAD, an acronym for Conflicting Marks Archive Dataset. This dataset has been meticulously organized into pairs of marks (Number of pairs = 18,355) involved in copyright infringement across word, figurative and mixed marks. Organizations sought to register these marks with the National Institute of Industrial Property (INPI) in Brazil, and had their applications denied after analysis by intellectual property specialists. The robustness of this dataset is ensured by the intrinsic similarity of the conflicting marks, since the decisions were made by INPI specialists. This characteristic provides a reliable basis for the development and testing of tools designed to analyze similarity between marks, thus contributing to the evolution of practices and computer-based solutions in the field of intellectual property. Full article

Nanotechnologies are being increasingly widely used in advanced energy fields. Triboelectric nanogenerators (TENGs) represent a class of new-type flexible energy-harvesting devices with promising application prospects in future human societies. As one of the most important parts of TENG devices, triboelectric materials play key roles in the achievement of high-efficiency power generation. Conventional polymer tribo-negative materials, such as polytetrafluoroethylene (PTFE), polyvinylidene difluoride (PVDF), and the standard polyimide (PI) film with the Kapton^® trademark based on pyromellitic anhydride (PMDA) and 4,4′-oxydianiline (ODA), usually suffer from low output performance. In addition, the relationship between molecular structure and triboelectric properties remains a challenge in the search for novel triboelectric materials. In the current work, by incorporating functional groups of trifluoromethyl (–CF₃) with strong electron withdrawal into the backbone, a series of fluorine-containing polyimide (FPI) negative friction layers have been designed and prepared. The derived FPI-1 (6FDA-6FODA), FPI-2 (6FDA-TFMB), and FPI-3 (6FDA-TFMDA) resins possessed good solubility in polar aprotic solvents, such as the N,N-dimethylacetamide (DMAc) and N-methyl-2-pyrrolidone (NMP). The PI films obtained via the solution-casting procedure showed glass transition temperatures (T_g) higher than 280 °C with differential scanning calorimetry (DSC) analyses. The TENG prototypes were successfully fabricated using the developed PI films as the tribo-negative layers. The electron-withdrawing trifluoromethyl (–CF₃) units in the molecular backbones of the PI layers provided the devices with an apparently enhanced output performance. The FPI-3 (6FDA-TFMDA) layer-based TENG devices showcased an especially impressive open-circuit voltage and short-circuit current, measuring 277.8 V and 9.54 μA, respectively. These values were 4~5 times greater when compared to the TENGs manufactured using the readily accessible Kapton^® film. Full article

This article has examined the effect of the duration of membership in the World Trade Organization (WTO) on the submission of trademarks by countries’ residents. The analysis used an unbalanced sample of 124 countries (including developed and developing countries) and, primarily, the binominal regression approach supplemented by the generalized method of moments estimator, which was utilized for the robustness check. Results have shown that the effect of the duration of WTO membership on trademarks works through the channel of trade costs. This effect is positive for less developed economies and negative for relatively advanced economies. These findings reflect the fact that as countries spend more time as WTO members, they experience a higher submission of patents in relation to trademarks, especially if they enjoy an improvement in their real per capita income (and export complex products). Furthermore, countries that receive higher Aid for Trade flows (which help to reduce trade costs) experience yet a higher number of trademark applications, but to a lesser extent than patent filings. Full article

The current Human Development Index (HDI) has a promising potential to consider further dimensions, the technological dimensions in specific, in order to absorb various innovational aspects whenever human development is to be benchmarked among countries. Hence, the innovation-based HDI was developed herein using one of the well-known Multi-Criteria Decision Making (MCDM) techniques: the Preference Ranking Organization Method for Enrichment of Evaluations II (PROMETHEE II) considering a mixture of technological criteria, including the Global Innovation Index (GII) itself. The G8 countries, as leading countries worldwide, were investigated in this regard in order to attain such a benchmarking attempt. The model was formulated using seven criteria selected from the World Bank (WB) Open Data (such as High-technology exports as a percentage of manufactured exports, Research and development (R&D) expenditure as a percentage of GDP, and Trademark applications, …, etc.) along with the GII, for the purpose of conducting an MCDM-based evaluation model for the G8 countries. The results of the developed index affirm that the ranking of the G8 countries has distinctly been changed as a consequence of considering technological and innovational aspects, compared to the original HDI (i.e., USA +4—from 5th to 1st; Canada −4, from 2nd to 6th). By utilizing MCDM methods (including PROMETHEE II), this paper also affirms that an infinite number of indexes can be developed in the future by employing a huge number of WB indicators with respect to various MCDM approaches. Hence, international communities are in need of setting up commonly accepted guidelines in order to facilitate having a unified prioritization (i.e., unified preference) regarding the potential criteria and/or indicators to be considered globally for better sustainable development. Full article

Milk is considered a complete meal that requires supervision to determine its suitability for human consumption. The development of sustainable devices that evaluate food properties has gained importance due to the necessity of integrating these instruments into the production chain. However, the materials employed to develop it, such as polymers, semiconductors, and glass, lack sustainability and require specialized equipment to fabricate them. Different chemical techniques have been used to miniaturize these detection systems such as microfluidics, which have been used in milk component detection using colorimetry. In this work, a cantilever beam paper-based microfluidic system is proposed to evaluate differences in milk, according to nutritional information, using its electromechanical response. A 20-microliter milk drop is deposited in the system, which induces hygroexpansion and deflection due to liquid transport within the paper. Likewise, a conductive path is added on the beam top surface to supply a constant current that induces heat to evaporate the solution. According to the results obtained, it is possible to point out differences between trademarks with this microfluidic system. The novelty of this system relies on the paper electromechanical response that integrates the hygroexpansion-induced displacement, which can be used for further applications such as milk microtesters instead of colorimetric tests that use paper as a property-evaluation platform in combination with chemical reactions. Full article

Patents and related statistics are the indicators of technological progress. There have been controversial discussions about the value of patents as an indicator of technological advancement. Patent research has been conducted for research and development to develop the core framework of the United States Patent and Trademark Office. This study was conducted to classify the patents in terms of technology-assisted instruction using the Patent Co-citation Analysis (PCA) method and factor analysis. For the analysis, education, demonstration, rendition, instructional aids, instructional equipment, teaching aids, and didactic materials were chosen as keywords to construct a citation relationship network of patents and to classify core patent issues. The study results showed that 225 patents were cited more than 25 times. They were classified into 11 categories. The result provided information on the development and application of technology-assisted education to develop teaching tools further. Full article

Though much attention is dedicated to the development of its research and innovation policy, the European Union constantly struggles to match the level of the strongest innovators in the world. Therefore, there is a necessity to analyze the individual efforts and conditions of the 27 member states that might determine their final innovative performance. The results of a scientific literature review showed that there is a growing interest in the usage of artificial intelligence when seeking to improve decision-making processes. Data envelopment analysis, as a branch of computational intelligence methods, has proved to be a reliable tool for innovation efficiency evaluation. Therefore, this paper aimed to apply DEA for the assessment of the European Union’s innovation efficiency from 2000 to 2020, when innovation was measured by patent, trademark, and design applications. The findings showed that the general EU innovation efficiency situation has improved over time, meaning that each programming period was more successful than the previous one. On the other hand, visible disparities were found across the member states, showing that Luxembourg is an absolute innovation efficiency leader, while Greece and Portugal achieved the lowest average efficiency scores. Both the application of the DEA method and the gathered results may act as viable guidelines on how to improve R&I policies and select future investment directions. Full article

Nanotechnology and nanomaterials have gained much attention in recent years due to their remarkable features. Among nanoparticles, photocatalytic material, such as zinc oxide, have shown tremendous applications in each and every field of science. In the present research, investigators have synthesized zinc oxide nanoparticles (ZnONPs) using Scallion’s peel extract. ZnONPs were both spherical and rod-shaped, where the size for spherical particles was 40–100 nm and rod-shaped, particles size was more than 200 nm as confirmed by microscopic techniques. The typical trademark bands of ZnONPs at 400–800 cm⁻¹ were revealed by infrared spectroscopy, which also showed bands of carbonyl and hydroxyl groups. The hydrodynamic size by particle size analyzer (PSA) shows a size near about 200 nm in diameter. Furthermore, the synthesized ZnONPs were used to assess their potential as a micronutrient for the plant and nano adsorbent for the removal of antibiotics (ampicillin) and methylene blue dye from the simulated wastewater. The antibiotic and dye removal were observed under UV light and visible light against contact time. In comparison to control seeds, seeds grown with ZnONPs have shown better germination and seedling. It could be concluded that ZnONPs acted as an important nanosized source of nutrition for agricultural applications. Thus, the effect of ZnONPs has been proven as a nano-based nutrient source for agricultural purposes. The remediation study found that remediation of both ampicillin and methylene blue dye was efficient under UV light under similar experimental parameters from the simulated wastewater by the ZnONPs. Full article