Search results

In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.

Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.

A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.

This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.

It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.

Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.

Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.

We have developed in this paper a morphological disambiguation hybrid system for the Arabic language that identifies the stem, lemma and root of a given sentence words. Following an out-of-context analysis performed by the morphological analyser Alkhalil Morpho Sys, the system first identifies all the potential tags of each word of the sentence. Then, a disambiguation phase is carried out to choose for each word the right solution among those obtained during the first phase. This problem has been solved by equating the disambiguation issue with a surface optimization problem of spline functions. Tests have shown the interest of this approach and the superiority of its performances compared to those of the state of the art.

The study's main objective is to evaluate the morphological developments in the characteristics of the spatial configurations of the residential layouts in Kerman, Iran, in examining the impact on the level of visual privacy through the spectrum of permeability and wayfinding in space syntax analysis.

In this paper, plan graph analysis is used to measure the syntactic properties of seven topological residential architecture plans in Kerman, Iran, built from the 1970s to 2010s. The methodology involves the development of mathematical measurements to signify permeability and simulation of visibility graph analysis (VGA) to indicate wayfinding.

The findings reveal the residential layouts of Iranian houses tend to be less integrated over decades of design development from the 1970s to 2010s. Reduction in spatial integration corresponds to increase segregation allowing for enhanced visual privacy. The study underpins that, even with the constraints in the scale of the house and reduction in the number of nodes, as evident in the design of the modern residential layout, the efficient level of visual privacy is still achievable with regards to the standards demanded by the local culture.

The study examines the development in residential spatial configuration and building scale on visual privacy through a proposed methodology based on the level of permeability and wayfinding measured as a combined effect using the space syntax analysis and visual accessibility.

This paper is intended to assess the developments conducted on the master plan of Old Najaf, mainly in three areas: the Imam Ali Holy Shrine and its surroundings, the Great Market Area and the location of the Town of Visitors.

In order to analyse the implementation of the transformation phases in Old Najaf, the Strengths, Weaknesses, Opportunities, and Threats (SWOT) technique was used to identify and organise the strengths, weaknesses, opportunities and threats related to the examined case study of the city's historic centre. At the first stage, all available data (photographs, maps, documents and reports) were collected from different sources, including previous studies by governmental institutions, departments and agencies. Ultimately, the SWOT analysis was used for each identified phase in the morphological evolution of the historic centre. This can offer an opportunity to observe the implications of urban planning practices in Old Najaf from the mid-20th century to the present day. In order to identify the well-organised urban design practices and appropriate strategies, the implemented studies and projects were examined by the four factors of the SWOT analysis.

The current results have revealed important urban transformations, already made and/or ongoing, of those aforementioned three main areas, which imply a great loss of the city's traditional character and urban heritage. Further, the environmental and socio-economic issues should be involved in the analysis to evaluate how they have influenced the current outcomes of Old Najaf in relation to the urban configuration and orientation.

The rich cultural and architectural heritage of Al-Najaf historic centre is dramatically neglected and seriously threatened to be lost. Hence, conservation on both tangible and intangible levels is urgently needed. It is the first paper which focussed on this problem and tries to learn from the British Conservation Experiences in this field.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

The purpose of this paper is to analyze theory of inventive problem-solving (TRIZ) in terms of knowledge, skill, workload and affect to understand its effectiveness in enabling designers to achieve their optimized mental performance.

TASKS framework, which aims to capture the causal relations among Task workload, affect, skills, knowledge and mental stress, is adopted as our methodology. The framework supports the analysis of how a methodology influence designer’s affect, skills, knowledge and workload. TRIZ-related publications are assessed using the TASKS framework to identify the barriers and enablers in TRIZ-supported design.

TRIZ has limitations on its logic and tools. Nevertheless, it could create a beneficial impact on mental performance of designers.

This paper provides a theory-driven TRIZ usability analysis based on the materials in the literature following the TASKS framework. The impact of TRIZ, as an enabler or a barrier, has been analyzed in accomplishing a design task.

This paper aims to identify the aspects that social actors consider in constructing shared futures in communities. In their application in emerging countries, especially in the Global South, the socio-cultural particularities of communities and actors are often overlooked, generating friction or social conflicts. This paper presents two critical elements contributing to the debate: the importance of understanding Social Actors within a model of generating community futures in emerging countries; and the relevant factors that influence the actors in an exercise of building futures in communities.

From qualitative research, a case study of community foresight of the future was used: the future of Puerto Gaitán 2037 (Meta, Colombia). A method of information collection was applied from observation of the participants and analysis of documentation. The analysis method was the deductive qualitative analysis (DQA).

The participation of the social actors presents a model of five relevant elements that influence the actors for the successful construction of futures in communities. The first four factors, revealed from theory, are presented in real life. Likewise, a fifth factor is proven, Long-term thinking, which is evidenced by a model of application of futures studies for the specific context, applicable to the case of communities in countries of the Global South.

Although there are isolated examples of recommendations regarding studies to generate the future of communities, to the best of the author’s knowledge, this is the first study that presents concrete factors that contribute to guiding the construction of community futures from social actors, especially in countries of the Global South such as Colombia. It is also one of the first studies to use the DQA as a method of analysis in a topic of futures studies.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

This study aims to reveal how the COVID-19 vaccine was accepted in the Japanese Twitter-sphere. This study explores how the topics related to the vaccine promotion project changed on Twitter and how the topics that were likely to spread changed during the vaccine promotion project.

The computational social science methodology was adopted. This study collected all tweets containing the word “vaccine” using the Twitter API from March to October 2021 and conducted the following analysis: analyzing frequent words and identifying topics likely to spread through the cosine similarity and Tobit model.

First, vaccine hesitancy–related words were frequently mentioned during the vaccine introduction and dissemination periods and had diffusing power only during the former period. Second, vaccine administration–related words were frequently mentioned and diffused through April to May and had diffusing power throughout the period. The background to these findings is that the sentiment of longing for vaccines outweighed that of hesitancy toward vaccines during this period.

This study finds that the timing of the rise in vaccine hesitation sentiment and the timing of the start of vaccine supply were misaligned. This is one of the reasons that Japan, which originally exhibited strong vaccine hesitancy, did not face vaccine hesitancy in the COVID-19 vaccine promotion project.

Assessing whether a book is relevant or suitable for use in teaching materials is not an easy and haphazard matter, various methods and theories have been offered by researchers in studying this matter. Taking a study of the context of textbooks, researchers found the urgency that textbooks are a foundation for education, socialization and transmission of knowledge and its construction. Researchers offer another approach, namely by using praxeology as a study tool so that the goals of the textbooks previously intended are fulfilled.

The researcher uses a qualitative approach through grounded theory. Grounded theory procedures are designed to develop a well-integrated set of concepts that provide a thorough theoretical explanation of the social phenomena under study. A grounded theory must explain as well as describe. It may also implicitly provide some degree of predictability, but only with respect to certain conditions (Corbin and Strauss, 1990). Document analysis in conducting this research study. Document analysis itself examines systematic procedures for reviewing or evaluating documents, both printed and electronic materials.

Two issues regarding gender acquisition have been investigated in L2 Arabic acquisition studies; the order in which L2 Arabic learners acquire certain grammatical features of the gender system and the effect of L1 on the acquisition of some grammatical features from L2 grammatical gender. Arabic has a two-gender system that classifies all nouns, animate and inanimate, as masculine or feminine. Verbs, nouns, adjectives, personal, demonstrative and relative pronouns related to nouns in the syntactic structure of sentences show gender agreement.

In practice, as a book intended for non-speakers, the book is presented using a general view of linguistic theory. In relation to the gender agreement, the presentation of the book begins and is inserted with the concepts of nouns and verbs. Returning to the praxeology context, First, The Know How (Praxis) explains practice (i.e. the tasks performed and the techniques used). Second, To Know Why or Knowledge (logos) which explains and justifies practice from a technological and theoretical point of view. Answering the first concept, the exercise presented in the book is a concept with three clusters explained at the beginning of the discussion. And the second concept, explained with a task design approach which includes word categorization by separating masculine and feminine word forms.

Practically, this research obtains perspectives studied from a textbook, namely the Arabic gender agreement is presented with various examples of noun contexts; textbook authors present book concepts in a particular way with regard to curriculum features and this task design affects student performance, and which approach is more effective for developing student understanding. Empirically, the material is in line with the formulation of competency standards for non-Arabic speakers in Indonesia.

With this computational search, the researcher found a novelty that was considered accurate by taking the praxeology context as a review in the analysis of non-speaking Arabic textbooks, especially in the year 2022 (last data collection in September) there has been no study on this context. So then, the researcher finds other interests in that praxeology can examine more broadly parts of the task of the contents of the book with the approach of relevant linguistic theories.