18 research outputs found
Book Review: Backhaus, Peter (2007): Linguistic Landscapes: A Comparative Study of Urban Multilingualism in Tokyo. Clevedon: Multilingual Matters; 158 Pages ISBN 9781853599460
No full textBackhaus examines urban multilingualism in the linguistic landscape of Tokyo, the capital city of Japan. In this monograph, the linguistic landscape is seen as a sub-discipline of sociolinguistics. The significance of this monograph to linguistic landscape research is that it represents the first comprehensive approach tackling multilingualism in the linguistic landscape and overcoming a range of methodological problems facing former studies. In this sense, Backhaus’s approach in data collection and analysis may help linguistic landscapers and researchers to undertake research in multilingualism in the linguistic landscape. The current work comprises acknowledgements, a foreword by Bernard Spolsky, six chapters, an appendix, references, and an index. While the first three chapters represent an introduction and theoretical background, the fourth chapter in turn paves the way for the application of an empirical study in Tokyo’s linguistic landscape, applied in chapter five.That chapter one discusses the examination of written language in the public space of metropolises is the bulk of Backhaus’s work. In this respect, the author (p.1) refers to previous studies such as Halliday (1972), who considers the city not only a place of talk, but also a place of writing and reading. At the same time, this work focuses on ‘urban language contact in the written medium: the languages of the signs’. Backhaus (p.1) holds:Every urban environment is a myriad of written messages on public display: office and shop signs, billboards, and neon advertisements, traffic signs, topographic information and area maps, emergency guidance and political poster campaigns, stone inscriptions, and enigmatic graffiti discourse.The author maintains that these messages contribute to the making of the linguistic landscape of any given place.In chapter two, Semiotic Background and Terminology, Backhaus gives an introduction to the main features of language use on signs, arguing that the examination of multilingualism on signs in the public space differs from other modes of communication in written and spoken contexts. In addition, the writer discusses different definitions and interpretations of the term linguistic landscape and senses and types of the term ‘sign’. After Itagi and Singh (2002), the author (p.10) draws a distinction between the noun ‘linguistic landscape’ and the gerund ‘linguistic landscaping’. While the former refers to ‘the planning and implementation of actions pertaining to language on signs’, the latter relates to ‘the result of these actions’. Throughout his monograph, Backhaus maintains a distinction between these two terms as cited above. As maintained by Backhaus (p.12), only the paper introduced by Landry and Bourhis (1997) established this field of study as a coherent discipline, even though several previous studies employed linguistic landscape research. This is mainly apparent in Backhaus’s expansion upon the definition of survey items suggested by Landry and Bourhis (1997). In chapter three, Previous Approaches to the Linguistic Landscape: An Overview, Backhaus gives a comprehensive overview of previous linguistic landscape studies conducted in different urban settings, including Brussels (Tulp, 1978), Montreal (Monnier, 1989), Paris and Dakar (Calvet, 1990,1994), and Lira, a town in Uganda (Reh, 2004). In light of these studies, the author notices that the language policy of the state does not indicate which code(s) prevail(s) in the public space, whose language(s) is /are mainly manifested in language practices on nonofficial signs.. The author also discusses the methodological issues followed in the above studies to arrive at a congruent methodological framework aiming at examining multilingualism from a sociolinguistic point of view.In the light of the methodology followed in the abovementioned studies, Chapter four outlines the main concerns that envelope the sociolinguistics of the linguistic landscape. Interestingly, the chapter aims to bridge the gap between theory and practice by introducing three research questions aiming at directing the current work. These research parameters include linguistic landscape by whom, for whom, and the general language situation. To accomplish this study, the writer applies both qualitative and quantitative procedures while gathering and analysing data. According to the writer, this chapter attempts to find a coding scheme suitable for carrying out a sociolinguistic study in the linguistic landscape and devoid of methodological problems.In chapter five, the author (p.64) introduces a frame for studying the linguistic landscape and applies a fine-grained coding scheme to a corpus of signs. According to Backhaus, a sound data collection procedure requires two conditions: the determination of the geographical limits of the survey area and the unit of analysis. Backhaus investigated the linguistic landscape of 29 survey areas of the Yamanote Line, a circular railway line connecting a number of major city centres in Tokyo. These stations represent a multi-layered picture of the city centre in the sense that they include very busy and less crowded districts. The boundaries of each survey area were specified as consisting of an area located between the traffic lights of two consecutive intersections , wherein the poles of traffic lights represent the end of any given survey area. The survey items were also thoroughly defined (p.66):A sign was considered to be any piece of written text within a spatially definable frame. The underlining definition is physical, not semantic. It is rather broad, including anything from the small handwritten sticker attached to a lamp-post to huge commercial billboards outside a department store. Items such as push and pull stickers at entrance doors, lettered foot mats, or botanic explanation plates on trees were considered signs, too.In analysing data collected, the first step is to categorise countable items into monolingual and multilingual signs. Backhaus has excluded monolingual Japanese signs from data collected because he wants to examine urban multilingualism in Tokyo. A sign will be considered multilingual if it contains two languages or more, say Japanese and English (p.67). Backhaus presents a congruent methodology to study the linguistic landscape by introducing research parameters and analytical categories. These research questions include ‘linguistic landscaping by whom?, linguistic landscaping for whom?, and linguistic landscape quo vadis?’. These guiding questions are analysed according to nine criteria: languages contained, combinations, top-down and bottom-up forces, geographic distribution, code preference, part writing, visibility, idiosyncrasies, and layering (p.65).In chapter six, the writer closes his book by summarising the findings of the Tokyo sample, which are guided by the questions cited above. It reveals that nonofficial agencies are almost the main responsible for the majority of multilingual signs in the linguistic landscape of Tokyo, whereas official forces participate in the construction of multilingualism on signs by less than 30 per cent. The presence of complete and partial translations and transliterations on signs is very useful for the readers from the foreign and Japanese populations. It was noticed that English is generally confined to slogans, titles, and business names, while Japanese relates to more specific information. The general linguistic situation reveals the impact of language interference from Japanese into English, which is apparent in the number of linguistic idiosyncrasies noticed in the linguistic landscape. In comparing the older and newer versions of signs, there is a noticeable preference toward the use of foreign languages at the expense of Japanese, which shows signs of multilingualism in Tokyo’s linguistic landscape. However, Japanese will be the predominant language at least in the near future. As pointed out throughout, Backhaus presents a congruent methodological approach, which has added new dimensions to the existing field of linguistic landscape. More specifically, Backhaus identifies three guiding research questions: Linguistic Landscape by whom? Linguistic landscape for whom? Linguistic landscape quo vadis?. At the same time, his definition of the unit of analysis as described above contributed greatly to linguistic landscape research. Although Backhaus relies on former studies, Backhaus has created analytical categories neglected by previous studies, especially linguistic idiosyncrasies, and uses his own terminology, particularly ‘part writing’ with its main types adopted from the field of musicology: homophonic, mixed, polyphonic, monophonic signs. The same notions with the exception of monophonic signs have been implemented by Reh (2004), but the terminological designations are different. I wonder why Backhaus uses the term ‘polyphonic signs’, which might be replaced by code mixing or switching in that it may be mainly subdivided into intra-sentential code-switches and inter-sentential code-switches. This work also counts on the observations made by Scollon and Scollon (2003), especially those on code prominence and layering. For example, code preference as an analytical category in Backhaus’ quantitative study relies on placement and size in case that there is a conflict, font size outweighs order. As far as my current project is concerned, the relevance of this work comes from the methodological considerations provided, which will help to expand upon Backhaus’ paradigm to apply in the linguistic landscape of urban Jordan. In other words, we will adapt and build upon this methodological framework to devise a coding scheme suitable for the linguistic landscape of Jordanian cities.
Dimensionality Reduction, Modelling, and Optimization of Multivariate Problems Based on Machine Learning
No full textSimulation-based optimization design is becoming increasingly important in engineering. However, carrying out multi-point, multi-variable, and multi-objective optimization work is faced with the “Curse of Dimensionality”, which is highly time-consuming and often limited by computational burdens as in aerodynamic optimization problems. In this paper, an active subspace dimensionality reduction method and the adaptive surrogate model were proposed to reduce such computational costs while keeping a high precision. In this method, the active subspace dimensionality reduction technique, three-layer radial basis neural network approach, and polynomial fitting process were presented. For the model evaluation, a NASA standard test function problem and RAE2822 airfoil drag reduction optimization were investigated in the experimental design problem. The efficacy of the method was proved by both the experimental examples in which the adaptive surrogate model in a dominant one-dimensional active subspace is given and the optimization efficiency was improved by two orders. Furthermore, the results show that the constructed surrogate model reduced dimensionality and alleviated the complexity of conventional multivariate surrogate modeling with high precision
Innovative Energy-Efficient Proxy Re-Encryption for Secure Data Exchange in Wireless Sensor Networks
No full textIn the realm of wireless sensor networks (WSNs), preserving data integrity, privacy, and security against cyberthreats is paramount. Proxy re-encryption (PRE) plays a pivotal role in ensuring secure intra-network communication. However, existing PRE solutions encounter persistent challenges, including processing delays due to the transfer of substantial data to the proxy for re-encryption and the computational intensity of asymmetric cryptography. This study introduces an innovative PRE scheme that is meticulously customized for WSNs to enhance the secure communication between nodes within the network and external data server. The proposed PRE scheme optimizes efficiency by integrating lightweight symmetric and asymmetric cryptographic techniques, thereby minimizing computational costs during PRE operations and conserving energy for resource-constrained nodes. In addition, the scheme incorporates sophisticated key management and digital certificates to ensure secure key generation and distribution, which in turn, facilitates seamless authentication and scalable data sharing among the entities in WSN. This scheme maintains sensor-node data encryption and delegates secure re-encryption tasks exclusively to cluster heads, thereby reinforcing data privacy and integrity. Comprehensive evaluations of security, performance, and energy consumption validated the robustness of the scheme. The results confirm that the proposed PRE scheme significantly enhances the security, efficiency, and overall network lifetime of WSNs
Enhancing three variants of harmony search algorithm for continuous optimization problems
No full textMeta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. But the HS has a slow convergence rate, which causes the algorithm to have a weak exploitation process in finding the global optima. Different variants of HS introduced in the literature to enhance the algorithm and fix its problems, but in most cases, the algorithm still has a slow convergence rate. Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. In this work, we adopted a new improved version of OBL, to improve three variants of Harmony Search, by increasing the convergence rate speed of these variants and improving overall performance. The new OBL version named improved opposition-based learning (IOBL), and it is different from the original OBL by adopting randomness to increase the solution's diversity. To evaluate the hybrid algorithms, we run it on benchmark functions to compare the obtained results with its original versions. The obtained results show that the new hybrid algorithms more efficient compared to the original versions of HS. A convergence rate graph is also used to show the overall performance of the new algorithms
Spatial information of fuzzy clustering based mean best artificial bee colony algorithm for phantom brain image segmentation
No full textFuzzy c-means algorithm (FCM) is among the most commonly used in the medical image segmentation process. Nevertheless, the traditional FCM clustering approach has been several weaknesses such as noise sensitivity and stuck in local optimum, due to FCM hasn’t able to consider the information of contextual. To solve FCM problems, this paper presented spatial information of fuzzy clustering-based mean best artificial bee colony algorithm, which is called SFCM-MeanABC. This proposed approach is used contextual information in the spatial fuzzy clustering algorithm to reduce sensitivity to noise and its used MeanABC capability of balancing between exploration and exploitation that is explore the positive and negative directions in search space to find the best solutions, which leads to avoiding stuck in a local optimum. The experiments are carried out on two kinds of brain images the Phantom MRI brain image with a different level of noise and simulated image. The performance of the SFCM-MeanABC approach shows promising results compared with SFCM-ABC and other stats of the arts
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
No full textBackground: Research gaps refer to unanswered questions in the existing body of knowledge, either due to a lack of studies or inconclusive results. Research gaps are essential starting points and motivation in scientific research. Traditional methods for identifying research gaps, such as literature reviews and expert opinions, can be time consuming, labor intensive, and prone to bias. They may also fall short when dealing with rapidly evolving or time-sensitive subjects. Thus, innovative scalable approaches are needed to identify research gaps, systematically assess the literature, and prioritize areas for further study in the topic of interest. Objective: In this paper, we propose a machine learning–based approach for identifying research gaps through the analysis of scientific literature. We used the COVID-19 pandemic as a case study. Methods: We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. Our approach is based on the BERTopic topic modeling technique, which leverages transformers and class-based term frequency-inverse document frequency to create dense clusters allowing for easily interpretable topics. Our BERTopic-based approach involves 3 stages: embedding documents, clustering documents (dimension reduction and clustering), and representing topics (generating candidates and maximizing candidate relevance). Results: After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. The final list of research gaps identified 21 different areas, which were grouped into 6 principal topics. These topics were: “virus of COVID-19,” “risk factors of COVID-19,” “prevention of COVID-19,” “treatment of COVID-19,” “health care delivery during COVID-19,” “and impact of COVID-19.” The most prominent topic, observed in over half of the analyzed studies, was “the impact of COVID-19.” Conclusions: The proposed machine learning–based approach has the potential to identify research gaps in scientific literature. This study is not intended to replace individual literature research within a selected topic. Instead, it can serve as a guide to formulate precise literature search queries in specific areas associated with research questions that previous publications have earmarked for future exploration. Future research should leverage an up-to-date list of studies that are retrieved from the most common databases in the target area. When feasible, full texts or, at minimum, discussion sections should be analyzed rather than limiting their analysis to abstracts. Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction
PID controller tuning using multi-objective ant colony optimization for blood glucose level of a diabetic patient
No full textIn this research, a nonlinear suboptimal controller was provided for type 1 diabetes patients' blood glucose level regulation based on a Proportional-Integral-Derivative (PID) controller with Ant Colony Optimization (ACO). The ACO approach is used to determine the ideal PID controller gain settings within a stability area. This study simulates three cases of a physiological model of glucose regulation in people with type 1 diabetes (No insulin treatment, fixed insulin injection, and Controlled blood glucose concentration using a PID controller) by using the Bergman Model in the context of meal-induced disturbances. In terms of dynamic performance, such as a reduction in maximum overshoot, settling time, and rising time, simulation findings suggest that the proposed technique for PID tuning using the ACO algorithm is more adaptable and cost-effective.</p
Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation
No full textClustering using fuzzy C-means (FCM) is a soft segmentation method that has been extensively investigated and successfully implemented in image segmentation. FCM is useful in various aspects, such as the segmentation of grayscale images. However, FCM has some limitations in terms of its selection of the initial cluster center. It can be easily trapped into local optima and is sensitive to noise, which is considered the most challenging issue in the FCM clustering algorithm. This paper proposes an approach to solve FCM problems in two phases. Firstly, to improve the balance between the exploration and exploitation of improved global best-guided artificial bee colony algorithm (IABC). This is achieved using a new search probability model called PIABC that improves the exploration process by choosing the best source of food which directly affects the exploitation process in IABC. Secondly, the fuzzy clustering algorithm based on PIABC, abbreviated as PIABC-FCM, uses the balancing of PIABC to avoid getting stuck into local optima while searching for the best solution having a set of cluster center locations of FCM. The proposed method was evaluated using grayscale images. The performance of the proposed approach shows promising outcomes when compared with other related works
Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors
No full textSecuring multimedia data on disk drives is a major concern because of their rapidly increasing volumes over time, as well as the prevalence of security and privacy problems. Existing cryptographic schemes have high computational costs and slow response speeds. They also suffer from limited flexibility and usability from the user side, owing to continuous routine interactions. Dynamic encryption file systems can mitigate the negative effects of conventional encryption applications by automatically handling all encryption operations with minimal user input and a higher security level. However, most state-of-the-art cryptographic file systems do not provide the desired performance because their architectural design does not consider the unique features of multimedia data or the vulnerabilities related to key management and multi-user file sharing. The recent move towards multi-core processor architecture has created an effective solution for reducing the computational cost and maximizing the performance. In this paper, we developed a parallel FUSE-based encryption file system called ParallelFS for storing multimedia files on a disk. The developed file system exploits the parallelism of multi-core processors and implements a hybrid encryption method for symmetric and asymmetric ciphers. Usability is significantly enhanced by performing encryption, decryption, and key management in a manner that is fully dynamic and transparent to users. Experiments show that the developed ParallelFS improves the reading and writing performances of multimedia files by approximately 35% and 22%, respectively, over the schemes using normal sequential encryption processing
Improved flat mobile core network architecture for 5G mobile communication systems
No full textThe current mobile network core is built based on a centralized architecture, including the S-GW and P-GW entities to serve as mobility anchors. Nevertheless, this architecture causes non-optimal routing and latency for control messages. In contrast, the fifth generation (5G) network will redesign the network service architecture to improve changeover management and deliver clients a better Quality-of-Experience (QoE). To enhance the design of the existing network, a distributed 5G core architecture is introduced in this study. The control and data planes are distinct, and the core network also combines IP functionality anchored in a multi-session gateway design. We also suggest a control node that will fully implement the control plane and result in a flat network design. Its architecture, therefore, improves data delivery, mobility, and attachment speed. The performance of the proposed architecture is validated by improved NS3 simulation to run several simulations, including attachment and inter- and intra-handover. According to experimental data, the suggested network is superior in terms of initial attachment, network delay, and changeover management
