Search results for: minority forms of information processing

Authors: Mengxin Feng, Feng Xu, Zhiyong Lai

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As a typical representative of the countryside, traditional Chinese villages are rich in cultural landscape resources and historical information, but they are still in continuous decline. The problems of people's weak protection awareness and low cultural recognition are still serious, and the protection of cultural heritage is imminent. At the same time, with the rapid development of rural tourism, its cultural value has been explored and paid attention to again. From the perspective of tourists, this study aimed to explore people's perception and identity of cultural landscape resources under the current cultural tourism development background. We selected eleven typical landscape elements of Lingshui Village, a traditional village in Beijing, as research objects and conducted a questionnaire survey with two scales of perception and identity to explore the characteristics of people's perception and identification of landscape elements. We found that there was a strong positive correlation between the perception and identity of each element and that geographical location influenced visitors' overall perception. The perception dimensions scored the highest in location, and the lowest in history and culture, and the identity dimensions scored the highest in meaning and lowest in emotion. We analyzed the impact of visitors' backgrounds on people's perception and identity characteristics and found that age and education were two important factors. The elderly had a higher degree of perceived identity, as the familiarity effect increased their attention. Highly educated tourists had more stringent criteria for perception and identification. The above findings suggest strategies for conserving and optimizing landscape elements in the traditional village to improve the acceptance and recognition of cultural information in traditional villages, which will inject new vitality into the development of traditional villages.

Keywords: traditional village, tourist perception, landscape elements, perception and identity

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Authors: Khamdan Cahyari, Pratikno Hidayat

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Indonesia has produced more than 1.8 million ton pineapple fruit in 2013 of which turned into waste due to industrial processing, deterioration and low qualities. It was estimated that this waste accounted for more than 40 percent of harvested fruits. In addition, pineapple leaves were one of biomass waste from pineapple farming land, which contributed even higher percentages. Most of the waste was only dumped into landfill area without proper pretreatment causing severe environmental problem. This research was meant to valorize the pineapple waste for producing renewable energy source of biogas through mesophilic (30℃) anaerobic digestion process. Especially, it was aimed to investigate effect of substrate concentration of pineapple fruit waste i.e. peel, core as well as effect of microwave pretreatment of pineapple leaves waste. The concentration of substrate was set at value 12, 24 and 36 g VS/liter culture whereas 800-Watt microwave pretreatment conducted at 2 and 5 minutes. It was noticed that optimum biogas production obtained at concentration 24 g VS/l with biogas yield 0.649 liter/g VS (45%v CH4) whereas microwave pretreatment at 2 minutes duration performed better compare to 5 minutes due to shorter exposure of microwave heat. This results suggested that valorization of pineapple waste could be carried out through biogas production at the aforementioned process condition. Application of this method is able to both reduce the environmental problem of the waste and produce renewable energy source of biogas to fulfill local energy demand of pineapple farming areas.

Keywords: pineapple waste, substrate concentration, microwave pretreatment, biogas, anaerobic digestion

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Authors: Aneeqa Suhail, Shabana Naveed

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The public sector (in both developed and developing countries) has gone through various waves of radical reforms in recent decades. In Pakistan, under the influence of New Public Management(NPM) Reforms; best practices of private sector are introduced in the public sector to modernize public organizations. Human Resource Information System (HRIS) has been popular in the private sector and proven to be a successful system, therefore it is being adopted in the public sector too. However, implementation of private business practices in public organizations us very challenging due to differences in context. This implementation gets further critical in Pakistan due to a centralizing tendency and lack of autonomy in public organizations. Adoption of HRIS by public organizations in Pakistan raises several questions: What challenges are faced by public organizations in implementation of HRIS? Are benefits of HRIS such as efficiency, process integration and cost reduction achieved? How is the previous system improved with this change and what are the impacts? Yet, it is an under-researched topic, especially in public enterprises. This study contributes to the existing body of knowledge by empirically exploring benefits and challenges of implementation of HRIS in public organizations. The research adopts a case study approach and uses qualitative data based on in-depth interviews conducted at various levels in the hierarchy including top management, departmental heads and employees. The unit of analysis is LESCO, the Lahore Electric Supply Company, a state-owned entity that generates, transmits and distributes electricity to 4 big cities in Punjab, Pakistan. The findings of the study show that LESCO has not achieved the benefits of HRIS as established in literature. The implementation process remained quite slow and costly. Various functions of HR are still in isolation and integration is a big challenge for the organization. Although the data is automated, the previous system of manually record maintenance and paperwork is still in work, resulting in the presence of parallel practices. The findings also identified resistance to change from top management and labor workforce, lack of commitment and technical knowledge, and costly vendors as major barriers that affect the effective implementation of HRIS. The paper suggests some potential actions to overcome these barriers and to enhance effective implementation of HR-technology. The findings are explained in light of an institutional logics perspective. HRIS’ new logic of automated and integrated HR system is in sharp contrast with the prevailing logic of process-oriented manual data maintenance, leading to resistance to change and deadlock.

Keywords: human resource information system, technological changes, state-owned enterprise, implementation challenges

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Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

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Authors: Xiaoqing Peng, Aijing Luo, Yang Chen

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Background: Cyberchondria, as an "emerging risk" accompanied by the information era, is a new abnormal pattern characterized by excessive or repeated online searches for health-related information and escalating health anxiety, which endangers people's physical and mental health and poses a huge threat to public health. Objective: To explore and discuss the research status, hotspots and trends of Cyberchondria. Methods: Based on a total of 77 articles regarding "Cyberchondria" extracted from Web of Science from the beginning till October 2019, the literature trends, countries, institutions, hotspots are analyzed by bibliometric analysis, the concept definition of Cyberchondria, instruments, relevant factors, treatment and intervention are discussed as well. Results: Since "Cyberchondria" was put forward for the first time in 2001, the last two decades witnessed a noticeable increase in the amount of literature, especially during 2014-2019, it quadrupled dramatically at 62 compared with that before 2014 only at 15, which shows that Cyberchondria has become a new theme and hot topic in recent years. The United States was the most active contributor with the largest publication (23), followed by England (11) and Australia (11), while the leading institutions were Baylor University(7) and University of Sydney(7), followed by Florida State University(4) and University of Manchester(4). The WoS categories "Psychiatry/Psychology " and "Computer/ Information Science "were the areas of greatest influence. The concept definition of Cyberchondria is not completely unified in the world, but it is generally considered as an abnormal behavioral pattern and emotional state and has been invoked to refer to the anxiety-amplifying effects of online health-related searches. The first and the most frequently cited scale for measuring the severity of Cyberchondria called “The Cyberchondria Severity Scale (CSS) ”was developed in 2014, which conceptualized Cyberchondria as a multidimensional construct consisting of compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals which was proved to be not necessary for this construct later. Since then, the Brazilian, German, Turkish, Polish and Chinese versions were subsequently developed, improved and culturally adjusted, while CSS was optimized to a simplified version (CSS-12) in 2019, all of which should be worthy of further verification. The hotspots of Cyberchondria mainly focuses on relevant factors as follows: intolerance of uncertainty, anxiety sensitivity, obsessive-compulsive disorder, internet addition, abnormal illness behavior, Whiteley index, problematic internet use, trying to make clear the role played by “associated factors” and “anxiety-amplifying factors” in the development of Cyberchondria, to better understand the aetiological links and pathways in the relationships between hypochondriasis, health anxiety and online health-related searches. Although the treatment and intervention of Cyberchondria are still in the initial stage of exploration, there are kinds of meaningful attempts to seek effective strategies from different aspects such as online psychological treatment, network technology management, health information literacy improvement and public health service. Conclusion: Research on Cyberchondria is in its infancy but should be deserved more attention. A conceptual consensus on Cyberchondria, a refined assessment tool, prospective studies conducted in various populations, targeted treatments for it would be the main research direction in the near future.

Keywords: cyberchondria, hypochondriasis, health anxiety, online health-related searches

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Authors: C. Busuioc, S. I. Jinga, E. Pavel

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The continuous need of more non-volatile memories with a higher storage capacity, smaller dimensions and weight, as well as lower costs, has led to the exploration of optical lithography on active media, as well as patterned magnetic composites. In this context, optical lithography is a technique that can provide a significant decrease of the information bit size to the nanometric scale. However, there are some restrictions that arise from the need of breaking the optical diffraction limit. Major achievements have been obtained by employing a vitoceramic material as active medium and a laser beam operated at low power for the direct writing procedure. Thus, optical discs with ultra-high density were fabricated by a conventional melt-quenching method starting from analytical purity reagents. They were subsequently used for 3D recording based on their photosensitive features. Naturally, the next step consists in the elucidation of the composition and structure of the active centers, in correlation with the use of silver and rare-earth compounds for the synthesis of the optical supports. This has been accomplished by modern characterization methods, namely transmission electron microscopy coupled with selected area electron diffraction, scanning transmission electron microscopy and electron energy loss spectroscopy. The influence of laser diode parameters, silver concentration and fluorescent compounds formation on the writing process and final material properties was investigated. The results indicate performances in terms of capacity with two order of magnitude higher than other reported information storage systems. Moreover, the fluorescent photosensitive vitroceramics may be integrated in other applications which appeal to nanofabrication as the driving force in electronics and photonics fields.

Keywords: data storage, fluorescent compounds, laser writing, vitroceramics

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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Authors: Geumchan Hwang

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Professional sport leagues in Europe and North America are shut down due to novel coronavirus disease (COVID-19) outbreak. Football leagues in Europe (e.g., La Liga, English Premier League, Bundesliga, Serie A, and Ligue 1) and big four professional sport leagues in North America (e.g., National Football League, Major League Baseball, National Basketball Association, and National Hockey League) are indefinitely suspended or delayed. COVID-19 outbreak has a growing negative impact on economics of sport leagues. For example, loss of revenue in Europe’s top five leagues due to the COVID-19 pandemic was estimated at € 4 billion and loss of revenue in the NBA was estimated at $650 million as of March 2020. In the unprecedented difficult situation, sport teams and leagues try to communicate with sport fans through diverse media platforms. In sport, however, very few studies have been done regarding how sport organizations effectively communicate with sport fans during pandemics, such as COVID-19 outbreak. Understanding sport organizations’ crisis communication is important to develop effective crisis management strategies for sport organizations. Therefore, the purpose of the study is to examine how sport organizations communicate with sport fans via online platforms in COVID-19 outbreak and how sport fans evaluate their communication strategies. 9 official sport league sites (i.e., five major football leagues in Europe and four major sport leagues in North America) and COVID-19 news articles published between January and June in 2020 will be analyzed in terms of coronavirus information, teams and players’ live update, fan interaction, fan support, and community engagement. In addition, comments posted on social media sites (i.e., Facebook and Twitter) of major sport leagues will be also analyzed to examine how sport fans perceive online messages provided by sport leagues as an effective communication strategy. To measure the effectiveness of crisis communication performance, five components (i.e., prompt, compassionate, honest, informative, and interactive) of crisis communication will be collected from leagues’ official websites information and social media posts. Upon completing data collection, content analysis method will be used to evaluate effectiveness of crisis communication among 9 professional sport leagues. The results of the study will provide athletic directors, administrators, and public relations managers in sport organizations with practical information regarding how athlete celebrities and sport organizations should interact with their fans in pandemic situations. In particular, this study will contribute to developing specific crisis management plan for sport organizations. For instance, football teams and leagues in Europe will be able to create standard manuals to minimize damages caused by disease outbreak, such as COVID-19 outbreak.

Keywords: COVID-19, communication, sport leagues, fans

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Authors: Joan O. Ogundele, Aladesanmi A. Oshodi, Adekunle I. Amoo

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Abstract In-vitro multi-enzyme protein digestibility (IVMPD) and some anti-nutritional factors (ANF) of five melon (egusi) seed flours (MSF) and their protein isolates (PI) were carried out. Their PI have potentials comparable to that of soya beans. It is important to know the IVMPD and ANF of these protein sources as to ensure their safety when adapted for use as alternate protein sources to substitute for cow milk, which is relatively expensive in Nigeria. Standard methods were used to produce PI of Citrullus colocynthis, Citrullus vulgaris, African Wine Kettle gourd (Lageneria siceraria I), Basket Ball gourd (Lagenaria siceraria II) and Bushel Giant Gourd (Lageneria siceraria III) seeds and to determine the ANF and IVMPD of the MSF and PI unheated and at 37oC. Multi-enzymes used were trypsin, chymotrypsin and peptidase. IVMPD of MSF ranged from (70.67±0.70) % (C. vulgaris) to (72.07± 1.79) % (L.siceraria I) while for their PI ranged from 74.33% (C.vulgaris) to 77.55% (L.siceraria III). IVMPD of the PI were higher than those of MSF. Heating increased IVMPD of MSF with average value of 79.40% and those of PI with average of 84.14%. ANF average in MSF are tannin (0.11mg/g), phytate (0.23%). Differences in IVMPD of MSF and their PI at different temperatures may arise from processing conditions that alter the release of amino acids from proteins by enzymatic processes. ANF in MSF were relatively low, but were found to be lower in the PI, therefor making the PI safer for human consumption as an alternate source of protein.

Keywords: Anti-nutrients, Enzymatic protein digestibility, Melon (egusi)., Protein Isolates.

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Authors: Seval Yilmaz, Filiz Bayrakci Karel, Ali Savas Koparal

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Textile products produced by leather have been indispensable for human consumption. Various chemicals are used to enhance the durability of end-products in the processing of leather products. The wastewaters from the leather industry which contain these chemicals exhibit toxic effects on the receiving environment and threaten the natural ecosystem. In this study, leather industry wastewater (LIW), which has high loads of contaminants, was treated using advanced treatment techniques instead of conventional methods. During the experiments, the performance of electrochemical methods was investigated. During the electrochemical experiments, the performance of batch electrooxidation (EO) using boron-doped diamond (BDD) electrodes with monopolar configuration for removal of chemical oxygen demand (COD) from LIW were investigated. The influences of electrolysis time, current density (which varies as 5 mA/cm², 10 mA/cm², 20 mA/cm², 30 mA/cm², 50 mA/cm²) and initial pH (which varies as 3,80 (natural pH of LIW), 7, 9) on removal efficiency were investigated in a batch stirred cell to determine the best treatment conditions. The current density applied to the electrochemical reactors is directly proportional to the consumption of electric energy, so electrical energy consumption was monitored during the experiment. The best experimental conditions obtained in electrochemical studies were as follows: electrolysis time = 60 min, current density = 30.0 mA/cm², pH 7. Using these parameters, 53.59% COD removal rates for LIW was achieved and total energy consumption was obtained as 13.03 kWh/m³. It is concluded that electrooxidation process constitutes a plausible and developable method for the treatment of LIW.

Keywords: BDD electrodes, COD removal, electrochemical treatment, leather industry wastewater

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Alex Gonzalez Caceres, Jan Karlshøj, Tor Arvid Vik

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Life cycle of residential buildings are expected to be several decades, 40% of European residential buildings have inefficient energy conservation measure. The existing building represents 20-40% of the energy use and the CO₂ emission. Since net zero energy buildings are a short-term goal, (should be achieved by EU countries after 2020), is necessary to plan the next logical step, which is to prepare the existing outdated stack of building to retrofit them into an energy efficiency buildings. In order to accomplish this, two specialize and widespread tool can be used Building Information Modelling (BIM) and life-cycle assessment (LCA). BIM and LCA are tools used by a variety of disciplines; both are able to represent and analyze the constructions in different stages. The combination of these technologies could improve greatly the retrofitting techniques. The incorporation of the carbon footprint, introducing a single database source for different material analysis. To this is added the possibility of considering different analysis approaches such as costs and energy saving. Is expected with these measures, enrich the decision-making. The methodology is based on two main activities; the first task involved the collection of data this is accomplished by literature review and interview with experts in the retrofitting field and BIM technologies. The results of this task are presented as an evaluation checklist of BIM ability to manage data and improve decision-making in retrofitting projects. The last activity involves an evaluation using the results of the previous tasks, to check how far the IFC format can support the requirements by each specialist, and its uses by third party software. The result indicates that BIM/LCA have a great potential to improve the retrofitting process in existing buildings, but some modification must be done in order to meet the requirements of the specialists for both, retrofitting and LCA evaluators.

Keywords: retrofitting, BIM, LCA, energy efficiency

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Authors: Mohamed Benaicha, Mahdi Allam

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A new two stage electrochemical process as a safe, large area and low processing cost technique for the production of semi-conducting CuInSe2 (CIS) thin films is studied. CuIn precursors were first potentiostatically electrodeposited onto molybdenum substrates from an acidic thiocyanate electrolyte. In a second stage, the prepared metallic CuIn layers were used as substrate in the selenium electrochemical deposition system and subjected to a thermal treatment in vacuum atmosphere, to eliminate binary phase formation by reaction of the Cu2-x Se and InxSey selenides, leading to the formation of CuInSe2 thin film. Electrochemical selenization from aqueous electrolyte is introduced as an alternative to toxic and hazardous H2Se or Se vapor phase selenization used in physical techniques. In this study, the influence of film deposition parameters such as bath composition, temperature and potential on film properties was studied. The electrochemical, morphological, structural and compositional properties of electrodeposited thin films were characterized using various techniques. Results of Cyclic and Stripping-Cyclic Voltammetry (CV, SCV), Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray microanalysis (EDX) investigations revealed good reproducibility and homogeneity of the film composition. Thereby optimal technological parameters for the electrochemical production of CuIn, Se as precursors for CuInSe2 thin layers are determined.

Keywords: photovoltaic, CIGS, copper alloys, electrodeposition, thin films

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

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Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

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Authors: Sarekha Woranuch, Rangrong Yoksan

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Active packaging has been developed based on the incorporation of certain additives, in particular antimicrobial and antioxidant agents, into packaging systems to maintain or extend product quality and shelf-life. Ferulic acid is one of the most effective natural phenolic antioxidants, which has been used in food, pharmaceutical and active packaging film applications. However, most phenolic compounds are sensitive to oxygen, light and heat; its activities are thus lost during product formulation and processing. Grafting ferulic acid onto polymer is an alternative to reduce its loss under thermal processes. Therefore, the objectives of the present research were to study the thermal stability of ferulic acid after grafting onto chitosan, and to investigate the possibility of using ferulic acid-grafted chitosan (FA-g-CTS) as an antioxidant for active biodegradable packaging film. FA-g-CTS was incorporated into biodegradable film via a two-step process, i.e. compounding extrusion at temperature up to 150 °C followed by blown film extrusion at temperature up to 175 °C. Although incorporating FA-g-CTS with a content of 0.02–0.16% (w/w) caused decreased water vapor barrier property and reduced extensibility, the films showed improved oxygen barrier property and antioxidant activity. Radical scavenging activity and reducing power of the film containing FA-g-CTS with a content of 0.04% (w/w) were higher than that of the naked film about 254% and 94%, respectively. Tensile strength and rigidity of the films were not significantly affected by adding FA-g-CTS with a content of 0.02–0.08% (w/w). The results indicated that FA-g-CTS could be potentially used as an antioxidant for active packaging film.

Keywords: active packaging film, antioxidant activity, chitosan, ferulic acid

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Authors: Karolína Augustovaá

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Turkey’s eastern borders have been at the center of criticism by the European Commission who condemns restrictions against Kurdish civilians as the result of Turkey’s military operations against terrorist organizations (namely PKK). Yet, the Commission has launched economic and political support for numerous military projects along the Iran-Turkey border to fight cross-border crime (namely “illegal” migration) along its external borders. Whilst border externalization has been extensively examined in the EU’s wide neighborhood, its analysis from the ground in conflict zones is emerging. The existing analysis also rarely considers the impact of external border management beyond international migration - on the local context and its people. However, tough externalization policies at borders, where local wars are fought, are fundamental to scrutinize as they invite us to question the effects of EU’s migration management on diverse communities navigating their life along external borders. To fill this research lacunae, this article examines intersections between the local military operations and international (EU-Turkey) migration management at the Turkey’s border with Iran and questions their impact on the everyday struggles of people living at and migrating across the border. To do so, it applies critical feminist and military literature to border studies. Methodologically, the article draws upon ethnographic research in Van (Eastern Turkey), using participant observations and interviews with sixty participants. This article argues that the EU’s externalization policies add to the violence generated by the local militarized conflict and eventually (re-)produce it in the forms of push-backs and physical violence against people who daily cross the border irregularly for their physical/economic survival. By doing so, I suggest that (inter)national fears of terrorism and migration inter-sect, materialize and affect everyday sites of diverse racialized groups living at and moving across external borders, such as international migrants (Afghans) and the local residents (Kurds) at the Turkey-Iran border. This article highlights the need to analyze the local border context in tandem with international migration management in the EU’s wider neighborhood to understand how conflict and violence evolves there.

Keywords: european union border externalization, eastern turkey, migration, conflict, kurdish question

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Adi Levy

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Military and security personnel defections during nonviolent resistance (NVR) campaigns are recognized as an effective way of undermining the regime’s power, but they also may generate moral dilemmas that contradict the moral standing of NVR tactics. NVR campaigns have been primarily praised for their adherence to moral and legal norms, yet some of NVR tactics raise serious ethical concerns. This paper focuses on NVR tactics that seek to promote defections and disobedience within military and security personnel to sustain their campaign. Academic literature regarding NVR tactics indicates that compared to violent forms of resistance, defections are more likely to occur when security forces confront nonviolent activists. Indeed, defections play a strategically fundamental role in nonviolent campaigns, particularly against authoritarian regimes, as it enables activists to undermine the regime’s central pillars of support. This study examines the events of the Arab Spring and discusses the ethical problems that arise in nonviolent activists’ promotion of defections and disobedience. The cases of Syria and Egypt suggest that the strategic promotion of defections and disobedience was significantly effective in sustaining the campaign. Yet, while such defections enhance nonviolent activists’ resilience, how they are promoted can be morally contentious and the consequences can be dire. Defections are encouraged by social, moral and emotional appeals that use the power disparities between unarmed civilians and powerful regimes to affect soldiers and security personnel’s process of decision-making. In what is commonly referred to as dilemma action, nonviolent activists deliberately entangle security forces in a moral dilemma that compels them to follow a moral code to protect unarmed civilians. In this way, activists sustain their struggle and even gain protection. Nonviolent activists are likely to be completely defeated when confronted with armed forces. Therefore they rely on the military and security personnel’s moral conscious of convincing them to refrain from using force against them. While this is effective, it also leaves soldiers and security forces exposed to the implications and punishments that might follow their disobedience or defection. As long as they remain nonviolent, activists enjoy civilian immunity despite using morally contentious tactics. But the severe implications brought upon defectors. As a result, demand a deep examination of this tactic’s moral permissibility and a discussion that assesses culpability for the moral implications of its application.

Keywords: culpability, defections, nonviolence, permissibility

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Authors: Ewenam Gbormittah

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Because of the effects of the pandemic, companies are focusing on the future of work arrangements for their employees. This includes adapting to a remote or hybrid working model. It is important that employers provide those working remotely or in a hybrid mode a rewarding onboarding experience and opportunities for interaction. Although, Information & Communication Technologies (ICT) have transformed the ways organisations manage employees over the years, there is still a need for a platform where organisations can adjust their onboarding to suit the social and interactive aspects of their employees, to facilitate successful integration. This study aimed to explore this matter by investigating whether Virtual Reality (VR) technology contributes to new employees integration into the organisation during their job-onboarding (JOB) process. The research questions are as follows: (1) To what extent does VR have an impact on employees successful integration into the organisation, and (2) How does VR help elements of new employees Psychological Contract (PC) during the course of interactions. An exploratory case study approach, which consisted of a semi-structured interview was conducted on 20 employees, split from two different case organisations. The results of the data were analysed according to each case, and then a cross-case comparison was provided. The results have generated 8 themes, presenting in excess of 7 sub-themes for CS1 and presented 7 themes, in excess of 7 sub-themes for CS2. The cross-case analysis has revealed that VR does have the potential to support employees integration into the organisation. However, the effects were shown to be stronger for employees in CS2, compared to employees in CS1. The results highlight practical implications for onboarding psychology and strategic talent solutions within recruitment. Such strategy this research particularly outlines, involves providing insights on how to manage the PC of employees from the recruitment stage to creating successful employment relationships.

Keywords: job-onboarding, psychological contract, virtual reality, case study one, case study two

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Authors: Hyoseop Shin

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As design rules become smaller, semiconductor processes are becoming a new problem because defects that were not previously a problem affect yields. Recently, semiconductor fine inspection technology has been required to develop high-precision, high-efficiency technology to manage defects, and the detection capability of semiconductor inspection equipment has been improved by studying defect detection through a comprehensive understanding of semiconductor inspection equipment, semiconductor processing, and defects. The optimal test parameters were applied to actual equipment by conditional comparison results aimed at detecting 30 nm particles in low-density semiconductors, thereby improving the detection capability of particle inspection equipment. The improvement of 30 nm particle detection has been studied based on the results of image analysis and evaluation through defect simulation. Factor analysis such as wavelength polarization incident angle of semiconductor equipment parameters and acquisition of scattering signals of actual equipment has been found to have found the optimal conditions of detection power and contributed to defect detection. As a result, it was confirmed that the detection power differed significantly in the experiment of 266 nm wavelength and P incident polarization conditions using P polarization, and 30 nm particles were detected, contributing to the yield improvement.

Keywords: electronic simulation system, a semiconductor defect, Reynolds' equation, semiconductor optical measuring equipment, facility engineering

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Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

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Authors: Aliyaa Zaidan, Rayan Bahabri

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The twenty-first century revealed an accelerating change and intensifying complexity of communication technology. Online social networking engines have gained astounding recognition worldwide. The influence of those social media platforms on dentistry and dental students is not well established. Therefore, this study aimed to evaluate the impact of using social media on professional and profile level among dental students in Saudi Arabia. A cross-sectional study developed via online questionnaire concerning on social media usage and its effect on professional and profile level of dental students and dental interns from several universities in Saudi Arabia. A total of 296 dental students and dental interns in Saudi Arabia responded to the questionnaire. Ninety-eight percent of the participants usually use the social media on a regular basis. Most social media sites used among the participants were Snapchat, Instagram, and YouTube by 85%, 81%, 77% respectively. Forty-one percent of the participants agreed that using social media in the dental field is a necessity nowadays. Thirty-eight percent of participants agreed that using social media is an easy way to gain a reliable knowledge, while 43% agreed that social media will improve the quality of healthcare. Furthermore, 65% of the students deemed using social media for academic purposes will improve their performance. Fifty-five percent of the respondents often use social media tools to obtain information about subject or procedures related to the dental field. Regarding profile reputation of dental students, 40% of the respondents agreed that their profile information published on social networking websites, could be used by others to judge their level of professionalism. Male and female dental students both agreed that their reputation would be adversely affected by 37%,63%, respectively, if their social networking activity were viewed by members of the public. The discrepancy among student levels reveals that social media profile positively influence the acceptance to postgraduate programs (P= 0.01).

Keywords: dental students, professional, reputation, social media

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Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Andrea Zielke-Nadkarni

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Pain management is a question of quality of life and an indicator for nursing quality. Chronic pain which is predominant in oncology and palliative nursing situations is perceived today as a multifactorial, individual emotional experience with specific characteristics including the sociocultural dimension when dealing with migrant patients. This dimension of chronic pain is of major importance in professional nursing of migrant patients in hospices or palliative care units. Objectives of the study are: 1. To find out more about the sociocultural views on pain and nursing care, on customs and nursing practices connected with pain of both Turkish Muslim and German Christian women, 2. To improve individual and family oriented nursing practice with view to sociocultural needs of patients in severe pain in palliative care. In a qualitative-explorative comparative study 4 groups of women, Turkish Muslims immigrants (4 from the first generation, 5 from the second generation) and German Christian women of two generations (5 of each age group) of the same age groups as the Turkish women and with similar educational backgrounds were interviewed (semistructured ethnographic interviews using Spradley, 1979) on their perceptions and experiences of pain and nursing care within their families. For both target groups the presentation will demonstrate the following results in detail: Utterance of pain as well as “private” and “public” pain vary within different societies and cultures. Permitted forms of pain utterance are learned in childhood and determine attitudes and expectations in adulthood. Language, especially when metaphors and symbols are used, plays a major role for misunderstandings. The sociocultural context of illness may include specific beliefs that are important to the patients and yet seem more than far-fetched from a biomedical perspective. Pain can be an influential factor in family relationships where respect or hierarchies do not allow the direct utterance of individual needs. Specific resources are often, although not exclusively, linked to religious convictions and are significantly helpful in reducing pain. The discussion will evaluate the results of the study with view to the relevant literature and present nursing interventions and instruments beyond medication that are helpful when dealing with patients from various socio-cultural backgrounds in painful end-oflife situations.

Keywords: pain management, migrants, sociocultural context, palliative care

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Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

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Authors: Yusarina Mat-Isa, Zuraidah Mohd-Sanusi, Mohd-Nizal Haniff, Paul A. Barnes

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In view that money laundering has become eminent for banking institutions, it is an obligation for the banking institutions to adopt a risk-based approach as the integral component of the accepted policies on anti-money laundering. In doing so, those involved with the banking operations are the most critical group of personnel as these are the people who deal with the day-to-day operations of the banking institutions and are obligated to form a judgement on the level of impending risk. This requirement is extended to all relevant banking institutions staff, such as tellers and customer account representatives for them to identify suspicious customers and escalate it to the relevant authorities. Banking institutions staffs, however, face enormous challenges in identifying and distinguishing money launderers from other legitimate customers seeking genuine banking transactions. Banking institutions staffs are mostly educated and trained with the business objective in mind to serve the customers and are not trained to be “detectives with a detective’s power of observation”. Despite increasing awareness as well as trainings conducted for the banking institutions staff, their competency in assessing money laundering risk is still insufficient. Several gaps have prompted this study including the lack of behavioural perspectives in the assessment of money laundering risk in the banking institutions. Utilizing experimental approach, respondents are randomly assigned within a controlled setting with manipulated situations upon which judgement of the respondents is solicited based on various observations related to the situations. The study suggests that it is imperative that informed judgement is exercised in arriving at the decision to proceed with the banking services required by the customers. Judgement forms a basis of opinion for the banking institution staff to decide if the customers posed money laundering risk. Failure to exercise good judgement could results in losses and absorption of unnecessary risk into the banking institutions. Although the banking institutions are exposed with choices of automated solutions in assessing money laundering risk, the human factor in assessing the risk is indispensable. Individual staff in the banking institutions is the first line of defence who are responsible for screening the impending risk of any customer soliciting for banking services. At the end of the spectrum, the individual role involvement on the subject of money laundering risk assessment is not a substitute for automated solutions as human judgement is inimitable.

Keywords: banking institutions, experimental approach, money laundering, risk assessment

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Authors: Ye Tian

Abstract:

Soft power has replaced hard power and become one of the most attractive ways nations pursue to expand their international influence. One of the ways to improve a nation’s soft power is to commercialise the country and brand or rebrand it to the international audience, and thus attract interests or foreign investments. In this process, translation has often been regarded as merely a tool, and researches in it are either in translating literature as culture export or in how (in)accuracy of translation influences the branding campaign. This paper proposes to analyse nation branding campaign with framing theory, and thus gives an entry for translation studies to come to a central stage in today’s soft power research. To frame information or elements of a text, an event, or, as in this paper, a nation is to put them in a mental structure. This structure can be built by outsiders or by those who create the text, the event, or by citizens of the nation. To frame information like this can be regarded as a process of translation, as what translation does in its traditional meaning of ‘translating a text’ is to put a framework on the text to, deliberately or not, highlight some of the elements while hiding the others. In the discourse of nations, then, people unavoidably simplify a national image and put the nation into their imaginary framework. In this way, problems like stereotype and prejudice come into being. Meanwhile, if nations seek ways to frame or reframe themselves, they make efforts to have in control what and who they are in the eyes of international audiences, and thus make profits, economically or politically, from it. The paper takes African nations, which are usually perceived as a whole, and the United Kingdom as examples to justify passive and active framing process, and assesses both positive and negative influence framing has on nations. In conclusion, translation as framing causes problems like prejudice, and the image of a nation is not always in the hands of nation branders, but reframing the nation in a positive way has the potential to turn the tide.

Keywords: framing, nation branding, stereotype, translation

Procedia PDF Downloads 141