Search results for: Coping strategies

Authors: S. Fore, L. Zuze

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Frequent machine breakdowns, low plant availability and increased overtime are a great threat to a manufacturing plant as they increase operating costs of an industry. The main aim of this study was to improve Overall Equipment Effectiveness (OEE) at a manufacturing company through the implementation of innovative maintenance strategies. A case study approach was used. The paper focuses on improving the maintenance in a manufacturing set up using an innovative maintenance regime mix to improve overall equipment effectiveness. Interviews, reviewing documentation and historical records, direct and participatory observation were used as data collection methods during the research. Usually production is based on the total kilowatt of motors produced per day. The target kilowatt at 91% availability is 75 Kilowatts a day. Reduced demand and lack of raw materials particularly imported items are adversely affecting the manufacturing operations. The company had to reset its targets from the usual figure of 250 Kilowatt per day to mere 75 per day due to lower availability of machines as result of breakdowns as well as lack of raw materials. The price reductions and uncertainties as well as general machine breakdowns further lowered production. Some recommendations were given. For instance, employee empowerment in the company will enhance responsibility and authority to improve and totally eliminate the six big losses. If the maintenance department is to realise its proper function in a progressive, innovative industrial society, then its personnel must be continuously trained to meet current needs as well as future requirements. To make the maintenance planning system effective, it is essential to keep track of all the corrective maintenance jobs and preventive maintenance inspections. For large processing plants these cannot be handled manually. It was therefore recommended that the company implement (Computerised Maintenance Management System) CMMS.

Keywords: Maintenance, Manufacturing, Overall Equipment Effectiveness

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Authors: Giani Gradinaru

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Biodiversity crisis is one of the many crises that started at the turn of the millennia. Concrete form of expression is still disputed, but there is a relatively high consensus regarding the high rate of degradation and the urgent need for action. The strategy of action outlines a strong economic component, together with the recognition of market mechanisms as the most effective policies to protect biodiversity. In this context, biodiversity and ecosystem services are natural assets that play a key role in economic strategies and technological development to promote development and prosperity. Developing and strengthening policies for transition to an economy based on efficient use of resources is the way forward. To emphasize the co-viability specific to the connection economyecosystem services, scientific approach aimed on one hand how to implement policies for nature conservation and on the other hand, the concepts underlying the economic expression of ecosystem services- value, in the context of current technology. Following the analysis of business opportunities associated with changes in ecosystem services was concluded that development of market mechanisms for nature conservation is a trend that is increasingly stronger individualized within recent years. Although there are still many controversial issues that have already given rise to an obvious bias, international organizations and national governments have initiated and implemented in cooperation or independently such mechanisms. Consequently, they created the conditions for convergence between private interests and social interests of nature conservation, so there are opportunities for ongoing business development which leads, among other things, the positive effects on biodiversity. Finally, points out that markets fail to quantify the value of most ecosystem services. Existing price signals reflect at best, only a proportion of the total amount corresponding provision of food, water or fuel.

Keywords: ecosystem services, economic evaluation, nature conservation

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Authors: Benazeer Md. Shahzada, Verelst Jan, Van Grembergen Wim, Mannaert Herwig

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This article is an extension and a practical application approach of Wheeler-s NEBIC theory (Net Enabled Business Innovation Cycle). NEBIC theory is a new approach in IS research and can be used for dynamic environment related to new technology. Firms can follow the market changes rapidly with support of the IT resources. Flexible firms adapt their market strategies, and respond more quickly to customers changing behaviors. When every leading firm in an industry has access to the same IT resources, the way that these IT resources are managed will determine the competitive advantages or disadvantages of firm. From Dynamic Capabilities Perspective and from newly introduced NEBIC theory by Wheeler, we know that only IT resources cannot deliver customer value but good configuration of those resources can guarantee customer value by choosing the right emerging technology, grasping the right economic opportunities through business innovation and growth. We found evidences in literature that SOA (Service Oriented Architecture) is a promising emerging technology which can deliver the desired economic opportunity through modularity, flexibility and loose-coupling. SOA can also help firms to connect in network which can open a new window of opportunity to collaborate in innovation and right kind of outsourcing. There are many articles and research reports indicates that failure rate in outsourcing is very high but at the same time research indicates that successful outsourcing projects adds tangible and intangible benefits to the service consumer. Business executives and policy makers in the west should not afraid of outsourcing but they should choose the right strategy through the use of emerging technology to significantly reduce the failure rate in outsourcing.

Keywords: Absorptive capacity, Dynamic Capability, Netenabled business innovation cycle, Service oriented architecture.

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries.

In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530.

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Authors: Mei-Fang Wu, Shu-Li Wang, Feng-Tsung Cheng

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Highly developed technology and highly competitive global market highlight the important role of competitive advantages and operation performances in sustainable company operation. Activity-Based Costing (ABC) provides accurate operation cost and operation performance information. Rich literatures provide relevant research with cases study on Activity-Based Costing application, but the research on cause relationship between key success factors and its specific outcome, such as profitability or share market are few. These relationships provide the ways to handle the key success factors to achieve the specific outcomes for ensuring to promote the competitive advantages and operation performances. The main purposes of this research are exploring the key success paths by Key Success Paths approach which will lead the ways to apply Activity-Base Costing. The Key Success Paths is the innovative method which is exploring the cause relationships and explaining what are the effects of key success factors to specific outcomes of Activity-Based Costing implementation. The cause relationships between key success factors and successful specific outcomes are Key Success Paths (KSPs). KSPs are the guidelines to lead the cost management strategies to achieve the goals of competitive advantages and operation performances. The research findings indicate that good management system design may affect the well outcomes of Activity-Based Costing application and achieve to outstanding competitive advantage, operating performance and profitability as well by KSPs exploration.

Keywords: Activity-Based Costing, Key success factors, Key success paths approach, Key success paths, Key failure paths.

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Authors: Etim, Victoria Enefiok, Dada, Oluseyi Akintunde, Bassey Okon

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Phonological disorder is a serious and disturbing issue to many parents and teachers. Efforts towards resolving the problem have been undermined by other specific disabilities which were hidden to many regular and special education teachers. It is against this background that this study was motivated to provide data on the prevalence of phonological disorders in children with specific language impairment (CWSLI) as the first step towards critical intervention. The study was a survey of 15 CWSLI from St. Louise Inclusive schools, Ikot Ekpene in Akwa Ibom State of Nigeria. Phonological Processes Diagnostic Scale (PPDS) with 17 short sentences, which cut across the five phonological processes that were examined, were validated by experts in test measurement, phonology and special education. The respondents were made to read the sentences with emphasis on the targeted sounds. Their utterances were recorded and analyzed in the language laboratory using Praat Software. Data were also collected through friendly interactions at different times from the clients. The theory of generative phonology was adopted for the descriptive analysis of the phonological processes. Data collected were analyzed using simple percentage and composite bar chart for better understanding of the result. The study found out that CWSLI exhibited the five phonological processes under investigation. It was revealed that 66.7%, 80%, 73.3%, 80%, and 86.7% of the respondents have severe deficit in fricative stopping, velar fronting, liquid gliding, final consonant deletion and cluster reduction, respectively. It was therefore recommended that a nationwide survey should be carried out to have national statistics of CWSLI with phonological deficits and develop intervention strategies for effective therapy to remediate the disorder.

Keywords: Language disorders, phonology, phonological processes, specific language impairment.

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Authors: Asli Yagmur Akbulut

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Despite a robust and growing job market and lucrative salaries, there is a global shortage of Information Technology (IT) professionals. To make matters worse, women continue to be underrepresented in the IT workforce and among IT degree holders. In today’s knowledge based economy and society, it is extremely important to increase the presence of women in the IT field. In order to do so, it is necessary to reduce entry barriers and attract more women to pursue degrees in various IT fields including the field of Management Information Systems (MIS). Even though MIS is considered to have a more feminine nature, women still tend to avoid majoring in this field. Unfortunately, there is a lack of research that investigates the specific factors that may deter women from pursuing a degree in MIS. To address this research gap, this study examined a set of key environmental barriers that might prevent women from pursuing an MIS degree and explored whether there were any gender differences between female and male students in terms of these key barriers. Based on a survey of 280 students enrolled in an introductory level MIS course, the study empirically confirmed that there were significant differences between male and female students in terms of the key contextual barriers perceived. Female students demonstrated major concerns about gender discrimination related barriers, whereas male students were more concerned about negative social influences. Both male and female students were equally concerned about not being able to fit in well with other MIS majors. The findings have important implications for MIS programs, as the information gained can be used to design and implement specific intervention strategies to overcome the barriers and attract larger pools of women to the MIS discipline. The paper concludes with a discussion of the findings, implications, and future research directions.

Keywords: Gender differences, MIS major, underrepresentation, women in IT.

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: Wen Hui Kuan, Chia Ling Chang, Pei Shan Lui

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The Chichiawan stream in the Wulin catchment in Taiwan is the natural habitat of Formosan landlocked salmon. Human and agriculture activities gradually worsen water quality and impact the fish habitat negatively. To protect and manage Formosan landlocked salmon habitat, it is important to understand a variety land-uses affect on the watershed responses to storms. This study discusses watershed responses to the dry-day before a storm event and a variety of land-uses in the Wulin catchment. Under the land-use planning in the Wulin catchment, the peak flows during typhoon events do not have noticeable difference. However, the nutrient exports can be highly reduced under the strategies of restraining agriculture activities. Due to the higher affinity of P for soil than that of N, the exports of TN from overall Wuling catchment were much greater than Ortho-P. Agriculture mainly centralized in subbasin A, which is the important source of nutrients in nonpoint source discharge. The subbasin A supplied about 26% of the TN and 32% of the Ortho-P discharge in 2004, despite the fact it only covers 19% area of the Wuling catchment. The subbasin analysis displayed that the agricultural subbasin A exports higher nutrients per unit area than other forest subbasins. Additionally, the agricultural subbasin A contributed a higher percentage to total Ortho-P exports compares to TN. The results of subbasin analysis might imply the transport of Ortho-P was similar to the particulate matter which was mainly influenced by the runoff and affected by the desorption from soil particles while the TN (dominated as nitrate-N) was mainly influenced by base-flow.

Keywords: Chiachiawan stream, Formosan landlocked salmon, modeling, typhoon, watershed response.

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: Political tendency, prediction, sentiment analysis, Twitter.

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Authors: S. Figueiredo, M. Alves Martins, C. Silva, C. Simões

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This study integrates a larger research empirical project that examines second language (SL) learners’ profiles and valid procedures to perform complete and diagnostic assessment in schools. 102 learners of Portuguese as a SL aged 7 and 17 years speakers of distinct home languages were assessed in several linguistic tasks. In this article, we focused on writing performance in the specific task of narrative essay composition. The written outputs were measured using the score in six components adapted from an English SL assessment context (Alberta Education): linguistic vocabulary, grammar, syntax, strategy, socio-linguistic, and discourse. The writing processes and strategies in Portuguese language used by different immigrant students were analysed to determine features and diversity of deficits on authentic texts performed by SL writers. Differentiated performance was based on the diversity of the following variables: grades, previous schooling, home language, instruction in first language, and exposure to Portuguese as Second Language. Indo-Aryan languages speakers showed low writing scores compared to their peers and the type of language and respective cognitive mapping (such as Mandarin and Arabic) was the predictor, not linguistic distance. Home language instruction should also be prominently considered in further research to understand specificities of cognitive academic profile in a Romance languages learning context. Additionally, this study also examined the teachers’ representations that will be here addressed to understand educational implications of second language teaching in psychological distress of different minorities in schools of specific host countries.

Keywords: Second language, writing assessment, home language, immigrant students, Portuguese language.

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Authors: Vânia Graça, Paula Quadros-Flores, Altina Ramos

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The use of Digital Technologies in teaching and learning processes is currently a reality, namely in initial teacher training. This study aims at knowing the digital reality of students in initial teacher training in order to improve training in the educational use of ICT and to promote digital technology integration strategies in an educational context. It is part of the IFITIC Project "Innovate with ICT in Initial Teacher Training to Promote Methodological Renewal in Pre-school Education and in the 1st and 2nd Basic Education Cycle" which involves the School of Education, Polytechnic of Porto and Institute of Education, University of Minho. The Project aims at rethinking educational practice with ICT in the initial training of future teachers in order to promote methodological innovation in Pre-school Education and in the 1st and 2nd Cycles of Basic Education. A qualitative methodology was used, in which a questionnaire survey was applied to teachers in initial training. For data analysis, the techniques of content analysis with the support of NVivo software were used. The results point to the following aspects: a) future teachers recognize that they have more technical knowledge about ICT than pedagogical knowledge. This result makes sense if we consider the objective of Basic Education, so that the gaps can be filled in the Master's Course by students who wish to follow the teaching; b) the respondents are aware that the integration of digital resources contributes positively to students' learning and to the life of children and young people, which also promotes preparation in life; c) to be a teacher in the digital age there is a need for the development of digital literacy, lifelong learning and the adoption of new ways of teaching how to learn. Thus, this study aims to contribute to a reflection on the teaching profession in the digital age.

Keywords: Digital technologies, initial teacher training, pedagogical use of ICT, skills.

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Authors: Olugbade Damola, Adekomi Adebimbo, Sofowora Olaniyi Alaba

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One of the major problems facing education in Nigeria is the provision of quality Science and Technology education. Inadequate teaching facilities, non-usage of innovative teaching strategies, ineffective classroom management, lack of students’ motivation and poor integration of ICT has resulted in the increase in percentage of students who failed Basic Science and Technology in Junior Secondary Certification Examination for National Examination Council in Nigeria. To address these challenges, the Federal Government came up with a road map on education. This was with a view of enhancing quality education through integration of modern technology into teaching and learning, enhancing quality assurance through proper monitoring and introduction of innovative methods of teaching. This led the researcher to investigate how MOODLE LMS could be used to enhance students’ learning outcomes in BST. A sample of 120 students was purposively selected from four secondary schools in Ogbomoso. The experimental group was taught using MOODLE LMS, while the control group was taught using the conventional method. Data obtained were analyzed using mean, standard deviation and t-test. The result showed that MOODLE LMS was an effective learning platform in teaching BST in junior secondary schools (t=4.953, P<0.05). Students’ attitudes towards BST was also enhanced through MOODLE LMS (t=15.632, P<0.05). The use of MOODLE LMS significantly enhanced students’ retention (t=6.640, P<0.05). In conclusion, the Federal Government efforts at enhancing quality assurance through integration of modern technology and e-learning in Secondary schools proved to have yielded good result has students found MOODLE LMS to be motivating and interactive. Attendance was improved.

Keywords: MOODLE, learning management system, quality assurance, basic science and technology.

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Authors: A. K. Prajapati

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In this paper, the periodic surveillance scheme has been proposed for any convex region using mobile wireless sensor nodes. A sensor network typically consists of fixed number of sensor nodes which report the measurements of sensed data such as temperature, pressure, humidity, etc., of its immediate proximity (the area within its sensing range). For the purpose of sensing an area of interest, there are adequate number of fixed sensor nodes required to cover the entire region of interest. It implies that the number of fixed sensor nodes required to cover a given area will depend on the sensing range of the sensor as well as deployment strategies employed. It is assumed that the sensors to be mobile within the region of surveillance, can be mounted on moving bodies like robots or vehicle. Therefore, in our scheme, the surveillance time period determines the number of sensor nodes required to be deployed in the region of interest. The proposed scheme comprises of three algorithms namely: Hexagonalization, Clustering, and Scheduling, The first algorithm partitions the coverage area into fixed sized hexagons that approximate the sensing range (cell) of individual sensor node. The clustering algorithm groups the cells into clusters, each of which will be covered by a single sensor node. The later determines a schedule for each sensor to serve its respective cluster. Each sensor node traverses all the cells belonging to the cluster assigned to it by oscillating between the first and the last cell for the duration of its life time. Simulation results show that our scheme provides full coverage within a given period of time using few sensors with minimum movement, less power consumption, and relatively less infrastructure cost.

Keywords: Sensor Network, Graph Theory, MSN, Communication.

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Jinhwan Yu, Jooyeon Yook

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After Apple's first introduction its smart phone, iPhone in the end of 2009 in Korea, the number of Korean smarphone users had been rapidly increasing so that the half of Korean population became smart phone users as of February, 2012. Currently, smart phones are positioned as a major digital media with powerful influences in Korea. And, now, Koreans are leaning new information, enjoying games and communicating other people every time and everywhere. As smart phone devices' performances increased, the number of usable services became more while adequate GUI developments are required to implement various functions with smart phones. The strategy to provide similar experiences on smart phones through familiar features based on employment of existing media's functions mostly contributed to smart phones' popularization in connection with smart phone devices' iconic GUIs. The spread of Smart phone increased mobile web accesses. Therefore, the attempts to implement PC's web in the smart phone's web are continuously made. The mobile web GUI provides familiar experiences to users through designs adequately utilizing the smart phone's GUIs. As the number of users familiarized to smart phones and mobile web GUIs, opposite to reversed remediation from many parts of PCs, PCs are starting to adapt smart phone GUIs. This study defines this phenomenon as the reversed remediation, and reviews the reversed remediation cases of Smart phone GUI' characteristics of PCs. For this purpose, the established study issues are as under: · what is the reversed remediation? · what are the smart phone GUI's characteristics? · what kind of interrelationship exist s between the smart phone and PC's web site? It is meaningful in the forecast of the future GUI's change by understanding of characteristics in the paradigm changes of PC and smart phone's GUI designs. This also will be helpful to establish strategies for digital devices' development and design.

Keywords: Graphic User Interface, Remediation, Smart Phone, South Korea, Web Site

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Authors: N. A. Samat, S. H. Mohd Imam Ma’arof

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Dengue disease is an infectious vector-borne viral disease that is commonly found in tropical and sub-tropical regions, especially in urban and semi-urban areas, around the world and including Malaysia. There is no currently available vaccine or chemotherapy for the prevention or treatment of dengue disease. Therefore prevention and treatment of the disease depend on vector surveillance and control measures. Disease risk mapping has been recognized as an important tool in the prevention and control strategies for diseases. The choice of statistical model used for relative risk estimation is important as a good model will subsequently produce a good disease risk map. Therefore, the aim of this study is to estimate the relative risk for dengue disease based initially on the most common statistic used in disease mapping called Standardized Morbidity Ratio (SMR) and one of the earliest applications of Bayesian methodology called Poisson-gamma model. This paper begins by providing a review of the SMR method, which we then apply to dengue data of Perak, Malaysia. We then fit an extension of the SMR method, which is the Poisson-gamma model. Both results are displayed and compared using graph, tables and maps. Results of the analysis shows that the latter method gives a better relative risk estimates compared with using the SMR. The Poisson-gamma model has been demonstrated can overcome the problem of SMR when there is no observed dengue cases in certain regions. However, covariate adjustment in this model is difficult and there is no possibility for allowing spatial correlation between risks in adjacent areas. The drawbacks of this model have motivated many researchers to propose other alternative methods for estimating the risk.

Keywords: Dengue disease, Disease mapping, Standardized Morbidity Ratio, Poisson-gamma model, Relative risk.

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Authors: Ashly Joseph, Jithu Paulose

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Large language models (LLMs) have revolutionized natural language processing capabilities, enabling applications such as chatbots, dialogue agents, image, and video generators. Nevertheless, their trainings on extensive datasets comprising personal information poses notable privacy and safety hazards. This study examines methods for addressing these challenges, specifically focusing on approaches to enhance the security of LLM outputs, safeguard user privacy, and adhere to data protection rules. We explore several methods including post-processing detection algorithms, content filtering, reinforcement learning from human and AI inputs, and the difficulties in maintaining a balance between model safety and performance. The study also emphasizes the dangers of unintentional data leakage, privacy issues related to user prompts, and the possibility of data breaches. We highlight the significance of corporate data governance rules and optimal methods for engaging with chatbots. In addition, we analyze the development of data protection frameworks, evaluate the adherence of LLMs to General Data Protection Regulation (GDPR), and examine privacy legislation in academic and business policies. We demonstrate the difficulties and remedies involved in preserving data privacy and security in the age of sophisticated artificial intelligence by employing case studies and real-life instances. This article seeks to educate stakeholders on practical strategies for improving the security and privacy of LLMs, while also assuring their responsible and ethical implementation.

Keywords: Data privacy, large language models, artificial intelligence, machine learning, cybersecurity, general data protection regulation, data safety.

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Authors: Walenty Oniszczuk

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The use of buffer thresholds, blocking and adequate service strategies are well-known techniques for computer networks traffic congestion control. This motivates the study of series queues with blocking, feedback (service under Head of Line (HoL) priority discipline) and finite capacity buffers with thresholds. In this paper, the external traffic is modelled using the Poisson process and the service times have been modelled using the exponential distribution. We consider a three-station network with two finite buffers, for which a set of thresholds (tm1 and tm2) is defined. This computer network behaves as follows. A task, which finishes its service at station B, gets sent back to station A for re-processing with probability o. When the number of tasks in the second buffer exceeds a threshold tm2 and the number of task in the first buffer is less than tm1, the fed back task is served under HoL priority discipline. In opposite case, for fed backed tasks, “no two priority services in succession" procedure (preventing a possible overflow in the first buffer) is applied. Using an open Markovian queuing schema with blocking, priority feedback service and thresholds, a closed form cost-effective analytical solution is obtained. The model of servers linked in series is very accurate. It is derived directly from a twodimensional state graph and a set of steady-state equations, followed by calculations of main measures of effectiveness. Consequently, efficient expressions of the low computational cost are determined. Based on numerical experiments and collected results we conclude that the proposed model with blocking, feedback and thresholds can provide accurate performance estimates of linked in series networks.

Keywords: Blocking, Congestion control, Feedback, Markov chains, Performance evaluation, Threshold-base networks.

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Authors: Adrian Lo

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Since the advent of modern architecture, notions of free plan and transparency have proliferated well into current trends. The movement’s notion of a spatially homogeneous, open and limitless ‘free plan’ contrasts with the spatially heterogeneous ‘series of rooms’ defined by load bearing walls, which in turn triggered new notions of transparency created by vast expanses of glazed walls. Similarly, transparency was also dichotomized as something that was physical or optical, as well as something conceptual, akin to spatial organization. As opposed to merely accepting the duality and possible incompatibility of these dichotomies, this paper seeks to ask how can space be both literally and phenomenally transparent, as well as exhibit both homogeneous and heterogeneous qualities? This paper explores this potential destabilization or blurring of spatial phenomena by dissecting the transparent layers and volumes of a series of selected case studies to investigate how different architects have devised strategies of spatial ambiguity and interpenetration. Projects by Peter Eisenman, Sou Fujimoto, and SANAA will be discussed and analyzed to show how the superimposition of geometries and spaces achieve different conditions of layering, transparency, and interstitiality. Their particular buildings will be explored to reveal various innovative kinds of spatial interpenetration produced through the articulate relations of the elements of architecture, which challenge conventional perceptions of interior and exterior whereby visual homogeneity blurs with spatial heterogeneity. The results show how spatial conceptions such as interpenetration and transparency have the ability to subvert not only inside-outside dialectics, but could also produce multiple degrees of interiority within complex and indeterminate spatial dimensions in constant flux as well as present alternative forms of social interaction.

Keywords: interpenetration, literal and phenomenal transparency, spatial heterogeneity, visual homogeneity

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Authors: I.V. Saradhi, G.G. Pandit, V.D. Puranik

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Increasing concerns over climate change have limited the liberal usage of available energy technology options. India faces a formidable challenge to meet its energy needs and provide adequate energy of desired quality in various forms to users in sustainable manner at reasonable costs. In this paper, work carried out with an objective to study the role of various energy technology options under different scenarios namely base line scenario, high nuclear scenario, high renewable scenario, low growth and high growth rate scenario. The study has been carried out using Model for Energy Supply Strategy Alternatives and their General Environmental Impacts (MESSAGE) model which evaluates the alternative energy supply strategies with user defined constraints on fuel availability, environmental regulations etc. The projected electricity demand, at the end of study period i.e. 2035 is 500490 MWYr. The model predicted the share of the demand by Thermal: 428170 MWYr, Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr in the base line scenario. Coal remains the dominant fuel for production of electricity during the study period. However, the import dependency of coal increased during the study period. In baseline scenario the cumulative carbon dioxide emissions upto 2035 are about 11,000 million tones of CO2. In the scenario of high nuclear capacity the carbon dioxide emissions reduced by 10 % when nuclear energy share increased to 9 % compared to 3 % in baseline scenario. Similarly aggressive use of renewables reduces 4 % of carbon dioxide emissions.

Keywords: Carbon dioxide, energy, electricity, message.

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Authors: Juliana Amaka Ugwu

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Trapping efficiency of methyl eugenol and three locally made food-based lures were evaluated in three locations for trapping of B. dorsalis on mango homestead trees in Ibadan South west Nigeria. The treatments were methyl eugenol, brewery waste, pineapple juice, orange juice, and control (water). The experiment was laid in a Complete Randomized Block Design (CRBD) and replicated three times in each location. Data collected were subjected to analysis of variance and significant means were separated by Turkey’s test. The results showed that B. dorsalis was recorded in all locations of study. Methyl eugenol significantly (P < 0.05) trapped higher population of B. dorsalis in all the study area. The population density of B. dorsalis was highest during the ripening period of mango in all locations. The percentage trapped flies after 7 weeks were 77.85%-82.38% (methyl eugenol), 7.29%-8.64% (pineapple juice), 5.62-7.62% (brewery waste), 4.41%-5.95% (orange juice), and 0.24-0.47% (control). There were no significance differences (p > 0.05) on the population of B. dorsalis trapped in all locations. Similarly, there were no significant differences (p > 0.05) on the population of flies trapped among the food attractants. However, the three food attractants significantly (p < 0.05) trapped higher flies than control. Methyl eugenol trapped only male flies while brewery waste and other food based attractants trapped both male and female flies. The food baits tested were promising attractants for trapping B. dorsalis on mango homestead tress, hence increased dosage could be considered for monitoring and mass trapping as management strategies against fruit fly infestation.

Keywords: Attractants, trapping, mango, Bactrocera dorsalis.

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Authors: Suman Senapati, Goutam Saha

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Real world Speaker Identification (SI) application differs from ideal or laboratory conditions causing perturbations that leads to a mismatch between the training and testing environment and degrade the performance drastically. Many strategies have been adopted to cope with acoustical degradation; wavelet based Bayesian marginal model is one of them. But Bayesian marginal models cannot model the inter-scale statistical dependencies of different wavelet scales. Simple nonlinear estimators for wavelet based denoising assume that the wavelet coefficients in different scales are independent in nature. However wavelet coefficients have significant inter-scale dependency. This paper enhances this inter-scale dependency property by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimator is derived by Maximum a Posteriori (MAP) estimator. A framework is proposed based on these to denoise speech signal for automatic speaker identification problems. The robustness of the proposed framework is tested for Text Independent Speaker Identification application on 100 speakers of POLYCOST and 100 speakers of YOHO speech database in three different noise environments. Experimental results show that the proposed estimator yields a higher improvement in identification accuracy compared to other estimators on popular Gaussian Mixture Model (GMM) based speaker model and Mel-Frequency Cepstral Coefficient (MFCC) features.

Keywords: Speaker Identification, Log Gabor Wavelet, Bayesian Bivariate Estimator, Circularly Symmetric Probability Density Function, SIRP.

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: Femtocell networks, game theory, interference mitigation, spectrum allocation.

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Authors: Lowai Abed

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The differences in languages play a big role in cross-cultural communication. If meanings are not translated accurately, the risk can be crucial not only on an interpersonal level, but also on the international and political levels. The use of metaphorical language by politicians can cause great confusion, often leading to statements being misconstrued. In these situations, it is the translators who struggle to put forward the intended meaning with clarity and this makes translation an important field to study and analyze when it comes to cross-cultural communication. Owing to the growing importance of language and the power of translation in politics, this research analyzes part of President Bush’s speech in 2001 in which he used the word “Crusade” which caused his statement to be misconstrued. The research uses a discourse analysis of cross-cultural communication literature which provides answers supported by historical, linguistic, and communicative perspectives. The first finding indicates that the word ‘crusade’ carries different meaning and significance in the narratives of the Western world when compared to the Middle East. The second one is that, linguistically, maintaining cultural meanings through translation is quite difficult and challenging. Third, when it comes to the cross-cultural communication perspective, the common and frequent usage of literal translation is a sign of poor strategies being followed in translation training. Based on the example of Bush’s speech, this paper hopes to highlight the weak practices in translation in cross-cultural communication which are still commonly used across the world. Translation studies have to take issues such as this seriously and attempt to find a solution. In every language, there are words and phrases that have cultural, historical and social meanings that are woven into the language. Literal translation is not the solution for this problem because that strategy is unable to convey these meanings in the target language.

Keywords: Crusade, metaphor, mistranslation, war in terror.

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Authors: Manat Srivanit, Hokao Kazunori

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Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.

Keywords: Urban climate, Urban morphology, Local climate zone, Urban planning, GIS and remote sensing

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Authors: Bi-Huei Tsai

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Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected data for the best accuracy. Particularly, Taiwanese regulatory FDI restrictions are also considered in our modified model to meet the realistic conditions. To validate the model-s effectiveness, this investigation compares the prediction accuracy of modified model with the conventional diffusion model, which does not take account of the profitability factors. The results clearly demonstrate the internal influence to be positive, as early FDI adopters- consistent praises of FDI attract potential firms to make the same move. The former erects a behavior model for the latter to imitate their foreign investment decision. Particularly, the results of modified diffusion models show that the earnings from Chinese branches are positively related to the internal influence. In general, the imitating tendency of potential consumers is substantially hindered by the losses in the Chinese branches, and these firms would invest less into China. The FDI inflow extension depends on earnings of Chinese branches, and companies will adjust their FDI strategies based on the returns. Since this research has proved that earning is an influential factor on FDI dynamics, our revised model explicitly performs superior in prediction ability than conventional diffusion model.

Keywords: diffusion model, genetic algorithms, nonlinear leastsquares (NLS) model, prediction error.

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Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

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The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, US. NJ DMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: Building Energy Modeling, eQUEST, peak demand, smart meters.

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Authors: V. Barot, S. McLeod, R. Harrison, A. A. West

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Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Keywords: Broadcaster, circular buffer, Component-based, distributed manufacturing, remote data propagation.

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Authors: Elena A. Railean

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Although scientific methods have been the subject of a large number of papers, the term ‘scientific methods in educational management’ is still not well defined. In this paper, it is adopted the metasystems perspective to define the mentioned term and distinguish them from methods used in time of the scientific management and knowledge management paradigms. In our opinion, scientific methods in educational management rely on global phenomena, events, and processes and their influence on the educational organization. Currently, scientific methods in educational management are integrated with the phenomenon of globalization, cognitivisation, and openness, etc. of educational systems and with global events like the COVID-19 pandemic. Concrete scientific methods are nested in a hierarchy of more and more abstract models of educational management, which form the context of the global impact on education, in general, and learning outcomes, in particular. However, scientific methods can be assigned to a specific mission, strategy, or tactics of educational management of the concrete organization, either by the global management, local development of school organization, or/and development of the life-long successful learner. By accepting this assignment, the scientific method becomes a personal goal of each individual with the educational organization or the option to develop the educational organization at the global standards. In our opinion, in educational management, the scientific methods need to confine the scope to the deep analysis of concrete tasks of the educational system (i.e., teaching, learning, assessment, development), which result in concrete strategies of organizational development. More important are seeking the ways for dynamic equilibrium between the strategy and tactic of the planetary tasks in the field of global education, which result in a need for ecological methods of learning and communication. In sum, distinction between local and global scientific methods is dependent on the subjective conception of the task assignment, measurement, and appraisal. Finally, we conclude that scientific methods are not holistic scientific methods, but the strategy and tactics implemented in the global context by an effective educational/academic manager.

Keywords: Educational management, scientific management, educational leadership, scientific method in educational management.

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