Search results for: IFF "Identify Friend or Foe"

Authors: Ajay Verma, Nitin Seth

Abstract:

In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature and researchers have tried to identify variables of supply chain competitiveness. This paper highlights some of the concepts of supply chain competitiveness and tries to identify select variables on the basis of literature review. Further, the paper tries to highlight the importance of the identified variables in the achievement of supply chain competitiveness. The aim is to explore the concept and to motivate researchers to further investigate the unexplored areas of this important subject domain.

Keywords: Supply Chain Competitiveness, Demand Management, Integration, Inventory Management, Flexibility, Information Technology.

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Authors: Pornpimol Bungkomkhun, Surapong Auwatanamongkol

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This paper presents a supervised clustering algorithm, namely Grid-Based Supervised Clustering (GBSC), which is able to identify clusters of any shapes and sizes without presuming any canonical form for data distribution. The GBSC needs no prespecified number of clusters, is insensitive to the order of the input data objects, and is capable of handling outliers. Built on the combination of grid-based clustering and density-based clustering, under the assistance of the downward closure property of density used in bottom-up subspace clustering, the GBSC can notably reduce its search space to avoid the memory confinement situation during its execution. On two-dimension synthetic datasets, the GBSC can identify clusters with different shapes and sizes correctly. The GBSC also outperforms other five supervised clustering algorithms when the experiments are performed on some UCI datasets.

Keywords: supervised clustering, grid-based clustering, subspace clustering

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Authors: Erika Ruiz, Nestor Ortiz

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Lean philosophy has evolved over time and has been implemented both in manufacturing and services, more recently lean has been integrated in the companies of the health sector. Currently it is important to understand the successful way to implement this philosophy and try to identify barriers and enablers to the sustainability of lean healthcare. The main purpose of this research is to identify the barriers and enablers in the implementation of Lean Healthcare based on case studies of Colombian healthcare centers. In order to do so, we conducted semi-structured interviews based on a maturity model. The main results indicate that the success of Lean implementation depends on its adaptation to contextual factors. In addition, in the Colombian context were identified new factors such as organizational culture, management models, integration of the care and administrative departments and triple helix relationship.

Keywords: Barriers, enablers, implementation, lean healthcare, sustainability.

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Authors: Fahanim Abdul Rashid, Muhammad Azzam Ismail

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Part and parcel of building green homes (GHs) with favorable thermal comfort (TC) is to design and build with reduced carbon footprint (CF) from embodied energy in the building envelope and reduced operational CF overall. Together, the environmental impact of GHs can be reduced significantly. Nevertheless, there is still a need to identify the base CF value for Malaysian GHs and this can be done by assessing existing ones which can then be compared to conventional and vernacular houses which are built differently with different building materials. This paper underlines the research design and introduces the case studies. For now, the operational CF of the case studies is beyond the scope of this study. Findings from this research could identify the best building material and construction technique combination to build GHs depending on the available skills, financial constraints and the condition of the immediate environment.

Keywords: Embodied carbon footprint, Malaysian green homes.

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Authors: H. Izakian, S. A. Monadjemi, B. Tork Ladani, K. Zamanifar

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Nowadays, OCR systems have got several applications and are increasingly employed in daily life. Much research has been done regarding the identification of Latin, Japanese, and Chinese characters. However, very little investigation has been performed regarding Farsi/Arabic characters recognition. Probably the reason is difficulty and complexity of those characters identification compared to the others and limitation of IT activities in Farsi and Arabic speaking countries. In this paper, a technique has been employed to identify isolated Farsi/Arabic characters. A chain code based algorithm along with other significant peculiarities such as number and location of dots and auxiliary parts, and the number of holes existing in the isolated character has been used in this study to identify Farsi/Arabic characters. Experimental results show the relatively high accuracy of the method developed when it is tested on several standard Farsi fonts.

Keywords: Farsi characters, OCR, feature extraction, chain code.

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: Building measurement, construction management, learning challenges, evaluate survey.

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Authors: S. Sowmyayani, P. Arockia Jansi Rani

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Fall detection is one of the challenging problems in elderly care system. The objective of this paper is to identify falls in elderly care system. In this paper, an efficient fall detection method is proposed to identify falls using correlation factor and Motion History Image (MHI). The proposed method is tested on URF (University of Rzeszow Fall detection) dataset and evaluated with some efficient measures like sensitivity, specificity, precision and classification accuracy. It is compared with other recent methods. The experimental results substantially proved that the proposed method achieves 1.5% higher sensitivity when compared to other methods.

Keywords: Pearson correlation coefficient, motion history image, human shape identification.

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Authors: E. Ramaraj, A. Padmapriya

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In large Internet backbones, Service Providers typically have to explicitly manage the traffic flows in order to optimize the use of network resources. This process is often referred to as Traffic Engineering (TE). Common objectives of traffic engineering include balance traffic distribution across the network and avoiding congestion hot spots. Raj P H and SVK Raja designed the Bayesian network approach to identify congestion hors pots in MPLS. In this approach for every node in the network the Conditional Probability Distribution (CPD) is specified. Based on the CPD the congestion hot spots are identified. Then the traffic can be distributed so that no link in the network is either over utilized or under utilized. Although the Bayesian network approach has been implemented in operational networks, it has a number of well known scaling issues. This paper proposes a new approach, which we call the Pragati (means Progress) Node Popularity (PNP) approach to identify the congestion hot spots with the network topology alone. In the new Pragati Node Popularity approach, IP routing runs natively over the physical topology rather than depending on the CPD of each node as in Bayesian network. We first illustrate our approach with a simple network, then present a formal analysis of the Pragati Node Popularity approach. Our PNP approach shows that for any given network of Bayesian approach, it exactly identifies the same result with minimum efforts. We further extend the result to a more generic one: for any network topology and even though the network is loopy. A theoretical insight of our result is that the optimal routing is always shortest path routing with respect to some considerations of hot spots in the networks.

Keywords: Conditional Probability Distribution, Congestion hotspots, Operational Networks, Traffic Engineering.

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Authors: L.Tahmooresnejad, M.A.Shafia, R.Salami

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Technology transfer is a common method for companies to acquire new technology and presents both challenges and substantial benefits. In some cases especially in developing countries, the mere possession of technology does not guarantee a competitive advantage if the appropriate infrastructure is not in place. In this paper, we identify the localization factors needed to provide a better understanding of the conditions necessary for localization in order to benefit from future technology developments. Our theoretical and empirical analyses allow us to identify several factors in the technology transfer process that affect localization and provide leverage in enhancing capabilities and absorptive capacity.The impact factors are categorized within different groups of government, firms, institutes and market, and are verified through the empirical survey of a technology transfer experience. Moreover, statistical analysis has allowed a deeper understanding of the importance of each factor and has enabled each group to prioritize their organizational policies to effectively localize their technology.

Keywords: Absorption Capacity, Adaptation, Technology Transfer, Technology Localization

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Authors: Bagher Rahimpour Cami, Hamid Hassanpour, Hoda Mashayekhi

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Nowadays websites provide a vast number of resources for users. Recommender systems have been developed as an essential element of these websites to provide a personalized environment for users. They help users to retrieve interested resources from large sets of available resources. Due to the dynamic feature of user preference, constructing an appropriate model to estimate the user preference is the major task of recommender systems. Profile matching and latent factors are two main approaches to identify user preference. In this paper, we employed the latent factor and profile matching to cluster the user profile and identify user preference, respectively. The method uses the Distance Dependent Chines Restaurant Process as a Bayesian nonparametric framework to extract the latent factors from the user profile. These latent factors are mapped to user interests and a weighted distribution is used to identify user preferences. We evaluate the proposed method using a real-world data-set that contains news tweets of a news agency (BBC). The experimental results and comparisons show the superior recommendation accuracy of the proposed approach related to existing methods, and its ability to effectively evolve over time.

Keywords: Content-based recommender systems, dynamic user modeling, extracting user interests, predicting user preference.

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Authors: P. Hajek, J. Stejskal

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The aim of this paper is to analyze the ability to identify and acquire knowledge from external sources at the regional level in the Czech Republic. The results show that the most important sources of knowledge for innovative activities are sources within the businesses themselves, followed by customers and suppliers. Furthermore, the analysis of relationships between the objective of the innovative activity and the ability to identify and acquire knowledge implies that knowledge obtained from (1) customers aims at replacing outdated products and increasing product quality; (2) suppliers aims at increasing capacity and flexibility of production; and (3) competing businesses aims at growing market share and increasing the flexibility of production and services. Regions should therefore direct their support especially into development and strengthening of networks within the value chain.

Keywords: Knowledge, acquisition, innovative business, Czech republic, region.

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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Authors: Parvinder S. Sandhu, Harpreet Kaur, Amanpreet Singh

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Automatic reusability appraisal is helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this research work, structural attributes of software components are explored using software metrics and quality of the software is inferred by different Neural Network based approaches, taking the metric values as input. The calculated reusability value enables to identify a good quality code automatically. It is found that the reusability value determined is close to the manual analysis used to be performed by the programmers or repository managers. So, the developed system can be used to enhance the productivity and quality of software development.

Keywords: Neural Network, Software Reusability, Software Metric, Accuracy, MAE, RMSE.

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Authors: S. E. Musa, N. E. Mohamed, N. A. Ahmed

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In this study, several crossplots of the P-impedance with the lithology logs (gamma ray, neutron porosity, deep resistivity, water saturation and Vp/Vs curves) were made in three available wells, which were drilled in central part of the Blue Nile basin in depths varies from 1460m to 1600m. These crossplots were successful to discriminate between sand and shale when using PImpedance values, and between the wet sand and the pay sand when using both P-impedance and Vp/Vs together. Also some impedance sections were converted to porosity sections using linear formula to characterize the reservoir in terms of porosity. The used crossplots were created on log resolution, while the seismic resolution can identify only the reservoir, unless a 3D seismic angle stacks were available; then it would be easier to identify the pay sand with great confidence; through high resolution seismic inversion and geostatistical approach when using P-impedance and Vp/Vs volumes.

Keywords: Basin, Blue Nile, Inversion, Seismic.

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Authors: Mohammed Alshehri, Steve Drew

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More and more governments around the world are introducing e-government as a means of reducing costs, improving services, saving time and increasing effectiveness and efficiency in the public sector Therefore e-government has been identified as one of the top priorities for Saudi government and all its agencies. However, the adoption of e-government is facing many challenges and barriers such as technological, cultural, organizational, and social issues which must be considered and treated carefully by any government contemplating its adoption. This paper reports on a pilot study amongst online (e-ready) citizens to identify the challenges and barriers that affect the adoption of e-government services especially from their perspective in Saudi society. Based on the analysis of data collected from an online survey the researcher was able to identify some of the important barriers and challenges from the e-ready citizen perspective. As a result, this study has generated a list of possible strategies to move towards successful adoption of egovernment services in Saudi Arabia.

Keywords: Challenges, E-government services, adoption, SaudiArabia

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Authors: Ehsan Shahrabian, Ali Soleymani

Abstract:

Several yield-based stress indices have been developed that may be more applicable to work on drought tolerance. In this study, we investigate possibility of using stress susceptibility index (SSI), tolerance index (TOL), yield stability index (YSI), yield index (YI), stress tolerance index (STI), geometric mean productivity (GMP), harmonic mean (HARM), mean productivity (MP) to identify genotypic performance of some maize cultivars under normal and stressed condition. The results indicate that it was possible to identify superior genotypes for drought tolerance based on their stress indices and generally SSI indices which showed the lowest negative correlation with dry matter yield can be used as the best index for maize breeding programs to introduce drought tolerant hybrids. It was found that SC 647 showed the best behavior under drought stress condition based on TOL and SSI. A higher STI, GMP, and HARM values were attained for ko_6. It can be suggested that ko₆ should be cultivated in moderate stressful environment of Iran.

Keywords: Index, productivity, stress, susceptibility tolerance, yield.

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: Cutting condition, surface roughness, decision tree, CART algorithm.

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Authors: Amy LeBar, Kim L. Trenbath, Bennett Doherty, William Livingood

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Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC’s dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings, miscellaneous electric loads, plug loads, plug load management

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Authors: Meng-Lung Lin, Qiubing Wang, Fujun Sun, Tzu-How Chu, Yi-Shiang Shiu

Abstract:

The normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) derived from the moderate resolution imaging spectroradiometer (MODIS) have been widely used to identify spatial information of drought condition. The relationship between NDVI and NDMI has been analyzed using Pearson correlation analysis and showed strong positive relationship. The drought indices have detected drought conditions and identified spatial extents of drought. A comparison between normal year and drought year demonstrates that the amplitude analysis considered both vegetation and moisture condition is an effective method to identify drought condition. We proposed the amplitude analysis is useful for quick spatial assessment of drought information at a regional scale.

Keywords: NDVI, NDMI, Drought, remote sensing, spatialassessment.

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Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

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Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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Authors: Elnura Assyltayeva, Zhanar Aldubasheva, Zhengisbek Tolen

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An attempt has been made several times to identify and discuss the U.S. experience on the formation of political nation in political science. The purpose of this research paper is to identify the main aspects of the formation of civic identity in the United States and Kazakhstan, through the identification of similarities and differences that can get practical application in making decisions of national policy issues in the context of globalization, as well as to answer the questions “What should unite the citizens of Kazakhstan to the nation?" and “What should be the dominant identity: civil or ethnic (national) one?" Can Kazakhstan being multiethnic country like America, adopt its experience in the formation of a civic nation? Since it is believed that the “multi-ethnic state of the population is a characteristic feature of most modern countries in the world," it states that “inter-ethnic integration is one of the most important aspects of the problem of forming a new social community (metaetnic - Kazakh people, Kazakh nation" [1].

Keywords: nation, civic identity, nation building, globalization, interethnic relations, patriotism

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Authors: Rosida Ab. Razak, Mohamad Shanudin Zakaria

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The fundamental issues in ICT Governance (ICTG) implementation for Malaysian Public Sector (MPS) is how ICT be applied to support improvements in productivity, management effectiveness and the quality of services offered to its citizens. Our main concern is to develop and adopt a common definition and framework to illustrate how ICTG can be used to better align ICT with government’s operations and strategic focus. In particular, we want to identify and categorize factors that drive a successful ICTG process. This paper presents the results of an exploratory study to identify, validate and refine such Critical Success Factors (CSFs) and confirmed seven CSFs and nineteen sub-factors as influential factors that fit MPS after further validated and refined. The Delphi method applied in validation and refining process before being endorsed as appropriate for MPS. The identified CSFs reflect the focus areas that need to be considered strategically to strengthen ICT Governance implementation and ensure business success.

Keywords: IT Governance, Critical Success Factors.

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Authors: Alvise Pellegrini, Ernesto Benini

Abstract:

The design of a steam turbine is a very complex engineering operation that can be simplified and improved thanks to computer-aided multi-objective optimization. This process makes use of existing optimization algorithms and losses correlations to identify those geometries that deliver the best balance of performance (i.e. Pareto-optimal points). This paper deals with a one-dimensional multi-objective and multi-point optimization of a single-stage steam turbine. Using a genetic optimization algorithm and an algebraic one-dimensional ideal gas-path model based on loss and deviation correlations, a code capable of performing the optimization of a predefined steam turbine stage was developed. More specifically, during this study the parameters modified (i.e. decision variables) to identify the best performing geometries were solidity and angles both for stator and rotor cascades, while the objective functions to maximize were totalto- static efficiency and specific work done. Finally, an accurate analysis of the obtained results was carried out.

Keywords: Steam turbine, optimization, genetic algorithms.

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Authors: P. Prakasam, M. Madheswaran

Abstract:

A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.

Keywords: Bit Error rate, Receiver Operating Characteristics, Software Defined Radio, Wavelet Transform.

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Authors: Elizabeth Stojanovski

Abstract:

Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location, and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance and within study variance, and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: Random-effects, meta-analysis, Bayesian, variation.

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Authors: Popa Cosmin, Chiran Aurel

Abstract:

The study aimed to identify the logical structure of data and particularities of developing and testing a website designed for selling farm products through online auctions. The research is based on a short literature review in the field and exploratory trials of some successful models from other industries, in order to identify the advantages of using such tool, as well as the optimal structure and functionality of an auction portal. In the last part, the study focuses on the results of testing the website by the potential beneficiaries. Conclusions of the study underlines that the particularities of some agricultural products could raise difficulties in the process of selling them through online auctions, but the use of such system it is perceived to bring significant improvements in the supply chain. The results of scientific investigations require a more detailed study regarding the importance of using quality standards for agricultural products sold via online auction, the impact that implementation of an online payment system could have on trade with agricultural products and problems which could arise in using the website in different countries.

Keywords: E-commerce, online auctions, marketing.

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Authors: Tai-Yue Wang, Hui-Min Chiang, Su-Ni Hsieh, Yu-Min Chiang

Abstract:

In many industries, control charts is one of the most frequently used tools for quality management. Hotelling-s T2 is used widely in multivariate control chart. However, it has little defect when detecting small or medium process shifts. The use of supplementary sensitizing rules can improve the performance of detection. This study applied sensitizing rules for Hotelling-s T2 control chart to improve the performance of detection. Support vector machines (SVM) classifier to identify the characteristic or group of characteristics that are responsible for the signal and to classify the magnitude of the mean shifts. The experimental results demonstrate that the support vector machines (SVM) classifier can effectively identify the characteristic or group of characteristics that caused the process mean shifts and the magnitude of the shifts.

Keywords: Hotelling's T2 control chart, Neural networks, Sensitizing rules, Support vector machines.

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Authors: Kristine D. de Leon, Junifer A. Abatayo, Jose Cristina M. Pariña

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The current study is a comparative analysis of the use of shell nouns as a cohesive device (CD) in an English for Second Language (ESL) setting in order to identify their use and relationship in the quality of second language (L2) writing. As these nouns were established to anticipate the meaning within, across or outside the text, their use has fascinated writing researchers. The corpus of the study included published articles from reputable journals and graduate students’ papers in order to analyze the frequency of shell nouns using “highly prevalent” nouns in the academic community, to identify the different lexicogrammatical patterns where these nouns occur and to the functions connected with these patterns. The result of the study implies that published authors used more shell nouns in their paper than graduate students. However, the functions of the different lexicogrammatical patterns for the frequently occurring shell nouns are somewhat similar. These results could help students in enhancing the cohesion of their text and in comprehending it.

Keywords: Anaphoric-cataphoric, cohesive device, lexicogrammatical, shell nouns.

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Authors: Ahmad Alsolami, Darren Mundy, Manuel Hernandez-Perez

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Social media networks, such as Twitter, offer the perfect opportunity to either positively or negatively affect political attitudes on large audiences. The existence of influential users who have developed a reputation for their knowledge and experience of specific topics is a major factor contributing to this impact. Therefore, knowledge of the mechanisms to identify influential users on social media is vital for understanding their effect on their audience. The concept of the influential user is related to the concept of opinion leaders' to indicate that ideas first flow from mass media to opinion leaders and then to the rest of the population. Hence, the objective of this research was to provide reliable and accurate structural mechanisms to identify influential users, which could be applied to different platforms, places, and subjects. Twitter was selected as the platform of interest, and Saudi Arabia as the context for the investigation. These were selected because Saudi Arabia has a large number of Twitter users, some of whom are considerably active in setting agendas and disseminating ideas. The study considered the scientific methods that have been used to identify public opinion leaders before, utilizing metrics software on Twitter. The key findings propose multiple novel metrics to compare Twitter influencers, including the number of followers, social authority and the use of political hashtags, and four secondary filtering measures. Thus, using ratio and percentage calculations to classify the most influential users, Twitter accounts were filtered, analyzed and included. The structured approach is used as a mechanism to explore the top ten influencers on Twitter from the political domain in Saudi Arabia.

Keywords: Twitter, influencers, structured mechanism, Saudi Arabia.

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Authors: Taegyoo Woo, Jong Kang Park, Jong Tae Kim

Abstract:

Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Keywords: Visible light communication, optical channel, indoor positioning, Lambertian radiation.

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