Search results for: user attributes analysis

Authors: Loh Fu Quan, Fong Zi Heng, Burra Venkata Durga Kumar

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Cloud computing has completely transformed the way many businesses operate. Traditionally, confidential data of a business is stored in computers located within the premise of the business. Therefore, a lot of business capital is put towards maintaining computing resources and hiring IT teams to manage them. The advent of cloud computing changes everything. Instead of purchasing and managing their infrastructure, many businesses have started to shift towards working with the cloud with the help of a cloud service provider (CSP), leading to cost savings. However, it also introduces security risks. This research paper focuses on the security risks that arise during data migration and user authentication in cloud computing. To overcome this problem, this paper provides a comprehensive framework that includes Transport Layer Security (TLS), user authentication, security tokens and multi-level data encryption. This framework aims to prevent authorized access to cloud resources and data leakage, ensuring the confidentiality of sensitive information. This framework can be used by cloud service providers to strengthen the security of their cloud and instil confidence in their users.

Keywords: Cloud computing, Cloud security, Cloud security issues, Cloud security framework

Procedia PDF Downloads 121

Authors: Mehmet Yörükoğlu, Serhat Aydın

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Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.

Keywords: digital library, multi criteria decision making, SWARA-WASPAS method

Procedia PDF Downloads 152

Authors: Floriane Shala, Evangeline Wagner, Yichun Zhao

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Background: Proper educational training and support are proven to be major components of EHR (Electronic Health Record) implementation and use. However, the majority of health providers are not sufficiently trained in EHR use, leading to adverse events, errors, and decreased quality of care. In response to this, students studying Health Information Science, Public Health, Nursing, and Medicine should all gain a thorough understanding of EHR use at different levels for different purposes. The design of a usable and safe EHR system that accommodates the needs and workflows of different users, user groups, and disciplines is required for EHR learning to be efficient and effective. Objectives: This project builds several artifacts which seek to address both the educational and usability aspects of an educational EHR. The artifacts proposed are models for and examples of such an EHR with a configurable UI to be learned by students who need a background in EHR use during their degrees. Methods: Review literature and gather professional opinions from domain experts on usability, the use of workflow patterns, UI configurability and design, and the educational aspect of EHR use. Conduct interviews in a semi-casual virtual setting with open discussion in order to gain a deeper understanding of the principal aspects of EHR use in educational settings. Select a specific task and user group to illustrate how the proposed solution will function based on the current research. Develop three artifacts based on the available research, professional opinions, and prior knowledge of the topic. The artifacts capture the user task and user’s interactions with the EHR for learning. The first generic model provides a general understanding of the EHR system process. The second model is a specific example of performing the task of MRI ordering with a configurable UI. The third artifact includes UI mock-ups showcasing the models in a practical and visual way. Significance: Due to the lack of educational EHRs, medical professionals do not receive sufficient EHR training. Implementing an educational EHR with a usable and configurable interface to suit the needs of different user groups and disciplines will help facilitate EHR learning and training and ultimately improve the quality of patient care.

Keywords: education, EHR, usability, configurable

Procedia PDF Downloads 158

Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

Procedia PDF Downloads 444

Authors: Yuanhong Zhao, Qingping Yang, Andrew Fox, Tao Zhang

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Post-occupancy evaluation (POE) is a systematic approach to assess the actual building performance after the building has been occupied for some time. In this paper, a structured POE assessment was conducted using the building use survey (BUS) methodology in two higher educational buildings in the United Kingdom. This study aims to help close the building performance gap, provide optimized building operation suggestions, and to improve occupants’ satisfaction level. In this research, the questionnaire survey investigated the influences of environmental factors on user satisfaction from the main aspects of building overall design, thermal comfort, perceived control, indoor environment quality for noise, lighting, ventilation, and other non-environmental factors, such as the background information about age, sex, time in buildings, workgroup size, and so on. The results indicate that the occupant satisfaction level with the main aspects of building overall design, indoor environment quality, and thermal comfort in summer and winter on both two buildings, which is lower than the benchmark data. The feedback of this POE assessment has been reported to the building management team to allow managers to develop high-performance building operation plans. Finally, this research provided improvement suggestions to the building operation system to narrow down the performance gap and improve the user work experience satisfaction and productivity level.

Keywords: building performance assessment systems, higher educational buildings, post-occupancy evaluation, user satisfaction

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Authors: Mirko Sailio

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Border crossing automatization reduces required human resources in handling people crossing borders. As technology replaces and augments the work done by border officers, new cyber threats arise to threaten border security. This research analyses the current cyber threat actors and their capabilities. The analysis is conducted by gathering the threat actor data from a wide range of public sources. A model for a general border automatization system is presented, and its most significant cyber-security attributes are then compared to threat actor activity and capabilities in order to predict priorities in securing such systems. Organized crime and nation-state actors present the clearest threat to border cyber-security, and additional focus is given to their motivations and activities.

Keywords: border automation, cyber-security, threat actors, border cyber-security

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Authors: Parisa Bagheri Tookanlou

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In this paper, we analyze a product line design problem faced by a manufacturing firm where the product line consists of a customized product in addition to a standard product and is offered in a market in which customers are heterogeneous on aesthetic attributes of the product. The customization level of a product is defined by the fraction of aesthetic attributes of the product that the manufacturer chooses to customize. In contrast to the existing literature on product line design that predominantly assumes deterministic demand, we consider the presence of demand uncertainty and frame the product line design problem in a single period (news vendor) setting. We examine the effect of demand uncertainty on product line decisions. Furthermore, we also examine how product line decisions are influenced by channel structure. While we use the centralized channel as a benchmark, we consider the decentralized dual channel where the customized product is sold through an online channel owned by the manufacturer and the standard product is sold through a retailer. We introduce a supply contract between the manufacturer and the retailer for improving channel efficiency and coordinate the distribution channel.

Keywords: product line design, demand uncertainty, customization level, distribution channel

Procedia PDF Downloads 187

Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

Procedia PDF Downloads 332

Authors: Tawfig Eltaif, Hesham A. Bakarman, N. Alsowaidi, M. R. Mokhtar, Malek Harbawi

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In Commonly, it is primary problem that there is multiple user interference (MUI) noise resulting from the overlapping among the users in optical code-division multiple access (OCDMA) system. In this article, we aim to mitigate this problem by studying an interference cancellation scheme called successive interference cancellation (SIC) scheme. This scheme will be tested on two different detection schemes, spectral amplitude coding (SAC) and direct detection systems (DS), using partial modified prime (PMP) as the signature codes. It was found that SIC scheme based on both SAC and DS methods had a potential to suppress the intensity noise, that is to say, it can mitigate MUI noise. Furthermore, SIC/DS scheme showed much lower bit error rate (BER) performance relative to SIC/SAC scheme for different magnitude of effective power. Hence, many more users can be supported by SIC/DS receiver system.

Keywords: optical code-division multiple access (OCDMA), successive interference cancellation (SIC), multiple user interference (MUI), spectral amplitude coding (SAC), partial modified prime code (PMP)

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Authors: K. C. Wong

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This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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Authors: Rajinder Kumar Gupta, Rajni Kant Agrawal, Jaganniwas

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One of the most frightening phenomena of nature is the occurrence of earthquake as it has terrible and disastrous effects. Many earthquakes occur every day worldwide. There is need to have knowledge regarding the trends in earthquake occurrence worldwide. The recoding and interpretation of data obtained from the establishment of the worldwide system of seismological stations made this possible. From the analysis of recorded earthquake data, the earthquake parameters and source parameters can be computed and the earthquake catalogues can be prepared. These catalogues provide information on origin, time, epicenter locations (in term of latitude and longitudes) focal depths, magnitude and other related details of the recorded earthquakes. Theses catalogues are used for seismic hazard estimation. Manual interpretation and analysis of these data is tedious and time consuming. A geographical information system is a computer based system designed to store, analyzes and display geographic information. The implementation of integrated GIS technology provides an approach which permits rapid evaluation of complex inventor database under a variety of earthquake scenario and allows the user to interactively view results almost immediately. GIS technology provides a powerful tool for displaying outputs and permit to users to see graphical distribution of impacts of different earthquake scenarios and assumptions. An endeavor has been made in present study to compile the earthquake data for the whole world in visual Basic on ARC GIS Plate form so that it can be used easily for further analysis to be carried out by earthquake engineers. The basic data on time of occurrence, location and size of earthquake has been compiled for further querying based on various parameters. A preliminary analysis tool is also provided in the user interface to interpret the earthquake recurrence in region. The user interface also includes the seismic hazard information already worked out under GHSAP program. The seismic hazard in terms of probability of exceedance in definite return periods is provided for the world. The seismic zones of the Indian region are included in the user interface from IS 1893-2002 code on earthquake resistant design of buildings. The City wise satellite images has been inserted in Map and based on actual data the following information could be extracted in real time: • Analysis of soil parameters and its effect • Microzonation information • Seismic hazard and strong ground motion • Soil liquefaction and its effect in surrounding area • Impacts of liquefaction on buildings and infrastructure • Occurrence of earthquake in future and effect on existing soil • Propagation of earth vibration due of occurrence of Earthquake GIS based earthquake information system has been prepared for whole world in Visual Basic on ARC GIS Plate form and further extended micro level based on actual soil parameters. Individual tools has been developed for liquefaction, earthquake frequency etc. All information could be used for development of infrastructure i.e. multi story structure, Irrigation Dam & Its components, Hydro-power etc in real time for present and future.

Keywords: GIS based earthquake information system, microzonation, analysis and real time information about liquefaction, infrastructure development

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Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Ndagi Salihu

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Corporate governance mechanisms are the control measures for ensuring that all the interests groups are equally represented and management are working towards wealth creation in the interest of all. Therefore, there are many empirical studies during the last three decades on corporate governance and firm performance. However, little is known about the effects of family ownership on the relationship between corporate governance and firm performance, especially in the developing economy like Nigeria. This limit our understanding of the unique governance dynamics of family ownership with regards firm performance. This study examined the impact of family ownership on the relationship between governance mechanisms and financial performance of publicly listed companies in Nigeria. The study adopted quantitative research methodology using correlational ex-post factor design and secondary data from annual reports and accounts of a sample of 23 listed companies for a period of 5 years (2014-2018). The explanatory variables are the board size, board composition, board financial expertise, and board audit committee attributes. Financial performance is proxy by Return on Assets (ROA) and Return on Equity (ROE). Multiple panel regression technique of data analysis was employed in the analysis, and the study found that family ownership has a significant positive effect on the relationships between corporate governance mechanisms and financial performance of publicly listed firms in Nigeria. This finding is the same for both the ROA and ROE. However, the findings indicate that board size, board financial expertise, and board audit committee attributes have a significant positive impact on the ROA and ROE of the sample firms after the moderation. Moreover, board composition has significant positive effect on financial performance of the sample listed firms in terms of ROA and ROE. The study concludes that the use of family ownership in the control of firms in Nigeria could improve performance by reducing the opportunistic actions managers as well as agency problems. The study recommends that publicly listed companies in Nigeria should allow significant family ownership of equities and participation in management.

Keywords: profitability, board characteristics, agency theory, stakeholders

Procedia PDF Downloads 142

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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Authors: Ayubi Wirara, Ardya Suryadinata

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Improper application of the RSA algorithm scheme can cause vulnerability to attacks. The attack utilizes the relationship between broadcast messages sent to the user with some fixed polynomial functions that belong to each user. Scheme attacks carried out by applying the Chinese Remainder Theorem to obtain a general polynomial equation with the same modulus. The formation of the general polynomial becomes a first step to get back the original message. Furthermore, to solve these equations can use Coppersmith's theorem.

Keywords: RSA algorithm, broadcast message, Chinese Remainder Theorem, Coppersmith’s theorem

Procedia PDF Downloads 342

Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

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Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

Procedia PDF Downloads 125

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Jesse D. Cano, Marlon J. Remedios

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Cuban tourism has developed so much in the last 30 years to the point of becoming one of the engines of the Cuban economy. With such a development, Cuban companies opting for e-tourism as a way to publicize their products and attract customers has also grown. Despite this fact, the majority of Cuban tourism-themed websites simply provide information on the different products and services they offer which results in many cases, in the user getting overwhelmed with the amount of information available which results in the user abandoning the search before he can find a product that fits his needs. Customization has been recognized as a critical factor for successful electronic tourism business and the use of recommender systems is the best approach to address the problem of personalization. This paper aims to outline a preliminary technique to obtain predictions about which products a particular user would give a better evaluation; these products would be those which the website would show in the first place. To achieve this, the theoretical elements of the Cuban tourism environment are discussed; recommendation systems and geographic information systems as tools for information representation are also discussed. Finally, for each structural component identified, we define a set of rules that allows obtaining an electronic tourism system that handles the personalization of the service provided effectively.

Keywords: geographic information system, technique, tourism products, recommendation

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Mohan Ramasundaram, Amutha Prabakar Muniyandi

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Remote user authentication is one of the important tasks for any kind of remote server applications. Several remote authentication schemes are proposed by the researcher for Telecare Medicine Information System (TMIS). Most of the existing techniques have limitations, vulnerable to various kind attacks, lack of functionalities, information leakage, no perfect forward security and ineffectiveness. Authentication is a process of user verification mechanism for allows him to access the resources of a server. Nowadays, most of the remote authentication protocols are using two-factor authentications. We have made a survey of several remote authentication schemes using three factors and this survey shows that the most of the schemes are inefficient and subject to several attacks. We observed from the experimental evaluation; the proposed scheme is very secure against various known attacks that include replay attack, man-in-the-middle attack. Furthermore, the analysis based on the communication cost and computational cost estimation of the proposed scheme with related schemes shows that our proposed scheme is efficient.

Keywords: Telecare Medicine Information System, elliptic curve cryptography, three-factor, biometric, random oracle

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Authors: Yake Zhang, Peng Xu

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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.

Keywords: artificial intelligence, building energy modelling, building simulation, large language model

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Authors: Shonuga Olajumoke Adedoyinsola

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Staffing and Compensation are at the core of any employment exchange, and they serve as the defining characteristics of any employment relationship. Most organizations understand the benefits that a longer term approach to staff planning can bring and the answer to this problem lies not in trying to implement the traditional approach more effectively, but in implementing a completely different kind of process for strategic staffing. The study focuses on critical points of compensation, staffing and personnel management. The fundamentals of these programs include the elements of vision, potential, communication and motivation. The aim of the paper is to identify the most important attributes of compensation and incentives, staffing and personnel management. Research method is the analysis and synthesis of scientific literature, logical, comparative and graphic representation. On the basis of analysis, the author presents the models of these systems for positive employee attitudes and behaviors.

Keywords: compensation, employees, incentives, staffing, personnel management

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Authors: Abdulaziz Fageeh

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This study investigates the integration of artificial intelligence (AI) within the landscape of language learning and teaching, exploring its potential benefits and challenges. Employing a mixed-methods approach, the research draws upon a comprehensive literature review, case studies, user reviews, and in-depth interviews with educators and students. Findings demonstrate that AI tools, including language learning apps and writing assistants, can enhance personalization, improve writing skills, and increase accessibility to language learning resources. However, the study also highlights concerns regarding over-reliance on AI, potential accuracy and reliability issues, and ethical implications such as data privacy and potential bias. User and educator perspectives emphasize the importance of balancing AI with traditional teaching methods, fostering critical thinking skills, and addressing potential misuse. The study concludes by underscoring the need for ongoing research and development to ensure responsible AI integration in language learning, focusing on pedagogical strategies, ethical frameworks, and the long-term impact of AI on learning outcomes.

Keywords: artificial intelligence, language learning, education, technology, ethical considerations, user perceptions

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Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

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Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

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Authors: Keunhong Chae, Seokho Yoon

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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.

Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm

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Authors: Sun-Mi Park, Ji-Hyun Jung, Min-Jung Kang

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Software (SW) education is scheduled to be included in the National curriculum in South Korea by 2018. However, Korean national kindergarten curriculum has been excepted from the revision of the entire Korean national school curriculum including software education. Even though the SW education has not been considered a part of current national kindergarten curriculum, there is a growing interest of adopting software education into the ECE practice. Teachers might be a key element in introducing and implementing new educational change such as SW education. In preparation for the adoption of SW education in ECE, it might be necessary to figure out ECE teachers’ perception and attitudes toward early childhood software education. For this study, 219 ECE teachers’ concern level in SW education was surveyed by using the Stages of Concern Questionnaire (SoCQ). As a result, the teachers' concern level in SW education is the highest at stage 0-Unconcerned and is high level in stage 1-informational, stage 2-personal, and stage 3-management concern. Thus, a non-user pattern was mostly indicated. However, compared to a typical non-user pattern, the personal and informative concern level is slightly high. The 'tailing up' phenomenon toward stage 6-refocusing was shown. Therefore, the pattern aspect close to critical non-user ever appeared to some extent. In addition, a significant difference in concern level was shown at all stages depending on the awareness of necessity. Teachers with SW training experience showed higher intensity only at stage 0. There was statistically significant difference in stage 0 and 6 depending on the future implementation decision. These results will be utilized as a resource in building ECE teachers’ support system according to his or her concern level of SW education.

Keywords: concerns-based adoption model (CBAM), early childhood education teachers, software education, Stages of Concern (SoC)

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Authors: Ramlan Jantan, Norfadilah Kamaruddin, Shahriman Zainal Abidin

Abstract:

In this era of technology, the co-creation method has become a new development trend. In this light, most design businesses have currently transformed their development strategy from being goods-dominant into service-dominant where more attention is given to the end-users and their roles in the development process. As a result, the conventional development process has been replaced with a more cooperative one. Consequently, numerous studies have been conducted to explore the extension of co-creation method in the design development process and most studies have focused on issues found during the production process. In the meantime, this study aims to investigate potential values established during the pre-production process, which is also known as the ‘circumstances value creation’. User involvement is questioned and crucially debate at the entry level of pre-production process in value in-exchange jointly spheres; thus user experiences took place. Thus, this paper proposed a potential framework of the co-creation method for Malaysian interactive product development. The framework is formulated from both parties involved: the users and designers. The framework will clearly give an explanation of the value of the co-creation method, and it could assist relevant design industries/companies in developing a blueprint for the design process. This paper further contributes to the literature on the co-creation of value and digital ecosystems.

Keywords: co-creation method, co-creation framework, co-creation, co-production

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Authors: James Skon, Irina Beshentseva, Michelle Polak

Abstract:

Wifi solutions come in two major classes. Small Office/Home Office (SOHO) WiFi, characterized by inexpensive WiFi routers, with one or two service set identifiers (SSIDs), and a single shared passphrase. These access points provide no significant user management or monitoring, and no aggregation of monitoring and control for multiple routers. The other solution class is managed enterprise WiFi solutions, which involve expensive Access Points (APs), along with (also costly) local or cloud based management components. These solutions typically provide portal based login, per user virtual local area networks (VLANs), and sophisticated monitoring and control across a large group of APs. The cost for deploying and managing such managed enterprise solutions is typically about 10 fold that of inexpensive consumer APs. Low revenue organizations, such as schools, non-profits, non-government organizations (NGO's), small businesses, and even homes cannot easily afford quality enterprise WiFi solutions, though they may need to provide quality WiFi access to their population. Using available lower cost Wifi solutions can significantly reduce their ability to provide reliable, secure network access. This project explored and created a new approach for providing secured managed enterprise WiFi based on low cost hardware combined with both new and existing (but modified) open source software. The solution provides a cloud based management interface which allows organizations to aggregate the configuration and management of small, medium and large WiFi solutions. It utilizes a novel approach for user management, giving each user a unique passphrase. It provides unlimited SSID's across an unlimited number of WiFI zones, and the ability to place each user (and all their devices) on their own VLAN. With proper configuration it can even provide user local services. It also allows for users' usage and quality of service to be monitored, and for users to be added, enabled, and disabled at will. As inferred above, the ultimate goal is to free organizations with limited resources from the expense of a commercial enterprise WiFi, while providing them with most of the qualities of such a more expensive managed solution at a fraction of the cost.

Keywords: wifi, enterprise, cloud, managed

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Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

Abstract:

Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

Procedia PDF Downloads 130