Aware User Research Articles

Comparing cooling strategies to assess thermal comfort resilience of residential buildings in Barcelona for present and future heatwaves

The upcoming summers are expected to see an increase in the intensity and duration of heat waves due to the effects of climate change. As a consequence, the thermal resilience of actual buildings might not be sufficient to keep comfortable conditions for their inhabitants. Cooling strategies to keep the houses fresh and cool will assume more and more important as the severity of these climatic events will intensify. Several simulations have been performed to compare how a selected case study apartment behaves with passive measures like natural ventilation and active measures, like mechanical ventilation and air conditioning. Two different types of behaviours are discerned, depending on the commitment of the user and its willingness to take measures to counteract the building overheating. The effect of retrofitting is taken into account as well. The simulations use of historic data from the summer of 2018 and 2022 and future climate scenarios from the summer of 2030 and 2050. Results highlight how external overheating progressively degrades the thermal resilience of the building with ventilation scenarios, but how air conditioning is more appropriate to keep comfortable conditions inside the house. The behaviour is fundamental, as an aware user can significantly increase comfort in the case of natural ventilation and reduce energy consumption averagely by 15% in case of the air conditioning.

Protection Aware User Identity and Data Storage (PAUIDS) Scheme for Management of User Identification in Cloud

Cloud computing the technology which have the capability of modifying the method computing strongly, and storage resources will be accessed shortly. User Identification is an entity to detect the user who using the system or website. In information technology the protection of information consistently become a major issue to handle. The data might place in various locations in the world since it become particularly serious. The two main factors regarding cloud technology are information protection and security. The cloud operators can easily reach the sensitive information that affects the data security and protection measures. Therefore, this research protocol mainly focuses on secure data storage that always been a significant feature of quality of service. To guarantee the ‘rightness of users’ information in cloud storage system a Protection Aware User Identity and Data Storage (PAUIDS) algorithm is proposed that separates the document and independently stores the user information in the cloud storage servers. The proposed algorithm reduces the encryption and decryption time in a cloud storage system and providing secure and efficient data storage in cloud environments.

Angle Aware User Cooperation for Secure Massive MIMO in Rician Fading Channel

Massive multiple-input multiple-output communications can achieve high-level security by concentrating radio frequency signals towards the legitimate users. However, this system is vulnerable in a Rician fading environment if the eavesdropper positions itself such that its channel is highly “similar” to the channel of a legitimate user. To address this problem, this paper proposes an angle aware user cooperation (AAUC) scheme, which avoids direct transmission to the attacked user and relies on other users for cooperative relaying. The proposed scheme only requires the eavesdropper’s angle information, and adopts an angular secrecy model to represent the average secrecy rate of the attacked system. With this angular model, the AAUC problem turns out to be nonconvex, and a successive convex optimization algorithm, which converges to a Karush-Kuhn-Tucker solution, is proposed. Furthermore, a closed-form solution and a Bregman first-order method are derived for the cases of large-scale antennas and large-scale users, respectively. Extension to the intelligent reflecting surfaces based scheme is also discussed. Simulation results demonstrate the effectiveness of the proposed successive convex optimization based AAUC scheme, and also validate the low-complexity nature of the proposed large-scale optimization algorithms.

2388-PUB: App-Based Diabetes Management Plan: An Analogy between Diabetes Awareness and Plan Adoption

Background: A Government-led screening of Indian population mentions that 70% Indians have no clue that they have diabetes. This lack of awareness can act as a serving point for digital healthcare platforms to provide understandable and accessible self-care. Aim: This study was conducted to explore if diabetes awareness acts as a motivation to employ patient-centric diabetes management plans on digital healthcare platforms. Methods: A diabetes management product, Diabetes Care Plan (DCP) was developed by 1mg Technologies Pvt. Ltd. Post three months of launch, a targeted survey with 12 question items (covering general information, diet, and monitoring) was pushed to all users (DCP and non-DCP) on 1mg mobile app. Responses were collated over three consecutive days and analyzed. Results: A total of 3,168 users took the survey (visitors) with 2,533 users completing it (responders). Of these responders, the overall awareness was significantly higher in DCP users (90%) as compared to non-DCP users (64%). Also, DCP users seemed to have higher awareness regarding diabetes (91%), effects of diet (70%), and monitoring (90%) as compared to non-DCP users. Conclusion: An aware user is more receptive to choose digital diabetes care plans. Empowering consumers with relevant information and structured program can create a one-stop solution for their health needs, improved self-care, and pursuit of better clinical outcomes Disclosure S. Mishra: Employee; Self; 1mg Technologies Pvt. Ltd. L. Kanodia: Employee; Self; 1MG Technologies Pvt. Ltd. V. Gupta: Employee; Self; 1MG Technologies Pvt. Ltd. P. Verma: Employee; Self; 1mg Technologies Pvt Ltd. G. Agarwal: Board Member; Self; 1MG Technologies Pvt. Ltd. P. Tandon: Board Member; Self; 1MG Technologies Pvt. Ltd. U. Gupta: Employee; Self; 1mg Technologies Pvt. Ltd.

Energy-Aware Resource Management in Heterogeneous Cellular Networks With Hybrid Energy Sources

In this paper, we focus on reducing the on-grid energy consumption in heterogeneous radio access networks (HetNets) supplied with hybrid power sources (grid and renewables). The energy efficiency problem is analyzed over both short- and long-timescales by means of reactive and proactive management strategies. For short-timescale case, a renewable-energy (RE) aware user equipment-base station association is proposed and analyzed for the cases when no storage infrastructure is available. For long-timescale case, a traffic flow method is proposed for load balancing in RE base stations (BSs), which is combined with a model predictive controller (MPC) to include forecast capabilities of the RE source behavior in order to better exploit a Green HetNet with storage support. The mechanisms are evaluated with data of solar measurements from the region of Valle de Aburra, Medellin, Colombia and wind estimations from the Moscow region, Russian Federation. Results show how the green association proposal can reduce on-grid energy consumption in a HetNet by up to 34%, while is able to exceed the savings obtained by other methods, including the best-signal level policy by up to 15%, additionally providing high network efficiency and low computational complexity. For the long-timescale case, MPC attainable savings can be up to 22% with respect to the on-grid only Macro-BS approach. Finally, an analysis of our proposals in a common scenario is included, which highlights the relevance of storage management, although emphasizing the importance of combining reactive and proactive methods in a common framework to exploit the best of each approach.

Coordinated Power Management in Data Center Networks

In this paper, we present a coordinated power management technique for data center networks (DCN) which we have implemented in the popular network simulator NS3. The proposed mechanism includes three key entities: (a) a local controller (LC) that manages traffic at each DCN node (switches and routers), (b) a global controller (GC) that has a global view of the DCN and provides hints to the LC's based on this knowledge, and (c) a topology aware user request assignment controller (RAC) that controls placement of the external requests on the endpoint hosts based on hints from the GC. The main goal of the coordination from the energy management perspective is to properly direct and consolidate network traffic to maximize low power (or “sleep”) opportunities for the network interfaces while avoiding link congestion. In the process of testing out our mechanisms, we have enhanced the popular NS3 package for network modeling. The key enhancements are in the accounting of energy consumption at various levels and enhanced traffic routing mechanisms. We show that these mechanisms can reduce the power consumption by up to ∼40% in the common fat-tree based DCNs using the low power idle (LPI) feature of the Ethernet. We also apply our mechanism to the Hypercube network and show that it too can save a significant amount of energy.

Cache Aware User Association for Wireless Heterogeneous Networks

The proliferation of network devices and novel bandwidth hungry applications over the existing network imposes novel challenges in terms of fulfilling the users’ requirements. Dense deployment of small cells is thought to be a promising solution to fulfill these requirements. However, the user association in such dense networks becomes challenging and can greatly affect the network performance, as a user in such dense deployments can be connected to any of the available base stations. Traditionally, the user association has been performed based on the signal strength, however, such an approach does not apply when taking into account novel bandwidth hungry applications. Moreover, in recent years, a successful paradigm has been proposed to handle such bandwidth hungry applications, i.e., caching at small cell base stations. In this paper, we aim to solve this joint problem of user association and content caching in a dense small cell setting. To solve this problem, we present a novel iterative scheme that uses matching theory and a learning approach to find a suboptimal solution of the joint NP hard problem. Note that the user association and cache placement are strongly coupled, i.e., the association of users at a base station will determine the cache placement at base stations and the availability of cache at base stations will force the users to change their associations. Simulation results show that the proposed scheme (i.e., cache aware user association) significantly outperforms the cache unaware scheme and achieves a performance gain of up to 31% in terms of normalized utility and saves up to twice the backhaul bandwidth. Moreover, the proposed scheme also achieves up to 82% of the utility obtained by the optimal solution.

Concurrent Optimization of Coverage, Capacity, and Load Balance in HetNets Through Soft and Hard Cell Association Parameters

Ultradense heterogeneous networks (HetNets) are emerging as an inevitable approach to tackle the capacity crunch in cellular networks. However, imbalanced load among small and macrocells and poor resource utilization as a consequence in HetNets remains a long-standing problem. This paper addresses this problem by presenting a solution for maximization of coverage and capacity while minimizing load imbalance among macro and small cells. Most recent studies on the topic focus on either optimization of coverage, capacity or load, or a combination of two of these three intertwined objectives. We formulate the optimization problem as a function of two hard parameters namely antenna tilt and transmit power, and a soft parameter, cell individual offset, that affect the coverage, capacity, and load directly. The resulting solution is a combination of the otherwise conflicting coverage and capacity optimization (CCO) and load balancing (LB) self-organizing network (SON) functions. In the presented joint CCO-LB solution, a conflict free operation of CCO and LB is ensured by designing a novel load aware user association methodology and resolving the effects of shadowing on coverage probability using stochastic approximation. The problem is proven to be nonconvex and is solved using genetic algorithm, sequential quadratic programming, and pattern search algorithms. The proposed CCO-LB solution is compared against two recently proposed CCO and CCO-LB solutions in the literature. Results show that the proposed solution can yield significant gain in terms of throughput, spectral efficiency, and load distribution.

Ontology-based effective information retrieval from the web using concept aware user profile construction

Similar document retrieval from the enormous volume of documents in database is a critical task. In this research work, improved information retrieval system utilising cooperative ontological based user profile construction (IIRS-COUPC) is introduced for accurate similar document retrieval. Here, cooperative ontology-based user profile (COUP) is built to take back the documents from diverse ideas that match with the user's demand. In order to make simplicity of document looking for process and merges the numerous users with identical demands, documents clustering (DC) and query clustering (QC) is accomplished in this work independently. Lastly, concept mapping (CM) is accomplished to take back the documents which matches with the user needs proficiently. The whole assessment of the current research work is accomplished in the java simulation environment from which it is shown that the current research methodologies confirms its improved performance.

Ontology-based effective information retrieval from the web using concept aware user profile construction

Similar document retrieval from the enormous volume of documents in database is a critical task. In this research work, improved information retrieval system utilising cooperative ontological based user profile construction (IIRS-COUPC) is introduced for accurate similar document retrieval. Here, cooperative ontology-based user profile (COUP) is built to take back the documents from diverse ideas that match with the user's demand. In order to make simplicity of document looking for process and merges the numerous users with identical demands, documents clustering (DC) and query clustering (QC) is accomplished in this work independently. Lastly, concept mapping (CM) is accomplished to take back the documents which matches with the user needs proficiently. The whole assessment of the current research work is accomplished in the java simulation environment from which it is shown that the current research methodologies confirms its improved performance.

Taxonomy of mobile users' security awareness

The popularity of smartphones, coupled with the amount of valuable and private information they hold, make them attractive to attackers interested in exploiting the devices to harvest sensitive information. Exploiting human vulnerabilities (i.e., social engineering) is an approach widely used to achieve this goal. Improving the security awareness of users is an effective method for mitigating social engineering attacks. However, while in the domain of personal computers (PCs) the security awareness of users is relatively high, previous studies have shown that for the mobile platform, the security awareness level is significantly lower. The skills required from a mobile user to interact safely with his/her smartphone are different from those that are required for safe and responsible PC use. Therefore, the awareness of mobile users to security risks is an important aspect of information security. An essential and challenging requirement of assessing security awareness is the definition of measureable criteria for a security aware user. In this paper, we present a hierarchical taxonomy for security awareness, specifically designed for mobile device users. The taxonomy defines a set of measurable criteria that are categorized according to different technological focus areas (e.g., applications and browsing) and within the context of psychological dimensions (e.g., knowledge, attitude, and behavior). We demonstrate the applicability of the proposed taxonomy by introducing an expert-based procedure for deriving mobile security awareness models for different attack classes (each class is an aggregation of social engineering attacks that exploit a similar set of human vulnerabilities). Each model reflects the contribution (weight) of each criterion to the mitigation of the corresponding attack class. Application of the proposed procedure, based on the input of 17 security experts, to derive mobile security awareness models of four different attack classes, confirms that the skills required from a smartphone user to mitigate an attack are different for different attack classes.

Impact of Neighbors on the Privacy of Individuals in Online Social Networks

Abstract The problem of user privacy enforcement in online social networks (OSN) cannot be ignored and, in recent years, Facebook and other providers have improved considerably their privacy protection tools. However, in OSN’s the most powerful data protection “weapons” are the users themselves. The behavior of an individual acting in an OSN highly depends on her level of privacy attitude: an aware user tends not to share her private information, or the private information of her friends, while an unaware user could not recognize some information as private, and could share it without care to her contacts. In this paper, we experimentally study the role of the attitude on privacy of an individual and her friends on information propagation in social networks. We model information diffusion by means of an extension of the Susceptible-Infectious-Recovered (SIR) epidemic model that takes into account the privacy attitude of users. We employ this diffusion model in stochastic simulations on a synthetic social network, designed for miming the characteristics of the Facebook social graph.

SLNR-based User Scheduling in Multi-cell networks: from Multi-antenna to Large-Scale Antenna System

In this paper, we investigate the performance of Signal to Leakage and Noise Radio (SLNR) based user scheduling in uplink of multi-cell with large-scale antenna system. Large antenna array is desired to improve the performance in future system by providing better beamforming capability. However, some studies have found that the signal channel is ‘hardened’ (becomes invariant) when the antenna number goes extremely large, which implies that the signal channel aware user scheduling may have no gain at all. With the mathematic tool of order statistics, we analyzed the signal and interference terms of SLNR in a homogeneous multicell network. The derived distribution function of signal and interference shows that the leakage channel’s variance is much more influential than the signal channel’s variance in large-scale antenna regime. So even though the signal channel is hardened, the SLNR-based scheduling can achieve remarkable multiuser diversity (MUD) gain due to the fluctuation of the uplink leakage channel. By providing the final SINR distribution, we verify that the SLNR-based scheduling can leverage MUD in a better way than the signal channel based scheduling. The Monte Carlo simulations show that the throughput gain of SLNR-based scheduling over signal channel based scheduling is significant.

A Performance and Usability Aware Secure Two-Factor User Authentication Scheme for Wireless Sensor Networks

Recently, several user authentication schemes for wireless sensor networks based on two-factor concept using the smart card technology were proposed. However, they have serious limitations in terms of security and usability. First, even though they are enhancements of other works, they still have several security flaws, such as vulnerability against parallel session, privileged-insider, and gateway-node bypassing attacks and lack of mutual authentication between user station and gateway node. On the other hand, they also present a usability constraint, in a sense that they do not consider the use case when sensor nodes cannot communicate with gateway node. In this case, data collected by isolated sensor nodes could not be accessed until they recover such communication, which is in many times not recoverable rapidly or forever (e.g., military applications, natural disaster monitoring). Due to all these reasons, this paper proposes a robust user authentication scheme which fixes the security weaknesses of previous solutions and provides wider usability considering the use case when the sensor nodes cannot communicate with the gateway node. Once the solution is described, its security is ensured by formal proof and analysis against attacks. Additionally, performance and cost analysis are executed to determine its level of feasibility for real implementation.

Model Driven Adaptation and Usability for Context Aware User Interfaces

In recent years, given the development of networks and technological innovations, the user mobility has increased so much. That is why the interactive applications must be executed on both mobile devices as PDAs, mobile phones and PC. The user is then progressing in a varied and dynamic environment. Therefore, the challenges of the User Interface are related to the adaptation to the context of use. This paper describes a model-based approach to generate user interfaces adapted to their context of use, while respecting usability. The Model Driven Engineering is used to provide solutions to the problems of adaptation and usability and allow automatic generation of user interfaces. The case study pertaining to a tourist guide system is used to illustrate our approach.