Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma

Personalization refers to the tailoring of products and purchase experience to the tastes of individual consumers based upon their personal and preference information. Recent advances in information acquisition and processing technologies have allowed online vendors to offer varieties of web-based personalization that not only increases switching costs, but also serves as important means of acquiring valuable customer information. However, investments in online personalization may be severely undermined if consumers do not use these services due to privacy concerns. In the absence of any empirical evidence that seeks to understand this consumer dilemma, our research develops a parsimonious model to predict consumers usage of online personalization as a result of the tradeoff between their value for personalization and concern for privacy. In addition to this tradeoff, we find that a consumers intent to use personalization services is positively influenced by her trust in the vendor. Our findings suggest that: 1. online vendors can improve their abilities to acquire and use customer information through trust building activities; 2. it is of critical importance that vendors understand and evaluate the different values consumers may place in enjoying various types of personalization.     

Extroversion,neuroticism and self-concept: their impact on internet users in India

The aim of this study was to find out the influence of personality structure of an individual, i.e., extroversion, neuroticism and self-concept on the usage of the Internet in India. Further, it was also aimed to find out the correlation between the three above-mentioned variables in the light of Internet usage. Exploratory research design was used in this study and the tools used were: Eysenck Personality Inventory and Mohsin Self-Concept Inventory. The Internet was the medium for data collection and individuals were invited by e-mail to participate in the study. The method of random sampling was used for selecting the sample size of 200. In this study, Internet users were classified as heavy or light users based on the number of hours spent online. While we found no significant difference between heavy and light users of Internet on extroversion and neuroticism, it was found that the heavy users scored high on self-concept.     

SecDL: QoS-Aware Secure Deep Learning Approach for Dynamic Cluster-Based Routing in WSN Assisted IoT

In WSN-assisted IoT, energy efficiency and security which play pivotal role in Quality of Service (QoS) are still challenging due to its open and resource constrained nature. Although many research works have been held on WSN-IoT, none of them is able to provide high-level security with energy efficiency. This paper resolves this problem by designing a novel Secure Deep Learning (SecDL) approach for dynamic cluster-based WSN-IoT networks. To improve energy efficiency, the network is designed to be Bi-Concentric Hexagons along with Mobile Sink technology. Dynamic clusters are formed within Bi-Hex network and optimal cluster heads are selected by Quality Prediction Phenomenon (QP²) that ensure QoS and also energy efficiency. Data aggregation is enabled in each cluster and handled with a Two-way Data Elimination then Reduction scheme. A new One Time-PRESENT (OT-PRESENT) cryptography algorithm is designed to achieve high-level security for aggregated data. Then, the ciphertext is transmitted to mobile sink through optimal route to ensure high-level QoS. For optimal route selection, a novel Crossover based Fitted Deep Neural Network (Co-FitDNN) is presented. This work also concentrates on IoT-user security since the sensory data can be accessed by IoT users. This work utilizes the concept of data mining to authenticate the IoT users. All IoT users are authenticated by Apriori based Robust Multi-factor Validation algorithm which maps the ideal authentication feature set for each user. In this way, the proposed SecDL approach achieves security, QoS and energy efficiency. Finally, the network is modeled in ns-3.26 and the results show betterment in network lifetime, throughput, packet delivery ratio, delay and encryption time.

     

Energy-saving potential by changing window position and size in an isolated building

The physical comfort of a building completely depends on the airing in the building. The window plays a superior role in providing ventilation without burning artificial energy. The forced system releases high poisonous gases such as CFCs, HCFCs, and HFCs. This paper concentrates on improvement of natural ventilation which is freely available by changing the size of the window and the orientation of the building. The computational fluid approach is used to understand the physical mechanism of air circulating inside the building. The forces and moments of air created inside the building also measured to achieve healthier considerations of circulation. From the results, it is evident that the natural ventilation is not only dependent on the velocity of air but also the orientation and shape of windows, and implementing an optimised design can save up to 20% of energy in residential buildings.     

Scaring the Already Scared: Some Problems With HIV/AIDS Fear Appeals in Namibia

Fear appeals are often used in public health campaigns in Africa to prevent further spread of HIV/AIDS. Based on the extended parallel processing model framework (K. Witte, 1991), this research assessed the impact of such messages in a high-fear situation. A 2 (high threat, low threat) × 2 (high efficacy, no efficacy) experiment with a no-message offset control and efficacy-only conditions tested several predictions. Participants demonstrated high preexisting fear about HIV/AIDS. As a likely consequence, statistical equivalence tests indicated that messages' threat levels had little impact on perceptions of fear or on outcome measures such as attitudes, intentions, or behaviors. It is concluded that the use of fear appeals to persuade audience with high levels of preexisting fear is ill-advised and ineffective.     

A model of advertiser—portal contracts: Personalization strategies under privacy concerns

Online portals provide personalization for “free”since the information acquired from consumers' usage of these services is valuable for advertising and targeted marketing purposes. Consumers' usage of services is determined by the tradeoff between their marginal value for personalized services and the resulting information privacy concerns and is captured by their personalization for privacy (P4P) ratio. A portal's decision to offer personalized services is dependent upon its cost of offering the services and revenue due to advertisers' marginal value for information (MVI) acquired therein. Through three models, our paper examines the strategic interaction between a portal that determines the service level to be offered and advertisers who pay the portal for placing advertisements through which they acquire information. Our first model of an independent portal finds that while all profits are increasing in the advertiser's MVI, with increasing P4P ratio the advertiser's profits are increasing at a faster rate than the portal's profits. In our second model, we consider an information sharing regime between two advertisers and find that a high MVI advertiser has a distinct first-mover advantage in announcing the services rate for the entire market. Our final model considers a portal that has its own advertising capabilities and we find that while this case is superior to others in the high MVI advertiser's and portal's profits, the consumer welfare and overall social welfare is dependent on the relative valuations of the two advertisers.     

Thin flexible photosensitive cholesteric displays

Abstract— A novel optically addressable, flexible bistable cholesteric liquid‐crystal display (ChLCD) is presented. These displays utilizeazo‐binaphthalene photosensitive chiral dopants that undergo photo‐isomerization upon exposure to light. The isomerization results in a change in the pitch of the cholesteric liquid crystal (ChLC), which enables the creation of inherently high‐resolution light‐weight displays that are optically written. The displays can be photo‐addressed without patterned electrodes or complex addressing schemes. Capitalizing on the dynamic pitch and the bistability of photosensitive ChLCDs, the display is switched with a single pulse at a specific single voltage to drive the region of the display with a shorter pitch to the focal‐conic texture and the region of the display with a longer pitch to the planar texture. Once in the different textures, the display can hold an image indefinitely regardless of ambient lighting. As such, these displays are a natural fit for badges, shelf‐labels, and point‐of‐sale cards. In this paper, the photosensitive properties of an encapsulated display system in comparison to an unencapsulated display system is discussed. Properties such a photosensitivity, thermal relaxation, and electro‐optical response are studied and reported. In addition, a flexible optically addressable ChLCD is developed and demonstrated.     

Multi-View AAM Fitting and Construction

Active Appearance Models (AAMs) are generative, parametric models that have been successfully used in the past to model deformable objects such as human faces. The original AAMs formulation was 2D, but they have recently been extended to include a 3D shape model. A variety of single-view algorithms exist for fitting and constructing 3D AAMs but one area that has not been studied is multi-view algorithms. In this paper we present multi-view algorithms for both fitting and constructing 3D AAMs. Fitting an AAM to an image consists of minimizing the error between the input image and the closest model instance; i.e. solving a nonlinear optimization problem. In the first part of the paper we describe an algorithm for fitting a single AAM to multiple images, captured simultaneously by cameras with arbitrary locations, rotations, and response functions. This algorithm uses the scaled orthographic imaging model used by previous authors, and in the process of fitting computes, or calibrates, the scaled orthographic camera matrices. In the second part of the paper we describe an extension of this algorithm to calibrate weak perspective (or full perspective) camera models for each of the cameras. In essence, we use the human face as a (non-rigid) calibration grid. We demonstrate that the performance of this algorithm is roughly comparable to a standard algorithm using a calibration grid. In the third part of the paper, we show how camera calibration improves the performance of AAM fitting. A variety of non-rigid structure-from-motion algorithms, both single-view and multi-view, have been proposed that can be used to construct the corresponding 3D non-rigid shape models of a 2D AAM. In the final part of the paper, we show that constructing a 3D face model using non-rigid structure-from-motion suffers from the Bas-Relief ambiguity and may result in a “scaled” (stretched/compressed) model. We outline a robust non-rigid motion-stereo algorithm for calibrated multi-view 3D AAM construction and show how using calibrated multi-view motion-stereo can eliminate the Bas-Relief ambiguity and yield face models with higher 3D fidelity. Electronic Supplementary Material The online version of this article () contains supplementary material, which is available to authorized users.     

Investigation on Mechanical and Thermal Properties of Stainless Steel Wire Mesh-Glass Fibre Reinforced Polymer Composite

Silicon - This work cope with the fabrication of hybrid structure composite made of woven glass fibre and Stainless Steel Wire Mesh (SSWM) embedded in Epoxy resin. The hybrid structure composite...     

Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

Recently, energy harvesting wireless sensor networks (EHWSN) have increased significant attention among research communities. By harvesting energy from the neighboring environment, the sensors in EHWSN resolve the energy constraint problem and offers lengthened network lifetime. Clustering is one of the proficient ways for accomplishing even improved lifetime in EHWSN. The clustering process intends to appropriately elect the cluster heads (CHs) and construct clusters. Though several models are available in the literature, it is still needed to accomplish energy efficiency and security in EHWSN. In this view, this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks (CROC-SEHWSN) model. The presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in EHWSN. The CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization (RO) algorithm. Besides, the CROC-SEHWSN model derives a fitness function (FF) involving seven distinct parameters connected to WSN. To accomplish security, trust factor and link quality metrics are considered in the FF. The design of RO algorithm for secure clustering process shows the novelty of the work. In order to demonstrate the enhanced performance of the CROC-SEHWSN approach, a wide range of simulations are carried out and the outcomes are inspected in distinct aspects. The experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.