A Modified Imperialist Competitive Algorithm for Spoofing Attack Detection in Single-Frequency GPS Receivers

Wireless Personal Communications - A GPS spoofing attack broadcasts counterfeit signals to resemble standard GPS satellite signals to take control of the correlation peaks of GPS signals to force...     

A Mobile Cloud-Based eHealth Scheme

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.     

Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of various Neural Networks trained on a custom dataset. It can be automated into assisting designers, allowing them to focus on the other more complicated parts of the system they are designing by quickly generating what would rather be straightforward busywork. Over the past 20 years, the boom in how much the internet is used and the sheer volume of pages on it demands a high level of work and time to create them. For the efficiency of the process, we proposed a multi-model-based architecture on image captioning, consisting of Convolutional neural network (CNN) and Long short-term memory (LSTM) models. Our proposed approach trained on our custom-made database can be automated into assisting designers, allowing them to focus on the other more complicated part of the system. We trained our model in several batches over a custom-made dataset consisting of over 6300 files and were finally able to achieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50 hand-drawn images at 87.86%     

Exploring the roles of portfolio steering committees in project portfolio governance

Governing project portfolios engages different actors in organizations including portfolio managers, portfolio officers, top managers, and others who may team up as portfolio steering committees. While portfolio steering committees play a regular role in project portfolio governance, their role is still unclear. Through an in-depth multiple case study in three Danish companies, the roles of portfolio steering committees were explored. The results showed that portfolio committees may play three distinct roles in portfolio governance: a) communication and consolidation role, b) negotiation role, and c) decision making role. The results challenged the notion that portfolio committee meetings are the place and time to make collective decisions on the portfolio, rather, portfolio steering committees might unintentionally become or intentionally be used for other purposes than decision making. The empirical evidence of the study proposes that these three roles might be related to two governance design factors: frequency and duration of committee meetings.     

Mcchanical and Microstructural Properties of Ultra-fine Grained AZ91 Magnesium Alloy l ubes Processed via Multi Pass Tubular Channel Angular Pressing (TCAP)

Ultra-fine grained(UFG) cylindrical tubes were produced via recently developed tubular channel angular pressing(TCAP) process through different passes from as-cast AZ91 magnesium alloy.The microstructure and mechanical properties of processed tube through one to four passes of TCAP process at 200 ℃ were investigated.Microhardness of the processed tube was increased to 98.5 HV after one pass from an initial value of 67 HV.An increase in the number of passes from one to higher number of passes has no more effect on the microhardness.Yield and ultimate strengths were increased by 4.3 and 1.4 times compared to those in as-cast condition.Notable increase in the strength was achieved after one pass of TCAP while higher number of passes has no more effect.Microstructural investigation shows notable decrease in the grain size to around 500 nm from the primary value of ~ 150 μm.Dissolution and distribution of hard Mg_(17)Al_(12) phase in the grain boundaries of dynamically recrystallized UFG AZ91 with a mean grain size of ~500 nm was an interesting issue of TCAP processing at 200 ℃ compared to other severe plastic deformation processes.     

Investigation and Simulation of a Two-Channel Drop Filter with Tunable Double Optical Resonators

In this paper, a photonic crystal (PhC) two-channel drop filter based on two 2×2 & 2×3 ring resonators is proposed. This structure is made of Germanium rods in an air background at a two-dimensional (2D) square lattice. Refractive index is chosen in a way in which that device can be easily fabricated. The photonic crystal two-channel drop filter is composed using a horizontal waveguide and two ring resonators, which are placed symmetrically about the horizontal axis. These ring resonators operate as energy coupling and capture the electromagnetic energy propagated in bus waveguide at their resonance frequencies. The filter characteristics are calculated using 2D finite-difference time-domain (FDTD) and plane wave expansion (PWE) methods. We show a two-channel drop filter with two resonators, based on studied basic structures and achieving optimal modes for channel drop filters with one resonator. We have done this through choosing the proper radii for all rods of lattice, setting radii of coupling rods, lattice constant, and studying basic structures having different refractive indexes. Finally, we show 84 % and 100 % dropping efficiencies can be achieved at D and C ports in the communication window and 100 % in direct port. The size of this device is 14.56 μm (length)×11.96 μm (width). This small size makes it possible to use the device in multiplexer applications in future communication systems and in all-optical integrated circuits.     

Dynamic analysis of carbon nanotubes under electrostatic actuation using modified couple stress theory

Modified couple stress theory is a size-dependent theorem capturing the micro/nanoscale effects influencing the mechanical behaviors of the micro- and nanostructures. In this paper, it is applied to investigate the nonlinear vibration of carbon nanotubes under step DC voltage. The vibration, natural frequencies and dynamic pull-in characteristics of the carbon nanotubes are studied in detail. Moreover, the effects of various boundary conditions and geometries are scrutinized on the dynamic characteristics. The results reveal that application of this theory leads to the higher values of the natural frequencies and dynamic pull-in voltages.     

A novel image encryption based on hash function with only two-round diffusion process

In this paper, a novel algorithm for image encryption based on hash function is proposed. In our algorithm, a 512-bit long external secret key is used as the input value of the salsa20 hash function. First of all, the hash function is modified to generate a key stream which is more suitable for image encryption. Then the final encryption key stream is produced by correlating the key stream and plaintext resulting in both key sensitivity and plaintext sensitivity. This scheme can achieve high sensitivity, high complexity, and high security through only two rounds of diffusion process. In the first round of diffusion process, an original image is partitioned horizontally to an array which consists of 1,024 sections of size 8 × 8. In the second round, the same operation is applied vertically to the transpose of the obtained array. The main idea of the algorithm is to use the average of image data for encryption. To encrypt each section, the average of other sections is employed. The algorithm uses different averages when encrypting different input images (even with the same sequence based on hash function). This, in turn, will significantly increase the resistance of the cryptosystem against known/chosen-plaintext and differential attacks. It is demonstrated that the 2D correlation coefficients (CC), peak signal-to-noise ratio (PSNR), encryption quality (EQ), entropy, mean absolute error (MAE) and decryption quality can satisfy security and performance requirements (CC <0.002177, PSNR <8.4642, EQ >204.8, entropy >7.9974 and MAE >79.35). The number of pixel change rate (NPCR) analysis has revealed that when only one pixel of the plain-image is modified, almost all of the cipher pixels will change (NPCR >99.6125 %) and the unified average changing intensity is high (UACI >33.458 %). Moreover, our proposed algorithm is very sensitive with respect to small changes (e.g., modification of only one bit) in the external secret key (NPCR >99.65 %, UACI >33.55 %). It is shown that this algorithm yields better security performance in comparison to the results obtained from other algorithms.