Ahmed Said Balamesh

Secure vehicle-to-vehicle communication is essential for electric-vehicle platoons because broadcast wireless links may expose safety and control messages to passive eavesdropping. This paper investigates a physical-layer security (PLS) framework for electric-vehicle (EV) platoons under Rician fading, representing the line-of-sight conditions common in highway platooning. The proposed Jamming-Aided Cooperative Relay Selection (JACRS) framework uses an amplify-and-forward relay, destination-assisted full-duplex friendly jamming, residual self-interference modelling, and a strict total transmit power budget. Relay selection is evaluated using a full-channel state information (CSI) secrecy-selection benchmark, a practical legitimate-link CSI rule, and a deterministic platoon-geometry-aware rule based on Cooperative Adaptive Cruise Control (CACC) position information without instantaneous eavesdropper CSI. Monte Carlo simulations, supported by semi-analytical secrecy-outage and deterministic-slot benchmarks, compare the proposed scheme with Rayleigh and no-jamming amplify-and-forward (AF) baselines. Under the simulated geometry, the scheme achieves a peak ergodic secrecy rate close to 5.0 bps/Hz at 40 dBm and reduces interception risk by 78.07% relative to the Rayleigh baseline. Relay diversity reduces secrecy outage from 14.14% to 0.04% under full CSI and to 0.22% using legitimate-link CSI. The geometry-aware rule reduces the gap between practical legitimate-link selection and the full-CSI benchmark, indicating that platoon position information can improve relay selection under the tested conditions.

This chapter addresses a prominent problem that is ubiquitous in scientific and engineering applications including the usually challenging task of cryptanalysis. This problem is the problem of integer factorization, i.e., the decomposition of a composite integer into a product of smaller integers, restricted herein to be prime integers. This is an intractable problem that might admit real-time hardware solutions for small bit sizes. This chapter suggests manual and automated scalable solutions for integer factorization based on equation solving over big Boolean algebras. The manual solution is illustrated over a form of 8-variable Karnaugh maps that is highly regular and modular. This solution covers the problem of 6 bits, which includes the problems of 5, 4, and 3 bits as special cases. Additionally, an automated solution is used, and the findings are then shown and briefly explained. These findings demonstrate the well-known evolution of temporal and spatial complexity with increasing input bit count. In future work, the largest possible hardware circuit that could be obtained via the automated solution is to be constructed, verified and tested. The complexity in our solution comes from two sources. One involves the task of finding the Boolean expressions for the solution. This task is slow, but it has to be done once, and only once, for a problem of a given size. The hardware implementation (e.g., an FPGA implementation) could serve as a ready real-time look-up solution not only of the pertinent problem but also of all smaller problems.

This paper considers the problem of solving a system of Boolean equations over a finite (atomic) Boolean algebra other than the two-valued one, referred to herein as a ‘big’ Boolean algebra. The paper suggests the replacement of this system of equations by a single Boolean equation, and then proposes a novel method for solving this equation by using its atomic decomposition into several independent switching equations. This method has many advantages including the efficient derivation of a complete compact listing of all particular solutions in a form similar to the recently-developed permutative additive form, but obtained in a more direct fashion without using parameters. Many detailed examples are used to illustrate the proposed new method. The examples demonstrate how the consistency condition might force a collapse of the underlying Boolean algebra into a subalgebra, and also how to list a huge number of particular solutions in a very small space.

Handwritten signatures are widely utilized as a form of personal recognition. However, they have the unfortunate shortcoming of being easily abused by those who would fake the identification or intent of an individual which might be very harmful. Therefore, the need for an automatic signature recognition system is crucial. In this paper, a signature recognition approach based on a probabilistic neural network (PNN) and wavelet transform average framing entropy (AFE) is proposed. The system was tested with a wavelet packet (WP) entropy denoted as a WP entropy neural network system (WPENN) and with a discrete wavelet transform (DWT) entropy denoted as a DWT entropy neural network system (DWENN). Our investigation was conducted over several wavelet families and different entropy types. Identification tasks, as well as verification tasks, were investigated for a comprehensive signature system study. Several other methods used in the literature were considered for comparison. Two databases were used for algorithm testing. The best recognition rate result was achieved by WPENN whereby the threshold entropy reached 92%.

In Inverse Synthetic Aperture Radar (ISAR) imaging, the Range Instantaneous Doppler (RID) method is used to compensate for the non-uniform rotational motion of the target that degrades the Doppler resolution of the ISAR image. The Instantaneous Range Instantaneous Doppler method (IRID) is proposed in this paper as a tool that compensates for higher order phase terms that may degrade both, the slant-range resolution and the Doppler resolution of the ISAR image. In IRID, adaptive S-distribution was applied on both the slant-range and Doppler dimensions of the image, thus, producing a better focused ISAR image. The IRID method was applied to simulated and measured data sets, and the ISAR images show that the IRID results offer better visual ISAR images than the RID results.

PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III), that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT) and Shannon entropy denoted by wavelet entropy (WE) feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%), which outperformed our occurrence rearrangements based method. The recognition rate was (81.41%) with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification.

Gamma radiography is used to monitor the corrosion of pipelines in remote locations; usually high radioactivity (10¹¹–10¹² Bq) is used. The technique is also not useful for imaging pipes with thick walls or large vessel walls. In this work, Compton backscattered radiation was used for the wall-thickness determination and corrosion imaging of pipe and flat materials using extremely-low-activity sources with radioactivities on the order of 10⁴–10⁵ Bq. A two-dimensional scanning system was designed to scan object surfaces, and the signals from a NaI(Tl) scintillation detector were fed into a computer for image construction using the LabView program. Thicknesses greater than 1 cm and 1.5 cm could be measured for Fe and Al and for polyvinyl chloride (PVC) and poly methyl methacrylate (PMMA), respectively. It was also possible to detect changes of less than 1 mm in depression depth for depressions measuring 3 mm in diameter. One- and two-dimensional images artificial defects on a pipe surface were successfully constructed.

In this work, a gamma ray Compton backscatter technique is used for imaging defects and thickness variations in insulated pipes and metal plates containing depressions of various diameters and at various depths from one side of the object. The scattered radiation was measured by a scintillation detector that scans the object using a two-dimensional mechanical scanning system. The gamma spectrum was displayed with a multichannel analyzer (MCA), and the energy window width was selected so that only Compton single scatter counts were measured. Images were constructed using the LabVIEW computer program. Successful images of defects on the outer surface of the object under the insulation were obtained, and the system was found to be able to detect wall thickness changes in large pipes with walls more than 15 mm thick. Low activity sources of 10⁸ Bq (a few mCi) were used, and the dose rate near the surface is four orders of magnitude lower than conventional industrial radiography sources, permitting it to be much safer.

We have demonstrated electrical spin-injection from GaCrN dilute magnetic semiconductor (DMS) in a GaN-based spin light emitting diode (spin-LED). The remanent in-plane magnetization of the thin-film semiconducting ferromagnet has been used for introducing the spin polarized electrons into the non-magnetic InGaN quantum well. The output circular polarization obtained from the spin-LED closely follows the normalized in-plane magnetization curve of the DMS. A saturation circular polarization of ∼2.5% is obtained at 200 K.