Gaussian filter based à-trous algorithm for image fusion

Image fusion integrates complementary information from various perspectives in order to provide a meaningful interpretation of useful features and textures in multisource images. Here, we present a multiresolution algorithm based on Stationary Wavelet Transform for fusion of two test images of same size. The algorithm uses a Gaussian low-pass filtering technique for the high frequency subbands of SWT decomposition. The new approach gave sharper edges and structural enhancement than region based approaches involving calculation of energy around salient features. The key feature of Gaussian filtering is the flexibility of using filters with different values for standard deviation depending on the application and the range of detail necessary for processing

Cybersecurity Index for undergraduate computer science courses in the UK

The paper proposes a novel index to classify how well UK Computer Science courses articulate cybersecurity-related content through their course/module pages. The aim of this work is to raise awareness among British Universities to pay more attention to include and standardize cybersecurity content in computer science courses. Our results show that 80% of analyzed courses scored 1 or 2-stars on a 5-Stars scale. The results also suggest the need for a formal delivery of cybersecurity content from the first year of the courses and possibly in a collaborative manner with the British Computer Society (BCS). To emphasize cybersecurity education in mitigating security lapses, the analogy is: it is better if most people know how to use a match than to train many fire-fighters

Music Source Separation Based on a Lightweight Deep Learning Framework (DTTNET: DUAL-PATH TFC-TDF UNET)

Music source separation (MSS) aims to extract 'vocals', 'drums', 'bass' and 'other' tracks from a piece of mixed music. While deep learning methods have shown impressive results, there is a trend toward larger models. In our paper, we introduce a novel and lightweight architecture called DTTNet, which is based on Dual-Path Module and Time-Frequency Convolutions Time-Distributed Fully-connected UNet (TFC-TDF UNet). DTTNet achieves 10.12 dB cSDR on 'vocals' compared to 10.01 dB reported for Bandsplit RNN (BSRNN) but with 86.7% fewer parameters. We also assess pattern-specific performance and model generalization for intricate audio patterns.Comment: Submitted to ICASSP 202

Forecasting Tropical Cyclones with Cascaded Diffusion Models

As cyclones become more intense due to climate change, the rise of AI-based modelling provides a more affordable and accessible approach compared to traditional methods based on mathematical models. This work leverages diffusion models to forecast cyclone trajectories and precipitation patterns by integrating satellite imaging, remote sensing, and atmospheric data, employing a cascaded approach that incorporates forecasting, super-resolution, and precipitation modelling, with training on a dataset of 51 cyclones from six major basins. Experiments demonstrate that the final forecasts from the cascaded models show accurate predictions up to a 36-hour rollout, with SSIM and PSNR values exceeding 0.5 and 20 dB, respectively, for all three tasks. This work also highlights the promising efficiency of AI methods such as diffusion models for high-performance needs, such as cyclone forecasting, while remaining computationally affordable, making them ideal for highly vulnerable regions with critical forecasting needs and financial limitations. Code accessible at \url{https://github.com/nathzi1505/forecast-diffmodels}.Comment: 6 pages, 3 figure

Smart, secure and sustainable robotic hand

Robotic manipulators have a wide range of applications in many sectors from automation to medical surgery. Since decades, researchers and developers have been proposing creative designs in leveraging specific applications or to demonstrate proof of concepts in bespoke scenarios. This paper presents a novel smart, secure and sustainable framework for the design of a 3D printed robotic hand. The smart robotic hand, consisting of two elements: i) a user-wearable glove and ii) a mechanical hand, is a seamless entity in which the movement of the mechanical hand is controlled by the user-wearable glove. A real-time communication between the glove (server) and the mechanical hand (client) is facilitated through a secure wireless client-server model running on a commercially available microcontroller making it light-weight and cost-effective. In order to promote sustainable 3D printing, a conscious decision was taken to use recyclable and biodegradable Polylactic acid (PLA) based wood filament for the casing of the mechanical hand as well a cotton and linen based material for the user glove

Bio-inspired framework for security in IoT devices

One of the many things COVID-19 has taught humanity is that the internet is not just a commodity but a vital service integral to the modern world. As we become ever more connected, there is a growing need to secure data and communication streams. If data is valued, then it should be protected. Unfortunately, some of the least secure devices in modern electronic systems are the Internet of Things (IoT) devices- partly due to their low processing power and always-on functionality. Polymorphism is the notion of changing one’s form. In biological organisms, polymorphic (mutating or changing) viruses trick the natural security mechanisms by changing their unique signatures (e.g. DNA or proteins). In computing, antivirus software systems are adapted to detect and remove constantly changing software viruses. However, polymorphism at the firmware level and over the wireless medium is neither well understood nor explored for IoT devices. This paper proposes a novel and bio-inspired framework for securing distributed IoT devices often assumed to be working at the intersection of engineering, computing, and cybersecurity domains. The proposed framework attempts to exploit the notion of polymorphism in resource-constrained (e.g. memory, power, band-width) IoT devices. The framework’s core aim is to detect, reject, and block foreign agents individually or collaboratively and in real-time within a client and server model by changing the access credentials and encryption keys as soon as an unauthorised client is detected. The framework proposed for the bio-inspired framework for security in IoT devices is designed to remain operationally compartmentalised, functionally integrated, and objectively unified

Wideband microstrip quasi-elliptic function bandpass filter with high out-of-band rejection

Presented in this article is a novel and compact quasi-elliptic function bandpass filter based on microstrip technology that exhibits a high out-of-band rejection over a very wide frequency range. The design comprises stub-loaded halfwavelength resonators that are electromagnetically coupled to resonant structures that are interdigitally coupled to the input and output feed-lines. Perturbation introduced by the presence of the stub causes the resonators to act as a multimode device. In addition, the stub introduces two transmission zeros to significantly improve the filter’s passband selectivity and suppress harmonic and spurious modes. This configuration yields a wideband response with low insertion loss of 0.73 dB, high return-loss 40 dB across 2-4.5 GHz and 5.74-16 GHz. The planar filter structure can be easily manufactured using standard PCB technology

Improved adaptive impedance matching for RF front‑end systems of wireless transceivers

In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a low-pass passive T-impedance matching LC-network inserted between an RF transceiver and its antenna. Results of the AQGA tuning method are presented for applications across 1.4 to 5 GHz (satellite services, LTE networks, radar systems, and WiFi bands). Compared to existing genetic algorithm-based tuning techniques the proposed algorithm converges much faster to provide a solution. At 1.4, 2.3, 3.4, 4.0, and 5.0 GHz bands the proposed AQGA is on average 75%, 49.2%, 64.9%, 54.7%, and 52.5% faster than conventional genetic algorithms, respectively. The results reveal the proposed AQGA is feasible for real-time application in RF-front-end systems

Method and tool for generating table of relevance in literature review (MTTR)

Every day, researchers in computing and IT are challenged with several articles that they need to rate, classify and separate quickly and effectively to contextualize and further advance their research effectively. It is considered that literature review is the most important step of discovery. Notably, a literature review is a part that allows the researcher to adjust the perspectives and limitations of an area of study. However, there is a lack of effective methods and tools for this activity. Often, traditional knowledge management techniques result in the “Gordian Knot” slowing down the process of literature review considerably. In this article, we present a Method and Tool for Generating Table of Relevance in Literature Review (MTTR). The MTTR is an innovative organizing method supported by software tools that make the literature review activity more efficient, faster and cheaper. An interesting feature of MTTR is data visualization using the Heat Map technique, Word Cloud and statistical techniques in designating and comparing each scientific article with the other relevant articles. The productivity gains in MTTR occur due to the automation in structuring and sorting scientific articles. In addition to efficiency, the lowest cost has the potential to place the MTTR as a preferred tool for the researcher. The anecdotal evidence reported in this article suggests that it is possible to carry out a literature review in a much shorter time with MTTR than in the traditional manner

Realizing UWB antenna array with dual and wide rejection bands using metamaterial and electromagnetic bandgaps techniques

This research article describes a technique for realizing wideband dual notched functionality in an ultra-wideband (UWB) antenna array based on metamaterial and electromagnetic bandgap (EBG) techniques. For comparison purposes, a reference antenna array was initially designed comprising hexagonal patches that are interconnected to each other. The array was fabricated on standard FR-4 substrate with thickness of 0.8 mm. The reference antenna exhibited an average gain of 1.5 dBi across 5.25–10.1 GHz. To improve the array’s impedance bandwidth for application in UWB systems metamaterial (MTM) characteristics were applied it. This involved embedding hexagonal slots in patch and shorting the patch to the ground-plane with metallic via. This essentially transformed the antenna to a composite right/left-handed structure that behaved like series left-handed capacitance and shunt left-handed inductance. The proposed MTM antenna array now operated over a much wider frequency range (2–12 GHz) with average gain of 5 dBi. Notched band functionality was incorporated in the proposed array to eliminate unwanted interference signals from other wireless communications systems that coexist inside the UWB spectrum. This was achieved by introducing electromagnetic bandgap in the array by etching circular slots on the ground-plane that are aligned underneath each patch and interconnecting microstrip-line in the array. The proposed techniques had no effect on the dimensions of the antenna array (20 mm × 20 mm × 0.87 mm). The results presented confirm dual-band rejection at the wireless local area network (WLAN) band (5.15–5.825 GHz) and X-band satellite downlink communication band (7.10–7.76 GHz). Compared to other dual notched band designs previously published the footprint of the proposed technique is smaller and its rejection notches completely cover the bandwidth of interfering signals