ABSTRACT. Innovation is the de-facto strategy for sustainable development in the developed world and in most developing nations. The semiconductor industry happens to be one of the most innovation driven industries in the world in addition to being a driver of innovation in many industries such that it has been regarded as the driving engine of the world economy. Today, the rise of a nascent domestic semiconductor industry in Egypt is accompanied by major shifts, new market dynamics and evolving technology trends. The global semiconductor industry is undergoing major transformations due to several recent and current events such as the COVID pandemic, the US-China technology trade war, the Ukrainian and Iran wars as well as due to emerging global technology trends such as AI, Physical AI, electric and autonomous vehicles, drones and Robotics. As a result, several important dynamics have emerged and may prove highly valuable in enabling countries like Egypt to be a world player in this industry. The world is moving from a globalization model that has prevailed for decades to a model where manufacturing is more regional and distributed. Many players are starting to establish regional manufacturing facilities in contrast to depending on the Far East and specifically China as the World’s major manufacturer of electronics. This is driven by geopolitical reasons as well as security of supply chain and avoiding its disruption as has been the case in recent years. In addition, one important reason to move manufacturing facilities to regions closer to big markets is to minimize the cost of transportation and its negative impact on the environment. On the design side, many global players are looking for talent around the world to augment their resources and their ability to develop and produce new products in time. Such global companies will establish Offshore Design Centers (ODCs) wherever they find critical mass of talent that they can tap into. Egypt’s semiconductor industry has made significant strides in the last two decades and this has been recognized by the Global Semiconductor Alliance (GSA) by launching a local Chapter of the GSA in Egypt in June 2022. This talk will present the Egyptian semiconductor ecosystem, how this industry emerged in Egypt and a possible strategy for growing this promising industry in Egypt going forward.

ABSTRACT. Egypt and the ITU: This talk highlights Egypt’s strategic partnership with the International Telecommunication Union (ITU); for Global and Regional Digital Leadership explore the cooperative relationship between the United Nations’ specialized agency for ICTs and a nation positioned as a vital digital bridge between the global North and the Global South. As the ITU establishes the essential standards, spectrum allocations, and developmental frameworks that underpin our connected world, Egypt leverages its leadership within the Union to influence global policy and accelerate domestic transformation. By integrating its national goals with the ITU’s three core pillars—Radiocommunication (ITU-R), Standardization (ITU-T), and Development (ITU-D)—Egypt has moved beyond standard participation to active governance. As a re-elected member of the ITU Council and host to the ITU Arab Regional Office, the nation plays a decisive role in the Radio Regulations Board (RRB), protecting regional interests in spectrum management and cybersecurity. The talk further examines how this international influence fuels the "Digital Egypt" strategy, aligning infrastructure milestones, such as nationwide 5G deployment and fiber-optic expansion, with global benchmarks. Ultimately, this session illustrates how Egypt’s proactive engagement in emerging technology and AI governance reinforces its status as a premier regional hub, driving a more secure, inclusive, and technologically advanced future for the Arab and African regions.

ABSTRACT. Zero-day exploits circumvent the traditional Signature-based Intrusion Detection Systems (SIDS) due to the unpatched vulnerability, so holistic anomaly-based IDS (AIDS) architecture is introduced, which is benchmarked against the CICIDS2017 repository to detect novel intrusion vectors. Acute class disparities were handled in a two-step oversampling scheme; after combining Synthetic Minority Oversampling Technique (SMOTE) with Conditional Tabular Generative Adversarial Networks (CTGAN), high-fidelity and diverse attack examples were generated. The dimensionality reduction is done through the Least Absolute Shrinkage and Selection Operator (LASSO). This refined feature space is used to train three unsupervised models of anomaly detection: One-Class Support Vector machine (OC-SVM), K-Nearest neighbors (KNN), and Isolation Forest (IF). Performance evaluation on a reserved set of zero-day tests showed that OC-SVM achieved the highest effectiveness, with a 0.8253 Zero-Day Detection Rate (ZDR) and a 0.9094 F1-score. These results validate the proposed framework for detecting new attacks, indicating their potential as a generalized solution for active intrusion detection.

ABSTRACT. Industrial robotic manipulators increasingly rely on software-defined, network-connected motion pipelines, expanding the attack surface into motion-command semantics. False data injection attacks (FDIAs) can alter joint-command trajectories while preserving syntactic validity, potentially evading network-only IDS. We propose and experimentally evaluate a semantic-aware pre-execution validation gate as Stage-1 defense. This layer combines unsupervised anomaly detection using an Isolation Forest trained on benign joint-command dynamics and lightweight semantic constraints bounding stepwise displacement. In simulation on a 5-DOF robotic arm, we consider two attack models: an abrupt single-step injection and a low-rate multi-step drift. The step-wise semantic check reliably blocks abrupt manipulations, but slow drift can evade it. To address this, we introduce a trajectory-consistency rule that compares each command against a trusted reference trajectory within tolerance. Under the chosen thresholds, the extended gate achieves a false-positive rate of 0.002 and an F1-score of 0.941 on the drift attack, meeting the 50 ms control-cycle deadline.

ABSTRACT. Distributed Artificial Intelligence (AI) systems deployed across heterogeneous edge environments face significant resilience challenges due to dynamic failures, resource constraints, and device heterogeneity. Traditional fault-tolerance mechanisms often fail to maintain semantic continuity and system performance in such environments. This paper presents Neuro-Adaptive Self-Healing (NASH), a novel architectural framework designed to enhance the reliability of distributed edge AI systems. The proposed framework integrates Hierarchical Reinforcement Learning (HRL) with adaptive model partitioning and context-aware recovery mechanisms to enable intelligent self-healing during system disruptions. The NASH framework dynamically manages AI model placement across heterogeneous edge devices, including NVIDIA Jetson, Raspberry Pi, and mobile platforms, based on real-time hardware telemetry such as CPU/GPU utilization, thermal conditions, and battery levels. Experimental evaluation demonstrates that the proposed approach significantly improves system resilience, achieving a recovery latency of 75 ms compared with 150 ms for the baseline approach, while reducing resource overhead to 10% and maintaining 98.5% semantic continuity during failure scenarios. The results indicate that the proposed NASH framework provides an effective solution for maintaining reliable AI services in heterogeneous edge computing environments.

ABSTRACT. This paper presents the design and simulation of a millimeter-wave Voltage-Controlled Oscillator (VCO) implemented in TSMC 65nm CMOS technology, operating at 28 GHz and targeting 5G Ka-band applications. The proposed circuit utilizes a complementary cross-coupled LC topology to maximize transconductance efficiency and minimize phase noise under strict power constraints. To ensure robust integration, the design includes output buffers employing inductive peaking to extend bandwidth and drive capability. Simulation results demonstrate a phase noise of –104.36 dBc/Hz at 1 MHz offset. The VCO core dissipates a power of only 2.1 mW from a 1.5V supply with a fast startup time of approximately 2.2 ns at an oscillation frequency of 28 GHz. By employing a common-source amplifier as a buffer stage, the output power is 5.6 dBm at 28 GHz. The achieved Figure of Merit (FoM) of -190 dBc/Hz validates the proposed design as a high-performance, energy-efficient solution for next-generation millimeter-wave frequency synthesizers. Keywords: VCO, 5G, Ka-band, LC oscillator, phase noise, CMOS, millimeter-wave

ABSTRACT. This paper presents a dual-band filtering power amplifier (DB-FPA) in which the input and output matching networks are synthesized from the same dual-band bandpass-filtering cell, thereby unifying impedance transformation and frequency selectivity within a single design framework. The proposed architecture is organized around three coupled subsystems: a dual-band filter-like input matching network, a GaN-based amplification core, and a dual-band filter-like output matching network. The employed dual-band filter is derived from a symmetric coupled-line structure loaded by a dual-path resonant cell, whose unequal electrical lengths generate two transmission bands through controlled phase interference. By embedding this filtering mechanism at both transistor ports, the amplifier simultaneously realizes dual-band source/load matching, selective transmission, and inter-band suppression, without resorting to separate external filtering stages. The suggested DB-PA exhibits two well-defined operating bands of 1.4–1.6 GHz/ 3.35–3.6 GHz, with favorable small-signal selectivity and good matching performance. Under large-signal excitation, the amplifier delivers output power in the 38.0–41.6 dBm range, while the drain efficiency reaches 62.6%–72.4% in the lower band and 60.8%–77.3% in the upper band.

ABSTRACT. Resonant Cavity Enhanced Photodetectors (RCE-PDs) are widely considered as a promising solution for high-speed photodetection, as they effectively overcome the inherent trade-off between transit-time-limited bandwidth and quantum efficiency because of the multipaths of the incident light due to the presence of the Fabry-Pérot cavity that the photodetector is inserted in. In the case of Resonant Cavity Enhanced Avalanche Photodetectors (RCE-APDs), the photocurrent is further enhanced through the avalanche multiplication gain. In these photodetectors, the influences of tolerances in the dimensions of the multiplication, absorption, and charge layers on the electron ionization coefficients, multiplication gain, and overall device performance are investigated. This paper presents a stochastic analysis of the multiplication gain in RCE-separated absorption multiplication-APDs (RCE-SAM-APD), that is based on Monte Carlo simulations and on the frequency response of the photodetector.

ABSTRACT. This paper presents the design and optimization of a high-efficiency rectifier for radio frequency (RF)- energy harvesting (EH) applications operating at 0.9 GHz, targeting low-power wireless sensor and IoT systems. The proposed architecture employs a high-pass T-matching network integrated with a voltage doubler topology utilizing the HSMS-2852 Schottky diode. The design is implemented and analyzed using Advanced Design System (ADS) through S-parameter and Harmonic Balance simulations to ensure an accurate nonlinear performance evaluation. All critical parameters, including the matching network components, the rectification stage, the DC- pass filter, and the load resistance, are carefully optimized to maximize the RF-to-DC conversion efficiency and output voltage. The rectifier achieves a peak conversion efficiency of 55.122% at 0.9 GHz with an input power of 0 dBm and a 6 kΩ load, producing a DC output voltage of 2 V. Furthermore, the proposed design demonstrates an impedance bandwidth −10 dB of 150 MHz centered at 0.9 GHz, ensuring stable operation under frequency variations. Compared with recently reported rectifiers, the proposed circuit achieves improved efficiency while maintaining compact size and design simplicity on Rogers RO3003 substrate, making it suitable for integration into compact wireless power transfer and ambient RF harvesting systems.

ABSTRACT. This paper introduces an automatic and systematic method to design a generic multiple-impedance matching-network using a novel proposed computer aided design (CAD) tool. The task of this tool is to achieve conjugate matching for multiple source-load impedances at an arbitrary frequencies. Maximum gain within the acceptable user-defined design parameters is achieved. Design automation feature provided by the tool relies on the built-in multi-objective optimization algorithms using Matlab software. This tool provides the designer the ability to dictate various design parameters such as source/load complex impedances, frequencies of operation, bandwidths, and VSWR to be achieved simultaneously. Starting with suggesting applicable circuit configurations, the proposed CAD tool provides the acceptable operating ranges for each component, and the corresponding design parameters. The included interactive feature gives the designer extra degree of freedom to study the impact of each component on the whole network performance. To demonstrate the interesting features of the proposed CAD tool, a wide-band antenna is introduced as a practical case study to be matched with 50-$\Omega$ load. Based on the predefined constraints, the tool provides many solutions to solve the matching problem with the user constraints.