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In areas affected by natural disasters, the functionality of communication networks is often compromised, resulting in partial or complete outages. Effective message sharing, crucial for facilitating prompt recovery efforts, is achieved by establishing mobile ad-hoc networks among user-owned devices. Network operations in post-disaster scenarios are inhibited by intermittent connectivity, delays, and energy constraints, necessitating routing strategies that ensure seamless communication amidst node failures and mobility challenges. To meet this challenge, we previously introduced an adaptive and distributed routing mechanism named ADRIN, capitalizing on the inherent periodicity in human mobility. The present work, ADRIN2.0, extends the capabilities of ADRIN by incorporating a first-order Markov model-based mobility tracing approach to discern stable communication routes. It creates a spatiotemporal ad-hoc network to relay data multi-hop to the base station. Extensive simulations affirm that ADRIN2.0 approximates the underlying mobility distribution and facilitates data forwarding, even during node failures. ADRIN2.0 achieves a balance between data delivery rate and energy efficiency while minimizing latency, showing improvements over three centralized and two distributed routing benchmarks.

This paper presents a non-isolated bidirectional dc-to-dc converter (BDDC) topology employing a switched inductor switched capacitor (SISC) module. The bidirectional power flow capability aid to its application mainly in microgrids and electric vehicles. The switched inductor (SI) and switched capacitor (SC) cells in combination assist in the generation of high gain voltage without using a bulky transformer. The theoretical analysis of the proposed converter, its gain calculation, and small signal analysis are analyzed in detail. It benefits from having a wide voltage-gain range and less voltage stress across the power switches. Also, the proposed (SISC-BDDC) can operate both in boost and buck modes. Simulations are carried out for both the modes using MATLAB/Simulink platform. A 200 prototype is also developed to operate with $V_{\mathrm {in}}$ = 12 V and $V_{\mathrm {out}}$ = 160-200V. Using the dSPACE1104 control platform, the maximum efficiency of 95.25% of the converter is justified in steady and transient operating conditions.

Transportation is currently advancing towards Electric Vehicle (EV) technology. This paper presents a brief and systematic analysis of the real-time issues obtained in Electric Vehicles (EVs) due to the various ranges of energy storage devices. In general, EV energy management system is integrated with power electronic circuits for effective power conversion and reliable operation. Some issues are addressed while using the batteries in EV systems such as charging time, efficiency of battery, and raw materials. Not only battery issues but also real-time non-technical issues and operational issues are also discussed in this paper. During energy conversion with power electronic circuits, the system attains extreme temperature levels which in turn reduces the performance of the system. To maintain an optimum temperature level, it is important to study the temperature effect of the system at the most prior levels. Due to the adaption of power electronic components, some extent of noise is generated, technically treated as Electromagnetic Interference (EMI), as system capacity increases the EMI content also improved proportionately. Therefore, to mitigate the EMI effect, the low pass filter-based EMI filter is introduced in the system such that the noise level is suppressed. Bidirectional Charging System (BCS) is one of the emerging technologies in EV to obtain autonomous power supply systems in the form of Vehicle to Grid (V2G), Grid to Vehicle (G2V), and Vehicle to Load (V2L). To know the behaviour of BCS the proposed RNN controller is employed and is compared with ANN bidirectional charging model. BCS charging system with RNN controller has better dynamic response to exchange the power via DC/DC converter and AC/DC converter as compared to ANN controller.

This paper proposes a new reduced switch count seven-level triple boost inverter based on switched capacitor technique. The proposed topology has fewer number of components and has the ability of balancing the voltage across the capacitors. The structure of the proposed topology is very simple and can be easily extended to higher number of voltage levels. The generalized structure for higher number of levels is presented. The level shifted pulse width modulation approach is used to evaluate the proposed topology. In addition, design of switched capacitors and power loss calculation of semiconductor switches are provided. This proposed inverter topology is compared with the state-of-art topologies to demonstrate its superior performance. Further, thermal modelling of the topology is done in PLECS to calculate the power losses and efficiency. Finally, this proposed 7-level topology is simulated using MATLAB/Simulink and tested on experimental prototype for the performance verification and the results are included.

Digital watermarking is considered one of the most promising techniques to verify the authenticity and integrity of digital data. It is used for a wide range of applications, e.g., copyright protection, tamper detection, traitor tracing, maintaining the integrity of data, etc. In the past two decades, a wide range of algorithms for relational database watermarking has been proposed. Even though a number of surveys exist in the literature, they are unable to provide insightful guidance to choose the right watermarking technique for a given application. In this paper, we provide an exhaustive empirical study and thorough comparative analysis of various relational database watermarking techniques in the literature. Our work is different from the existing survey papers as we consider both distortion-based and distortion-free techniques along with a rigorous experimental analysis demonstrating a detailed comparison on robustness, data usability, and computational cost with considerable empirical evidence.

Recently, machine learning (ML) methods have been used to create powerful language models for a broad range of natural language processing tasks. An important subset of this field is that of generating code of programming languages for automatic software development. This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description, and code-to-code. The most popular applications that work in these paradigms were found to be code generation from natural language descriptions, documentation generation, and automatic program repair, respectively. The most frequently used ML models in these studies include recurrent neural networks, transformers, and convolutional neural networks. Other neural network architectures, as well as non-neural techniques, were also observed. In this review, we have summarized the applications, models, datasets, results, limitations, and future work of 37 publications. Additionally, we include discussions on topics general to the literature reviewed. This includes comparing different model types, comparing tokenizers, the volume and quality of data used, and methods for evaluating synthesized code. Furthermore, we provide three suggestions for future work for code generation using ML.

This paper presents the design, fabrication, and control of a quadruped wall-climbing robot. The robot’s kinematics is inspired by lizards, which use trot-gait for the locomotion. The key features of this robot are its pressure-sensitive adhesive (PSA) enabled adhesion and peeling mechanism and the locomotion controller capable of straight and turning motion. We obtained an average vertical climbing speed of 1.35 cm/s without payload and 1.25 cm/s with a payload of 20 gm. Rapid prototyping techniques namely 3D-printing and 2D-LASER cutting are used to fabricate the entire structure of the robot, allowing easy replication of the entire robot in case a swarm of such robots is needed. This paper also reports climbing stability criteria for the developed robot expressed in terms of the pitching moment. We envisage that the developed robot can be deployed in surveillance, reconnaissance, cleaning, and repairing applications.

Online coadaptive training has been successfully employed to enable people to control motor imagery (MI)-based brain-computer interfaces (BCIs), allowing to completely skip the lengthy and demotivating open-loop calibration stage traditionally applied before closed-loop control. However, practical reasons may often dictate to eventually switch off decoder adaptation and proceed with BCI control under a fixed BCI model, a situation that remains rather unexplored. This work studies the existence and magnitude of potential post-adaptation effects on system performance, subject learning and brain signal modulation stability in a state-of-the-art, coadaptive training regime inspired by a game-like design. The results extracted in a cohort of 20 able-bodied individuals reveal that ceasing classifier adaptation after three runs (approx. 30 min) of a single-session training protocol had no significant impact on any of the examined BCI control and learning aspects in the remaining two runs (about 20 min) with a fixed classifier. Fifteen individuals achieved accuracies that are better than chance level and allowed them to successfully execute the given task. These findings alleviate a major concern regarding the applicability of coadaptive MI BCI training, thus helping to further establish this training approach and allow full exploitation of its benefits.

This review paper assesses the main approaches in the electrical characterization of advanced MOSFETs towards their future analog and RF applications. Those approaches are shown to be different from the traditionally used ones for the assessment of the device perspectives for digital applications. Based on the original research realized by our group over the last years, advantages and necessity of those techniques will be demonstrated on different study cases of various advanced MOSFETs, such as Fully Depleted Silicon-on-Insulator (FDSOI), FinFETs and NanoWires (NW) in a wide temperature range (from cryogenic, 4 K up to 250°C). A wide frequency band characterization (from DC up to hundred GHz range) will be positioned as a key element enabling a fair device assessment towards analog and RF applications. Importance of the “extrinsic” parasitic elements in the advanced devices is enormous, sometimes even dominating the device performance. Therefrom arises the need for a proper separate extraction and discussion of “intrinsic” versus “extrinsic” parameters.

This work presents a detailed RF characterization of 28-nm FD-SOI nMOSFETs at cryogenic temperatures down to 4.2 K. Two main RF Figures of Merit (FoMs), i.e., current-gain cutoff frequency (ft) and maximum oscillation frequency (fmax), as well as parasitic elements of the small-signal equivalent circuit, are extracted from the measured S-parameters. An improvement of up to ~130 GHz in ft and ~75 GHz in fmax is observed for the shortest device (25 nm) at low temperature. The behavior of RF FoMs versus temperature is discussed in terms of small-signal equivalent circuit elements, both intrinsic and extrinsic (parasitics). This study suggests 28-nm FD-SOI nMOSFETs as a good candidate for future cryogenic applications down to 4.2 K and clarifies the origin and limitations of the performance.

This work studies the self-heating (SH) effect in ultra-thin body ultra-thin buried oxide (UTBB) FDSOI MOSFETs at cryogenic temperatures down to 77 K. S-parameter measurements in a wide frequency range, with the so-called RF technique, are employed to assess SH parameters and related variation of analog figures of merit (FoMs) at different temperatures. Contrary to the expectations, the effect of self-heating on analog FoMs is slightly weaker at cryogenic temperatures with respect to room-temperature case. The extracted thermal resistance and channel temperature rise at 300 K and 77 K in short-channel devices are of the same order of magnitude. The observed increase in SH characteristic frequency with temperature reduction emphasizes the advantage of the RF technique for the fair analysis of SH-related features in advanced technologies at cryogenic temperatures.

Lightpaths in translucent optical networks have to undergo regeneration at certain nodes designated as regeneration sites to maintain its quality of transmission. Regenerating an optical signal necessitates optical-electronic-optical conversion and is thus a costly affair due to use of regeneration resources. Thus minimizing the cost of regeneration in such networks is vital. Minimizing cost of regeneration leads to two different problems; 1) the problem of minimizing the total cost of regeneration for the connections served and 2) the problem of minimizing the cost of regeneration at regeneration sites while serving the connections. The previous works on lightpath establishment in such networks have mostly addressed the first problem. In this paper we study the second problem i.e. the problem of minimizing the cost of regeneration at regeneration sites during dynamic establishment of lightpaths. As the problem is NP-Complete, we propose an Integer Linear Program for small networks and then propose two heuristic routing approaches for large networks. Time complexity analysis shows that our heuristic algorithms run in polynomial time. Extensive simulation experiments reveal that our approaches are not only efficient to address the problem but can also provide better blocking performance when regeneration resources are scarcely deployed at regeneration sites.

In this paper, we have proposed two energy-efficient heuristics: (i) CMDE-RSCA (crosstalk-aware), and (ii) FMDE-RSCA (fragmentation-aware) to address the issues of inter-core crosstalk, and fragmentation within the core respectively- to ensure quality transmission of the optical signal for dynamic traffic in space division multiplexing elastic optical network (SDM-EON), while maintaining survivability of the network against single link failure. These heuristics based on multipath based survivability are compared with three existing survivable approaches based on p-cycles and shared path in terms of bandwidth blocking, energy consumption, crosstalk, and fragmentation. Both these algorithms outperform all three existing heuristics in terms of all parameters. In between CMDE-RSCA and FMDE-RSCA, CMDE-RSCA leads to consume lesser energy, whereas FMDE-RSCA produces lesser bandwidth blocking.

This article presents a feasibility study on the transmission of information through the biological tissues exploiting light. The experimental results demonstrating the potentials of optical wireless communications through biological tissues (OCBT) are presented. The main application of the proposed technology is in-body communications, where wireless connectivity needs to be provided to implanted electronic devices, such as pacemakers, cardiac defibrillators, and smart pills, for instance. Traditionally, in-body communications are performed using radio and acoustic waves. However, light has several fundamental advantages making the proposed technology highly attractive for this purpose. In particular, optical communications are highly secure, private, safe, and in many cases, extremely simple with the potential of low-power implementation. In the experiments, near-infrared light was used, as the light propagation in biotissues is more favorable in this part of the spectrum. The amount of light exposure given to biotissues was controlled to keep it within the safety limits. Information transmission experiments were carried out with the temperature-controlled ex vivo samples of porcine tissue. The tissue temperature was found to be significantly affecting the light propagation process. Communication performance with respect to the biotissue thickness and light direction was assessed. The results showed that optical channels to and from the possible implant are nearly reciprocal. Communication links were established to the deepness of more than four centimeters, and the data rates of up to 100 Kbps were obtained. The encouraging results of this study allow us to anticipate the potential applications of the proposed light-based technology to communicate with the various electronic devices implanted at different depths in the human body.