Microwave hyperthermia (MH) treatment for breast cancer is a research interest due to its capability to initiate cell necrosis in malignant tumor or to enhance the effect of other treatment modalities such as chemotherapy. The goal of MH treatment is to increase temperature of malignant tumor up to 45°C based on the treatment plan; however, microwave energy focusing is a challenging problem and may cause unwanted hotspots on healthy tissues. Therefore, there is a need to monitor the temperature to ensure that tumor and healthy tissues are at desired temperatures. In this paper, an iterative differential microwave imaging algorithm for temperature monitoring is presented. The algorithm is based on Born iterative method (BIM) and Tikhonov regularization. Feasibility of the algorithm is shown computationally using realistic digital breast phantoms via (i) TMz polarized 2-D scattered fields; and (ii) scattered fields calibrated from scattering parameters, which are obtained by a 3-D electromagnetic simulation program. An approach for selection of matching medium in hyperthermia monitoring applications is also presented. The reconstructions are performed with scattered field data collected at 11 discrete frequency points uniformly taken from the 0.5-1.5 GHz range. For a specific heating scenario, reconstruction error is lower than 0.3% with ±10% noise on reference dielectric property distribution and 35 dB signal to noise ratio (SNR). The results show that the proposed approach provides up to 3°C and 0.1°C resolution in temperature estimation with ±10\% noise on reference dielectric property distribution for 25 dB and 55 dB SNR values, respectively.

This paper is accepted for the IEEE SMC 2022 conference and addresses the problem of transfer of control authority between a robot’s AI and a remote human operator, when controlling a Mixed-Initiative (MI) robotic system. We propose a negotiation-theoretic method that enables the robot’s AI and the human operator to cooperatively and dynamically determine (i. e. negotiate) the transfer of control authority between these two agents. An experimental study is presented in which a state-of-the-art Expert-guided Mixed-Initiative Control Switcher (EMICS) method is compared with our proposed Negotiation-Enabled Mixed-Initiative Control Switcher (NEMICS) algorithm. Results suggest that the NEMICS framework is able to successfully avoid conflicts for control, which is a fundamental challenge encountered with previous MI control methods. Comparing NEMICS with the EMICS, we provide evidence of improved navigational safety (i. e. fewer collisions). Additionally, our usability study suggests that human operators perceived their interactions with NEMICS as less intrusive than with EMICS. The accompanying video demonstrates the differences between NEMICS and EMICS.

In recent years, deep learning has become the mainstream development direction in the change detection field, and its accuracy and speed have also reached a high level. However, the change detection method based on deep learning cannot predict all the change areas accurately, and its application is limited due to local prediction defects. For this reason, we propose an interactive change detection network (ICD) for very high resolution (VHR) based on a deep convolution neural network. The network integrates positive and negative click information in the distance layer of the change detection network, and users can correct the prediction defects by adding clicks. We carried out experiments on the open source dataset WHU and LEVIR-CD. By adding clicks, their F1-scores can reach 0.920 and 0.912, respectively, which are 4.3% and 4.2% higher than the original network. To better evaluate the correction ability of clicks, we propose a set of evaluation index—click correction ranges, which is suitable for evaluating clicks, and we carry out experiments on the above models. The results show that the method of adding clicks can effectively correct the prediction defects and improve the result accuracy.

Abstract - Diabetes is  chronic and metabolic disease. According to the World Health Organization (WHO), 422 million of adults suffer from diabetes worldwide. In fact, in 2012 diabetes caused 1.5 million deaths in the world. In Mexico, our country,diabetes is a highly relevant public health problem. For example, in 2015 there were 11 million cases of diabetes. Our contribution is to apply novel data science techniques to medical records at a dental clinic in Northeast Mexico to discover the relationship between diabetes and dental caries. Our research work follows IBM’s data science methodology. The analysis of data was carried out with machine learning. Five experiments were carried out on 193 dental records. Our findings corroborate the results found in related work.

In this paper, to demonstrate the chaotic behavior of a new 6D discrete system, the modern Matlab-Simulink software environment was used. We have obtained a discrete 6D chaotic system by the Euler method from a continuous 6D system of dynamic equations. In the Matlab-Simulink environment, models for continuous and discrete 6D systems of equations were created, and the results were identical. To demonstrate the synchronization of two unidirectional connected continuous and discrete 6D systems, Simulink models were proposed.  A discrete 6D system was applied for the chaotic masking of a narrow-band harmonic signal and image encryption. For visualizing and practical realization of the new chaotic discrete system we used Arduino Uno board and six light-emitting diodes (LEDs). The programming code and connecting technique are also shown. The program code was debugged into the free Arduino simulation environment such as Tinkercad. Compiling hex. file in the program software Arduino IDE allows us to simulate a 6D chaotic system using the Arduino Uno microcontroller in the Proteus 8 environment.

In recent years Kubernetes has become the de facto standard in the realm of service orchestration. Despite its great benefits, there are still numerous challenges to make it compatible with decentralised cloud computing platforms. One of the challenges of mobile edge computing is that the location of the users is changing over time. This mobility will constantly alter the proximity of the users to their connected services. One solution to this problem is to regularly move services to computing nodes near the users. However, distributing the services in edge nodes only subject to user movements will result in the fragmentation of active nodes. This leads to having active nodes that do not use their full capacity. We have proposed a method called Mobile-Kube to reduce the latency of Kubernetes applications on mobile edge computing devices while maintaining energy consumption at a reasonable level. An experimental framework is designed on top of real-world Kubernetes clusters and real-world traces of mobile users’ movements have been used to simulate the user’s mobility. Experimental results show that Mobile-Kube can achieve similar energy consumption performance to a heuristic approach that focuses on reducing energy consumption only while reducing the latency of services by 43%.

Image captioning is a sentence summarizing the semantic content of an image. Describing the essential information of an image in the form of a statement typically deals with computer vision and natural language processing. The prior research frequently addressed this subject simply using standard machine learning approaches that model such systems by extracting the hand-engineered characteristics from the input data. With the resurgence of deep-learning approaches, the image captioning area has experienced state-of-the-art outcomes in numerous application domains, including visual aid, traffic assistance, medical support, and remote sensing. This research thoroughly reviews the application domain-based image captioning frameworks by addressing both classical and modern deep learning-based architectures. We further propose a taxonomy to characterize the same by studying their distinct technological foundations and performances across diverse datasets. We also describe evaluation metrics used to examine the captioning image models across several domains. Finally, we highlight open research problems concerning such models from a futuristic standpoint.

Utilizing a crossdisciplinary approach, we explore Shannon information-theoretic characterizations of the information capacity limits of generic electromagnetic surfaces intended for possible use in wireless communication links. Our principal task is to first formulate at a general and rigorous level the electromagnetic theory of the information that can be extracted from the Maxwellian fields radiated by an arbitrarily-shaped continuous surface. This is then followed by a detailed derivation and illustration of practical physics-informed algorithms for computing approximations of the Shannon capacity of surfaces with any given geometry operating in Gaussian (AWGN) channels. Our formalism can address both near- and far-field information capacity scenarios, with a mathematical treatment that includes a complete characterization of the source-field polarization structure, mutual coupling, and interactions.

Integrating digital twins (DTs) and multi-access edge computing (MEC) is a promising technology that realizes edge intelligence in 6G, which has been recognized as the key enabler for Industrial Internet of Things (IIoT). In this paper, we explore a DT-assisted MEC system for the IIoT scenario where a DT server is created as a digital counterpart of the MEC server, via estimating the computation state of the MEC server within the DT modelling cycle. To achieve energy and spectrally efficient offloading, we consider that IIoT devices communicate with industrial gateways (IGWs) through a non-orthogonal multiple access (NOMA) protocol. Each IIoT device has an industrial computation task that can be executed locally or fully offloaded to IGW. We aim to minimize the total task completion delay of all IIoT devices by jointly optimizing the IGW’s subchannel assignment as well as the computation capacity allocation, edge association, and transmit power control of IIoT device. The resulting problem is shown to be a mixed integer non-convex optimization problem, which is NP-hard and challenging to solve. We decompose the original problem into four solvable sub-problems, and then propose an overall alternating optimization algorithm to solve the sub-problems iteratively until convergence. Validated via simulations, the proposed scheme shows superiority to the benchmarks in reducing the total task completion delay and increasing the percentage of offloading IIoT devices.

Let $P_s:= \mathbb F_2[x_1,x_2,\ldots ,x_s]$ be the graded polynomial algebra over the prime field of two elements, $\mathbb F_2$, in $s$ variables $x_1, x_2, \ldots , x_s$, each of degree one. This algebra is considered as a graded module over the  mod-2 Steenrod algebra, $\mathscr {A}$. The classical “hit problem”, initiated by Frank Peterson [Abstracts Amer. Math. Soc. 833 (1987), 55-89], concerned with seeking a minimal set of $\mathscr A$-module $P_s.$ Equivalently, when $\mathbb F_2$ is an $\mathscr A$-module concentrated in degree 0, one can write down explicitly a monomial basis for the $\mathbb Z$-graded vector space over $\mathbb F_2$: $$ QP_s:= \mathbb F_2 \otimes_{\mathscr A} P_s = P_s/\mathscr A^+\cdot P_s,$$ where $\mathscr A^{+}$ denotes the augmentation ideal of $\mathscr A.$ The problem is unresolved in general. In this paper, we study the hit problem for $P_s$ with $s\geq 5.$ More explicitly, we first compute explicitly the dimension of $QP_s$ for $s = 5$ in the generic degree $21\cdot 2^{t}-5$ with $t = 1.$ Note that the problem when $t = 0$ was solved by N. Sum [Vietnam J. Math. 49 (2021), 1079-1096]. Next, we study the dimension of $QP_s$ in degrees $s+5$ for $8\leq s\leq 9.$ This study corrects some results in Moetele and Mothebe’s paper [East-West Journal of Mathematics 18 (2016), 151-170]. We also give an explicit formula for the dimension of $QP_s$ in degree $14$ for all $s > 0$ and in degree $15$ for all $s > 0,\, s\neq 10.$ As applications, we investigate William Singer’s conjecture [Math. Z. 202 (1989), 493-523] on the algebraic transfer of rank $5$ in degrees $21\cdot 2^{t}-5$ for all $t\geq 0$ and of ranks $s > 0$ in internal degrees $d,\, 13\leq d\leq 15.$ This is a completely new result of proving the Singer conjecture for all ranks $s$ in certain internal degrees. In particular, our results have shown that any element in the $Sq^{0}$-families $\{\chi_t=(Sq^{0})^{t}(\chi_0)\in {\rm Ext}_{\mathscr A}^{5, 21\cdot 2^{t+1}}(\mathbb F_2, \mathbb F_2)|\, t\geq 0\}$ and $\{D_1(t)=(Sq^{0})^{t}(D_1(0))\in {\rm Ext}_{\mathscr A}^{5, 57\cdot 2^{t}}(\mathbb F_2, \mathbb F_2)|\, t\geq 0\}$ belongs to the image of the algebraic transfer of rank $5.$ For higher ranks, we explore the behavior of the algebraic transfer of rank 7 in the generic degrees $23\cdot 2^{t}-7$ for $t = 0$ and $\ell\cdot 2^{t}-7$ for $\ell\in \{9,\, 16\},\,  t\leq 3.$ Our results then claim that the non-zero elements $Pc_0\in {\rm Ext}_{\mathscr A}^{7, 23\cdot 2^{0}}(\mathbb F_2, \mathbb F_2),$\ $k_0 = k\in {\rm Ext}_{\mathscr A}^{7, 9\cdot 2^{2}}(\mathbb F_2, \mathbb F_2)$ and $h_6D_2\in {\rm Ext}_{\mathscr A}^{7, 2^{7}}(\mathbb F_2, \mathbb F_2)$ are not in the image of the transfer, and that every indecomposable element in the $Sq^{0}$-family $\{Q_2(t) = (Sq^{0})^{t}(Q_2(0))\in {\rm Ext}^{7, 2^{t+6}}_{\mathscr A}(\mathbb F_2, \mathbb F_2):\, t\geq 0\}$ belongs to the image of the transfer.

The increasing frequency and intensity of high impact storms, especially in Northeast United States, requires utilities and emergency managers to be increasingly prepared for lengthy power outage restorations. Historically, restoration has relied on emergency managers decennial experience with limited access to predictive models. This study highlights the development of a combined system composed of the UConn Outage Prediction Model (OPM) for predicting weather-related damage in the distribution system and an Agent-Based Model (ABM) for estimating the time to electric power restoration. The combined system is validated using Outage Management System (OMS) and crew deployment information for four historical extreme weather events that occurred in the State of Connecticut in the past decade. Through the ABM’s ability to test different restoration strategies, we study the impact that human knowledge and decisions have on the outage restoration curve. Furthermore, we use the model to test how the restoration could have been different if crews were allocated to area work centers based on the location of damage predictions from the UConn OPM and on increased crew counts, reflecting a more aggressive storm preparedness. This test highlights how an OPM-ABM system can benefit emergency preparedness and response managers in advance of storms impact.

The electromagnetic congestion due to the continuous growth of spectral demand has been skyrocketing for the past years. Joint radar-communication systems are thus attracting attention as they can alleviate the spectrum occupancy by using the same bandwidth to perform both applications. In this context, a cooperative radar-communication system, which is a specific category that uses communication codes to both transmit information and perform radar missions, can be considered. Continuous phase modulated (CPM) codes are considered in this article in order to generate high resolution radar images from an airborne radar. Since mitigating the sidelobe level energy is essential for good image quality, we resort here to optimized mismatched filters. A fast algorithm is proposed to minimize the computational time of these filters. Simulated data are generated, as well as re-synthesized SAR images, reconstructed from real chirp-based data, using CPM codes and mismatched filters. Their performance is evaluated using different comparison tools, and shows that the use of mismatched filtering and different messages embedded in the phase of each transmitted code, provides enhanced image quality.

The concept of rationality or irrationality of real numbers has been a fundamental question in mathematics for centuries. However, the theoretical and computational complexity of determining whether a given real number is rational or irrational presents an intriguing challenge. This research aims to explore the Undecidability of this problem and its inherent connection to the unresolvability found in the halting problem within the realm of computational theory. By investigating the parallels between the decision problem for rationality of real numbers and the halting problem, this study seeks to delve into the theoretical limits of computation and the boundaries that exist within mathematical systems. Through a combination of mathematical analysis and computational modeling, the research will examine the implications of Undecidability in determining the rationality of real numbers, shedding light on the broader implications for computability theory and theoretical computer science. The findings of this research will contribute to a deeper understanding of the intrinsic computational unresolvability present in determining the rationality of real numbers, offering insights into the intertwined nature of mathematical and computational complexity. Furthermore, the exploration of this topic has the potential to spark new perspectives on the limits of rationality and computability, paving the way for further investigations and potential applications in fields such as cryptography, number theory, and algorithmic complexity.

On any chip, the number of transistors doubles every eighteen months according to Moore’s law. When there are more transistors in a circuit, there is a higher probability that one of those transistors will have a fault. To avoid and detect possible errors,testing is required. To test the required circuit, the BIST (Built-in-Self-Test) energy saving design emplos a modified MISR as the ORA (Output Response Analyzer) and a bit-swapping LFSR as the TPG (Test Pattern Generator). In this paper, we select two circuits - a combined circuit and an 8x8 BCD  multiplier as CUT (circuit under test). TPG generates test patters that are fed into CUT, hile ORA evaluates the data generated by CUT and checks for errors in the circuit, and generates a pass/fail signal. This BIST structure detects one of the errors in the circuit.All results are matched to Xilinx ISE Design Suite 14.7 using Verilog and integrated into Vivado 2018.2.

This letter presents a reconfigurable intelligent surface (RIS)-equipped vehicle model to help improve the visual paths of millimeter-wave (mmWave) multiple-input and multiple-output (MIMO) communications. As obstacles disrupt the connections between a base station and its users, in this letter we propose a RIS-equipped vehicle to mitigate the interruptions of obstacles and enrich the service area. We set a RIS on the roof of a vehicle and use it in the MIMO mmWave systems to improve the visual paths and serve several single-antenna users efficiently. To verify the superiority of the channel estimation performance, we also propose a multiple RIS-assisted channel (m-RISC) model and employ an orthogonal matching pursuit (OMP) algorithm in this letter. The simulation result shows the achievable sum rate and the normalized mean squared error performance of the proposed m-RISC model, which outperforms the single RISC (s-RISC) model.

While the millimeter-wave (mmWave) communica- tion is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack.

In this study, an automated machine learning approach for the segmentation of MS lesions from multi- modal magnetic resonance images (mmMRI) is presented. The method is based on a U-Net like convolutional neural network (CNN) for 2D slice-based segmentation of 3D brain MRI volumes. The different modalities are encoded in sep- arate downsampling channels. The skip connections input feature maps to multi-scale feature fusion blocks at every stage of the network. These are followed by multi-scale feature upsampling blocks, which use the information from lesion shape and location. The CNN is evaluated on two publicly available datasets: The ISBI 2015 longitudinal MS lesion segmentation challenge dataset which contains 14 MS patients and the MICCAI 2016 MSSEG challenge dataset consisting of 15 MS patients. Regarding the ISBI Challenge, the proposed method was among the top performing ap- proaches to which open-access papers are available. The MICCAI dataset served to evaluate the robustness of the architecture against scanner variability and to show the improvements in performance after transfer learning.

A design oriented analysis of the RCD-type voltage clamp circuit, used to protect the active power semiconductor of the forward converter with demagnetizing winding. The operation of the circuit is described and analysis aimed at the dimensioning of the parameters is presented. The results are validated with the use of numerical examples and computer simulation, and are appropriate for the dimensioning and optimization of the circuit parameters.