Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless Physical Layer Security: Towards Practical Assumptions and Requirements

The current research on physical layer security is far from implementations in practical networks, arguably due to impractical assumptions in the literature and the limited applicability of physical layer security. Aiming to reduce the gap between theory and practice, this thesis focuses on wireless physical layer security towards practical assumptions and requirements. In the first half of the thesis, we reduce the dependence of physical layer security on impractical assumptions. The secrecy enhancements and analysis based on impractical assumptions cannot lead to any true guarantee of secrecy in practical networks. The current study of physical layer security was often based on the idealized assumption of perfect channel knowledge on both legitimate users and eavesdroppers. We study the impact of channel estimation errors on secure transmission designs. We investigate the practical scenarios where both the transmitter and the receiver have imperfect channel state information (CSI). Our results show how the optimal transmission design and the achievable throughput vary with the amount of knowledge on the eavesdropper’s channel. Apart from the assumption of perfect CSI, the analysis of physical layer security often ideally assumed the number of eavesdropper antennas to be known. We develop an innovative approach to study secure communication systems without knowing the number of eavesdropper antennas by introducing the concept of spatial constraint into physical layer security. That is, the eavesdropper is assumed to have a limited spatial region to place (possibly an infinite number of) antennas. We show that a non-zero secrecy rate is achievable with the help of a friendly jammer, even if the eavesdropper places an infinite number of antennas in its spatial region. In the second half of the thesis, we improve the applicability of physical layer security. The current physical layer security techniques to achieve confidential broadcasting were limited to application in single-cell systems. The primary challenge to achieve confidential broadcasting in the multi-cell network is to deal with not only the inter-cell but also the intra-cell information leakage and interference. To tackle this challenge, we design linear precoders performing confidential broadcasting in multi-cell networks. We optimize the precoder designs to maximize the secrecy sum rate with based on the large-system analysis. Finally, we improve the applicability of physical layer security from a fundamental aspect. The analysis of physical layer security based on the existing secrecy metric was often not applicable in practical networks. We propose new metrics for evaluating the secrecy of transmissions over fading channels to address the practical limitations of using existing secrecy metrics for such evaluations. The first metric establishes a link between the concept of secrecy outage and the eavesdropper’s ability to decode confidential messages. The second metric provides an error-probability-based se-
Modeling of e-Commerce Enterprise Expansion Processes

Informatization is the most noticeable factor in the impact of new technologies on e-commerce. In a highly competitive environment, the issue of enterprise expansion is relevant. In this regard, it is appropriate to present a conceptual model for the extension process, which can become the basis of strategic planning. The presented model is quite universal and can be used in the development of expansion plans for small businesses of different types. Prerequisites for creating an information model of expansion are the availability of expansion opportunities, expansion strategy, availability of appropriate software and a specialist who will design, create and troubleshoot related to the development, which are involved in the description of design decisions within a certain specific subject area at a certain stage of development, the chosen design methodology.
Massive-MIMO Based Statistical QoS Provisioning for mURLLC Over 6G UAV Mobile Wireless Networks

The sixth generation (6G) wireless networks are required to provide the massive ultra-reliable low-latency communication (mURLLC) services for massive subscribers, and thus, need to be supported by new techniques. Since the massive multiple-input multiple-output (massive MIMO) technique with massive antennas is able to substantially improve the channel performance, it has been widely applied to achieve the goal of mURLLC networks. Moreover, based on the inherent advantages of high mobility and dynamically deployment, the emerging unmanned aerial vehicle (UAV) technique has also been considered as one of the promising candidate techniques in the 6G wireless networks. However, how to integrate the massive MIMO and UAV techniques has never been thoroughly studied. In this paper, we first establish the massive MIMO channel model between a set of UAVs and a ground station, equipped with uniform rectangular antenna array. Then, we derive the expression of channel capacity for this channel model, which is a function of the distance between each UAV and each antenna. To support the mURLLC traffics in the 6G wireless networks, we employ the effective capacity theory to measure the maximum packet arrival rate, and we also derive the upper-bound on the effective capacity, which is a function of our obtained channel capacity. Finally, we validate and evaluate our derived results of the UAV communication with massive MIMO channel over 6G wireless networks through numerical analyses.
Continuous Hydrothermal Flexibility Coordination Under Wind Power Uncertainty

This paper proposes a stochastic continuous-time optimization model for coordinating the operation of flexibility reserve in a hybrid hydro-thermal-wind power system. The proposed continuous-time model captures the sub-hourly uncertainty and variations of wind power and load, and accurately models and schedules the ramping flexibility of the hydrothermal system to match the uncertainty and variations of wind power and load. A simplified Northern European system is studied over a 30-hour period to examine the potential of using hydropower as a comprehensive flexibility provider. Norwegian hydropower is shown to be a significant source of flexibility used to mitigate wind power variations, especially during ramping constrained periods. The hydropower provides 73.5% of the balancing energy in the base case, which includes smoothing out longer wind power deviations as well as rapid ramping relief. The short-term implications of increasing the offshore wind power in the North Sea by 50% compared to 2020 was also studied in the Northern European test system. The increased wind power causes steeper ramping in the net load, which drives the hydropower to its full balancing potential to allow thermal units to operate within their ramping limits.
Can musical encryption be both? A survey of music-based ciphers

Abstract The purpose of this article is to analyze the characteristics of a range of music-based ciphers (from the fifteenth to twentieth centuries) with respect to their intended goals and actual outcomes. Historically, the practitioners of music-based ciphers generally fall into one of two distinct groups: composers and cryptographers. The primary goal of the composers was to create music that embedded extra-musical content by means of musico-alphabetic correspondences. The cryptographers were generally interested in presenting many varieties of cryptographic methods of which ciphers incorporating musical notes were a very small part. The systems used by the former were usually so superficial they should not really be considered encryption; whereas the systems used by the latter were so mechanical that most would not consider the results to be music. Musical encryption can rarely be both because the attributes needed for convincing musicality and strong encryption are not mutually conducive. However, after examining these music-based cryptosystems in detail, I will consider what criteria might be necessary to create a reasonably secure cipher which produces a normatively-musical output and apply these in the form of an original music-based cipher. For most of the ciphers, interactive web applications have been developed which render plaintext into enciphered melodies.
Multisource Domain Transfer Learning Based on Spectral Projections for Hyperspectral Image Classification

Hyperspectral image classification is an important topic for hyperspectral remote sensing with various applications. Hyperspectral image classification accuracy. It has been greatly improved with the introduction of deep neural networks, while the idea of transfer learning provides an opportunity to solve the problem even with the lack of training samples. In this article, we propose an effective transfer learning approach for hyperspectral images, projecting hyperspectral images with different sensors and different number of bands into a general spectral space, preserving the relative positions of each band for spectral alignment, and designing a hierarchical depth neural network for shallow feature transfer and deep feature classification. The experiments show that the proposed method can effectively preserve the source domain features, especially for the scenarios with very few samples in the target domain, which can significantly improve the classification accuracy and reduce the risk of model overfitting. Meanwhile, this strategy greatly reduces the requirement of source domain data, using multisensor data to jointly train a more robust general feature model. The proposed method can achieve high accuracies even with few training samples compared to currently many state-of-the-art classification methods.
The Role of Infocommunication Technologies in the dot.com Bubble and in the Implementation of Unconventional Monetary Policy

In less than two decades, the Internet and the use of infocommunication technologies have immeasurably changed human lives. People have turned from objects who only receive information to subjects who are able to make relatively independent decisions. Moreover, the use of info communication technologies has significantly changed not only the conditions of development of individuals, but also the conditions of the development of whole national and world economies. Many established companies and new businesses have made millions using the info communication technologies, and many are hoping to do the same. In this study, we explore the role of info communication technologies in the Dot-com crisis and in the implementation of unconventional monetary policy. The Dot.com crisis is considered as one of the stimulating factors for the use of the unconventional monetary policy. The influence of the Dot.com bubble and unconventional monetary policy on the socio-economic development of countries is also revealed. We are also studying the possibility of a repeat of such a crisis today. It is difficult to argue that the growing popularity of info communication technologies, an increase in the number of companies in this area and a sharp increase in stock market indicators will lead to a repeat of the 2000 crisis, but it is still necessary to study these trends and learn lessons from past crises.
Mathematics in the Classroom: A Survey of Teachers' Opinions on the Use of Information and Communication Technologies (ICTs) in Teaching and Learning

Aim: The purpose of this study was to look into how school mathematics teachers use ICT in their classrooms, as well as the perceived barriers and challenges to ICT integration in mathematics classrooms. Study Design: The research was conducted using a descriptive cross-sectional survey research approach. Methodology: A cluster sampling strategy was utilized to pick 120 teachers from public schools in the keta municipality of the Volta region for this study. The questionnaire was returned by 105 teachers, with an 87.5 percent response rate, and descriptive statistics were utilized to analyze the data. 72 percent of the 105 teachers were males and 28 percent were females. Results: According to the findings, mathematics teachers use ICT in their classrooms to a very limited extent. Some mathematics teachers, on the other hand, frequently utilise ICT for common computer applications, including obtaining information on the internet for teaching, networking with colleagues and students, sending emails, and producing lesson notes etc. Respondents lacked proper training and access to instructional technologies, according to the findings. The lack of printers and presentation equipment in schools, according to respondents, may hinder their ability to integrate ICT into the teaching and learning process. Conclusions: Because of a lack of technical know-how and inadequate ICT tools, most mathematics teachers do not use ICT in their classroom. Teachers who have minimal experience with ICT, on the other hand, prefer to utilise it for non-teaching purposes.
Antibiotic-resistant pathogenic bacterial isolates from patients attending the outpatient department of university of Cape Coast hospital, Ghana: A retrospective study between 2013–2015

Uropathogenic Escherichia coli (E. coli) is an important urinary tract infection (UTI) that has been associated with both complicated and uncomplicated disease conditions. The global emergence of multiple drug-resistant (MDR) and extended-spectrum β-lactamase (ESBL) is of public health concern as the resistance limits the current treatment options. The objective of this study was to analyze the antibiotic-resistant patterns among the uropathogenic E. coli isolates at the University of Cape Coast (UCC) hospital between 2013 and 2015 as baseline data to understand the current antibiotic resistance situation within UCC and its environs. A retrospective cross-sectional study of bacteria isolates at UCC hospital from January 2013 to December 2015 were analyzed. A standard biochemical and antibiotic susceptibility tests were performed using Kirby-Bauer NCCLs modified disc diffusion technique. The network of interaction between pathogenic isolates and antibiotic resistance was performed using Cytoscape software. Statistical significance was tested using ANOVA and one-sample Wilcoxon test. The overall E. coli prevalence was 15.76% (32/203); females had the highest infection of 17.33% (26/150) compared to male subjects who had 11.32% (6/53) out of all the pathogenic infections. The E. coli prevalence among the age categories were 2/21 (9.52%), 27/154 (17.53%) and 4/21 (19.05%) among ≤20 years, 21–40 years and 41–60 years respectively. The isolated resistant pathogens exhibited different antibiotic resistance patterns. An interaction network of nodes connecting to other nodes indicating positive correlations between the pathogens and antibiotic resistance was established. Escherichia coli, Citrobacter spp, Klebsiella spp among other isolated pathogens formed higher centrality in the network of interaction with antibiotic resistance. The individual E. coli isolates showed a significant difference in the mean ± SD (95% CI) pattern of antibiotic resistance, 2.409±1.205 (1.828–2.990), χ2 = 36.68, p<0.0001. In conclusion, the study reports the interaction of E. coli isolates at UCC hospital and its antibiotic-resistant status between 2013 and 2015. This data forms the baseline information for assessing the current antibiotic status in UCC and its environs.
The convex grating with high efficiency for hyperspectral remote sensing

The convex grating is one of the key elements in Offner imaging spectrometers. In this paper the diffraction efficiency of the convex grating is investigated by using rigorous coupled-wave analysis (RCWA), which indicates that within the visible and near infrared broadband, the first-order diffraction efficiency can be over 40% through controlling the blaze angle of blazed convex grating. The blazed convex grating with the period of 6. 17μm in the center, the blaze angle about 2.9 degree, the anti-blaze angle about 21 degree, and the ruled area – a convex substrate with its radius 36.31mm and aperture 23.6mm has been fabricated by holographic lithography - scan ion beam etching. Experimental measurements show that the first-order diffraction efficiency is more than 30%, and the first-order diffraction efficiency at blazed wavelength can reach 62%.
Inverse method to identify crack parameters in multi-span beam using genetic algorithm

Abstract The increased flexibility due to the presence of an open crack in the multi-span beam is made bases for identification of crack location and size. The genetic algorithm is coupled with the inverse dynamics of the cracked beam to get effective solution. The modal parameters, obtained through non-destructive vibration testing, are the input to the code and the location and size of crack are the output. The crack is modeled as rotational spring, and support conditions are generalized in the formulation for cracked multi-span beam.
Vehicle Position Nowcasting with Gossip Learning

Nowcasting, i.e., short-term forecasting, of end user location is becoming increasingly important for anticipatory resource management in radio access networks (RAN). In this paper, we look at the case of vehicles moving in dense urban environments, and we tackle the location nowcasting problem with a particular class of machine learning (ML) algorithms that goes under the name Gossip Learning (GL). GL is a peer-to-peer machine learning approach based on direct, opportunistic exchange of models among nodes via wireless device-to-device (D2D) communications, and on collaborative model training. It has recently proven to scale efficiently to large numbers of static nodes, and to offer better privacy guarantees than traditional centralized learning architectures. We present new decentralized algorithms for GL, suitable for setups with dynamic nodes. In our approach, nodes improve their personalized model instance by sharing it with neighbors, and by weighting neighbors' contributions according to an estimate of their marginal utility. Our results show that the proposed GL algorithms are capable of providing accurate vehicle position predictions for time horizons of a few seconds, which are sufficient to implement effective anticipatory radio resource management.
Identification of commercial blocks of outstanding performance of sugarcane using data mining

In order to achieve more efficient agricultural production systems, studies relating to the patterns of influence factors on commercial blocks of outstanding performance can be performed to assist management practices. The performance is considered to be the difference between the yield of a given block and the average yield of the homogeneous group that it belongs to. The methods available to identify these outstanding blocks are usually subjective. The aim of this study was to propose an objective and repeatable approach to identify outstanding performance blocks. The proposed approach consisted of performance determination, using regression trees, and the classification of these blocks by k-means clustering. This approach was illustrated using a sugarcane model. The main factors influencing the tonnes of cane per hectare (TCH) and total recoverable sugar (TRS) yields were found to be crop age and water availability during ripening, respectively. These were used to create potential yield groups, and blocks with high and low performance were identified. The proposed approach was found to be valid in the identification of outstanding sugarcane blocks, and it can be applied to different crops or in the context of precision agriculture.
Simplified Cross‐Validation in Principal Component Regression (PCR) and PCR‐Like Machine Learning for Water Supply Forecasting

Cross‐validated principal component regression (PCR) is widely used in day‐to‐day operational forecasting systems for seasonal river runoff volume in western North America. Complexities are increasing in both predictor datasets (including climate‐science products) and in predictive models employed instead of linear regression within the PCR framework (including artificial intelligence), potentially complicating cross‐validation for model evaluation. We explored these issues with 300 modeling experiments on two high‐impact and hydroclimatically diverse basins in the western United States, the Truckee River (Sierra Nevada) and Rio Grande headwaters (southern Rockies), using five different PCR and PCR‐like machine learning models. The results suggest out‐of‐sample error is satisfactorily estimated by applying cross‐validation to only the final, supervised learning, step of PCR/PCR‐like procedures. The outcome facilitates streamlined algorithms and potentially reduced computational times for more complex emerging model architectures and datasets; provides reassurance around a possible inability to perform genuinely complete cross‐validation when predictors include certain complex and externally sourced data sources; and may reflect mitigation of overtraining by geophysical process‐informed model development protocols normally used during feature selection in operational water supply forecast (WSF). The results provide practical guidance helping support the design of next‐generation WSF models.
Frequency Multiplier Based on Field-Effect Transistor Structure with Negative Differential Resistance for Infocommunication System Facilities

A new electrical circuit of signal frequency multiplier based on nonlinear and reactive properties of field-effect transistor structure with negative differential resistance has been developed. Negative differential resistance provided compensating losses in the oscillating circuit, which increased the signal output power, efficiency of the multipliers, as well as stability of their operation. Equivalent circuit has been developed, on its basis the operation of frequency multiplier in the modes of frequency doubling and tripling has been investigated. A mathematical model of frequency multipliers based on nonlinear and reactive properties of the transistor structures with negative resistance has been proposed. The research results confirm the efficiency of the proposed frequency multipliers in a wide frequency range.
Impact of land use and climate change on forest reserves in Ghana

ABSTRACT Using supervised classified Landsat 7 images ETM – 2000 and 2010 and Landsat 8 images – 2020, this study examines the various Land Use Land Cover Changes (LULCC) in the Bosomkese forest reserve in Ghana. The study recorded significant changes in all the various forest covers driven predominately by illegal logging, bushfires, illegal farming, and agricultural expansion projects within the reserve. These results suggest that there is a need for stringent punishment for culprits involved in forest illegalities, capacity-building interventions and participatory forest management by the Forestry Commission, environmental management institutions, and forest fringe communities to protect the forest reserve.
Network Time Protocol Best Current Practices

The Network Time Protocol (NTP) is one of the oldest protocols on the Internet and has been widely used since its initial publication. This document is a collection of Best Practices for general operation of NTP servers and clients on the Internet. It includes recommendations for stable, accurate and secure operation of NTP infrastructure. This document is targeted at NTP version 4 as described in RFC 5905.