Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Imperfect CSI and Imperfect SIC on Artificial Noise Assisted Precoded Multiuser Secure NOMA-GSM

In this paper, secure downlink transmission with artificial noise (AN) aided generalized spatial modulation (GSM) has been analyzed. The transmitter sends the precoded data to the legitimate receivers (LUs) and the eavesdropper (eve) overhears it. The main emphasis is laid on the effect of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) on the secrecy capacity of LUs. AN is transmitted along with the information symbols to maintain the secrecy at the LUs. NOMA is used to transmit the data of all LUs at once. As precoding at the transmitter and AN designing is based on perfect CSI, hence imperfection in CSI leads to degradation in the capacity. Imperfection in SIC has been considered as an error in SIC at one user keeps repeating itself for other users. Monte-carlo simulations has been carried out to present the effect of both the errors simultaneously and separately on the capacity.
Pressureless Silver Sintering Die-Attach for SiC Power Devices

Pressureless silver sintering is an interesting die-attach technique that could overcome the reliability limitations of the power electronic devices caused by their packaging. In this paper, we study the manufacturing parameters that affect the die attach: atmosphere, drying time, heating ramp rate, sintering temperature and duration. It is found that sintering under air gives better results, but causes the substrates to oxidize. Sintering under nitrogen keeps the surfaces oxide-free, at the cost of a weaker attach.
Design Methods for interactive TV: two empirical studies

The central question for this paper is how to improve the production process by closing the gap between industrial designers and software engineers of television(TV)-based User Interfaces (UI) in an industrial environment. Software engineers are highly interested whether one UI design can be converted into several fully functional UIs for TV products with different screen properties. The aim of the software engineers is to apply automatic layout and scaling in order to speed up and improve the production process. However, the question is whether a UI design lends itself for such automatic layout and scaling. This is investigated by analysing a prototype UI design done by industrial designers. In a first requirements study, industrial designers had created meta annotations on top of their UI design in order to disclose their design rationale for discussions with software engineers. In a second study, industrial designers assessed the potential of four different meta annotation approaches. The question was which annotation method industrial designers would prefer and whether it could satisfy the technical requirements of the software engineering process. One main result is that the industrial designers preferred the method they were already familiar with, which therefore seems to be the most effective one although the main objective of automatic layout and scaling could still not be achieved.
When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity

Stable coexistence relies on negative frequency-dependence, in which rarer species invading a patch benefit from a lack of conspecific competition experienced by residents. In nature, however, rarity can have costs, resulting in positive frequency-dependence (PFD) particularly when species are rare. Many processes can cause positive frequency-dependence, including a lack of mates, mutualist interactions, and reproductive interference from heterospecifics. When species become rare in the community, positive frequency-dependence creates vulnerability to extinction, if frequencies drop below certain thresholds. For example, environmental fluctuations can drive species to low frequencies where they are then vulnerable to PFD. Here, we analyze deterministic and stochastic mathematical models of two species interacting through both PFD and resource competition in a Chessonian framework. Reproductive success of individuals in these models is reduced by a product of two terms: the reduction in fecundity due to PFD, and the reduction in fecundity due to competition. Consistent with classical coexistence theory, the effect of competition on individual reproductive success exhibits negative frequency-dependence when individuals experience greater intraspecific competition than interspecific competition i.e., niche overlap is less than one. In the absence of environmental fluctuations, our analysis reveals that (1) a synergistic effect of PFD and niche overlap that hastens exclusion, (2) trade-offs between susceptibility to PFD and maximal fecundity can mediate coexistence, and (3) coexistence, when it occurs, requires that neither species is initially rare. Analysis of the stochastic model highlights that environmental fluctuations, unless perfectly correlated, coupled with PFD ultimately drive one species extinct. Over any given time frame, this extinction risk decreases with the correlation of the demographic responses of the two species to the environmental fluctuations, and increases with the temporal autocorrelation of these fluctuations. For species with overlapping generations, these trends in extinction risk persist despite the strength of the storage effect decreasing with correlated demographic responses and increasing with temporal autocorrelations. These results highlight how the presence of PFD may alter the outcomes predicted by modern coexistence mechanisms.
Generation of Overhead View Images by Estimating Intrinsic and Extrinsic Camera Parameters of Multiple Fish-Eye Cameras

In recent years, systems to support driving a car using cameras are increasing. As an example, a system to generate overhead view images is proposed and used to assist drivers. In this paper, we propose a method for generating overhead view images with small errors by estimating intrinsic and extrinsic camera parameters of multiple fish-eye cameras. The accuracy of generated images is evaluated quantitatively by experiments and effectiveness of the proposed method is shown.
Empowering Random Walk Link Prediction Algorithms in Complex Networks by Adapted Structural Information

In the link prediction problem a relevant algorithm running over a network attempts to determine whether a link between two nodes will exist in the future, given that it is not present at the moment. Most link prediction algorithms take into account the structure of the network on which they are applied and based on this, they attempt to predict the existence or not of future new edges in the network. However, many of them are quite standardized, applying the same concept and parametrization to all networks, thus not always achieving good results in every different network structure. Algorithms based on Graph Neural Networks (GNNs) are more adaptive to any network structure but they do not give appreciable results when the only information available is the network structure. In this paper, we propose a new approach to this problem that approximates the structure of a complex network by allowing adjusted weight to this network structure to create additional information, which we can embed into effective algorithms such as local and superposed random walk link prediction. To achieve this goal, we use well-known kernel functions such as Sigmoids, in which we fit their parameters appropriately by a genetic algorithm to achieve the best possible approximation. To demonstrate the effectiveness of our proposed method we have compared our prediction method results based on precision, AUC and AUPR on eleven selected networks of different structures and properties with seven well-known link prediction algorithms and one more utilizing GNNs. In every case, we have improved the results of random walk algorithms and in most cases we achieved better results from all employed benchmark algorithms.
AI and Computer Vision in Cultural Heritage Preservation

In the recent years, rapid advances in technology, especially in Artificial Intelligence (AI) and Machine Learning (ML), have impacted the way economy functions, as well as society at large. The integration of these technologies in tourism plays a significant role in cultural heritage preservation. This research explores the intersection of artificial intelligence, cultural heritage, and tourism, with a focus on Montenegro’s efforts to leverage digital transformation for tourism development. Many monuments are not marked and there is no background information about their historical significance. With four UNESCO World Heritage sites, Montenegro is recognized as country with high touristic potential and rich cultural heritage, which implies that implementation of AI technologies can preserve forgotten monuments and give them a new life, as well as enhance the overall touristic experience and position Montenegro at the forefront of international touristic landscape. Using a well-known framework Flask, we developed web application that allows users to take images of a monument, upload it to our web application and after a few seconds, they get annotated image of a recognized monument, along with a text containing more information about the said monument.
Critical Success Factors of Internet Shopping in Japan: Customer-Centric and Website-Centric Perspectives

The results from a study conducted on the effect of factors on the customers’ attitude toward using Internet shopping in Japan are presented in this paper. The research model was an extended version of the consumers’ acceptance of virtual stores model with the addition of a new factor, need specificity, grouping critical success factors based on their customer-centric and website-centric perspectives sources, and examining how the differences in customer characteristics affect the actual use of Internet shopping. The results of an online questionnaire filled out by 1,215 Japanese online customers pointed out that gender, education level, innovativeness, net-orientation, and need specificity, factors of customer-centric perspective, have positive impacts on the actual use of Internet shopping. The implication also shows that Japanese online customers do not consider the service quality of Internet shopping, a factor of the websitecentric perspective, as significantly as offline customers do.
Assessment of Robustness of Power Systems From a Network Perspective

In this paper, we study the robustness assessment of power systems from a network perspective. Based on Kirchhoff's laws and the properties of network elements, and combining with a complex network structure, we propose a model that generates power flow information given the electricity consumption and generation information. It has been widely known that large scale blackouts are the result of a series of cascading failures triggered by the malfunctioning of specific critical components. Power systems could be more robust if there were fewer such critical components or the network configuration was suitably designed. The percentage of unserved nodes (PUN) caused by a failed component and the percentage of noncritical links (PNL) that will not cause severe damage are used to provide quantitative indication of a power system's robustness. We assess robustness of the IEEE 118 Bus, Northern European Grid and some synthesized networks. The influence of network structure and location of generators are explored. Simulation results show that the connection with short average shortest path length can significantly reduce a power system's robustness, and that the system with lower generator resistance has better robustness with a given network structure. We also propose a new metric based on node-generator distance (DG) for measuring the accessibility of generators in a power network which is shown to affect robustness significantly.
Collaborative Gaussian Processes for Preference Learning

We present a new model based on Gaussian processes (GPs) for learning pair-wise preferences expressed by multiple users. Inference is simplified by using a preference kernel for GPs which allows us to combine supervised GP learning of user preferences with unsupervised dimensionality reduction for multi-user systems. The model not only exploits collaborative information from the shared structure in user behavior, but may also incorporate user features if they are available. Approximate inference is implemented using a combination of expectation propagation and variational Bayes. Finally, we present an efficient active learning strategy for querying preferences. The proposed technique performs favorably on real-world data against state-of-the-art multi-user preference learning algorithms.
Nutritional, Safety and Sensory Evaluation of Innovative Siwi Date Snacks with Flavors and Fillings

Background: Due to their nutritional benefits and economic importance, dates are essential for all ages, nations, and civilizations. Dates include some nutritional components that can boost their nutritious worth. Objective(s): We aimed to assess the quality and safety attributes of Siwi semi-dry dates and their products with diverse tastes and fillings by measuring their chemical composition, safety features, and sensory aspects. Methods: Eleven Siwi semi-dry date products were evaluated . The flavors were milk, coconut, Oreo, cinnamon, coffee, Nescafé, cappuccino, caramel, peanut butter, Lotus, and Nutella. Additionally, our study assessed their chemical composition, including vitamin and mineral content besides evaluating their quality, safety, and sensory characteristics. Statistical analysis was performed, with a 5% least significant difference calculated for each treatment. Results : This study investigated Siwi semi-dry date snacks, revealing distinct nutritional profiles. Dark mix whole dates had the highest calorie, protein, and fat content; while plain whole dates had the lowest. Plain whole dates were rich in carbohydrates and sugars. Dark mix whole dates generally showed elevated vitamin and mineral levels. Quality attributes like texture favoured plain whole dates. Microbiological analysis confirmed safety, with no aflatoxins detected. Sensory evaluation ranked milk whole dates as the highest for colour, taste, odour, texture, and overall acceptance. These insights provide comprehensive overview, valuable information for both consumers and producers of Siwi semi-dry date snacks. Conclusion: Dates are a significant food source for carbohydrates, fibres, minerals, and vitamins. The quality attributes of date-based products increase the potential of being nutritious snacks.
Application of hybrid DEPSO algorithm to study the performance of different PID controller structures for automatic generation control of a two-area multi-units interconnected power system

This paper deals with design and analysis of automatic generation control (AGC) of a two area four unit interconnected thermal power system. Three different structures of proportional integral-derivative (PID) controller are used to study the transient response of the proposed system. Areal consists of two thermal generating units with reheat turbines and area2 has two thermal generating units with non-reheat turbines. The gains of PID controllers are optimized by using a novel hybrid Differential Evolution-Particle Swarm Optimization (DEPSO) technique. Step load perturbation (SLP) of 1 % is applied in areal to study the performance of different structures of PID controllers. Finally it is observed that the 3rd PID controller configuration performs better than the other two.
Reining In Windows API Abuses with In-lined Reference Monitors

Malware attacks typically effect damage by abusing operating system resources (e.g., the file system) that are exposed via system API calls. A method of using automated binary code-rewriting to monitor API calls and their arguments is presented and evaluated. Unlike traditional monitoring approaches, the framework requires no modification of the operating system, has no effect upon trusted processes, and preserves the behavior of most complex x86 native code binaries generated by mainstream compilers, including binaries that are object-oriented, graphical, contain callbacks, and use a mixture of static and dynamic linking. A separate verifier certifies that rewritten binaries cannot circumvent the monitor at runtime, allowing the binary-rewriter to remain untrusted. An implementation for Microsoft Windows demonstrates that the technique is effective and practical for real-world systems and architectures.
Modelling of stagnant zone formation on diamond cutting tool when turning titanium alloy

Diamond tools are increasingly used in advanced manufacturing because of their unique properties such as high hardness and thermal conductivity, and low thermal expansion unbeatable by any other known material. Despite their importance in machining of precision parts, extensive research on diamond tool wear is still underway. Particularly, maintaining the cutting edge sharpness and prolonging tool life are very important for machining difficult-to-cut materials. It is believed that the existence of stagnant zone on the tool rake face during cutting can protect the cutting edge from rapid wear. In this research, a new analytical stagnant zone model is derived based on boundary layer theory in fluid mechanics. The stagnant zone model predicts the stagnant zone length on diamond tools when machining titanium alloy. The cutting tool stress and chip velocity distributions required for the analysis of the stagnant zone model were taken from Finite Element (FE) modelling and simulation of orthogonal machining. Machining of Ti-6Al-4V with polycrystalline diamond and diamond-coated tools were experimentally carried out to obtain cutting forces and stagnant zone information at various cutting conditions. Used tools and postprocessed chips were investigated under scanning electron (SEM), field-emission scanning electron (FE-SEM) and optical microscopes. In FE modelling, input data such as material properties and the constants required in Johnson-Cook constitutive model were taken from the literature, and the friction data were calculated from experimentally measured forces. FE simulations were carried out for various cutting speeds, feeds, edge radius and surface roughness of the tool. The developed FE model is validated by comparing the predicted and experimental cutting forces. The predicted cutting forces are agreeable with the experiments. MATLAB is used to fit the equations that represent velocity and stress distribution as well as to calculate the stagnant zone length in the developed stagnant zone model. It is found that the predicted values are closed to the experimental results for both diamond tools. The average stagnant zone lengths formed at certain cutting conditions are between 0.1mm and 0.3mm. The used tool geometry, chip morphology and simulated shear strain, temperature, and velocity plots are also consistent with stagnant zone formation. The proposed stagnant zone model indicates that formation of stagnant zone is a function of cutting condition, tool geometry, the tool surface finish and material properties.
Application of Technology Acceptance Model (TAM) to The Use of 3D Digital Design (Case Study Fashion Design Results of 2 Fashion Design Students at Jakarta State University)

This study aims to determine the acceptance of users, in this case, students majoring in Fashion Education at Jakarta State University, to the 3D Digital Design application, which is used in making the final project of the Fashion Design 2 course. The respondents in this study were Fashion Design Education students who had taken the Applied Computer and Fashion Design 2 courses. This study used quantitative research methods with quantitative descriptive data analysis techniques. The result of this study showed that media and technology could increase productivity, performance, and process efficiency in making 3D fashion designs for students.
Clinical management guidelines of pediatric septic shock

Septic shock in children is the prototype combination of hypovolemia,cardiogenic and distributive shock. Recently published American college of critical care medinie(ACCM )recommendations for hemodynamic support of neonatal and pediatric patients with sepsis,Surviving sepsis campaign and its pediatric considerations and subsequent revision of definitions for pediatric sepsis has led to compilation of this review article. Practical application of this information in Indian set up in a child with septic shock will be discussed based on available evidence.Though guidelines mainly apply to pediatric age group,however a reference has been made to neonatal age group wherever applicable.
Diversity-multiplexing gain tradeoff: A tool in algebra?

Since the invention of space-time coding numerous algebraic methods have been applied in code design. In particular algebraic number theory and central simple algebras have been on the forefront of the research. In this paper we are turning the table and asking whether information theory can be used as a tool in algebra. We first show how diversity-multiplexing gain tradeoff (DMT) bounds of Zheng and Tse will give us information of the spread of determinants in matrix lattices and then apply these results to analyze unit groups of orders of division algebras. The results considering unit groups are not new or the best possible but we do find that this interesting relation between algebra and information theory is quite surprising and worth pointing out.
Low Distortion Multilevel Inverter for Efficient Solar PV Generation for EV Application

Renewable power generation has zero carbon emissions in various cases, but due to their default generation mode (DC power, such as in solar PV, fuel cells, etc.), these require inverters to supply the power to the ac loads. The power quality is an issue to address while doing DC/AC inversion and is also important for key EV applications such as driving EV motor. The inverters required may be of conventional 3-level, multi-pulse, or multi-level types. For the integration of discrete dc sources (such as SPV, fuel cell, etc.), multi-level inverters (MLIs) are preferred due to the various advantages of this structure. For the operation of MLIs, different modulation techniques are available in the literature viz. fundamental frequency switching or high-frequency switching. Total Harmonic Distortion (THD) in the output voltage produced by the inverter depends on the switching scheme chosen. To meet the requirement of various standards on harmonics, in this work, an optimized Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) technique is implemented for the control of a 9-level MLI. The proposed scheme improves the productivity of the inverter system as compared to Sinusoidal PWM (SPWM). In the presented scheme, THD due to odd harmonic components (including triplen harmonics) up to 49th order has been minimized using Genetic Algorithm Optimization (GAO) technique by considering multiple transitions per quarter cycle. It has been observed that the THD and distinct harmonic components up to the 49th order are within the limit set by various standards on harmonics. The viability of the presented scheme has been tested using analytical and simulation studies on a 9-level MLI.