Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Cyber-Attacks for Modern Digital Railway System Using Cyber Range

The simulation of a modern railway system on the cyber range will investigate the supple behavior of cyber-attacks in a modern digital railway system. The contemporary digital railway simulation architecture will focus on the railway's signaling system and the control command system, which is a classic SCADA system. With the introduction of IoT technology to railway systems, they have become vulnerable to cyber-attacks. The simulation is conducted on the cyber range server by simulating STCS. The cyber threats will be analyzed through penetration testing using Kali Linux on the simulated STCS on the cyber range. We analyze the impact of the threat agent groups, especially denial of service (DoS) and quay chain attacks that mainly target the STCS. The DoS attack generates the congestion of packets in the railway system network and will compromise the SCADA components in the STCS. The quay chain attack compromises the SCADA component, resulting in a delay in the signal system of STCS. The attack tree analysis helps us to understand the behavior of threat agents on STCS. Based on the research, we identified some mitigation techniques to reduce the cyber-attacks impact on the modern digital railway system.
A Review of the Recent Applications of Aluminum Nitride-Based Piezoelectric Devices

Piezoelectric materials have attracted considerable attention over the last two decades because many technologies utilize their core properties of piezoelectric materials. Previous applications consisted of bulk structures; however, a shift towards better performance and a more simplified and compatible fabrication method are required. Aluminum nitride (AlN) is a material that fits these criteria; it has a non-centrosymmetric crystal structure with a polarized c-axis and exhibits piezoelectric properties. Furthermore, it has an added benefit as the fabrication process of AIN is compatible with complementary metal–oxide semiconductor technology. This has led to a rapid increase in the adoption and interest in AlN-based devices. In this review, the crystal structure of AlN and its piezoelectric properties are compared with those of aluminum scandium nitride. Subsequently, functional devices such as consumer-based devices, telecommunication-based devices, industrial-related applications, and medical applications are presented. Finally, a summary and discussion of the future AlN research are presented.
Design of a dichroic Cassegrain subreflector

The design of a dichroic subreflector for a dual-frequency reflector antenna is described. This antenna consists of a Ku -band Cassegrain feed requiring the subreflector surface to be highly reflective at 13-15 GHz and a primary focus S -band feed requiring the subreflector to be transparent at 2.0-2.3 GHz. Such a performance is achieved by a surface of crossed dipoles printed on a dielectric sheet. The influence of parameters, dipole length, width and spacing, and the dielectric constant and thickness of the sheet on the reflection and transmission coefficients is experimentally evaluated. An analysis based upon the Floquent mode theory is shown to correctly predict the experimental results. The construction of a hyperbolic subreflector using the selected surface parameters is briefly described. As compared to a solid subreflector of identical shape, this dichroic subreflector produced a negligible loss (less than 0.1 dB) over a 13-15 GHz band. At the S band the loss was less than 0.2 dB over narrow selected bands and the axial ratio deterioration was also no more than 0.2 dB.
A Fusing Domain Feature and Sharing Label Space-Based Fault Diagnosis Approach for Different Distribution and Unlabeled Rolling Bearing Sample

As the different distributions between the source and target domains, rolling bearing fault diagnosis based on domain adaptation (DA) has achieved a good result in unlabeled sample fault diagnosis of target domain. However, most transfer strategies focus mainly on the domain-invariant feature between the source and target domains, with little attention paid to the intrinsic feature of the target domain. This limitation causes poor knowledge transfer from the source domain due to domain confusion. Therefore, this article proposes a novel method for unlabeled rolling bearing fault diagnosis in the target domain that leverages both the intrinsic features of the target domain and the shared label space between the two domains. First, a new deep clustering network is constructed to extract the intrinsic features of the target domain, where these features are clustered several central areas based on their same attributive feature. Second, the novel adversarial DA network is designed to extract the invariant features to construct the sharing label space between the source and target domains. Third, the new pseudolabel technology is introduced to mark the target unlabeled data by fusing the invariant feature of the target domain with the sharing label space and eliminate the negative knowledge transfer. Finally, these marked labels combining the intrinsic feature of the target domain are used to train the fault diagnosis classifier, where this realizes a well-prediction model for the target domain. Several transfer tasks on two rolling bearing datasets demonstrate the efficiency of the proposed method. The proposed transfer technology realizes the accuracy prediction of rolling bearing state on target unlabeled samples. Moreover, the efficiency of the method is better than the contrasting method, and this new diagnostic technology offers a promising fault diagnosis tool under some practical industrial problem.
Job Satisfaction and OrganisationalCommitment of Academic Staff inKyambogo University, Uganda

commitment of full-time academic staff of Kyambogo University, Uganda. Specifically, the study examined the influence of intrinsic and extrinsic job satisfaction on organisational commitment of full-time academic staff. Basing on the conceptualisation by Allen and Meyer (1990), organisational commitment was studied in terms of affective, continuance and normative commitment. Using the quantitative approach for inferential analysis, the study adopted the cross-sectional research design on a sample of 175 fulltime academic staff. The researcher used a self-administered questionnaire to collect the data. Data analysis involved carrying out structural equation modelling (SEM) using SmartPLS. The results indicated that while intrinsic job satisfaction positively and significantly influenced organisational commitment among full-time academic staff, extrinsic job satisfaction had a negative and insignificant influence on their organisational commitment. The study concluded that while intrinsic job satisfaction is imperative for organisational commitment of academic staff, extrinsic job satisfaction did not. Therefore, it was recommended that to boost academic staff members’ organisational commitment, university managers should promote their intrinsic satisfaction more than extrinsic job satisfaction.
Comparative Study on Ginger Powder and Ginger Extract Nanoparticles: Effects on Growth, Immune–Antioxidant Status, Tissue Histoarchitecture, and Resistance to Aeromonas hydrophila and Pseudomonas putida Infection in Oreochromis niloticus

A 10 week feeding trial was conducted to evaluate the potential effects of ginger powder (GP) and ginger extract nanoparticles (GNPs) on the growth parameters, digestive enzymes (lipase and amylase) activities, blood hematology, blood biochemical indices, immune indices (interleukin 10, immunoglobulin M, nitric oxide, and lysozymes), antioxidant activity, histological characteristics of kidney, spleen, liver, and intestine, and resistance to Aeromonas hydrophila or Pseudomonas putida infection in Nile tilapia, Oreochromis niloticus. Fish (n = 225, 27.01 ± 0.15 g) were stocked in 15 glass tanks (50 × 40 × 60 cm) and randomly allocated to five experimental treatments (TRTs) in triplicate (15 fish/replicate, 45 fish/TRT), consisting of five isocaloric–isonitrogenous diets. The treatments comprised the basal diet (1) without any additives (control group, CON), (2) with 0.5% GP (GP0.5), (3) with 1% GP (GP1), (4) with 0.5% GNPs (GNPs0.5), and (5) with 1% GNPs (GNPs1). Fish were manually fed to satiety three times a day (at 9 a.m., 12 p.m., and 2 p.m.). Fish were weighed at the start of the experiment, then the body weight, weight gain, feed intake, and feed conversion ratio were determined at the end of the experiment. At the end of the feeding period, 15 fish/TRT were intraperitoneally inoculated with two pathogenic bacterial strains (A. hydrophila or P. putida) in two separate challenge tests. Blood samples were collected from each TRT at two aliquots for hematological and biochemical analysis at the end of the feeding period. A significant improvement in fish growth was observed in GP and GNPs TRTs compared to the control group. There were no significant changes in the total amount of feed intake/fish in response to the experimental diets. Diets enriched with GNPs, particularly the GNPs1 TRT, resulted in a significant increase (p < 0.05) in digestive enzyme activity (lipase and amylase), serum growth hormone level, proteinogram, and immune indices (lysozyme, immunoglobulin M, interleukin 10, and nitric oxide). In addition, a significant increase in hepatic antioxidant enzymes (superoxide dismutase, reduced glutathione, and catalase) was observed in fish fed with GNPs-enriched diets. Survival percentages following bacterial challenge were higher in GNPs1, followed by GP1 and GNPs0.5 TRTs. Normal histomorphology was found in liver, kidney, and spleen tissues in all experimental TRTs. We conclude that GP and GNPs could be included in Nile tilapia diets for promoting fish growth, immunity, antioxidant status, and disease resistance without harming organ functions. In particular, the most effective treatment was GNPs1.
A NEW LOW-COMPLEXITY ALGORITHM FOR THE PULSE TRANSIT TIME EVALUATION

The pulse transit time (PTT) is a physiological parameter commonly derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) signal. It is defined as the time taken for the arterial pulse to travel from the heart to a peripheral site, and can be used as a direct indicator of Cardiovascular Diseases (CVD). In this study, we propose a new low-complexity algorithm for the (PTT) estimation. The (PTT) is calculated as the interval between the peak of the ECG R-wave and a time point on the PPG. We considered a dataset of 37 subjects containing a simultaneous recording of the (ECG) and the (PPG). The computation of the (PTT) consists of detecting the peak and foot points of a (PPG) and the R peak of the (ECG) signal. Our algorithm is improved by a temporal analysis by windowing. The results obtained are promising. The average sensitivity (SEN) and accuracy (ACC) obtained are respectively (97.5%, and 96.82%) for the detection of R peaks and (97.77%, and 97.64%) for the detection of PPG peaks. The sensitivity (SEN) and accuracy (ACC) of the foot (PPG) detection were 98.33% and 94.14%.
Comparison of Dental Images Based on Morphology and Appearance of Teeth

Computers are used in dentistry to recognize teeth, cavities, filled teeth, crowns, dental therapy, and digital smile design (DSD). use the intelligent algorithm K-Mean with Euclidean distance in two stages of the stage classification process. The first was to determine the type of tooth based on its location and size in order to select the central incisor teeth to the next classification process, through which the tooth type was determined based on the lower angles of the tooth This study classified teeth based on their incisal surfaces. Rounds, squares, squares/rounds. LORIN showed tooth outlines. In this investigation, we used extracted denture central incisors. Savitzky-Golay-Filter and morphology processes followed. Central incisor test showed the most consistent results after removing 75% or 66% of the tooth’s crown, with a detection accuracy of 85.7%. Dentures were classified using dentists’ input (dentists). the study validated the detection’s reliability.
A priori error estimates of a finite‐element method for an isothermal phase‐field model related to the solidification process of a binary alloy

We introduce a piecewise linear finite-element scheme with semi-implicit time discretization for an evolutionary phase field system modelling the isothermal solidification process of a binary alloy. This system can be written in a vectorial form as a nonlinear parabolic system. The convergence of the scheme with error estimate is then proved by introducing a generalized vectorial elliptic projector.
A Study on High-Frequency Transformer Design With Different Core Configurations for Flyback Converter Topology

The rapid advancements in the switched mode regulator technology necessitate an effective magnetic circuit for the converter topology. The design of magnetics plays a vital role in achieving the essential requirements of switching regulator circuits such as high-power density level, low thermal dissipation and high efficiency. Hence, this paper is focused on the high-frequency practical transformer design for flyback topology that is most widely used in the switched mode power supplies units. A case study is performed by employing different core configuration for high frequency flyback transformer which is the main contribution of this paper. The comparative performance analysis in terms of the dimensions, losses incurred and efficiency is reported for selecting the proper choice of core for the flyback topology.
Online newspapers and banner Ads

Rapid growth in online advertising revenues indicates that World Wide Web advertising is viable as an alternative to traditional media. In this new environment, academics and practitioners acknowledge the importance of establishing credibility and providing informative information in commercials. The current study analyzes the effectiveness of banner advertising and examines the impacts of (1) advertiser credibility and (2) informative advertisement on consumer attitudes toward advertisements and brands advertised on the online newspaper website detik.com. A survey of 104 respondents aged 16-35 was conducted using self-administered structured questionnaires. Structural equation modeling was then used to test and refine a model representing correlated relationships among the variables. The findings implied that advertiser credibility and the substance of informative advertising influenced attitudes toward advertising, whereas attitudes toward brands were affected by all variables investigated. For business practitioners, this study suggested that to improve customer attitudes toward advertisements and brands advertised; advertisers should assess the credibility and information delivered in advertisements.
Affective Surveillance Management in Virtual Emotion Based Smart Complex Infrastructure

Affective computing has evolved substantially thanks to recent great advances for numerous applications including emotion sensing, human interactions, emotion-enabled communications, eHealth, metaverse. Also, it is highly anticipated that such an evolved affective computing and its technology can be applied to secure surveillance based on virtual emotion detection in advanced smart cities. In this article, we design an energy-aware affective surveillance management system for virtual emotion based smart complex architecture. With an affective surveillance perspective in smart complex environment with multi levels of ground and underground, the proposed system basically provides low resource affective surveillance which is formed by various system components such as IoT devices, mobile robots and smart UAVs. Then, we present a formal representation of the problem that is to minimize the number of non-working affective components. Three different approaches are developed to resolve the problem as well as their performances are evaluated through extensive experiments. Besides, the open research issues are presented for new research branch of affective surveillance.
A Novel Single-Stage AC/DC Converter Integrated Interleaved DCM Boost PFC and LLC DC–DC With Reduced Bus Voltage

Due to the applied pulse frequency modulation control and switch integration, single-stage boost-LLC ac/dc converters suffer from high bus voltage, which makes them difficult to operate for high voltage input. To solve this issue, a novel single-stage ac/dc converter by incorporating the interleaved discontinuous conduction mode (DCM) boost cell and an LLC cell is proposed. Different from the existing topology, in the proposed converter, two capacitors employed for splitting the ac input voltage into two parts are placed before the rectifier bridge. Thus, the voltage across each power factor correction (PFC) cell is halved and the bus voltage can be significantly reduced. Furthermore, two high-frequency diodes and one filter capacitor are omitted, which helps improve the zero-crossing distortion of the input current. More importantly, the circuit efficiency is thus increased. Hence, low bus voltage, low component count, and high efficiency are the main advantages of the proposed converter. Simulations and experimental results are presented to prove the aforementioned features of the proposed converter.
Parameter multi‐domain ‘hp’ empirical interpolation

In this paper, we introduce two parameter multi‐domain ‘ hp’ techniques for the empirical interpolation method (EIM). In both approaches, we construct a partition of the original parameter domain into parameter subdomains: h‐refinement. We apply the standard EIM independently within each subdomain to yield local (in parameter) approximation spaces: p‐refinement. Further, for a particularly simple case, we introduce a priori convergence theory for the partition procedure. We show through two numerical examples that our approaches provide significant reduction in the EIM approximation space dimension and thus significantly reduce the computational cost associated with EIM approximations. Copyright © 2012 John Wiley & Sons, Ltd.
A Physical Unclonable Function Leveraging Hot Carrier Injection Aging

Physical Unclonable Functions (PUFs) are low-cost cryptographic primitives used to generate unique, secure, and stable IDs for device authentication and secure communication. PUFs rely on process variation inherent in the manufacturing flow making it impossible to predict or clone chip IDs providing a high level of security and tamper resistance. A commonly studied PUF is the memory PUF which suffers high Bit Error Rate (BER) across environmental conditions. This paper introduces a novel NFET PUF featuring a Hot Carrier Injection (HCI) stress mechanism to lower BER to near zero. Post-Si data from a lkb PUF array fabricated in Intel4 FinFET technology is presented in comparison to a hybrid-SRAM style PUF. BER results were studied with different stress parameters enabling manufacturing flow for HCI based PUFs.
Who is cooperative in negotiations? The impact of political skill on cooperation, reputation and outcomes

Purpose The purpose of this study is to predict cooperation in negotiation through the lens of individual differences. Specifically, this paper examines how a social competence variable called “political skill” relates to cooperation and subsequent effects on negotiation process, outcomes and negotiator reputation. The authors demonstrate how political skill fits in the evolving literature focusing on individual differences in negotiation by comparing political skill to a wide range of other individual difference measures. Design/methodology/approach This study was conducted by assessing individual difference measures at the beginning of graduate-level negotiation courses and tracking negotiation behaviors and outcomes over several months. This approach was chosen to minimize the potential for short, time-limited interactions to mask existing relationships. It also allowed the authors to include multiple negotiation interactions, which takes a broader view of negotiation performance, and assess negotiator reputation by allowing it to emerge over time. Findings The results of this study show that political skill, self-rated at the beginning of this study, is significantly related to a negotiator’s overall use of cooperative behavior as rated by peers. Political skill also showed a significant relationship with reputation for cooperativeness and aggregate outcomes in negotiations. These results control for other individual difference measures such as personality, implicit negotiation beliefs, social value orientation and negotiation self-efficacy. Originality/value Using a method that allows the effects of an individual difference to materialize over time, this study empirically establishes the connection between political skill and negotiation reputation, process and outcomes. The methodological contributions of this study explore the relations between self-rated individual difference variables, peer-rated cooperative behaviors and objective coded negotiation outcomes in evaluating political skill in negotiation.
Modeling of NBTI Induced Threshold Voltage Shift Based on Activation Energy Maps Under Consideration of Variability

One of the major challenges for modeling BTI degradation in modern technology nodes and deeply scaled transistors is the occurrence of significant time dependent variability (TDV). This means that due to the sparsity of defects, the impact of single defects as well as variation in the number of defects per device need to be taken into consideration. We present a modeling approach based on physical principles to describe both mean parameter degradation as well as TDV. Our approach is based on activation energy maps combined with an exponential-Poisson model in order to capture variability. For parameter extraction a combination of ultra fast measurements on large area transistors and transistor array measurements are applied. Thereby, ultra fast measurements have the capability to make a wide range of capture-/emission times experimentally accessible, improving the confidence of the extracted activation energy map. On the other hand, transistor arrays have proven to be the ideal test vehicle to efficiently measure an ensemble of transistors and to asses TDV.
The Design of Optimized RISC Processor for Edge Artificial Intelligence Based on Custom Instruction Set Extension

Edge computing is becoming increasingly popular in artificial intelligence (AI) application development due to the benefits of local execution. One widely used approach to overcome hardware limitations in edge computing is heterogeneous computing, which combines a general-purpose processor with a domain-specific AI processor. However, this approach can be inefficient due to the communication overhead resulting from the complex communication protocol. To avoid communication overhead, the concept of an application-specific instruction set processor based on customizable instruction set architecture (ISA) has emerged. By integrating the AI processor into the processor core, on-chip communication replaces the complex communication protocol. Further, custom instruction set extension (ISE) reduces the number of instructions needed to execute AI applications. In this paper, we propose a uniprocessor system architecture for lightweight AI systems. First, we define the custom ISE to integrate the AI processor and GPP into a single processor, minimizing communication overhead. Next, we designed the processor based on the integrated core architecture, including the base core and the AI core, and implemented the processor on an FPGA. Finally, we evaluated the proposed architecture through simulation and implementation of the processor. The results show that the designed processor consumed 6.62% more lookup tables and 74% fewer flip-flops while achieving up to 193.88 times enhanced throughput performance and 52.75 times the energy efficiency compared to the previous system.