Miracle-dz/UniFAR-FTUs huggingface dataset:
ZSL-SLCNN: Zero-Shot Learning with Semantic Label CNN for Malware Classification

Malware is becoming increasingly sophisticated, with new malware constantly emerging, posing challenges for cybersecurity teams to classify them accurately. Traditional supervised learning methods have achieved impressive results recently, thanks to the contributions of various novel techniques and models. However, a notable drawback of this approach is its inability to classify malicious code it has never encountered, in other words, with untrained labels. Zero-shot Learning has been explored in diverse fields to address this limitation, but its performance still needs to improve. Notably, most current studies only focus on one-layer mapping, with few outstanding achievements, and studies using zero-shot learning in malware classification need to be improved. In this paper, we propose a novel method utilizing Semantic Labels with two-layer mapping to enhance the efficiency of traditional Zero-Shot Learning. This study explores how zero-shot learning can be leveraged to detect image-based malware using merely simple CNN and pre-trained word embedding as semantic labels. Through experimental results, we demonstrate the effectiveness of our proposed method for classifying both seen and unseen malware families.
CNTFET-based Approximate Ternary Adder Design

Multiple-Valued Logic (MVL) offers better data representation allowing higher information processing within the same amount of digits. With a trade-off in accuracy, approximate computation is a method to improve the power, size, and speed of digital circuits. This paper presents the design of CNTFET-based ternary half adder, full adder, 2-trit carry ripple adder, and 4trit carry ripple adder with different accuracies. The proposed designs are implemented using HSPICE tool and simulated for power consumption, delay, and error analysis. The trade-off between the transistor count and the computation accuracy of the propsoed designs is discussed. Simulation results show that the approximate and corrected approximate designs could significantly improve power-delay product and transistor count compared to their accurate designs. For some cases, approximate and corrected approximate designs have up to $19.8 \times$ improvement in the transistors count and up to $295.3 \times$ improvement in PDP compared to their accurate designs. The corrected designs outperform the approximate ones in terms of accuracy while achieving around $1.5 \times$ improvement in AED.
The extensional geodynamic setting of Early Cretaceous granitic intrusions in the Eastern North China Craton: Evidence front laser ablation Ar-40/Ar-39 dating of K-bearing minerals

Early Cretaceous Gudaoling batholith,distributed in the Liaodong Peninsula,eastern North China Craton,is composed by three types of grantoids,deformed diorite at Miaoling,gnessie granodiorite at Wanjialing,medium-grained monzogranite and enclave at Gudaoling.The diorite and granodiorites have evidently gnessis structures,indicating that they had experienced ductile deformation. The directions of foliations and lineations are accordant with those of host mylonites at the lower plate of a normal fault,suggesting that the Gudaoling batholith is a syn-tectonic intrusion.Laser ablation ~(4o)Ar/~(39)Ar dating of K-bearing minerals (hornblende,biotite and K- feldspar) from each type of granitoid and mylonites gives a result that Gudaoling batholith and its host mylonites had experienced a deformation and metamorphism event during Early Cretaceous (120～113 Ma),showing a rapid cooling and exhumation history. This event in the Liaodong Peninsula,as well as east North China Craton are consistent with the timing of formation of pull-apart basins and metamorphic core complexes,large-scale gold mineralization and A-type granitic intrusions in the eastern North China Craton, which are shallow crustal response of destruction and lithospheric removal of east North China Craton.
Comportement agronomique et résistance aux principaux déprédateurs des lignées de Sarchimor et Catimor au Costa Rica

Vingt-sept lignees de Catimor et Sarchimor, provenant des trois origines de l'Hybride de Timor sont comparees aux lignees commerciales Catuai et Caturra, dans deux essais de la station de CICAFE du Costa Rica (1200 m d'altitude ). Les comparaisons portent sur la productivite, la granulometrie, la circonference du tronc, les loges rides et caracolis, l'incidence de la rouille orangee et des nematodes (Meloidogyne exigua et Pratylenchus Sp.), la resistance vis-a-vis du CBD (Colletotrichum kahawae). Les resultats indiquent des differences significatives entre les lignees de Catimor et Sarchimor pour tous les caracteres observes et confirment la valeur de ces lignees issues de l'Hybride de Timor, pour la selection de lignees productives et resistantes a la rouille orangee, au CBD et a M. exigua.
Concealed Object Detection Based on Wavelet Convolution for Millimeter Wave Image

The detection of concealed objects in millimeter- wave (MMW) images has garnered considerable attention due to its non-contact and non-invasive nature, setting it apart from traditional security inspection methods. Nonetheless, the low image resolution inherent in this technology poses challenges in detecting small targets effectively. This research endeavors to address these limitations in the context of detecting safety- hazard objects carried by miners, who wear thick overalls, thus presenting a more complex detection scenario. To surmount these challenges, we propose a novel enhancement technique that leverages wavelet transform to augment existing detectors. The introduced approach, termed Wavelet-Conv, is integrated into the YOLOv8 architecture for enhanced detection performance. To ensure comprehensive evaluation, we meticulously curated a dedicated dataset with diverse instances of concealed objects and conducted extensive experiments to evaluate the proposed model. Results substantiate the efficacy of our method, as it significantly improves recall and mean average precision (mAP) in concealed object detection within MMW images, surpassing the performance of existing state-of-the-art methods.
Comparison of DTC-Related Spurs in Fractional-N Digital PLLs with MASH-and-ENOP-based Divider Controllers

Fractional$- N$ digital phase locked loops (DPLL’s) typically use a digital-to-time converter (DTC) to cancel the quantization error (QE) produced by the divider controller that is typically a digital $\Delta- \Sigma$ modulator (DDSM). In practice, the nonlinear transfer characteristic of the DTC interacting with the accumulated QE of a conventional Multi-stAge noiSe-sHaping (MASH) DDSM causes fractional spurs which deteriorate the system’s output phase noise performance. The Enhanced Nonlinearity-induced nOise Performance (ENOP) DDSM exhibits fractional-spur immunity when interacting with nonlinearities that can be modeled by polynomial functions. This paper compares the generation of fractional spurs when using MASH and ENOP DDSMs respectively. The application of the latter in a DPLL is shown to successfully mitigate the fractional spurs. Block and system level behavioral simulations underpin our observations.
Edge Termination Design Considerations for 1.2kV 4H-SiC MOSFETs While Utilizing Room Temperature Ion Implantations

Several 1.2kV-rated 4H-SiC MOSFETs were fabricated with various edge termination (ET) structures to investigate the effects of both Junction Termination Extension (JTE) based and P+ ring-based ETs, which were implanted at room temperature (RT). The study revealed that JTE-based ETs exhibited reduced generation of Basal Plane Dislocations (BPD) and consequently suppressed leakage currents when the P+ dose exceeded the previously established RT critical aluminum dose of 1x1015 cm-2. In contrast, the P+ ring-based termination structures led to elevated leakage currents, even in the absence of BPDs within RT-implanted devices. Consequently, when producing devices using RT ion implantation, JTE-based ETs proved to be the ideal choice.
Sense Model of Illness Cognition

The Revised Illness Perception Questionnaire (IPQ-R) has been shown to assess illness perception reproducibly in primary cutaneous T-cell lymphomas (CTCL). Illness perception reflects patients’ individual concepts of understanding and interpretation of the disease, influencing illness behaviour and health-related quality of life (HRQOL). This study investigated the clinical relevance of the relationships between illness perception, illness behaviour, and HRQOL in CTCL and cutaneous B-cell lymphomas (CBCL). A total of 92 patients completed the IPQ-R, the Scale for the Assessment of Illness Behavior (SAIB), and a skin-specific HRQOL tool (Skindex-29). Data on illness behaviour were not evidently related to illness perception, whereas illness perception was significantly associated with HRQOL. Both, IPQ-R and HRQOL results correlated with disease entity, stage, and socio-demographics. Only IPQ-R re-sults provided practical information on patients’ needs to train personal coping strategies. IPQ-R assessment in CTCL and CBCL might be a useful instrument to improve individual disease management.
Game-based Analytical Skills Testing for Graduate Software Engineering Recruitment

Game-based recruitment is an emerging trend adopted by organizations globally, given its proven results in boosting candidate perceptions of the company and providing an improved recruitment experience. This paper explores the use of game-based analytical skill testing in the recruitment process of entry-level graduate software engineers in Sri Lanka. The Test of Logical Thinking by Tobin and Capie has been used as a reference, and a game-based version has been developed using the MDA framework, relying on mechanics, dynamics, and aesthetics. The testing phase has been carried out using a focus group of eight fresh graduate software engineering recruits, and the results have depicted a significantly high level of accuracy between the results produced through the paper-based and game-based versions. Candidate perceptions of the recruitment process and the employer have been recorded to be positively influenced by the introduction of game-based testing in the recruitment process.
Implications for culture contact history from a glass artefact on a Diingwulung earth mound in Weipa

This paper reports on a glass artefact found on an earth mound at Diingwulung in Wathayn Country, near Weipa, far north Queensland. Despite intense research efforts and cultural heritage management surveys over many years, and the fact that they have been reported commonly within the ethnographic literature, such artefacts have been found rarely outside of Aboriginal mission contexts. As well as describing the artefact, its location and the frontier contact complex of the area, this paper includes the background of knapped glass artefacts in Australia, archaeological and ethnographic descriptions of Indigenous glass use in far north Queensland and the methodology of glass artefact analysis. Although it is only a single artefact, we argue that this glass piece has much to reveal not only regarding its chronology, use, and the function of the site where it was found, but also about culture contact, persistence of traditional technology, connections to Country and the continuity and extent of post-contact Indigenous occupation of the area.
Transport mode recognition for smart eyewear using multimodal audio and accelerometer data

Wearable devices have enabled a wide range of sensing applications, including activity recognition such as walking, cycling, or running, among others. Despite the substantial advances in the research field of human activity recognition (HAR), the recognition of complex activities such as transportation modes (TM) requires more investigation. In this paper, we present a sound-accelerometer-based approach for transport mode detection through a wearable instrumented frame. Our experimental results demonstrate the robustness of the multimodal strategies compared to the monomodal ones that only rely on the accelerometer or sound data. Furthermore, we assessed the resource memory requirements of our proposed multimodal strategies to consider their integration within a microcontroller unit (MCU) for real-time detection.
Parenting and Adolescent Adjustment in Asian-Russian Cultural Contexts: How Different is it from the West?

The study is based on unique comparative data about the family life of 15-year-olds (n = 1,539) from the Asian region of the Russian Federation. The study asks: what forms do parent-adolescent relations take in the AsianRussian cultural context, and which of those approaches support adolescent adjustment? The study separates the accounts of urban, ethnic Russian adolescents in the region’s largest city, Novosibirsk; their rural, ethnic Russian counterparts in Novosibirsk Oblast; ethnic Russian and Buriiat adolescents in Ulan-Ude, capital city of the Republic of Buriiatia; and ethnic Russian and Altay adolescents in the rural Republic of Altai. Results make allowance for 15 yearolds’ differing family make-up and socio-economic circumstances. The study finds parenting patterns are differentiated by location and ethnicity, including a permissive pattern as the norm in urban Novosibirsk, and an indigenous traditional pattern among rural Altay families. Indulgent or democratic parent-adolescent relations – represented by reports of responsive parenting combined with low-to-moderate control – appear to promote adolescent self-worth and psychological health. Authoritarian parenting – reports of unresponsive parenting with high behavioural control – appear detrimental to adolescent mental health. Those findings are more akin to what is found in Western European societies rather than Anglo-Saxon contexts in the United States and United Kingdom. The study also finds no evidence to support the notion that a strict collectivist-hierarchical parenting pattern benefits Asian-Russian adolescents, in the way the latter pattern is reported to benefit East Asian adolescents.
The Age of Indulgence: An Online Impulsive and Compulsive Buying Analysis

With the rapid growth and emergence of e-commerce in Indonesia, which offers easy access to an unlimited range of product customers, online impulse buying and online compulsive buying are on the rise, with the trend of self-indulging and rewarding oneself or having a lack of self-control surrounding consumer intention to buy online impulsively and compulsively. Drawing from the theory of planned behavior and construal level theory, the present study examined how lack of self-control and self-indulgence affect online impulsive and compulsive buying. Empirical evidence was collected from 174 users who have used Shopee, the largest e-commerce platform in Southeast Asia. The results of structural equation modeling revealed that lack of self-control and self-indulgence significantly influence consumer intention to buy online impulsively and compulsively. The findings show that self-indulgence is the stronger variable in affecting consumer intention to both impulsively and compulsively buy online. This current study contributes to previous findings by addressing the impact of other variables (lack of self-control and self-indulgence) on online compulsive and impulsive buying. This research suggests that managers implement impulsive and compulsive marketing tactics through the learning of consumer behavior (self-indulgence and lack of self-control) that is aligned with ethical values to attract consumers and gain sales.
New Energy-Efficient 3-2 and 4-2 Approximate Adder Compressors Topologies

Addition units are present across many computational kernels inherent in various error-tolerant applications, including machine learning, signal, image, and video processing. Notably, adder compressors are the target when high speed and low power are the main design concerns. This work introduces energy-efficient structures of 3-2 approximate adder compressors (Ax3-2) and three distinct versions of 4-2 approximate adder compressors (Ax4-2). We compared our proposed Ax3-2 and Ax4-2 compressors with state-of-the-art energy-efficient approximate adder compressors (AxACs). Both Ax3-2 and Ax4-2 models passed through rigorous tests as standalone units. Furthermore, we integrated the Ax4-2 models into an essential application kernel appearing in video coding, i.e., the Sum Squared Differences (SSD) video accelerator. We introduce Ax3-2 and Ax4-2 that yield a new Pareto front concerning both energy-quality and area-quality trade-offs, thereby demonstrating a marked improvement over the prevailing state-of-the-art energy-efficient AxACs.
GRU for Overcoming Seasonality and Trend in PM2.5 Air Pollution Forecasting

Pollution forecasting is important to research, especially for hazardous particles like PM2.5. However, trends and seasonality that can hide in the dataset make the forecasting model’s performance unfavorable. Our research aims to design a forecasting model methodology that involves trend and seasonality analysis using the seasonal decomposition of time series by Loess (STL). We obtained the PM2.5 concentration dataset from Kaggle. The next step is applying the STL to analyze trends and seasonal components in datasets. Then we compared three forecasting models: gated recurrent unit (GRU), long short-term memory (LSTM), and one-dimensional convolutional LSTM (1D Conv-LSTM). We use the mean absolute error (MAE) for model performance comparisons. The STL test results show a trend component in the dataset that can influence forecasting performances. GRU exhibits a better MAE than LSTM, 1D ConvLSTM, and two state-of-the-art method: Stacked LSTM and BiLSTM. GRU’s MAE score is 13.9. We conclude that GRU is a lightweight solution that can overcome trends and seasonality in PM2.5 datasets.
Modified Switching PWM Method to Reduce the THD and Power Loss of NPC Inverters

Minimizing total harmonic distortion (THD) and mitigating switching power loss because of high frequency switching in a solar photovoltaic (PV) fed multilevel inverter (MLI) based grid-tied system is always considered as a research challenge. The THD and power loss of MLI determine the power quality of MLI which are influenced by the pulse width modulation (PWM) method. Yet, conventional PWM techniques for multilevel inverters (MLI) encounter challenges concerning increased total harmonic distortion (THD) and power loss issues. This research endeavor introduces a novel level shifted carrier-based PWM approach to mitigate total harmonic distortion (THD) and minimize power loss in neutral point clamped (NPC) inverters. Apart from these, thermal analysis results for the proposed PWM method are provided in this work. The proposed PWM method is tested in an NPC inverter-based grid-tied PV system. The system is modeled and simulated in MATLAB/Simulink and PLECS software platforms as well as reduced scale experimental test is also conducted to validate the simulation analysis.
Exploring Customer-based Determinants of Social Media Marketing Activities for Local Brands: Evidence from Indonesia

The effective promotion of local brands managed by mostly small and medium-sized enterprises (SMEs) in a highly competitive market remains a challenge, highlighting the urgent need for social media marketing activities (SMMA) to enhance reach and reduce costs. Unfortunately, the development of SMMA has not reached its full potential, and there is a lack of studies focusing on the determinants of SMMA for SMEs. Therefore, this study aims to investigate the factors influencing SMMA for local brands from a customer perspective. We conducted a survey involving 403 active customers in Indonesia who engage with local brands on social media. The data were analyzed using an exploratory factor analysis (EFA) approach. This study identifies (a) precision information delivery and (b) trendiness as essential factors determining SMMA. This research contributes novel insights to the SMMA literature, particularly in the context of promoting local brands, by introducing a more manageable dimension of SMMA.
Decode-and-Forward Based Cooperative MIMO System using Deep Learning for Wireless Body Area Networks

In this article, we introduce a Decode-and-Forward (DF) based cooperative Multiple-Input Multiple-Output (MIMO) system using autoencoder (AE) technique, abbreviated as AE-DF, for Wireless Body Area Network (WBAN). In our scheme, the source, relay, and destination nodes are designed using neural networks, forming an AE. The learning parameters of the AE are trained synchronously through two sequential phases, allowing for optimal synchronization of the entire system. Additionally, in order to effectively reduce co-channel interference (CCI) in the received signal streams and enhance the bit error rate (BER) performance of the AE-DF system, we introduce the Minimum Mean Square Error Network (MMSEnet) detector employing deep learning at the relay and destination node. We assess the performance of these systems in scenarios with perfect channel state information (CSI) and imperfect CSI. The simulation results demonstrate that our system significantly outperforms the baseline system which is the conventional DF-based cooperative MIMO system using Minimum Mean Square Error (MMSE) detector.
Dominance of grain size impacts on seasonal snow albedo at open sites in New Hampshire

Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near‐daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single‐Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land‐based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate.
A Novel Efficient Hardware Implementation of Symbol Timing and Carrier Phase Synchronizer for QPSK Receivers

This paper presents an effective hardware design for symbol timing and carrier phase synchronizer in a QPSK SDR receiver intended for implementation on an FPGA. The joint synchronization model is meticulously constructed based on previously established theories. We have made several improvements to the carrier phase synchronizer to enhance its performance. The functionality of the joint synchronizer is initially tested through MATLAB simulations. Subsequently, we perform hardware design, optimizing and accelerating it to achieve high clock speeds and efficient resource utilization. Finally, we implement the hardware design on an FPGA device, specifically the Xilinx XC7A35T, and verify its performance with an actual QPSK signal under cable transmission conditions, including attenuation and frequency offset. The verification results demonstrate that our synchronizer functions properly, even when the signal is attenuated and subject to a frequency offset of up to 0.8% of the symbol rate.