Miracle-dz/UniFAR-FTUs huggingface dataset:
Maize Disease Recognition Based On Image Enhancement And OSCRNet

Background: Under natural light irradiation, there are significant challenges in the identification of maize leaf diseases because of the difficulties in extracting lesion features from constantly changing environments, uneven illumination reflection of the incident light source and many other factors.Results: In the present paper, a novel maize image recognition method was proposed. Firstly, an image enhancement framework of the maize leaf was designed, and a multi-scale image enhancement algorithm with color restoration was established to enhance the characteristics of the maize leaf in a complex environment and to solve the problems of high noise and blur of maize images. Subsequently, an OSCRNet maize leaf recognition network model based on the traditional ResNet backbone architecture was designed. In the OSCRNet maize leaf recognition network model, an octave convolution with characteristics to accelerate network training was adopted, reducing unnecessary redundant spatial information in the maize leaf images. Additionally, a self-calibrated convolution with multi-scale features was employed to realize the interactions of different feature information in the maize leaf images, enhance feature extraction, and solve the problems of similarity of maize disease features and easy learning disorders. Concurrently, batch normalization was employed to prevent network overfitting and enhance the robustness of the model. The experiment was conducted on the maize leaf image data set. The highest identification accuracy of rust, grey leaf disease, northern fusarium wilt, and healthy maize was 94.67%, 92.34%, 89.31% and 96.63%, respectively. Conclusions: The aforementioned methods were beneficial in solving the problems of slow efficiency, low accuracy and image recognition training, and also outperformed other comparison models. The present method demonstrates strong robustness for maize disease images collected in the natural environment, providing a reference for the intelligent diagnosis of other plant leaf diseases.
Multi-Criteria Decision Making Model for Application Maintenance Offshoring Using Analytic Hierarchy Process

The phenomenon of Global Software Development (GSD) has attracted the interest of businesses all over the world. It brings together partners from various national and corporate cultures to develop applications with numerous advantages, including access to a vast labor pool, cost savings, and round the clock growth. GSD, on the other hand, is technologically and organizationally diverse and poses a number of obstacles for the development team, such as geographical distance, cultural differences, communication and language barriers. Global services are provided by selecting one of the suitable global delivery options, i.e., the onshore model, nearshore model or offshore model. Experts typically choose one of the models based on the nature of the project and the needs of the customer. However, the vendors and clients lack an adequate decision support system that can assist them in making suitable sourcing decisions. Therefore, the current study presents a Multi-Criteria Decision Making (MCDM) model for offshore outsourcing decisions of application maintenance. To achieve our target, two systematic literature reviews were conducted that explored a list of 15 influencing factors. The identified factors were further evaluated in the outsourcing industry by performing an empirical study that resulted in a list of 10 critical success factors. We propose a sourcing framework based on the critical success factors that can assist decision makers in adopting a suitable sourcing strategy for the offshore outsourcing of application maintenance. In order to further enhance the decision-making process, the MCDM model is developed based on the Analytic Hierarchy Process (AHP). The MCDM model is evaluated with three case studies in highly reputable international companies, including IBM Stockholm, Sweden, Vattenfall AB, Stockholm, Sweden and a London based company in the United Kingdom. The outcomes of these case studies are further reviewed and validated by the outsourcing specialists in other firms. The proposed model is used as a decision support system that determines the ranking of sourcing alternatives and suggests the most suitable option for application maintenance offshoring.
How do 3-year-olds use relevance inferencing to interpret indirect speech?

If a child asks a friend to play football and the friend replies, ‘I have a cough’, the requesting child must make a ‘relevance inference’ to determine the communicative intent. Relevance inferencing is a key component of pragmatics, that is, the ability to integrate social context into language interpretation and use. We tested which cognitive skills relate to relevance inferencing. In addition, we asked whether children’s lab-based pragmatic performance relates to children’s parent-assessed pragmatic language skills. We tested 3.5- to 4-year-old speakers of British English (Study 1: N = 40, Study 2: N = 32). Children were presented with video-recorded vignettes ending with an utterance requiring a relevance inference, for which children made a forced choice. Study 1 measured children’s Theory of Mind, their sentence comprehension and their real-world knowledge and found that only real-world knowledge retained significance in a regression analysis with children’s relevance inferencing as the outcome variable. Study 2 then manipulated children’s world-knowledge through priming but found this did not improve children’s performance on the relevance inferencing task. Study 2 did, however, reveal a significant correlation between children’s relevance inferencing and a measure of morpho-syntactic production. In both studies parents rated their children’s pragmatic language usage in daily life, which was found to relate to performance in our lab-based relevance inferencing task. This set of studies is the first to empirically demonstrate that lab-based measures of relevance inferencing are reflective of children’s pragmatic abilities ‘in the wild’. There was no clear association between relevance inferencing and Theory of Mind. There was mixed evidence for the role of formal language, which should be further investigated. Finally, real-world knowledge was indeed associated with relevance inferencing but future experimental work is required to test causal relations.
A Secure Biometric Key Generation Mechanism via Deep Learning and Its Application

Biometric keys are widely used in the digital identity system due to the inherent uniqueness of biometrics. However, existing biometric key generation methods may expose biometric data, which will cause users’ biometric traits to be permanently unavailable in the secure authentication system. To enhance its security and privacy, we propose a secure biometric key generation method based on deep learning in this paper. Firstly, to prevent the information leakage of biometric data, we utilize random binary codes to represent biometric data and adopt a deep learning model to establish the relationship between biometric data and random binary code for each user. Secondly, to protect the privacy and guarantee the revocability of the biometric key, we add a random permutation operation to shuffle the elements of binary code and update a new biometric key. Thirdly, to further enhance the reliability and security of the biometric key, we construct a fuzzy commitment module to generate the helper data without revealing any biometric information during enrollment. Three benchmark datasets including ORL, Extended YaleB, and CMU-PIE are used for evaluation. The experiment results show our scheme achieves a genuine accept rate (GAR) higher than the state-of-the-art methods at a 1% false accept rate (FAR), and meanwhile satisfies the properties of revocability and randomness of biometric keys. The security analyses show that our model can effectively resist information leakage, cross-matching, and other attacks. Moreover, the proposed model is applied to a data encryption scenario in our local computer, which takes less than 0.5 s to complete the whole encryption and decryption at different key lengths.
HOW FASHION INFLUENCER CONTRIBUTES TO CONSUMERS’ PURCHASE INTENTION OF UNIVERSITY STUDENT

Fashion is receiving more attention these days since it has become a continual existence in a person’s everyday life, especially for the younger generation as it represents their identity. On the other hand, the dynamic competitive environment of marketing-led fashion brands to put in the excess effort to achieve effective marketing strategies. As social media grew, one of the most effective ways to do it is using influencers in the marketing campaign. Influencer marketing is becoming increasingly popular throughout the world, prompting marketers to consider it an essential component of their marketing strategy. This research determines the factors of fashion influencers that contribute to influencing purchase intention. The variables constructed include trustworthiness, expertise, similarity, likability, and familiarity. Further, consumer attitude is proposed to mediate between trustworthiness, expertise, similarity, likability, and familiarity to purchase intention. The research was conducted using a quantitative approach and analyzed using a regression method through IBM SPSS Statistics. From 234 qualified respondents, the results presented trustworthiness, similarity, familiarity, and likability significantly contribute to purchase intention, and consumers' attitudes towards influencers are proven to be mediate the relationships between independents variables and purchase intention. The findings of the study assist marketers and advertisers in the fashion industry in understanding the elements influencing consumer attitudes about fashion influencers and, as a result, better choose influencers capable of establishing purchase intentions in existing and potential customers.
PERAN INTELLECTUAL CAPITAL DALAM PENGARUH CORPORATE SOCIAL RESPONSIBILITY TERHADAP FINANCIAL PERFORMANCE

Tujuan penelitian ini untuk mengetahui pengaruh langsung dari corporate social responsibility (CSR) terhadap financial performance, serta pengaruh tidak langsung corporate social responsibility terhadap financial performance melalui intellectual capital sebagai variabel mediasi. Pengolahan data menggunakan software Smart PLS. Data penelitian ini berasal dari laporan tahunan masing-masing perusahaan yang tergolong subsektor bank dan terdaftar pada Bursa Efek Indonesia periode 2011-2018. Data kuantitatif sekunder tersebut dihitung menggunakan rumus Corporate Social Disclosure Index sebagai indikator CSR, Value Added Intellectual Coefficient (VAICTM) sebagai indikator intellectual capital, Tobin’s Q sebagai indikator financial performance. Hasil penelitian ini membuktikan adanya pengaruh positif dari corporate social responsibility terhadap financial performance, corporate social responsibility terhadap intellectual capital, dan intellectual capital terhadap financial performance.
Ethical Leadership as an Influence: A Multi-Level Analysis Predicting Citizenship Behavior

This study incorporates two different types of perspectives determining the factors influencing citizenship behavior. Social exchange perspective incorporates the interpersonal relations of leaders and followers, which are hamper through workplace ostracism. Social learning perspective considers an employee’s behavior to be influence by the ethical behavior of their leader. In order to study the impact of these diverse views on citizenship behavior, a multilevel model of ethical leadership is develop in order to determine the direct, indirect and cascading effects of workplace ostracism on either organizational or compulsive citizenship behavior. The study proposed that immediate level managers ethical leadership practices tend to have the greatest impact on the citizenship behavior of employees. In addition, if the immediate level manager adopts an ostracized behavior with its subordinates then it will lead to compulsive citizenship behavior. Besides this, higher-level manager’s ethical leadership practices also play a vital role in influencing citizenship behavior unlike lower level managers who have the least influential impact on middle level employees.
Differential Retrodirective Array With Integrated Circuits in Low-Cost 0.18 μm CMOS for Automatic Tracking

This communication presents a differential retrodirective array (RDA) for real-time tracking. The proposed differential RDA consists of three phase-conjugating chips and two circularly polarized antenna arrays. The phase-conjugating circuit chip, which is in $0.18~\mu \text{m}$ CMOS process, includes a differential low-noise amplifier, a double-balanced mixer, and a differential power amplifier. The specifically designed chip consumes 38.4 mW with a low voltage supply of 1.2 V. Experimental results of monostatic and bistatic cases show that the RDA has a 3 dB beamwidth up to 77°. To the best knowledge of the authors, the proposed RDA with circular polarization, which is promising for tracking free-moving targets, is the first differential RDA enabled by specifically designed low-cost CMOS chips.
Russian News Similarity Detection with SBERT: pre-training and fine-tuning

Computation of text similarity is one of the most challenging tasks in NLP as it implies understanding of semantics beyond the meaning of individual words (tokens). Due to the lack of labelled data this task is often accomplished by means of unsupervised methods such as clustering. Within the DE2021: “Russian News Clustering and Headline Selection” we propose a method of building robust text embeddings based on Sentence Transformers architecture, pretrained on a large dataset of in-domain data and then fine-tuned on a small dataset of paraphrases leveraging GlobalMultiheadPooling.
The effects of crosslinking agents on faba bean flour–chitosan‐curcumin films and their characterization

Although glutaraldehyde (GLU) has been frequently preferred to improve some characteristics of bio‐degradable food packages, it is regarded as a hazardous chemical. Therefore, in this study, the possibility of replacement GLU with citric acid (CA) a non‐toxic compound was questioned in a film formation. Different ratios of GLU and CA on faba bean flour, chitosan, and curcumin film were examined. To determine the most favorable film composition, water solubility (WS), swelling degree (SD), water contact angle (WCA), water vapor permeability (WVP), and mechanical properties of the films were examined. In addition, the effects of crosslinking agent and their ratios on crystallinity (XRD), thermal properties (DSC and TGA), and antioxidant activity (DPPH and ABTS) were also studied. Time Domain Nuclear Magnetic Resonance (TD‐ NMR) relaxometry was also employed to explain distribution and mobility of the protons in faba bean flour, chitosan, and curcumin films. At the end of the analysis, it was concluded that CA and GLU reduced SD by 75% and 13% compared to the films without cross‐linker, respectively. Incorporation of crosslinking agent increased the WCA from 77.22° to 99.41° and caused formation of more hydrophobic surfaces. Increasing both crosslinking ratios restricted the permeance drastically which was more than 110%. Furthermore, the lowest WVP was measured for the films containing CA at 1.5% w/v ratio (FC‐1.5C). While GLU improved the tensile strength (TS) of the film, lower elongation of the films caused formation of brittle character which limited the utilization of the films. At the end of the analysis, it was concluded that FC‐1.5 had more feasible character with respect to the other films and CA was suggested as a crosslinking agent instead of GLU for faba bean‐chitosan films.
The Nomological Net of Knowledge, Self-Reported Knowledge, and Overclaiming in Children

Abstract Research on self-reported knowledge and overclaiming in children is sparse. With the current study, we aim to close this gap by developing an overclaiming questionnaire measuring self-reported knowledge and overclaiming that is tailored to children. Moreover, we examine the nomological net of self-reported knowledge and overclaiming in childhood discussing three perspectives: Overclaiming as (a) a result of deliberate self-enhancement tendencies, (b) a proxy for declarative knowledge, and (c) an indicator of creative engagement. We juxtaposed overclaiming, as indicated by claiming familiarity with non-existent terms, and self-reported knowledge with fluid and crystallized intelligence, creativity, and personality traits in a sample of 897 children attending third grade. The results of several latent variable analyses were similar to findings known from adult samples: We found no strong evidence for any of the competing perspectives on overclaiming. Just like in adults, individual differences in self-reported knowledge were strongly inflated by overclaiming, and only weakly related to declarative knowledge.
Adsorptive performances of magnetic graphene oxide adsorbent for the removal of fluoroquinolones in the Langat River Basin, Malaysia

ABSTRACT The presence of pharmaceuticals in aquatic systems is a matter of great concern. As a result of their high solubility and low volatility, their removal has been very challenging. In this work, the synthesis, characterisation and adsorption study of graphene oxide-based magnetic nanoparticles (GO@Fe3O4) were explored for the removal of fluoroquinolones (FQs). GO@Fe3O4 adsorbent was synthesised by a one-step co-precipitation method using ammonium ferrous sulphate ((NH4)2FeSO4) and ferric chloride hexahydrate (FeCl3 · 6H2O) as iron sources and ammonium solution as precipitant. The removal of four FQs (ofloxacin, enrofloxacin, sparfloxacin. and gemifloxacin) by GO@Fe3O4 adsorbent was explored. The effect of contact time, initial pH of the solution, initial FQs concentration on the removal efficiency, and reusability were investigated. The pseudo-second-order kinetic model represented the adsorption process for GO@Fe3O4 adsorbent. The Freundlich isotherm model was a better fit with adsorption capacities of 44.4, 40.8, 64.0, and 51.8 mg/g for ofloxacin, enrofloxacin, sparfloxacin, and gemifloxacin, respectively. Under optimised conditions, GO@Fe3O4 adsorbent was successfully applied for the removal of FQs in water samples from the Langat River basin. The results showed enhanced sorption capacity and high removal efficiency towards for FQs removal from an aqueous solution and has the potential to be an alternative adsorbent.
Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

Currently, research on the development of crash models in terms of crash frequency on road segments and crash severity applies the principles of spatial analysis and heterogeneity due to the methods’ suitability compared with traditional models. This study focuses on crash severity and frequency in Thailand. Moreover, this study aims to understand crash frequency and fatality. The result of the intra-class correlation coefficient found that the spatial approach should analyze the data. The crash frequency model’s best fit is a spatial zero-inflated negative binomial model (SZINB). The results of the random parameters of SZINB are insignificant, except for the intercept. The crash frequency model’s significant variables include the length of the segment and average annual traffic volume for the fixed parameters. Conversely, the study finds that the best fit model of crash severity is a logistic regression with spatial correlations. The variances of random effect are significant such as the intersection, sideswipe crash, and head-on crash. Meanwhile, the fixed-effect variables significant to fatality risk include motorcycles, gender, non-use of safety equipment, and nighttime collision. The paper proposes a policy applicable to agencies responsible for driver training, law enforcement, and those involved in crash-reduction campaigns.
A Compact Dual-Band Quasi-Elliptic Filter Based on Hybrid SIW and Microstrip Technologies

In this brief, by combining substrate integrated waveguide (SIW) and microstrip technologies, a novel dual-band filter is proposed to achieve a quasi-elliptic response for both passbands. The dual-mode characteristics of the SIW cavities, namely TE101 and TE201 modes, are used to create two passbands. Different with the conventional inductive windows, two pairs of uniform impedance resonators (UIRs) with electric mutual coupling, which are etched between the two rectangular SIW cavities, are used to couple the TE101 and TE201 modes, respectively. Good merits are achieved in this way, including: 1) Independent coupling paths are created for TE101 and TE201 modes, which would reduce the complexity of numerical optimization; 2) Since the electric couplings are generated between each pair of the UIRs, it would be easy to realize a cross coupling by only constructing inductive windows between the SIW cavities. A filter prototype with central frequencies operated at 8 GHz and 10 GHz is then designed and fabricated for validation, which shows a compact size and high selectivity with controllable transmission zeros.
Precipitation Susceptibility of Marine Stratocumulus with Variable Above and Below-Cloud Aerosol Concentrations over the Southeast Atlantic

Abstract. Aerosol-cloud-precipitation interactions (ACIs) provide the greatest source of uncertainties in predicting changes in Earth’s energy budget due to poor representation of marine stratocumulus and the associated ACIs in climate models. Using in situ data from 329 cloud profiles across 24 research flights from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign in September 2016, August 2017, and October 2018, it is shown that contact between above-cloud biomass-burning aerosols and marine stratocumulus over the southeast Atlantic Ocean was associated with precipitation suppression and a decrease in the precipitation susceptibility (So) to aerosols. The 173 “contact” profiles with aerosol concentration (Na) greater than 500 cm−3 within 100 m above cloud tops had 50 % lower precipitation rate (Rp) and 20 % lower So, on average, compared to 156 “separated” profiles with Na less than 500 cm−3 up to at least 100 m above cloud tops. Contact and separated profiles had statistically significant differences in droplet concentration (Nc) and effective radius (Re) (95 % confidence intervals from a two-sample t-test are reported). Contact profiles had 84 to 90 cm−3 higher Nc and 1.4 to 1.6 μm lower Re compared to separated profiles. In clean boundary layers (below-cloud Na less than 350 cm−3), contact profiles had 25 to 31 cm−3 higher Nc and 0.2 to 0.5 μm lower Re. In polluted boundary layers (below-cloud Na exceeding 350 cm−3), contact profiles had 98 to 108 cm−3 higher Nc and 1.6 to 1.8 μm lower Re. On the other hand, contact and separated profiles had statistically insignificant differences between the average liquid water path, cloud thickness, and meteorological parameters like surface temperature, lower tropospheric stability, and estimated inversion strength. These results suggest the changes in cloud properties were driven by ACIs rather than meteorological effects, and the existing relationships between Rp and Nc must be adjusted to account for the role of ACIs.