Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentasi Citra Warna Otomatis Rambu Lalu Lintas dengan Penerapan Mask Thresholder

Segmentasi rambu jalan dan sistem pengenalan merupakan aspek penting dan esensial untuk digunakan pada sistem autopilot, smart car atau autonomous vehicle yang memungkinkan kendaraan dapat berjalan tanpa pengemudi manusia. Namun demikian pada paper ini citra rambu jalan yang diproses dalam bentuk image dan bukan vidio/kamera. Penelitian ini bertujuan memperoleh citra warna rambu jalan dengan presisi yang tinggi. Pada penelitian ini ditawarkan metode segmentation rambu jalan dengan mengembangkan Fuzzy C-means dengan menginjeksikan teknik mask-tresholder untuk mendapatkan hasil segmentasi warna rambu jalan dengan presisi tinggi. Mula-mula citra dideteksi dalam ruang warna RGB kemudian diubah menjadi model warna L*a*b dan dilanjukan ekstraksi untuk mendapatkan komponan warna *a*. Fuzzy C-means dterapkan pada citra warna *a* untuk segmentasi foreground dan background. Proses dilanjutkan dengan operasi opening – closing dan hole filling untuk mereduksi noise pada hasil segmentasi. Sampai pada tahap ini hasil segmentasi yang diperoleh adalah citra binary dimana foreground dalam warna putih dan bacground dalam warna hitam. Oleh karena itu untuk mendapatkan citra hasil segmentasi rambu jalan dalam ruang warna RGB maka diperlukan proses konvolusi. Teknik konvolusi yang dilakukan pada penelitian ini adalah dengan mengalikan tiap piksel citra mask tresholder dengan citra semula dalam ruang warna RGB. Citra mask tresholder yang digunakan dalam penelitian ini adalah citra binary hasil segmentasi dengan Fuzzy Cmeans. Metode yang ditawarkan telah diuji dengan citra rambu jalan sejumlah 18 citra. Hasil yang diperoleh menunjukkan kinerja metode yang diusulkan mampu mensegmentasi citra rambu jalan dalam sesuai warna citra semula. Menggunakan metode jaccard untuk mengukur akurasi kinerja didapat tingkat akurasi adalah 97,73%.
Cultural Influences on Opinion Expression in an Online and Offline Context

This study compares the expression of opinion in incongruent offline and online settings regarding the issue of gender desegregation in Kuwait’s public schools. Spiral of silence theory provides the theoretical foundation for examining the impact of certain cultural factors and religious influences on the expression of opinion, their relationship to the fundamental tenets of the theory, such as fear of social isolation, and Twitter use variables among respondents to a survey. The results to a questionnaire administered to 534 public and private university students indicate greater overall expression of opinion in the offline than online context. Offline and online, the nonconformist personality variable was a positive predictor of expression of opinion, and fear of social isolation was a negative predictor. The perceived position of Islam on the issue was a predictor of expression of opinion only in the offline context. Finally, daily average use of Twitter was an additional predictor of expression of opinion in the online environment.
Reference governor for switching converters with power factor correction

It is increasingly common to require performance improvement for power converters without modifying the original integrated controller, due to the multiple uses a single converter can serve. Such a goal can be met with the design of a regulator for the pre-compensated system, which serves as an add-on to enable new features and tighter performance targets. That is usually addressed with a Reference Governor (RG). We present here the design of an RG algorithm for a single-phase AC-DC boost converter, which is already controlled by an integrated digital Power Factor Correction (PFC) module. The converter operates in continuous conduction mode, and unitary power factor is achieved by a standard cascaded proportional-integral control with input voltage feedforward. We show that the non-invasive RG algorithm can improve the total harmonic distortion, power factor and voltage regulation. The proposed approach is based on model predictive control and subspace identification of the closed-loop prediction model. Numerical results on a high-fidelity simulator for power electronics confirm the advantages of the approach.
Preparation of nanoparticles of shellac and shellac-oligomer conjugates

Abstract Shellac is a natural biodegradable oligoester produced by lac insects, containing reactive functional groups such as hydroxyl, carboxylic acid, ester, aldehyde, and alkene groups, which can be used for chemical functionalization. Herein, shellac is functionalized with poly(ethylene glycol) (PEG) or poly(N-isopropylacrylamide) (PNIPAM) via grafting-to and grafting-from methods. The functional polymer conjugates are then processed as nanoparticles by the miniemulsion-solvent evaporation process. Shellac-PEG nanoparticles are enriched with apolipoprotein AI after incubation in fetal bovine serum at 37 °C. Moreover, shellac-PNIPAM nanoparticles adsorb specifically prothrombin at 37 °C (T > volume phase transition temperature, VPTT). Graphical Abstract
Strategies for Managing Endowment Funds: Case Studies of Selected Malaysian Public Universities

The Malaysian government has strongly encouraged Malaysia’s public universities to seek additional sources of income to assure the sustainability of their finances. Endowment is one of the sources encouraged by the government for implementation by these universities. This encouragement has received a positive response from public universities: all of them have now implemented endowment funds. However, the strategies used by these institutions in managing these funds are still poorly documented. Therefore, this study was conducted to explore the strategies used by Malaysian public universities in managing such funds. It is a qualitative study conducted by interviewing six representatives from selected public universities: Universiti Malaya (UM), Universiti Kebangsaan Malaysia (UKM) and Universiti Teknologi Malaysia (UTM). These public universities were selected because they recorded the highest collection of endowment funds. This study found that the strategies in managing endowment funds in Malaysian public universities include diversified investment portfolios, the appointment of investment experts, Shariah-compliant investments as an alternative, and diversified income sources.
Generalized Super-Twisting control of a Dual Active Bridge for More Electric Aircraft

In this work the control of a Dual Active Bridge (DAB) is presented. The application is within the innovative framework of the More Electric Aircraft (MEA) concept, and its goal is to recharge a battery pack in the case of standard loading conditions, while using the batteries to supply energy to an extra-load in the case of overload. The control objective is achieved through the adoption of the Generalized Super-Twisting algorithm. Rigorous mathematical proofs of stability are given for the controlled system and for supervisor switching between normal condition and overload. The effectiveness of the proposed strategy is shown by detailed simulations in Matlab/Stateflow/Electronics.
A nonfunctional copy of the salmonid sex-determining gene (sdY) is responsible for the “apparent” XY females in Chinook salmon, Oncorhynchus tshawytscha

Abstract Many salmonids have a male heterogametic (XX/XY) sex determination system, and they are supposed to have a conserved master sex-determining gene (sdY) that interacts at the protein level with Foxl2 leading to the blockage of the synergistic induction of Foxl2 and Nr5a1 of the cyp19a1a promoter. However, this hypothesis of a conserved master sex-determining role of sdY in salmonids is challenged by a few exceptions, one of them being the presence of naturally occurring “apparent” XY Chinook salmon, Oncorhynchus tshawytscha, females. Here, we show that some XY Chinook salmon females have a sdY gene (sdY-N183), with 1 missense mutation leading to a substitution of a conserved isoleucine to an asparagine (I183N). In contrast, Chinook salmon males have both a nonmutated sdY-I183 gene and the missense mutation sdY-N183 gene. The 3-dimensional model of SdY-I183N predicts that the I183N hydrophobic to hydrophilic amino acid change leads to a modification in the SdY β-sandwich structure. Using in vitro cell transfection assays, we found that SdY-I183N, like the wild-type SdY, is preferentially localized in the cytoplasm. However, compared to wild-type SdY, SdY-I183N is more prone to degradation, its nuclear translocation by Foxl2 is reduced, and SdY-I183N is unable to significantly repress the synergistic Foxl2/Nr5a1 induction of the cyp19a1a promoter. Altogether, our results suggest that the sdY-N183 gene of XY Chinook females is nonfunctional and that SdY-I183N is no longer able to promote testicular differentiation by impairing the synthesis of estrogens in the early differentiating gonads of wild Chinook salmon XY females.
Business households in the context of Vietnam's culture and law

The article analyzes and clarifies the position and role of business households in the system of business entities in the market economy in Vietnam. From its small-scale position, restrictions on the rights to use labor, and business locations, current Vietnamese laws have established provisions to ensure equality in legal status, autonomy, and self-responsibility on business transactions of business households. However, the business household is built and managed based on the family, the members of the business household both show blood relation and economic relation. Therefore, the family traditional cultural factors have a huge impact on the internal and business relations of household businesses. The traditional family relationship and the relationship among the members (of the business household) in the business relations related to asset liability and the development support policy of the State will form the pillar to promote the development of household businesses to become an important and indispensable part of the market economy and international integration in our country currently.
Identification of the occurrence and potential mechanisms of heterotopic ossification associated with 17-beta-estradiol targeting MKX by bioinformatics analysis and cellular experiments

Background Tendon heterotopic ossification (HO) is a common condition occurring secondary to tendon injury or surgical trauma that significantly affects the patient’s quality of life. The treatment of tendon HO remains challenging due to a lack of clarity regarding the pathological mechanism. Mohawk (MKX) is a key factor in preventing tendon HO; however, its upstream regulatory mechanism remains to be understood. This study aimed to identify potential compounds that target and regulate MKX and explore their functional mechanisms. Methods Bioinformatics analysis of MKX-related compounds and proteins was performed based on data from the STITCH and OncoBinder databases. Subsequently, the SymMap database was used to study MKX-related traditional Chinese medicine drugs and symptoms. Next, the OncoBinder genomic and proteomic discovery model was applied to identify potential regulators of MKX. The analytical tool Expert Protein Analysis System for proteomics was used to predict the three-dimensional structure of MKX, and the AutoDockTools software was used to identify pockets of activity at potential sites for molecular docking. Furthermore, we evaluated the effect of different doses of 17-beta-estradiol on bone marrow-derived mesenchymal stem cells (BM-MSCs). Results By predicting the three-dimensional structure of MKX and simulating molecular docking, Pro-Tyr and 17-beta-Estradiol were found to target and bind to MKX. Analysis of the STITCH and OncoBinder databases showed that MKX had a significant regulatory correlation with suppressor interacting 3 A/histone deacetylase 1 (SIN3A/HDAC1). The GO and KEGG pathway enrichment analysis revealed that the functions of MKX and its associated proteins were mainly enriched in osteogenic-related pathways. Assessment of the proliferation of BM-MSCs revealed that 17-beta-estradiol possibly upregulated the mRNA expression of the HDAC1-SIN3A/BMP pathway-related RUNX2, thereby promoting the proliferation of BM-MSCs. Conclusions The compounds Pro-Tyr and 17-beta-Estradiol may bind to MKX and thus affect the interaction of MKX with SIN3A/HDAC1.
Islanding Detection Based on Wavelet Transform and Neural Network

The function of islanding detection is required for the grid-connected inverter-based distributed generation system due to safety reasons and to maintain the quality of power supply. Passive methods have a large non detection zone and the detecting time is long, while active schemes have negative influence on power quality, so a novel passive islanding detection method was proposed. In this method, wavelet transform was adopted to extract feature vectors from the voltage of point of common coupling(PCC) point and the output current of inverter, and then pattern recognition was exerted by BP neural network to determine whether there was an island phenomenon. The simulation and experiment results show that this method is faster than the traditional passive methods in islanding detection, and the non-detection zone is smaller. At the same time, because no disturbance was added to the control signal in the method, there isn't a negative impact on power quality. The method overcomes the shortcoming of active methods and has high accuracy and reliability.
Neuro-Symbolic AI = Neural + Logical + Probabilistic AI

There is a broad consensus that both learning and reasoning are essential to achieve true artificial intelligence. This has put the quest for neural-symbolic artificial intelligence (NeSy) high on the research agenda. In the past decade, neural networks have caused great advances in the field of machine learning. Conversely, the two most prominent frameworks for reasoning are logic and probability. While in the past they were studied by separate communities, a significant number of researchers has been working towards their integration, cf. the area of statistical relational artificial intelligence (StarAI). Generally, NeSy systems integrate logic with neural networks. However, probability theory has already been integrated with both logic (cf. StarAI) and neural networks. It therefore makes sense to consider the integration of logic, neural networks and probabilities. In this chapter, we first consider these three base paradigms separately. Then, we look at the well established integrations, NeSy and StarAI. Next, we consider the integration of all three paradigms as Neural Probabilistic Logic Programming, and exemplify it with the DeepProbLog framework. Finally, we discuss the limitations of the state of the art, and consider future directions based on the parallels between StarAI and NeSy.
Radiation distribution estimation with a non-directional detector using a plane source model*

The Fukushima Daiichi nuclear disaster occurred during the Great East Japan Earthquake. Inside the reactor, materials with high radioactivity were scattered entirely, leading to a severe condition that restricted the number of measurement spots where the detector could be used. We propose a new system based on a plane model that uses fewer measurement spots and causes fewer estimation errors. We estimated the radiation source distribution using the maximum-likelihood estimation method optimized by gradient descent. Consequently, it was found that the proposed system, showed fewer errors than the previous system with a limited number of measurement spots. GRAPHICAL ABSTRACT
Veracity Assessment of Multimedia Facebook Posts for Infodemic Symptom Detection using Bi-modal Unsupervised Machine Learning Approach

Abstract: Ascertaining the truthfulness and trustworthiness of information posted on social media has been challenging with the proliferation of unsubstantiated, misleading, and inciting news, with different intents by purveyors. Unlike the traditional media with some level of regulations, user-generated posts on social networks does not pass through censorships in order to establish the truism of news items hence the need to be cautious of posted information on the networks. The lingering issue of recent suspension of Twitter microblogging site by the Nigerian government and the consequent decision to regulate social network operations in the country similarly centers on the subject of social media dependability for legitimate social engagements by millions of savvy Nigerian users. Whereas existing models in literature have proposed state-of-the-arts, this study seeks to improve on obtainable studies with a bi-modal machine learning methodology that indicate symptoms of infodemic social media posts. Using a multimedia facebook corpus, an unsupervised natural language processor, Inception v3 model, coupled with a hierarchical clustering network, is deployed for the duo of image and text sentiment analytics. Experimental result uniquely identified infodemic tendencies in facebook text-corpus and efficiently differentiates image-corpus into respective clusters through the Euclidian distance metrics. The most infodemic post returned a -0.9719 compound score while the most positive post returns 0.9488. Veracity assessment of polarized opinions expressed in negative clusters reveals that provocative, derogatory, obnoxious, etc. indicate propensity for infodemic tendencies. Keywords: Fake news. Facebook. Social media. Sentiment Analysis. Infodemic
Parametric design for cooling turbine blades based on analytic and feature modeling

Based on analytic and feature modeling methods,a parametric design method for three-dimensional internally cooling turbine blade model with ribs and bleed was developed.Blade profiles were defined by five-order polynomial expression.The cooling passage profiles were defined by the thickness of wall according to the blade profiles.A FORTRAN program was written with the intent to provide rapid and robust geometry generation of realistic turbine blades.The ribs,rabbet and margin pale were designed by means of CAD with feature modeling method.As an example,a tri-cavities internal cooling turbine blade was successfully established using this method.
PROCESS MINING IMPLEMENTATION BENEFITS FOR ORGANIZATIONS USING ERP SYSTEMS

One of the most valuable assets of an organization is its organizational data. Enterprise recourse planning (ERP) is one of the information systems that can be a source for data and implemented processes for the most of the organizations. Business process management and data driven approach are combined in process mining to address the increasing needs of organizations. The core idea of process mining is to utilize ERP or any other information systems implicit data by using algorithms to create new process model, analyze a process model or enhance an existing process model. In this review paper, I will discuss how organizations benefit more from ERP in improving their business process by using process mining technique in business process management cycle. The paper contains examples of related work that use process mining in different business process that have been implemented in ERP.
Study on Phase-Shift ZVZCS Full Bridge Converter and Its Digital Controlled

One DSP-based digital controlled method is proposed for phase-shift ZVZCS full bridge converter using transformer auxiliary winding. By using this method, the ZVZCS full bridge converter is fully digital controlled. This paper analyzes the converter's principle of operation and presents the digital control scheme. By applying this control scheme, a 2.5 kW DC/DC converter has been achieved.
A THREE-YEAR STUDY OF THE GDPR AND THE CONSUMER

This paper presents an empirical study of the General Data Protection Regulation (GDPR) from the consumer perspective. Based on data collected through an online survey questionnaire over a period of three years (2018–2020), we identify trends and patterns among Norwegian consumers. The findings show that the GDPR has not significantly affected consumer awareness, nor level of control over their own personal data. Concerning the enhanced rights of deletion, data portability and access to personal data, the patterns are similar, revealing that most of our respondents ‘might execute’ their rights. Pertaining to website cookies, most of the respondents are unsure, and the general trend from 2019 to 2020 reveals a greater uncertainty. This paper contributes with new insights for the industry and to the information privacy field.
A HOLISTIC FRAMEWORK FOR INFORMATION SYSTEM FOR THE MANAGEMENT OF INDOOR ENVIRONMENTAL QUALITIES (IEQ) IN BUILT FACILITIES

Because every building is considered as a long-run investment, regardless of its scale, at least to its owner, broadly by collectively impacting the national development of built assets. It is a vital aspect to ensure the qualities which define its inhabitance experience. Buildings’ indoor environments have been undermined being observed as an uncontrolled expensive application of systems, targeted for research, while indoor environmental quality (IEQ) is one of the assembly of aspects that aim to appraise almost any built facility performance. There have been research efforts in literature, with global and contextual limitations, covering dispersed relations and topics in the IEQ domain, such as the control, and analysis of occupants’ satisfaction and facilities systems performance in respect to standards. These research efforts were more focused on investigating results rather than allowing for an automated solution for the creation of universal standards. Therefore, emerged a need for modelling IEQ management in an inclusive manner, to allow for the sustainable management and understanding of facilities components’ impacts, on both occupants’ experiences and wellbeing, whereas the power of information systems with the capabilities of todays’ hardware and technologies, set a new era, for the architectural science in digital means. This research paper proposes a conceptual information system framework modelled in Integrated Computer Aided Manufacturing Definition for Function Modeling (IDEF 0 ) diagram, to enable the architects and the facility managers to sustainably manage and monitor IEQs in built facilities. The proposed framework is based on a standardized big data analytics that can provide architects and facility managers with meaningful insights for achieving an evidence based, and informed design thinking, as well as sustainable monitoring of built facilities in real time. improved IEQ conditions. The study linked the production of raw materials used in construction of wooden houses, to the aspects, a potential for achieving high quality IEQ. measurements taken, utilized different and sensing that can provide quantified data for further analyses of performance. The limitation of this study is that it focused on collection of measurements during period of time (cold period of the heating season). The study indicated that wooden houses possess satisfactory IEQ performance conditions for its occupants.