Miracle-dz/UniFAR-FTUs huggingface dataset:
SIGN LANGUAGE RECOGNITION ON VIDEO DATA BASED ON GRAPH CONVOLUTIONAL NETWORK

Sign language is a very important means of communication for the deaf and the mute. Therefore, it is necessary to automatically recognize sign language by a computer so that non-disabled people can understand the sign language that is used. Many studies on sign language recognition have been carried out, one of which is the sign language alphabet recognition using the Convolutional Neural Network (CNN). However, CNN cannot represent a skeletal data structure that has the graph form. The Graph Convolutional Network (GCN) is a generalization of CNN that can perform feature extraction from graphs in non-Euclidean space. GCN is widely used in action recognition research such as the Shift-GCN method. This study used hand joints position estimated by MediaPipe Hands that shaped like a graph. The graph is processed using the modified Shift-GCN that introduces a shift weighting approach based on the vertices adjacency. The dataset used in this study is hand keypoints extracted from video data of 26 American Sign Language (ASL) alphabets. Based on the experimental results, the proposed method achieved the best accuracy of 99.962%.
SciFig: A Scientific Figure Dataset for Figure Understanding

Most existing large-scale academic search en-001 gines are built to retrieve text-based informa-002 tion. However, there are no large-scale retrieval 003 services for non-textual components such as 004 scientific figures and tables. One challenge to-005 wards such services is scientific figure under-006 standing that represents visual information by 007 text. A key problem is a lack of datasets con-008 taining annotated scientific figures and tables, 009 which can be used for classification, question-010 answering, and auto-captioning. Here, we de-011 sign a pipeline that extracts figures and tables 012 from scientific literature and a deep-learning-013 based framework that classifies scientific fig-014 ures using visual features. Using this pipeline, 015 we develop the first large-scale annotated cor-016 pus, S CI F IG consisting of more than 264k sci-017 entific figures extracted from ≈ 56 k research 018 papers in the ACL Anthology. We make avail-019 able the S CI F IG - PILOT dataset that contains 020 1671 manually labeled scientific figures belong-021 ing to 19 different categories. The dataset is 022 accessible at https://bit.ly/3m4u0eq under a CC 023 BY-NC license. 024
Complementarities in Platform Ecosystems: A Study of Coevolution of Made-in-Korea Digital Entertainment Phenomenon

Business ecosystems are pushed by competition to develop complementarities that increase their chances of survival. However, scholars continue to cite the lack of understanding in coevolution as a complementarity mechanisms of businesses, especially in the digital platform ecosystems. In this research-in-progress paper, we explore the development of complementarities, found in the coevolution of entities in digital platform ecosystems. Through initial case studies of globally developed Korean entertainment and culture industry, we discover a possible categorization of different types of coevolution in the digital platform ecosystem; namely ‘ digital transformation ’ – business coevolving with its environment, ‘ platformization ’ – core platform coevolving with its complementors, and ‘ reconfiguration ’-core ecosystem coevolving with its sub-ecosystems. Based on the findings, we suggest that there is a need to extend the definition of platform ecosystems to also incorporate the sub-ecosystems’ coevolutionary interaction. A new conceptual framework is presented with future plans to develop both the work and the model.
topractical practical measurementsin-situ sampling of water stable isotopes in tree stems and soils

Using water stable isotopes to track plant water uptake or soil water processes has become an invaluable tool in ecohydrology and physiological ecology. Recent studies have shown that laser absorption spectroscopy can measure equilibrated water vapour well enough to support inference of liquid stable isotope composition of plant or soil water, on-site and in real-time. However, current in-situ systems require the presence of an instrument in the field. Here we tested, first in 15 the lab and then in the field, a method for equilibrating, collecting, storing, and finally analysing water vapour for its isotopic composition that does not require an instrument in the field. We developed a vapour storage vial system (VSVS) that relies on in-situ sampling into crimp neck vials with a double-coated cap using a pump and a flow meter powered through a small battery and measuring the samples in a laboratory. All components are inexpensive and commercially available. We tested the system’s ability to store the isotopic composition of its contents by sampling a range of water vapour of known isotopic 20 compositions (from -95 to +1700‰ for δ 2 H) and measuring the isotopic composition after different storage periods. Samples for the field trial were taken in a boreal forest in northern Sweden. The isotopic composition was maintained to within 0.6 to 4.4‰ for δ 2 H and 0.6 to 0.8‰ for δ 18 O for natural-abundance samples. Although 2 H-enriched samples showed higher uncertainty, they were sufficient to quantify label amounts. We detected a small change in the isotopic composition of the sample after long storage period, but it was correctable by linear regression models. We observed the same trend for the 25 samples obtained in the field trial for δ 18 O but observed higher variation in δ 2 H compared to the lab trial. Our method combines the best of two worlds, sampling many trees in-situ while measuring at high precision in the laboratory. This provides the ecohydrology community a tool that is not only cost-efficient but also easy to use.
Enhancement of the Speech with Emotion Recognition using Artificial Intelligence

-Automatic speech emotion recognition (SER) plays an important role in HCI systems for measuring people’s emotions has dominated psychology by linking expressions to group of basic emotions (i.e., anger, disgust, fear, happiness, sadness, and surprise). In this work, we introduce a split based enhancement to signal which we are loading. This paper describes about speech enhancement and speech emotion recognition from speech signal based on features analysis and NN-classifier. Speech enhancement is done based on the phase and frequency value of the particular signal.The recognition system involves speech emotion detection, features extraction and selection and finally classification. These features are useful to distinguish the maximum number of samples accurately and the NN classifier based on discriminant analysis is used to classify the six different expressions. The simulated results will be shown that the filter based feature extraction with used classifier gives much better accuracy with lesser algorithmic complexity than other speech emotion expression recognition approaches.
Research on the Structure Optimization of Regional Heterogeneous Human Capital

This paper uses the differences of education level to measure the heterogeneity of human capital. Study on the cross-section data of the provincial area in 2013.Screen the heterogeneity human capital index for economic growth with stepwise regression method. The heterogeneous human capital and material capital, which has a significant effect on economic growth, is taking as the input index. Take economic growth as an output indicator. Analyze the efficiency of heterogeneous human capital in different regions with data envelopment analysis method. Determine the heterogeneous human capital structure adjustment direction based on the input redundant data. The research results show that the vast majority of the provinces in China are in the non DEA effective state because of heterogeneous human capital. Redundancy occurs mainly in the junior middle school education human capital. The path of optimizing the structure of human capital is to increase the investment of high school education (high school and secondary vocational education), and transfer the elementary human capital to the medium human capital. DEA model results show that, relatively effective DMUs are Beijing, Shanghai, Guangdong, Tibet. Scale efficiency in most provinces showed an increasing state except Tianjin, Hebei, Inner Mongolia, Liaoning, Jiangsu, Zhejiang, Fujian, Shandong provinces (city). Study the input redundancy (S 1 - 、 S 2 - 、 S 3 - 、 S 4 -) and the output value ( S 1 + ) can found out that the main reason of the non DEA effective is the redundancy of the heterogeneous human capital. Most of the provinces have redundant human capital in junior middle school education, only a few provinces have redundant human capital in senior middle school education human capital and college and above
ANALYSIS OF FACTORS AFFECTING USE BEHAVIORS OF TOKOPEDIA MOBILE COMMERCE IN DKI JAKARTA

Tokopedia, as a large m-commerce platform, is highly targeted by people in DKI Jakarta to fulfill their online shopping needs. This study aims to analyze the factors that influence use behavior in the use of m-commerce with the modification of the UTAUT theory. The variables used are performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention. The number of samples taken was 411 respondents with a domicile of DKI Jakarta. The statistical method used with Smart PLS. The results of empirical analysis show that the variable performance expectancy and effort expectancy does not affect behavioral intention. Tokopedia mobile commerce users are still not satisfied with the use of the application on smartphone users and Tokopedia m-commerce is still difficult to learn because of the use of applications and user interfaces that are still relatively complex which makes it difficult for users to operate Tokopedia m-commerce . In contrast, the variables social influence and facilitation conditions have a significant effect on behavioral intention, and behavioral intention has a significant effect on use behavior .
Edinburgh Research Explorer The greatest catch

physiological settings. The two recent studies from the Hentze and Landthaler laboratories have taken the RNA bait concept a step further by capturing proteins by covalent cross-linking to polyadenylated RNA, mainly corresponding to mRNAs, and thereby generated a global mRNA interactome in HeLa [2] or HEK-293 [3] cell culture systems. In both studies, RNA-binding proteins are physically cross-linked to mRNAs using 254 nM UV-C light [2] or 365 nM UV in conjunction with PARs [2,3]. Next, cellular mRNA and the bound interactome are eﬃciently captured with oligo-dT-coated beads and puriﬁed under stringent conditions to eliminate contamination from non-cross-linked proteins, including those deriving from non-cross-linked protein-protein interactions. Finally, proteins are released by RNAse digestion, gel resolved and analyzed by quantitative mass spectrometry (MS) approaches to reveal protein interactome of cellular mRNAs based spectral Both studies validated their data set by Abstract Purification of proteins cross-linked to mRNAs has identified 800 mRNA-binding proteins and their characteristics.
BlockFlex: Enabling Storage Harvesting with Software-Defined Flash in Modern Cloud Platforms

Cloud platforms today make efﬁcient use of storage resources by slicing them among multi-tenant applications on demand. However,ourstudydiscloses thatcloudstorage is stillseriously underutilized for both allocated and unallocated storage. Although cloud providers have developed harvesting techniques toallowevictablevirtualmachines(VMs)touseunallocatedre-sources, these techniques cannot be directly applied to storage resources,due to the lack of systematic support forthe isolation of space, bandwidth, and data security in storage devices. In this paper, we present BlockFlex, a learning-based storage harvesting framework, which can harvest available ﬂash-based storage resources at a ﬁne-grained granularity in modern cloud platforms. We rethink the abstractions of storage virtualization and enable transparent harvesting of both allocated and unallocated storage for evictable VMs. BlockFlex explores both heuristics and learning-based approaches to maximize the storage utilization, while ensuring the performance and security isolation between regular and evictable VMs at the storage device level. We develop BlockFlex with programmable solid-state drives (SSDs) and demonstrate its efﬁciency with various datacenter workloads.
The Role of DACT Family Members in Tumorigenesis and Tumor Progression

Disheveled-associated antagonist of β-catenin (DACT), which ubiquitously expressed in human tissue, is critical for regulating cell proliferation and several developmental processes in different cellular contexts. In addition, DACT is essential for some other cellular processes, such as cell apoptosis, migration and differentiation. Given the importance of DACT in these cellular processes, many scientists are gradually interested in studying the role of DACT in tumorigenesis and cancer progression. This review article focuses on the latest research regarding the essential functions and potential DACT mechanisms in the occurrence and progression of tumors. Our study indicates that DACT may act as a tumor biomarker for cancer diagnosis and prognosis, as well as a promising therapeutic target in cancers.
Rainbow: A Rendering-Aware Index for High-Quality Spatial Scatterplots with Result-Size Budgets

We study the problem of computing a spatial scatterplot on a large dataset for arbitrary zooming/panning queries. We introduce a general framework called “Rainbow” that generates a high-quality scatterplot for a given result-size budget. Rainbow augments a spatial index with judiciously selected representative points offline. To answer a query, Rainbow traverses the index top-down and selects representative points with a good quality until the result-size budget is reached. We experimentally demonstrate the effectiveness of Rainbow
DOES THE PREDATOR BECOME THE PREY? KNOWLEDGE SPILLOVER AND THE LEARNING OF KNOWLEDGE PROTECTION IN ALLIANCES

Does a firm that successfully absorbs knowledge from its partner learn to protect its own knowledge in a subsequent alliance? Our analysis of 529 alliances of East Asian firms during 1999– 2015 suggests that as firms more skillfully overcome their partners’ knowledge protection, they learn to better protect their own knowledge in subsequent alliances, but such vicarious learning increases at a diminishing rate. This learning is further reinforced when the appropriability regime in the previous partner’s country is stronger than that in the firm’s country and when the firm’s business similarity with its previous partner is greater than with its subsequent partner. In turn, this learning is weakened by increased value chain scope and the firm’s relative absorptive capacity in its previous alliance.
Distributed Frequency Regulation in Power Grids with Low and Time-Varying Inertia

—This paper presents a distributed frequency con- trol method for power grids with high penetration of inverter-connected resources under low and time-varying inertia due to renewable energy (RE). We provide a distributed virtual inertia (VI) allocation method using the distributed subgradient algorithm. We implement our distributed control strategy under full and sparse communication architectures. The distributed full and sparse communication controllers achieve comparable performance to a centralized controller and stabilize the test system within 6 s. We study the sensitivity of the controller performance to varying objective function weights on phase angle versus frequency deviation, gradient step sizes, and allowed rate of change of inertia (RoCoI) coefﬁcients. We observe that the settling time of the states and the controller performance and effort are susceptible to changes in the gradient step size and objective weights on the frequency and angle deviation. While a higher objective weight on angle versus frequency deviations positively affects their settling times, it negatively impacts controller performance and control effort. The impact of this work is to propose distributed control schemes as new mechanisms that act before or in alignment with primary and secondary control to safely regulate the frequency in future power grids.
Alternative Activation Comparison between Innate, Classic, and Substrate Fate in Activated Macrophages: A

Macrophagesplayarelevantroleininnateandadaptiveimmunitydependingonthebalanceofthestimulireceived.Fromananalyticaland functional pointofview,macrophagestimulationcanbesegregatedintothreemainmodes,asfollows:innate,classic,andalternativepath-ways. Thesedifferentialactivationsresultintheexpressionofspeciﬁcsetsofgenesinvolvedinthereleaseofpro-oranti-inﬂammatorystimuli. In the present work, we have analyzedwhether speciﬁc metabolic patterns depend on the signaling pathway activated. A [1,2- 13 C 2 ]glucose tracer-basedmetabolomicsapproachhasbeenusedtocharacterizethemetabolicﬂuxdistributionsinmacrophagesstimulatedthroughthe classic, innate, and alternative pathways. Using this methodology combined with mass isotopomer distribution analysis of the new formed metabolites,thedatashowthatactivatedmacrophagesareessentiallyglycolyticcells,andaclearcutoffbetweentheclassic/innateactivation and the alternativepathway exists.Interestingly,macrophage activation through LPS/IFN- g or TLR-2, -3, -4, and -9 results in similarﬂux distribution patterns regardless of the pathway activated. However, stimulation through the alternative pathway has minor metabolic effects.Themolecularbasisofthedifferencesbetweenthesetwotypesofbehaviorinvolvesaswitchintheexpressionof6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFK2) from the liver type-PFK2 to the more active ubiquitous PFK2 isoenzyme, which responds to Hif-1 a activation and increases fructose-2,6-bisphosphateconcentration 2010, 185: 605–614.
Theoretical Modelling of the Heat Capacity of PuO 2 and Molecular Dynamics Calculations

A new generation of fast breeder reactors (FBRs) is under development with the objective of making nuclear energy more sustainable. Most promising reactor designs are fuelled, at least in their early phase of deployment, with UO 2 -PuO 2 oxide fuel. Heat capacity is important for the evaluation of thermal conductivity and performance under transient conditions. If, on the one hand, the heat capacity of UO 2 has been deeply studied, on the other hand, measurements on PuO 2 are scarce or even lacking at high temperatures. Numerical methodologies such as MD calculations have been proposed to overcome the difficulties encountered in experimental measurements. In parallel, scientists have employed theoretical models as valuable tools for the interpretation of enthalpy measurements. Previous studies have pointed out that several issues of PuO 2 heat capacity require more investigation such as the deviation of MD calculations from measurements in the low temperature domain, the existence of the Bredig transition, the formation of defects at high temperature and correlated increase of heat capacity. This paper presents results on the heat capacity of PuO 2 obtained using a two-fold approach: theoretical modelling and MD calculations based on a PuO 2 interatomic potential published recently.
Advances of Password Cracking and Countermeasures in Computer Security

—With the rapid development of internet technologies, social networks, and other related areas, user authentication becomes more and more important to protect the data of the users. Password authentication is one of the widely used methods to achieve authentication for legal users and defense against intruders. There have been many password cracking methods developed during the past years, and people have been designing the countermeasures against password cracking all the time. However, we find that the survey work on the password cracking research has not been done very much. This paper is mainly to give a brief review of the password cracking methods, import technologies of password cracking, and the countermeasures against password cracking that are usually designed at two stages including the password design stage (e.g. user education, dynamic password, use of tokens, computer generations) and after the design (e.g. reactive password checking, proactive password checking, password encryption, access control). The main objective of this work is offering the abecedarian IT security professionals and the common audiences with some knowledge about the computer security and password cracking, and promoting the development of this area.
Planning Considerations for Smart and Sustainable Transportation Infrastructure: Case Study of Non-Motorised Transport Facilities in Johannesburg South Africa

Non-motorised transportation (NMT) infrastructure, including for walking, cycling and other forms of active or human-powered transport, is a key part of the overall transport network of any "smart" city. Attention to key factors that could potentially influence the sustainability of NMT infrastructure systems at the planning stage is arguably crucial in achieving a sustainable and smart transport network. This study examines critical factors taken into account in the planning and delivery of NMTs to ensure the delivery of sustainable and smart transport networks. Three projects in Johannesburg, South Africa were selected using convenience sampling, based on the availability of information. Document analysis and interview were employed for data collection. Thematic content analysis was conducted with the aid of atlas-ti software. Findings revealed that community’s specific needs with regard to accessibility and services, design, costs, distribution and speed of traffic, distances, as well as occurrence of accidents and incidents were critical factors considered in the planning of NMT infrastructure. Other factors included locational characteristics such as topography, and existing land uses which may affect facility costs and integration of NMT infrastructure. The provision of non-motorised transport facilities, not only ensures the safety of road users, but improves liveability and quality of life and welfare of communities, as well as environment and as such, attention to the factors which should ideally be considered at the planning stage to ensure sustainability of the NMT system is vital.
Variation in stem-final consonant clusters in Korean nominal inflection

This study investigates how Korean stem-final consonant clusters /ps/, /ks/, /lp/, /lk/, /ls/, and /lm/ exhibit variation, when a vowel-initial inflectional suffix is attached to noun stems. It is well-established that the Korean stem-final consonant clusters are either fully faithfully preserved (i.e. conservative), or simplified by deleting one of the two consonantal elements C 1 and C 2 (i.e. innovative). However, there has been no study about dominant patterns across clusters: which consonant cluster is more prone to preservation or simplification when inflected. When it comes to simplification, it has also been unclear which of C 1 or C 2 undergoes deletion, and why. Results of a production experiment show that there is a stark dichotomy between the clusters that share the same [±sonorant] feature (/ps/, /ks/, /lm/) and those that do not (/lp/, / lk/, /ls/): the former preferred conservative forms, whereas the latter favored innovative forms. Innovative forms in particular are accounted for in relation to consonant cluster simplification in isolation forms of nouns, following Kenstowicz’s (1996) Base-Identity effect. While the nature of the consonant cluster turned out to be a significant factor for variation in inflected forms, other factors (inflectional suffixes, speakers’ regional dialects, and gender) did not. This study is significant, in that it sheds light on a blind spot in the discussions of variation in stem-final consonant clusters in Korean and provides a comprehensive analysis that connects consonant cluster simplification in isolation forms with conservative/innovative forms in inflected forms.