Reviewerly/exHarmony huggingface dataset:
PEMEROLEHAN MORFOLOGI DAN SINTAKSIS PADA ANAK USIA 2-4 TAHUN (KAJIAN PSIKOLINGUISTIK)

This study aims to determine and describe the language acquisition system of children aged 2 years 6 months and children aged 3 years 1 month, especially those at the level of morphology and syntax.The method used in this research is descriptive qualitative method.The research subjects were Sheva, a child aged 2 years 6 months and Raya, a child aged 3 years and 1 month.It can be concluded that: 1) At the level of morphology, a child who is 2 years and 6 months old (Sheva) produces more words that are monomorphemic, there is no morpheme that distinguishes the meaning of words, is able to say more than syllables, although not regularly able to compose simple sentences, there is an affixation process.Whereas in children aged 3 years and 1 month (Raya), they produce more words, monomorphemic words are clearer, there are morphemes that can distinguish the meaning of words, there are free morphemes and bound morphemes, sentence arrangement is regular and longer, can use three or more words, there is an affixation process.2) At the level of syntax, children aged 2 years 6 months (Sheva), the resulting sentence patterns are very simple, sentences that are still incomplete, imperfect pronunciation of phonemes, are able to produce simple declarative, imperative and interrogative sentences.Meanwhile, children who are 3 years and 1 month old (Raya) can produce sentences that resemble adults, their pronunciation is clear enough, they are able to multi-word and can produce clear declarative, imperative, and interrogative sentences.
POP and PUSH: Demystifying and Defending against (Mach) Port-oriented Programming

Apple devices (e.g., iPhone, MacBook, iPad, and Apple Watch) are high value targets for attackers.Although these devices use different operating systems (e.g., iOS, macOS, iPadOS, watchOS, and tvOS), they are all based on a hybrid kernel called XNU.Existing attacks demonstrated that vulnerabilities in XNU could be exploited to escalate privileges and jailbreak devices.To mitigate these threats, multiple security mechanisms have been deployed in latest systems.In this paper, we first perform a systematic assessment of deployed mitigations by Apple, and demonstrate that most of them can be bypassed through corrupting a special type of kernel objects, i.e., Mach port objects.We summarize this type of attack as (Mach) Port Object-Oriented Programming (POP).Accordingly, we define multiple attack primitives to launch the attack and demonstrate realistic scenarios to achieve full memory manipulation on recently released systems (i.e., iOS 13 and macOS 10.15).To defend against POP, we propose the Port Ultra-SHield (PUSH) system to reduce the number of unprotected Mach port objects.Specifically, PUSH automatically locates potential POP primitives and instruments related system calls to enforce the integrity of Mach port kernel objects.It does not require system modifications and only introduces 2% runtime overhead.The PUSH framework has been deployed on more than 40,000 macOS devices in a leading company.The evaluation of 18 public exploits and one zero-day exploit detected by our system demonstrated the effectiveness of PUSH.We believe that the proposed framework will facilitate the design and implementation of a more secure XNU kernel.
Analysis and Research on the Teaching Methods of Vocational College Teachers under the Background of Big Data

The teaching methods of vocational college teachers can not only reflect the comprehensive quality and professional level of teachers, but also highlight the innovative ability of teachers. Good teaching methods can not only help students learn professional knowledge, but also affect students' professional employment development. This article analyzes the teaching methods of vocational college teachers under the background of big data.
Ontology Assisted Modelling of Galvanic Corrosion of Magnesium

Multi-physics and multiscale modelling frameworks, especially for the computer based analysis of surface damage and corrosion, requires not only robust computational tools but also an efficient data-centric architecture for handling information exchange at different modelling scales.The issue to exchange data provided by different computational solvers as well as required and used in different programming languages forms a request in specific formats signifying a strong non-uniformity for an easy nexus with other solvers.This non-uniformity has created a need to focus on intermittent state-of-theart data-centric software tools, which aim to bridge data exchange technology, to ensure heterogeneity across a wide range of solvers [1].Moreover, data organization in the form of ontological representation and metadata structures are necessary to be prepared as a standard for a coherent representation of information regardless of the diverse nature of data formats specific to a scientific discipline.A domain ontology based on the European Materials & Modelling Ontology (EMMO) for galvanic corrosion is outlined and connected to corresponding concepts in a galvanic corrosion model.This fundamental work provides and discusses the concept, underlying terminology and working mechanism of a data-centric architecture for exchanging and interfacing data-flow between data sources/sinks and solvers.It realizes an ontological representation of physics and chemistry of galvanic corrosion.Thus, it is a nuclei for further improvement's of interoperability between complex corrosion related phenomena and models.It paves the way for accurate computational corrosion engineering.
INTELLIGENT RECOGNITION OF LAYERED GEOLOGICAL BODY BASED ON MACHINE LEARNING AND SEISMIC EXPLORATION

Seismic exploration is a non-destructive detection technology widely applied in oil and gas exploration or geological structure exploration. The seismic signals are quite difficult to be interpreted due to the complexity of underground structures and the inhomogeneous media. Limitations of current methods used in seismic signals interpretation and needs for expert knowledge considerably reduce the efficiency of interpretation. We established a nonlinear model using neural network to predict geological information. Firstly, we generated thousands of random layered geological models of media in rock, water and air. Then we got one signal data each model by using finite difference method to simulate the propagation of seismic waves. At last, 80% signals and geological models data are used as training data sets and 20% as test data sets. As the tests show, this neural network accurately predicts signals the depths of underground media interface and velocity of the media between. We didn't use any filtering or feature extraction method in the work above. This method improves the seismic exploration economically and efficiently. The method of machine learning nicely fits in the simplified geological situation in karst area. This research is a preliminary discussion on the feasibility of applying machine learning method into seismic exploration.
DSCESM: Data Security for Cloud Environment with Scheduled Key Managers

Distributed Cloud Environment (DCE) has the ability to store the data and share it with others. One of the main issues arises during this is, how safe the data in the cloud while storing and sharing. Therefore, the communication media should be safe from any intruders residing between the two entities. What if the key generator compromises with intruders and shares the keys used for both communication and data? Therefore, the proposed system makes use of the Station-to-Station (STS) protocol to make the channel safer. The concept of encrypting the secret key confuses the intruders. Duplicate File Detector (DFD) checks for any existence of the same file before uploading. The scheduler assigns the work of generating keys to the key manager who has less task to complete or free of any task. By these techniques, the proposed system makes time-efficient, cost-efficient, and resource efficient compared to the existing system. The performance is analysed in terms of time, cost and resources.
On primitives for compensation handling as adaptable processes

Mechanisms for compensation handling and dynamic update are increasingly relevant in the specification of reliable communicating systems. Compensations and updates are intuitively similar: both specify how the behavior of a concurrent system changes at runtime in response to an exceptional event. However, calculi for concurrency with compensations and updates are technically quite different. We compare calculi for concurrency with compensation handling and dynamic update from the standpoint of their relative expressiveness. We develop two encodings of a process calculus with compensation handling into a calculus of adaptable processes. These encodings differ in the target language considered: the first considers adaptable processes with subjective updates in which, intuitively, a process reconfigures itself; the second considers objective updates in which a process is reconfigured by a process in its context. Our main discovery is that subjective updates are more efficient than objective ones in encoding primitives for compensation handling: the first encoding requires less computational steps than the second one to mimic a single computation step in the source language of compensable processes. Our encodings satisfy strong correctness criteria; they shed light on the intricate semantics of compensation handling.
An Approach for Adaptive Security of Cloud Applications within the ATMOSPHERE Platform

Self-protecting systems can reduce response time to known attacks by automating decision-making processes in security operations. This paper briefly describes the ATMOSPHERE platform for monitoring and enforcement of trustworthiness in cloud systems, as well as proposes a way to enhance its Trustworthiness Monitoring &amp; Assessment framework (responsible for analyzing and planning adaptation actions) in order to instantiate the concept of adaptive security for self-protecting cloud infrastructures and applications. The paper approaches adaptive security based upon adaptive Web Application Firewalls, and enhances a software-based, feedback control loop (named MAPE-K) for monitoring and analysis of security events, as well as the planning and execution of adaptation actions for securing cloud applications. This is a work in progress, currently under development, to be integrated to ATMOSPHERE&amp;apos;s framework.
Virtual Environments for Smart House System Studying

Today, virtual worlds are used not only in the gaming industry. Virtual, augmented and cross-reality also allow to organize effectively 3D environments that provide the effect of immersion and user interaction with objects and processes of the learning environment. The combination of physical objects and virtual models is a modern trend in the online lab development. Based on this approach, online experiment becomes more visual and interesting for students. In addition, it reduces queues for experiments on the real equipment. The paper presents the results of the development of an interactive web-oriented virtual model that expands the Smart House & IoT remote laboratory functionality as well as 3D virtual environment of Smart House for the virtual reality helmet. The proposed solutions will motivate students to study home automation technologies and the features of Smart Home systems realization.
On an Intuitionistic Fuzzy Form of the Goguen’s Implication

In the present paper we construct a new intuitionistic fuzzy implication, giving intuitionistic fuzzy form to Goguen’s implication. Some of its basic properties are studied and illustrated with examples. Geometrical interpretations of the different forms of the new implication are given. Other forms of the Goguen’s implication are discussed.
Session-based concurrency, declaratively

Abstract Session-based concurrency is a type-based approach to the analysis of message-passing programs. These programs may be specified in an operational or declarative style: the former defines how interactions are properly structured; the latter defines governing conditions for correct interactions. In this paper, we study rigorous relationships between operational and declarative models of session-based concurrency. We develop a correct encoding of session $$\pi $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>π</mml:mi> </mml:math> -calculus processes into the linear concurrent constraint calculus ( $$\texttt {lcc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>lcc</mml:mi> </mml:math> ), a declarative model of concurrency based on partial information (constraints). We exploit session types to ensure that our encoding satisfies precise correctness properties and that it offers a sound basis on which operational and declarative requirements can be jointly specified and reasoned about. We demonstrate the applicability of our results by using our encoding in the specification of realistic communication patterns with time and contextual information.
Managing Services Using Ansible

As an amazing system administrator, you need to be able to face the differences in Linux distributions and face them with a smile. We have just installed the Apache web server; on CentOS the associated service did not start after the installation, whereas it did in Ubuntu. Of course, ultimately, we would like the service running on all web servers, regardless of the distribution. Not only are we faced with this issue relating to services; we have edited the SSHD configuration on all systems using the lineinfile module, but those changes are not affected until a restart of the service itself. So, our systems are still at risk. In this chapter we will solve some of these issues and prepare for future solutions by implementing both the service and systemd module in Ansible. We will see how we can start and enable services as needed, as well as stopping and disabling services we do not need. Critically, for changes in configuration files that affect services, we can restart the service on a change in the file's state. This is a new element to us in Ansible, known as a handler.
Class Normalization for (Continual)? Generalized Zero-Shot Learning

Normalization techniques have proved to be a crucial ingredient of successful training in a traditional supervised learning regime. However, in the zero-shot learning (ZSL) world, these ideas have received only marginal attention. This work studies normalization in ZSL scenario from both theoretical and practical perspectives. First, we give a theoretical explanation to two popular tricks used in zero-shot learning: normalize+scale and attributes normalization and show that they help training by preserving variance during a forward pass. Next, we demonstrate that they are insufficient to normalize a deep ZSL model and propose Class Normalization (CN): a normalization scheme, which alleviates this issue both provably and in practice. Third, we show that ZSL models typically have more irregular loss surface compared to traditional classifiers and that the proposed method partially remedies this problem. Then, we test our approach on 4 standard ZSL datasets and outperform sophisticated modern SotA with a simple MLP optimized without any bells and whistles and having ~50 times faster training speed. Finally, we generalize ZSL to a broader problem -- continual ZSL, and introduce some principled metrics and rigorous baselines for this new setup. The project page is located at this https URL.
EDA and Quantum Computing

Quantum computing (QC) is fast emerging as a potential disruptive technology that can upend some businesses in the short-term and many enterprises in the long run. Electronic Design Automation (EDA) is uniquely positioned to not only benefit from quantum computing technologies but can also impact the pace of development of that technology. Quantum circuits will play a key role in driving the synergy between quantum and EDA. Much like standard cell libraries became the most important abstraction between CMOS technology and most EDA tooling and spawned four decades of EDA innovation and designer productivity, quantum circuits can unleash a similar streak of innovation in quantum computing.
The manifestations of digital literacy in social media among Indonesian youth

Digital literacy capability is a must in the era of internet access, especially in the use of social media. All internet users, especially university students, must practice digital literacy. This study aims to found the common forms of university students' digital literacy behavior when using social media. This study uses a mixed-method approach as it consists of data search using a digital literacy scale, an open-ended questionnaire, and interviews with university students in Yogyakarta. The results of this study indicate that respondents with high digital literacy levels conduct a process of evaluating truthful information by checking trusted sources of information directly and discussing their findings with significant others. The likelihood and ability to evaluate information correctly is affected by family background, formal education, and negative hoax impact awareness. The study also found that after respondents perform across (double) checks, they will usually forward the information, also known as doing a repost. This research implies a description of digital literacy behavior carried out by students in Yogyakarta; with this study, digital literacy behavior expects to provide an overview of information technology policymakers.
Assessment of Heavy Metal Contents in Three Different Land used Soils in Ohaji/Egbema Imo State, Nigeria

This assessment of some heavy metal contents in different land used soils in Ohaji/Egbema, Imo State was conducted between June, 2019 and May, 2020. Three land used soils namely; the grass land, continuously cropped and forest land were studied. Soil profile representations were established in each of the physiographic units and soil samples collected from the pedogenetic horizons for the analysis of some heavy metals like Lead (Pb), Copper (Cu), Manganese (Mn), Zinc (Zn), and Iron (Fe). The heavy metals observed in this study were Cu, Mn, Zn and Fe while Pb was not detected in this study. The results of this study showed that the grass land, continuously cropped and forest land had no Pb detected. The heavy metal contents(Cu, Mn, Zn and Fe) detected decreases with depth from 0.15cm depth to 60-90 cm depth in grass land and continuously cropped and forested land respectively. The occurrence of Fe was high in forested land which ranges from 7.8-6.3Mg/Kg with mean value of 7.0Mg/Kg than continuous cropped land and grass land with lower values. The forest land had high sodium content with mean value of 0.74 and high electrical conductivity with a mean 4.91 dsm-1. The results showed low to moderate heavy metal load in forest land and high to moderate load of heavy metals in the grass land and continuously cropped land.
A Combined Approach for a Privacy-Aware Digital Forensic Investigation in Enterprises

Stricter policies, laws and regulations for companies on the handling of private information arise challenges in the handling of data for Digital Forensics investigations. This paper describes an approach that can meet necessary requirements to conduct a privacy-aware Digital Forensics investigation in an enterprise. The core of our approach is an entropy-based identification algorithm to detect specific patterns within files that can indicate non-private information. Therefore we combine various approaches with the goal to detect and exclude files containing sensitive information systematically. This privacy-preserving method can be integrated into a Digital Forensics examination process to prepare an image which is free from private as well as critical information for the investigation. We implemented and evaluated our approach with a prototype. The approach demonstrates that investigations in enterprises can be supported and improved by adapting existing algorithms and processes from related subject areas to implement privacy-preserving measures into an investigation process.
Digital academic entrepreneurship: New opportunities for students in the development of the information environment

Purpose of the article. The purpose of the research is to analyze the opportunities of digital academic entrepreneurship provided to students in the context of the development of the information environment. Main results. To develop digital academic entrepreneurship, it is necessary to combine all available resources (human, organizational, financial) of existing research parks and departments for the development and support of entrepreneurship, create exemplary successful spin-off projects (subsidiaries created by employees or alumni of a university, based on technologies, the rights to which belong to the university), train students in entrepreneurial skills, and unlock scientific knowledge by institutions that are unable to ensure the practical use of their patents. Application of the study. The results of the work can be used in the organization of academic entrepreneurship at universities. The materials and conclusions of the study can be used in teaching the subjects of the business cycle in higher education.
Scale adaptive side window bilateral filter

Recently a filtering method based on side windows has been reported. Although this method has strong ability to preserve edge structure, its ability to smooth textures is weaker than using a full window. In this paper, we propose a scale adaptive side window based bilateral filter (SASWBF). An expanding ratio parameter is designed to control the side window varying to the full window. To adapt the size of spatial kernel at each pixel, the scale of filtering window is estimated using a structure measure. A bilateral filter using Fourier basis is adopted to accelerate the filter processing. The computational complexity of the proposed smoothing filter does not depend on the window size and thus is in almost constant time. Our experimental results demonstrates that the proposed filter performs well.
Distance Education. An Emerging Strategy for Education in the pandemic COVID19

This work shows the current situation of the pandemic due to COVID19 and its impact on Educational Institutions, forcing the adoption of emerging strategies to continue with the education of students, and thus prevent them from missing one or more school cycles (annually in basic education, semester or quarterly).The work shows antecedents of some pandemics and the measures taken by the Autonomous University of Aguascalientes, as well as the tools used in the adoption of distance education, and describes some of the actions to reduce the impact on the education of students.