Tool For Representation Research Articles

Le discours gastronomique et les identités culturelles sur Wikipédia

Language and food are tightly connected. As part of our daily experience, our culinary traditions and cultures are shaped by the discourses we create on them. Via translation, virtual and digital spaces have become instrumental sites for disseminating culinary discourses with deep roots in cultural history. As this study clearly shows, Wikipedia communities rely on a long history of translations and intercultural relations. From a discourse analysis perspective, this paper focuses on the representation of global French cuisine in four Wikipedia articles (French, Spanish, English, and Polish) dedicated to the prominent dish Boeuf bourguignon. Our corpus aims at shedding light on contemporary translation and discursive practices that contribute to representing cultural identities. By focusing on cultural-bound terms (culturemes), intertextuality, and multilingual sources, our study foregrounds translation as a tool for cultural representation beyond traditional source-text dichotomies.

Cartographies of Everyday Conflicts in Public Spaces. Informal Micro-activities on Formal Infrastructure. Carapungo Entry Park, Quito

Through the understanding of cartography as an alternative representation tool, this paper researches the existing and usually invisible relationships between informal micro-activities and formal public spaces. For this purpose, Carapungo Entry Park located in the north of Quito (Ecuador), is taken as a case study, being a paradigmatic case of the complexity and multiplicity that constitutes informality in Latin American cities. After a first analysis based on the formal planning of this park, we will focus on dissident spatial practices carried out by inhabitants who occupy and appropriate a formal space. These situations of conflict originate spatial constructions based on spontaneity, fluidity, adaptability, movement, and temporality, which include local culture, economy, and social interaction. With the production of cartographies, the processes and activities generated by formal and informal vendors, passers-by, and public transport passengers, are made visible and analyzed. The expected results based on cartography as an alternative representation, are the presentation of relations of tensions, forces, conflicts, and negotiations that allow us to identify patterns, trends and behaviors that have no place in the supposed precision and rigor of the regulations in the formal planning of public space.

E-Learning Methodology

E-learning is the most important explosion propelled by the internet transformation. It is the use of technology which enables people to learn anytime and anywhere. While teaching can be based in or out of the classrooms, the use of computers and Internet forms the major component of E-learning. It can be termed as a network enabled transfer of skills and knowledge, and the delivery of education is made to a large number of recipients at the same time. E-learning can offer effective instructional methods, such as practising with associated feedback, combining collaboration activities with self-paced study and personalizing learning paths based on learners’ needs. The focus of E-learning is on both asynchronous and synchronous methodology. It investigates three major E-learning tools which are (i) curriculum tools (ii) digital library tools and (iii) knowledge representation tools. This paper reports on the extent to which the effectiveness and students’ attitudes towards E-learning impacts on their learning styles. The paper also reviews literature and gives a scholarly background to the study by reviewing some contributions made by various researchers and institutions on the concept of E-learning. Finally, the paper suggests that synchronous tools should be integrated into asynchronous environments to allow for any-time learning model and gave remark that E-learning needs to improve from various barriers.

An integrated care pathway for maternal and childcare: evidence from Ethiopia, Tanzania, and Uganda

Abstract Performance monitoring and evaluation are key to quality improvement in maternal and child healthcare in Sub-Saharan Africa. This study presents the experience of designing and implementing bottom-up and integrated performance evaluation tools for care pathway to monitor and manage maternity healthcare services. The research project involved four health districts and relative reference hospitals, supported by the NGO Doctors with Africa CUAMM in Ethiopia, Tanzania, and Uganda. The maternal and childcare pathway developed consists of 23 indicators, calculated at hospital and district level, relating to pregnancy, childbirth and first year of life phases. The authors developed staves and performance maps, as graphical representation tools, to display longitudinally integrated health services provision performance along the continuum of care. Substantial variation was observed between the phases of each maternal and childcare pathway and across the care pathways of the different analysed settings. The most impressive results across the four settings are: 1) regarding pregnancy phase, that women tend to attend more than four antenatal classes, still with a quite high drop-out rate, and are largely tested for syphilis, 2) with respect to childbirth, that there are varying percentage levels in terms of C-sections, episiotomies and peri/intra-partum asphyxia cases, and 3) as it regards first year of life, there emerges scope for improvement considering the vaccination coverages attained for pentavalent, measles and polio vaccinations. Thanks to the collaboration with local managers and health professionals, the maternal and childcare pathway allowed to monitor the changes in the quality of maternity services provided within the analysed contexts. The benchmarking approach encouraged local professionals to learn from other settings. The use of such tool allowed the development of targeted quality improvement actions, shared among all involved stakeholders. Key messages • In collaboration with local professionals, we designed and implemented an integrated pathway for maternal and childcare, covering the phases of pregnancy, childbirth and first year of life. • Benchmarking performance results encouraged collaboration among professionals and allowed the identification of actions to improve the provision of maternal and childcare services.

Document classification as a theoretical problem of documentology

The changes and amendments to the general document classification as a theoretical problem of document studies and documentology, are discussed. The document in the meaning “recorded information” is the subject of classification. The author examines the faceted-block classification of document based on various characteristics united into six clusters: “Types of documents physical carrier”, “Types of documents by document acquisition circumstances”, “Types of documents by information representational and transfer tools (by signative component)”, “Types of documents by information reception (perceptive component)”, “Types of documents by their environmental circumstances”. The document classification within each facet is independent which enables to characterize any document in various parameters. The changes and amendments are made to the general document classification based on increasing number and weight of electronic documents including digital versions of originally non-digital documents. The refined general classification is to facilitate special classification in particular types (classes, groups) of documents. The general document classification is applicable to various scientific disciplines within documentology, and to teaching documentological disciplines.

A novel deep learning model based on target transformer for fault diagnosis of chemical process

Deep learning is a powerful tool for feature representation, and many methods based on convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been applied on fault diagnoses for chemical processes. However, unlike attention mechanisms, these networks are inefficient when extracting features of long-term dependencies. The transformer method employs a self-attention mechanism and sequence-to-sequence model originally designed for natural language processing (NLP). This approach has attracted significant attention in recent years due to its great success in NLP fields. The fault diagnosis of a chemical process is a task based on multi-variable time series, which are similar to text sequences with a greater focus on long-term dependencies. This paper proposes a modified transformer model called Target Transformer, which includes not only a self-attention mechanism, but also a target-attention mechanism for chemical process fault diagnoses. The Tennessee Eastman (TE) process was used to evaluate our method’s performance.

The Representation of Causality and Causation with Ontologies: A Systematic Literature Review.

To explore how disease-related causality is formally represented in current ontologies and identify their potential limitations. We conducted a systematic literature search on eight databases (PubMed, Institute of Electrical and Electronic Engendering (IEEE Xplore), Association for Computing Machinery (ACM), Scopus, Web of Science databases, Ontobee, OBO Foundry, and Bioportal. We included studies published between January 1, 1970, and December 9, 2020, that formally represent the notions of causality and causation in the medical domain using ontology as a representational tool. Further inclusion criteria were publication in English and peer-reviewed journals or conference proceedings. Two authors (SS, RM) independently assessed study quality and performed content analysis using a modified validated extraction grid with pre-established categorization. The search strategy led to a total of 8,501 potentially relevant papers, of which 50 met the inclusion criteria. Only 14 out of 50 (28%) specified the nature of causation, and only 7 (14%) included clear and non-circular natural language definitions. Although several theories of causality were mentioned, none of the articles offers a widely accepted conceptualization of how causation and causality can be formally represented. No current ontology captures the wealth of available concepts of causality. This provides an opportunity for the development of a formal ontology of causation/causality.

Set-membership estimation based on ellipsoid bundles for discrete-time LPV descriptor systems

This paper considers set-membership estimation for discrete-time linear parameter-varying descriptor systems. Ellipsoid bundle, a new set representation tool combining certain characteristics of ellipsoids and zonotopes, is used to design a set-membership estimation method for the considered systems. We use the L∞ technique to design the estimator parameters in order to optimize estimation accuracy. This paper also studies the stability problem of the proposed method and establishes an offline sufficient stability condition. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.

Theatre as Installation in the Syndemic Architectures of Rimini Protokoll and Battersea Arts Centre

This essay proposes a theory of (post)-pandemic performance that reconceives the theatre, via its buildings, as installation. Innovations designed to navigate theatre-making within the context of pandemic, and the imperatives of online and physically distanced productions, open new perspectives on theatre’s projects and venues. Taking installation as its primary optic, the essay reviews two recent performance events: Black Box, a physically distanced audio tour staged by Berlin-based theatre company Rimini Protokoll at Schauspiel Stuttgart in 2021, and The Way Out (2020), a digital performance directed by British filmmaker Suri Krishnamma and recorded at Battersea Arts Centre, London. These productions restage entire arts centers as installational encounters to explore how theatre might address itself to its histories and futures. Taking the form of theatrical tours, the events encompass areas beyond the stage that are functional or transitional, raising questions not only about how we move through specific performance spaces, but also how we position ourselves in relation to theatre’s institutions. In (post)-syndemic theatre, the installational thus gives view onto both the physical-material of theatre’s buildings and representational tools, and the institutional in its structures of power.

Synthesis of a novel pyrazole heterocyclic derivative as corrosion inhibitor for low-carbon steel in 1M HCl: Characterization, gravimetrical, electrochemical, mathematical, and quantum chemical investigations

A novel organic corrosion inhibitor, named 3, 5-dimethyl-1H-pyrazol-1-yl m (4-((4-hydroxybenzylidene) amino) phenyl) methanone (DPHM) has been effectively synthesized and characterized. The diagnosis of functional groups and constituents of DPHM has been conducted by FTIR, 1H NMR, and 13C NMR. The inhibitor efficacy for low-carbon steel in 1 M HCl was evaluated by using weight loss and electrochemical techniques. The inhibition efficiency was increased with increasing the temperature and DPHM concentrations. The inhibition efficiency approaches a maximum value of 89.5% at 400 ppm of DPHM and 60 °C. The efficiency of the inhibitor was attributed to the formation of a protective mono-layer on the steel surface. The Langmuir adsorption isotherm was used to inspect the adsorption process mechanism. Theoretical quantum chemical simulations were used to investigate the mechanism of inhibition. The results revealed that the DPHM was the donor of electron, while the steel surface was an electron acceptor. Mathematical and statistical modelling were used as powerful tool for data representation. Exponential model, with 0.992 correlation coefficient, was the most accurate one.

Viscoelastic or viscoplastic glucose theory (vgt #85): a study on the influences of cardiovascular disease risk (cvd risk), estimated daily average glucose (eag), and body weight (bw) from a type 2 diabetes patient’s psychological reactions and lifestyle changes during 9-quarters of the covid-19 pandemic period from y2020q1 to y2022q1 based on gh-method: math-physical medicine, especially the vgt energy tool (no.

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory (VGT), he suddenly realized that there is a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms), in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of biomedical impact or inter-relationship from this COVID pandemic had on some of his collected (eAG and BW) or calculated (CVD Risk) biomarkers. Therefore, in this article, he selects a chain of mutually influenced biomarkers of the cardiovascular disease risk % (CVD risk), estimated daily average glucose (eAG), and body weight (BW) along with the COVID-19 infection cases in the USA as the key input variable to conduct a series of inter-connected VGT analysis research work.

Viscoelastic or viscoplastic theory (VGT #83): A study of influences on consumer price index resulted from consumer psychological reactions and consumption behavior change during the COVID-19 pandemic 9-quarters period from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 673)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all of the biomedical variables are changing from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. From 1980 to 1981, the author attended a college in California for his MBA degree, emphasizing finance and marketing. In addition, he spent many years managing a successful high-tech semiconductor business in Silicon Valley, where it involved many key factors of economics and finance, such as gross domestic product (GDP), inflation rate, consumer price index (CPI), NASDAQ stock performance, price-earnings ratio (P/E ratio), various investment decisions, return on investments (ROI), etc. As a result, money subjects associated with finance and economics are not unfamiliar subjects to him. In addition, during the 9 years from 2002 to 2010, he self-studied psychology and established 4 psychotherapy centers to take care of 200+ abused women and abandoned children. Therefore, he has accumulated a considerable amount of knowledge on psychological behaviors, especially from the field of clinical psychology of abused victims. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he suddenly realized that there is a strong similarity between medicine and economics. The behaviors and patterns of economic variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms), in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of economic impact or inter-relationship from this pandemic had on some of the current economic indices. Therefore, in this article, he selects the CPI of US cities as the output variable along with the COVID-19 death and infection cases in the USA as two input variables to conduct his combined study of both economics and medicine.

Viscoelastic or viscoplastic theory (VGT #84): A comparison study of the influences on the gross domestic product (GDP), inflation rate, and consumer price index (CPI) in the USA resulting from consumer psychological reactions and spending behavior changes over 9-quarters during the COVID-19 pandemic period from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 674)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships on a selected medical output (symptom) versus either singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. From 1980 to 1981, the author attended a college in California for his MBA degree, emphasizing finance and marketing. In addition, he spent many years managing a successful high-tech semiconductor business in Silicon Valley, where it involved many key factors of economics and finance, such as gross domestic product (GDP), inflation rate, consumer price index (CPI), NASDAQ stock performance, price/earnings ratio (P/E ratio), various investment decisions, return on investments (ROI), etc. As a result, he has a strong background in money topics associated with finance and economics. In addition, during the 9 years from 2002 to 2010, he self-studied psychology and established 4 psychotherapy centers to take care of 200+ abused women and abandoned children. Therefore, he has accumulated a considerable amount of knowledge on psychological behaviors, especially in the field of clinical psychology of abused victims. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he suddenly realized a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms) in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics.

Networked Knowledge and Complex Networks: An Engineering View

Along with the development of information technologies such as mobile Internet, information acquisition technology, cloud computing and big data technology, the traditional knowledge engineering and knowledge-based software engineering have undergone fundamental changes where the network plays an increasingly important role. Within this context, it is required to develop new methodologies as well as technical tools for network-based knowledge representation, knowledge services and knowledge engineering. Obviously, the term “network” has different meanings in different scenarios. Meanwhile, some breakthroughs in several bottleneck problems of complex networks promote the developments of the new methodologies and technical tools for network-based knowledge representation, knowledge services and knowledge engineering. This paper first reviews some recent advances on complex networks, and then, in conjunction with knowledge graph, proposes a framework of networked knowledge which models knowledge and its relationships with the perspective of complex networks. For the unique advantages of deep learning in acquiring and processing knowledge, this paper reviews its development and emphasizes the role that it played in the development of knowledge engineering. Finally, some challenges and further trends are discussed.

Viscoelastic or Viscoplastic Glucose Theory (VGT #85): A Study on the Influences of Cardiovascular Disease Risk, Estimated Daily Average Glucose, and Body Weight from a Type 2 Diabetes Patient’s Psychological Reactions and Lifestyle Changes During 9-Quarters of the COVID-19 Pandemic Period from Y2020Q1 to Y2022Q1 Based on GH-Method: Math-Physical Medicine, Especially the VGT Energy Tool (No. 675)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus either singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their asso- ciated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Profes- sor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he sud- denly realized a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms) in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of biomedical impact or inter-relationship from this COVID pandemic had on some of his collected (eAG and BW) or calculated (CVD Risk) biomarkers. Therefore, in this article, he selects a chain of mutually influenced biomarkers of the cardiovascular disease risk % (CVD risk), estimated daily average glucose (eAG), and body weight (BW) along with the COVID-19 infection cases in the USA as the key input variable to conduct a series of inter-connected VGT analysis research work.

Physiological and cognitive discontinuities: From mythical mediation to implicit discretization of architectural design tools

In architectural design, representation tools are often compared according to their alleged effects on the creativity of designers. Moreover, their mediating capacities are often mythicized, to such an extent that one might surmise the direct transmission of the mental images from the designer's consciousness to an external representation. In this speculative essay, we demonstrate that the process of representation at work in architectural design originates from the designer's consciousness natural cognitive ability, rather than from the use of a specific mediation tool between the designer and his environment, between the mentally constructed architectural project and its representation. The effects of any tool of representation—analog or digital—on our perceptual apparatus depend primarily on the cognitive mechanisms affecting the discontinuous flow of internal representations formed by our consciousness. In other words, we propose to shed a new light on these limitations through the heuristic modeling of an architectural project designer confronted with his own cognitive biases, and the limits of the representation processes. In the present essay, the discontinuities and uncertainties inherent to the processes of representation are reintegrate in the models.

TAKSONOMI BERPIKIR SPASIAL (TAXONOMY OF SPATIAL THINKING) DAN KESESUAIANNYA DI SMAN 1 TOMOHON

One measure of the impact of a new idea in geography education is how well the idea is put into everyday practice. Spatial thinking skills are actually not a new idea in geography education; Spatial analysis has long been one of its core traditions but the use of the term is new and has only just begun to be widely used. Spatial thinking skills are the use of spatial concepts such as distance, direction, and area; representational tools such as maps and graphs; along with appropriate thought processes, to conceptualize and solve problems. The aim of this article is to help teachers incorporate spatial thinking into their instruction through a concrete tool, the taxonomy of spatial thinking, applied to tried and true strategies of pedagogical questioning, both in text and in a classroom context. Our main premise is that students' spatial thinking can, and should, be facilitated by the careful design, selection, and use of questions.

A Novel Approach for the Recruitment Process in Human Resources Management

Discovering and using valuable and meaningful data which is hidden in large databases can have strategic importance in the managerial decision-making process for organizations to gain competitive advantage. With the increasing data flow, it has become more difficult for organizations to store this data and gain useful knowledge to manage their business operations and functions. A knowledge discovery process that is based on data mining methods has widely been used in business operations and management functions. This paper investigates formal concept analysis which is a powerful tool in knowledge representation and discovery and explains association rule mining based on formal concept analysis. An experimental study is given for employee selection function of HRM by using formal concept analysis method to model the qualifications of candidates which are needed for the job position. The qualifications of the candidates are modelled with concept lattices, and the qualifications of the candidates are matched with the ones determined in the job specification.

Identifying ATT&CK Tactics in Android Malware Control Flow Graph through Graph Representation Learning and Interpretability (Student Abstract)

To mitigate a malware threat it is important to understand the malware’s behavior. The MITRE ATT&ACK ontology specifies an enumeration of tactics, techniques, and procedures (TTP) that characterize malware. However, absent are automated procedures that would characterize, given the malware executable, which part of the execution flow is connected with a specific TTP. This paper provides an automation methodology to locate TTP in a sub-part of the control flow graph that describes the execution flow of a malware executable. This methodology merges graph representation learning and tools for machine learning explanation.

Self-Communicating Deep Reinforcement Learning Agents Develop External Number Representations

Symbolic numbers are a remarkable product of human cultural development. The developmental process involved the creation and progressive refinement of material representational tools, such as notched tallies, knotted strings, and counting boards. In this paper, we introduce a computational framework that allows the investigation of how material representations might support number processing in a deep reinforcement learning scenario. In this framework, agents can use an external, discrete state to communicate information to solve a simple numerical estimation task. We find that different perceptual and processing constraints result in different emergent representations, whose specific characteristics can facilitate the learning and communication of numbers.