Three-layered Approach Research Articles

FamLink2 – A comprehensive tool for likelihood computations in pedigrees analyses involving linked DNA markers accounting for genotype uncertainties

There is an increasing demand for software that can handle an arbitrary number of linked markers in forensic genetics; primarily with application to inference of relationships and direct matching but also in applications such as ancestry inference and mixture interpretation. With the emergence of sequencing technologies, denser sets of SNP markers are generated and analyzed. Additionally, sequence data of low quality and quantity DNA generate uncertainty about the underlying true genotype. We provide an efficient implementation of a general model for pedigree likelihood computations with genetic marker data using a three-layered approach. The top and first layer is the population model where allele frequencies and population substructure are accounted for. The second layer is the inheritance model which efficiently handles linked markers using an IBD model. The third and bottom layer is the observational level where we model the likelihood of the true genotype given underlying reads as well as parameters for errors. We exemplify the utility of our implementation as well as provide validation according to guidelines established by the ISFG using a combination of two published SNP panels. We demonstrate that computations are feasible for panels encompassing 10,000 markers and we argue that, due to the properties of the underlying algorithm, extending the number of markers will result in a linear increase in computation time. In addition we study the impact of parameters used in our model and suggest some guidelines pertaining to their values. The results demonstrate that a probabilistic model for low coverage sequence read data is needed instead of relying on an a threshold based genotype and applying our general model for inference of relationships on a real case can be superior, i.e. higher information content, to other methods relying on either fixed genotypes with low quality sequence data or simple pair wise relationship tests. In summary, the implementation, FamLink2 (freely available at https://famlink.se), can jointly handle genetic linkage, genotype uncertainty and population substructure for an arbitrary pedigree with data for any number of individuals. Whereas the current study will focus on calculations disregarding mutations, FamLink2 has the ability to model mutations for certain built-in pedigrees.

Micro-meso-macro framework: a three-layered approach to understand brand pride

Purpose This study aims to develop a micro-meso-macro framework of brand pride to understand brand pride, its forms, characteristics and the interdependence of this construct, in a comprehensive manner. Design/methodology/approach Literature in brand pride has been systematically extracted, analysed and evaluated, to propose an integrated framework which presents a holistic view of brand pride. Findings At the micro level, brand pride is associated with owning individual level characteristics such as personality, culture, values, beliefs and motivation action and behaviour of the individual; at the meso level, brand pride is associated with characteristics at brand level, actions and behaviour such as brand personality, brand value and image. At the macro level, brand pride is associated with brand interactive characteristics, actions and behaviour, at a broader network of systems and environment such as brand responsible behaviour and brand’s adaptability in creating a robust network in uncertainty. Originality/value This paper identifies brand pride as a useful connecting point between brands and the surrounding environment, to achieve a more sustainable branding practice. Although previous researchers explored its effects on brand loyalty in various contexts, a comprehensive, holistic model for enhancing brand pride, suitable for application at various situations and various levels, was missing. This research fills this gap through a unique contribution by proposing a micro-meso-macro framework, which is a three-layered approach to brand pride.

Multi-agent cloud based license plate recognition system

This paper presents a multi-agent license plate recognition system, specifically designed to address the diverse and challenging nature of license plates. Utilizing a multi-agent architecture with agents operating in individual Docker containers and orchestrated by Kubernetes, the system demonstrates remarkable adaptability and scalability. It leverages advanced neural networks, trained on a comprehensive dataset, to accurately identify various license plate types under dynamic conditions. The system’s efficacy is showcased through its three-layered approach, encompassing data collection, processing, and result compilation, significantly outperforming traditional license plate recognition (LPR) systems. This innovation not only marks a technological leap in license plate recognition but also offers strategic solutions for enhancing traffic management and smart city infrastructure globally.

Ulusötesi Ailelere Kavramsal Bir Açılım: Sıradışı Uzak Mesafe Aileler

Transnational families are among the by-products of global capitalism, the feminization of migration and the globalization of care work. Transnational families owe their existence to the rise of communication and transportation technologies, economic transformations, and cultural features in their countries of origin and destination. A transnational family is different from an ordinary immigrant family. The defining factor is not the act of cross-border movement of the family, but the dispersion of the family, nuclear or extended, across international borders, where different family members spend time in one or another country depending on various factors. The emergence of transnational family experience relates to economic, political, social, and cultural factors, and has far-reaching causes and consequences. This study offers a new conceptual approach to the discussion of transnational families departing from Judith Stacey’s (1996) “postmodern family condition”. As a family arrangement made possible in the postmodern family condition, transnational families better describe situations in which families are not visible yet not absent, not necessarily broken but separated. Transnational families require a whole new understanding and definition of familial relationships, which should focus on the fluid nature of those in the absence of a concrete family setting. The role of immigrant women in such a family structure stands as a challenge to the stereotypical “modern family” as defined by Stacey; hence, enabling the conceptualization of transnational families as part of the postmodern condition. The impact transnational family experience has on various actors involved is examined by asking some fundamental questions such as: How are the decisions concerning who migrate under what conditions taken? How does the transnational family experience affect gender relations? What are the global and local conditions that make this experience possible? This study employs a three-layered approach to analyze the issue. First, the structural backdrop to transnational families is analysed; namely, the expansion of global capitalism that feeds female labour migration and the demand for the service sector, especially domestic care services. Second, the changes in the concept of family due to societal structural transformations and the emergence of new family forms are discussed. Third, the consequences of the first two aspects of the experience of transnational family life and its impact on parties involved at various levels are analysed: providers of care work and their families (parents, children, and extended family members), receivers of care work (employers and their families), and mediators of global care work (agencies and states).

Evaluating provincial carbon emission characteristics under China’s carbon peaking and carbon neutrality goals

This study defines Provincial Carbon Emission Characteristics (PCEC) as the socioeconomic conditions influencing provincial carbon emissions, the potential for carbon neutrality, and carbon management strategies. Given China’s commitment to peak carbon emissions and to achieve carbon neutrality, the development of a robust and versatile PCEC evaluation system is imperative. However, previous studies that rely on single-objective evaluation models are limited. To address this gap, we propose a multi-objective PCEC evaluation system using a novel three-layer approach. This approach enhances the scientific rigor, comprehensiveness, and comparability of PCEC evaluation indicators (PCEC-EIs) by segregating the extraction process into three layers: (1) a factor layer, which identifies critical socioeconomic conditions; (2) a quantitative layer, which selects optimal quantitative indicators for each identified condition; and (3) a standardized layer, which standardizes these indicators, thereby improving their comparability. By applying hierarchical cluster analysis, our study classified 30 Chinese provinces into 7 distinct clusters, each with unique carbon emission characteristics. Further investigation of these clusters across various climate governance issues revealed the versatility of our multi-objective PCEC evaluation system. Our system supports the identification of provinces qualified to reach the emission peak earlier than 2030, differentiation of carbon intensity reduction efforts during the carbon peaking stage, and exploration of various emission reduction pathways to achieve carbon neutrality. Hence, our findings can guide the creation of bespoke emission-reduction strategies for each province; thus, aiding China’s national ambition to achieve peak carbon emissions and carbon neutrality. Importantly, our three-layered approach has broader implications beyond China, potentially assisting other regions or countries in grappling with similar climate-mitigation challenges.

Tourist encounters with a “GoPro”: three layers of hike&fly paragliding travels

Hike&fly is a recent development in adventure tourism combining cross-country paragliding flights with hiking in remote destinations and is currently under-researched as a relatively new tourism phenomenon. As it highly intersects with media technologies such as the GoPro, the paper explores how this media technology can introduce new ways of studying mobile tourist practices from a more-than-representational perspective. By drawing on work in mobility and media studies, the paper argues that the GoPro does not simply record the subjective viewpoints of the users and their environment but also modifies how users encounter and make sense of destinations. Through challenging the former notion, the paper makes two contributions to tourism geographies: First, the paper provides background – based on preliminary fieldwork – on the recent development of hike&fly paragliding travels and the role of GoPro in the context of adventure tourism. Secondly, it contributes a methodological framework for further studies on tourist encounters with a “GoPro” by proposing a three-layered approach that considers the GoPro’s ability to augment the human body, record a video trace, and generate somatic images.

Three-layered approach utilizing pedicled buccal fat pad in surgical closure of chronic oroantral fistula: A case series study.

Three-layered approach utilizing pedicled buccal fat pad in surgical closure of chronic oroantral fistula: A case series study.

The dual face of structural object case: on Lithuanian genitive of negation

We analyze genitive of negation (GN) in Lithuanian. When the verb is negated, GN is realized on an object that would otherwise be realized as accusative. We demonstrate that Lithuanian GN is a syntactic (in line with Arkadiev 2016) and morphological phenomenon in contrast to Russian GN, whose realization is influenced by semantic factors (e.g. Kagan 2013). It differs from Russian (Pesetsky 1982) in that (i) it is always assigned to a DP which would otherwise bear structural accusative regardless of its semantic properties, and (ii) it cannot affect a structural nominative DP regardless of whether it is an external or internal argument. Lithuanian GN, in this respect, is similar to Polish GN (e.g. Przepiórkowski 2000, Witkoś 2008). We offer a three-layered approach to case, arguing that GN is a reflection of structural object case, assigned in syntax, then translated to morphological genitive case at PF and, finally, realized at Vocabulary Insertion (Halle & Marantz 1993). Thus, structural object case has two morphological realizations: as genitive under negation or as accusative in the absence of negation. Lithuanian also exhibits long-distance GN (Arkadiev 2016), showing that case boundaries can cross non-finite clauses without an overt CP element, suggesting these are not phases.

Auditing large language models: a three-layered approach

AbstractLarge language models (LLMs) represent a major advance in artificial intelligence (AI) research. However, the widespread use of LLMs is also coupled with significant ethical and social challenges. Previous research has pointed towards auditing as a promising governance mechanism to help ensure that AI systems are designed and deployed in ways that are ethical, legal, and technically robust. However, existing auditing procedures fail to address the governance challenges posed by LLMs, which display emergent capabilities and are adaptable to a wide range of downstream tasks. In this article, we address that gap by outlining a novel blueprint for how to audit LLMs. Specifically, we propose a three-layered approach, whereby governance audits (of technology providers that design and disseminate LLMs), model audits (of LLMs after pre-training but prior to their release), and application audits (of applications based on LLMs) complement and inform each other. We show how audits, when conducted in a structured and coordinated manner on all three levels, can be a feasible and effective mechanism for identifying and managing some of the ethical and social risks posed by LLMs. However, it is important to remain realistic about what auditing can reasonably be expected to achieve. Therefore, we discuss the limitations not only of our three-layered approach but also of the prospect of auditing LLMs at all. Ultimately, this article seeks to expand the methodological toolkit available to technology providers and policymakers who wish to analyse and evaluate LLMs from technical, ethical, and legal perspectives.

Auditing Large Language Models: A Three-Layered Approach

Auditing Large Language Models: A Three-Layered Approach

Preliminary Experimental Results of Context-Aware Teams of Multiple Autonomous Agents Operating under Constrained Communications

This work presents and experimentally tests the framework used by our context-aware, distributed team of small Unmanned Aerial Systems (SUAS) capable of operating in real time, in an autonomous fashion, and under constrained communications. Our framework relies on a three-layered approach: (1) an operational layer, where fast temporal and narrow spatial decisions are made; (2) a tactical layer, where temporal and spatial decisions are made for a team of agents; and (3) a strategical layer, where slow temporal and wide spatial decisions are made for the team of agents. These three layers are coordinated by an ad hoc, software-defined communications network, which ensures sparse but timely delivery of messages amongst groups and teams of agents at each layer, even under constrained communications. Experimental results are presented for a team of 10 small unmanned aerial systems tasked with searching for and monitoring a person in an open area. At the operational layer, our use case presents an agent autonomously performing searching, detection, localization, classification, identification, tracking, and following of the person, while avoiding malicious collisions. At the tactical layer, our experimental use case presents the cooperative interaction of a group of multiple agents that enables the monitoring of the targeted person over wider spatial and temporal regions. At the strategic layer, our use case involves the detection of complex behaviors, i.e., the person being followed enters a car and runs away, or the person being followed exits the car and runs away, which require strategic responses to successfully accomplish the mission.

Using DRG to analyze hospital production: a re-classification model based on a linear tree-network topology


 Background: Hospital discharge records are widely classified through the Diagnosis Related Group (DRG) system; the version currently used in Italy counts 538 different codes, including thousands of diagnosis and procedures. These numbers reflect the considerable effort of simplification, yet the current classification system is of little use to evaluate hospital production and performance.
 Methods: As the case-mix of a given Hospital Unit (HU) is driven by its physicians’ specializations, a grouping of DRGs into a specialization-driven classification system has been conceived through the analysis of HUs discharging and the ICD-9-CM codes. We propose a three-folded classification, based on the analysis of 1,670,755 Hospital Discharge Cards (HDCs) produced by Lombardy Hospitals in 2010; it consists of 32 specializations (e.g. Neurosurgery), 124 sub-specialization (e.g. skull surgery) and 337 sub-sub-specialization (e.g. craniotomy).
 Results: We give a practical application of the three-layered approach, based on the production of a Neurosurgical HU; we observe synthetically the profile of production (1,305 hospital discharges for 79 different DRG codes of 16 different MDC are grouped in few groups of homogeneous DRG codes), a more informative production comparison (through process-specific comparisons, rather than crude or case-mix standardized comparisons) and a potentially more adequate production planning (considering the Neurosurgical HUs of the same city, those produce a limited quote of the whole neurosurgical production, because the same activity can be realized by non-Neurosugical HUs).
 Conclusion: Our work may help to evaluate the hospital production for a rational planning of available resources, blunting information asymmetries between physicians and managers. 

A three-layer system to win the war against COVID-19 and invest in health systems of the future

The COVID-19 pandemic taught us many lessons, most critically that its human and economic toll would have been significantly smaller if countries had in place strong layers of defence that...

Understanding and recommending security requirements from problem domain ontology: A cognitive three-layered approach

Socio-technical systems (STS) are inherently complex due to the heterogeneity of its intertwined components. Therefore, ensuring STS security continues to pose significant challenges. Persistent security issues in STS are extremely critical to address as threats to security can affect entire enterprises, resulting in significant recovery costs. A profound understanding of the problems across multiple dimensions of STS is the key in addressing such security issues. However, we lack a systematic acquisition of the scattered knowledge related to design, development, and execution of STS. In this work, we methodologically analyze security issues from a requirements engineering perspective. We propose a cognitive three-layered framework integrating various modeling methodologies and knowledge sources related to security. This framework helps in understanding essential components of security and making recommendations of security requirements regarding threat analyses and risk assessments using Problem Domain Ontology (PDO) knowledge base. We also provide tool support for our framework. With the goal-oriented security reference model, we demonstrate how security requirements are recommended based on PDO, with the help of the tool. The organized acquisition of knowledge from SME groups and the domain working group provides rich context of security requirements, and also enhances the re-usability of the knowledge set.

A Tool to Extract Name Entity Recognition From Big Data in Banking Sectors

Generally, the Internet is the global system of interconnected computer networks, connecting millions of computers as well as people, and thus generates a massive quantity of information on a daily basis. This leads to extracting the necessary information using information filtering (IF) in several domains. In our implementation, the named entity recognition (NER) technique is employed to automatically extract valuable data from the unstructured natural language texts. As several works has been outlined in detecting named entities, plenty of very different NER tools exist for several domains. However, NER remains a giant challenge so to solve this problem we proposed a novel framework by combining three efficient classifiers. This article proposes a three-layered neural network approach with conditional random field (CRF), the Pachinko allocation model (PAM), and the Adaptive Neuro-Fuzzy Inference System (ANFIS) for detecting named entities in three steps. First, a classifier based on CRF is employed to train the input file. Second, PAM is employed to boost the previous output created by CRF to enhance the label annotation. Third, the ANFIS captures the deep features of the information by itself from the pre-trained information to attain accurate predictions. Experimental results show that the learned model yields a banking domain with a recall rate of 92%, a precision rate of 95% and F-measure of 92% by implementing it in the R Platform.

Multiobjective Mission Route Planning Problem: A Neural Network-Based Forecasting Model for Mission Planning

This paper presents a three-layered approach for the mission route planning problems involving a team of autonomous vehicles where they have to collectively navigate to a number of target locations in an environment with both static and dynamic obstacles. The first layer computes the maximum distance that need to be traveled to complete a mission by a team of vehicles. We have developed a nearest-neighbor-search based approach to assign closely located tasks to each vehicle in the team. We developed a stochastic optimization based path planning algorithm that can compute the collision-free (with both static and dynamic obstacles) trajectory for a vehicle to navigate from start to the target location. By combining task assignment with path planning algorithm, we can estimate the maximum traveled distance for a mission with a team of vehicles. The second layer determines the optimal number of vehicles required for a mission based on any user defined constraint by casting it as a multiobjective optimization problem with two competing objectives, i.e. time vs cost. The methods derived in layer one are utilized to evaluate the objective functions in layer two. Finally, we have proposed a data driven neural network-based prediction model that will forecast the mission completion time with a reasonable accuracy which will utilize the historical information of the previous missions. The forecasting model is intended to facilitate the effective planning of parallel and subsequent missions. We have demonstrated the effectiveness of our approach with numerical simulation results for every layer mentioned above.

An Overview of Indicators and Indices Used for Urban Mobility Assessment

The urban mobility is affected by global trends resulting in a growing passenger and freight transport demand. In order to improve the understanding of urban mobility in general, to evaluate mobility services and to quantify the overall transport system performance, it is necessary to assess urban mobility. Urban mobility assessment requires the application of methodology integrating different metrics and explicitly applying a multi-dimensional approach. Since scientific community does not define urban mobility in an unambiguous way, part of this paper is devoted to the analysis of the definition of urban mobility. This step enables better understanding of urban mobility in general, as well as understanding of the urban mobility assessment process. Usually, a three-layered approach that includes urban mobility data, indicators and indices is used for the assessment. Therefore, the aim of this paper was to perform extensive research in order to synthesize, define and organize the elements of those layers. The existing urban mobility indicators and indices have been developed for specific urban areas, taking into account local specifications, and they are not applicable in other cities. Also, the choice of urban mobility indicators is mainly related to the existence of data sources, which limits the objective and comparable assessment of the mobility of cities where such data do not exist.

Energy Efficient Mobile Data Collection in Three Layered Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are widely used for different applications such as monitoring and surveillance in both civilian and military domains. Mobile data collection has significant impact on the performance of WSN. Therefore it is essential to have mechanisms to improve it. In this paper we proposed a three-layered approach that is used to collect data in wireless sensor network. The three layers include sensor layer which is made up of collection of sensors, cluster head layer which is made up of all cluster heads, and the mobile collector layer. The proposed approach also takes care of distributed load balanced clustering. The aim of the proposed approach is to achieve scalable solution with low data collection latency and energy efficiency. While sensors are organized into clusters the distributed algorithm is applied so as to ensure that the efficiency of the network is achieved. We built a prototype application using Microsoft .NET which simulates the proposed approach. The empirical results revealed that the proposed layered approach is energy efficient, scalable and achieves low latency in data collection.

Let’s stop the enemy!

In April 2017, the Hungarian government launched a national consultation entitled ‘Let’s stop Brussels’ focusing on topical issues such as Brussels’ prohibition of reductions in household utility charges; illegal immigration; foreign attempts to influence the domestic political scene; Brussels’ attacks on tax reductions and job creation programmes in Hungary. The present study investigates whether there is any extent of manipulation applied in the questionnaire of the consultation sent to Hungarian eligible voters by using van Dijk’s (2006) triangulated Critical Discourse Analytical (CDA) approach. Van Dijk’s three-layered approach to the investigation of manipulation in discourse is an integrated theory that establishes links between three different dimensions of manipulation: society, cognition and discourse. A CDA framework allows a text to be evaluated as manipulative in terms of its context categories rather than merely in terms of its textual elements. Accordingly, the presence of manipulation in the discourse of the national consultation is explored by examining the balance in its participants and in the information shared; by considering its influence on social cognition; and by revealing the rhetorical techniques applied in the discourse of the set of questions. The results of the study show that various techniques of manipulation were applied in all the three layers of the discourse of the consultation.

Perception of (im)politeness and the underlying cultural conceptualisations

Abstract The present study sets out to investigate the role of ‘culture’ as one of the many important factors that influence the evaluation of (im)politeness in Persian from a Cultural Linguistics perspective. The paper argues that Cultural Linguistics, and in particular the notion of cultural schema, has the potential to offer a robust analytical framework for the exploration of (im)polite use of language. We elaborate on this proposal by presenting examples of data from Persian in which speakers interpret impolite behaviour in light of a number of Persian cultural schemas. The study also offers a novel three-layered approach for the analysis of (im)politeness data that combines metadiscourse analysis with the ethnography of cultural conceptualisations, while highlighting the importance of the notion of ‘heterogeneous distribution’ of cultural conceptualisations, a pivotal theoretical concept in Cultural Linguistics which accounts for the variations in speakers’ evaluation of (im)politeness.