Miracle-dz/UniFAR-FTUs huggingface dataset:
Using difference in intersectional research with im/migrant and racialized sex workers

Intersectionality attends to the interactions between social difference and power, although theoretical models vary in their emphasis on one or the other. Difference-centred models often distinguish between processes of constructing social difference, systems that institutionalize social difference and identities that include social difference. This article discusses the analytical expectations that can emerge in intersectional research that focus on difference, by analysing the use and construction of difference by im/migrant and racialized women in sex work. The first analytical expectation is the distinction between salience and difference when starting from the lived realities and voices of individuals, groups and communities. The second analytical expectation concerns the interaction between two intersectional methodologies, between identities and lived experiences, and processes of constructing difference.
Mathematical modeling and analysis of a vehicle crash

Because of the fact that vehicle crash tests are complex and complicated experiments it is advisable to establish their mathematical models. This paper contains an overview of the kinematic and dynamic relationships of a vehicle in a collision. There is also presented basic mathematical model representing a collision together with its analysis. The main part of this paper is devoted to methods of establishing parameters of the vehicle crash model and to real crash data investigation i.e. - creation of a Kelvin model for a real experiment, its analysis and validation. After model's parameters extraction a quick assessment of an occupant crash severity is done.
Workflow Modelling and Execution with Coloured Petri Nets in COSM

Modern distributed organisations use data communication increasingly fast, globaly and at decreasing costs. Such developments facilitate flexible access to decentralized services in open networks and also allow coordination of complex interorganizational tasks as distributed applications. This paper descibes concepts and recent extensions to the distributed systems architecture COSM (Common Open System Market) which supports design, implementation, and execution of both access to arbitrary services in open networks and concurrent workflow modelling. Formal basis of the workflow model are Coloured Petri Nets (CPN) which provide powerful means to specify and verify activity coordination in concurrent environments. CPN specifications, however, usually lack automated tool support for transforming them into efficiently executable applications. COSM, on the other hand already provides a generic platform to manage distributed sewrvices (i.e. their properties, interfaces, etc.) in order to enable human users to engage easily ad-hoc sessions with arbitrary service providers in open network environments. Extending COSM service descriptions with CPN workflow representations integrates dynamic workflow modeling into the system support COSM service management platform.It could therefore help to bridge the gap between concrete system support for open distributed applications and formal models of concurrent workflow specifications. This paper presents both a brief review of COSM concepts and prototype implementation details of its first CPN extensions, motivated by a workflow example from a real-world project environment.
RECONFIGURATION MANEUVER EXPERIMENTS USING THE SPHERES TESTBED ONBOARD THE ISS

This paper presents recent results of reconfiguration maneuver experiments performed onboard the International Space Station (ISS) using the SPHERES testbed of the MIT Space Systems Laboratory (SSL). These experiments were designed using two different two-stage path planning algorithms previously developed by the authors to solve the general multispacecraft translation and rotation reconfiguration maneuver problem with coupled constraints. This problem is particularly difficult because of the nonlinearity of the attitude dynamics, the non-convexity of some of the constraints, and the coupling between the positions and attitudes of all spacecraft. Flight data are shown in this paper and compared to the theoretical results. The success of these experiments validate the results of the two-stage algorithms. This paper also lists the lessons learnt from these experiments, which will be used to improve future SPHERES ISS reconfiguration maneuvers.
Estimating processor performance of library function

Fast estimation of processor performance can easily lead to large savings in time which would otherwise be spent in long time consuming execution on an instruction set simulator. The estimation of standard library functions are made difficult by the fact that standard libraries are sometimes delivered as binary files, which makes use of an instruction set simulator, the only option for performance estimation. In this paper, we present an estimation methodology which does not require execution of an application on an instruction set simulator. We use simple mathematical model of performance of standard library function which relates the number of instruction executed to the size/number of arguments passed.
View-invariant person re-identification with an Implicit Shape Model

In this paper, we approach the task of appearance based person re-identification for scenarios where no biometric features can be used. For that, we build on a person re-identification approach that uses the Implicit Shape Model (ISM) and SIFT features for re-identification. This approach builds identity models of persons during tracking and employs these models for re-identification. We apply this re-identification, which was until now only evaluated in the infrared spectrum, to data acquired in the visible spectrum. Furthermore we evaluate view independence of the re-identification approach and introduce methods that extend view invariance. Specifically, we (i) propose a method for online view-determination of a tracked person, (ii) use the online view-determination to generate view specific identity models of persons which increase model distinctiveness in re-identification, and (iii) introduce a method to convert identity models between views to increase view independence.
Designing a Query Language for RDF: Marrying Open and Closed Worlds

When querying an RDF graph, a prominent feature is the possibility of extending the answer to a query with optional information. However, the definition of this feature in SPARQL --the standard RDF query language-- has raised some important issues. Most notably, the use of this feature increases the complexity of the evaluation problem, and its closed-world semantics is in conflict with the underlying open-world semantics of RDF. Many approaches for fixing such problems have been proposed, being the most prominent the introduction of the semantic notion of weakly-monotone SPARQL query. Weakly-monotone SPARQL queries have shaped the class of queries that conform to the open-world semantics of RDF. Unfortunately, finding an effective way of restricting SPARQL to the fragment of weakly-monotone queries has proven to be an elusive problem. In practice, the most widely adopted fragment for writing SPARQL queries is based on the syntactic notion of well designedness. This notion has proven to be a good approach for writing SPARQL queries, but its expressive power has yet to be fully understood. The starting point of this paper is to understand the relation between well-designed queries and the semantic notion of weak monotonicity. It is known that every well-designed SPARQL query is weakly monotone; as our first contribution we prove that the converse does not hold, even if an extension of this notion based on the use of disjunction is considered. Given this negative result, we embark on the task of defining syntactic fragments that are weakly-monotone, and have higher expressive power than the fragment of well-designed queries. To this end, we move to a more general scenario where infinite RDF graphs are also allowed, so that interpolation techniques studied for first-order logic can be applied. With the use of these techniques, we are able to define a new operator for SPARQL that gives rise to a query language with the desired properties (over finite and infinite RDF graphs). It should be noticed that every query in this fragment is weakly monotone if we restrict to the case of finite RDF graphs. Moreover, we use this result to provide a simple characterization of the class of monotone CONSTRUCT queries, that is, the class of SPARQL queries that produce RDF graphs as output. Finally, we pinpoint the complexity of the evaluation problem for the query languages identified in the paper.
The Causal Impact of Removing Children from Abusive and Neglectful Homes

This paper measures impacts of removing children from families investigated for abuse or neglect. We use removal tendencies of child protection investigators as an instrument. Our analysis focuses on young children investigated before age 6 and finds that removal significantly increases test scores and reduces grade repetition for girls. There are no detectable impacts for boys. This pattern of results does not appear to be driven by heterogeneity in preremoval characteristics, foster placements, or types of schools attended after removal. The results are consistent with the hypothesis that development of abused and neglected girls is more responsive to home removal.
Ensemble missing data techniques for software effort prediction

Constructing an accurate effort prediction model is a challenge in software engineering. The development and validation of models that are used for prediction tasks require good quality data. Unfortunately, software engineering datasets tend to suffer from the incompleteness which could result to inaccurate decision making and project management and implementation. Recently, the use of machine learning algorithms has proven to be of great practical value in solving a variety of software engineering problems including software prediction, including the use of ensemble (combining) classifiers. Research indicates that ensemble individual classifiers lead to a significant improvement in classification performance by having them vote for the most popular class. This paper proposes a method for improving software effort prediction accuracy produced by a decision tree learning algorithm and by generating the ensemble using two imputation methods as elements. Benchmarking results on ten industrial datasets show that the proposed ensemble strategy has the potential to improve prediction accuracy compared to an individual imputation method, especially if multiple imputation is a component of the ensemble.
Intruder tracking in WSNs using binary detection sensors and mobile sinks

Powered by digital transmission advances in recent years, wireless sensor networks (WSNs) are beginning to experience a boom in different areas. Of special interest are those applications offering real-time tracking and monitoring of objects in motion, both indoors and outdoors. A WSN can have a large number of nodes, each with multiple neighbor nodes. These nodes work together to create a self-configuring mesh that can efficiently achieve a common objective. In this paper, we focus on the accuracy of intruder tracking and monitoring, when relying on low-cost binary detection sensing mechanisms. To overcome the limitations imposed by this kind of sensors, we propose an intruder tracking algorithm to estimate the intruder location. In our study, we adopted the IEEE 802.15. 4 standard for radio communications, and the MRLG (Mobile-sink Routing for Large Grids) protocol to route data to a mobile sink. Experimental results based on a grid sensor deployment show that the tracking error, measured as the mean euclidean distance between the estimated and the real intruder locations, is typically maintained below 10 meters, validating the applicability of the proposed solution.
Stem alternations and multiple exponence

In a canonical inflectional paradigm, inflectional affixes mark distinctions in morphosyntactic value, while the lexical stem remains invariant. But stems are known to alternate too, constituting a system of inflectional marking operating according to parameters which typically differ from those of the affixal system, and so represent a distinct object of inquiry. Cross-linguistically, we still lack a comprehensive picture of what patterns of stem alternation are found, and hence the theoretical status of stem alternations remains unclear. We propose a typological framework for classifying stem alternations, basing it on the paradigm-internal relationship between the features marked by stem alternations versus those marked by affixes. Stem alternations may mark completely different features from the affixes (§2), or the same features (§3). Within the latter, the values may match (§3.1) – a rare situation – or be conflated (§3.2). Conflation in turn may involve natural semantic/morphosyntactic classes (§3.
Mengatasi Imbalanced Class Pada Software Defect Prediction Menggunakan Two-Step Clustering-Based Undersampling dan Bagging Tehcnique

Ketidakseimbangan kelas seringkali menjadi masalah di berbagai set data dunia nyata, di mana satu kelas (yaitu kelas minoritas) berisi sejumlah kecil titik data dan yang lainnya (yaitu kelas mayoritas) berisi sejumlah besar titik data. Sangat sulit untuk mengembangkan model yang efektif dengan menggunakan data mining dan algoritma machine learning tanpa mempertimbangkan preprocessing data untuk menyeimbangkan set data yang tidak seimbang. Random undersampling dan oversampling telah digunakan dalam banyak penelitian untuk memastikan bahwa kelas yang berbeda mengandung jumlah titik data yang sama. Dalam penelitian ini, kami mengusulkan kombinasi two-step clustering-based random undersampling dan bagging technique untuk meningkatkan nilai akurasi software defect prediction. Metode yang diusulkan dievaluasi menggunakan lima set data dari repositori program data metrik NASA dan area under the curve (AUC) sebagai evaluasi utama. Hasil telah menunjukkan bahwa metode yang diusulkan menghasilkan kinerja yang sangat baik untuk semua dataset (AUC> 0,9). Dalam hal SN, percobaan kedua mengungguli percobaan pertama di hampir semua dataset (3 dari 5 dataset). Sementara itu, dalam hal SP, percobaan pertama tidak mengungguli percobaan kedua di semua dataset. Secara keseluruhan percobaan kedua mengungguli dan lebih baik daripada percobaan pertama karena evaluasi utama dalam klasifikasi kelas yang tidak seimbang seperti SDP adalah AUC Oleh karena itu, dapat disimpulkan bahwa metode yang diusulkan menghasilkan kinerja yang optimal baik untuk set data skala kecil maupun besar.
Ancient Origin and Gene Mosaicism of the Progenitor of Mycobacterium tuberculosis

The highly successful human pathogen Mycobacterium tuberculosis has an extremely low level of genetic variation, which suggests that the entire population resulted from clonal expansion following an evolutionary bottleneck around 35,000 y ago. Here, we show that this population constitutes just the visible tip of a much broader progenitor species, whose extant representatives are human isolates of tubercle bacilli from East Africa. In these isolates, we detected incongruence among gene phylogenies as well as mosaic gene sequences, whose individual elements are retrieved in classical M. tuberculosis. Therefore, despite its apparent homogeneity, the M. tuberculosis genome appears to be a composite assembly resulting from horizontal gene transfer events predating clonal expansion. The amount of synonymous nucleotide variation in housekeeping genes suggests that tubercle bacilli were contemporaneous with early hominids in East Africa, and have thus been coevolving with their human host much longer than previously thought. These results open novel perspectives for unraveling the molecular bases of M. tuberculosis evolutionary success.
Knowledge-based agents in a command and control simulation

To facilitate research into multi-agent planning issues, we have developed the Command and Control Testbed Using Simulation (CACTUS) and the Situation-based Autonomous Reasoner in a GBB Environment (SARGE). CACTUS is a simulation of combat operations for platoon-sized units in battalion-level engagements. We model in detail those command and control problems impacting the way planning is done by a formation commander. These include incomplete and uncertain information, imperfect control, differing agent characteristics, and limited inter-unit communications.The testbed originally required the user to input specific movement and firing instructions for each unit simulated. An interface to the simulation permits the integration of automated planners in place of user input. The SARGE commander was built to relieve the user of the need to provide detailed instructions at the simulation system level. Units with SARGE commanders take goal level instructions and SARGE then explictly reasons about plans to achieve those goals and submits the instructions necessary to implement those plans in CACTUS. SARGE uses the blackboard model of reasoning as implemented in the Generic Blackboard (GBB) tool. User access to the knowledge affecting SARGE behavior allows us to assess the impact of different tactical and doctrinal schemes on planning at higher levels of command.The SARGE and CACTUS systems provide the foundations for developing automated planners for multiple unit formations by raising the level of abstraction for inputting instruction to subordinate units. We will use this incremental approach to address command and control issues at progressively higher levels in the chain of command and to develop, refine, and evaluate artificial intelligence techniques to integrate human and machine capabilities. Our ultimate goal is to collect applicable techniques into a system supporting rapid prototyping of tactical decision aids. SARGE and CACTUS are vital steps in this process.
One Size Doesn’t Fit All: When to Use Signature-based Pruning to Improve Template Matching for RDF graphs

Signature-based pruning is broadly accepted as an effective way to improve query performance of graph template matching on general labeled graphs. Most techniques which utilize signature-based pruning claim its benefits on all datasets and queries. However, the effectiveness of signature-based pruning varies greatly among different RDF datasets and highly related to their dataset characteristics. We observe that the performance benefits from signature-based pruning depend not only on the size of the RDF graphs, but also on the underlying graph structure and the complexity of queries. This motivates us to propose a flexible RDF querying framework, called RDF, which selectively utilizes signature-based pruning by evaluating the characteristics of RDF datasets and query templates. We demonstrate the scalability and efficiency of RDFvia experimental results using both real and synthetic datasets.
Fast visual tracking and localization in multi-agent systems

In this paper an implementation of an algorithm for fast visual tracking and localization of mobile agents has been described. Based on an extremely rapid method for visual detection of an object, described localization strategy provides a real time solution suitable for the design of multi-agent control schemes. The agents tracking and localization is carried out through five differently trained cascades of classifiers that process images captured by cameras mounted on agents. In this way, each agent is able to determine relative positions and orientations of all other agents performing tasks in its field of view. The described localization method is suitable for applications involving robot formations. Performance of the proposed method has been demonstrated on a laboratory setup composed of two mobile robot platforms.
Decimal engine for energy-efficient multicore processors

Prior work demonstrated the use of specialized pro-cessors, or accelerators, be energy-efficient for binary floating-point (BFP) division and square root, and for decimal floating-point (DFP) operations. In the dark silicon era, where not all the circuits on the die can be powered simultaneously, we propose a hybrid BFP/DFP engine to perform BFP division and DFP addition, multiplication and division. The main purpose of this engine is to offload the binary floating-point units for this type of operations and reduce the latency for decimal operations, and power and temperature for the whole die.
Composition Behaviors for Application Construction

The formation of software modules is critically dependent on the mechanisms of software composition. Common software composition tools, such as linkers, provide only a narrow set of standard composition behaviors. Advanced program composition systems, such as Hyper/J and AspectJ, define several ad hoc extensions to these behaviors. In real-world programs, these standard and extended composition behaviors fail to encapsulate common program changes. These failures are especially visible in flexible program construction. The addition of program features often requires complex frameworks or scattered changes to many pre-existing modules. This paper presents several alternative composition behaviors that enhance modularity for common forms of software evolution. These behaviors extend the ways that developers can combine software units. These behaviors subsume many of the ad hoc extensions that have been proposed.
Development of Transgenic Cotton Lines Expressing Allium sativum Agglutinin (ASAL) for Enhanced Resistance against Major Sap-Sucking Pests

Mannose-specific Allium sativum leaf agglutinin encoding gene (ASAL) and herbicide tolerance gene (BAR) were introduced into an elite cotton inbred line (NC-601) employing Agrobacterium-mediated genetic transformation. Cotton transformants were produced from the phosphinothricin (PPT)-resistant shoots obtained after co-cultivation of mature embryos with the Agrobacterium strain EHA105 harbouring recombinant binary vector pCAMBIA3300-ASAL-BAR. PCR and Southern blot analysis confirmed the presence and stable integration of ASAL and BAR genes in various transformants of cotton. Basta leaf-dip assay, northern blot, western blot and ELISA analyses disclosed variable expression of BAR and ASAL transgenes in different transformants. Transgenes, ASAL and BAR, were stably inherited and showed co-segregation in T1 generation in a Mendelian fashion for both PPT tolerance and insect resistance. In planta insect bioassays on T2 and T3 homozygous ASAL-transgenic lines revealed potent entomotoxic effects of ASAL on jassid and whitefly insects, as evidenced by significant decreases in the survival, development and fecundity of the insects when compared to the untransformed controls. Furthermore, the transgenic cotton lines conferred higher levels of resistance (1–2 score) with minimal plant damage against these major sucking pests when bioassays were carried out employing standard screening techniques. The developed transgenics could serve as a potential genetic resource in recombination breeding aimed at improving the pest resistance of cotton. This study represents the first report of its kind dealing with the development of transgenic cotton resistant to two major sap-sucking insects.