Miracle-dz/UniFAR-FTUs huggingface dataset:
Requirements Identification and Representation in Software Product Line

Software Product Line (SPL) core assets development is an effective approach in software reuse in which core assets can be shared among the members of the product line with an explicit treatment of variability. Considering reuse early in development phase can promise the increase in reuse and understanding reuse at a later development phase. This paper concentrates on identifying and representing variability at requirement level. The proposed approach differs slightly from other approaches where identification of the variant requirements is done with commonality and variability analysis and using two important requirements model, feature and use case model. Relation between both requirements model is through matrix table. This paper illustrates the application of this approach using the library systems product line example.
XMedia: Web People Search by Clustering with Machinely Learned Similarity Measures

In this paper we present an approach to person name disambiguation that clusters documents on the basis of textual features using cosine similarity and a machinely learned meta similarity measure. The approach achieves an F-measure of B-Cubed Precision and Recall of 0.74 1 on the Clustering Subtask for WePS-2. Such task consists of clustering a set of documents that mention an ambiguous person name according to the actual entities referred to that name.
Developing a Model of Technology Appropriation: A Marxian Perspective

This paper explores the philosophical origins of appropriation of Information Systems (IS) using Marxian and other socio-cultural theory. It provides an in-depth examination of appropriation and its application in extant IS theory. We develop a three-tier model using Marx’s foundational concepts and from this generate four propositions that we test in an empirical example of IS in anesthesia. Using Marxian theory, this paper seeks common ground among existing theories of technology appropriation in IS research. This work contributes to IS research by (1) opening philosophical discussions on appropriation and the human ↔ technology nexus, (2) drawing on these varying perspectives to propose a general conceptualization of technology appropriation and (3) providing a starting point towards a general causal model of technology appropriation.
An Approach to Horizontal Tilt Correction of Vehicle License Plate Based on Matchstick Model

Aiming at the problem of precision and real time in traditional methods to horizontal tilt correction of vehicle license plate, an approach based on matchstick model is presented. The principle is to get the correct license image from its tilt character line. A matchstick model is built up by abstracting the features of characters. By rotating the image with a certain degree, we can find whether it is horizontal with the matchstick model. Experimental results show that this method has high correction accuracy, less calculation and strong real time characteristics.
Maximizing Concurrency and Analyzable Timing Behavior in Component-Oriented Real-Time Distributed Computing Application Systems

Demands have been growing in safety-critical application fields for producing networked real-time embedded computing (NREC) systems together with acceptable assurances of tight service time bounds (STBs). Here a service time can be defined as the amount of time that the NREC system could take in accepting a request, executing an appropriate service method, and returning a valid result. Enabling systematic composition of large-scale NREC systems with STB certifications has been recognized as a highly desirable goal by the research community for many years. An appealing approach for pursuing such a goal is to establish a hard-real-time (HRT) component model that contains its own STB as an integral part. The TMO (Time-Triggered Message-Triggered Object) programming scheme is one HRT distributed computing (DC) component model established by the first co-author and his collaborators over the past 15 years. The TMO programming scheme has been intended to be an advanced high-level RT DC programming scheme that enables development of NREC systems and validation of tight STBs of such systems with efforts far smaller than those required when any existing lower-level RT DC programming scheme is used. An additional goal is to enable maximum exploitation of concurrency without damaging any major structuring and execution approaches adopted for meeting the first two goals. A number of previously untried program structuring approaches and execution rules were adopted from the early development stage of the TMO scheme. This paper presents new concrete justifications for those approaches and rules, and also discusses new extensions of the TMO scheme intended to enable further exploitation of concurrency in NREC system design and programming.
The Information Geometry of Mirror Descent

We prove the equivalence of two online learning algorithms: 1) mirror descent and 2) natural gradient descent. Both mirror descent and natural gradient descent are generalizations of online gradient descent when the parameter of interest lies on a non-Euclidean manifold. Natural gradient descent selects the steepest descent along a Riemannian manifold by multiplying the standard gradient by the inverse of the metric tensor. Mirror descent induces non-Euclidean structure by solving iterative optimization problems using different proximity functions. In this paper, we prove that mirror descent induced by Bregman divergence proximity functions is equivalent to the natural gradient descent algorithm on the dual Riemannian manifold. We use techniques from convex analysis and connections between Riemannian manifolds, Bregman divergences, and convexity to prove this result. This equivalence between natural gradient descent and mirror descent, implies that: 1) mirror descent is the steepest descent direction along the Riemannian manifold corresponding to the choice of Bregman divergence and 2) mirror descent with log-likelihood loss applied to parameter estimation in exponential families asymptotically achieves the classical Cramér-Rao lower bound.
Wireless Sensor Networks Issues and Applications

Wireless Sensor Networks have come to the forefront of the scientific community recently. Current WSNs typically communicate directly with a centralized controller or satellite. On the other hand, a smart WSN consists of a number o f sensors spread across a geographical area; each sensor has wireless communication capability and sufficient intelligence for signal processing and networking of the data. The structures of WSNs are tightly application-dependent, and many services are also dependent on application semantics. Thus, there is no single typical WSN application, and dependency on applications is higher than in traditional distributed applications. The application/middleware layer must provide functions that create effective new capabilities for efficient extraction, manipulation, transport, and representation of information derived from sensor data. This paper provides a survey of Wireless Sensor Networks Issues and Applications, where the use of such sensor networks has been proposed.
Optimization for the operation of electric power generation taking account of distributed regional demand in Japan

The purpose of this study is to analyze impacts of distributed regional demand on the operational characteristics. Many energy models for the operation of electric power generation tended to regard Japan as a single demand node. However, the power generation plants and electricity demand are distributed throughout the nation. There is still unknown about the impacts of distributed electricity demand on the operation of electric utilities. We have designed two types of model to estimate the impacts of distributed regional demand on the operation characteristics. The first model regards Japan as a single area for electricity consumption, and the second model considers the distributed consumption of electricity. In conclusion, we should note that it is important to consider the distributed regional demand in order to estimate operation characteristics appropriately.
Language-support system using character recognition

We have developed a prototype system that supports language translation for distance lecturing and local learning. The system automatically detects a word displayed in a video image by matching the identified character markers; it then translates the word into the other language and displays the translated word using text, image, and/or sound. The ARToolkit is used as an image-processing tool to search the video image for character markers, which are composed of square frames and registered characters. The use of image processing enables any language to be used as the source language; Japanese is used in the prototype. The use of video makes it easy to implement the system in existing telecommunication systems, because a user just prepares a PC for capturing video images. A Web browser is used as the presentation tool; it can handle any content format normally supported by a Web browser: images, sounds, 3D models, and characters. An automatic voice function automatically reads out words on user demand. The software consists of a character-recognition part (server) and a display part (client); the server controls the client through socket communications. This software architecture makes it possible for one lecturer to simultaneously teach students with various mother tongues, when the clients treat multi-language, because there is a different client for each student. Testing of this language-support system for distance lecturing between Thailand and Japan using a satellite communication system showed that it could be used for both fundamental language lecturing and language translation during international exchange.
Disentangling the effects of climate and people on Sahel vegetation dynamics

Abstract. The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982–2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. We do not exclude the possibility of a greater human influence on vegetation dynamics over the coming decades with changing land use.
Selection Effects with Heterogeneous Firms

We characterize how firms select between alternative ways of serving a market. “First-order” selection effects, whether firms enter or not, are extremely robust. “Second-order” ones, how firms serve a market conditional on entry, are much less so: more efficient firms select the entry mode with lower market-access costs if firms’ maximum profits are supermodular in production and market-access costs, but not necessarily otherwise. We derive microfoundations for supermodularity in a range of canonical models. Notable exceptions include horizontal and vertical FDI with “subconvex” demands (i.e., less convex than CES), fixed costs that increase with productivity, and R&D with threshold effects.
A Correctness Proof for a Practical Byzantine-Fault-Tolerant Replication Algorithm

We have developed a practical algorithm for state-machine replication [7, 11] that tolerates Byzantine faults. The algorithm is described in [4]. It offers a strong safety property — it implements a linearizable [5] object such that all operations invoked on the object execute atomically despite Byzantine failures and concurrency. Unlike previous algorithms [11, 10, 6], ours works correctly in asynchronous systems like the Internet, and it incorporates important optimizations that enable it to outperform previous systems by more than an order of magnitude [4].
CD8+ T Cells and IFN-γ Mediate the Time-Dependent Accumulation of Infected Red Blood Cells in Deep Organs during Experimental Cerebral Malaria

Background Infection with Plasmodium berghei ANKA (PbA) in susceptible mice induces a syndrome called experimental cerebral malaria (ECM) with severe pathologies occurring in various mouse organs. Immune mediators such as T cells or cytokines have been implicated in the pathogenesis of ECM. Red blood cells infected with PbA parasites have been shown to accumulate in the brain and other tissues during infection. This accumulation is thought to be involved in PbA–induced pathologies, which mechanisms are poorly understood. Methods and Findings Using transgenic PbA parasites expressing the luciferase protein, we have assessed by real-time in vivo imaging the dynamic and temporal contribution of different immune factors in infected red blood cell (IRBC) accumulation and distribution in different organs during PbA infection. Using deficient mice or depleting antibodies, we observed that CD8+ T cells and IFN-γ drive the rapid increase in total parasite biomass and accumulation of IRBC in the brain and in different organs 6–12 days post-infection, at a time when mice develop ECM. Other cells types like CD4+ T cells, monocytes or neutrophils or cytokines such as IL-12 and TNF-α did not influence the early increase of total parasite biomass and IRBC accumulation in different organs. Conclusions CD8+ T cells and IFN-γ are the major immune mediators controlling the time-dependent accumulation of P. berghei-infected red blood cells in tissues.
EFFECT OF RADIATION DOSE LEVEL ON ACCURACY AND PRECISION OF MANUAL SIZE MEASUREMENTS IN CHEST TOMOSYNTHESIS EVALUATED USING SIMULATED PULMONARY NODULES

The aim of the present study was to investigate the dependency of the accuracy and precision of nodule diameter measurements on the radiation dose level in chest tomosynthesis. Artificial ellipsoid-shaped nodules with known dimensions were inserted in clinical chest tomosynthesis images. Noise was added to the images in order to simulate radiation dose levels corresponding to effective doses for a standard-sized patient of 0.06 and 0.04 mSv. These levels were compared with the original dose level, corresponding to an effective dose of 0.12 mSv for a standard-sized patient. Four thoracic radiologists measured the longest diameter of the nodules. The study was restricted to nodules located in high-dose areas of the tomosynthesis projection radiographs. A significant decrease of the measurement accuracy and intraobserver variability was seen for the lowest dose level for a subset of the observers. No significant effect of dose level on the interobserver variability was found. The number of non-measurable small nodules (≤5 mm) was higher for the two lowest dose levels compared with the original dose level. In conclusion, for pulmonary nodules at positions in the lung corresponding to locations in high-dose areas of the projection radiographs, using a radiation dose level resulting in an effective dose of 0.06 mSv to a standard-sized patient may be possible in chest tomosynthesis without affecting the accuracy and precision of nodule diameter measurements to any large extent. However, an increasing number of non-measurable small nodules (≤5 mm) with decreasing radiation dose may raise some concerns regarding an applied general dose reduction for chest tomosynthesis examinations in the clinical praxis.
The enactment of a flipped classroom approach in a senior secondary mathematics class and its impact on student engagement

Once considered the domain of higher education, the flipped classroom is increasingly being implemented in secondary school settings. Although enactments of the approach vary, it typically involves the use of digital technologies to shift direct instruction to the home environment, providing for more targeted in-class teaching. This paper describes how a flipped classroom approach was enacted in a senior secondary mathematics classroom and reports on the students' and teacher's perceptions of the impact of the approach in terms of students' engagement with mathematics. It adds to the limited research in this area through providing an account of how flipping the classroom works in practice and its potential for engaging students in mathematics.
Exit charts for iteratively decoded multilevel modulation

We investigate EXIT charts for the design and analysis of Bit-Interleaved Coded Modulation (BICM) with iterative decoding. Analytical expressions for EXIT functions of convolutional codes and mappings are derived. For the demapper, we show EXIT functions for different channel models and introduce bit-wise EXIT functions and a symbol-wise description. These functions are used in an optimization procedure to find new mappings.
Resilience of Complex Networks

This article determines and characterizes the minimal number of actuators needed to ensure structural controllability of a linear system under structural alterations that can severe the connection between any two states. We assume that initially the system is structurally controllable with respect to a given set of controls, and propose an efficient system-synthesis mechanism to find the minimal number of additional actuators required for resilience of the system w.r. t such structural changes. The effectiveness of this approach is demonstrated by using standard IEEE power networks.
Analysis of Rotor Saturation in Synchronous Reluctance and PM-Assisted Reluctance Motors

The design of synchronous reluctance (REL) machines is complex and involves a lot of variables. It is difficult to design proper rotor flux-barrier geometry that yields satisfactory performance, in terms of torque ripple, average torque, etc. Geometry optimization is often necessary to find optimum solutions on the basis of some objective functions. However, it is not easy to determine the main impact of each geometry variable on the machine performance. The main contribution of this paper is to investigate the effect of a different level of saturation of the magnetic rotor path, comparing the performance of some synchronous REL machines. The effect of the insertion of permanent magnets is also investigated. The comparison has been carried out on the basis of finite-element analysis, considering average torque, torque ripple, power factor, torque and power versus speed curves and efficiency. A prototype has been tested to compare the simulation results with the experimental measurements.
Gene Expression Analysis of the 26S Proteasome Subunit PSMB4 Reveals Significant Upregulation, Different Expression and Association with Proliferation in Human Pulmonary Neuroendocrine Tumours

Background: Proteasomal subunit PSMB4 was suggested to be a survival gene in an animal model of hepatocellular carcinoma and in glioblastoma cell lines. In pulmonary adenocarcinoma, a high expression of these genes was found to be associated with poor differentiation and survival. This study investigates the gene expression levels of 26S proteasome subunits in human pulmonary neuroendocrine tumours including typical (TC) and atypical (AC) carcinoid tumours as well as small cell (SCLC) and large cell (LCNEC) neuroendocrine carcinomas. Material and methods: Gene expression levels of proteasomal subunits (PSMA1, PSMA5, PSMB4, PSMB5 and PSMD1) were investigated in 80 neuroendocrine pulmonary tumours (each 20 TC, AC, LCNLC and SCLC) and compared to controls. mRNA levels were determined by using TaqMan assays. Immunohistochemistry on tissue microarrays (TMA) was performed to determine the expression of ki67, cleaved caspase 3 and PSMB4. Results: All proteasomal subunit gene expressions were significantly upregulated in TC, AC, SCLC and LCNEC compared to controls. PSMB4 mRNA is differently expressed between all neuroendocrine tumour subtypes demonstrating the highest expression and greatest range in LCNEC (p=0.043), and is significantly associated with proliferative activity (p=0.039). Conclusion: In line with other 26S proteasomal subunits PSMB4 is significantly increased, but differently expressed between pulmonary neuroendocrine tumours and is associated with the proliferative activity. Unlike in pulmonary adenocarcinomas, no association with biological behaviour was observed, suggesting that increased proteasomal subunit gene expression is a common and probably early event in the tumorigenesis of pulmonary neuroendocrine tumours regardless of their differentiation.
An Experimental Study Towards Understanding Data Delivery Performance Over a WSN Link

The performance of a wireless sensor network (WSN) depends fundamentally on how its various parameters are configured under different link quality conditions. Surprisingly, even though WSNs have been extensively researched, there still lacks an in-depth understanding on how parameter configurations affect, in particular jointly, the performance under different link quality conditions. To fill the gap, this paper presents an extensive experimental study on the performance of a wireless sensor network link, where measurement data of more than 200 million packets were collected. Different from existing work, we consider major parameters from different layers together and measure their joint effects on key performance metrics under an extensive set of parameter configurations. Based on the large amount of measurement data, we investigate the impacts of these parameters and their joint configurations on the performance, introduce empirical models to theoretically reason the impacts, discuss implications of the obtained results, and suggest practical guidelines for parameter configurations. Through these, a comprehensive overview of parameter configuration impacts on the erformance is provided, which provides new insights on wireless link performance in WSNs.