Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Corporate Social Media Crises on Facebook Using Social Set Analysis

Social media crises pose significant challenges for organizations in terms of their rapid rate of spread and potential persistent negative associations in terms of brand parameters and sustained negative advocacy by internet users and/or consumers. This paper reports on a technique for detecting social media crises using social set analysis-an approach to computational social based on associational sociology and set theory. Based on a conceptual and formal model of social data, we conduct social set analysis of the facebook wall data of four diferent Danish companies. Findings show the voluminous but also transient nature of social media crises and aggregate user behavioural patterns. We discuss the implications of our findings and the application of the crisis detetction technique for analyzing other epiosodic activities such as product promotions, election campaigns.
Stator winding thermal conductivity evaluation: An industrial production assessment

The thermal conductivity between winding and lamination is one of the most critical parameters in electrical machine thermal analysis. Its value depends on the insulation materials and on the manufacturing process of the winding system and for this reason cannot be computed using analytical equations. In this paper a practical investigation on equivalent thermal conductivity of electrical machines stator winding is presented and discussed. The fully experimental approach is based on a fast transient thermal test to evaluate the winding equivalent thermal conductivity. The test campaign is carried out on two sets of Total Enclosed Fan Cooled “TEFC” industrial induction motors produced by two different manufacturers; the rated power of the devices under test ranges from 1.5 kW up to 55 kW.
Decision Support System Design and Implementation for Outpatient Prescribing: The Safety in Prescribing Study

Abstract : Decision support (i.e., alerts and reminders) at the time of medication prescribing has been shown to be an effective method for reducing potential medication errors for inpatients, but much less is known about the effects in the outpatient setting. Using qualitative methods to inform our work, medication safety decision support and provider education interventions were designed to improve the use of medications in ambulatory care. This paper presents the study rationale, design, development, and implementation of the interventions. We include a summary of the qualitative findings, including usability testing of the decision support, and we describe how the qualitative findings enhanced the intervention design. We also describe our approach to clinician recruitment. We enumerate limitations of the existing electronic medical record to accommodating recommendations from the qualitative work and usability testing. Our qualitative interviews suggest that clinicians prefer decision support alerts that are clear, concise, and easy to navigate, with minimal information in the alert text. In usability testing, we found that decision support alerts are followed less often when they appear at inappropriate times in workflow, are difficult to read, add to time pressure, and are canceled before being fully read. Our deliberate approach to clinician recruitment for the educational sessions achieved an impressive attendance rate of 85 percent. This study shows that careful consideration of alert design and provider education is critical. Future work will examine the effectiveness of the decision support and whether our educational intervention improves physician response.
Designing FPT Algorithms for Cut Problems Using Randomized Contractions

We introduce a new technique for designing fixed-parameter algorithms for cut problems, namely randomized contractions. With our framework: (1) We obtain the first FPT algorithm for the parameterized version of the UNIQUE LABEL COVER problem, with single exponential dependency on the size of the cutset and the size of the alphabet. As a consequence, we extend the set of the polynomial time solvable instances of UNIQUE GAMES to those with at most O(√{log n}) violated constraints. (2) We obtain a new FPT algorithm for the STEINER CUT problem with exponential speed-up over the recent work of Kawarabayashi and Thorup (FOCS'11). (3) We show how to combine considering 'cut' and 'uncut' constraints at the same time. We define a robust problem NODE MULTIWAY CUT-UNCUT that can serve as an abstraction of introducing uncut constraints, and show that it admits an FPT algorithm with single exponential dependency on the size of the cutset. To the best of our knowledge, the only known way of tackling uncut constraints was via the approach of Marx, O'Sullivan and Razgon (STACS'10), which yields algorithms with double exponential running time. An interesting aspect of our algorithms is that they can handle real weights, to the best of our knowledge, the technique of important separators does not work in the weighted version.
B2C e-Commerce Success: a Test and Validation of a Revised Conceptual Model

: Since the advent of the Internet, B2C e-Commerce has grown substantially across the globe. Whilst much research has examined factors influencing adoption of e-commerce, not as many studies have investigated the post-adoption phenomenon of success. Those studies that have investigated IS success and the extensions required to accommodate e-commerce have mainly been conceptual. Few have attempted to test and validate the models empirically. The purpose of this study was to fill this gap. By drawing from the technology acceptance model, expectation-confirmation theory and IS success theory, a revised conceptual model was derived. The model and relationships were tested and validated using data gathered from 166 online consumers in South Africa. 7 interrelated dimensions of B2C e-commerce success were confirmed, namely service quality, system quality, information quality, trust, perceived usefulness, user satisfaction and continuance intentions. Direct relationships between dimensions were identified. These showed that user intentions to continue using an online retail site are directly influenced by perceived usefulness, user satisfaction and system quality. User satisfaction is directly influenced by service quality and perceived usefulness, whilst perceived usefulness is directly influenced by trust and information quality. Trust in the online retailer is directly influenced by service quality and system quality. The implications of these and other findings are discussed.
Multimodal literacy: storytelling across senses

This paper describes a novel framework for literature that presents the reader with a multimodal experience (visual, haptic and auditory). We present an initial prototype, extending an iPad with a surface vibration transducer for haptic feedback to augment the reading of a short story. Text provides the reader with verbal information, whereas other senses perceive the context through non-verbal cues. We use our own framework to create this storytelling across senses, integrating text, sound, animation and tactile sensation. We believe with a multi-modal reading experience, users will enjoy reading more, will feel more immersed and remember the narrative better.
Coordination, incorporation and dynamic semantic representation in transfer

Factorized coordinated predicative structures prove to be a problem to transfer whenever the bilingual lexicon suggests a non-isomorphic translation for one of the predicative conjuncts, in particular a solution that requires incorporation of the predicative description into the translation of the source (support) verb. The problem disappears if the factorized structure is ’multiplied out’, resulting in a structure where the coordination is raised to VP. Since many languages make use of such factorized coordinations and since, normally, one can translate them into each other, ’multiplying out’ is unnecessary in most of the cases and costly. We suggest a semantics based transfer architecture in this paper which, per default, avoids unfolding the factorized representation and makes it dependent on constraints formulated in the bilingual lexicon whether corresponding structural revision is needed. If so, triggered by such constraints, it is computed on the fly during transfer.
ART: Adaptive fRequency-Temporal Co-Existing of ZigBee and WiFi

Recent large-scale deployments of wireless sensor networks have posed a high demand on network throughput, forcing all (discrete) orthogonal ZigBee channels to be exploited to enhance transmission parallelism. However, the interference from widely deployed WiFi networks has severely jeopardized the usability of these discrete ZigBee channels, while the existing CSMA-based ZigBee MAC is too conservative to utilize each channel temporally. In this paper, we propose ART (Adaptive fRequency-Temporal co-existing) as a framework consisting of two components: FAVOR (Frequency Allocation for Versatile Occupancy of spectRum) and P-CSMA ( Probabilistic CSMA), to improve the co-existence between ZigBee and WiFi in both frequency and temporal perspectives. On one hand, FAVOR allocates continuous (center) frequencies to nodes/links in a near-optimal manner, by innovatively converting the problem into a spatial tessellation problem in a unified frequency-spatial space. This allows ART to fully exploit the “frequency white space” left out by WiFi. On the other hand, ART employs P-CSMA to opportunistically tune the use of CSMA for leveraging the “temporal white space” of WiFi interference, according to real-time assessment of transmission quality. We implement ART in MicaZ platforms, and our extensive experiments strongly demonstrate the efficacy of ART in enhancing both throughput and transmission quality.
Experimental Verification of a Posteriori Quality Enhancement of Security Images

The image quality is a crucial issue in the applied imaging system incl. security. The security imaging systems have special qualitative requirements - the general perceptive image quality is not so important compared to the preservation of selected security image characteristics such as an identification or classification. In the first part we have tested the impact of image enhancing algorithms on the display readability in presence of noise. We have chosen the registration plate as an example and two noise types have been added in order to find the readability threshold. The second part has been devoted to de-noising techniques for image noise removal and deals with advanced WT (wavelet transform) based method of noise suppression for security purposes. Specific requirements on the proposed noise suppression technique can be stated. It should be efficient, both in the sense of low computational complexity but also by means of high noise suppression performance. Moreover, the system must preserve all the important features of the scene being watched. Several tests have been done to verify high noise suppression performance, computational efficiency and low distortion of important features.
Are Many Reactive Agents Better Than a Few Deliberative Ones?

Problem solvers fa l l along a wide spectrum ranging f r om highly del iberat ive to h igh ly reactive. H igh ly del iberat ive systems are able to design op t ima l l y efficient solut ions to problems, bu t they require complete wor ld models and consume inord inate computa t iona l resources. Reactive systems move in real t ime but cannot guarantee efficient solut ions. They are also subject to looping behavior. One way to generate incremental ly more efficient solut ions is to be incremental ly more del iberat ive, e.g., to increase the amount of menta l search between actions. Th is paper presents an alternat ive method for generat ing more efficient solut ions: increasing the number of reactive agents simultaneously a t tack ing a given problem. Th is method provides a second, orthogonal degree of f reedom. We f ind tha t in many domains, increasing agents is dramat ica l ly superior to increasing single-agent del iberat iveness. Th is is because solut ion qual i ty improves rap id ly as more reactive agents are added, but search t ime only increases l inearly. Th is contrasts w i t h add ing more deliberativeness, which incurs exponent ia l ly increasing t ime costs. A m ple empir ical evidence is presented to support our conclusions. 1 I n t r o d u c t i o n Th is paper considers two aspects of computa t iona l prob-
Real-time CAD model matching for mobile manipulation and grasping

Humanoid robotic assistants need capable and comprehensive perception systems that enable them to perform complex manipulation and grasping tasks. This requires the identification and recognition of supporting planes and objects in the world, together with their precise 6D poses. In this paper, we propose a 3D perception system architecture that can robustly fit CAD models in cluttered table setting scenes for the purpose of grasping with a mobile manipulator. Our approach uses a powerful combination of two different camera technologies, Time-Of-Flight (TOF) and RGB, to robustly segment the scene and extract object clusters. Using an a-priori database of object models we then perform a CAD matching in 2D camera images. We validate the proposed system in a number of experiments, and compare the system's performance and reliability with similar initiatives.
Contemporary Strategies in the Management of Hepatocellular Carcinoma

Liver transplantation is the treatment of choice for selected patients with hepatocellular carcinoma (HCC) on a background of chronic liver disease. Liver resection or locoregional ablative therapies may be indicated for patients with preserved synthetic function without significant portal hypertension. Milan criteria were introduced to select suitable patients for liver transplant with low risk of tumor recurrence and 5-year survival in excess of 70%. Currently the incidence of HCC is climbing rapidly and in a current climate of organ shortage has led to the re-evaluation of locoregional therapies and resectional surgery to manage the case load. The introduction of biological therapies has had a new dimension to care, adding to the complexities of multidisciplinary team working in the management of HCC. The aim of this paper is to give a brief overview of present day management strategies and decision making.
Prague Czech-English Dependency Treebank: Any Hopes for a Common Annotation Scheme?

The Prague Czech-English Dependency Tree-bank (PCEDT) is a new syntactically annotated Czech-English parallel resource. The Penn Treebank has been translated to Czech, and its annotation automatically transformed into dependency annotation scheme. The dependency annotation of Czech is done from plain text by automatic procedures. A small subset of corresponding Czech and English sentences has been annotated by humans. We discuss some of the problems we have experienced during the automatic transformation between annotation schemes and hint at some of the difﬁculties to be tackled by potential guidelines for dependency annotation of English.
Do Government-linked Companies Necessarily Underperform?

Different from the typical findings in the privatization literature, this study of 31 Singapore government-linked companies (GLCs) covering a period from 1975 to1998 shows no significant changes in performance upon share issue privatization. Also, there is no evidence that the GLCs are less profitable than a selected group of non-GLCs that match by size and industry. Taking a buy-andhold strategy, we find that GLC stocks provide statistically equivalent market-adjusted returns as the selected non-GLC stocks over various investment horizons up to five years. Hence, governmentowned enterprises need not necessarily be less efficient than private-run enterprises.
Standard Verilog-VHDL interoperability

During the last few years HDLs have become the driver behind the move to top down design in the electronic design industry. Two HDLs, VHDL and Verilog HDL have become the dominant de facto industry standard HDLs. Since the industry has made a huge investment in both HDLs and there is every indication that each will retain significant market share for the foreseeable future, it is critical that there exist a standard methodology for interoperability between the two languages. The paper describes the relevant issues for interoperability and suggests solutions where they currently exist. It further summarizes the work which needs to be done for a complete solution and the groups who are involved in achieving this goal. The emphasis in the paper is on simulation since the semantics of the two languages are specified only for that discipline. While the importance of other disciplines such as logic synthesis cannot be underestimated in the top down design process, the lack of standard language semantics makes general analysis problematic. <<ETX>>
The renormalizability for massive Abelian gauge field theories re-visited

We give a simplified proof for the perturbative renormalizability of theories with massive vector particles. For renormalizability it is sufficient that the vector particle is treated as an gauge field, corresponding to an Abelian gauge group. Contrary to the non-Abelian case one does not need the Higgs mechanism to create the appropriate mass terms. The proof uses ``Stueckelberg's trick'' and the Ward-Takahashi identities from local Abelian gauge invariance. The simplification is due to the fact that, again contrary to the non-Abelian case, no BRST analysis is needed.
Optimized H.264 motion estimation algorithm based on UMHexagonS

H.264 has adopted UMHexagonS algorithm as fast motion estimation algorithm for integer pixel formally, but this algorithm has some shortages such as search points are lots, quantity of operation is kind of big, costs much time, and so on. These need to be solved as soon as possible. This paper introduces and analyses UMHexagonS algorithm. In order to solve these problems, this paper brings forward classification strategy for search algorithm according to statistical properties of the motion vector prediction value, and improves the template based on original algorithm according to the characteristic of center bias of motion vector. The results of experiments show that the improved algorithm in this paper reduces the time of motion estimation by 15%~27%. At the meantime, it can ensure PSNR and rate basically unchanged.
Prosody prediction using a tree-structure similarity metric

In this paper, we present ongoing work on prosody prediction for speech synthesis. Our approach considers sentences as treelike structures and decides on the prosody from a corpus of such structures through tree similarity measurements in a nearest neighbour context. We introduce a syntactic structure and a performance structure representation, the tree similarity metrics considered, and then we discuss the prediction method. Experiments are currently under process to qualify this approach. aspect of through relations Our approach is attempt achieve goal.
Frequent neighboring class set mining with constraint condition

As these present frequent neighboring class set mining algorithms aren't able to extract frequent neighboring class set with constraint condition, this paper proposes an algorithm of mining frequent neighboring class set with constraint condition based on down-up search strategy, which is suitable for mining frequent neighboring class set with constraint spatial classes in large spatial data. The algorithm uses the digital method to create database of neighboring class set, and then generates candidate frequent neighboring class set with constraint condition through down-up search strategy, namely, it connects two k-frequent neighboring class sets with constraint classes to generate (k+1)-candidate frequent neighboring class set with constraint classes, it only need scan once database to extract frequent neighboring class set with constraint condition. The algorithm uses logic operation to compute support of candidate frequent neighboring class set with constraint condition, it is very fast. The result of experiment indicates that the algorithm is fast and more efficient when mining short frequent neighboring class set with constraint condition in large spatial data.
Microwave Effect of 0.9 GHz and 1.8 GHz Cw Frequencies Exposed to Unrestrained Swiss Albino Mice

Long term radio frequency electromagnetic fleld (RF EMF) exposures due to Global System for Mobile communication (GSM) frequencies were investigated in this study. 158 Swiss Albino mice in unrestrained conditions were used as surrogate and divided into four groups. The average peak fleld strength generated and measured inside the cages placed at a far fleld from the antennas is 0:6 £ 10 i3 mW/cm 2 , and the speciflc absorption rate at 0.9GHz and 1.8GHz is 2:33 £ 10 i3 W/kg and 1:97 £ 10 i4 W/kg, respectively. Three samples of the mice chosen at random each from sham and exposed groups in week 4 and subsequently biweekly basis were taken for haematology and histopathology tests. The complete blood count result shows that haematological parameters of both the sham exposed and exposed mice were within the normal range of mice in the control group. A statistical analysis was conducted to determine whether difierences observed between the experimental groups were signiflcant. The histopathology examination on some internal organs shows that spleen and bone marrow of the mice were normal for all the three experimental groups, while a sign of tissue degeneration and in∞ammations were observed after 8 weeks of exposure on the brain,
Obstacle detection during day and night conditions using stereo vision

We have developed a stereo vision based obstacle detection (OD) system that can be used to detect obstacles in off-road terrain during both day and night conditions. In order to acquire enough depth estimates for reliable OD during low visibility conditions, we propose a stereo disparity (depth) estimation approach that uses fine-to-coarse selection in a stereo image pyramid. This fine-to-coarse selection is based on a novel disparity validity metric that reflects the estimation reliability. Dense three-dimensional terrain data is reconstructed from the estimated stereo disparities. In our OD methods, several geometric properties, such as the terrain slope, are inspected to distinguish between obstacles and drivable terrain. This is achieved in a robust and efficient manner by considering the inherent uncertainty in stereo depth and using a hysteresis threshold. A large and varied collection of day- and nighttime images has been used to evaluate the performance of our system. The results show that our methods can reliably detect different types of obstacles in all tested conditions.
Flexible Plan Reuse in a Formal Framework

The reuse of plans is widely considered as a valuable tool for the improvement of eeciency in planning systems because it avoids the repetition of planning eeort. Several approaches which investigate the modiication and reuse of sequential plans in the framework of strips-based planning have been developed. In this paper we present a domain-independent approach to exible plan reuse based on a deductive framework. A formalization of the whole reuse process is proposed including the modiication, representation and retrieval of plans. Plan modiication is based on a semantic approach which yields provably correct modiied plans. The plan library is represented in a hybrid knowledge representation formalism linking the planning logic with a terminological logic and is dynamically created and maintained by the system requiring no user interaction. Apart from sequential plans, this approach enables a planner to reuse and modify plans containing control structures like conditionals and iterations. Comparing the performance of the deductive plan reuse system with performance measures reported from other systems it turns out that deductive approaches can compete very well with heuristic ones.