Miracle-dz/UniFAR-FTUs huggingface dataset:
Adoption of E-Business by Small and Medium Enterprises in Kenya: Barriers and Facilitators

The study looks into the internet-based electronic business adoption profile of small and medium-sized enterprises (SMEs) as well as the factors affecting their willingness to adopt ebusiness usage. The study adopted a literature review methodology where a wide spectrum of literature was interrogated. This methodology has its limitation in that there is need to empirically validate the findings through studies in different geographical regions and economic sectors. It is noted that e-business adoption is significantly influenced by its perceived benefits. The benefits are majorly financial. However, based on the literature reviewed, the main barriers to e-business adoption appear to be the unwillingness of managers to be responsible for technological change. Ignorance surrounding the technology is fuelling concerns about security, costs, legislation and interoperability. This paper is presented in the following order: introduction, problem statement, literature review, theoretical framework, methodology, findings, conclusion and recommendations.
The Effect of Garbage Collection on Cache Performance

Abstract : Cache performance is an important part of total performance in modern computer systems. This paper describes the use of trace-driven simulation to estimate the effect of garbage collection algorithms on cache performance Traces from four large Common Lisp programs have been collected and analyzed with an all-associatively cache simulator. While previous work has focused on the effect of garbage collection on page reference locality this evaluation unambiguously shows that garbage collection algorithms can have a profound effect on cache performance as well. On processors with a direct-mapped cache a generation stop-and-copy algorithm exhibits a miss rate up to four times higher than a comparable generation mark-and-sweep algorithm. Furthermore, two-way set-associative caches are shown to reduce the miss rate in stop-and-copy algorithms often by a factor of two and sometimes by a factor of almost five over direct-mapped caches. As processor speeds increase, cache performance will play an increasing role in total performance. These results suggest that garbage collection algorithms will play an important part in improving that performance.
Preliminary study on early detection technology of lung cancer based on surface-enhanced Raman spectroscopy

This paper analyzes the data of surface-enhanced Raman spectroscopy of the saliva which come from the issues of 19 lung cancers and 45 normal people. The original data are normalized, and then selected the 14 screened characteristic peaks for further Logistic Regression Analysis using SPSS16.0 software. There is significant difference between lung cancer and normal human's Raman spectra of saliva and the accuracy is up to 96.9% by Logistic Regression Analysis. It is also found that two spectrum peaks are different between the normal and the lung cancer's SERS: Raman peak 758 cm-1 is existed in the normal, compared with lower 7cm-1 in patients of lung cancer, and Raman peak 1244cm-1 is existed in the normal compared with lower 11cm-1 in patients of lung cancer. It provides characteristic peaks for clinical diagnosis of lung cancer, especially in the early period.
Depth map compression for unstructured lumigraph rendering

Image-based rendering techniques require capturing an object or scene from many viewpoints. Often, depth maps are used in addition to the original images for rendering new iews for novel viewpoints not coinciding with one of the original camera positions. Due to the high amount of data, efficient compression is necessary. When the data is stored or transmitted, it is not only desirable to compress the image data but also the depth information. In this paper, the case of sequences recorded with a single, hand-held camera is investigated. These sequences are used for unstructured lumigraph rendering. In addition, the case of multi-view video sequences is analyzed. For both cases, depth maps are compressed using H.264/AVC, and the achievable data rates are studied. For the case of unstructured lumigraph rendering, the effect of depth map compression on the quality of rendered images is analyzed in a second step.
‘Much ado about something’ how school leaders affect attitudes towards inclusive education: the case of Oman

ABSTRACT The development of inclusive education (IE) is arguably the biggest challenge currently facing school systems in Oman. School leadership (SL) was argued to be a determinant of organisational effectiveness and an antecedent of organisational commitment (OC). The current study investigated how SL affects teachers’ attitudes towards inclusive education (TATIE). A total of 378 teachers from both genders responded to the Principal Leadership Style (PLS), Scale of Teachers’ Attitudes towards Inclusive Classrooms (STATIC), and the Organisational Commitment Questionnaire (OCQ). Using structural modeling, we tested a set of hypotheses drawn from a conceptualised model which we developed from previous research evidence. Results supported our conceptualised model. OC was found to mediate the relationship between PLS and TATIE. Further, different PLSs showed different indirect effects on TATIE through OC. Results are discussed in relation to the context of Oman.
Fast and Accurate k-llleans For Large Datasets

Clustering is a popular problem with many applications. We consider the k-means problem in the situation where the data is too large to be stored in main memory and must be accessed sequentially, such as from a disk, and where we must use as little memory as possible. Our algorithm is based on recent theoretical results, with significant improvements to make it practical. Our approach greatly simplifies a recently developed algorithm, both in design and in analysis, and eliminates large constant factors in the approximation guarantee, the memory requirements, and the running time. We then incorporate approximate nearest neighbor search to compute k-means in o(nk) (where n is the number of data points; note that computing the cost, given a solution, takes 8(nk) time). We show that our algorithm compares favorably to existing algorithms both theoretically and experimentally, thus providing state-of-the-art performance in both theory and practice.
Design and implementation of a robotic dolphin for water quality monitoring

This paper presents a novel mechanical design and multimodal locomotion control of a bio-inspired robotic dolphin for water quality monitoring. In order to obtain a better hydrodynamic performance, a robotic dolphin modelled after killer whale is developed. Depending on its powerful propulsive posterior body and fluke, the robotic dolphin can realize fast and flexible dolphin-like swimming. Moreover, a pair of pectoral fins with separate degree of freedom and a yawing dorsal fin are designed for turning maneuvers. Besides, many onboard sensors including an inertial navigation system, GPS, a depth sensor, infrared sensors and a replaceable water quality multiprobe are employed to implement autonomous water monitoring task. As for the control level, a Central Pattern Generators (CPGs) -based controller is utilized to realize multimodal locomotion including forward swimming, turning, diving and surfacing. Finally, both extensive experiments and field testing demonstrate the feasibility of the proposed bio-inspired water quality monitoring system.
Modified Decoding Algorithm of LLR-SPA 1

In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain) to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity. Copyright © 2014 IFSA Publishing, S. L.
NiCT at TREC 2009: Employing Three Models for Entity Ranking Track

This paper describes experiments carried out at NiCT for the TREC 2009 Entity Ranking track. Our main study is to develop an effective approach to rank entities via measuring the “similarities” between supporting snippets of entities and input query. Three models are implemented to this end. 1) The DLM regards entity ranking as a task of calculating the probabilities of generating input query given supporting snippets of entities via language model. 2) The RSVM ranks entities via a supervised Ranking SVM. 3) The CSVM, an unsupervised model, ranks entities according to the probabilities of input query belonging to topics represented by entities and their supporting snippets via SVM classifier. The evaluation shows that the DLM is the best on P@10, while the RSVM outperforms the others on nDCG.
AOJS: aspect-oriented javascript programming framework for web development

JavaScript is a popular scripting language that is particularly useful for client-side programming together with HTML /XML on the Web. As JavaScript programs become more complex and large, separation of concerns at the implementation level is a significant challenge. Aspect orientation has been a well known concept to realize improved separation; however, existing mechanisms require modifications in the target modules for aspect weaving in JavaScript (i.e., not "complete" separation). In this paper, we propose an Aspect-Oriented JavaScript framework, named "AOJS", which realizes the complete separation of aspects and other core modules in JavaScript. AOJS can specify function executions, variable assignments and file initializations in JavaScript programs as the joinpoints of aspects. Moreover, AOJS guarantees the complete separation of aspects and core program modules by adopting a proxy-based architecture for aspect weaving. By utilizing these features, we confirmed that AOJS offers improved modifiability and extendability for JavaScript programming.
Improved phone recognition on TIMIT using formant frequency data and confidence measures

This paper presents a novel approach to integration of formant frequency and conventional MFCC data in phone recognition experiments on TIMIT. Naive use of format data introduces classification errors if formant frequency estimates are poor, resulting in a net drop in performance. However, by exploiting a measure of confidence in the formant frequency estimates, formant data can contribute to classification in parts of a speech signal where it is reliable, and be replaced by conventional MFCC data when it is not. In this way an improvement of 4.7% is achieved. Moreover, by exploiting the relationship between formant frequencies and vocal tract geometry, simple formant-based vocal tract length normalisation reduces the error rate by 6.1% relative to a conventional representation alone.
Factorization of canonic homographies for camera calibration and scene modeling

This paper proposes a novel framework to calibrate cameras and model a scene simultaneously using both self-calibration constraints and geometric information on parallelograms. The proposed method is a factorization-based approach solving the problem by decomposing a measurement matrix into camera and parallelogram parameters. Since the factorization-based approach recovers all camera poses simultaneously, the consistency of rigid transformations among cameras can be ensured. This paper also suggests the strategy dealing with the missing data, which is usually an obstacle to factorization-based approaches. The proposed method is more useful than the previous factorization-based approach using parallelepipeds because parallelograms are more basic scene elements. Moreover, this paper describes the unifying method using the constraints from parallelograms and parallelepipeds simultaneously in the proposed framework. The results of the experiments with synthetic data and real outdoor images are presented to demonstrate the feasibility of the proposed method.
Directing for Cinematic Virtual Reality: how the traditional film director’s craft applies to immersive environments and notions of presence

ABSTRACT Virtual Reality (VR) has been an area of research for over 40 years yet only recently has it begun to achieve public acceptance. One key to this has been the development of ‘Cinematic Virtual Reality’ (CVR) where media fidelity approaches that found in feature film. Unlike traditional VR, CVR limits the level of control users have within the environment to choosing viewpoints rather than interacting with the world itself. This means that CVR production arguably represents a new type of filmmaking. Grammars for filmmakers have developed significantly resulting in a rich vocabulary available to use to create compelling stories. Relatedly, researchers into VR have also begun to understand mechanisms behind compelling engagement within VR. This paper looks to find a bridge between these two previously disparate media. It is argued that the concepts of ‘suspension of disbelief’ and ‘presence’ can be linked via ‘transportation theory’. The applicability of existing filmmaking directing techniques for the creation of CVR projects is then explored. Existing film production methods are considered in a manner adapted to establishing ‘presence’ in a CVR space. Finally, areas for future exploration are considered in light of the immaturity of CVR as a medium.
A case study on the Tower of Hanoi challenge: Representation, reasoning and execution

The Tower of Hanoi puzzle, has recently been established as a robotics challenge as a part of EU Robotics coordination action in 2011 and IEEE IROS Conference in 2012. It provides a good standardized test bed to evaluate integration of high-level reasoning capabilities of robots together with their manipulation and perception aspects.We address this challenge within a general planning and monitoring framework: we represent the puzzle in a logic-based formalism, integrate task planning and motion planning, solve this hybrid planning problem with a state-of-the-art automated reasoner (e.g., a SAT solver), execute the computed plans under feedback control while also monitoring for failures, and recover from failures as required. We show the applicability of this framework by implementing it using two robotic manipulators on a physical experimental setup.
Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality.

CONTEXT Better health care quality is a universal goal, yet measuring quality has proven to be difficult and problematic. A central problem has been isolating physician practices from other effects of the health care system. OBJECTIVE To validate clinical vignettes as a method for measuring the competence of physicians and the quality of their actual practice. DESIGN Prospective trial conducted in 1997 comparing 3 methods for measuring the quality of care for 4 common outpatient conditions: (1) structured reports by standardized patients (SPs), trained actors who presented unannounced to physicians' clinics (the gold standard); (2) abstraction of medical records for those same visits; and (3) physicians' responses to clinical vignettes that exactly corresponded to the SPs' presentations. Setting Outpatient primary care clinics at 2 Veterans Affairs medical centers. PARTICIPANTS Ninety-eight (97%) of 101 general internal medicine staff physicians, faculty, and second- and third-year residents consented to be randomized for the study. From this group, 10 physicians at each site were randomly selected for inclusion. MAIN OUTCOME MEASURES A total of 160 quality scores (8 cases x 20 physicians) were generated for each method using identical explicit criteria based on national guidelines and local expert panels. Scores were defined as the percentage of process criteria correctly met and were compared among the 3 methods. RESULTS The quality of care, as measured by all 3 methods, ranged from 76.2% (SPs) to 71.0% (vignettes) to 65.6% (chart abstraction). Measuring quality using vignettes consistently produced scores closer to the gold standard of SP scores than using chart abstraction. This pattern was robust when the scores were disaggregated by the 4 conditions (P<.001 to <.05), by case complexity (P<.001), by site (P<.001), and by level of physician training (P values from <.001 to <.05). The pattern persisted, although less dominantly, when we assessed the component domains of the clinical encounter--history, physical examination, diagnosis, and treatment. Vignettes were responsive to expected directions of variation in quality between sites and levels of training. The vignette responses did not appear to be sensitive to physicians' having seen an SP presenting with the same case. CONCLUSIONS Our data indicate that quality of health care can be measured in an outpatient setting by using clinical vignettes. Vignettes appear to be a valid and comprehensive method that directly focuses on the process of care provided in actual clinical practice. Vignettes show promise as an inexpensive case-mix adjusted method for measuring the quality of care provided by a group of physicians.
High Voltage Breakdown pHEMTs for C-band HPA

High Voltage Breakdown (HVB) HPA MMIC based on GaAs pHEMTs technology represents a useful way for high power RF application. To increase the breakdown voltage respect to conventional device, a field-plate (FP) gate structure is implemented in our standard 0.5 µm process. With this solution the off-state breakdown voltage of the device has been improved from 18V to 28V, while keeping constant the drain current. As expected, FP devices showed smaller drain current collapse than standard devices under pulsed DC measurement conditions and a significant increase in power density, i.e. 1.4 W/mm. To guaranty a full advantage for real HPA applications we have carried out numerical simulations, to optimise device thermal behaviour as a function of GaAs thickness and gate pitch. On the basis of this technology development, reliable and reproducible HPA have been fabricated with an output power of circa 30 W and power added efficiency (PAE) of circa 35% in the 4.9–6.1GHz frequency range. Therefore this proposed technological solution enables the realization of very high power T/R modules with reliable GaAs technology, waiting for more disruptive and less mature GaN HEMT one.
Unusually high mechanical stability of bacterial adhesin extender domains having calcium clamps

To gain insight into the relationship between protein structure and mechanical stability, single molecule force spectroscopy experiments on proteins with diverse structure and topology are needed. Here, we measured the mechanical stability of extender domains of two bacterial adhesins MpAFP and MhLap, in an atomic force microscope. We find that both proteins are remarkably stable to pulling forces between their N- and C- terminal ends. At a pulling speed of 1 μm/s, the MpAFP extender domain fails at an unfolding force Fu = 348 ± 37 pN and MhLap at Fu = 306 ± 51 pN in buffer with 10 mM Ca2+. These forces place both extender domains well above the mechanical stability of many other β-sandwich domains in mechanostable proteins. We propose that the increased stability of MpAFP and MhLap is due to a combination of both hydrogen bonding between parallel terminal strands and intra-molecular coordination of calcium ions.
TOSOM: A Topic-Oriented Self-Organizing Map for Text Organization

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method. Keywords—Self-Organizing Map, Topic Identification, Learning Algorithm, Text Clustering.
Time Course of Processes and Representations Supporting Visual Object Identification and Memory

Event-related potentials (ERPs) were used to delineate the time course of activation of the processes and representations supporting visual object identification and memory. Following K. Srinivas (1993), 66 young people named objects in canonical or unusual views during study and an indirect memory test. Test views were the same or different from those at study. The first ERP repetition effect and earliest ERP format effect started at 150 msec. Multiple ERP repetition effects appeared over time. All but the latest ones were largest for same views, although other aspects of their form specificity varied. Initial ERP format effects support multiple-views-plus-transformation accounts of identification and indicate the timing of processes of object model selection (frontal N350 from 148250 to 500700 msec) and view transformation via mental rotation (posterior N400/P600 from 250356 to 700 msec). Thereafter, a late slow wave reflects a memory process more strongly recruited by different than same views. Overall, the ERP data demonstrate the activation of multiple memory processes over time during an indirect test, with earlier ones (within 148400 msec) characterized by a pattern of form specificity consistent with the specific identification-related neural process or representational system supporting each memory function.
EyeC: Coordinated Views for Interactive Visual Exploration of Eye-Tracking Data

Visual attention and eye movement are important subjects of investigation with a wide area of application scenarios. The analysis of eye tracking data comprises examinations of differences between subjects and groups of subjects and identification of patterns and outliers within and between groups. To allow for such complex queries in an intuitive way, we present an interactive visual analysis tool using coordinated views. The views display areas of interest, statistical graphics of fixation times and time series and comprise novel visual encodings for spatiotemporal analysis and subject similarities. Interaction mechanisms allow for a refined analysis that takes into account all aspects of the data. We apply our approach to eye tracking data from psychological experiments and conduct a case study to demonstrate its effectiveness and intuitiveness.