Miracle-dz/UniFAR-FTUs huggingface dataset:
SLA Defined Metrics as a Tool to Manage Outsourced Help Desk Support Services

Many organizations implement information technology (IT) service management practices to improve IT operations as it contributes to organizational performance. When outsourcing an IT service such as help desk support for customers, the organization may some of its ability to manage the relationship and ensure effective services are provided to the organization and customers. This paper presents the case of the Colorado Community College System’s use of specific metrics, defined in the service level agreement (SLA), as a tool to manage the relationship with an outsourced IT help desk support service.
Improving mobile ad-hoc streaming performance through adaptive layer selection with scalable video coding

Numerous types of mobile devices are now popular with end users, who increasingly use them to carry multimedia content on the go. As wireless connectivity is integrated into many handheld devices, streaming multimedia content among mobile ad-hoc peers is becoming a popular application. In this paper, we first introduce a mathematical model for calculating the probability of successfully streaming a multimedia object between two mobile ad-hoc peers. Unlike previous techniques that assume a constant wireless bandwidth or fixed node location, our work supports the 802.11 Auto-Rate Fallback scheme along with two popular mobility models: the random waypoint and the random walk mobility model. When delivery of the whole video content is of crucial importance, we introduce a novel streaming strategy to improve the probability of successfully streaming a video sequence based on our proposed mathematical model. This strategy takes advantage of the Scalable Video Coding scheme to adaptively select the number of enhancement layers to be streamed to the receiver. Simulation results show that our strategy can improve the probability to stream a media object by a maximum of 60% while keeping the video quality relatively high.
Urinary Signatures of Renal Cell Carcinoma Investigated by Peptidomic Approaches

Renal Cell Carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's lifespan only for early stage tumours. Moreover, solid renal masses cannot be confidently differentiated from RCC. Therefore, markers to distinguish malignant kidney tumours and for their detection are needed. Two different peptide signatures were obtained by a MALDI-TOF profiling approach based on urine pre-purification by C8 magnetic beads. One cluster of 12 signals could differentiate malignant tumours (n = 137) from benign renal masses and controls (n = 153) with sensitivity of 76% and specificity of 87% in the validation set. A second cluster of 12 signals distinguished clear cell RCC (n = 118) from controls (n = 137) with sensitivity and specificity values of 84% and 91%, respectively. Most of the peptide signals used in the two models were observed at higher abundance in patient urines and could be identified as fragments of proteins involved in tumour pathogenesis and progression. Among them: the Meprin 1α with a pro-angiogenic activity, the Probable G-protein coupled receptor 162, belonging to the GPCRs family and known to be associated with several key functions in cancer, the Osteopontin that strongly correlates to tumour stages and invasiveness, the Phosphorylase b kinase regulatory subunit alpha and the SeCreted and TransMembrane protein 1.
Time-domain interpolated channel estimation with noise suppression for multicarrier transmissions

The accuracy of channel estimation has a great impact on the system throughput of multicarrier transmissions. Two novel time-domain interpolated channel estimation schemes are proposed. Channel estimates in the frequency domain are transformed into the time domain and a threshold on either actual power or accumulative power is applied to minimize the noise jitter over the whole bandwidth. Then, the noise suppressed channel estimates are transformed back into the frequency domain by FFT interpolation for channel equalization. The numerical results show that the proposed algorithms can considerably improve the system throughput over conventional schemes.
How useful are semantic links for the detection of implicit references in CSCL chats?

Chat conversations are used for a large range of Computer-Supported Collaborative Learning (CSCL) tasks especially because they allow the creation of multiple conversation threads that run in parallel. Thus, several different topics can be debated at the same time, fostering the exploitation of different ideas and facilitating collaborative knowledge creation. In order to detect these threads, our method proposed to firstly detect the links that arise between the utterances of a conversation. From a computational linguistics perspective, there is a wide variety of different types of links between utterances and there is no mechanism to compute all of them. This paper proposes to explain to what degree semantic similarity measures from Natural Language Processing (NLP) may be used to detect the links that arise between utterances in CSCL chat conversations and which is the effectiveness of applying solely this technique for implicit links identification.
Reliability of Module Based Software System

This paper consider the problem of determining the reliability of a software system which can be decomposed in a number of modules. We have derived the expression of the reliability of a system using the Markovian model for the transfer of control between modules in order. We have given the expression of reliability by considering both benign and catastrophic failure. The expression of reliability presented in this work is applicable for some control software which are designed to detect its own internal errors.
Evaluation of the Document Categorization in "Fixed-point Observatory"

“Fixed-point observatory” is a prototype to support users to grasp recent trends in the fields of their interest from large-scale information. It consists of content-based categorizer, named-entity-based categorizer and multiple-document summarizer. We have evaluated the content-based categorizer, which adopts the simple “bag-of-words” model. Though the quality seems be sufficient for rough classification, it might be improved to use the categorizer in other applications.
RepTor: An Intelligent Hybrid Neural Network Based Recipe Generator for Semiconductor Process Modeling and Characterization

An intelligent hybrid neural network based recipe generator is presented as a convenient tool for process optimization typically aiming highly-nonlinear plasma process in semiconductor manufacturing. As the wafer size continuously expanding up to 300mm in current high-volume manufacturing (even forecasting 450mm in 2012), fast and convenient process settlement cannot be over emphasized to meet the time-to-market of the newly developed products. In this paper, we suggest a recipe generator based on neural network and particle swamp optimization, nominally RepTor, to help minimizing material cost for process setup and maximizing accuracy of process modeling. RepTor is verified using SiO2 deposition process for modeling and predicting the wafer geometry in conjunction with tool parameter. We have convinced the capability of the suggested recipe generator, and it provides a good starting point for further fine tuning of process optimization.
AGE INFLUENCES ASYMMETRY IN DIFFERENTIAL LUMINANCE SENSITIVITY

Just as the eye changes morphologically with aging, many visual functions also decrease during life1-3. Age-related decrease of differential luminance sensitivity (dls) has often been described in perimetric studies4, whereas little is yet known about the effect of age on asymmetries in the visual field5. Our study evaluates the influence of age on nasal-temporal and superior-inferior asymmetries in incremental and decremental dls.
Combination therapy with an angiotensin‐converting‐enzyme inhibitor and an angiotensin II receptor antagonist ameliorates microinflammation and oxidative stress in patients with diabetic nephropathy

Recent studies have pointed to the effectiveness of combination therapy with an angiotensin‐converting‐enzyme inhibitor (ACEI) and an angiotensin receptor blocker (ARB) for diabetic nephropathy. However, some controversy over this combination treatment remains and the mechanisms underlying its renoprotective effects have not been fully clarified. Therefore, we compared the renoprotective effects of imidapril (ACEI) and losartan (ARB) combination therapy with losartan monotherapy in patients with diabetic nephropathy. We also compared the anti‐inflammatory and anti‐oxidative stress effects of these two treatments.
A data analytics case study assessing factors affecting pavement deflection values

Road networks are a national critical infrastructure. The road assets need to be monitored and maintained efficiently as their conditions deteriorate over time. The condition of one of such assets, road pavement, plays a major role in the road network maintenance programmes. Pavement conditions depend upon many factors such as pavement types, traffic and environmental conditions. This paper presents a data analytics case study for assessing the factors affecting the pavement deflection values measured by the traffic speed deflectometer TSD device. The analytics process includes acquisition and integration of data from multiple sources, data pre-processing, mining useful information from them and utilising data mining outputs for knowledge deployment. Data mining techniques are able to show how TSD outputs vary in different roads, traffic and environmental conditions. The generated data mining models map the TSD outputs to some classes and define correction factors for each class.
Late-onset bilateral lens dislocation and glaucoma associated with a novel mutation in FBN1

Purpose To describe the clinical and genetic findings in one Chinese family with late-onset bilateral lens dislocation and secondary glaucoma. Methods One family including three affected members and 16 unaffected family members was examined clinically. After informed consent was obtained, genomic DNA was extracted from venous blood of all participants. Linkage analysis was performed with two microsatellite markers around the fibrillin-1 (FBN1) gene (D15S992 and D15S126). Mutation screening was performed using direct DNA sequence analysis and single strand conformation polymorphism (SSCP). Results Clinical examination and pedigree analysis revealed that four members in three generations were affected by late-onset lens dislocation and secondary glaucoma but had no signs of cardiovascular abnormality or abnormal skeletal features. By genotyping, the family showed the linkage to FBN1 on 15q21.1. After mutation screening analysis on 65 exons of FBN1, a novel heterozygous missense mutation, c.2860C>T (R954C), was detected. This mutation cosegregated with the disease phenotype in the family and was not found in 100 normal controls. Conclusions Late-onset isolated ectopia lentis with secondary glaucoma is consistent with a novel mutation in FBN1. Our finding expands the spectrum of FBN1 mutations and is useful for further genetic consultation and genetic diagnosis.
Investigating the social integration and wellbeing of transgender individuals: A meta-synthesis

ABSTRACT Introduction: There is growing literature about the experiences of social integration and wellbeing of transgender individuals. However, there has been no synthesis across this body of research. Accordingly, the aim of this review was to aggregate, interpret, and synthesize findings from qualitative studies pertaining to the social integration and wellbeing of transgender individuals. Methods: This study synthesized findings from 18 qualitative and mixed method studies which had explored the social integration and wellbeing of transgender individuals, using Noblit and Hare's meta-ethnography method. The Critical Appraisal Skills Programme was also used to appraise the 18 included studies. Results: Data from the included 18 individual studies ranged from moderate to strong in quality. Data analysis revealed five major themes which influenced transgender individuals' daily lives. These were gender transition and disclosing gender identity, health and self-isolation, living with stigma and discrimination: health care, leisure and work, the importance of relationships, and last, overcoming adversity: stories of what can work. Conclusion: This meta-synthesis reinforces many preconceived notions about transgender individuals. These include being at high risk of social exclusion, experiencing discrimination and stigma across many social situations, and last, being at high risk of poor wellbeing. This study also found that there is further need for studies that investigate the self-isolation of transgender individuals as well as this group's relationship and experiences with health care professionals and providers.
Mapping Complex Urban Land Cover from Spaceborne Imagery: The Influence of Spatial Resolution, Spectral Band Set and Classification Approach

Detailed land cover information is valuable for mapping complex urban environments. Recent enhancements to satellite sensor technology promise fit-for-purpose data, particularly when processed using contemporary classification approaches. We evaluate this promise by comparing the influence of spatial resolution, spectral band set and classification approach for mapping detailed urban land cover in Nottingham, UK. A WorldView-2 image provides the basis for a set of 12 images with varying spatial and spectral characteristics, and these are classified using three different approaches (maximum likelihood (ML), support vector machine (SVM) and object-based image analysis (OBIA)) to yield 36 output land cover maps. Classification accuracy is evaluated independently and McNemar tests are conducted between all paired outputs (630 pairs in total) to determine which classifications are significantly different. Overall accuracy varied between 35% for ML classification of 30 m spatial resolution, 4-band imagery and 91% for OBIA classification of 2 m spatial resolution, 8-band imagery. The results demonstrate that spatial resolution is clearly the most influential factor when mapping complex urban environments, and modern “very high resolution” or VHR sensors offer great advantage here. However, the advanced spectral capabilities provided by some recent sensors, coupled with contemporary classification approaches (especially SVMs and OBIA), can also lead to significant gains in mapping accuracy. Ongoing development in instrumentation and methodology offer huge potential here and imply that urban mapping opportunities will continue to grow.
Evaluating the Application of Learning Requirements Planning Model in the ERP Project of Esfahan Steel Company

It seems that inappropriate application and implementation of Enterprise Resource Planning (ERP) can harm performance of organizations. For the ERP to be successful there is a necessity for a systematic training plan aligned with the organizational master plan. The model of Learning Requirements Planning (LRP) is developed for linking training with the implementation process of ERP. The aim of this article is to investigate and evaluate the application of LRP model in the ERP project of Esfahan Steel Company as the pioneer in the steel industry of Iran. This research is survey based. The research population includes the employees involved in the implementation of ERP. The results imply that at the time of implementing the project, the required training has not been effective and since the accomplishment of the project, learning has not been continuous. Consequently, in the implementation of the ERP project of Esfahan Steel Company, learning has not been treated effectively.
A Possible Origin of Bimodal Distribution of Gamma-Ray Bursts

We study the distribution of the durations of gamma-ray bursts (GRBs) in the unified model of short and long GRBs recently proposed by Yamazaki, Ioka, and Nakamura. Monte Carlo simulations show clear bimodal distributions, with lognormal-like shapes for both short and long GRBs, in a power-law as well as a Gaussian angular distribution of the subjets. We find that the bimodality comes from the existence of the discrete emission regions (subjets or patchy shells) in the GRB jet. To explain other temporal properties of short and long GRBs, the subjet parameters should depend on the angle in the whole jet.
Signature Movements Lead to Efficient Search for Threatening Actions

The ability to find and evade fighting persons in a crowd is potentially life-saving. To investigate how the visual system processes threatening actions, we employed a visual search paradigm with threatening boxer targets among emotionally-neutral walker distractors, and vice versa. We found that a boxer popped out for both intact and scrambled actions, whereas walkers did not. A reverse correlation analysis revealed that observers' responses clustered around the time of the “punch", a signature movement of boxing actions, but not around specific movements of the walker. These findings support the existence of a detector for signature movements in action perception. This detector helps in rapidly detecting aggressive behavior in a crowd, potentially through an expedited (sub)cortical threat-detection mechanism.
The Relationship Between Agnostic Selective Classification Active Learning and the Disagreement Coefficient

A selective classifier (f,g) comprises a classification function f and a binary selection function g, which determines if the classifier abstains from prediction, or uses f to predict. The classifier is called pointwise-competitive if it classifies each point identically to the best classifier in hindsight (from the same class), whenever it does not abstain. The quality of such a classifier is quantified by its rejection mass, defined to be the probability mass of the points it rejects. A "fast" rejection rate is achieved if the rejection mass is bounded from above by O(1/m) where m is the number of labeled examples used to train the classifier (and O hides logarithmic factors). Pointwise-competitive selective (PCS) classifiers are intimately related to disagreement-based active learning and it is known that in the realizable case, a fast rejection rate of a known PCS algorithm (called Consistent Selective Strategy) is equivalent to an exponential speedup of the well-known CAL active algorithm. We focus on the agnostic setting, for which there is a known algorithm called LESS that learns a PCS classifier and achieves a fast rejection rate (depending on Hanneke's disagreement coefficient) under strong assumptions. We present an improved PCS learning algorithm called ILESS for which we show a fast rate (depending on Hanneke's disagreement coefficient) without any assumptions. Our rejection bound smoothly interpolates the realizable and agnostic settings. The main result of this paper is an equivalence between the following three entities: (i) the existence of a fast rejection rate for any PCS learning algorithm (such as ILESS); (ii) a poly-logarithmic bound for Hanneke's disagreement coefficient; and (iii) an exponential speedup for a new disagreement-based active learner called ActiveiLESS.
Simultaneous time- and frequency-domain extrapolation

In this paper, given the early-time response and the low-frequency response of a causal system, we simultaneously extrapolate them in the time and frequency domains. The approach is iterative and is based on a simple discrete Fourier transform. Simultaneous extrapolation in time and frequency domains is further enhanced by using the matrix pencil technique in the time domain and the Cauchy method in the frequency domain. The results are further enhanced through the Hilbert transform, hence enforcing the physical constraints of the system and thereby guaranteeing a causal extrapolation in time. It is, therefore, possible to generate information over a larger domain from limited data. It is important to note that through this extrapolation, no new information is created. The early-time and low-frequency data are complementary and contain all the desired information. The key is to extract this information in an efficient and accurate manner. The electric current on a scatterer is used as an example for the method.
Mislocalized Rhodopsin Does Not Require Activation to Cause Retinal Degeneration and Neurite Outgrowth in Xenopus laevis

Mutations in the C terminus of rhodopsin disrupt a rod outer segment localization signal, causing rhodopsin mislocalization and aggressive forms of retinitis pigmentosa (RP). Studies of cultured photoreceptors suggest that activated mislocalized rhodopsin can cause cell death via inappropriate G-protein-coupled signaling. To determine whether this pathway occurs in vivo, we developed a transgenic Xenopus laevis model of RP based on the class I rhodopsin mutation Q344Ter (Q350Ter in X. laevis). We used a second mutation, K296R, to block the ability of rhodopsin to bind chromophore and activate transducin. We compared the effects of expression of both mutants on X. laevis retinas alone and in combination. K296R did not significantly alter the cellular distribution of rhodopsin and did not induce retinal degeneration. Q350Ter caused rhodopsin mislocalization and induced an RP-like degeneration, including loss of rods and development of sprouts or neurites in some remaining rods, but did not affect the distribution of endogenous rhodopsin. The double mutant K296R/Q350Ter caused a similar degeneration and neurite outgrowth. In addition, we found no protective effects of dark rearing in these animals. Our results demonstrate that the degenerative effects of mislocalized rhodopsin are not mediated by the activated form of rhodopsin and therefore do not proceed via conventional G-protein-coupled signaling.
Sensing visual attention using an interactive bidirectional HMD

This paper presents a novel system for sensing of attentional behavior in Augmented Reality (AR) environments by analyzing eye movement. The system is based on light weight head mounted optical see-through glasses containing bidirectional microdisplays, which allow displaying images and eye tracking on a single chip. The sensing and interaction application has been developed in the European project ARtSENSE in order to (1) detect museum visitors attention/interest in artworks as well as in presented AR content, (2) present appropriate personalized information based on the detected attention as augmented overlays, and (3) allow museum visitors gaze-based interaction with the system or the AR content. In this paper we present a novel algorithm for pupil estimation in low resolution eye-tracking images and show first results on attention estimation by eye movement analysis and interaction with the system by gaze.
Promoting Cultural Traditions, Social Inclusion and Local Community Participation in Environmental Development Schemes

The protection of the environment has been at the heart of local communities. The old sages, in most communities creatively fashioned cultural traditions with the goal of conserving the environment while judiciously using its precious resources. It is regrettable that local people and their time-tested cultural practices are neglected in environmental schemes, especially at the consultation and implementation stages. The thrust of the research was to highlight the benefits of incorporating local communities and their cultural traditions in all activities related to the environment using the classic example of the people of Anyinam in Ghana. Focus group discussions and direct observations were the main instrumentations used for soliciting data from the phenomenological study in a qualitative research approach. The study concludes that developmental planners and policy makers must promote the full participation of local communities in environmental schemes to aid in better infrastructure development schemes for the environment.