Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the software engineering component in MIS research

he academic study of management information systems (MIS) is a recent addition to most universities. Because of its arrival, because of the youth of business schools compared to other colleges in universities, and because of the insecurity and uncertainty that marks youth, its study is accompanied by introspective smdies and commentaries about what MIS is and what it should accomplish. As recently as 1980, a founder of the field, Peter Keen, wrote, " At present, MIS research is a theme rather than a substantive field , Perhaps MIS is only a theme , Perhaps MIS will eventually be absorbed into other more clearly-defined disciplines, such as accounting ([141, p. 3. " During the 1980s MlS emerged as a scientific field, although a fragmented and pluralistic one. Davis [6] lists the MIS important reference disciplines as computer science, behavioral science, decision science, organizations and management, organizational functions, management accounting, and microeconomics. Culnan and Swanson [3] simplify this list to three components: computer science, management science, and organization science. We can safely characterize the field of MIS as
Extracting Message Types from BlueGene / L ’ s Logs

In this paper we present the results on extracting message types from the BlueGene/L supercomputer logs using the IPLoM (Iterative Partitioning Log Mining) algorithm. Previous work using IPLoM indicates that IPLoM shows promise as message type extraction algorithm. We compared the results of IPLoM against manually produced message types produced on the BlueGene/L data. To provide a baseline of performance we also perform similar experiments using SLCT (Simple Log File Clustering Tool). The results show that IPLoM improves the performance of SLCT by finding the infrequent patterns in the data and is also able to achieve an F-Measure result of 91% based on micro-average classification accuracy.
Understanding Effects of Subjectivity in Measuring Chord Estimation Accuracy

To assess the performance of an automatic chord estimation system, reference annotations are indispensable. However, owing to the complexity of music and the sometimes ambiguous harmonic structure of polyphonic music, chord annotations are inherently subjective, and as a result any derived accuracy estimates will be subjective as well. In this paper, we investigate the extent of the confounding effect of subjectivity in reference annotations. Our results show that this effect is important, and they affect different types of automatic chord estimation systems in different ways. Our results have implications for research on automatic chord estimation, but also on other fields that evaluate performance by comparing against human provided annotations that are confounded by subjectivity.
Procedural-based category learning in patients with Parkinson's disease: impact of category number and category continuity

Previously we found that Parkinson's disease (PD) patients are impaired in procedural-based category learning when category membership is defined by a nonlinear relationship between stimulus dimensions, but these same patients are normal when the rule is defined by a linear relationship (Maddox and Filoteo, 2001; Filoteo et al., 2005a,b). We suggested that PD patients' impairment was due to a deficit in recruiting “striatal units” to represent complex nonlinear rules. In the present study, we further examined the nature of PD patients' procedural-based deficit in two experiments designed to examine the impact of (1) the number of categories, and (2) category discontinuity on learning. Results indicated that PD patients were impaired only under discontinuous category conditions but were normal when the number of categories was increased from two to four. The lack of impairment in the four-category condition suggests normal integrity of striatal medium spiny cells involved in procedural-based category learning. In contrast, and consistent with our previous observation of a nonlinear deficit, the finding that PD patients were impaired in the discontinuous condition suggests that these patients are impaired when they have to associate perceptually distinct exemplars with the same category. Theoretically, this deficit might be related to dysfunctional communication among medium spiny neurons within the striatum, particularly given that these are cholinergic neurons and a cholinergic deficiency could underlie some of PD patients' cognitive impairment.
The Low-Mass Limit for Total Mass of W UMa-type Binaries

The observations of W UMa type stars show a well-defined short-period limit of 0.22 d, which is equivalent to a lower mass limit of approximately 1 solar mass for the total binary mass. It is currently believed that cool contact binaries are formed from detached binaries losing angular momentum (AM) via a magnetized wind. Orbital evolution of detached binaries with various component masses was followed until the primary component reached the critical Roche surface and the Roche lobe overflow (RLOF) began. It was assumed that the minimum initial, i.e. ZAMS, orbital period of such binaries is equal to 2 d and that the components lose AM just as single stars. According to the mass-dependent formula for AM loss rate of single stars, derived in this paper, the AM loss time scale increases substantially with decreasing stellar mass. The formula was applied to binaries with the initial primary component masses between 1.0 and 0.6 solar mass and two values of mass ratio q=1 and 0.5. Detailed calculations show that the time needed to reach RLOF by a 1 solar mass primary is of the order of 7.5 Gyr, but it increases to more than 13 Gyr for a binary with an initial primary mass of 0.7 solar mass. Binaries with less massive primaries have not yet had time to reach RLOF even within the age of the Universe. This sets a lower mass limit for the presently existing contact binaries
Sparse representation based on matrix rank minimization and k-means clustering for recognition

In this paper, we propose a sparse coding algorithm based on matrix rank minimization and k-means clustering and for recognition. We consider the problem of removing the noise in the training samples and generating more samples at the same time. To accomplish this, we extended the matrix rank minimization problem to cope with complex data. Samples from the same class are segmented into several groups by k-means clustering algorithm, and matrix rank minimization is applied on the clustered data to separate the noises and recover the low-rank structures in the grouped data. An over-complete dictionary is constructed by connecting the low-rank structures and the training samples together to keep the samples diversity. Sparse representation is operated based on this over-complete dictionary for recognition. Furthermore, a parameter is introduced to adjust the weighting of the coefficients that code the noises. We apply the proposed algorithm for character and face recognition. Experiments with improved performances validate the effectiveness of the proposed algorithm.
Beagle: A Stimulating Quest Throughout the Hospital

Beagle is a design concept aiming to improve the quality of life and the development of hospitalized adolescents (12-16) with Cystic Fibrosis (CF). During hospitalization CF patients are isolated to prevent cross infection of bacteria. They suffer from boredom, a decrease in social contact and a negatively affected physical activity level. Beagle is a concept that facilitates various forms of playful interaction for adolescents throughout the hospital, motivating them to become physically active within the boundaries of the hospital's installed segregation policy. A first explorative and qualitative study was conducted to see how adolescents experience and use Beagle.
The analysis of a sparse grid stochastic collocation method for partial differential equations with high-dimensional random input data.

This work describes the convergence analysis of a Smolyak-type sparse grid stochastic collocation method for the approximation of statistical quantities related to the solution of partial differential equations with random coefficients and forcing terms (input data of the model). To compute solution statistics, the sparse grid stochastic collocation method uses approximate solutions, produced here by finite elements, corresponding to a deterministic set of points in the random input space. This naturally requires solving uncoupled deterministic problems and, as such, the derived strong error estimates for the fully discrete solution are used to compare the computational efficiency of the proposed method with the Monte Carlo method. Numerical examples illustrate the theoretical results and are used to compare this approach with several others, including the standard Monte Carlo.
Graphical readings of possibilistic logic bases

Possibility theory offers either a qualitative, or a numerical framework for representing uncertainty, in terms of dual measures of possibility and necessity. This leads to the existence of two kinds of possibilistic causal graphs where the conditioning is either based on the minimum, or on the product operator. Benferhat et al. [3] have investigated the connections between min-based graphs and possibilistic logic bases (made of classical formulas weighted in terms of certainty). This paper deals with a more difficult issue: the product-based graphical representation of possibilistic bases, which provides an easy structural reading of possibilistic bases.
Results from the Mars Phoenix Lander Robotic Arm experiment

[1] The Mars Phoenix Lander was equipped with a 2.4 m Robotic Arm (RA) with an Icy Soil Acquisition Device capable of excavating trenches in soil deposits, grooming hard icy soil surfaces with a scraper blade, and acquiring icy soil samples using a rasp tool. A camera capable of imaging the scoop interior and a thermal and electrical conductivity probe were also included on the RA. A dozen trench complexes were excavated at the northern plains landing site and 31 samples (including water-ice-bearing soils) were acquired for delivery to instruments on the Lander during the 152 sol mission. Deliveries included sprinkling material from several centimeters height to break up cloddy soils on impact with instrument portals. Excavations were done on the side of the Humpty Dumpty and the top of the Wonderland polygons, and in nearby troughs. Resistive forces encountered during backhoe operations show that soils above the 3–5 cm deep icy soil interfaces are stronger with increasing depth. Further, soils are similar in appearance and properties to the weakly cohesive crusty and cloddy soils imaged and excavated by the Viking Lander 2, which also landed on the northern plains. Adsorbed H2O is inferred to be responsible for the variable nature and cohesive strength of the soils. Backhoe blade chatter marks on excavated icy soil surfaces, combined with rasp motor currents, are consistent with laboratory experiments using grain-supported icy soil deposits, as is the relatively rapid decrease in icy soil strength over time as the ice sublimated on Mars.
Continuous Stochastic Feature Mapping Based on Trajectory HMMs

This paper proposes a technique of continuous stochastic feature mapping based on trajectory hidden Markov models (HMMs), which have been derived from HMMs by imposing explicit relationships between static and dynamic features. Although Gaussian mixture model (GMM)- or HMM-based feature-mapping techniques work effectively, their accuracy occasionally degrades due to inappropriate dynamic characteristics caused by frame-by-frame mapping. While the use of dynamic-feature constraints at the mapping stage can alleviate this problem, it also introduces inconsistencies between training and mapping. The technique we propose can eliminate these inconsistencies while retaining the benefits of using dynamic-feature constraints, and it offers entire sequence-level transformation rather than frame-by-frame mapping. The results obtained from speaker-conversion, acoustic-to-articulatory inversion-mapping, and noise-compensation experiments demonstrated that our new approach outperformed the conventional one.
Rapid High Resolution Genotyping of Francisella tularensis by Whole Genome Sequence Comparison of Annotated Genes (“MLST+”)

The zoonotic disease tularemia is caused by the bacterium Francisella tularensis. This pathogen is considered as a category A select agent with potential to be misused in bioterrorism. Molecular typing based on DNA-sequence like canSNP-typing or MLVA has become the accepted standard for this organism. Due to the organism’s highly clonal nature, the current typing methods have reached their limit of discrimination for classifying closely related subpopulations within the subspecies F. tularensis ssp. holarctica. We introduce a new gene-by-gene approach, MLST+, based on whole genome data of 15 sequenced F. tularensis ssp. holarctica strains and apply this approach to investigate an epidemic of lethal tularemia among non-human primates in two animal facilities in Germany. Due to the high resolution of MLST+ we are able to demonstrate that three independent clones of this highly infectious pathogen were responsible for these spatially and temporally restricted outbreaks.
A Network-Based Logistics Tracking and Communication Information System

Through RFID technology and the positioning and navigation technology based on Wi-Fi/ GPS, we establish the logistics tracking information system (LTIS) of the supply chain storage and transportation. On the basis of which we propose a network-based logistics tracking and communication information system (LTCIS). In this process ,we combine with other sophisticated means of communication technology by coupling and network. Key words-RFID;GPS; LTIS; LTCIS
OF PARTICLE-MATTER-INTERACTION-BASED COOLING SCHEMES FOR A NEUTRINO FACTORY *

An ionization cooling channel is a tightly spaced lattice containing absorbers for reducing the momentum of the muon beam, rf cavities for restoring the momentum and strong solenoids for focusing the beam. Such a lattice is an essential feature of most designs for Neutrino Factories and Muon Colliders. Here, we explore three different approaches for designing ionization cooling channels with periodic solenoidal focusing. Key parameters such as the engineering constraints that are arising from the length and separation between the solenoidal coils are systematically examined. In addition, we propose novel approaches for reducing the peak magnetic field inside the rf cavities by using either a magnetic shield system or a bucked coils configuration. Our lattice designs are numerically examined against two independent codes: The ICOOL and G4BL code. The feasibility of our proposed cooling channels to muon accelerators is examined by applying the proposed lattices to the frontend of a Neutrino Factory.
Virtual test driver for critically stable driving maneuvers

In this paper a virtual test driver will be presented which has been developed to carry out standard test maneuvers. The virtual test driver must be able to effectively control a road vehicle under critically stable driving conditions. Results obtained from the virtual test driver will be used to evaluate the performance of a race car under development as an entrant to the Formula Student competition.
Towards an Estimation of the Accuracy of TCP Reassembly in Network Forensics

Today, honeypot operators are strongly relying on network analysis tools to examine network traces collected in their honeynet environment. The accuracy of such analysis depends on the ability of the tools to properly reassemble streams especially TCP sessions. Network forensics analysis quality is tight to those tools and we evaluated widely used network analysis tools. We pinpoint TCP reassembly errors with their causes and propose algorithms and analytical techniques to measure them in order to improve network forensic analysis.
Antennas and Propagation in UHF RFID Systems

In this paper, we discuss antennas and propagation aspects in current passive UHF RFID systems. We consider a "reader-tag-reader" link and concentrate on each part of it: reader antennas, propagation channel, and tags. We include channel modeling equations and support our discussion with experimental measurements of tag performance in various conditions. We also provide a comprehensive literature review.
A multi-technique characterization of electroless gold contacts on single crystal CdZnTe radiation detectors

Cadmium zinc telluride (CdZnTe) is now established as a popular choice of sensor for the detection of γ-rays and hard x-rays, leading to its adoption in security, medical and scientific applications. There are still many technical challenges involving the deposition of high-quality, uniform metal contacts on CdZnTe. A detailed understanding of the interface between the bulk CdZnTe and the metal contacts is required for improvements to be made. To understand these complex interfaces, a range of complementary materials characterization techniques have been employed, including x-ray photoelectron spectroscopy depth profiling, focused ion beam cross section imaging and energy dispersive x-ray spectroscopy. In this paper a number of Redlen CdZnTe detectors with asymmetric anode/cathode contacts have been investigated. The structures of the contacts were imaged and their compositions identified. It was found that the two stage electroless indium/electroless gold deposition process on ‘polished only’ surfaces formed a complex heterojunction on the cathode, incorporating compounds of gold, gold–tellurium, tellurium oxide (of varying stoichiometry) and cadmium chloride up to depths of several 100 nm. Trace amounts of indium were found, in the form of an indium–gold compound, or possibly indium oxide. At the surface of the CdZnTe bulk, a thin Cd depleted layer was observed. The anode heterojunction, formed by a single stage electroless gold deposition, was thinner and exhibited a simpler structure of gold and tellurium oxide. The differing (asymmetric) nature of the anode/cathode contacts gave rise to asymmetric current–voltage (I–V) behaviour and spectroscopy.
A baseline method for search-based software engineering

Background: Search-based Software Engineering (SBSE) uses a variety of techniques such as evolutionary algorithms or meta-heuristic searches but lacks a standard baseline method. Aims: The KEYS2 algorithm meets the criteria of a baseline. It is fast, stable, easy to understand, and presents results that are competitive with standard techniques. Method: KEYS2 operates on the theory that a small sub-set of variables control the majority of the search space. It uses a greedy search and a Bayesian ranking heuristic to fix the values of these variables, which rapidly forces the search towards stable high-scoring areas. Results: KEYS2 is faster than standard techniques, presents competitive results (assessed with a rank-sum test), and offers stable solutions. Conclusions: KEYS2 is a valid candidate to serve as a baseline technique for SBSE research.
Secret Sharing Systems with Authentication-Based Steganography

Recently, Lin and Tsai proposed a secret image-sharing scheme using steganography and a parity-checking detection mechanism to provide effective security for secret image sharing. In this paper, we present a robust authentication method to detect stego-images, while retaining the same high capacity of embedding information, with a cyclic redundancy check and hash function both being applied for authentication detection. As observed from our experiments, the quality of shares embedded in the stego-image in our scheme was higher than that of previous studies. Therefore, in terms of precise detection and higher PSNR measures, the requirements for both authentication and fidelity were satisfied.
A morphological analysis of Arabic language based on multicriteria decision making: TAGHIT system

In this paper, we present our work on Arabic morphology and especially the mechanisms for resolving the morphological ambiguity in Arabic text. These researches, which have given birth to TAGHIT system which is a morphosyntactic tagger for Arabic, where the originality of our work lies in the implementation of our internal system of a new approach to disambiguation different from those that currently exist, which is based on the principles and techniques issued from multicriteria decision making.
Constructing Network Coding in Cyclic Networks with the Best Linear Independence

Capacity of Network coding in cyclic networks can be strictly better than routing. Harvey et al. showed that it exists in the practical scenarios such as the widespread P2P networks. Thus, it is of application significance to investigate how to construct network code in cyclic networks. According to Li et al., there are four levels of network code in cyclic networks, including Convolutional Multicast(CM), Convolutional Broadcast(CB), Convolutional Dispersion(CD), and Basic Convolutional Network Code(BCNC). This paper focuses on the BCNC that is with the best linear independence, which means it can provide the most efficient transmission in that it has the minimum redundance. The contributions of this paper are (1)to improve our previous BCNC algorithm; (2)to show insights of the essential difference between BCNC and CM/CB/CD which is of great theoretical significance to understand how different kinds of cycles affect the network coding construction.
Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp. ] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination.