Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Technology Risk in R&D Project Planning: Optimal Timing and Parallelization of R&D Activities

An inherent characteristic of R&D projects is technological uncertainty, which may result in project failure, and time and resources spent without any tangible return. In pharmaceutical projects, for instance, stringent scientific procedures have to be followed to ensure patient safety and drug efficacy in pre-clinical and clinical tests before a medicine can be approved for production. A project consists of several stages, and may have to be terminated in any of these stages, with typically a low likelihood of success. In project planning and scheduling, this technological uncertainty has typically been ignored, and project plans are developed only for scenarios in which the project succeeds. In this paper, we examine how to schedule projects in order to maximize their expected net present value, when the project activities have a probability of failure, and where an activity's failure leads to overall project termination. We formulate the problem, show that it is NP-hard and develop a branchand- bound algorithm that allows to obtain optimal solutions. We also present polynomial-time algorithms for special cases, and present a number of managerial insights for R&D project and planning, including the advantages and disadvantages of parallelization of R&D activities in different settings.
Optimal splitters for database partitioning with size bounds

Partitioning is an important step in several database algorithms, including sorting, aggregation, and joins. Partitioning is also fundamental for dividing work into equal-sized (or balanced) parallel subtasks. In this paper, we aim to find, materialize and maintain a set of partitioning elements (splitters) for a data set. Unlike traditional partitioning elements, our splitters define both inequality and equality partitions, which allows us to bound the size of the inequality partitions. We provide an algorithm for determining an optimal set of splitters from a sorted data set and show that it has time complexity O(k lg2 N), where k is the number of splitters requested and N is the size of the data set. We show how the algorithm can be extended to pairs of tables, so that joins can be partitioned into work units that have balanced cost. We demonstrate experimentally (a) that finding the optimal set of splitters can be done efficiently, and (b) that using the precomputed splitters can improve the time to sort a data set by up to 76%, with particular benefits in the presence of a few heavy hitters.
Cost of SIP Signaling in Wireless Networks and Services

Developers of SIP mostly concentrated on making SIP to do what no other protocol can do. In a way they failed to consider the weaknesses and dangers. From this realization we did a study on the weaknesses of SIP and SIP signaling in Wireless Networks and Services. From our study we identified Delay and Security as the most severe problems, which we discuss in this paper.
Designing the Unexpected: Endlessly Fascinating Interaction for Interactive Installations

We present A Delicate Agreement, an interactive art installation designed to intrigue viewers by offering them an unfolding story that is endlessly fascinating. To achieve this, we set our story in the liminal space of an elevator, and populated this elevator with a set of unique characters. Viewers watch the story unfold through peepholes in the elevator's doors, where in turn their gaze can trigger changes in the storyline. This storyline's interactive response was created via a complex adaptive system using simple rules based on Goffman's performance theory.
Association between MTHFR C677T Polymorphism and Risk of Acute Lymphoblastic Leukemia: A Meta-Analysis Based on 51 Case-Control Studies

Background Studies and systematic reviews have reached inconsistent conclusions on the role of 5, 10-methylenetetrahydrofolate reductase (MTHFR) polymorphism C677T in acute lymphoblastic leukemia (ALL) risk. Material/Methods The present meta-analysis comprising of 51 case-control studies, including 7892 cases and 14 280 controls was performed to reevaluate the association between MTHFR C677T polymorphism and ALL risk. Results Statistical differences were found in the dominant model (TT+CT vs. CC, odd ratio (OR)=0.89, 95% CI, 0.79–1.00, P=0.04) and the CT vs. CC (OR=0.89, 95% CI, 0.80–1.00, P=0.05), but not in the allele contrast model (T vs. C, OR=0.92, 95% CI, 0.84–1.01, P=0.08), additive model (TT vs. CC, OR=0.87, 95% CI, 0.73–1.05, P=0.15), or recessive model (TT vs. CT+CC, OR=0.94, 95% CI, 0.81–1.10, P=0.44) in overall populations. In the subgroup analyses stratified by age (children and adults) and ethnicity (Asian and Caucasian), no significant associations between MTHFR C677T polymorphism and ALL risk were observed. Conclusions The current study found no sufficient evidence of a protective role of MTHFR C677T polymorphism in ALL susceptibility.
Ability to 'explain in plain english' linked to proficiency in computer-based programming

This study investigates the relationship between novice programmers' ability to explain code segments and their ability to write code. Results show a strong correlation between ability to correctly answer 'explain in plain English' (EiPE) questions and ability to write code indicating that there are aspects of reasoning about code that are common to both writing code and explaining code. Student explanations were categorized using the Structure of the Observed Learning Outcome (SOLO) taxonomy. The better programmers were more likely to articulate relational aspects of the algorithms. While earlier work also found such a link, the code writing in those earlier studies was done on paper. This is the first such result where the writing component was done with 'hands on' a computer. Our results add further evidence for the existence of an aspect of reasoning about code that is common to both explaining code and writing code, which in turn suggests that a judicious mix of teaching both code skills and code explaining skills may lead to a more effective process by which novices learn to reason about code.
Capacity evaluation with limited feedback for amplify-and-forward MIMO relay channels in urban environment

The combination of multiple-input multiple-output (MIMO) and relay technology promises to increase coverage and system capacity, while the actual performance of MIMO relay system highly depends on the practical channel conditions. Based on the propagation measurement data in urban environment, we deal with the capacity evaluation for a two-hop amplify-and-forward MIMO relay channel in this paper. Since achieving the theoretic capacity requires the channel state information of both hops at the relay node, a limited feedback scheme is introduced. Distinguished from the conventional schemes, both precoding matrix and channel eigenvalues are quantized and fed back, and a novel codebook design method for the eigenvalues is proposed. Adopting the presented scheme, the values of ergodic capacity for various antenna configurations, precoding codebooks, feedback quantities and power allocation strategies are finally evaluated by real channel responses. The numerical results indicate that the proposed scheme outperforms the existing ones and the channel eigenvalues are essential for feedback.
Ensemble approach to detect profile injection attack in recommender system

Recommender systems apply knowledge discovery techniques to specific problem of making personalized recommendation for the products or services to the users. The huge growth in the information and the number of visitors to the web sites especially on e-commerce in last few years creates some challenges for recommender systems. E-commerce recommender systems are highly vulnerable to the profile injection attacks, involving insertion of fake profiles into the system to influence the recommendations made to the users. Prior work has shown that even a small number of malicious profiles can bias the system significantly. In this paper, we compare six machine learning algorithms and based on their performance we build our ensemble model and measure its performance in the detection of profile injection attacks.
A New Di erential Formalism forOptimization of Set

In many practical problems, we must optimize a set function, i.e., nd a set a for which f(a) ! max, where f is a function deened on the class of sets. Such problems appear in design, in image processing, in game theory, etc. In particular, if we use statistical methods (i.e., random sets) to solve the corresponding set-related practical problems, then, at the end, we get a probability distribution on the class of all sets; to arrive at a single answer, we can, e.g., apply the Maximum Likelihood Method, i.e., optimize the likelihood set function L(a). Most optimization problems can be solved (or at least simpliied) by using the fact that small deviations from an optimal solution can only decrease the value of the objective function; as a result, some derivative must be equal to 0. This approach has been successfully used, e.g., for set functions in which the desired set a is a shape, i.e., a smooth (or piece-wise smooth) surface. In some real-life problems, however, there are no reasons to assume smoothness and therefore, these existing methods are not applicable. For such problems, we design a new diierential formalism for optimizing set functions.
Whither mobile services' market?: Portraying profiles of mobile users and exploring their economic behavior

Introduction The recent developments in mobile services’ market have brought about extensive research from both scholars and practitioners. However, this research has mainly focused on the supply side of the market. As a stream of observations pertaining to the troubles of WAP, the consecutive revisions of world 3G diffusion forecasts, and the slow actual 3G uptake, scholars and practitioners have emphasized that technological advances and service availability do not automatically lead to widespread adoption and use (Baldi & Thaung, 2002; Funk, 2001). Parallel, and resulting from the scant research on adopting enduser’s perspectives in relation to mobile services, there have been augmented calls for research spanning beyond aggregate diffusion models as these have appeared to be “insufficient as bases for understanding the end-user requirements” (Pedersen, Methlie, & Thorbjørnsen, 2002b:1). Thus, in order to enrich the demand side analysis, a thorough investigation of mobile users’ perception and attitudes towards mobile services as well as observations of their actual usage patterns are warranted.
A power-optimal repeater insertion methodology for global interconnects in nanometer designs

This paper addresses the problem of power dissipation during the buffer insertion phase of interconnect performance optimization. It is shown that the interconnect delay is actually very shallow with respect to both the repeater size and separation close to the minimum point. A methodology is developed to calculate the repeater size and interconnect length which minimizes the total interconnect power dissipation for any given delay penalty. This methodology is used to calculate the power-optimal buffering schemes for various ITRS technology nodes for 5% delay penalty. Furthermore, this methodology is also used to quantify the relative importance of the various components of the power dissipation for power-optimal solutions for various technology nodes.
Superparamagnetic iron oxide nanoparticles conjugated with epidermal growth factor (SPION–EGF) for targeting brain tumors

Superparamagnetic iron oxide nanoparticles (SPIONs) conjugated with recombinant human epidermal growth factor (SPION–EGF) were studied as a potential agent for magnetic resonance imaging contrast enhancement of malignant brain tumors. Synthesized conjugates were characterized by transmission electron microscopy, dynamic light scattering, and nuclear magnetic resonance relaxometry. The interaction of SPION–EGF conjugates with cells was analyzed in a C6 glioma cell culture. The distribution of the nanoparticles and their accumulation in tumors were assessed by magnetic resonance imaging in an orthotopic model of C6 gliomas. SPION–EGF nanosuspensions had the properties of a negative contrast agent with high coefficients of relaxation efficiency. In vitro studies of SPION–EGF nanoparticles showed high intracellular incorporation and the absence of a toxic influence on C6 cell viability and proliferation. Intravenous administration of SPION–EGF conjugates in animals provided receptor-mediated targeted delivery across the blood–brain barrier and tumor retention of the nanoparticles; this was more efficient than with unconjugated SPIONs. The accumulation of conjugates in the glioma was revealed as hypotensive zones on T2-weighted images with a twofold reduction in T2 relaxation time in comparison to unconjugated SPIONs (P<0.001). SPION–EGF conjugates provide targeted delivery and efficient magnetic resonance contrast enhancement of EGFR-overexpressing C6 gliomas.
Combining Objective and Subjective Data in Evaluation of Spoken Dialogues

Evaluation of human-computer spoken dialogues is often based on analyses of objective metrics such as task completion rate, turn-taking, time consumption, etc. While these data are easily obtained and processed from log files, they offer or very little information about the actual usability of the given service as perceived by the test subjects. This study combines the evaluation based on objective data obtained from log files with subjective data, where the test subjects express their attitudes to a number issues directly related to the usability of the service. It is shown how the joint analysis can be used to support, but also question findings from either source.
Experiences with Scalability of Display Walls

Immersive virtual environments require large-scale high resolution displays to match the human visual acuity. This drives the need to study scalability issues related to display wall systems. This paper reports our experiences in scaling up the display wall system at Princeton University from 8 to 24 projectors. We discuss scalability techniques for automatic projector calibration, cluster management, data distribution for still images, motion video, and multi-channel audio.
Producer's replenishment policy for an EPQ model with rework and machine failure taking place in backorder reloading time

This paper studies the optimal producer's replenishment policy for an economic production quantity (EPQ) model with rework and breakdown taking place in backorder replenishing time. A recent published article has studied the lot-sizing problem on an imperfect quality EPQ model. However, another reliability factor - random machine breakdown is inevitable in most real-life production systems. To deal with stochastic machine failures, production planners must practically calculate the mean time between failures (MTBF) and establish the robust plan accordingly, in terms of the optimal production run time that minimizes total production-inventory costs for such an unreliable system. This study extends Chiu's work and assumes that a machine failure takes place in the backorder replenishing stage. Mathematical modeling and cost analysis are employed. The renewal reward theorem is used to cope with variable cycle length. Convexity of the long-run average cost function is proved and an optimal manufacturing lot-size that minimizes the expected overall costs for such an imperfect system is derived. Numerical example is provided to demonstrate its practical usages.
Moduli and Kähler potential in fermionic strings.

We study the problem of identifying the moduli fields in fermionic four-dimensional string models. We deform a free-fermionic model by introducing exactly marginal operators in the form of Abelian Thirring interactions on the world-sheet, and show that their couplings correspond to the untwisted moduli fields. We study the consequences of this method for simple free-fermionic models which correspond to Z2 ×Z2 orbifolds ¯
Leader-following consensus criteria for multi-agent systems with time-delay and static interconnection topology

This paper proposes new delay-dependent consensus criteria for multi-agent systems with time-varying delays and static interconnection topology. By constructing a suitable Lyapunov-Krasovskii's functional and utilizing convex-hull properties, new delay-dependent consensus criteria for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.
SIDR: Structure-aware intelligent data routing in hadoop

The MapReduce framework is being extended for domains quite different from the web applications for which it was designed, including the processing of big structured data, e.g., scientific and financial data. Previous work using MapReduce to process scientific data ignores existing structure when assigning intermediate data and scheduling tasks. In this paper, we present a method for incorporating knowledge of the structure of scientific data and executing query into the MapReduce communication model. Built in SciHadoop, a version of the Hadoop MapReduce framework for scientific data, SIDR intelligently partitions and routes intermediate data, allowing it to: remove Hadoop's global barrier and execute Reduce tasks prior to all Map tasks completing; minimize intermediate key skew; and produce early, correct results. SIDR executes queries up to 2.5 times faster than Hadoop and 37% faster than SciHadoop; produces initial results with only 6% of the query completed; and produces dense, contiguous output.
Harmonic Variance: A Novel Measure for In-focus Segmentation

We introduce an efficient measure for estimating the degree of in-focus within an image region. This measure, harmonic mean of variances, is computed from the statistical properties of the image in its bandpass filtered versions. We incorporate the harmonic variance into a graph Laplacian spectrum based segmentation framework in order to accurately align the in-focus measure responses on the underlying image structure. Our results demonstrate the effectiveness of this novel measure for determining and segmenting in-focus regions in low depth-of-field images.
Developing Mentors: An Analysis of Shared Mentoring Practices

ABSTRACT Understanding how experienced teachers share and articulate effective mentoring practices can guide efforts to prepare quality mentors. This qualitative study focused on mentoring practices within a teacher-designed student-teaching program conceptualized while the mentor teachers within the program were students in a graduate-level mentoring course and implemented upon the mentors’ completion of their graduate studies. Data sources included interviews and field notes from meetings with mentors and student teachers. The results detail specific mentoring practices: explicit instruction through scaffolding, developing the whole teacher, student-teacher-directed learning, fostering student teachers’ individual practice, explicit mentoring of one another, and reflecting on mentoring. These practices were enabled by program structures such as mentor meetings, an online forum, and mentors’ observation of all student teachers in the program.
Validation of an Accelerometer to Quantify a Comprehensive Battery of Gait Characteristics in Healthy Older Adults and Parkinson's Disease: Toward Clinical and at Home Use

Measurement of gait is becoming important as a tool to identify disease and disease progression, yet to date its application is limited largely to specialist centers. Wearable devices enables gait to be measured in naturalistic environments, however questions remain regarding validity. Previous research suggests that when compared with a laboratory reference, measurement accuracy is acceptable for mean but not variability or asymmetry gait characteristics. Some fundamental reasons for this have been presented, (e.g., synchronization, different sampling frequencies) but to date this has not been systematically examined. The aims of this study were to: 1) quantify a comprehensive range of gait characteristics measured using a single triaxial accelerometer-based monitor; 2) examine outcomes and monitor performance in measuring gait in older adults and those with Parkinson's disease (PD); and 3) carry out a detailed comparison with those derived from an instrumented walkway to account for any discrepancies. Fourteen gait characteristics were quantified in 30 people with incident PD and 30 healthy age-matched controls. Of the 14 gait characteristics compared, agreement between instruments was excellent for four (ICCs 0.913-0.983); moderate for four (ICCs 0.508-0.766); and poor for six characteristics (ICCs 0.637-0.370). Further analysis revealed that differences reflect an increased sensitivity of accelerometry to detect motion, rather than measurement error. This is most likely because accelerometry measures gait as a continuous activity rather than discrete footfall events, per instrumented tools. The increased sensitivity shown for these characteristics will be of particular interest to researchers keen to interpret “real-world” gait data. In conclusion, use of a body-worn monitor is recommended for the measurement of gait but is likely to yield more sensitive data for asymmetry and variability features.
Predicate matching and subscription matching in Publish/Subscribe systems

An important class of publish/subscribe matching algorithms work in two stages. First, predicates are matched and then matching subscriptions are derived. We observe that in practice, the domain types over which predicates are defined are often of fixed enumerable cardinality. Based on this observation we propose a table-based look-up scheme for fast predicate evaluation that finds all matching predicates for each type with one table lookup. We compare this scheme to alternative general-purpose implementations. This observation may also suggests that matching in publish/subscribe systems could equally well be implemented with standard database technology. We propose two DBMS-based matching algorithms and compare the better one with a special purpose publish/subscribe matching algorithm implementation. We provide first evidence that for application scenarios that require large subscription workloads and process many events a DBMS-based solution is not a feasible alternative.
How Shallow is a Bug? Why Open Source Communities Shorten the Repair Time of Software Defects

A central tenet of the open source software development methodology is that the community of users and developers is instrumental in improving the quality of software. Using a 10-year longitudinal dataset from the Firefox community, I investigate how the size of a community in terms of bug reporters and software developers, the social networks of developers and the quality of user contributions influence the time needed to repair software defects. The results show that a large open source community in terms of bug reporters reduces the time needed to resolve a defect while the addition of new software developers to an open source community takes away resources to fix bugs and increase the time needed to resolve a defect. In addition, software developers occupying dense network positions need less time to solve a bug. Finally, user contributions are beneficial when bugs are lively discussed but there is no support for the prediction that the experience of the bug reporter or the quality of the bug report reduces the time needed to solve a software defect.