Miracle-dz/UniFAR-FTUs huggingface dataset:
Experience Report: Understanding Cross-Platform App Issues from User Reviews

App developers publish apps on different platforms, such as Google Play, App Store, and Windows Store, to maximize the user volumes and potential revenues. Due to the different characteristics of the platforms and the different user preference (e.g., Android is more customized than iOS), app testing cases on these three platforms should also be designed differently. Comprehensive app testing can be time-consuming for developers. Therefore, understanding the differences of the app issues on these platforms can facilitate the testing process. In this paper, we propose a novel framework named CrossMiner to analyze the essential app issues and explore whether the app issues exhibit differently on the three platforms. Based on five million user reviews, the framework automatically captures the distributions of seven app issues, i.e., "battery", "crash", "memory", "network", "privacy", "spam", and "UI". We discover that the apps for different platforms indeed generate different issue distributions, which can be employed by app developers to schedule and design the testing cases. The verification based on the official user forums also demonstrates the effectiveness of our framework. Furthermore, we also identify that the issues related to "crash" and "network" are more concerned by users than the other issues on these three platforms. To assist developers in gaining a deep insight on the user issues, we also prioritize the user reviews corresponding to the issues. Overall, we aim at understanding the differences of issues on different platforms and facilitating the testing process for app developers.
Efficient replication for distributed fault tolerant memory

In-memory computing aims to bring forward application data from the storage to the server's main memory. By locating the working set closer to its application, in memory, great performance gains can be achieved. Most approaches in this arena have built solutions that either need traditional applications to be re-written or require new software acquisition. We built FVP, a solution that uses RAM to seamlessly accelerate any application running in VMs across servers in a virtualized datacenter. Therefore, applications need not be re-written and still reap the acceleration benefits of inmemory computing. VM I/O is absorbed by the server's memory, so the VM experiences memory latencies. However, due to the volatility of RAM, fault tolerance is essential without which our solution would be inconsequential. We discuss how we solved the practical challenges we faced when implementing a Distributed Fault Tolerant Memory (DFTM) acceleration layer while preserving VM performance. We also discuss other new challenges that inmemory computing brings to our field.
Efficient and safe on-line motion planning in dynamic environments

This paper presents a new on-line planner for dynamic environments that is based on the concept of Velocity Obstacles (VO). It addresses the issue of motion safety, i.e. avoiding states of inevitable collision, by selecting a proper time horizon for the velocity obstacle. The proper choice of the time horizon ensures that the boundary of the velocity obstacle coincides with the boundary of the set of inevitable collision states. This time horizon is determined by the minimum time it would take the robot to avoid collision, either by stopping or by passing the respective obstacle. The planner generates a near-time optimal trajectory to the goal by selecting at each time step the velocity that minimizes the time-to-go and is out of the velocity obstacle. The planner takes into account the shape, velocity, and path curvature of the obstacle's trajectory. It is demonstrated for on-line motion planning in very crowded static and dynamic environments.
The Role of Complementary Resources in the Development of E-Supply Chains and the Firm's Performance: An Exploratory Analysis of Secondary Data

E-supply chains e-SCs, which are Internet-enabled supply chains, are progressively being implemented by companies to improve their operational and financial performance. Several studies exist where the association between the development of an e-supply chain and the performance of a firm have been investigated. However, there is a paucity of literature that describes how information technology IT resources interact with other complementary resources to e-supply chains that positively impact a firm's performance. This paper seeks to adopt a resource-based view of the firm RBVF and empirically tests a framework that identifies and validates the relationships among IT resources, complementary resources to e-supply chains, and performance of a firm. This study utilizes secondary data from two sources-data collected by the South Korean Ministry of Commerce, Industry and Energy MOCIE and financial data from the Korea Exchange. The data from a total of 170 firms representing 10 industries in South Korea was analyzed using a partial least-squares technique PLS. The results of the analysis confirm that IT resources do not directly influence supply chain performance. However, when associated with a complementary resource, IT resources positively affect both supply chain operations and a firm's financial performance. The findings of this research support the current existing literature on the RBVF approach with regard to the domain of supply chain management, and can provide additional insights to industry practitioners on how to effectively utilize complementary resources in developing e-SCs to deliver improved performance.
Case Adaptation Using Genetic Algorithms

In order to adapt past experiences to new situations, case-based reasoning algorithms generally rely on domain knowledge and heuristics. Unfortunately, the amount of domain-specific knowledge and domainand task-specific heuristics needed for such case adaptation is usually quite large. In contrast, in our current work we are exploring the use of a knowledge-lean method based on genetic algorithms for the subtask of case adaptation. We are applying these ideas to the domain of structural design of tall buildings.
Real-World Assessment of Clinical Outcomes in Patients with Lower-Risk Myelofibrosis Receiving Treatment with Ruxolitinib

Few trial-based assessments of ruxolitinib in patients with lower-risk myelofibrosis (MF) have been conducted, and no studies have made such assessments in a real-world population. We assessed changes in spleen size and constitutional symptoms during ruxolitinib treatment using a retrospective, observational review of anonymized US medical record data of patients diagnosed with IPSS low-risk (n = 25) or intermediate-1-risk (n = 83) MF. The majority of patients were male (low risk, 60%; intermediate-1 risk, 69%). Most patients (92% and 77%) were still receiving ruxolitinib at the medical record abstraction date (median observation/exposure time, 8 months). The proportion of patients with moderate or severe palpable splenomegaly (≥10 cm) decreased from diagnosis (56%) to best response (12%). Fatigue was reported in 47% of patients and was the most common constitutional symptom. For most symptoms in both risk groups, shifts in the distribution of severity from more to less severe from diagnosis to best response were observed. Both patients with low-risk and intermediate-1-risk MF experienced a substantial decrease in spleen size with ruxolitinib treatment in real-world settings. For most symptoms examined, there were distinct improvements in the distribution of severity during ruxolitinib treatment. These findings suggest that patients with lower-risk MF may benefit clinically from ruxolitinib treatment.
The Many Elements of Traditional Fire Knowledge: Synthesis, Classification, and Aids to Cross-cultural Problem Solving in Fire-dependent Systems Around the World

I examined the hypothesis that traditional social-ecological fire systems around the world include common elements of traditional fire knowledge (TFK). I defined TFK as fire-related knowledge, beliefs, and practices that have been developed and applied on specific landscapes for specific purposes by long time inhabitants. In all, 69 distinct elements of TFK were documented in 35 studies, including accounts from 27 countries on 6 continents. On all 6 continents, 21 elements (30%) were recorded, and 46 elements (67%) were recorded on 4 or more continents. The top 12 most commonly reported elements, which were included in > 50 % of the studies, were fire effects on vegetation; season of the year; fire effects on animals; moisture of live or dead fuels; the onset or end of rainy season, dry season, or timing of rain; burning illegal or regulated by central government; fire intensity, heat output, i.e., hot or cool fire; frequency, return interval, time since fire; fire control; firebreaks, barriers; consequences of not burning; and plant or animal phenology. Traditional fire knowledge was multifaceted: 13 studies included more than 25 elements. Practicing traditional fire management also entails understanding the ways in which multiple elements interact and influence one another. Three classification systems provide insight into TFK systems, including typologies of agroecological type, preand postindustrial anthropological fire regimes, and viability status. The longevity of traditional fire knowledge and practice faces serious threats at precisely the time when climate change promises disruptions in fire activity that will be problematic for indigenous and nonindigenous societies alike. Central governments tend to adopt the pathological response of command and control during times of fire increase, further constraining traditional fire management. The opposite is needed: to seriously engage traditional practitioners in solving fire problems of global significance.
WORK FAMILY CONFLICT AND ITs WORK AND NON-WORK OUTCOMES: MODERATING ROLE OF GENDER AND SOCIAL SUPPORT

The purpose of the present research was to examine the relationship between work family conflict and its directions with work and non-work outcomes. The study also examined the moderating role of social support and gender in relation between work family conflict (i.e., work-interference-with family and family-interference-with work) and outcomes. The research was conducted in two distinct studies; Study I (N= 216) was aimed at addressing the psychometric properties of the instruments in local context and Study II was main study (N= 366) which aimed at testing hypotheses formulated for the present research. The sample for both the studies was drawn purposively from financial institution, telecom and health sector organizations of Rawalpindi and Islamabad. Instruments included Work Family Conflict Scale (Carlson, Kacmar, & Williams, 2000), Perceived Social Support Scale (Caplan, Cobb, French, Harrison, & Pinneau, 1975), General Job Satisfaction Scale (Hackman & Oldham, 1975), Turnover Intention Scale (O’Driscoll & Beehr, 1994), Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985), and ENRICH Marital Satisfaction Subscale (Fowers & Olson, 1993). The results of Study I revealed fair to good model fit for study variables. Reliability estimates also provided fair to satisfactory internal consistency evidences for the instruments used. Results of Study II found that Work family conflict was significantly negatively correlated with Job satisfaction and Marital Satisfaction as an outcome variable. The relationship was negative for Turnover Intention. Work-interferencewith family did not correlate with Job Satisfaction and Turnover Intention. Familyinterference-with Work was significantly negatively correlated with Marital Satisfaction. Among the work-related sources of support, supervisor support moderated the relation between work-interference-with family and job satisfaction as well as turnover intention.
"MORITZ" a pipe crawler for tube junctions

This paper deals with the further development of the tube crawling robot "MORITZ", which was built at the Technical University of Munich. This robot can climb through pipes of different inclinations. It is improved in the recent research project, so that it also can manage tube junctions. After a brief introduction about problems concerning such a robot the used gait pattern is explained. Additionally some simulation results-showing the load at the robot during a motion through a tube crossing-are presented. Moreover the new developed joints in the central body as well as the sensors are described. The paper ends with a brief description of the crawler's control and its modifications for the new climbing maneuver in tube crossings.
Frequency distribution based weighted sub-band approach for classification of emotional/stressful content in speech

In this paper we explore the use of nonlinear Teager Energy Operator based features derived from multi-resolution sub-band analysis for classification of emotional/stressful speech. We propose a novel scheme for automatic sub-band weighting in an effort towards developing a generic algorithm for understanding emotion or stress in speech. We evaluate the proposed algorithm using a corpus of audio material from a military stressful Soldier of the Quarter Board evaluation panel. We establish classification performance of emotional/stressful speech using an open speaker set with open test tokens. With the new frequency distribution based scheme, we obtain a relative detection error reduction of 81.3% in stress speech, and a 75.4% relative detection rate reduction in neutral speech detection error rate. The results suggest a important step forward in establishing an effective processing scheme for developing generic models of neutral and emotional speech.
The Impact of Gurus: Parker Grades and en primeur Wine Prices*

Abstract The purpose of this paper is to measure the impact of Robert Parker's oenological grades on Bordeaux wine prices. We study their impact on the so-called en primeur wine prices, i.e., the prices determined by the château owners when the wines are still extremely young. The Parker grades are usually published in the spring of each year, before the wine prices are established. However, the wine grades attributed in 2003 have been published much later, in the autumn, after the determination of the prices. This unusual reversal is exploited to estimate a Parker effect. We find that, on average, the effect is equal to 2.80 euros per bottle of wine. We also estimate grade-specific effects, and use these estimates to predict what the prices would have been had Parker attended the spring tasting in 2003. (JEL Classification: C21, D89, L15).
Ferrocene-oligonucleotide conjugates for electrochemical probing of DNA.

Toward the development of a universal, sensitive and convenient method of DNA (or RNA) detection, electrochemically active oligonucleotides were prepared by covalent linkage of a ferrocenyl group to the 5'-aminohexyl-terminated synthetic oligonucleotides. Using these electrochemically active probes, we have been able to demonstrate the detection of DNA and RNA at femtomole levels by HPLC equipped with an ordinary electrochemical detector (ECD) [Takenaka,S. , Uto,Y. , Kondo,H. , Ihara,T. and Takagi,M. (1994) Anal. Biochem. , 218, 436-443]. Thermodynamic and electrochemical studies of the interaction between the probes and the targets are presented here. The thermodynamics obtained revealed that the conjugation stabilizes the triple-helix complexes by 2-3 kcal mol-1 (1-2 orders increment in binding constant) at 298 K, which corresponds to the effect of elongation of additional several base triplets. The main cause of this thermodynamic stabilization by the conjugation is likely to be the overall conformational change of whole structure of the conjugate rather than the additional local interaction. The redox potential of the probe was independent of the target structure, which is either single- or double stranded. However, the potential is slightly dependent (with a 10-30 mV negative shift on complexation) on the extra sequence in the target, probably because the individual sequence is capable of contacting or interacting with the ferrocenyl group in a slightly different way from each other. This small potential shift itself, however, does not cause any inconvenience on practical applications in detecting the probes by using ECD. These results lead to the conclusion that the redox-active probes are very useful for the microanalysis of nucleic acids due to the stability of the complexes, high detection sensitivity and wide applicability to the target structures (DNA and RNA; single- and double strands) and the sequences.
Octree textures on graphics hardware

Author(s): Kniss, Joe M. ; Lefohn, Aaron; Strzodka, Robert; Sengupta, Shubhabrata; Owens, John D. | Abstract: We implement an interactive 3D painting application that stores paint in an octree-like GPU-based adaptive data structure. Interactive painting of complex or unparameterized surfaces is an important problem in the digital film community. Many models used in production environments are either difficult to parameterize or are unparameterized implicit surfaces. We address this problem with a system that allows interactive 3D painting of complex, unparameterized models. The included movie demonstrates interactive painting of a 817k polygon model with effective paint resolutions varying between 64^3 to 2048^3. Our implementation differs from previous work in two important ways: first, it uses an adaptive data structure implemented entirely on the GPU, and second, it enables interactive performance with high quality by supporting quadlinear (mipmapped) filtering and fast, constant-time data accesses.
QUANTIFYING UNCERTAINTY OF FLOOD FORECASTING USING DATA DRIVEN MODELS

Flooding is a complex and inherently uncertain phenomenon. Consequently forecasts of it are inherently uncertain in nature due to various sources of uncertainty including model uncertainty, input uncertainty and parameter uncertainty. Several approaches have been reported to quantify and propagate uncertainty through flood forecasting models using probabilistic and fuzzy set theory based methods. In this paper, a method for quantifying uncertainty in flood forecasting using data driven modeling techniques is presented. Uncertainty of the model outputs is estimated in terms of prediction intervals. First, prediction intervals for training (calibration) data using clustering techniques to identify the distinguishable regions in input space with similar distributions of model errors were constructed. Secondly, a data driven model was built using the computed prediction intervals as targets. Thirdly, the constructed model was validated by estimating the prediction intervals for unseen (test) data. The method was tested on Sieve and Bagmati river basins using various data driven models. Preliminary results show that the method is superior to another method (uniform interval method) estimating prediction intervals.
A design space for engineering graphical adaptive menus

This paper presents a design space for exploring design options of adaptive graphical menus based on Bertin's eight visual variables: position, size, shape, value, color, orientation, texture, and motion. In order to transform a traditional (static) menu into an adaptive one, at least one visual variable should be exploited to convey which menu items have been promoted or demoted depending on five characteristics: select, associative, quantitative, order, and length. The paper reviews selected adaptive menu interaction techniques belonging to each of these variables, classifies them according to the variables and characteristics and suggests not yet explored adaptive menu designs. It then defines four stability properties depending on which variables remain constant after adaptivity. A supporting software for prototyping the rendering of graphical adaptive menus is then introduced.
Tuning Bayes Baseline for Dialect Detection

This paper describes an analysis of our submissions to the Dialect Detection Shared Task 2016. We proposed three different systems that involved simplistic features, to name: a Naive-bayes system, a Support Vector Machines-based system and a Tree Kernel-based system. These systems underperform when compared to other submissions in this shared task, since the best one achieved an accuracy of ~0.834.
Data Mining for Fraud Detection

– The advent of new technologies and the fast base of technological development have created new possibilities as well as imposing new challenges. Fraud, which is one of the greatest challenges for businesses and organizations, has been equipped with new technologies to take new and unconventional forms that are stealthier and more difficult to recognize than the traditional forms of this crime. Therefore, the techniques for detecting fraud had to develop as well to provide more efficient protection. The most recognized and effective technology that has been implemented for fraud detection is data mining. This research paper will explore some of the most effective data mining techniques for detecting different types of fraud. These techniques will first be categorized according into supervised and unsupervised methods. Those techniques will be explored in the fields of mobile telecommunication fraud, credit card fraud, medical insurance fraud and computer systems intrusion detection. In addition, a real life case will be presented to illustrate the application of one of the techniques in credit card fraud detection.
Quantum ergodicity on large regular graphs

We propose a version of the Quantum Ergodicity theorem on large regular graphs of fixed valency. This is a property of delocalization of "most" eigenfunctions. We consider expander graphs with few short cycles (for instance random large regular graphs). Our method mimics the proof of Quantum Ergodicity on manifolds: it uses microlocal analysis on regular trees.
The Properties of Income Risk in Privately Held Businesses

Our paper represents the first attempt in the literature to estimate the properties of business income risk from privately held businesses in the US. Using a new, large, and confidential panel of US income tax returns for the period 1987-2009, we extensively document the empirical stylized facts about the evolution of various business income risk measures over time. We find that business income is much riskier than labor income, not only because of the probability of business exit, but also because of higher income fluctuations, conditional on no exit. We show that business income is less persistent, but is also characterized by higher probabilities of extreme upward transition, compared to labor income. Furthermore, the distribution of percent changes for business income is more dispersed than that for labor income, and it also indicates that business income faces substantially higher tail risks. Our results suggest that the high-income households are more likely to bear both the big positive and the big negative business income percent changes.