Miracle-dz/UniFAR-FTUs huggingface dataset:
Andro-profiler: Detecting and Classifying Android Malware based on Behavioral Profiles

Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices. Accordingly, techniques have been introduced for identifying, classifying, and defending against mobile threats utilizing static, dynamic, on-device, off-device, and hybrid approaches. In this paper, we contribute to the mobile security defense posture by introducing Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware. Andro-profiler classifies malware by exploiting the behavior profiling extracted from the integrated system logs including system calls, which are implicitly equivalent to distinct behavior characteristics. Andro-profiler executes a malicious application on an emulator in order to generate the integrated system logs, and creates human-readable behavior profiles by analyzing the integrated system logs. By comparing the behavior profile of malicious application with representative behavior profile for each malware family, Andro-profiler detects and classifies it into malware families. The experiment results demonstrate that Andro-profiler is scalable, performs well in detecting and classifying malware with accuracy greater than $98\%$, outperforms the existing state-of-the-art work, and is capable of identifying zero-day mobile malware samples.
Character building or subversive consequences of employment during high school : Causal effects based on propensity score models for categorical treatments

The present study revisited the unresolved issue of the long-term effects of part-time working intensity during high school on students’ achievement, participation in postsecondary education, time allocation, and work-related values and expectations. Using data from the Educational Longitudinal Study of 2002 (N = 14,654), the effects of part-time working in Year 12 on outcomes assessed at graduation from high school and 2 years later were studied with propensity score methods for categorical treatments. Three theoretical perspectives on the effects of part-time working intensity (subversion of academic goals, character building, threshold model) were contrasted. Substantively, there were negative linear effects of working intensity on achievement outcomes. Results for higher education participation partly supported a threshold model. Heterogeneous effects for self-reported time use and work-related values suggested that the negative effects on achievement outcomes were not due to a simple zero-sum game. Ironically, working with high intensity led students to value having a good job more strongly but might undermine their chances of achieving this goal. However, these effects were only recognized 2 years after high school graduation, when occupational expectations were negatively affected by working intensity in Year 12.
Variable duration hidden Markov model and morphological segmentation for handwritten word recognition

A complete system for the recognition of unconstrained handwritten words using a continuous density variable duration hidden Markov model (CDVDHMM) is described. A new segmentation algorithm based on mathematical morphology is used to translate the 2-D image into a 1-D sequence of sub-character symbols. This sequence of symbols is modeled by the CDVDHMM. Generally, there are two information sources associated with the written text. While the shape information of each character symbol is modeled as a mixture Gaussian distribution, the linguistic knowledge, i.e., constraint, is modeled as a Markov chain. In this context, the variable duration state is used to take care of the segmentation ambiguity among the consecutive characters. Some experimental results are described to demonstrate the success of the proposed scheme. <<ETX>>
Music, Possession and Shamanism Among Khond Tribes

This paper studies the role and the meaning of music in spirit possession and shamanism in two villages among the Khond, a group of tribes settled in the hinterland of the Indian region of Orissa. I describe three types of possession: the voluntary and powerful possession of shamans, the occasional possession of priests, and the involuntary possession of patients. In each case we find the possessed person experiences a different degree of agency based on their relationship to music. ‘Musical language’ is an important highly codified precondition for possession among the Khond, and is used distinctively in priest's and shaman's possession. Closely analysing the role of musical performance in Khond and related cultures, I employ an interdisciplinary methodology, moving from ethnomusicology and the history of religions, that emphasises the embodied, geographically specific traditions, providing analysis of the unique work accomplished by musical language in two villages.
Conflict Resolution in the Family: A PET Evaluation Study

Conflict resolution models have been widely advocated but less widely tested. Parent Effectiveness Training (PET; Gordon, 1975) and Youth Effectiveness Training (YET; Hall & Zener, 1979) incorporate a simple conflict resolution technique. PET has now received considerable empirical support (Cedar, 1985; Levant, 1983). Few studies, however, have used behavioural measures rather than questionnaires. The experimental subjects in the present study were 13 parent-adolescent dyads who completed the appropriate Effectiveness Training program (PET/YET). Assessment of videorecorded interactions in a role-play conflict situation showed significantly greater improvement in conflict resolution skills from pretraining to posttraining in the experimental group compared to the matched control group, for both parents and adolescents. No significant changes were found on the Parent Attitude Survey (Hereford, 1963), the FIRO-B (Schutz, 1967), or the Self Esteem Inventory (Coopersmith, 1967). Methodological issues and possible flow-on effects from children learning conflict resolution skills in the family are discussed.
SRp30c Is a Repressor of 3′ Splice Site Utilization

ABSTRACT Several intron elements influence exon 7B skipping in the mammalian hnRNP A1 pre-mRNA. We have shown previously that the 38-nucleotide CE9 element located in the intron separating alternative exon 7B from exon 8 can repress the use of a downstream 3′ splice site. The ability of CE9 to act on heterologous substrates, combined with the results of competition and gel shift assays, indicates that the activity of CE9 is mediated by a trans-acting factor. UV cross-linking analysis revealed the specific association of a 25-kDa nuclear protein with CE9. Using RNA affinity chromatography, we isolated a 25-kDa protein that binds to CE9 RNA. This protein corresponds to SRp30c. Consistent with a role for SRp30c in the activity of CE9, recombinant SRp30c interacts specifically with CE9 and can promote splicing repression in vitro in a CE9-dependent manner. The closest homologue of SRp30c, ASF/SF2, does not bind to CE9 and does not repress splicing even when the intronic SRp30c binding sites are replaced with high-affinity ASF/SF2 binding sites. Only the first 7 nucleotides of CE9 are sufficient for binding to SRp30c, and mutations that abolish binding also prevent repression. Our results indicate that SRp30c can function as a repressor of 3′ splice site utilization and suggest that the SRp30c-CE9 interaction may contribute to the control of hnRNP A1 alternative splicing.
Visuospatial Reasoning

Visuospatial reasoning is not simply a matter of running to retrieve a fly ball or wending a way through a crowd or plotting a path to a destination or stacking suitcases in a car trunk. It is a matter of determining whether gears will mesh (Schwartz & Black, 1996a), understanding how a car brake works (Heiser & Tversky, 2002), discovering how to destroy a tumor without destroying healthy tissue (Duncker, 1945 ; Gick & Holyoak, 1980, 1983), and designing a museum (Suwa & Tversky, 1997). Perhaps more surprising, it is also a matter of deciding whether a giraffe is more intelligent than a tiger (Banks & Flora, 1977; Paivio, 1978), whether one event is later than another (Boroditsky, 2000), and whether a conclusion follows logically from its’ premises (Barwise & Etchemendy, 1995 ; Johnson-Laird, 1983). All these abstract inferences, and more, appear to be based on spatial reasoning. Why is that? People begin to acquire knowledge about space and the things in it probably before they enter the world. Indeed, spatial knowledge is critical to survival and spatial inference critical to effective survival. Perhaps because of the (literal) ubiquity of spatial reasoning, perhaps because of the naturalness of mapping abstract elements and relations to spatial ones, spatial reasoning serves as a basis for abstract knowledge and inference. The prevalence of spatial figures of speech in everyday talk attests to that: We feel close to some people and remote from others; we try to keep our spirits up, to perform at the peak of our powers, to avoid falling into depressions, pits, or quagmires; we enter fields that are wide open, struggling to stay on top of things and not get out of depth. Right now, in this section, we establish fuzzy boundaries for the current field of inquiry.
Preference for Cute Infants Does Not Depend on Their Ethnicity or Species: Evidence from Hypothetical Adoption and Donation Paradigms

Results of previous work suggest a preference of adult observers for cute compared to less cute infants. In Study 1 we investigated whether the preference for cute infants depends on the ethnicity and species of the infant. We simultaneously presented two faces (one cute and one less cute) and asked Caucasian participants to choose the infant to whom they would rather give a toy (Task 1) and which infant they would rather adopt (Task 2). The infants were Caucasian or African human babies or dog puppies. For all face categories and in both tasks we found a strong preference for cute infants. A possible reason for preferring cute infants may be that cute infants look healthier than less cute infants. To investigate whether cuteness is associated with the assessment of health we conducted Study 2. Faces of Caucasian and African infants and dog puppies were rated for cuteness and health. The findings revealed a significant relationship between health and cuteness evaluation across all stimuli. We suggest that one reason why cute infants are preferred might be because they are perceived as being healthier.
Fast normalized cut with linear constraints

Normalized cut is a widely used technique for solving a variety of problems. Although finding the optimal normalized cut has proven to be NP-hard, spectral relaxations can be applied and the problem of minimizing the normalized cut can be approximately solved using eigen-computations. However, it is a challenge to incorporate prior information in this approach. In this paper, we express prior knowledge by linear constraints on the solution, with the goal of minimizing the normalized cut criterion with respect to these constraints. We develop a fast and effective algorithm that is guaranteed to converge. Convincing results are achieved on image segmentation tasks, where the prior knowledge is given as the grouping information of features.
Career management tactical innovations and successful interorganizational transitions

Purpose – The purpose of this paper is to identify the major variables that should be studied when exploring the relationship of innovations in career management tactics and successful or unsuccessful interorganizational transitions.Design/methodology/approach – This study takes a conceptual stance, using the careers and diffusion of innovation literature to identify the major variables.Findings – Two innovations and two major refinements in career management tactics suggested by contemporary career concepts are identified, personal criteria for transition success are described, and likely barriers to accepting these tactical innovations are hypothesized. Other factors likely to affect transition success are also revealed by analyzing a conceptual model of interorganizational transition success.Originality/value – The paper introduces the idea that the use of new career management tactics might be related to interorganizational transition success or the lack of it. It proposes one method of developing qua.
Invisible designated confirmer signatures without random oracles

We present the first O(1)-size designated confirmer signatures (DCS) with security in the state-of-the-art model of Camenisch and Michels, Eurocrypt 2000, without random oracles. In particular, we achieve the security notion called the "invisibility of signature" therein. We do so by a simple upgrade of Gentry, et al. [7]. Then we also present O(1)-size identity-based DCS without random oracle by without invisibility, and O(1)-size undeniable signature without random oracle and with invisibility.
Privacy streamliner: a two-stage approach to improving algorithm efficiency

In releasing data with sensitive information, a data owner usually has seemingly conflicting goals, including privacy preservation, utility optimization, and algorithm efficiency. In this paper, we observe that a high computational complexity is usually incurred when an algorithm conflates the processes of privacy preservation and utility optimization. We then propose a novel privacy streamliner approach to decouple those two processes for improving algorithm efficiency. More specifically, we first identify a set of potential privacy-preserving solutions satisfying that an adversary's knowledge about this set itself will not help him/her to violate the privacy property; we can then optimize utility within this set without worrying about privacy breaches since such an optimization is now simulatable by adversaries. To make our approach more concrete, we study it in the context of micro-data release with publicly known generalization algorithms. The analysis and experiments both confirm our algorithms to be more efficient than existing solutions.
Leveraging Organizational Knowledge through Electronic Knowledge Repositories in Public Accounting Firms: An Empirical Investigation

ABSTRACT: We investigate one of the most widely used knowledge management tools in public accounting firms, electronic knowledge repositories (EKRs), using a research model theoretically grounded in the expectation-confirmation theory (ECT). The research model was tested with survey data collected from 230 employees from four large public accounting firms. The results indicate that perceived usefulness and subjective norms exhibit a sustained positive influence on individuals' EKR behavioral intention, while individual satisfaction has no significant impact on EKR behavioral intention. The supplementary group analyses on firm type, individual experience level, and individual usage level reveal that individual and firm characteristics affect individual EKR usage intention. We contribute to knowledge management research by being one of the first studies to explore the use of EKRs in public accounting firms. The results offer insights on the factors that impact individuals' attitude and intention to use EKRs.
Portrayal of Men and Women in U.S. Spanish-Language Television Commercials

While numerous studies have analyzed women's portrayals in U.S. general market television as well as depiction of both sexes in several foreign countries, no data have been published regarding gender depictions targeted to the growing U.S. Hispanic market via Spanish-language television. A content analysis of 162 prime-time commercials from a Spanish-language television affiliate in a major U.S. market revealed depiction of women is most likely to be in traditional sex-stereotypical roles. In only a few cases was a male character cast as a parent or performer of household chores, and never as a homemaker. Some of the commercials appeared to be “re-treads” of general market creative edited for the Hispanic market.
Time Reversal Based Active Array Source Localization

Source localization especially direction-of-arrival (DOA) estimation using sensor arrays is of considerable interest in both classical array signal processing and radar applications. Most radar systems are designed under the line-of-sight (LOS) assumption with multipath echos treated as undesired clutter noise. Strong multipath, therefore, has a negative impact on the resolution of the radar systems and their ability in accurately localizing the target. Rather than treating multipath as a detrimental effect, the paper introduces time reversal (TR) to exploit spatial/multipath diversity in improving the capability of the existing localization algorithms. In particular, we design TR based range and DOA estimators that adaptively adjust the probing radar waveforms to the multipath characteristics of the environment. The benefits of the spatial/multipath diversity in the proposed DOA and range estimators are quantified by deriving the respective Cramér-Rao bounds (CRB) and comparing them with the analytical expressions for their conventional counterparts. Numerical simulations also confirm the benefit of applying TR to source localization algorithms especially at low signal-to-noise ratios below -5 dB.
Group communication and employee turnover: How coworkers encourage peers to voluntarily exit

When employees are assigned to work together, the coworker relationship may not always prove to be “a match made in heaven. ” From time‐to‐time, coworkers may intentionally try to terminate some of these organizationally sanctioned relationships. This typology of 12 message‐based and seven behavior‐based strategies clearly suggest that coworkers do try to disengage work relationships by encouraging peer exit. This study suggest that the utilization of these strategies by coworkers may motivate turnover. Therefore, studying the particular messages shared and behaviors performed in workgroups may provide greater insight into the relationship between turnover and group communication.
Comparative effects of valsartan and enalapril on cardiac sympathetic nerve activity and plasma brain natriuretic peptide in patients with congestive heart failure

Objective: To evaluate the effects of valsartan on cardiac sympathetic nerve activity, plasma brain natriuretic peptide (BNP) concentration, cardiac function, and symptoms in patients with congestive heart failure (CHF) by comparison with those of enalapril. Methods: 50 patients with CHF (left ventricular ejection fraction (LVEF) < 40%) were randomly assigned to valsartan (80 mg/day; n = 25) or enalapril (5 mg/day; n = 25). All patients were also treated with a loop diuretic. The delayed heart to mediastinum count (H/M) ratio, delayed total defect score (TDS), and washout rate were determined from 123I-meta-iodobenzylguanidine (MIBG) images. Plasma BNP concentrations were measured before and after six months of treatment. The left ventricular end diastolic volume (LVEDV) and LVEF were also determined by echocardiography. Results: In patients receiving valsartan, TDS decreased from a mean (SD) of 43 (8) to 39 (10) (p < 0.01), H/M ratio increased from 1.70 (0.17) to 1.78 (0.22) (p < 0.05), washout rate decreased from 46 (11)% to 41 (10)% (p < 0.05), and plasma BNP concentration decreased from 237 (180) pg/ml to 143 (93) pg/ml (p < 0.05). In addition, LVEDV decreased from 172 (42) ml to 151 (45) ml (p < 0.05) and LVEF increased from 31 (7)% to 39 (10)% (p < 0.001). However, these parameters did not change significantly in patients receiving enalapril. Conclusion: Plasma BNP concentration and 123I-MIBG scintigraphic and echocardiographic parameters improved significantly after six months of treatment with valsartan. These findings indicate that valsartan can improve cardiac sympathetic nerve activity and left ventricular performance in patients with CHF.
Beyond the standard Higgs after the 125 GeV Higgs discovery

An elementary, weakly coupled and solitary Higgs boson allows one to extend the validity of the Standard Model up to very high energy, maybe as high as the Planck scale. Nonetheless, this scenario fails to fill the universe with dark matter and does not explain the matter–antimatter asymmetry. However, amending the Standard Model tends to destabilize the weak scale by large quantum corrections to the Higgs potential. New degrees of freedom, new forces, new organizing principles are required to provide a consistent and natural description of physics beyond the standard Higgs.
Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset

YouTube-8M is the largest video dataset for multi-label video classification. In order to tackle the multi-label classification on this challenging dataset, it is necessary to solve several issues such as temporal modeling of videos, label imbalances, and correlations between labels. We develop a deep neural network model, which consists of four components: the frame encoder, the classification layer, the label processing layer, and the loss function. We introduce our newly proposed methods and discusses how existing models operate in the YouTube-8M Classification Task, what insights they have, and why they succeed (or fail) to achieve good performance. Most of the models we proposed are very high compared to the baseline models, and the ensemble of the models we used is 8th in the Kaggle Competition.
YADING: Fast Clustering of Large-Scale Time Series Data

Fast and scalable analysis techniques are becoming increasingly important in the era of big data, because they are the enabling techniques to create real-time and interactive experiences in data analysis. Time series are widely available in diverse application areas. Due to the large number of time series instances (e.g., millions) and the high dimensionality of each time series instance (e.g., thousands), it is challenging to conduct clustering on large-scale time series, and it is even more challenging to do so in real-time to support interactive exploration.In this paper, we propose a novel end-to-end time series clustering algorithm, YADING, which automatically clusters large-scale time series with fast performance and quality results. Specifically, YADING consists of three steps: sampling the input dataset, conducting clustering on the sampled dataset, and assigning the rest of the input data to the clusters generated on the sampled dataset. In particular, we provide theoretical proof on the lower and upper bounds of the sample size, which not only guarantees YADING's high performance, but also ensures the distribution consistency between the input dataset and the sampled dataset. We also select L1 norm as similarity measure and the multi-density approach as the clustering method. With theoretical bound, this selection ensures YADING's robustness to time series variations due to phase perturbation and random noise.Evaluation results have demonstrated that on typical-scale (100,000 time series each with 1,000 dimensions) datasets, YADING is about 40 times faster than the state-of-the-art, sampling-based clustering algorithm DENCLUE 2.0, and about 1,000 times faster than DBSCAN and CLARANS. YADING has also been used by product teams at Microsoft to analyze service performance. Two of such use cases are shared in this paper.
Building Data Integration Systems: A Mass Collaboration Approach

Building data integration systems today is largely done by hand, in a very labor intensive and error prone process. In this paper, we describe a conceptually new solution to this problem: that of mass collaboration. The basic idea is to think about a data integration system as having a ﬁnite set of parameters whose values must be set. To build such a system, the system administrators can construct and deploy a system “shell”, then ask the users to help the system “au-tomatically converge” to the correct parameter values. This way, the enourmous burden of system developments is lifted from the administrators and spread “thinly” over a multitude of users. We discuss the challenges to this approach and pro-pose solutions. We then describe our current effort in applying this approach to the problem of schema matching in the context of data integration.