Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Data Deletion Fails? A Study on Deletion Flaws and Data Remanence in Android Systems

Smart mobile devices are becoming the main vessel of personal privacy information. While they carry valuable information, data erasure is somehow much more vulnerable than was predicted. The security mechanisms provided by the Android system are not flexible enough to thoroughly delete sensitive data. In addition to the weakness among several provided data-erasing and file-deleting mechanisms, we also target the Android OS design flaws in data erasure, and unveil that the design of the Android OS contradicts some secure data-erasure demands. We present the data-erasure flaws in three typical scenarios on mainstream Android devices, such as the data clearing flaw, application uninstallation flaw, and factory reset flaw. Some of these flaws are inherited data-deleting security issues from the Linux kernel, and some are new vulnerabilities in the Android system. Those scenarios reveal the data leak points in Android systems. Moreover, we reveal that the data remanence on the disk is rarely affected by the user’s daily operation, such as file deletion and app installation and uninstallation, by a real-world data deletion latency experiment. After one volunteer used the Android phone for 2 months, the data remanence amount was still considerable. Then, we proposed DataRaider for file recovering from disk fragments. It adopts a file-carving technique and is implemented as an automated sensitive information recovering framework. DataRaider is able to extract private data in a raw disk image without any file system information, and the recovery rate is considerably high in the four test Android phones. We propose some mitigation for data remanence issues, and give the users some suggestions on data protection in Android systems.
A robust voice activity detector based on Weibull and Gaussian Mixture distribution

In this paper, we focus on the observation and state duration distributions in hidden semi-Markov model (HSMM)-based voice activity detection. To perform robustly in noisy environment, firstly, acoustic features of noisy speech are extracted by Mel-frequency cepstrum processor after filtering the raw speech with a modified Wiener filter. According to the statistic on TIMIT database, we use Gaussian Mixture distributions (GMD) for both speech and non-speech state to correlate the MFCC feature vectors and state sequences. The transition probability in HSMM is not a constant like in HMM but depends on the elapsed time in last state, and is modeled by Weibull distribution (WD) in this paper. The final VAD decision is made according to the likelihood ratio test (LRT) incorporating state prior knowledge. Also a adaptive threshold is used to achieve better detection results. Experiments on noisy speech data show that the proposed method performs more robustly and accurately than the standard ITU-T G.729B, AMR2, HMM-based VAD and VAD using Laplacian-Gaussian model.
Fault-Prone Module Prediction Using a Prediction Model and Manual Inspection

This paper proposes a fault-prone prediction approach that combines a fault-prone prediction model and manual inspection. Manual inspection is conducted by a predefined checklist that consists of questions and scoring procedures. The questions capture the fault signs or indications that are difficult to be captured by source code metrics used as input by prediction models. Our approach consists of two steps. In the first, the modules are prioritized by a fault-prone prediction model. In the second step, an inspector inspects and scores α percent of the prioritized modules. We conducted a case study of source code modules in commercial software that had been maintained and evolved over ten years and compared AUC (Area Under the Curve) values of Alberg Diagram among three prediction models: (A) support vector machines, (B) lines of code, and (C) random predictor with four prioritization orders. Our results indicated that the maximum AUC values under appropriate α and the coefficient of the inspection score were larger than the AUC values of the prediction models without manual inspection in each of the four combinations and the three models in our context. In two combinations, our approach increased the AUC values to 0.860 from 0.774 and 0.724. Our results also indicated that one of the combinations monotonically increased the AUC values with the numbers of manually inspected modules. This might lead to flexible inspection; the number of manually inspected modules has not been preliminary determined, and the inspectors can inspect as many modules as possible, depending on the available effort.
Improved Differential Fault Analysis of Trivium

Combining different cryptanalytic methods to attack a cryptosystem became one of the hot topics in cryptanalysis. In particular, algebraic methods in side channel and differential fault analysis (DFA) attracted a lot of attention recently. In [13], Hojsik and Rudolf used DFA to recover the inner state of the stream cipher Trivium which leads to recovering the secret key. For this attack, they required 3.2 one-bit fault injections on average and 800 keystream bits. In this paper, we give an example of combining DFA attacks and algebraic attacks. We use algebraic methods to improve the DFA of Trivium [13]. Our improved DFA attack recovers the inner state of Trivium by using only 2 fault injections and only 420 keystream bits.
Frequency separation in projection-based force reflection algorithms for bilateral teleoperators

The projection-based force reflection (PBFR) algorithms were previously demonstrated to substantially improve stability characteristics of the force reflecting teleoperator systems and haptic interfaces without transparency deterioration in the steady state; however, the transient response of the PFBR algorithms suffers from relatively slow force convergence. In particular, the high frequency component of the contact force, which is very important for the haptic perception of stiff surfaces, is typically filtered out. In this paper, a solution to this problem is proposed which is based on the idea to separate different frequency bands in the force reflection signal and consequently apply the projection-based principle to the low-frequency component, while reflecting the high-frequency component directly. It is shown that, for bilateral teleoperators with irregular communication delays, stability can always be achieved by implementing the above described force reflection scheme, if the cut-off frequency of the complementary filters is sufficiently high and a certain weighting coefficient in the force reflection algorithm is sufficiently low. Experimental results demonstrate that substantial simultaneous improvement of stability and transparency is achieved using the proposed method.
Model-based interrelations of adaptive filter algorithms in acoustic echo control

The design of fast learning and yet robust adaptive filters for acoustic echo control in hands-free voice communication has attracted the research community for decades. This paper presents a fresh and unified view of adaptive filter algorithms in order to change and to generalize some of the previously well-established paradigms. The unified understanding is achieved by introducing state-space dynamical echo path models which also resemble the real world characteristics of hands-free systems.
Ubiquitous Expression of MAKORIN-2 in Normal and Malignant Hematopoietic Cells and Its Growth Promoting Activity

Makorin-2 (MKRN2) is a highly conserved protein and yet its functions are largely unknown. We investigated the expression levels of MKRN2 and RAF1 in normal and malignant hematopoietic cells, and leukemia cell lines. We also attempted to delineate the role of MKRN2 in umbilical cord blood CD34+ stem/progenitor cells and K562 cell line by over-expression and inhibition of MKRN2 through lentivirus transduction and shRNA nucleofection, respectively. Our results provided the first evidence on the ubiquitous expression of MKRN2 in normal hematopoietic cells, embryonic stem cell lines, primary leukemia and leukemic cell lines of myeloid, lymphoid, erythroid and megakaryocytic lineages. The expression levels of MKRN2 were generally higher in primary leukemia samples compared with those in age-matched normal BM cells. In all leukemia subtypes, there was no significant correlation between expression levels of MKRN2 and RAF1. sh-MKRN2-silenced CD34+ cells had a significantly lower proliferation capacity and decreased levels of the early stem/progenitor subpopulation (CFU-GEMM) compared with control cultures. Over-expression of MKRN2 in K562 cells increased cell proliferation. Our results indicated possible roles of MKRN2 in normal and malignant hematopoiesis.
Neural repetition suppression to identity is abolished by other-race faces

Human beings are remarkably skilled at recognizing faces, with the marked exception of other-race faces: the so-called “other-race effect. ” As reported nearly a century ago [Feingold CA (1914) Journal of Criminal Law and Police Science 5:39–51], this face-recognition impairment is accompanied by the popular belief that other-race faces all look alike. However, the neural mechanisms underlying this high-level “perceptual illusion” are still unknown. To address this question, we recorded high-resolution electrophysiological scalp signals from East Asian (EA) and Western Caucasian (WC) observers as they viewed two EA or WC faces. The first adaptor face was followed by a target face of either the same or different identity. We quantified repetition suppression (RS), a reduction in neural activity in stimulus-sensitive regions following stimulus repetition. Conventional electrophysiological analyses on target faces failed to reveal any RS effect. However, to fully account for the paired nature of RS events, we subtracted the signal elicited by target to adaptor faces for each single trial and performed unbiased spatiotemporal data-driven analyses. This unique approach revealed stronger RS to same-race faces of same identity in both groups of observers on the face-sensitive N170 component. Such neurophysiological modulation in RS suggests efficient identity coding for same-race faces. Strikingly, OR faces elicited identical RS regardless of identity, all looking alike to the neural population underlying the N170. Our data show that sensitivity to race begins early at the perceptual level, providing, after nearly 100 y of investigations, a neurophysiological correlate of the “all look alike” perceptual experience.
Adaptive stimulus optimization for sensory systems neuroscience

In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.
An investigation of the structural, connectional, and functional subspecialization in the human amygdala

Although the amygdala complex is a brain area critical for human behavior, knowledge of its subspecialization is primarily derived from experiments in animals. We here employed methods for large‐scale data mining to perform a connectivity‐derived parcellation of the human amygdala based on whole‐brain coactivation patterns computed for each seed voxel. Voxels within the histologically defined human amygdala were clustered into distinct groups based on their brain‐wide coactivation maps. Using this approach, connectivity‐based parcellation divided the amygdala into three distinct clusters that are highly consistent with earlier microstructural distinctions. Meta‐analytic connectivity modelling then revealed the derived clusters' brain‐wide connectivity patterns, while meta‐data profiling allowed their functional characterization. These analyses revealed that the amygdala's laterobasal nuclei group was associated with coordinating high‐level sensory input, whereas its centromedial nuclei group was linked to mediating attentional, vegetative, and motor responses. The often‐neglected superficial nuclei group emerged as particularly sensitive to olfactory and probably social information processing. The results of this model‐free approach support the concordance of structural, connectional, and functional organization in the human amygdala and point to the importance of acknowledging the heterogeneity of this region in neuroimaging research. Hum Brain Mapp 34:3247–3266, 2013. © 2012 Wiley Periodicals, Inc.
Punishment in the Community: The Future of Criminal Justice

Acknowledgements Introduction Part One - The Principles and Politics of Community Punishment 1. Introducing Community Punishment 2. From Alternatives to Custody to Punishment in the Community 3. The Criminal Justice Act 1991 and its Demise 4. Constructing the Punishing Community. Part Two - The Changing Role of the Probation Service 5. From 'Advise, Assist and Befriend' to 'Confront, Control and Monitor' 6. Taking the 'Social' out of Inquiry Reports 7. Demanding but not Degrading? The Appeal of Community Service 8. From Counselling to Instruction: the Development of 'Help' in Probation Discourse 9. Unacceptable Crimes or Unacceptable Criminals? Sex Offenders 10. Unacceptable Crimes or Unacceptable Criminals? Juvenile Delinquents 11. The Future of Punishment in the Community Conclusion: Seeing Custody as the Alternative Bibliography Index
Allele-specific quantitative proteomics unravels molecular mechanisms modulated by cis-regulatory PPARG locus variation

Abstract Genome-wide association studies identified numerous disease risk loci. Delineating molecular mechanisms influenced by cis-regulatory variants is essential to understand gene regulation and ultimately disease pathophysiology. Combining bioinformatics and public domain chromatin information with quantitative proteomics supports prediction of cis-regulatory variants and enabled identification of allele-dependent binding of both, transcription factors and coregulators at the type 2 diabetes associated PPARG locus. We found rs7647481A nonrisk allele binding of Yin Yang 1 (YY1), confirmed by allele-specific chromatin immunoprecipitation in primary adipocytes. Quantitative proteomics also found the coregulator RING1 and YY1 binding protein (RYBP) whose mRNA levels correlate with improved insulin sensitivity in primary adipose cells carrying the rs7647481A nonrisk allele. Our findings support a concept with diverse cis-regulatory variants contributing to disease pathophysiology at one locus. Proteome-wide identification of both, transcription factors and coregulators, can profoundly improve understanding of mechanisms underlying genetic associations.
Lack of Correlation between the Kinase Activity of LRRK2 Harboring Kinase-Modifying Mutations and Its Phosphorylation at Ser910, 935, and Ser955

Leucine-rich repeat kinase 2 (LRRK2) is extensively phosphorylated in cells within a region amino-terminal to the leucine-rich repeat domain. Since phosphorylation in this region of LRRK2, including Ser910, Ser935, Ser955, and Ser973, is significantly downregulated upon treatment with inhibitors of LRRK2, it has been hypothesized that signaling pathways downstream of the kinase activity of LRRK2 are involved in regulating the phosphorylation of LRRK2, although the precise mechanism has remained unknown. Here we examined the effects of LRRK2 inhibitors on the phosphorylation state at Ser910, Ser935, and Ser955 in a series of kinase-inactive mutants of LRRK2. We found that the responses of LRRK2 to the inhibitors varied among mutants, in a manner not consistent with the above-mentioned hypothesis. Notably, one of the kinase-inactive mutants, T2035A LRRK2, underwent phosphorylation, as well as the inhibitor-induced dephosphorylation, at Ser910, Ser935, and Ser955, to a similar extent to those observed with wild-type LRRK2. These results suggest that the kinase activity of LRRK2 is not involved in the common mechanism of inhibitor-induced dephosphorylation of LRRK2.
Design Neural Network Trees Efficiently and Effectively

Neural network tree (NNTree) is a hybrid learning model with the overall structure being a decision tree (DT), and each non-terminal node containing an expert neural network (ENN). Generally speaking, NNTrees outperform conventional DTs because better features can be extracted by the ENNs, and the performance can be improved further through re-training. In this study, we propose an algorithm that can grow NNTrees incrementally on-line. Experiments with several public databases show that, compared with off-line learning, the proposed growing algorithm can produce better NNTrees with less computational cost.
Unique maximum matching algorithms

We consider the problem of testing the uniqueness of maximum matchings, both in the unweighted and in the weighted case. For the unweighted case, we have two results. First, given a graph with n vertices and m edges, we can test whether the graph has a unique perfect matching, and find it if it exists, in O(mlog4n) time. This algorithm uses a recent dynamic connectivity algorithm and an old result of Kotzig characterizing unique perfect matchings in terms of bridges. For the special case of planar graphs, we improve the algorithm to run in O(nlogn) time. Second, given one perfect matching, we can test for the existence of another in linear time. This algorithm is a modification of Edmonds' blossom-shrinking algorithm implemented using depth-first search. A generalization of Kotzig's theorem proved by Jackson and Whitty allows us to give a modification of the first algorithm that tests whether a given graph has a unique f-factor, and find it if it exists. We also show how to modify the second algorithm to check whether a given f-factor is unique. Both extensions have the same time bounds as their perfect matching counterparts. For the weighted case, we can test in linear time whether a maximum-weight matching is unique, given the output from Edmonds' algorithm for computing such a matching. The method is an extension of our algorithm for the unweighted case.
Confidence-Based Demonstration Selection for Interactive Robot Learning

Effective learning by demonstration techniques enable complex robot behaviors to be taught from a small number of demonstrations. Demonstrations are obtained based on a selection algorithm, which governs which states are labeled by the human teacher. In this work, we examine selection algorithms used by the robot to request demonstration examples. Previous approaches typically rely on a fixed confidence threshold. In this work, we highlight the drawbacks of using a single threshold, and contribute an algorithm for automatically setting multiple confidence thresholds designed to target domain states with the greatest uncertainty. Our evaluation compares the proposed multi-threshold selection method to confidence-based selection using a single fixed threshold, and manual data selection by the teacher. Our results indicate that the multi-threshold approach significantly reduces the number of demonstrations required to learn the task.
ARE ASIAN MARKETS INTEGRATED? EVIDENCE FOR SIX COUNTRIES VIS-A-VIS JAPAN

This paper presents some empirical evidence on the degree of integration between the goods and financial markets of Japan and six Asian countries. The evidence is obtained by testing two international parity conditions using unconventional specifications: uncovered interest parity (UIP) and ex ante purchasing power parity (PPP). The results of cointegration tests are strongly supportive of the two conditions over the period 1980-1994. The paper concludes that Asian goods and financial markets have reached a high level of integration. [G14]
Facilitating Settlement at the Arbitration Table: Comparing Views on Settlement Practice Among Arbitration Practitioners in East Asia and the West

This article presents a cross cultural examination of how international arbitrators in East Asian and Western countries view the goal of settlement in international arbitration. The result of a 115 person survey and 64 follow up interviews shed light on the underlying cultural attitudes and approaches to settlement in international arbitration as practiced in diverse regions. The findings indicate that arbitration practitioner’s perceptions of the frequency of compromise decision in international arbitration demonstrate a high degree of convergence across regions. At the same time, cultural and socio-economic distinctions are reflected in varying arbitrator perceptions regarding the arbitrators’ role in settlement, whether settlement is regarded as a goal in arbitration and the types of efforts made pre-arbitration to settle disputes. In particular, arbitrators working in the East Asian region regard the goal of facilitating voluntary settlement in the context of international arbitration with greater importance and generally make greater efforts pre-arbitration to settle disputes as compared with counterparts in the West.
Fault–Tolerant Master-Workers Framework for MapReduce Applications

Over the past few years, the top web companies like Google, Yahoo etc have come up with several special techniques that process large amounts of raw data, such as crawled documents, web request logs, etc. The issue is how to handle large computations and large data. Parallel computing is the remedy for reducing the response time. The challenge here is to parallelizing the computation part and then Google introduced a technique called MapReduce to deal with this challenge. In this paper we are proposing a general Master-Workers(MW) Framework i.e., a framework for increasing the performance of the MapReduce applications. With various kinds of experiments we have shown our parallel framework which is efficient and robust for executing MapReduce applications on clusters. To this end, we build MW Framework for the users that can efficiently execute any MapReduce applications by varying parameters such as data size and the number of workers available. Our MW Framework is also robust against faults and poor machines.