Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient SQL-Querying Method for Data Mining in Large Data Bases

Data mining can be understood as a process of extraction of knowledge hidden in very large data sets. Often data mining techniques (e.g. discretization or decision tree) are based on searching for an optimal partition of data with respect to some optimization criterion. In this paper, we investigate the problem of optimal binary partition of continuous attribute domain for large data sets stored in relational data bases (RDB). The critical for time complexity of algorithms solving this problem is the number of simple SQL queries like SELECT COUNT FROM . WHERE attribute BETWEEN . (related to some interval of attribute values) necessary to construct such partitions. We assume that the answer time for such queries does not depend on the interval length. Using straightforward approach to optimal partition selection (with respect to a given measure), the number of necessary queries is of order O(N), where N is the number of preassumed partitions of the searching space. We show some properties of considered optimization measures, that allow to reduce the size of searching space. Moreover, we prove that using only O(logiV) simple queries, one can construct the partition very close to optimal.
Droplet microfluidic technology for single-cell high-throughput screening

We present a droplet-based microfluidic technology that enables high-throughput screening of single mammalian cells. This integrated platform allows for the encapsulation of single cells and reagents in independent aqueous microdroplets (1 pL to 10 nL volumes) dispersed in an immiscible carrier oil and enables the digital manipulation of these reactors at a very high-throughput. Here, we validate a full droplet screening workflow by conducting a droplet-based cytotoxicity screen. To perform this screen, we first developed a droplet viability assay that permits the quantitative scoring of cell viability and growth within intact droplets. Next, we demonstrated the high viability of encapsulated human monocytic U937 cells over a period of 4 days. Finally, we developed an optically-coded droplet library enabling the identification of the droplets composition during the assay read-out. Using the integrated droplet technology, we screened a drug library for its cytotoxic effect against U937 cells. Taken together our droplet microfluidic platform is modular, robust, uses no moving parts, and has a wide range of potential applications including high-throughput single-cell analyses, combinatorial screening, and facilitating small sample analyses.
A real-time social media aggregation tool: Reflections from five large-scale events

Social media is gaining interest among emergency response professionals and researchers as a source of real-time information about ongoing events. In this paper we summarize conclusions drawn while using a software prototype that collects, clusters and visualizes status updates from the social microblogging service Twitter in relation to five large-scale events during the spring of 2011. We identify different uses for gathered information and discuss metrics for prioritization of information with regard to these uses.
English-learning one- to two-year-olds do not show a consonant bias in word learning*

ABSTRACT Following the proposal that consonants are more involved than vowels in coding the lexicon (Nespor, Peña & Mehler, 2003), an early lexical consonant bias was found from age 1;2 in French but an equal sensitivity to consonants and vowels from 1;0 to 2;0 in English. As different tasks were used in French and English, we sought to clarify this ambiguity by using an interactive word-learning study similar to that used in French, with British-English-learning toddlers aged 1;4 and 1;11. Children were taught two CVC labels differing on either a consonant or vowel and tested on their pairing of a third object named with one of the previously taught labels, or part of them. In concert with previous research on British-English toddlers, our results provided no evidence of a general consonant bias. The language-specific mechanisms explaining the differential status for consonants and vowels in lexical development are discussed.
Taking up Cancer Immunotherapy Challenges: Bispecific Antibodies, the Path Forward?

As evidenced by the recent approvals of Removab (EU, Trion Pharma) in 2009 and of Blincyto (US, Amgen) in 2014, the high potential of bispecific antibodies in the field of immuno-oncology is eliciting a renewed interest from pharmaceutical companies. Supported by rapid advances in antibody engineering and the development of several technological platforms such as Triomab or bispecific T cell engagers (BiTEs), the “bispecifics” market has increased significantly over the past decade and may occupy a pivotal space in the future. Over 30 bispecific molecules are currently in different stages of clinical trials and more than 70 in preclinical phase. This review focuses on the clinical potential of bispecific antibodies as immune effector cell engagers in the onco-immunotherapy field. We summarize current strategies targeting various immune cells and their clinical interests. Furthermore, perspectives of bispecific antibodies in future clinical developments are addressed.
An efficient change detection algorithm based on a statistical nonparametric camera noise model

In this paper we present a change detection algorithm for grey level sequences based on the background subtraction technique, which achieves a good trade-off between time performance and detection quality. The basic idea consists in separating the background process into a deterministic background process and a stochastic camera noise process. The assumption that statistics of the camera noise for a pixel only depends on its current grey level allows to infer a nonparametric statistical camera noise model once and for all arising from a short bootstrap sequence. Hence, 256 couples of lower and upper deterministic thresholds are extracted, to be used in the background subtraction step. While the deterministic nature of the background model as well as of the thresholds lead to an efficient algorithm, utilising 256 couples of different thresholds results in a very sensitive detection. Experimental results allow to assess both the efficiency and the effectiveness of the method we devised.
Dynamic Head Cluster Election Algorithm for Clustered Ad-Hoc Networks

In distributed system, the concept of clustering consists on dividing the geographical area covered by a set of nodes into small zones. In mobile network, the clustering mechanism varied due to the mobility of the nodes any time in any direction. That causes the partitioning of the network or the joining of nodes. Several existing centralized or globalized algorithm have been proposed for clustering technique, in a manner that no one node becomes isolated and no cluster becomes overloaded. A particular node called head cluster or leader is elected, has the role to organize the distribution of nodes in clusters. We propose a distributed clustering and leader election mechanism for Ad-Hoc mobile networks, in which the leader is a mobile node. Our results show that, in the case of leader mobility the time needed to elect a new leader is smaller than the time needed a significant topological change in the network is happens.
Spinal Cord Axon Segmentation

An automatic method for accurately segmenting MRI images of axons would reduce the manpower required for axon and myelin research. We implement active contours, which is reported to successfully identify axons in electron micrographs, and evaluate its performance on MRI images. We also show that a simple method for estimating the error of a segmentation can achieve similar results to a ground truth error function when applied to a parameter optimisation problem.
Customer Value Analysis Based on BP Arithmetic

Customer is one of the most important resources of an enterprise. Customer value analysis is the basis of customer relationship management and customer classification is an important item of customer value analysis. Aiming at the characteristics of customer in the mobile telecommunication industry, the thesis designed the BP neural network model, and presented the doable evaluating programs using matlab6.5 neural network toolbox according to the customer value evaluation system. In this way, the objectively evaluation on customer value of the mobile telecommunication industry, according to the evaluation and calculation results, can present some suggestions to improve its customer value.
Fault-tolerant behavior in state-of-the-art grid workflow management systems

While the worko w paradigm, emerged from the eld of business processes, has been proven to be the most successful paradigm for creating scientic applications for execution also on Grid infrastructures, most of the current Grid worko w management systems still cannot deliver the quality, robustness and reliability that are needed for widespread acceptance as tools used on a day-to-day basis for scientists from a multitude of scientic elds. This paper introduces the current state of the art in fault tolerance techniques for Grid worko w systems. The examined categories and the summary of current solutions reveal future directions in this area and help to guide research towards open issues.
Nonparametric discriminant analysis via recursive optimization of Patrick-Fisher distance

A method for the linear discrimination of two classes is presented. It searches for the discriminant direction which maximizes the Patrick-Fisher (PF) distance between the projected class-conditional densities. It is a nonparametric method, in the sense that the densities are estimated from the data. Since the PF distance is a highly nonlinear function, we propose a recursive optimization procedure for searching the directions corresponding to several large local maxima of the PF distance. Its novelty lies in the transformation of the data along a found direction into data with deflated maxima of the PF distance and iteration to obtain the next direction. A simulation study and a medical data analysis indicate the potential of the method to find the sequence of directions with significant class separations.
A multichannel widely linear approach to binaural noise reduction using an array of microphones

This paper deals with the problem of binaural noise reduction using an array of microphones. This is a very important problem in applications such as teleconferencing and hearing aids where there is a need to mitigate the noise effect from the noisy signals picked up by multiple microphones and produce two “clean” outputs. The mitigation of the noise should be made in such a way that no audible distortion is added to the two outputs (this is the same as in the single-channel case) and meanwhile the spatial information of the desired sound source should be preserved so that, after noise reduction, the listener will still be able to localize the sound source thanks to his/her binaural hearing mechanism. In this paper, we present a novel approach to this problem where we first form a number of complex input signals from the multiple and real microphone observations. We also merge the two expected real outputs into a complex output signal. The widely linear estimation theory is then used to derive optimal noise reduction filters that can achieve noise reduction while preserving the desired signal (speech) and its spatial information. With this new formulation, the Wiener and minimum variance distortionless response (MVDR) filters are derived. Experiments are provided to justify the effectiveness of these filters.
Power Allocation for Goodput Optimization in BICM-OFDM Systems

This paper deals with the power allocation problem for coded multicarrier transmission. Specifically, we focus on a bit interleaved coded modulation (BICM) packet transmission implemented with orthogonal frequency division multiplexing (OFDM) and in the presence of automatic repeat request (ARQ) protocol. Capitalizing on the binary-input output-symmetric (BIOS) nature of the BICM channel it is provided a simple upper-bound of the rate of information bits received without any error, the so called goodput. Based on this theoretical characterization, we develop a power allocation strategy among the different subcarriers so that the system goodput performance metric is maximized. The effectiveness of the proposed method is numerically testified for BICM-OFDM transmission in the context of the typical WLAN scenario.
Characteristics and Prospects of the Adolescents' Deviant Behaviors on Internet

At first this paper discusses the concept,the types,the main expressions,and the explanations of deviant behaviors online. On the basis of above-mentioned discussions,the authors then open up prospects for research and suggest that the concept and the research method,the factors,the influences,the prevention,and intervention strategies of the deviant behaviors online and the relationship between deviant behaviors online and offline are important topics to be explored in the future.
Detecting Hidden Anomalies Using Sketch for High-speed Network Data Stream Monitoring

Monitoring network data streams in real-time to check security event become more and more important along with the rapid growth of Internet applications. The detection typically treats the traffic as a collection of flows that need to be examined for significant changes in traffic pattern (e.g., volume, number of connections). However, as link speeds and the number of flows increase, keeping per- flow state is either too expensive or too slow. We propose building compact summaries of the traffic data using the notion of sketches.In this paper, we proposed an IP address traceability network anomaly detection method at right time based on the summary data structure. In this method, the network traffic information is recorded into sketch online in every circle which is used to detect anomalies. By using EWMA forecasting model to get each circle forecast value, it computes the error sketch between the recoded value and forecast value and detects heavy network traffic change based on Mean-Standard deviation in the error sketch. The method is effective in detecting DDoS attack, scan attack. And it can trace the IP address of victim host. Evaluated by the experiment, the results show that this method takes up little computing and memory resources and is suitable for anomaly detection under the high-speed network traffic.
The Role of Transacademic Interface Managers in Transformational Sustainability Research and Education

Working towards sustainable solutions requires involving professionals and stakeholders from all sectors of society into research and teaching. This often presents a challenge to scholars at universities, as they lack capacity and time needed for negotiating different agendas, languages, competencies, and cultures among faculty, students, and stakeholders. Management approaches and quality criteria have been developed to cope with this challenge, including concepts of boundary organizations, transdisciplinary research, transition management, and interface management. However, few of these concepts present comprehensive proposals how to facilitate research with stakeholder participation while creating educational opportunities along the lifecycle of a project. The article focuses on the position of a transacademic interface manager (TIM) supporting participatory sustainability research and education efforts. We conceptualize the task portfolio of a TIM; outline the capacities a TIM needs to possess in order to successfully operate; and propose an educational approach for how to train students in becoming a TIM. For this, we review the existing literature on TIMs and present insights from empirical sustainability research and educational projects that involved TIMs in different functions. The article provides practical guidance to universities on how to organize these critical endeavors more effectively and to offer students an additional career perspective.
Program Behavior Analysis and Control for Online IDE

Compared with the traditional local IDE, online IDE provides a no-install programming environment. The proceeding in this area is attracting more and more researchers' focuses. Although online IDE can bring developers a lot of convenience for developing process, it also suffers from some special challenges. While most current research work focuses only on the implementation of basic features, some tough problems are still less touched. This paper summarized three main kinds of actual problems (Wrong file operations, Banned method calling, and Excessive resource consumption) encountered when using the online IDE, and proposed a program behavior analysis based solutions to control these problems adaptively. Finally, this paper demonstrated the effectiveness of the proposed solutions by applying them in a real online IDE.
Cylindrical Relief Textures Mapping

This paper describes a new Image Based Rendering technique aimed at increasing the realism of textured cylindrical surfaces by adding 3D details and enhancing the depth conceived by the viewer. Cylindrical relief texture mapping extends the existing work on planar relief textures by using cylinders as warp surfaces. After mapping the planar relief texture to a reference cylinder, cylindrical warping equations are used to generate an intermediate image for texture mapping the reference cylinder and introducing motion parallax. The strength of the technique is demonstrated by the visual realism provided, with examples showing how the proposed method can be used for generating depth enhanced panoramas and improved endoscopic simulations.
GhostRider: A Hardware-Software System for Memory Trace Oblivious Computation

This paper presents a new, co-designed compiler and architecture called GhostRider for supporting privacy preserving computation in the cloud. GhostRider ensures all programs satisfy a property called memory-trace obliviousness (MTO): Even an adversary that observes memory, bus traffic, and access times while the program executes can learn nothing about the program's sensitive inputs and outputs. One way to achieve MTO is to employ Oblivious RAM (ORAM), allocating all code and data in a single ORAM bank, and to also disable caches or fix the rate of memory traffic. This baseline approach can be inefficient, and so GhostRider's compiler uses a program analysis to do better, allocating data to non-oblivious, encrypted RAM (ERAM) and employing a scratchpad when doing so will not compromise MTO. The compiler can also allocate to multiple ORAM banks, which sometimes significantly reduces access times.We have formalized our approach and proved it enjoys MTO. Our FPGA-based hardware prototype and simulation results show that GhostRider significantly outperforms the baseline strategy.
"Jump and refine" for rapid pointing on mobile phones

Standard input devices for mobile phones are directional keys and discrete thumb-joysticks. These devices are dedicated to the discrete GUIs of the phones (eg. scroll lists and small icons arrays). Today, new mobile applications are arising and require adapted interfaces. In particular, the widespread of 3D applications will be favored if users can efficiently point on any part of thescreen. In this paper, we propose a new interaction technique called Jump and Refine for selection tasks on mobile phones. This technique is based on two levels of cursor displacement in order to reduce the number of keystrokes. The first level allows fast movements into an underlying grid. The second one can be used for accurate positioning into the selected area. We present a user study which shows that using a first coarse jump level decreases the selection completion times. The study also shows that the technique is widely accepted by the users. Finally, we discuss the optimal grid sizes.
Topological Field Parsing of German

Freer-word-order languages such as German exhibit linguistic phenomena that present unique challenges to traditional CFG parsing. Such phenomena produce discontinuous constituents, which are not naturally modelled by projective phrase structure trees. In this paper, we examine topological field parsing, a shallow form of parsing which identifies the major sections of a sentence in relation to the clausal main verb and the subordinating heads. We report the results of topological field parsing of German using the unlexicalized, latent variable-based Berkeley parser (Petrov et al., 2006) Without any language- or model-dependent adaptation, we achieve state-of-the-art results on the TuBa-D/Z corpus, and a modified NE-GRA corpus that has been automatically annotated with topological fields (Becker and Frank, 2002). We also perform a qualitative error analysis of the parser output, and discuss strategies to further improve the parsing results.
A Local-world Evolving Model for WSNs with the Self-regulating Attractiveness

Energy efficiency and fault-tolerant mechanism are two important issues in the research field of the WSNs. How to build the topological structure to improve the fault-tolerant ability and decrease the energy consumption is a puzzle for the researchers. In this paper, we take the complex network as a research instrument and use the scale-free feature to improve the robustness of the network. Besides, based on the more energy-efficient local world evolving model, through dynamic self-regulation of the node’s attractiveness, we reach the target of prolonging the network lifetime. The last but not least, the simulation result indicates that our model indeed effectively controls the excessive inflation of the node degree under the precondition of maintaining the scale-free feature. So our model makes definite sense to the research of topological structure in the WSNs.
Understanding gender differences in Korean emotional expressions for increased cultural competency of social workers

This study identified Korean emotional expressions described by male and female Koreans, who disagreed about their use under similar circumstances. The authors assessed the meanings of 504 ‘emotional’ terms, rank-ordered them according to how high the participants rated various emotions and used the kappa statistic to discern gender-based incongruence. The findings showed that identical emotional expressions might have nuanced differences in mutually exclusive emotional states. This was particularly apparent among males, who reported using the same expressions in two different situations. The results strengthen social workers’ language-centred activities, which help them assist Koreans and Korean-Americans to use helping processes.
Processing Spatio-Temporal Queries through a Streaming Fashion

In the past few years, the wide application of online map applications and location based services have significantly changed the ways of our life. Today, it is typical for us to search for directions or businesses on the Internet and find our ways through cell phones. Lots of the location based services require to provide answers to users continuously so that the users can interact with the applications. For example, a tourist may ask for the nearest three restaurants to be reported continuously while traveling in a city, so that he or she may choose to go to one at any time. As the the answers may change over time, the continuous nature of the applications poses new challenges on methods to process the queries efficiently. We look at a few key strategies to process spatio-temporal queries in a streaming fashion such as incremental and shared computation, safe regions, and time-constraint processing. We illustrate these strategies through the algorithms to several important types of continuous spatio-temporal queries.