Miracle-dz/UniFAR-FTUs huggingface dataset:
A Complex Permittivity Extraction Method Based on Anomalous Dispersion

A novel method to extract dielectric material parameters from the anomalous phase response is theoretically investigated and experimentally verified. A microstrip resonance circuit that operates in the anomalous dispersion spectrum is constructed by employing the material sample as the substrate. This topology results in a strongly dispersive transmission phase having a slope opposite to the case in normal dispersion. This unique phase reversal property facilitates the detection of the resonance frequency with higher accuracy. Furthermore, since the transmission phase and magnitude in the anomalous dispersive region are related through Kramers-Kronig-like equations, one phase measurement is sufficient to completely characterize a dielectric material. Five known dielectric samples are characterized and the extracted parameters are compared with the known parameters. The extracted dielectric constants are found to be within a 10% error range. The extracted resonant parameters are utilized in reconstructing the magnitude and phase spectra in off-resonance regions. The reconstructed and measured curves bear close resemblance.
Multi-phenotypic Role of Serum Response Factor in the Gastrointestinal System

Serum response factor (SRF) is a master transcription factor of the actin cytoskeleton that binds to highly conserved CArG boxes located within the majority of smooth muscle cell (SMC)-restricted promoters/enhancers. Although most studies of SRF focus on skeletal muscle, cardiac muscle, and vascular SMCs, SRF research has recently expanded into the gastrointestinal (GI) system. Genome scale analyses of GI SMC transcriptome and CArG boxes (CArGome) have identified new SRF target genes. In addition to circular and longitudinal smooth muscle layers, SRF is also expressed in GI mucosa and cancers. In the GI tract, SRF is the central regulator of genes involved in apoptosis, dedifferentiation, proliferation, and migration of cells. Since SRF is the cell phenotypic modulator, it may play an essential role in the development of myopathy, hypertrophy, ulcers, gastric and colon cancers within the GI tract. Given the multi-functional role displayed by SRF in the digestive system, SRF has received more attention emerging as a potential therapeutic target. This review summarizes the findings in SRF research pertaining to the GI tract and provides valuable insight into future directions.
A user behavior model for average precision and its generalization to graded judgments

We explore a set of hypothesis on user behavior that are potentially at the origin of the (Mean) Average Precision (AP) metric. This allows us to propose a more realistic version of AP where users click non-deterministically on relevant documents and where the number of relevant documents in the collection needs not be known in advance. We then depart from the assumption that a document is either relevant or irrelevant and we use instead relevance judgment similar to editorial labels used for Discounted Cumulated Gain (DCG). We assume that clicked documents provide users with a certain level of "utility" and that a user ends a search when she gathered enough utility. Based on the query logs of a commercial search engine we show how to evaluate the utility associated with a label from the record of past user interactions with the search engine and we show how the two different user models can be evaluated based on their ability to predict accurately future clicks. Finally, based on these user models, we propose a measure that captures the relative quality of two rankings.
Supporting the Collaborative Collection of User ' s Requirements

Most of the software systems development processes carry high risks for technological companies and service organizations. Some of these risks may ultimately produce delayed or failed projects with low quality software products. The Standish Group in 1999 presented the “Chaos Report”, which determined through a large scale scan on IT projects in northern hemisphere corporations that the software development industry continued to be marked by low quality products and services. According to this report, the main causes of failed projects during 1994 were the following: incomplete requirements (13,1%), little users participation (12,4%), lack of resources (10,6%), non-realistic expectations (9,9%), insufficient executive support (12.4%), changes in requirements and specifications (8,7%), lack of planning (8,1%), little administration of information technology (6,2%), technological incomprehension (4,3%), others (9,9%). It is important to note that a high percentage of errors are related to definition and administration of requirements and little user’s participation. Even though this study was performed some years ago, most of the current software projects are still dealing with the same risks. It is clear that any improvement in requirement engineering may substantially reduce the high risk that menace the quality of decision taken during the negotiations of the user’s final requirements. Requirement engineering includes the following steps (see e.g. Nuseibeh and Easterbrook, 2000): • Collect requirements: identify the stakeholders and obtain their requirements. • Model and analyze the requirements: build abstract descriptions for a better interpretation. • Communicate the requirements: transfer the knowledge among the stakeholders. • Come to an agreement on the requirements: negotiate the requirements with the stakeholders. • Evolve the requirements: manage changes not only in the requirements but also in the environment, or changes generated by the stakeholders.
First-aid: surviving and preventing memory management bugs during production runs

Memory bugs in C/C++ programs severely affect system availability and security. This paper presents First-Aid, a lightweight runtime system that survives software failures caused by common memory management bugs and prevents future failures by the same bugs during production runs. Upon a failure, First-Aid diagnoses the bug type and identifies the memory objects that trigger the bug. To do so, it rolls back the programto previous checkpoints and uses two types of environmental changes that can prevent or expose memory bug manifestation during re-execution. Based on the diagnosis, First-Aid generates and applies runtime patches to avoid the memory bug and prevent its reoccurrence. Furthermore, First-Aid validates the consistent effects of the runtime patches and generates on-site diagnostic reports to assist developers in fixing the bugs. We have implemented First-Aid on Linux and evaluated it with seven applications that contain various types of memory bugs, including buffer overflow, uninitialized read, dangling pointer read/write, and double free. The results show that First-Aid can quickly diagnose the tested bugs and recover applications from failures (in 0.084 to 3.978 seconds). The results also show that the runtime patches generated by First-Aid can prevent future failures caused by the diagnosed bugs. Additionally, First-Aid provides detailed diagnostic information on both the root cause and the manifestation of the bugs. Furthermore, First-Aid incurs low overhead (0.4-11.6% with an average of 3.7%) during normal execution for the tested buggy applications, SPEC INT2000, and four allocation intensive programs.
Quantitative Characterization of Glycan-Receptor Binding of H9N2 Influenza A Virus Hemagglutinin

Avian influenza subtypes such as H5, H7 and H9 are yet to adapt to the human host so as to establish airborne transmission between humans. However, lab-generated reassorted viruses possessing hemagglutinin (HA) and neuraminidase (NA) genes from an avian H9 isolate and other genes from a human-adapted (H3 or H1) subtype acquired two amino acid changes in HA and a single amino acid change in NA that confer respiratory droplet transmission in ferrets. We previously demonstrated for human-adapted H1, H2 and H3 subtypes that quantitative binding affinity of their HA to α2→6 sialylated glycan receptors correlates with respiratory droplet transmissibility of the virus in ferrets. Such a relationship remains to be established for H9 HA. In this study, we performed a quantitative biochemical characterization of glycan receptor binding properties of wild-type and mutant forms of representative H9 HAs that were previously used in context of reassorted viruses in ferret transmission studies. We demonstrate here that distinct molecular interactions in the glycan receptor-binding site of different H9 HAs affect the glycan-binding specificity and affinity. Further we show that α2→6 glycan receptor-binding affinity of a mutant H9 HA carrying Thr-189→Ala amino acid change correlates with the respiratory droplet transmission in ferrets conferred by this change. Our findings contribute to a framework for monitoring the evolution of H9 HA by understanding effects of molecular changes in HA on glycan receptor-binding properties.
Kernel Based Sequential Data Anomaly Detection in Business Process Event Logs

Business Process Management Systems (BPMS) log events and traces of activities during the execution of a process. Anomalies are defined as deviation or departure from the normal or common order. Anomaly detection in business process logs has several applications such as fraud detection and understanding the causes of process errors. In this paper, we present a novel approach for anomaly detection in business process logs. We model the event logs as a sequential data and apply kernel based anomaly detection techniques to identify outliers and discordant observations. Our technique is unsupervised (does not require a pre-annotated training dataset), employs kNN (k-nearest neighbor) kernel based technique and normalized longest common subsequence (LCS) similarity measure. We conduct experiments on a recent, large and real-world incident management data of an enterprise and demonstrate that our approach is effective.
A Typology of Critical Incidents in Intergroup Dialogue: Perspectives of Facilitators-in-Training

There is a growing body of research on the positive outcomes associated with participation in intergroup dialogue (IGD), a group intervention providing opportunities for sustained communication across social groups (Gurin, Nagda, & Zúñiga, 2013). Less research has examined the experiences of IGD facilitators. To better understand these experiences, we examined perceptions of critical incidents (CIs) in 7 consecutive IGD sessions among 13 IGD facilitators-in-training. We used latent semantic analysis (Landauer & Dumais, 1997) on 77 CI reports to derive pairwise similarity ratings. We then conducted a cluster analysis on these ratings and identified 6 clusters of CIs: (a) managing anxiety and promoting safety, (b) development of the group and the cofacilitator relationship, (c) learning from and with others, (d) vulnerable/meaningful disclosures, (e) difference and conflict, and (f) emotional openness. These clusters of CIs are discussed in terms of their relationships to the IGD literature, the literature on group counseling leadership, and the types of CIs identified by group members in previous research (Kivlighan & Arseneau, 2009).
Morphological Analysis and Diacritical Arabic Text Compression

Morphological analysis of Arabic words allows decreasing the storage requirements of the Arabic dictionaries, more efficient encoding of diacritical Arabic text, faster spelling and efficient Optical character recognition. All these factors allow efficient storage and archival of multilingual digital libraries that include Arabic texts. This paper presents a lossless compression algorithm based on the affix analysis that takes advantage of the statistical studies of the diacritical Arabic morphological features. The algorithm decomposes a given Arabic word into its root and its affixes. The affixes (prefix, infix, and suffix) are the redundant elements of the word. The roots are stored in the root dictionary. Also, we maintain categorized affix dictionaries and their valid combinations to validate and generate the morphological forms during encoding and decoding using a list of patterns. Since our goal is lossless reproducible Arabic text, stemming is not an option and noise words (high frequency words) cannot be filtered out. The size of the obtained root dictionary is about 8000 three-character roots and 700 four character roots. We also code the most frequently occurring diacritical bigrams (biliterals) and trigrams (triliterals) with unused codewords in ASCII, ASMO-449, and Unicode standard codes. Using combined methods of root dictionaries and the proposed coding scheme, compression ratios of proper Arabic text compare favorably with other unigram non-diacritical methods. Keyword: Compression, Affixes, Morphological Analysis, Dictionary, Root, Diacritics, lexicon, spelling, archival, digital library.
A Preliminary Investigation of a Randomized Dependent Group Contingency for Hallway Transitions

Abstract:We conducted a preliminary investigation of a randomized dependent group contingency to decrease disruptive behavior during hallway transitions. Two first-graders, identified by their classroom teacher, participated in this study. A multiple baseline across transitions was used to evaluate the effects of the randomized dependent group contingency on participants' disruptive behavior during hallway transitions. Results indicated that both participants engaged in lower levels of disruptive behavior during the group contingency compared to baseline although to varying degrees.
Development of a aural real-time rhythmical and harmonic tracking to enable the musical interaction with the Waseda Flutist Robot

The Waseda Flutist Robot is able to play the flute at the level of an intermediate human player. This ability opens a wide field of possibilities to research human-robot musical interaction. This research is focused on enabling the flutist robot to interact more naturally with musical partners in the context of a Jazz band. For this purpose a Musical-Based Interaction System (MbIS) has been proposed to enable the robot to process both visual and aural cues coming throughout the interaction with musicians. In a previous publication, we have concentrated on the implementation of visual communication techniques. We created an interaction interface that enabled the robot to detect instrument gestures of partner musicians during a musical performance. Two computer vision approaches were implemented to create a two-skill-level interface for visual human-robot interaction in a musical context. In this paper we focus on the aural perception system of the robot. The method introduced here enables the robot to, a suitable environment provided, detect the tempo and harmony of a partner musician's play, with a specific focus on improvisation. We achieve this by examining the rhythmical and harmonic characteristics of the recorded sound. We apply the same approach to amplitude and frequency spectrum, thus, in the former case tracking amplitude transients. In the latter case, as we focus on communication with monophonic woodwind instruments, we follow the most prominent peak in the frequency spectrum. We specifically use a similar technique for the audio analysis as we did for our previous research on motion tracking. From the experimental results, we have shown that after implementing our algorithm the robot is able to correctly recognize a number of rhythms and harmonies. It is able to engage in a simple form of stimuli and reaction play with a human musician.
Design and Implementation of a Multiple-Instruction-Stream Multiple-Execution-Pipeline Architecture

This paper describes a single chip Multiple-InstructionStream Multiple-Execution-Pipeline (MIS-MEP) architecture capable of improving processor throughput. The MISMEP architecture uses multiple instruction dispatch/branch units (slots) to dispatch instructions from multiple instruction streams. Multiple dedicated execution pipelines are provided that are shared by these slots and instructions can be executed on the pipelines in parallel. The slot can communicate and synchronize with one another via queues and synchronization registers. Two examples show how to use the queues and synchronization registers. The MIS-MEP processor can issue 3.945 and 1.633 instructions per cycle in the two examples respectively.
Facial Expression Recognition Using Texture Description of Displacement Image

In recent years, facial expression recognition, as an interesting problem in computer vision has been performed by means of static and dynamic methods. Dynamic information plays an important role in recognizing facial expression in the image sequences. However, using the entire dynamic information in the expression image sequences is of higher computational cost compared to the static methods. To reduce the computational cost, instead of entire image sequence, only neutral and emotional faces can be employed. In the previous research, this idea was used by means of Difference of Local Binary Pattern Histogram Sequences (DLBPHS) method in which facial important small displacements were vanished by subtracting Local Binary Pattern (LBP) features of neutral and emotional face images. In this paper, a novel approach is proposed to utilize two face images. In the proposed method, the face component displacements are highlighted by subtracting neutral image from emotional image; then, LBP features are extracted from the difference image as well as the emotional one. Then, the feature vector is created by concatenating two LBP histograms. Finally, a Support Vector Machine (SVM) is used to classify the extracted feature vectors. The proposed method is evaluated on standard databases and the results show a significant accuracy improvement compared to DLBPHS.
NTU Textual Entailment System for NTCIR 9 RITE Task

paper, we propose a system to deal with the Chinese textual entailment problem for NTCIR-9 RITE task. The RITE task consists of four subtasks, simplified Chinese binary classification (CS_BC), simplified Chinese multi-way classification (CS_MC), traditional Chinese binary classification (CT_BC), and traditional Chinese multi-way classification (CT_MC). According to the definitions of these subtasks, a machine learning based classification framework is proposed and tested under various setups. The performance of our system in the formal run achieves accuracies of 73.5%, 57.5%, 60.8%, and 48.3% for CS_BC, CS_MC, CT_BC, and CT_MC respectively.
Topological lens effects in universes with non-euclidean compact spatial sections

Universe models with compact spatial sections smaller than the observable universe produce a topological lens effect. Given a catalog of cosmic sources, we estimate the num- ber of topological images in locally hyperbolic and locally ellip- tic spaces, as a function of the cosmological parameters, of the volume of the spatial sections and of the catalog depth. Next we apply the crystallographic method, aimed to detect a topological signal in the 3D distance histogram between images, to com- pact hyperbolic models. Numerical calculations in the Weeks manifold allow us to check the absence of crystallographic sig- nature of topology, due to the fact that the number of copies of the fundamental domain in the observable covering space is low and that the points are not moved the same distance by the holonomies of space.
Implementation and evaluation of patient-specific three-dimensional internal dosimetry.

UNLABELLED Current methods for calculating the absorbed dose in a target region from a source region rely on a standard "reference man" geometry and assume an uniform distribution of radiolabel. While this approach is acceptable at the low levels of radioisotope administered for most diagnostic purposes, the generality of the calculations is not adequate for doses at the higher levels required for therapy and is not easily extendible to tumor dosimetry. METHODS We have developed an integrated system which utilizes patient anatomy and radionuclide distribution in the calculation of absorbed dose rate or total dose to any user-defined target region. Images of radionuclide distribution (PET/SPECT) are registered to anatomic images (CT/ MRI) and then entered into a three-dimensional internal dosimetry software system (3D-ID) where regions of interest are defined. Dose calculations are performed by the mathematical convolution between a user-specified, dose-point kernel with the activity in the source volume over the target volume. The resulting dose rate distribution may be scaled by cumulated activity to yield absorbed dose. In addition to calculating the mean dose, dose-volume histograms may be generated which plot absorbed dose with respect to percent of volume. The method was evaluated using selected standard man phantom organs. RESULTS Dose estimates for two patient studies are included to illustrate differences between patient-specific and MIRD-based calculations. The package provides an alternative approach to image display and three-dimensional internal dose calculations. CONCLUSION The dose-volume histogram representation of absorbed dose to a target volume provides valuable information in assessing tumor control probability and normal tissue toxicity.
Fast Binary Block Matching Motion Estimation using Efficient One-Bit Transform

Binary block matching algorithm employs one-bit transform (1BT) to transform video sequences from full resolution representation (8-bit/pixel in general) to 1-bit/pixel bit-plane, then performs block matching motion estimation in bit-plane to save computations. Unfortunately, current 1BT algorithms either have bad output motion vectors or are computational intensive. In this paper, a novel fast and efficient 1BT algorithm called the overlap-windowed thresholding algorithm (OWT), and a new fast binary block matching algorithm (FBBMA) based on OWT are proposed. Besides OWT, there are three other novelties in FBBMA, namely fast binary block matching, adaptive central-search-point prediction and center-biased search order, in which significant modifications are contained. Four more existing techniques are employed in FBBMA to further improve performance. Experimental results show the superiorities of all the proposed algorithms and modifications. With similar quality of predicted sequence, the proposed OWT algorithm performs 37 times faster than the filter thresholding method, which gives the best quality among current 1BTs. FBBMA significantly outperforms over several other fast motion estimation algorithms, including the diamond search algorithm that was recently adopted in MPEG-4, in terms of both speed up ratio and quality of predicted sequence. In addition, the output motion vectors of FBBMA need fewer bits to be encoded than most if not all other ME algorithms.