Miracle-dz/UniFAR-FTUs huggingface dataset:
Eden Trace Viewer : A Tool to Visualize Parallel Functional Program Executions

—This paper presents the Eden Trace Viewer (EdenTV), a tool which generates graphic representations of parallel program executions. The tracing tool was conceived to analyze the behavior of programs written in the parallel functional language Eden. With the high abstraction offered by parallel functional languages, tools for the analysis of the runtime behaviour are all the more important. We describe the concepts of Trace Generation , Trace Interpretation and Trace Representation in the EdenTV, giving brief technical details about its implementation. The functionality of the EdenTV is illustrated by two examples, emphasizing the utility of the EdenTV to analyze and improve the performance of parallel programs. An area of future work is to improve and optimize the tool in future versions, as well as to adapt it for other parallel functional languages.
Collusion in the U.S. crop insurance program: applied data mining

This paper quantitatively analyzes indicators of Agent (policy seller), Adjuster (indemnity claim adjuster), Producer (policy purchaser/holder) indemnity behavior suggestive of collusion in the United States Department of Agriculture (USDA) Risk Management Agency (RMA) national crop insurance program. According to guidance from the federal law and using six indicator variables of indemnity behavior, those entities equal to or exceeding 150% of the county mean (computed using a simple jackknife procedure) on all entity-relevant indicators were flagged as "anomalous. " Log linear analysis was used to test (I) hierarchical node-node arrangements and (2) a non-recursive model of node information sharing. Chi-square distributed deviance statistic identified the optimal log linear model. The results of the applied data mining technique used here suggest that the non-recursive triplet and Agent-producer doublet collusion probabilistically accounts for the greatest proportion of waste, fraud, and abuse in the federal crop insurance program. Triplet and Agent-producer doublets need detailed investigation for possible collusion. Hence, this data mining technique provided a high level of confidence when 24 million records were quantitatively analyzed for possible fraud, waste, or other abuse of the crop insurance program administered by the USDA RMA, and suspect entities reported to USDA. This data mining technique can be applied where vast amounts of data are available to detect patterns of collusion or conspiracy as may be of interest to the criminal justice or intelligence agencies.
Industrial Wireless Sensor Networks

The utility model relates to an industrial wireless sensor network, which comprises a gateway device and a plurality of intelligent acquisition terminal devices, wherein the gateway device consists of a gateway module and a backbone router which are connected through a serial port, the backbone router of the gateway device is connected with the intelligent acquisition terminal devices through radio frequency signals, and the gateway equipment sends data information to a user terminal through an Ethernet interface. The industrial wireless sensor network has the characteristics of being low in cost, easy to use, wide in perceive and the like, can stably acquires site information in real time under the situation that wired equipment in an industrial site cannot be installed or a cable is overlong, so that the reliability of the level signal is reduced, and can realize the measurement of certain important industrial process detected online in real time, which can not be realized due to cost or reliability in the traditional practices, the quality of products and industrial environment indexes can be improved, the manual acquisition and wire distribution cost can be saved, and the industrial wireless sensor network is conveniently applied in different industrial environments.
Semantic, Executive, and Visuospatial Abilities in Mathematical Reasoning of Referred College Students

Semantic retrieval (SR) and executive-procedural (EP), but not visuospatial (VS) skills, have been found to be uniquely predictive of mathematical calculation skills in a sample of clinically referred college students. This study set out to cross-validate these results in an independent sample of clinically referred college students (N = 337) as well as extend them by examination of the contributions of these cognitive domains to math reasoning skills. Results indicate that these cognitive domains were able to predict 30% of the variance in calculation skills and 50% of the variance in math reasoning; however, in both cases, only the domains of semantic retrieval and visuospatial skill contributed uniquely. Differences between studies, and the lack of unique contribution of the EP domain to either type of math skill, may be due to measurement and sampling differences, the degree of shared relations among domains, and the choice of measures that represent the EP domain. Implications and future directions are explored.
Blogging developer knowledge: Motivations, challenges, and future directions

Why do software developers place so much effort into writing public blog posts about their knowledge, experiences, and opinions on software development? What are the benefits, problems, and tools needed-what can the research community do to help? In this paper, we describe a research agenda aimed at understanding the motivations and issues of software development blogging. We interviewed developers as well as mined and analyzed their blog posts. For this initial study, we selected developers from various backgrounds: IDE plugin development, mobile development, and web development. We found that developers used blogging for a variety of functions such as documentation, technology discussion, and announcing progress. They were motivated by a variety of reasons such as personal branding, knowledge retention, and feedback. Among the challenges for blog authors identified in our initial study, we found primitive tool support, difficulty recreating and recalling recent development experiences, and management of blog comments. Finally, many developers expressed that the motivations and benefits they received for blogging in public did not directly translate to corporate settings.
Joint Learning of Object and Action Detectors

While most existing approaches for detection in videos focus on objects or human actions separately, we aim at jointly detecting objects performing actions, such as cat eating or dog jumping. We introduce an end-to-end multitask objective that jointly learns object-action relationships. We compare it with different training objectives, validate its effectiveness for detecting objects-actions in videos, and show that both tasks of object and action detection benefit from this joint learning. Moreover, the proposed architecture can be used for zero-shot learning of actions: our multitask objective leverages the commonalities of an action performed by different objects, e.g. dog and cat jumping, enabling to detect actions of an object without training with these object-actions pairs. In experiments on the A2D dataset [50], we obtain state-of-the-art results on segmentation of object-action pairs. We finally apply our multitask architecture to detect visual relationships between objects in images of the VRD dataset [24].
Endocytotic elimination and domain-selective tethering constitute a potential mechanism of protein segregation at the axonal initial segment

The axonal initial segment is a unique subdomain of the neuron that maintains cellular polarization and contributes to electrogenesis. To obtain new insights into the mechanisms that determine protein segregation in this subdomain, we analyzed the trafficking of a reporter protein containing the cytoplasmic II–III linker sequence involved in sodium channel targeting and clustering (Garrido, J.J., P. Giraud, E. Carlier, F. Fernandes, A. Moussif, M.P. Fache, D. Debanne, and B. Dargent. 2003. Science. 300:2091–2094). Here, we show that this reporter protein is preferentially inserted in the somatodendritic domain and is trapped at the axonal initial segment by tethering to the cytoskeleton, before its insertion in the axonal tips. The nontethered population in dendrites, soma, and the distal part of axons is subsequently eliminated by endocytosis. We provide evidence for the involvement of two independent determinants in the II–III linker of sodium channels. These findings indicate that endocytotic elimination and domain-selective tethering constitute a potential mechanism of protein segregation at the axonal initial segment of hippocampal neurons.
Capacity and Stable Throughput Regions for the Broadcast Erasure Channel With Feedback: An Unusual Union

We consider a source node broadcasting to two receivers over a general erasure channel with receiver feedback. We characterize the capacity region of the channel and construct algorithms based on linear network coding (either randomized or depending on channel dynamics) that achieve this capacity. We then consider stochastic arrivals at the source for the two destinations and characterize the stable throughput region achieved by adapting the same algorithms that achieve capacity. Next, we modify these algorithms to improve their delay performance and characterize their stable throughput regions. Although the capacity and stability regions obtained by the algorithms are not always identical (because of the extra overhead needed for the algorithms to handle stochastic traffic), they are within a few bits of each other and have similar forms. This example exhibits an unusual relationship between capacity and stability regions and extends similar prior studies for multiple access channels.
Different models and properties on LMP calculations

This paper introduces the fundamental concept of locational marginal price (LMP) in the electricity markets, and presents some special observations on LMP. Under market environment, LMP based settlement strategy is used to determine the amount of money earned from ISO by the energy sellers and paid to ISO by the energy buyers. Thus, depending on different market designs, four different calculation models and corresponding properties on LMP are discussed in this paper. Some interesting applications of LMP are also presented. In this paper, all studied examples are based on a simple 3-bus network
Mining DNA sequences based on spatially coded technique using spatial light modulator

In this paper, we present an optical computing method for string data alignment applicable to genome information analysis. By applying moire technique to spatial encoding patterns of deoxyribonucleic acid (DNA) sequences, association information of the genome and the expressed phenotypes could more effectively be extracted. Such moire fringes reveal occurrence of matching, deletion and insertion between DNA sequences providing useful visualized information for prediction of gene function and classification of species. Furthermore, by applying a cylindrical lens, a new technique is proposed to map two-dimensional (2D) association information to a one-dimensional (1D) column of pixels, where each pixel in the column is representative of superposition of all bright and dark pixels in the corresponding row. By such a time-consuming preprocessing, local similarities between two intended patterns can readily be found by just using a 1D array of photodetectors and post-processing could be performed on specified parts in the initial 2D pattern. We also evaluate our proposed circular encoding adapted for poor data alignment condition. Our simulation results together with experimental implementation verify the effectiveness of our dynamic proposed methods which significantly improve system parameters such as processing gain and signal to noise ratio (SNR).
Multimodal Neural Network for Overhead Person Re-Identification

Person re-identification is a topic which has potential to be used for applications within forensics, flow analysis and queue monitoring. It is the process of matching persons across two or more camera views, most often by extracting colour and texture based hand-crafted features, to identify similar persons. Because of challenges regarding changes in lighting between views, occlusion or even privacy issues, more focus has turned to overhead and depth based camera solutions. Therefore, we have developed a system, based on a Convolutional Neural Network (CNN) which is trained using both depth and RGB modalities to provide a fused feature. By training on a locally collected dataset, we achieve a rank-1 accuracy of 74.69%, increased by 16.00% compared to using a single modality. Furthermore, tests on two similar publicly available benchmark datasets of TVPR and DPI-T show accuracies of 77.66% and 90.36%, respectively, outperforming state-of-the-art results by 3.60% and 5.20%, respectively.
Parallel soft spherical detection for coded MIMO systems

A sub-optimum a-posteriori probability (APP) detector is proposed for iterative joint detection/decoding in a multiple-input multiple-output (MIMO) wireless communication system employing an outer code. The proposed detector searches inside a given sphere in a parallel manner to simultaneously find a list of m-best points based on an additive metric. The metric is formed by combining the channel output and the a-priori information. The parallel structure of the proposed method is suitable for hardware parallelization. The radius of the sphere and the value of m are selected according to the channel condition to reduce the complexity. Numerical results are provided showing a significant reduction in the average complexity (for a similar performance and peak complexity) as compared to the best earlier known method. The proposed scheme is applied for the decoding of the rate 2, 4 times 2 MIMO code employed in the 802.16e standard
Effect of annealing temperature on dielectric behavior of PVDF thick films

The polyvinylidene fluoride (PVDF) thick film has been fabricated by a solution casting method. The fabricated film is subjected to annealing at 50°C, 90°C, 100°C and 110°C for 5 hours. The effect of annealing on its structure, dielectric and conductivity is investigated. The β-phase PVDF is found to coexist with α-phase for annealing temperature upto 100°C, after that β-phase is converted to α-phase. The dielectric permittivity and tangent loss of film in the frequency range of 103 Hz to 105 Hz annealed at 100°C are 11 and 0.025 respectively. The improved behavior of dielectric and conductivity results from interface and crystal structure modification in the PVDF thick film.The polyvinylidene fluoride (PVDF) thick film has been fabricated by a solution casting method. The fabricated film is subjected to annealing at 50°C, 90°C, 100°C and 110°C for 5 hours. The effect of annealing on its structure, dielectric and conductivity is investigated. The β-phase PVDF is found to coexist with α-phase for annealing temperature upto 100°C, after that β-phase is converted to α-phase. The dielectric permittivity and tangent loss of film in the frequency range of 103 Hz to 105 Hz annealed at 100°C are 11 and 0.025 respectively. The improved behavior of dielectric and conductivity results from interface and crystal structure modification in the PVDF thick film.
Safety and Efficacy of Endoscopic Therapy for Nonmalignant Duodenal Duplication Cysts

AbstractAnalyze efficacy, safety of endoscopic therapy for duodenal duplication cysts (DDC) by comprehensively reviewing case reports.Tandem, independent, systematic, computerized, literature searches were performed via PubMed using medical subject headings or Keywords “cyst” and “duodenal” and “duplication”; or “cyst”, and “endoscopy” or “endoscopic”, and “therapy” or “decompression”; with reconciliation of generated references by two experts. Case report followed CARE guidelines.Literature review revealed 28 cases (mean = 1.3 ± 1.2 cases/report). Endoscopic therapy is increasingly reported recently (1984–1999: 3 cases, 2000–2015: 25 cases, P = 0.003, OR = 8.33, 95%-CI: 1.77–44.5). Fourteen (54%) of 26 patients were men (unknown-sex = 2). Mean age = 32.2 ± 18.3 years old. Procedure indications: acute pancreatitis-16, abdominal pain-8, jaundice-2, gastrointestinal (GI) obstruction-1, asymptomatic cyst-1. Mean maximal DDC dimension = 3.20 ± 1.53 cm (range, 1–6.5 cm). Endoscopic techniques included cyst puncture via needle knife papillotomy (NKP)/papillotome-18, snare resection of cyst-7, cystotome-2, and cyst needle aspiration/ligation-1. Endoscopic therapy was successful in all cases. Among 24 initially symptomatic patients, all remained asymptomatic post-therapy without relapses (mean follow-up = 36.5 ± 48.6 months, 3 others reported asymptomatic at follow-up of unknown duration; 1 initially asymptomatic patient remained asymptomatic 3 years post-therapy). Two complications occurred: mild intraprocedural duodenal bleeding related to NKP and treated locally endoscopically.A patient is reported who presented with vomiting, 15-kg-weight-loss, and profound dehydration for 1 month from extrinsic compression of duodenum by 14 × 6 cm DDC, underwent successful endosonographic cyst decompression with large fenestration of cyst and endoscopic aspiration of 1 L of fluid from cyst with rapid relief of symptoms. At endoscopy the DDC was intubated and visualized and random endoscopic mucosal biopsies were obtained to help exclude malignant or dysplastic DDC.Study limitations include retrospective literature review, potential reporting bias, limited patient number, variable follow-up.In conclusion, endoscopic therapy for DDC was efficacious in all 29 reported patients including current case, including patients presenting acutely with acute pancreatitis, or GI obstruction. Complications were rare and minor, suggesting that endoscopic therapy may be a useful alternative to surgery for nonmalignant DDC when performed by expert endoscopists.
Imaging Factors that Distinguish Between Patients with Asymptomatic and Symptomatic Cervical Spondylotic Myelopathy with Mild to Moderate Cervical Spinal Cord Compression

Background Not all patients with spinal cord compression due to cervical spondylotic myelopathy (CSM) have clinical symptoms and signs. The aim of this study was to investigate and compare the imaging findings in asymptomatic and symptomatic patients with CSM with mild to moderate cervical spinal cord compression. Material/Methods A retrospective clinical study included 68 patients. Group A (n=30) had no symptoms and signs; group B (n=38) had symptoms and signs of cervical myelopathy. The age, sex, body mass index (BMI), history of steroid treatment, duration of symptoms, number of spondylotic cervical segments, Torg ratio, range of motion (ROM), incidence of cervical segmental instability, overall curvature of the cervical spine, direction of spinal cord compression, and spinal cord magnetic resonance imaging (MRI) signal intensity were compared. Results For groups A and B, the Torg ratio was 90.3% and 83.6% (P<0.05), the incidence of cervical segmental instability was 23.3% and 65.8% (P<0.05), and the incidence of a spinal cord high intensity signal was 13.3% and 86.9% (P<0.05). Logistic regression analysis showed myelopathy as a dependent variable, independently associated with cervical segmental instability (OR=5.898, P=0.037), an MRI T2-weighted intramedullary high signal (OR=9.718, P=0.002), and Torg ratio (OR=0.155, P=0.006). Conclusions Cervical segmental instability, a high intramedullary signal on T2-weighted MRI, and the Torg ratio had the greatest capacity to distinguish between asymptomatic and symptomatic patients with CSM with mild to moderate cervical spinal cord compression.
IEEE Transactions on Pattern Analysis and Machine Intelligence Coding , Analysis , Interpretation , and Recognition of Facial Expressions

We describe a computer vision system for observing facial motion by using an optimal estimation optical flow method coupled with a geometric and a physical (muscle) model describing the facial structure. Our method produces a reliable parametric representation of the face’s independent muscle action groups, as well as an accurate estimate of facial motion. Previous efforts at analysis of facial expression have been based on the Facial Action Coding System (FACS), a representation developed in order to allow human psychologists to code expression from static pictures. To avoid use of this heuristic coding scheme, we have used our computer vision system to probabilistically characterize facial motion and muscle activation in an experimental population, thus deriving a new, more accurate representation of human facial expressions that we call FACS+. We use this new representation for recognition in two different ways. The first method uses the physics-based model directly, by recognizing expressions through comparison of estimated muscle activations. The second method uses the physics-based model to generate spatio-temporal motionenergy templates of the whole face for each different expression. These simple, biologically-plausible motion energy “templates” are then used for recognition. Both methods show substantially greater accuracy at expression recognition than has been previously achieved. Categories: Facial Expressions, Expression Recognition, Face Processing, Facial Analysis, Motion and Pattern Analysis, Vision-based HCI.
RapidProM: Mine Your Processes and Not Just Your Data

The number of events recorded for operational processes is growing every year. This applies to all domains: from health care and e-government to production and maintenance. Event data are a valuable source of information for organizations that need to meet requirements related to compliance, efficiency, and customer service. Process mining helps to turn these data into real value: by discovering the real processes, by automatically identifying bottlenecks, by analyzing deviations and sources of non-compliance, by revealing the actual behavior of people, etc. Process mining is very different from conventional data mining and machine learning techniques. ProM is a powerful open-source process mining tool supporting hundreds of analysis techniques. However, ProM does not support analysis based on scientific workflows. RapidProM, an extension of RapidMiner based on ProM, combines the best of both worlds. Complex process mining workflows can be modeled and executed easily and subsequently reused for other data sets. Moreover, using RapidProM, one can benefit from combinations of process mining with other types of analysis available through the RapidMiner marketplace.