Miracle-dz/UniFAR-FTUs huggingface dataset:
Guest Editors' Introduction: Special Section on Learning Deep Architectures

There has been a resurgence of research in the design of deep architecture models and learning algorithms, i.e., methods that rely on the extraction of a multilayer representation of the data. Often referred to as deep learning, this topic of research has been building on and contributing to many different research topics, such as neural networks, graphical models, feature learning, unsupervised learning, optimization, pattern recognition, and signal processing. Deep learning is also motivated and inspired by neuroscience and has had a tremendous impact on various applications such as computer vision, speech recognition, and natural language processing. The clearly multidisciplinary nature of deep learning led to a call for papers for a special issue dedicated to learning deep architectures.
Scutellaria baicalensis Alleviates Cantharidin-Induced Rat Hemorrhagic Cystitis through Inhibition of Cyclooxygenase-2 Overexpression

Cantharidin, an active component in mylabris, is used in traditional Chinese medicine (TCM) to treat scabies and hepatoma, but accompanied by hemorrhagic cystitis. Evidence shows that cantharidin induces human bladder carcinoma cell death through COX-2 overexpression in vitro. In TCM, Scutellaria baicalensis is usually used to cure mylabris-induced hematuria. This work was undertaken to determine the mechanisms of cantharidin-induced rat hemorrhagic cystitis and explore the uroprotective effect of S. baicalensis. In vitro results showed cantharidin could induce cytotoxicity through prostaglandin (PG)E2 overproduction of T24 cells. Boiling-water extract of S. baicalensis (SB-WE) could significantly inhibit PGE2 production and COX-2 expression in lipo-polysaccharide-induced RAW 264.7 cells, indicating obvious anti-inflammatory abilities. In vivo results indicated that cantharidin caused rat hemorrhagic cystitis with hematuria via c-Fos and COX-2 overexpression. SB-WE was given orally to cantharidin-treated rats, whereby hematuria level, elevated PGE2 and COX-2 protein overexpression were significantly and dose-dependently inhibited by SB-WE. The anti-inflammatory components of SB-WE are baicalin and wogonin, whose contents were 200.95 ± 2.00 and 31.93 ± 0.26 μg/mg, respectively. In conclusion, cantharidin induces rat cystitis through c-Fos and COX-2 over-expression and S. baicalensis can prevent the resulting hematuria because of its anti-inflammatory effects.
IMU-Aided Dual-Frequency RFID Based Localization in LOS/NLOS Hybrid Environment

The mitigation of NLOS (non-line-of-sight) propagation conditions is one of main challenges in wireless signals based indoor localization. When RFID localization technology is applied in applications, RSS fluctuates frequently due to the shade and multipath effect of RF signal, which could result in localization inaccuracy. In particularly, when tags carriers are walking in LOS (line-of-sight) and NLOS hybrid environment, great attenuation of RSS will happen, which would result in great location deviation. The paper proposes an IMU-assisted (Inertial Measurement Unit) RFID based indoor localization in LOS/NLOS hybrid environment. The proposed method includes three improvements over previous RSS based positioning methods: IMU aided RSS filtering, IMU aided LOS/NLOS distinguishing and IMU aided LOS/NLOS environment switching. Also, CRLB (Cramér-Rao Low Bound) is calculated to prove theoretically that indoor positioning accuracy for proposed method in LOS/NLOS mixed environment is higher than position precision of only use RSS information. Simulation and experiments are conducted to show that proposed method can reduce the mean positioning error to around 3 meters without site survey.
Interface Stability Behaviors of Methanol-Melamine-Formaldehyde Shell MicroPCMs/Epoxy Matrix Composites

Microcapsules containing phase change materials (microPCMs) have been widely applied in smart temperature-controlling materials. Interface stability plays a key role in these microPCMs/matrix composites. The aim of this study was to investigate the interface stability behaviors of methanol-melamine-formaldehyde (MMF) shell microPCMs containing paraffin/epoxy matrix composites. MMF prepolymer can be applied to fabricated microcapsules with smooth shells. The average diameter of the microPCMs could be controlled in the range of 5–45 μm by stirring speed of 500–6,000 r min−1. From the SEM morphologies of the interphase between the microPCMs and the epoxy-matrix, it is concluded that the interaction may be enhanced by MMF graft structure due to the increasing of molecular interaction in the interface. During a repeated heat-transmission process, not only the repeated-times of thermal absorbing-releasing process will damage the interface bonding, but also higher thermal conductive speed will make the interface bearing more debonding stress. Large microPCMs in matrix may supply better interface stability. Moreover, the numerical and experimental results are consistent to obtain a clear insight into the rule of interface debonding for microPCMs/matrix composites that the interface perfection can be enhanced by increasing the thickness of interphase. POLYM. COMPOS. , 2011. © 2011 Society of Plastics Engineers
A privacy-preserving authentication protocol for smart tags

RFID system has become a technology that many companies would like to adopt as it provides convenience to our society. Increasing competitiveness in the industry has reduced the cost of the technology, but it also raises considerable privacy concerns. Among many RFID applications that have made major impacts on various industries, the RFID-based authentication system has become a solution to resolve a number of issues, for instances, theft, compromised brand, lack of inventory control, supply chain inefficiencies, and etc. Many authentication protocols based on symmetric challenge-response scheme have been developed in order to ensure preservation of privacy. However, many of the these schemes cannot fully protect privacy in the presence of malicious readers or insider attacks. In this thesis, we first investigated possible security and privacy threats that security engineers face from an RFID system. We then presented a new protocol to authenticate smart tags without exposing their private identities and activity patterns with resource-limited devices, such as RFID smart tags or wireless sensor nodes. We further analyzed the RFID system’s security strength against various attacking scenarios, such as eavesdropping, collusive attack or tag-compromise situation, based on extensive experiments to validate the feasibility and security of our proposed solution.
An Overview of Models for Business Process Analysis -- Beyond Performance Measurement with KPIs

Almost all of today's performance measurement systems (PMS) rely on the usage of numeric indicators to quantify success or failure, normally referred to as key performance indicators (KPIs). This restriction makes it difficult to describe hard-measurable or business processes that are rather qualitative in nature. So, other existing models for process analysis containing convenient solutions and indicators have to be assessed and validated in order to offer them to stakeholders to thoroughly assess business processes. In this article, various existing models and frameworks for performance measurement were reviewed in an empirical investigation, categorized in systems and put into context to relevant theories. The result of the research is an overview of models for business process analysis that also incorporates indirect process performance aspects like soft goals, complexity, maturity or dependencies.
On the Efficient Representation and Execution of Deep Acoustic Models

In this paper we present a simple and computationally efficient quantization scheme that enables us to reduce the resolution of the parameters of a neural network from 32-bit floating point values to 8-bit integer values. The proposed quantization scheme leads to significant memory savings and enables the use of optimized hardware instructions for integer arithmetic, thus significantly reducing the cost of inference. Finally, we propose a "quantization aware" training process that applies the proposed scheme during network training and find that it allows us to recover most of the loss in accuracy introduced by quantization. We validate the proposed techniques by applying them to a long short-term memory-based acoustic model on an open-ended large vocabulary speech recognition task.
Cognitive cooperative communications on the Multiple Access Channel

In this paper, we investigate a three-user cognitive communication network where a primary two-user Multiple Access Channel (MAC) suffers interference from a secondary point-to-point (P2P) channel, sharing the same medium. While the P2P channel transmitter - transmitter 3 - causes an interference at the primary MAC receiver, we assume that the primary channel transmitters - transmitters 1 and 2 - do not cause any interference at the P2P receiver. It is assumed that one of the MAC transmitters has cognitive capabilities and cribs causally from the other MAC transmitter. Furthermore, we assume that the cognitive transmitter knows the message of transmitter 3 in a noncausal manner, thus introducing the three-user Multiple Access Cognitive Z-Interference Channel (MA-CZIC). We obtain inner and outer bounds on the capacity region of the three-user MA-CZIC for both strictly and nonstrictly causal cribbing cognitive encoders.
A secure authentication watermarking for halftone and binary images

An authentication watermark is a hidden data inserted into an image that can be used to detect any accidental or malicious alteration in the image. Many authentication‐watermarking techniques for continuous‐tone images are described in the literature, but only a quite small number of secure authentication watermarking techniques are available for binary/halftone images. This article proposes a simple solution for inserting a secure authentication watermark in binary/halftone images. It consists of choosing a set of pseudo‐random pixels in the image, clearing them, computing the message authentication code (or the digital signature) of the now‐cleared image, and inserting the resulting code into the selected random pixels. Dispersed‐dot halftone images watermarked by the proposed technique present better visual quality than do watermarked generic binary images. However, in practice, the visual degradation is hardly noticeable in either case. The proposed technique seems to be the only binary/halftone watermarking scheme that can detect even a single pixel alteration in the host image. It can be used with secret‐key or public‐key ciphers. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 147–152, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20018
Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.
Multimodal monitoring of cultural heritage sites and the FIRESENSE project

The FIRESENSE FP7 project aims to implement an automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire and extreme weather conditions. This challenging task requires the operation of a multimodal wireless sensor network, the setting up of an infrastructure to publish and access sensor data and the fusion of multiple modalities in a real-time fashion. This paper discusses the multimodal sensor data access and fusion aspects of the project.
Surface Enhanced Raman Scattering (SERS) Detection of Ammonium Nitrate (AN) Samples Fabricated Using Drop-on-Demand Inkjet Technology on Commercial and Fabricated SERS Substrates

Abstract : The U.S. Army and first responder community are increasingly focusing efforts on energetic materials detection and identification. Main hazards encountered in theater include homemade explosives (HMEs) and improvised explosive devices (IEDs), in part fabricated from simple components like ammonium nitrate (AN). In order to accurately detect and identify these unknowns (energetic or benign), fielded detection systems must be accurately trained using well-understood universal testing substrates. These training substrates must contain target species at known concentrations and recognized polymorphic phases. AN is an explosive precursor material that demonstrates several different polymorphic phases depending on how the material is deposited onto testing substrates. In this report, known concentrations of AN were uniformly deposited onto commercially available surface enhanced Raman scattering (SERS) substrates using a drop-on-demand inkjet printing system. The phase changes observed after the deposition of AN under several solvent conditions are investigated. Characteristics of the collected SERS spectra of AN are discussed and it is demonstrated that an understanding of the exact nature of the AN samples deposited results in an increased ability to accurately and reliably train hazard detection systems.
A novel algorithm for global peak power point tracking in partially shaded grid-connected PV system

Photovoltaic (PV) cell characteristics are highly nonlinear that are affected by varying insolation and temperature condition. In case of uniform insolation condition, the P-V curve shows single maximum power point (MPP), but under partially shaded conditions, the P-V characteristic shows multiple peaks. Therefore, the maximum power point tracking (MPPT) algorithm should determine the global peak power point avoiding the PV system getting trapped in local peak that gives considerable power loss. This paper proposes a novel fuzzy logic based tracking algorithm to determine global peak point in grid connected PV system under partially shaded condition. The proposed algorithm can track the maximum power point under normal as well as partial shading condition. The algorithm gives fast convergence and very low oscillation around the MPP with less complexity. The simulation results validate the performance and stability of the grid connected PV system using the proposed algorithm.
Software Analytics to Software Practice: A Systematic Literature Review

Software Analytics (SA) is a new branch of big data analytics that has recently emerged (2011). What distinguishes SA from direct software analysis is that it links data mined from many different software artifacts to obtain valuable insights. These insights are useful for the decision-making process throughout the different phases of the software lifecycle. Since SA is currently a hot and promising topic, we have conducted a systematic literature review, presented in this paper, to identify gaps in knowledge and open research areas in SA. Because many researchers are still confused about the true potential of SA, we had to filter out available research papers to obtain the most SA-relevant work for our review. This filtration yielded 19 studies out of 135. We have based our systematic review on four main factors: which software practitioners SA targets, which domains are covered by SA, which artifacts are extracted by SA, and whether these artifacts are linked or not. The results of our review have shown that much of the available SA research only serves the needs of developers. Also, much of the available research uses only one artifact which, in turn, means fewer links between artifacts and fewer insights. This shows that the available SA research work is still embryonic leaving plenty of room for future research in the SA field.
A spatial constrained K-means approach to image segmentation

General purposed color image segmentation is a challenging and important issue in image processing related applications. However, few systems successfully handle this issue for a broad diversity of images. In this paper, we are seeking a practical and generic solution to image segmentation. As a fast segmentation process, K-means based clustering is employed in feature space first. Then, in image plane, the spatial constraints are adopted into the hierarchical K-means clusters on each level. The two processes are carried out alternatively and iteratively. Also, an effective region merging method is proposed to handle the over segmentation. Extensive experiments show the proposed approach is fast and generic, thus practical in applications.
Development of an evidence-based complex intervention for community rehabilitation of patients with hip fracture using realist review, survey and focus groups

Objectives To develop an evidence and theory-based complex intervention for improving outcomes in elderly patients following hip fracture. Design Complex-intervention development (Medical Research Council (MRC) framework phase I) using realist literature review, surveys and focus groups of patients and rehabilitation teams. Setting North Wales. Participants Surveys of therapy managers (n=13), community and hospital-based physiotherapists (n=129) and occupational therapists (n=68) throughout the UK. Focus groups with patients (n=13), their carers (n=4) and members of the multidisciplinary rehabilitation teams in North Wales (n=13). Results The realist review provided understanding of how rehabilitation interventions work in the real-world context and three programme theories were developed: improving patient engagement by tailoring the intervention to individual needs; reducing fear of falling and improving self-efficacy to exercise and perform activities of daily living; and coordination of rehabilitation delivery. The survey provided context about usual rehabilitation practice; focus groups provided data on the experience, acceptability and feasibility of rehabilitation interventions. An intervention to enhance usual rehabilitation was developed to target these theory areas comprising: a physical component consisting of six additional therapy sessions; and a psychological component consisting of a workbook to enhance self-efficacy and a patient-held goal-setting diary for self-monitoring. Conclusions A realist approach may have advantages in the development of evidence-based interventions and can be used in conjunction with other established methods to contribute to the development of potentially more effective interventions. A rehabilitation intervention was developed which can be tested in a future randomised controlled trial (MRC framework phases II and III). Trial registration number ISRCTN22464643, Pre-results.
Simultaneous Estimation of Multiple Land-Surface Parameters From VIIRS Optical-Thermal Data

Traditional methods for estimating land-surface parameters from remotely sensed data generally focus on a single parameter with a specific spectral region, resulting in physical and spatiotemporal inconsistencies in current satellite products. We recently proposed a unified inversion scheme to estimate a suite of parameters simultaneously from both visible and near-infrared and thermal-infrared MODIS data. In this letter, we implemented this scheme to estimate six time-series parameters [leaf area index, fraction of absorbed photosynthetically active radiation, surface albedo, land-surface emissivity, land-surface temperature (LST), and upwelling longwave radiation (LWUP)] from the Visible Infrared Imaging Radiometer Suite (VIIRS) data. Several components of these schemes are refined, including the incorporation of a snow bidirectional reflectance distribution function model, determination of the best band combination, and better estimation of the snow-covered surface emissivity by accounting for the snow-cover fraction. Validation using the measurements at 12 sites of SURFRAD, CarboEuropeIP, and FLUXNET, and intercomparisons with MODIS and Global Land-Surface Satellite products, are carried out: the retrieved albedo, LST, and LWUP achieved accuracies ( $R^{2}$ ) of 0.77, 0.96, and 0.95, root mean square errors of 0.06, 2.9 K, and 18.3 W/m2, and biases of 0.01, 0.09 K, and −0.08 W/m2, respectively. The retrieved parameters can achieve comparable or higher accuracy than existing products, which indicates that the unified algorithm can be applied effectively to the VIIRS data with high physical and temporal consistency and accuracy.
Nomadic radio: scaleable and contextual notification for wearable audio messaging

Mobile workers need seamless access to communication andinformation services on portable devices. However current solutionsoverwhelm users with intrusive and ambiguous notifications. In thispaper, we describe scaleable auditory techniques and a contextualnotification model for providing timely information, whileminimizing interruptions. Users actions influence local adaptationin the model. These techniques are demonstrated in Nomadic Radio,an audio-only wearable computing platform.
"Let me convince you to buy my product ... ": A Case Study of an Automated Persuasive System for Fashion Products

Persuasivenes is a creative art aimed at making people believe in certain set of beliefs. Many a times, such creativity is about adapting richness of one domain into another to strike a chord with the target audience. In this research, we present PersuAIDE! - A persuasive system based on linguistic creativity to transform given sentence to generate various forms of persuading sentences. These various forms cover multiple focus of persuasion such as memorability and sentiment. For a given simple product line, the algorithm is composed of several steps including: (i) select an appropriate well-known expression for the target domain to add memorability, (ii) identify keywords and entities in the given sentence and expression and transform it to produce creative persuading sentence, and (iii) adding positive or negative sentiment for further persuasion. The persuasive conversion were manually verified using qualitative results and the effectiveness of the proposed approach is empirically discussed.
Strict modules and homotopy modules in stable homotopy

Let R be any associative ring with unit and let HR denote the corresponding Eilenberg–Mac Lane spectrum. We show that the category of algebras over the monad X 7→ HR∧X on the homotopy category of spectra is equivalent to the homotopy category associated to a model category of HR-module spectra, if the ring R is a field or a subring of the rationals, but not for all rings.