Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel robust digital image watermarking algorithm based on two-level DCT

In this paper, we propose a novel blind digital image watermarking algorithm which is resilient to many kinds of image processing attacks and geometric distortions. To embed the watermark, we first map the original watermark to another spread one aiming to fit for the image size and then embed it into the image two-level DCT coefficients we selected using a specified rule. We extract the watermark using two-level DCT accordingly with the help of the correlation scheme. Comparing with other achievements, our proposed schemes, including spread spectrum watermark generation, block-number-fixed image segmentation, two-level DCT and the feature vector extraction rule, play an important role in improving the watermark robustness. Experimental results demonstrate that our method can not only resist common image processing attacks, but also geometric distortions, such as scaling, aspect ratio changing, flip, rotation, and some kinds of combined transforms.
Metabotropic glutamate receptor modulation of voltage-gated Ca2+ channels involves multiple receptor subtypes in cortical neurons

Metabotropic glutamate receptor (mGluR) modulation of voltage-gated Ca2+ channels was examined in isolated deep layer frontoparietal cortical neurons under conditions designed to isolate calcium- independent modulatory pathways. Trans-1-aminocyclopentane-1,3- dicarboxylate (t-ACPD), a nonspecific mGluR agonist, produced rapid and reversible inhibition of Ca2+ channels. This effect was mimicked by agonists for group I and group II, but not group III, mGluRs. Effects of group I and II agonists often were observed in the same neurons, but separate subgroups of neurons were unresponsive to the group I agonist quisqualate or the group II agonist 2-(2,3-dicarboxycyclopropyl) glycine (DCG-IV). Inhibition by quisqualate and DCG-IV was nonocclusive in neurons responding to both agonists. These agonists thus appear to act on different mGluRs. The mGluR antagonist alpha-methyl-4- carboxylphenylglycine attenuated inhibition by t-ACPD, quisqualate, and DCG-IV. Inhibition by quisqualate and DCG-IV was voltage-dependent. Although the effects of both agonists were greatly reduced by N- ethylmaleimide (NEM), inhibition by DCG-IV was more sensitive to NEM than inhibition by quisqualate. t-ACPD-induced inhibition was reduced by omega-conotoxin GVIA (omega-CgTx) and omega-agatoxin IVA (omega- AgTx) but was affected little by nifedipine. Inhibition by DCG-IV and quisqualate also was reduced by omega-CgTx. We conclude that multiple mGluR subtypes inhibit Ca2+ channels in cortical neurons and that N- and possibly P-type channels are inhibited. Modulation is via a rapid- onset, voltage-dependent mechanism that likely involves a pertussis toxin (PTX)-sensitive G-protein. Type I mGluRs may work via additional PTX-insensitive pathways.
ANALISIS MODEL DAN MEDIA PEMBELAJARAN YANG DIGUNAKAN OLEH GURU PADA MATA PELAJARAN EKONOMI DI SMA SE-KECAMATAN INDERALAYA

Abstract : This research wants to describe the learning models and media applied by teachers teaching the E conomic s subject at SMA in the sub-districts of Indralaya and 4 teachers teaching the Economics subject asked as the samples. The data collection in this study is done by us ing the technique of documentation, observation, and interviews but the analysis techniques is done descriptively. The results showed that the teachers us e the direct instructional model, discussion learning models , and cooperative learning model, while the instructional media used is a visual medium, such as original drawings, concept maps made from cardboard, and use of a whiteboard as a learning medium. The learning plan created and used by teachers has been excellent with a n average score of 75%, the ability of teachers in implement ing the learning process , the learning evaluation model , and the use of instructional media is categorized into good grade of average score reached 78.2%. Abstrak: Penelitian ini bertujuan untuk mendeskripsikan model dan media pembelajaran yang digunakan oleh guru pada mata pelajaran ekonomi di SMA se- Kecamatan Indralaya. Sampel berjumlah 4 orang guru mata pelajaran ekonomi, pengumpulan data dalam penelitian ini menggunakan teknik dokumentasi, observasi, dan wawancara. Sedangkan teknik analisa dianalisis secara deskriptif. Hasil penelitian menunjukkan bahwa guru menggunakan model pembelajaran langsung, model pembelajaran diskusi dan model pembelajaran kooperatif, sedangkan media pembelajaran yang digunakan adalah media visual, seperti gambar asli, peta konsep terbuat dari karton, dan pemanfaatan papan tulis sebagai media pembelajaran. Perencanaan pembelajaran yang dibuat dan digunakan oleh guru telah baik dengan skor rerata 75%, kemampuan guru dalam melaksanakan proses pembelajaran dan evaluasi pembelajaran menggunakan model dan media pembelajaran termasuk katogori baik dengan skor rerata yaitu 78,2%.
Effects of Casing on Full Waveform Acoustic Logs

A general expression is derived for the dispersion relations and the impulse response of a radially layered borehole. The. model geometry consists of a central fluid cylinder surrounded by an arbitrary number of solid annUli. A Thomson-Haskell type propagator matrix is used to relate stresses and displacements across the layers. Although the model is completely general, the geometries considered here are restricted to those of a cased hole. Layers of steel, cement, and an infinite, outermost layer of a formation surround the fluid layer. Synthetic seismograms containing all body and interface waves are calculated for a variety of model parameters. Formation body wave arrivals are relatively unaffected by the presence of a casing. They may, however, be hard to identify if the cement velocities are close to or larger than those of the formation. The Stoneley and pseudo-Rayleigh wave arrivals are predominantly intJ.uenced by the casing parameters. They respond to the combined effects of the steel, the cement, and the formation.
Understanding Distributed Communication : Visualising Action , Awareness and Intent in a Network Environment

Complex communication networks have become a common facet of military, and civilian, operations in the past century. However, much of the cognitive impact of these complex networks is yet to be understood. We have endeavoured to create an effective analogue for an operational network using the Battleships scenario. From this experiment we have extracted several common features impacting shared situational awareness and operational intent. We have also created a prototype intent tracking software, in order to visually monitor the flow of concepts and ideas throughout the network.
Neurovascular and Neurometabolic Couplings in Dynamic Calibrated fMRI: Transient Oxidative Neuroenergetics for Block-Design and Event-Related Paradigms

Functional magnetic resonance imaging (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping brain activity. Interest in quantitative fMRI has renewed awareness in importance of oxidative neuroenergetics, as reflected by cerebral metabolic rate of oxygen consumption(CMRO2), for supporting brain function. Relationships between BOLD signal and the underlying neurophysiological parameters have been elucidated to allow determination of dynamic changes inCMRO2 by “calibrated fMRI,” which require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and volume (CBV). But how doCMRO2 changes, steady-state or transient, derived from calibrated fMRI compare with neural activity recordings of local field potential (LFP) and/or multi-unit activity (MUA)? Here we discuss recent findings primarily from animal studies which allow high magnetic fields studies for superior BOLD sensitivity as well as multi-modal CBV and CBF measurements in conjunction with LFP and MUA recordings from activated sites. A key observation is that while relationships between neural activity and sensory stimulus features range from linear to non-linear, associations between hyperemic components (BOLD, CBF, CBV) and neural activity (LFP, MUA) are almost always linear. More importantly, the results demonstrate good agreement between the changes inCMRO2 and independent measures of LFP or MUA. The tight neurovascular and neurometabolic couplings, observed from steady-state conditions to events separated by <200 ms, suggest rapid oxygen equilibration between blood and tissue pools and thus calibrated fMRI at high magnetic fields can provide high spatiotemporal mapping ofCMRO2 changes.
Towards constraint-based type inference with polymorphic recursion for functional and logic languages

Type inference in the context of polymorphic recursion is notoriously difficult. The extensions to the traditional λ-calculus type inference algorithm by both Hindley-Milner and Mycroft are not capable of deriving the most general, i.e. principal types for programs with polymorphic recursion. Henglein has proposed a different algorithm, based on arrow graph reweriting, with an extended occurs check that allows for practical principal type inference in a large class of programs. We propose a new constraint-based formulation of Henglein’s inference algorithm. Our formulation of the algorithm is simple, elegant and highly declarative in nature. It relates the opertional nature of the type inference more clearly to the formal theory of the type constraints and reveals how to extend the algorithm for logic programs.
Determination of the Far-Infrared Cosmic Background Using COBE DIRBE and WHAM Data

Determination of the cosmic infrared background (CIB) at far-infrared wavelengths using COBE DIRBE data is limited by the accuracy to which foreground interplanetary and Galactic dust emission can be modeled and subtracted. Most previous determinations of the far-infrared CIB were based on the detection of residual isotropic emission in sky maps from which the emission from interplanetary dust and the neutral interstellar medium were removed. In this paper we use the Wisconsin Hα Mapper (WHAM) Northern Sky Survey as a tracer of the ionized medium to examine the effect of this foreground component on determination of the CIB. We decompose DIRBE far-infrared data for five high Galactic latitude regions into H I- and Hα-correlated components and a residual component. We find the Hα-correlated component to be consistent with zero for each region, yielding CIB results that are essentially the same as those previously derived by the COBE DIRBE team: νIν(nW m-2 sr-1) < 75, <32, =25 ± 8, and =13 ± 3 at 60, 100, 140, and 240 μm, respectively (upper limits are 2 σ). For comparison, the estimated integrated light from galaxies based on Spitzer 160 μm source counts is 13.7 ± 1.7 and 10.7 ± 1.4 nW m-2 sr-1 at 140 and 240 μm, respectively. We derive upper limits on the 100 μm emissivity of the ionized medium that are typically about 40% of the 100 μm emissivity of the neutral atomic medium. If Hα is not a reliable tracer of far-infrared emission, we show that our analysis would underestimate the emissivity of the ionized medium and could slightly overestimate the CIB.
Feature Generation for Robust Semantic Role Labeling

Hand-engineered feature sets are a well understood method for creating robust NLP models, but they require a lot of expertise and effort to create. In this work we describe how to automatically generate rich feature sets from simple units called featlets, requiring less engineering. Using information gain to guide the generation process, we train models which rival the state of the art on two standard Semantic Role Labeling datasets with almost no task or linguistic insight.
A Connectionist Control Component for the Theorem Prover SETHEO

Today, the power of automated theorem provers is yet too weak for proving many challinging problems. However heuristics for guiding the proof search can dramatically improve the power of such provers. Since it is very diicult to develop heuristics by hand and since they have to be developed speciically for each problem domain (theory), we decided to derive heuristics automatically using machine learning techniques. Especially neural networks seem to be very suitable for the representation of heuristics because of their ability to deal with incomplete and inconsistent knowledge. In the following paper we describe our experiences with a connectionist control component for the theorem prover SETHEO. As SETHEO is very closely related to the programming language Prolog, our work might be of interest for a greater public than just the theorem proving community.
TRAIL: Topology Authentication in RPL

The IPv6 Routing Protocol for Low-Power and Lossy Networks was recently introduced as the new routing standard for the Internet of Things. Although RPL defines basic security modes, it remains vulnerable to topological attacks which facilitate blackholing, interception, and resource exhaustion. We are concerned with analyzing the corresponding threats and protecting future RPL deployments from such attacks. Our contributions are twofold. First, we analyze the state of the art, in particular the protective scheme VeRA and present two new rank order attacks as well as extensions to mitigate them. Second, we derive and evaluate TRAIL, a generic scheme for topology authentication in RPL. TRAIL solely relies on the basic assumptions of RPL that (1) the root node serves as a trust anchor and (2) each node interconnects to the root in a straight hierarchy. Using proper reachability tests, TRAIL scalably and reliably identifies any topological attacker without strong cryptographic efforts.
Relief analysis and extraction

We present an approach for extracting reliefs and details from relief surfaces. We consider a relief surface as a surface composed of two components: a base surface and a height function which is defined over this base. However, since the base surface is unknown, the decoupling of these components is a challenge. We show how to estimate a robust height function over the base, without explicitly extracting the base surface. This height function is utilized to separate the relief from the base. Several applications benefiting from this extraction are demonstrated, including relief segmentation, detail exaggeration and dampening, copying of details from one object to another, and curve drawing on meshes.
Fast simulation of LDPC codes over additive non-Gaussian noise channel

This paper shows a fast simulation method of low-density parity-check (LDPC) codes over an additive non-Gaussian noise channel. The evaluation of an error performance of LDPC codes is usually executed by using a Monte-Carlo simulation since the theoretical calculation method has not been reported. It is very difficult to evaluate an error performance of LDPC codes with finite block length when the error probability is very low. To solve this problem, some fast simulation methods by using importance sampling (IS) are proposed. However, the conventional methods can not reduce the simulation time of LDPC codes over an additive non-Gaussian noise channel because the simulation probability density function (PDF) used in IS is designed for an additive white Gaussian noise. We propose a new simulation PDF design related to the Chernoff bound to estimate an error performance of LDPC codes over an additive non-Gaussian noise channel. In addition, we show some numerical examples to demonstrate the effectiveness of the proposed simulation method. The simulation time of the proposed method is reduced to about 1/2000 of that of the conventional method when we estimate the frame error rate of 10−10.
A reputation-aware decision-making approach for improving the efficiency of crowdsourcing systems

A crowdsourcing system is a useful platform for utilizing the intelligence and skills of the mass. Nevertheless, like any open system that involves the exchange of things of value, selfish and malicious behaviors exist in crowdsourcing systems and need to be mitigated. Trust management has been proven to be a viable solution in many systems. However, a major difference between crowdsourcing systems and existing trust models designed for multi-agent systems is that human trustees have limited task processing capacity per unit time compared to an intelligent agent program. This paper recognizes a problem in current trust-aware decision-making methods for task assignment in crowdsourcing platforms. On the one hand, trust-based methods over-assign tasks to trusted workers, while on the other hand, workload-based solutions do not give sufficient guarantees on the quality of work. The proposed solution, the social welfare optimizing reputation-aware decision-making (SWORD) approach, strikes a balance between the two and is shown through extensive simulations to significantly improve social welfare of crowdsourcing platforms compared to related work.
Trust Formation Based on Subjective Logic and PGP Web-of-Trust for Information Sharing in Mobile Ad Hoc Networks

Trust play important roles in Mobile ad hoc networks since nodes may randomly joined and leave the network at their own pace. In catastrophe like massive accident or earthquake, groups of rescue personnel form a temporary network structure at the rescue site using their portable devices for coordinating the rescue relief. These groups of user from different agency need to use the temporary network for communication and also for sharing the information. Trust plays important roles in these groups since sharing of information must be among trusted and authorized nodes only. In this paper we form trust model adopting the PGP web-of-trust concept with subjective logic. The PGP web-of-trust is suitable method to adopt in mobile ad hoc networks since nodes are communicating based on peer to peer, hence peer recommendation can be use to create trust between peers. The use of subjective logic operators for calculating trust in the proposed trust model is appropriate since there is an element such as uncertainty as part of calculation. Uncertainty is important in this dynamic network since we do not have full information when decision is make. The trust value later is mapped with the access control policy to determine user access privileges.
Data quality in context

ATA-QUALITY (DQ) PROBLEMS ARE INCREASINGLY EVIdent, particularly in organizational databases. Indeed, 50% to 80% of computerized criminal records in the U.S. were found to be inaccurate, incomplete, or ambiguous. The social and economic impact of poor-quality data costs billions of dollars. [5-7, 10]. Organizational databases, however, reside in the larger context of information systems (IS). Within this larger context, data is collected from multiple data sources and stored in databases. From this stored data, useful information is generated for organizational decision-making. A new study reveals businesses are defining data quality with the consumer in mind.
On the Utility of CFDI

We consider the description logic CFDI∀− nc , a feature-based dialect that allows capturing value restrictions, a variety of identification constraints, and unqualified feature inverses. We introduce PTIME algorithms for various reasoning tasks in this logic, such as knowledge base consistency and logical implication and discuss the necessity of restrictions over CFDInc to maintain tractability. We then show how CFDI∀− nc ’s modeling capabilities make it suitable for capturing relational and object-relational data sources (including of n-ary relations) in a natural way. In addition, we show that CFDI∀− nc can simulate reasoning in DL-Litecore. We also discuss an approach to capturing a limited variant of role hierarchies within CFDI∀− nc .
Information Evolution And The Future Of The Web

The Web is an incredible informative media, but its same success has turned it into a two-sided phenomenon. On the one side, it has got plenty of information, a richness of contributions and data that is unprecedented in the history of humanity. On the other side, the sheer size of the information present in the Web make it hard to access and to use at all levels, humans and computer-based. In this paper we present a high level perspective on this two-sided nature of web information, by introducing the general concept of Trust Scenario and see its implications by defining major axes of information, and the corresponding directions they can lead to in the future of the Web.
Comparison of Laparoscopic-Assisted Operations and Laparotomy Operations for the Treatment of Hirschsprung Disease

AbstractThe purpose of this meta-analysis is to compare the relative merits among laparoscopic-assisted operations and laparotomy operations for patients with Hirschsprung disease.PubMed, Web of Science, and Wanfang databases were searched for the related articles. We analyzed dichotomous variables by estimating odds ratios (ORs) with their 95% confidence intervals (CIs) and continuous variables using the weighted mean difference (WMD) with the 95% CI. The random-effects model (REM) was used to combine the results. The outcome measures included operating time (OT), estimated blood loss (EBL), length of hospital stay (LOHS), mean first bowel movement (MFBM), and number of complications.Sixteen articles were included in the meta-analysis. These studies involved a total of 774 patients, 396 of whom underwent laparoscopic-assisted operations and 378 of whom underwent laparotomy operations. The EBL (WMD = −1.48, 95% CI = −1.82, −1.13), LOHS (WMD = −0.67, 95% CI = −0.86, −0.49), MFBM (WMD = −0.83, 95% CI = −1.05, −0.61), and number of complications (OR = 0.60, 95% CI = 0.40, 0.89) were significantly lower in laparoscopic-assisted operations than in laparotomy operations. The OT (WMD = 0.12, 95% CI = −0.05, 0.28) showed no significant differences between laparoscopic-assisted operations and laparotomy operations.Compared with laparotomy operations, laparoscopic-assisted operations are generally safer and more reliable for patients with Hirschsprung disease.
Stepped impedance low pass filter using microstrip line for C-band wireless communication

Wireless communication systems, satellite communication and radar systems are generally used low pass microwave filter for frequency selection. The low pass microwave filters are essential for reject harmonic components which are above cut off frequency. High impedance and low impedance microstrip lines are used in stepped impedance microwave filter design. In this proposed filter describes the design of C-band microstrip line low pass filter. In this paper we have choose the bandwidth of 4GHz and implemented with FR4 substrate. Relative permittivity is 4.2 with a thickness of 62 mil for 6th order low pass filter. I have achieved the cut off frequency 4.010GHz for -3dB. The return loss is greater than -47 dB. The proposed low pass stepped impedance microwave filter describes the designing of Butterworth approximation and cut off frequency at 4GHz with an realization of microstrip line. This low pass filter design is simulated by Advanced Design System (ADS) software.