Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition of bangla basic characters using multiple classifiers

Character recognition is an important area in image processing and pattern recognition fields. A novel scheme for recognition of offline basic characters of Bangla using multiple classifiers is described here. Compared to English characters, there are different complex shaped characters in Bangla alphabet. Dealing with such a large number of characters with a suitably designed feature set is a challenging problem. Moreover, such a large variety of complex shaped characters, some of which have close resemblance, make the problem more difficult. Considering the complexity of the problem, present approach makes an attempt to identify the basic characters. We have adopted this hybrid approach because it is nearly impossible to find a set of stroke features which are sufficient to classify the characters. A prototype of the system is tested with a data set containing 4423 characters of different font and size. On average, the recognition accuracies for Binary tree based classifier and Multilayer perceptron [with backpropagation for learning] (MLP) are 90% above approximately.
Teaching case-based argumentation through a model and examples

CATO is an intelligent learning environment designed to help beginning law students learn basic skills of making arguments with cases. Using CATO, students practice tasks of induction and analogical argumentation. They practice testing theories against a body of cases and making written arguments about a problem, comparing and contrasting it to past cases. CATO's model addresses arguments in which two opponents analogize a problem to favorable cases, distinguish unfavorable cases, assess the significance of similarities and differences between cases in light of normative knowledge about the domain, and use that knowledge to organize multi-case arguments. CATO communicates the model to students by presenting dynamically-generated argumentation examples and by reifying argument structure based on the model. CATO also provides a case database and tools based on the model that help make students' tasks more manageable. CATO was evaluated in the context of an actual legal writing course, in a study involving 30 first-year law students. We found that instruction with CATO leads to statistically significant improvement in students' basic argumentation skills, comparable to that achieved by an experienced legal writing instructor teaching groups of 4-10 students. However, on a more advanced legal writing assignment, meant to explore the frontier of the CATO instruction, students taught by the legal writing instructor had higher grades, suggesting a need for more integrated practice with the CATO model. CATO contributes to AI research fields modeling educational techniques as well as case-based and legal reasoning. It is a novel result that students can learn basic argumentation skills by studying computer-generated examples. It means that an instructional system does not necessarily need to rely on a very sophisticated understanding of students' arguments, which would be a significant obstacle to developing such systems. Also, CATO presents novel techniques for using background knowledge to support similarity assessment in case-based reasoning. Drawing on its background knowledge, CATO characterizes and re-characterizes cases in order to argue that two cases are similar or different. This is an important skill in the legal domain not previously modeled. CATO's arguments may help a user in assessing the similarity of cases in a more discriminatory way.
Speeding Up Neighbour-Joining Tree Construction

A widely used method for constructing phylogenetic trees is the neighbour-joining method of Saitou and Nei. We develope heuristics for speeding up the neighbour-joining method which generate the same phylogenetic trees as the original method. All heuristics are based on using a quad-tree to guide the search for the next pair of nodes to join, but differ in the information stored in quad-tree nodes, the way the search is performed, and in the way the quad-tree is updated after a join. We empirically evaluate the performance of the heuristics on distance matrices obtained from the Pfam collection of alignments, and compare the running time with that of the QuickTree tool, a well-known and widely used implementation of the standard neighbour-joining method. The results show that the presented heuristics can give a significant speed-up over the standard neighbour-joining method, already for medium sized instances.
Novel Hybrid Approach for Fault Diagnosis in 3-DOF Flight Simulator Based on BP Neural Network and Ant Colony Algorithm

In the 3-DOF(degree-of-freedom) flight simulator system, the relations between observed information and fault causes are very complicated. Based on the description of the basic principle of the ant colony algorithm, a novel hybrid approach for fault diagnosis in 3-DOF flight simulator is proposed in this paper, which is based on BP(back propagation) neural network and ant colony algorithm. Combining with rough set theory, ant colony algorithm is used to compute the reductions of the decision table. Then, the condition attributes of decision table are regarded as the input nodes of BP neural network and the decision attributes are regarded as the output nodes of BP neural network correspondingly. Experiments demonstrate that the proposed hybrid approach could achieve a fairly good performance, yield good prediction accuracy of the prediction errors
Wilkinson Microwave Anisotropy Probe Constraints on the Intracluster Medium

We devise a Monte Carlo-based, optimized filter match method to extract the thermal Sunyaev-Zel'dovich (SZ) signature of a catalog of 116 low-redshift X-ray clusters from the first-year data release of the Wilkinson Microwave Anisotropy Probe (WMAP). We detect an overall amplitude for the SZ signal at the ~8 σ level, yielding a combined constraint of fgash = 0.08 ± 0.01(ran) ± 0.01(sys) on the gas mass fraction of the intracluster medium. We also compile X-ray-estimated gas fractions from the literature for our sample and find that they are consistent with the SZ estimates at the 2 σ level, while both show an increasing trend with X-ray temperature. Nevertheless, our SZ estimated gas fraction is 30%-40% smaller than the concordance ΛCDM cosmic average. We also express our observations in terms of the SZ flux-temperature relation and compare it with other observations, as well as with numerical studies. Based on its spectral and spatial signature, we can also extract the microwave point-source signal of the clusters at the 3 σ level, which puts the average microwave luminosity (at ~41 GHz) of bright cluster members (MK ≤ -21) at (2.4 ± 0.8) × 1027 h-2 ergs s-1 Hz-1. Furthermore, we can constrain the average dark matter halo concentration parameter to cvir = 3.4 for clusters with TX > 5 keV. Our work serves as an example for how correlation of SZ surveys with cluster surveys at other frequencies can significantly increase our physical understanding of the intracluster medium.
Evaluating Dependency Representations for Event Extraction

The detailed analyses of sentence structure provided by parsers have been applied to address several information extraction tasks. In a recent bio-molecular event extraction task, state-of-the-art performance was achieved by systems building specifically on dependency representations of parser output. While intrinsic evaluations have shown significant advances in both general and domain-specific parsing, the question of how these translate into practical advantage is seldom considered. In this paper, we analyze how event extraction performance is affected by parser and dependency representation, further considering the relation between intrinsic evaluation and performance at the extraction task. We find that good intrinsic evaluation results do not always imply good extraction performance, and that the types and structures of different dependency representations have specific advantages and disadvantages for the event extraction task.
Effectiveness of overlay routing based on delay and bandwidth information

Recent research on overlay networks has revealed that user-perceived network performance, such as end-to-end delay performance, could be improved by an overlay routing mechanism. However, these studies consider only end-to-end delay, and few studies have focused on bandwidth-related information, such as available bandwidth and TCP throughput, which are important performance metrics especially for longlived data transmission. In the present paper, we investigate the effect of overlay routing both delay and bandwidth-related information, based on the measurement results of network paths between PlanetLab nodes. We consider three metrics for selecting the overlay route: end-to-end delay, available bandwidth, and TCP throughput. We then show that the available bandwidth-based overlay routing provides significant gain, as compared with delay-based routing. We further reveal the correlation between the latency and available bandwidth of the overlay paths and propose several guidelines for selecting an overlay path. key words: overlay networks, overlay routing, available bandwidth, endto-end delay, TCP throughput
Three-Dimensional Aggregates Enhance the Therapeutic Effects of Adipose Mesenchymal Stem Cells for Ischemia-Reperfusion Induced Kidney Injury in Rats

It has been shown that administration of adipose derived mesenchymal stem cells (AdMSCs) enhanced structural and functional recovery of renal ischemia-reperfusion (IR) injury. Low engraftment of stem cells, however, limits the therapeutic effects of AdMSCs. The present study was designed to enhance the therapeutic effects of AdMSCs by delivering AdMSCs in a three-dimensional (3D) aggregates form. Microwell was used to produce 3D AdMSCs aggregates. In vitro data indicated that AdMSCs in 3D aggregates were less susceptible to oxidative and hypoxia stress induced by 200 μM peroxide and hypoxia/reoxygenation, respectively, compared with those cultured in two-dimensional (2D) monolayer. Furthermore, AdMSCs in 3D aggregates secreted more proangiogenic factors than those cultured in 2D monolayer. 2D AdMSCs or 3D AdMSCs aggregates were injected into renal cortex immediately after induction of renal IR injury. In vivo data revealed that 3D aggregates enhanced the effects of AdMSCs in recovering function and structure after renal IR injury. Improved grafted AdMSCs were observed in kidney injected with 3D aggregates compared with AdMSCs cultured in 2D monolayer. Our results demonstrated that 3D AdMSCs aggregated produced by microwell enhanced the retention and therapeutic effects of AdMSCs for renal IR injury.
A Security and Privacy Review of VANETs

Vehicular ad hoc networks (VANETs) have stimulated interest in both academic and industry settings because, once deployed, they would bring a new driving experience to drivers. However, communicating in an open-access environment makes security and privacy issues a real challenge, which may affect the large-scale deployment of VANETs. Researchers have proposed many solutions to these issues. We start this paper by providing background information of VANETs and classifying security threats that challenge VANETs. After clarifying the requirements that the proposed solutions to security and privacy problems in VANETs should meet, on the one hand, we present the general secure process and point out authentication methods involved in these processes. Detailed survey of these authentication algorithms followed by discussions comes afterward. On the other hand, privacy preserving methods are reviewed, and the tradeoff between security and privacy is discussed. Finally, we provide an outlook on how to detect and revoke malicious nodes more efficiently and challenges that have yet been solved.
Generalized Structure of a Multilevel PWM Inverter

A generalized structure of a multilevel voltage source thyristor inverter is proposed. The multilevel concept is used to decrease the harmonic distortion in the output waveform without decreasing the inverter power output. A simple uniform PWM control of the output voltage is seen to be sufficient to practically remove all remaining harmonics. Harmonic analysis of n-step waveform is given, and the experimental results obtained on a three-step inverter are presented.
Supervised Learning with Tensor Networks

Tensor networks are approximations of high-order tensors which are efficient to work with and have been very successful for physics and mathematics applications. We demonstrate how algorithms for optimizing tensor networks can be adapted to supervised learning tasks by using matrix product states (tensor trains) to parameterize non-linear kernel learning models. For the MNIST data set we obtain less than 1% test set classification error. We discuss an interpretation of the additional structure imparted by the tensor network to the learned model.
A 0.85mm2 51%-Efficient 11-dBm Compact DCO-DPA in 16-nm FinFET for Sub-Gigahertz IoT TX Using HD2 Self-Suppression and Pulling Mitigation

In this paper, we propose a sub-gigahertz transmitter (TX) with a physically merged digitally controlled oscillator (DCO) and digital power amplifier (DPA). The matching transformer of single-ended DPA is placed inside the DCO transformer to save ~50% of area. The resulting DCO pulling is compensated via a feedback path and an inter-winding cancellation capacitor suppresses the second harmonic. Fabricated in 16-nm FinFET CMOS, the DPA reaches 51% efficiency at 11-dBm output with < −55-dBc HD2. The 1.8-GHz DCO exhibits −116-dBc/Hz phase noise (PN) at 1-MHz offset and draws 195 uW from 0.3-V supply. The error vector magnitude measured with a 2-MHz 64-Quadratic amplitude modulation (QAM) orthogonal frequency division multiplexing signal at 5-dBm average power is 3.7%.
Checking Intent-based Communication in Android with Intent Space Analysis

Intent-based communication is an inter-application communication mechanism in Android. While its importance has been proven by plenty of security extensions that protect it with policy-driven mandatory access control, an overlooked problem is the verification of the security policies. Checking one security extension's policy is indeed complex. Furthermore, intent-based communication introduces even more complexities because it is mediated by multiple security extensions that respectively enforce their own incompatible, distributed, and dynamic policies. This paper seeks a systematic approach to address the complexities involved in checking intent-based communication. To this end, we propose intent space analysis. Intent space analysis formulates the intent forwarding functionalities of security extensions as transformations on a geometric intent space. We further introduce a policy checking framework called IntentScope that proactively and automatically aggregates distributed policies into a holistic and verifiable view. We evaluate our approach against customized Android OSs and commodity Android devices. In addition, we further conduct experiments with four security extensions to demonstrate how our approach helps identify potential vulnerabilities in each extension.
A Hybrid Object Matching Method for Deep Web Information Integration

Object matching is a crucial step to integration of Deep Web sources. Existing methods suppose that record extraction and attribute segmentation are of high accuracy. But because of limitation of extraction techniques, information gained through the above methods is often incomplete. If we match object base on noisy and incomplete information, we can not achieve satisfactory performance. This paper proposes a hybrid object matching method, which considers structured and unstructured features and multi-level errors in extraction. We compare performance of the unstructured, structured and hybrid object matching models in our prototype system, which indicates that hybrid method has the highest performance.
Designing Products with Added Emotional Value: Development and Appllcation of an Approach for Research through Design

In this paper, a design approach is introduced for designing products with added emotional value. First, the approach was established, based on a theoretical framework and a non-verbal instrument to measure emotional responses. Second, the value of the design approach was assessed by applying it to the design of mobile telephones. Mobile telephones were found to be useful vehicles as people appear to have strong feelings about this product. A user study was conducted which resulted in the identification of two user groups (‘trend followers' and ‘security seekers') and for each group an emotional profile. Four telephones were designed which, for each group, either were intended to or were not intended to match the group's profile. Finally, these designs were evaluated with the non-verbal instrument. The results indicate that the approach is appropriate for designing products with added emotional value. The advantages and disadvantages of the approach are discussed and further research directions indicated.
Performance Evaluation of Load Balanced Web Proxies

A large university usually has many units that may locate far apart, and there are many proxy servers installed to give web access services to those units individually. However, some proxies may face the performance bottleneck when many users access the Internet simultaneously since such servers have limited capacity and could not handle high workload whereas the workload cannot be transferred to other proxies. This paper proposes an efficient load balancing technique called Shoot-Lowest Load which simulates the cache size at each proxy by counting the number and the size of log records generated by Squid proxy software in order to approximate the current workload at each proxy. We evaluate our work and compare it with the other two methods: Super Proxy and Time Round-Robin. Two metrics measured are the number of requests and the request size. In addition, the real proxy traffic is simulated as the testing dataset. The experimental results showed that our proposed method gave the best load balancing since it can closely estimate the current workload of each server so that a request will be sent to the proxy server with the lowest load.
Application of Neural Network for Scour and Air Entrainment Prediction

This research aims at introducing a system independent method for scour and air entrainment prediction utilizing Artificial Neural Network (ANN) based on previous experimental plunge pool scour tests for inclined circular jets. Furthermore, the current manuscript introduced a single ANN model to predict air entrainment devoid of pre-knowledge of the jet condition either smooth or rough jet. Regarding ANN applicability validation, its prediction results was compared to the earlier experimental results for three regression models; one for scour, and two air-models for a smooth and rough jet. The results from each model out of the three ANN models are proved more accurate than the corresponding pre-developed regression models. Relative error envelop of 5% was found to bound all the records for the prediction of air in both ANN models (smooth and rough). For the prediction of the scour, the ANN model was also better than the regression model with only two data records of 20% relative error.
Orientation of the Calcium Channel β Relative to the α12.2 Subunit Is Critical for Its Regulation of Channel Activity

Background The Cavβ subunits of high voltage-activated Ca2+ channels control the trafficking and biophysical properties of the α1 subunit. The Cavβ-α1 interaction site has been mapped by crystallographic studies. Nevertheless, how this interaction leads to channel regulation has not been determined. One hypothesis is that βs regulate channel gating by modulating movements of IS6. A key requirement for this direct-coupling model is that the linker connecting IS6 to the α-interaction domain (AID) be a rigid structure. Methodology/Principal Findings The present study tests this hypothesis by altering the flexibility and orientation of this region in α12. 2, then testing for Cavβ regulation using whole cell patch clamp electrophysiology. Flexibility was induced by replacement of the middle six amino acids of the IS6-AID linker with glycine (PG6). This mutation abolished β2a and β3 subunits ability to shift the voltage dependence of activation and inactivation, and the ability of β2a to produce non-inactivating currents. Orientation of Cavβ with respect to α12. 2 was altered by deletion of 1, 2, or 3 amino acids from the IS6-AID linker (Bdel1, Bdel2, Bdel3, respectively). Again, the ability of Cavβ subunits to regulate these biophysical properties were totally abolished in the Bdel1 and Bdel3 mutants. Functional regulation by Cavβ subunits was rescued in the Bdel2 mutant, indicating that this part of the linker forms β-sheet. The orientation of β with respect to α was confirmed by the bimolecular fluorescence complementation assay. Conclusions/Significance These results show that the orientation of the Cavβ subunit relative to the α12. 2 subunit is critical, and suggests additional points of contact between these subunits are required for Cavβ to regulate channel activity.
Region-Based Partial Volume Correction Techniques for PET Imaging: Sinogram Implementation and Robustness

Background/Purpose. Limited spatial resolution of positron emission tomography (PET) requires partial volume correction (PVC). Region-based PVC methods are based on geometric transfer matrix implemented either in image-space (GTM) or sinogram-space (GTMo), both with similar performance. Although GTMo is slower, it more closely simulates the 3D PET image acquisition, accounts for local variations of point spread function, and can be implemented for iterative reconstructions. A recent image-based symmetric GTM (sGTM) has shown improvement in noise characteristics and robustness to misregistration over GTM. This study implements the sGTM method in sinogram space (sGTMo), validates it, and evaluates its performance. Methods. Two 3D sphere and brain digital phantoms and a physical sphere phantom were used. All four region-based PVC methods (GTM, GTMo, sGTM, and sGTMo) were implemented and their performance was evaluated. Results. All four PVC methods had similar accuracies. Both noise propagation and robustness of the sGTMo method were similar to those of sGTM method while they were better than those of GTMo method especially for smaller objects. Conclusion. The sGTMo was implemented and validated. The performance of the sGTMo in terms of noise characteristics and robustness to misregistration is similar to that of the sGTM method and improved compared to the GTMo method.