Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Power Management with Scheduled Switching Modes in Wireless Sensor Networks

A wireless sensor network (WSN) comprises many sensor nodes each one containing a processing unit, one or more sensors, a power unit, and a radio for data communication. Nodes are power constrained, because they run on batteries, that in many cases cannot be easily replaced. This paper presents a novel dynamic power management technique, named Dynamic Power Management with Scheduled Switching Modes (DPM-SSM), derived from a more realistic analysis of the battery capacity recovery effect and the switching energy. This was only possible thanks to the application of a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). Preliminary results showed the potential for improving the battery lifetime by taking advantage of the battery recovery effect when a node transitions to a sleeping state, and mostly when transitions are scheduled after packet transmissions. DPM-SSM provides several DPM modes which are triggered depending on the battery remaining capacity. Simulations results show that DPM-SSM can provide real battery power recovery without compromising the timeliness of the applications running on the wireless sensor network.
Saccharomyces cerevisiae kinesin- and dynein-related proteins required for anaphase chromosome segregation

The Saccharomyces cerevisiae kinesin-related gene products Cin8p and Kip1p function to assemble the bipolar mitotic spindle. The cytoplasmic dynein heavy chain homologue Dyn1p (also known as Dhc1p) participates in proper cellular positioning of the spindle. In this study, the roles of these motor proteins in anaphase chromosome segregation were examined. While no single motor was essential, loss of function of all three completely halted anaphase chromatin separation. As combined motor activity was diminished by mutation, both the velocity and extent of chromatin movement were reduced, suggesting a direct role for all three motors in generating a chromosome-separating force. Redundancy for function between different types of microtubule-based motor proteins was also indicated by the observation that cin8 dyn1 double- deletion mutants are inviable. Our findings indicate that the bulk of anaphase chromosome segregation in S. cerevisiae is accomplished by the combined actions of these three motors.
A HYBRID HMM-RNN MODEL FOR OPTICAL MUSIC RECOGNITION

Optical music recognition (OMR) serves as one of the key technologies in Music Information Retrieval by mining symbolic knowledge directly from images of scores. A fullfledged OMR system encompasses both image recognition and music interpretation to convert image data to symbolic representations. This process has proved to be remarkably challenging, so the state-of-the-art OMR systems still leave much to be desired. The development of deep learning in recent years has brought great success in different domains, e.g. object recognition and scene understanding, and aroused researcher’s interest to address unsolved problems with this new tool. Other work has introduced the first attempts of using deep learning to address OMR, but the models apply more appropriately to text than music scores. In this paper we propose a hybrid model that combines the power of Hidden Markov Models (HMM) and Recurrent Neural Networks (RNN) for end-to-end score recognition.
Research of a Multi-dimension Measurement Trusting Model Based on Markov Chain

There are uncertain, dynamic and subjective features about trust relation in realistic network society, how to accurately depict and compute the trust values is a challenging issue in trust computing. Integrating with practical e-commerce application, this paper introduces a novel multi-dimension trusting model based on Markov chain mechanism consisting of evaluating, calculating, filtrating, and publication center. The multi-dimension evaluation metrics include the functional and nonfunctional properties and the corresponding weights. We adopt the continuous evaluation values to measure the trustworthiness of services. The Markov's chain-based trust measurement is given to dynamically calculate the trust value and discover the malicious behaviors. In order to conveniently manage and avoid the dead-lock, some constraint rules are proposed.
Line Matching through Global Optimization Constrained by Protective Invariants

In this work we propose a method for determining correspondences between sets of lines arising when observing a given scene from two different points of views. The method exploits results from the projective geometry and is capable of determining correspondences between images related by any arbitrary projective transformation. The proposed matching approach consists of an optimization process based on satisfaction of global constraints derived from the projective invariance of the cross ratio of any subset of four concurrent coplanar lines.
Futuristic model for school's content management systems : A beginning

One of the main elements in educational portal is Content Management System (CMS). CMS is a web application technology used for managing contents on websites which easy to be updated by anyone who uses a web form. By using CMS, teachers are authorized to contribute materials for teaching purposes while the students do their experiment to test their understanding of the subject. Problem Statement: In order to monitor the student's assessment progress and maintain the “engagement” of the students to the curriculum and assessments' activities, it is important for the parent to get the result of the assessment via mobile services. Approach: This research will concentrate on the analysis and development of futuristic CMS model by using Web 2.0 development, but the paper will explain the theoretical basis of this research first. The characteristic of Flow Theory will be considered to ensure the “engagement” of the student to the CMS exists. Result: A CMS model which can be used in secondary school. ICT Form five secondary schools subject will be used as a sample of teaching and learning materials. The proposed CMS can be embedded to the educational portal framework. Conclusion: With the proposed CMS, it encourages the “engagement” of the students in doing their curriculum activities and at the same time improve their level of understanding in ICT subject. As for their parent, they will receive a message of their children's performance to help them monitoring their children's performance in study.
SDI: New metric for quantification of speckle noise in ultrasound imaging

In ultrasound images a special type of acoustic noise, technically known as speckle noise, is the major factor of image quality degradation. In order to improve the image quality by means of speckle suppression and thus to increase the diagnostic potential of medical ultrasound, it is important to quantify the speckle. This paper describes, quality metrics for speckle in coherent imaging and their limitations. It also describes a new metric-SDI, its uniqueness in quantifying the speckle and comparison of performance with existing metrics. Empirical verification of SDI with a set of Test Images proves its speckle quantification in ultrasound. A subjective criterion is also taken into account to support the results.
KLEAP: an efficient cleaning method to remove cross-reads in RFID streams

Recently, the RFID technology has been widely used in many kinds of applications. However, because of the interference from environmental factors and limitations of the radio frequency technology, the data streams collected by the RFID readers are usually contain a lot of cross-reads. To address this issue, we propose a KerneL dEnsity-bAsed Probability cleaning method (KLEAP) to remove cross-reads within a sliding window. The method estimates the density of each tag using a kernel-based function. The reader corresponding to the micro-cluster with the largest density will be regarded as the position that the tagged object should locate in current window, and the readings derived from other readers will be treated as the cross-reads. Experiments verify the effectiveness and efficiency of the proposed method.
Using Markov Decision Processes and Reinforcement Learningto Solve the \ Remote Versus Local Execution " ProblemTammy

The problem of remote versus local execution requires the construction of a decision to execute a user job locally or to move that job to a remote server based on information of the machines involved, such that the overall user latency is minimized. We present an approach for solving the remote vs. local execution problem using ideas from Markov Decision Processes (MDPs) and Reinforcement Learning (RL). We designed a Decision Making Tool (DMT) that gathers information from a pool of machines available for remote execution as well as the local machine, and determines on which of the machines to execute the current job. A series of experiments were performed in the Duke Computer Science local network using mostly large-scale sorting jobs to test our approach. This paper describes our methodology, implementation, and experimental results. It turns that careful decision making can reduce signiicantly user latency.
Magnetic fields and ionized gas in the local group irregular galaxies IC 10 and NGC 6822

We performed a high-sensitivity search for galaxy-scale magnetic fields by radio polarimetry at 10.45 GHz and 4.85 GHz with the Eelsberg 100 m radio telescope, accompanied by H imaging, for the two Local Group irregular galaxies IC 10 and NGC 6822. Their star-forming bodies are small and rotate slowly. IC 10 is known to have a very high star-forming activity, resembling blue compact dwarfs, while NGC 6822 has a low overall star-formation level. Despite very dierent current star formation rates, our H imaging revealed a large web of diuse H filaments and shells in both IC 10 and NGC 6822. Some of them extend far away from the galaxy's main body. The total power emission of both objects shows bright peaks either at the positions of optically strong star-forming clumps (IC 10) or individual H ii regions or supernova remnants (NGC 6822). However, in both cases we detect a smoothly distributed, extended component. In IC 10 we found clear evidence for the presence of a diuse, mostly random magnetic field of '14G strength, probably generated by a fluctuation dynamo. One of the H-emitting filaments appears to be associated with enhanced magnetic fields. We also rediscuss the reddening of IC 10 and its implications for its distance. In the case of NGC 6822 we found only very weak evidence for nonthermal emission, except perhaps for some regions associated with local gas compression. We detect in both galaxies small spots of polarized emission, indicative of regular fields ('3G), at least partly associated with local compressional phenomena.
Towards a generic architecture for cooperative learning environments

To adapt information effectively to instructional contexts, we need active learning environments that can reason about the domain, the user's mental state and information needs and the general context of information use, as well as about strategies and methods for designing effective information presentations using multiple media. The paper proposes a generic multi-agent architecture for cooperative multimedia pedagogues' intelligent learning environments that help users to achieve their information needs. The aim is to support natural communication and effective collaboration between people and systems. Natural communication requires the integration of different modalities for information presentation and their effective use for achieving tutorial goals in various instructional contexts. Effective collaboration requires systems to work jointly with users towards achieving their information needs. Agents that make up the proposed architecture collaborate with users and between themselves to complete a partial shared plan for achieving users' information needs, as well as a partial shared information presentation plan for achieving tutorial goals.
Multiple mechanisms regulate muscle fiber diversity

Adult skeletal muscles are composed of clusters of multinucleated muscle cells called myofibers. At least three different types of myofibers can be detected within mammals based on their physiological properties and their expression of different contractile protein isoforms. Different skeletal muscles display a wide range of combinations of myofibers. Recent work has demonstrated that multiple mechanisms are responsible for the generation of these myofiber types during development. Muscle progenitor cells have been dissected into two categories on the basis of which isoforms of myosin heavy chain (MHC) they express when they differentiate. Neural and other environmental influences act to modify decisions concerning the type of contractile protein a myofiber may express, and this is most apparent for MHC. The other contractile protein gene families are initially regulated independent of the MHC gene family. One or more events late in development are responsible for coordinating isoform expression between the gene families to generate the adult phenotype. Studies of muscle gene expression have revealed that regulation can occur at the levels of transcription, alternative splicing of primary transcripts, mRNA stability, and translation. The current challenge is to decipher how environmental and functional information is intrepreted in terms of the activity of the regulators of muscle gene expression. —Gunning, P.; Hardeman, E. Multiple mechanisms regulate muscle fiber diversity. FASEB J. 5: 3064‐3070; 1991.
Behavioral constraints and the evolution of faithful social learning

Behavioral "traditions", i.e. behavioral patterns that are acquired with the aid of social learning and that are relatively stable in a group, have been observed in several species. Recently, however, it has been questioned whether non-human social learning is faithful enough to stabilize those patterns. The observed stability could be interpreted as a result of various constraints that limit the number of possible alternative behaviors, rather than of the fidelity of transmission mechanisms. Those constraints can be roughly described as "internal", such as mechanical (bodily) properties or cognitive limitations and predispositions, and "ex- ternal", such as ecological availability or pressures. Here we present an evolutionary individual-based model that explores the re- lationships between the evolution of faithful social learning and behavioral constraints, represented both by the size of the beha- vioral repertoire and by the "shape" of the search space of a given task. We show that the evolution of high-fidelity transmission mechanisms, when associated with costs (e.g. cognitive, biomechanical, energetic, etc.), is only likely if the potential behavioral repertoire of a species is large and if the search space does not provide information that can be exploited by individual learning. Moreover we show how stable behavioral patterns ("traditions") can be achieved at the population level as an outcome of both high-fidelity and low-fidelity transmission mechanisms, given that the latter are coupled with a small behavioral repertoire or with a search space that provide substantial feedback. Finally, by introducing the possibility of environmental change, we show that in- termediate rates of change favor the evolution of faithful social learning (Current Zoology 58 (2): 307318, 2012).
An Approach Technology-Based Marketing ( TBM ) : A New Competitive Approach for High-Tech Industries

This paper presents an innovative competitive approach for high-tech industries, named Technology Based Marketing (TBM). This approach is compared with other eight business approaches. Nowadays, competition is changing and becoming more dynamic and therefore more difficult. Hence, technology can be leveraged to a source of competitiveness. With the TBM approach, three types of technology can be leveraged product, production, and management. The success of the TBM approach depends on certain conditions, only some of which are controlled by the firm. Managers are forced to cope with conditions of uncertainty, both marketing and technological uncertainty. Although marketing uncertainty is unavoidable, technological uncertainty can be reduced. Adopting TBM enhances the ability to cope with uncertainty in order to achieve the firm’s goals.
A model of multi-DOF microrobot manipulator using artificial muscle

In this paper, we described a new type of multi-DOF manipulator using a structure with three artificial muscle (IPMC) segments. We develop the kinematic modeling of multilink motions for the control of the manipulator using a transposed Jacobian or an inverse Jacobian using as sensors elements of motions was realized by IPMC film too, because was used the special actuator-sensor segment (IPMC films are separated electrically by cutting grooves and both the sensor and the actuator can be unified in the same structure). The paper contain simulation results of this model.
Towards Commercial Wireless Sensor Networks: Business and Technology Architecture

In this paper we study the opportunities of commercial exploitation of applications based on sensor networks. Such applications are quite famous nowadays in many different domains of everyday life (e.g., health monitoring, traffic monitoring). We introduce a new business model for sensor based services. Such business model involves entities like the mobile network operator and capitalizes on existing standards for application service providers (e.g., the OSA/Parlay standard). We also present the required technical framework that would facilitate the
A 38 GHz low-loss reflection-type phase shifter

A differential millimeter-wave reflection-type phase shifter is designed at 38 GHz in 90 nm CMOS technology. The measured data shows that the phase shift is tunable up to 161 degrees by voltage control from 0 to 2 V. The insertion loss is compensated by adding a cross-coupled transistor pair, achieving a very low level of 1.45±0.35 dB over the entire phase tuning range. The circuit consumes dc power of 9.6 mW.
Regression of colonic low grade B cell lymphoma of the mucosa associated lymphoid tissue type after eradication ofHelicobacter pylori

BACKGROUND Lymphoma of the mucosa associated lymphoid tissue (MALT) arising in the stomach has been shown to be related to Helicobacter pylori infection, and total regression of gastric lymphoma after successful eradication of H pylori has consistently been reported. MALT-type lymphoma at other localisations, however, has to our knowledge not been linked to H pylori, and eradication of the bacteria has not been studied for management of such lymphomas. PATIENT/METHOD A 67 year old man was diagnosed with MALT-type lymphoma simultaneously involving the stomach and the colon descendens. In addition to the presence of MALT-type lymphoma, H pyloriassociated chronic gastritis was diagnosed, and treatment with clarithromycin, metronidazole, and omeprazole was initiated, resulting in its successful eradication. RESULTS Follow up performed four months later showed regression of the colonic manifestation, whereas the gastric lymphoma did not respond to antibiotic treatment, as assessed by regular follow up for 14 months, in spite of its restriction to mucosa and submucosa. The patient was therefore treated with oral cyclophosphamide (100 mg a day) resulting in partial remission after seven months of continuous treatment. Because of the presence of residual lymphoma, additional irradiation was performed, which led to complete remission of the gastric lymphoma. The patient remains in complete remission 40 months after diagnosis and 26 months after initiation of treatment. CONCLUSION In the case of concurrent gastric and intestinal low grade MALT-type lymphoma,H pylori eradication may cause regression of the intestinal lesion.
Axonal transport analysis using Multitemporal Association Tracking

Multitemporal Association Tracking (MAT) is a new graph-based method for multitarget tracking in biological applications that reduces the error rate and implementation complexity compared to approaches based on bipartite matching. The data association problem is solved over a window of future detection data using a graph-based cost function that approximates the Bayesian a posteriori association probability. MAT has been applied to hundreds of image sequences, tracking organelle and vesicles to quantify the deficiencies in axonal transport that can accompany neurodegenerative disorders such as Huntington's Disease and Multiple Sclerosis and to quantify changes in transport in response to therapeutic interventions.
Pitfalls of virtual machine introspection on modern hardware

Over the last few years there has been immense progress in developing powerful security tools based on Virtual Machine Introspection (VMI). VMI offers unique capabilities which can be used to check and enforce security policies in the presence of a potentially compromised guest. With the introduction of new hardware virtualization extensions, VMI can be further enhanced to provide lightweight, in-band control over the execution of virtual machines. In publications released before the extensions were available, security researchers issued warnings that these new extensions may be used to subvert VMI. Since hardware supporting these extensions is now available, in this paper, we aim to discuss and re-evaluate claims made in prior-art. We further continue the discussion by highlighting critical limitations of the virtualization extensions. We go on to show that thorough consideration and understanding of these limitations is necessary when developing VMI based security applications. Otherwise, improper handling will inadvertently expose these applications to subversion attacks. Finally, we take a look at Intel’s normal and dual-monitor System Management Mode and discuss how they can be used to both implement and subvert VMI based security applications.
Application of Support Vector Machine and Genetic Algorithm to Network Intrusion Detection

Intrusion detection is actually a classification problem. It is very important to increase the classification accuracy. Support Vector Machine (SVM) is a powerful tool to solve classification problems. Many works have been done in intrusion detection based on SVM, and the detection accuracy is relatively high. But how to get a higher accuracy is a new question. In this paper, we apply SVM and Genetic Algorithm (GA) to intrusion detection to solve this problem. We first use GA for feature selection and optimization, and then use SVM model to detect intrusions. In order to verify our approach, we tested our proposal with KDD Cup99 dataset, and analyzed its performance. The experimental results show that the proposed approach is an efficient way in network intrusion detection.
A Decorrelating Design-for-Digital-Testability Scheme for $\Sigma{-}\Delta$ Modulators

This paper presents a novel decorrelating design-for-digital-testability (D3T) scheme for Sigma-Delta modulators to enhance the test accuracy of using digital stimuli. The input switched-capacitor network of the modulator under test is reconfigured as two or more subdigital-to-charge converters in the test mode. By properly designing the digital stimuli, the shaped noise power of the digital stimulus can be effectively attenuated. As a result, the shaped noise correlation as well as the modulator overload issues are alleviated, thus improving the test accuracy. A second-order Sigma-Delta modulator design is used as an example to demonstrate the effectiveness of the proposed scheme. The behavioral simulation results showed that, when the signal level of the stimulus tone is less than -5 dBFS, the signal-to-noise ratios obtained by the digital stimuli are inferior to those obtained by their analog counterparts of no more than 1.8 dB. Circuit-simulation results also demonstrated that the D3T scheme has the potential to test moderate nonlinearity. The proposed D3T scheme has the advantages of achieving high test accuracy, low circuit overhead, high fault observability, and the capability of conducting at-speed tests.