Miracle-dz/UniFAR-FTUs huggingface dataset:
SPEEDA: A Secure Protocol and Energy Efficient for Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSN) consists of a set of small and resources-constrained devices. They have received much attention over the last few years for the study and development of a plethora of potential applications. However, the common denominator of all applications of these sensor networks is the vulnerability of micro-sensors because of their limited material resources the most constraining of which is energy. In fact, wireless sensors are limited in terms of calculation, storage, battery, etc. Therefore, every possible solution that aims to conserve these resources is extensively sought. Thus, a great deal of researches has been conducted leading to an effective technique answering the established problem. This solution concerns the aggregation of data which is one of the techniques that is actually considered as an essential paradigm for sensor networks since it tends to save computation and communication resources. Data aggregation allows in-network processing which leads to lesser packet transmissions and reduces redundancy, and therefore, helps in increasing network’s overall lifetime. However, sensor networks are usually deployed in unattended and hostile environments.Thus, the designer should not only consider the limited resources of the sensor nodes but also the security threats that can occur in an easily accessible network to the attacker. In this paper, we will give an overview study of the existing data aggregation solutions in wireless sensor networks then, we will propose a new efficient and secure approach to aggregation which can be evaluated with specific criteria.
NTT statistical machine translation for IWSLT 2006

We present the NTT translation system that is experimented for the evaluation campaign of “International Workshop on Spoken Language Translation (IWSLT). ” The system consists of two primary components: a hierarchical phrase-based statistical machine translation system and a reranking sys tem. The former is conceptualized as a synchronous-CFG in which phrases are hierarchically combined using nonterminals. The latter uses a modified voted perceptron approach with large number of features. Experiments showed that our hierarchical phrase-based model outperformed a conventional phrase-based model. In addition, our reranking algorithm further boosted the performance.
Competitive Binding between miR-122 and p68 onto Hepatitis C Viral RNA

Background Liver-specific microRNA (miR)-122 has been shown to be involved in regulating translation of hepatitis C viral (HCV) RNA. This study aimed to explore the molecular mechanism of miR-122 in regulating HCV RNA translation initiation. Material/Methods In human liver hepatocellular carcinoma cell line HepG2, UV cross-link assay was performed on a large scale to identify RNA-binding proteins with gradient concentrations of miR-122. Analytical ultracentrifugation was then used to separate the translation initiation complexes. All RNA-binding proteins were then identified by Western blotting. Results The binding of 68 kDa protein (p68) to HCV RNA was suppressed by the addition of miR-122 via the competitive binding assay. Such inhibition can be eliminated by the addition of 2′-O-methylated oligonucleotides. This binding suppression was determined to be specific for miR-122, which used the mature single-stranded RNA to suppress the binding of p68 onto HCV RNA. This binding inhibition was further validated by using authentic miR-122 with conserved regions and mutated sequences. Conclusions The binding of p68 onto HCV RNA can be specifically inhibited by miR-122 via a competitive binding process.
A Lysine Cluster in Domain II of Bacillus subtilis PBP4a Plays a Role in the Membrane Attachment of This C1-PBP

In PBP4a, a Bacillus subtilis class-C1 penicillin-binding protein (PBP), four clustered lysine (K) residues, K86, K114, K119, and K265, protrude from domain II. Replacement of these amino acids with glutamine (Q) residues by site-directed mutagenesis yielded Mut4KQ PBP4a. When produced in Escherichia coli without its predicted Sec-signal peptide, wild-type (WT) PBP4a was found mainly associated with the host cytoplasmic membrane, whereas Mut4KQ PBP4a remained largely unbound. After purification, the capacities of the two proteins to bind to B. subtilis membranes were compared. The results were similar to those obtained in E. coli: in vitro, a much higher percentage of WT PBP4a than of Mut4KQ PBP4a was found to interact with B. subtilis membranes. Immunodetection of PBP4a in B. subtilis membrane extracts revealed that a processed form of this PBP (as indicated by its size) associates with the B. subtilis cytoplasmic membrane. In the absence of any amphiphilic peptide in PBP4a, the crown of positive charges on the surface of domain II is likely responsible for the cellular localization of this PBP and its attachment to the cytoplasmic membrane.
On the Energy Efficiency for Heterogeneous Data Broadcasting

Data broadcast is an advanced technique to realize large scalability and bandwidth utilization in a mobile computing environment. In the heterogeneous data broadcast, the data size is variant with time in multiple broadcast channels. However, traditional indexing schemes do not consider variant data size to design indexing techniques in the multiple channels. Therefore, the above drawback leads to large power consumption in the heterogeneous data broadcast. In this paper, we remedy the problem of devising an indexing technique to index the data of variant size via the multiple channels. In view of the characteristics of variant data size in the multiple channels, we propose an indexing technique using an index tree to minimize average waiting time and average tuning time. Experimental results show that our approach is able to generate broadcast programs including data indices with high quality and is very efficient in the heterogeneous data broadcast.
Asymptotic ordinal inefficiency of random serial dictatorship

We establish that the fraction of preference profiles for which the random serial dictatorship allocation is ordinally efficient vanishes for allocation problems with many object types. We consider also a probabilistic setting where in expectation agents have moderately similar preferences reflecting varying popularity across objects. In this setting we show that the probability that the random serial dictatorship mechanism is ordinally efficient converges to zero as the number of object types becomes large. We provide results with similarly negative content for allocation problems with many objects of each type. One corollary is that ordinal efficiency is a strict refinement of ex-post efficiency at most preference profiles.
Temporal and phylogenetic evolution of the sauropod dinosaur body plan

The colossal size and body plan of sauropod dinosaurs are unparalleled in terrestrial vertebrates. However, to date, there have been only limited attempts to examine temporal and phylogenetic patterns in the sauropod bauplan. Here, we combine three-dimensional computational models with phylogenetic reconstructions to quantify the evolution of whole-body shape and body segment properties across the sauropod radiation. Limitations associated with the absence of soft tissue preservation in fossils result in large error bars about mean absolute body shape predictions. However, applying any consistent skeleton : body volume ratio to all taxa does yield changes in body shape that appear concurrent with major macroevolutionary events in sauropod history. A caudad shift in centre-of-mass (CoM) in Middle Triassic Saurischia, associated with the evolution of bipedalism in various dinosaur lineages, was reversed in Late Triassic sauropodomorphs. A craniad CoM shift coincided with the evolution of quadrupedalism in the Late Triassic, followed by a more striking craniad shift in Late Jurassic–Cretaceous titanosauriforms, which included the largest sauropods. These craniad CoM shifts are strongly correlated with neck enlargement, a key innovation in sauropod evolution and pivotal to their gigantism. By creating a much larger feeding envelope, neck elongation is thought to have increased feeding efficiency and opened up trophic niches that were inaccessible to other herbivores. However, we find that relative neck size and CoM position are not strongly correlated with inferred feeding habits. Instead the craniad CoM positions of titanosauriforms appear closely linked with locomotion and environmental distributions, potentially contributing to the continued success of this group until the end-Cretaceous, with all other sauropods having gone extinct by the early Late Cretaceous.
A Privacy-Preserving Integrity Measurement Architecture

TCG’s Trusted Platform Modules provide the functionality of remote attestation, which based on the integrity of software components in a specific platform configuration. Integrity Measurement Architecture(IMA) is the accredited remote attestation methods which formulates the integrity measurement process and integrity reporting protocol. However, as a binary attestation, all integrity measurements must be exposed to remote party-verifier. This can disclose the privacy of attesting platform. In this paper, We slightly adapt the Integrity Measurement Architecture(IMA) to provide privacy preserving. System configuration is partitioned into privacy-relevant tasks based on the measurement relationships and dependency relationships between components. During integrity reporting in remote attestation, only the measurements of task-relevant software components are released to verifier. Shield factors are introduced to hide integrity measurements during measurement process and hide the task-irrelevant integrity measurement during integrity report.
Look who is warning: individual differences in motivation activation influence behaviors during disasters

Abstract This study investigated individual differences in responses to disasters based on participants’ motivational reactivity and ethical ideology. Motivational reactivity was measured using the motivational activation measure (MAM), which assesses individual differences in appetitive and defensive system activations. Participants (N = 240) answered survey questions about how they would respond to natural disasters or emergency situations. Results showed that (1) participants with higher defensive activation scores were more likely to report they would share warnings during a disaster situation, (2) high appetitive system activation is associated with high ethical relativism, (3) high defensive system activation is associated with high ethical idealism, and (4) individuals’ personal moral philosophy moderates the effects of MAM score on intention to warn others. Theoretical and practical implications are also discussed.
Research on path planning and TSP based on genetic algorithm and Hopfield neural network

In the mobile robot technology, path planning is an important question. In this paper it gets the model information of global static environment by raster method, and by the genetic algorithm it can obtain the population diversity of the optimal planning path avoiding successfully obstacles and going through the designated points, then Hopfield neural network is used to solve the traveling salesman problem(TSP) and optimal round-trip problem of passing through the designed points, the proposed method is feasible and effective, the simulation results in the Matlab show better optimization effect.
A Fast Watershed-Based Image Segmentation Algorithm Using Local Merging Strategy

In this paper, a fast watershed-based image segmentation algorithm is proposed. Firstly, a homogeneity gradient image named after H-image is produced, and then the traditional watershed segmentation is used to initially segment the H-image to produce over-segmented image regions (objects), and at last local optimum merging strategy is utilized to merge neighbor regions to construct a hierarchical network of image objects according to different scales. Textural, color and shape information of segments is utilized in the merging process. Experiments demonstrate the validity of the algorithm proposed in this paper.
Comprehensive Examination Recommender Systems : Dr . Daqing He Educational Data Mining : Dr

As suggested by Konstan and Riedl [66], user-contributed content is one of the vast and important data resources in recommender systems. It includes users’ tags, reviews, playlists, blog posts and micro-blogging content, forums, etc. Although the aforementioned list include the mostly agreed upon forms of user-contributed content, an extreme view can even consider ratings of users or the trust links between them as a form of user-contributed information. Although link structure can be extracted from some of the user-contributed content (either explicit such as following in Twitter or implicit such as the structure extracted from retweets), I focus on the more recognized forms of user-contributed content. To categorize user-contributed content in recommender systems, we have multiple options: based on the type of user-contributed content, the type of recommendation algorithm they are used in, the ways it is incorporated in recommender systems, and the items being recommended. Since the main focus of the question is on user-contributed contents, I choose the type of content as my main categorization factor. However, I briefly overview the other factors in the following. As for type of recommendation algorithm that user-contributed content are used in, it can be utilized in content-based [45], collaborative filtering [79], knowledge-based [16], and hybrid recommender systems [5]. Since recommender systems in general have the same categorization, I skip
Analyzing the performance of memory management in RTSJ

The memory models used in the Real-Time Specification for Java (RTSJ) can incur large amounts of overhead; It is possible to reduce this overhead by taking advantage of hardware features. This paper provides an in-depth analytical investigation of the overhead of write barriers in RTSJ VMs, and describes and analyzes solutions for reducing them.
Comparison in structural stability between chain A and B of CLC-ec1 exchanger by using MD simulation

The CLC-type exchangers have been extensively studied in recent years. CLC-ec1, whose crystal structure is known and several experimental and theoretical hot spots have been identified, but the structural stability in true solution environment of this protein has not been provided. In this paper, we analyzed the structural stability of CLC-ec1 protein by using the atomistic molecular dynamics (MD) simulation. The simulation result indicates that there exists no inevitable correlation between chain A and chain B in expressing their biological function. Chain A has smaller average Cα displacement value than that of chain B. The calculated electrostatic binding free energy and its fluctuation of chain A are also smaller. These results indicate that chain A has more stable structure than chain B in physical essence. It is to say that chain A may be more reliable than chain B in expressing their biological function. This work proposes a new topic on future experimental and theoretical investigations for biologists and biophysicists.
Using psycholinguistic inquiry to measure emotional response to music: A feasibility study

Linguistic Inquiry and Word Count (LIWC) software, which can analyze elements of language, has been used to measure emotional responses to film clips, yet the viability of LIWC to study emotional responses to music has not been investigated. The purpose of this study was to assess the feasibility of using LIWC software to measure emotional responses to music. Undergraduate education majors (N = 56) listened to two 90-second musical excerpts, one happy and one sad. After each excerpt, participants wrote about induced and perceived emotional responses. A repeated-measures ANOVA used to analyze effects of excerpt, writing prompt, emotion and order revealed a significant main effect for emotion (p = .01). Significant interactions were found between emotion and excerpt (p < .001) and between excerpt, prompt and emotion (p = .005). Participants used significantly more positive emotion words than negative emotion words to describe the happy excerpt, and the reverse was true for the sad excerpt. Both writing prompts elicited the expected differences in emotional response; however, the perceived emotion prompt resulted in greater contrasts between positive and negative emotion words than the induced emotion prompt. Results indicate that it is feasible to use LIWC to measure emotional responses to music.
Younger and Brighter - New Distances to Globular Clusters Based on HIPPARCOS Parallax Measurements of Local Subdwarfs

We have used new parallax measurements, obtained by the Hipparcos satellite, of fifteen nearby, metal-poor stars to re-define the subdwarf main-sequence. All of these stars have parallaxes determined to an accuracy of at least 12 %. Comparing these measurements against previous ground-based data for nine stars reveals a systematic offset of 5 %, in the sense that the Hipparcos parallaxes are smaller (i.e. the inferred distances are larger). The availability of the Hipparcos observations expands the local subdwarf sample to the extent that we can separate the stars by abundance into intermediate ([Fe/H] ~ -1.4) and extreme ([Fe/H] ~ -2) subsets. Main-sequence fitting techniques are then used to match stars of the appropriate abundance range to the colour-magnitude diagrams of the seven globular clusters M5, NGC 6752, M13, M15, M92, M30 and M68. We derive respective distance moduli of 14.45, 13.17, 14.48, 15.38, 14.93, 14.95 and 15.29 magnitudes, with formal uncertainties of +/- 0.1 magnitude. The metal-poor systems M68, M15 and M30 have moderate foreground reddening, and varying E(B-V) by +/- 0.02 magnitudes can change the derived distances by up to +/- 7 %. With the exception of NGC 6752, however, our derived distances exceed previous estimates, particularly in the case of the four [Fe/H] ~ -2.1 globulars, where our distance moduli are ~ 0.3 magnitudes higher than the current standard values. We discuss briefly how these findings affect the RR Lyrae distance scale, isochrone-based estimates of the age of globular clusters and our picture of the early stages of star formation in the Galaxy. We note that our results go some way towards reconciling the apparent contradiction between the cluster ages and recent determinations of the Hubble constant.
Star economy in the user generated content: a new perspective for digital ecosystems

User generated content plays an important role in Web 2.0-based digital economy. The author focuses an emerging aspect of user participation-based digital economy. Cultural aspects of digital economy are largely unexplored in literature. They identified a new Internet-based social behavior so-called star-economy in a Japanese kid-based network service with the user content sharing. The author analyzed the star-economy in the emerging social game context. The author revisits the network effect (network externality) in the digital eco system in order to identify the landing pad for the star-economy. The author presents the lessons from the new dimension of network effect and exploits the staged based consideration of digital social systems.
On the use of neural networks to combine utterance and speaker verification systems in a text-dependent speaker verification task

Speaker Verification and Utterance Verification are examples of techniques that can be used for Speaker Authentication purposes. Speaker Verification consists of accepting or rejecting the claimed identity of a speaker by processing samples of his/her voice. Utterance Verification systems make use of a set of speaker-independent speech models to recognize a certain utterance and decide whether a speaker has uttered it or not. If the utterances consist of passwords, this technique can be used for identity verification purposes. Up to now, both techniques have been used separately. We propose an architecture consisting of both systems working in parallel with a novel output combination technique. Thus, a Neural Network is designed to learn from the data how to balance the influence of both outputs in order to jointly minimize the False Acceptance and False Rejection rates. The better performance of this architecture is compared with those of the individual systems in an over the phone speaker recognition task.
Solving data-sensitive coordination constraints

This paper studies complex coordination mechanisms based on constraint satisfaction. In particular, it focuses on data-sensitive connectors from the Reo coordination language. These connectors restrict how and where data can flow between loosely-coupled components taking into account the data values being exchanged. Unfortunately, existing engines for Reo provide a very limited support for data-sensitive connectors, even though data constraints are captured by the original semantic models for Reo. In our approach to execute Reo coordination constraints are not exhaustively solved at compile time but at runtime on a per-need basis, powered by existing constraint and SMT (satisfiability module theories) solvers. Predicate abstraction is used to reduce the original constraint satisfaction problem to a SAT problem, and applied to a restricted class of connectors that benefit from this mechanism. We show soundness and completeness of predicate abstraction, and validate our approach by evaluating the performance of a prototype implementation with different test cases, with and without abstraction.
Optical character recognition: An overview and an insight

Many researches are going on in the field of optical character recognition (OCR) for the last few decades and a lot of articles have been published. Also a large number of OCR is available commercially. In this literature a review of the OCR history and the various techniques used for OCR development in the chronological order is being done.
RATE-OF-SPEECH MODELING FOR LARGE VOCABULARY CONVERSATIONAL SPEECH RECOGNITION

Variations in rate of speech (ROS) produce changes in both spectral features and word pronunciations that affect automatic speech recognition (ASR) systems. To deal with these ROS effects, we propose to use parallel, rate-specific, acoustic models: one for fast speech, the other for slow speech. Rate switching is permitted at word boundaries, to allow modeling within-sentence speech rate variation, which is common in conversational speech. Due to the parallel structure of ratespecific models and the maximum likelihood decoding method, we do not need high-quality ROS estimation before recognition, which is usually hard to achieve. In this paper, we evaluate our approach on a large-vocabulary conversational speech recognition (LVCSR) task over the telephone, with several minimal pair comparisons based on different baseline systems. Experiments show that on a development set for the 2000 Hub-5 evaluation, introducing word-level ROS-dependent models results in a 1.9% absolute win over a baseline system without multiword pronunciation modeling, and a 0.7% absolute win over a baseline system that incorporates a 4.0% absolute win from multiword pronunciation modeling. The combination of rate-dependent acoustic models with rate-dependent pronunciations obtained by using a data-driven approach is also explored and shown to produce an additional win.