Miracle-dz/UniFAR-FTUs huggingface dataset:
RELIABLE AND ENHANCED ENERGY EFFICIENT REACTIVE ROUTING PROTOCOL FOR IWSNS

With the upcoming evolutionary technologies, Wireless sensor networks have made and gained worldwide attention in many applications. Sensor nodes are very small and are spatially deployed over the large target area to sense, measure, gather information and finally to transmit the data to the users. Industrial wireless sensor network have many advantages and applications. One of the challenging issues in IWSN is to provide reliable and efficient communication that to especially in dynamic and rough environment. The existing reactive routing protocols have limitations. In this work, secured and reliable reactive routing protocol is introduced to increase the energy efficiency, low delivery latency, to improve the packet delivery ratio. Another important is the introduction of special scheme called biased back-off scheme during the route-discovery phase. The aim of this scheme is to amplify the traversing delays. And along the guide path nodes carry out the transmission. Nodes involved in the transmission uses the nodes co-operation without the help of location information.
Computing Ratings and Rankings by Mining Feedback Comments

In Online section, the Reputation based trust models are extremely important for growth. We are intended to design framework, which is utilizes the perception made by user (generally to express conclusions about the item in free content criticism survey). Depending on criticism survey, remarks, feedback, comment, ratings are mined. In this framework, we have proposed a multidimensional trust model for registering notoriety scores from client input remarks. Furthermore we introduced opinion mining, or sentiment analysis on free text documents which has computing aspect ratings from overall ratings in feedback comments or reviews (positive or negative). Their aspect ratings and weights are computed based on regression from overall ratings and the positive bias in overall ratings is the focused goal. A calculation is proposed for mining criticism remarks which are utilized for weights and appraisals of measurement; regular dialect preparing consolidating strategies, supposition mining, and point displaying. By Implementing Hybrid Approach for comment analysis using kNN (K- nearest neighbor) and LDA (Latent Dirichlet allocation) Algorithm, We will rest describe our approach based on the typed dependency analysis to extracting aspect opinion expressions and identifying their associated ratings using KNN algorithm. In Las phase LDA algorithm is used for clustering dimension expressions into dimensions and computing dimension weights.
Improving dependency parsing using word clusters

This thesis describes a semi-supervised approach to improving statistical dependency parsing using word clusters as features in MaltParser, a data-driven transition-based dependency parser. We experiment with using different clustering features for generating clusters, using the minibatch variant of the K-means algorithm. The clusters are used as a source of additional information in an expanded feature model used by the MaltParser system. A baseline parser is applied to unlabeled text, generating a dependency representation of the text. K-means is then used for generating word clusters based on this dependency representation. We then re-train the parser with information on these clusters by using a cluster-informed feature model, having all the baseline feature functions, but expanded with addition cluster feature functions, making this an instance of semi-supervised learning. We report significantly improved parsing results when using a cluster-informed parser compared to the baseline parser, using both in-domain and out-of-domain data.
Quality metric for spherical panoramic video

Virtual reality (VR)/ augmented reality (AR) applications allow users to view artificial content of a surrounding space simulating presence effect with a help of special applications or devices. Synthetic contents production is well known process form computer graphics domain and pipeline has been already fixed in the industry. However emerging multimedia formats for immersive entertainment applications such as free-viewpoint television (FTV) or spherical panoramic video require different approaches in content management and quality assessment. The international standardization on FTV has been promoted by MPEG. This paper is dedicated to discussion of immersive media distribution format and quality estimation process. Accuracy and reliability of the proposed objective quality estimation method had been verified with spherical panoramic images demonstrating good correlation results with subjective quality estimation held by a group of experts.
Progress in Piezo‐Phototronic‐Effect‐Enhanced Light‐Emitting Diodes and Pressure Imaging

Wurtzite materials exhibit both semiconductor and piezoelectric properties under strains due to the non‐central symmetric crystal structures. The three‐way coupling of semiconductor properties, piezoelectric polarization and optical excitation in ZnO, GaN, CdS and other piezoelectric semiconductors leads to the emerging field of piezo‐phototronics. This effect can efficiently manipulate the emission intensity of light‐emitting diodes (LEDs) by utilizing the piezo‐polarization charges created at the junction upon straining to modulate the energy band diagrams and the optoelectronic processes, such as generation, separation, recombination and/or transport of charge carriers. Starting from fundamental physics principles, recent progress in piezo‐phototronic‐effect‐enhanced LEDs is reviewed; following their development from single‐nanowire pressure‐sensitive devices to high‐resolution array matrices for pressure‐distribution mapping applications. The piezo‐phototronic effect provides a promising method to enhance the light emission of LEDs based on piezoelectric semiconductors through applying static strains, and may find perspective applications in various optoelectronic devices and integrated systems.
Asynchronous proactive cryptosystems without agreement

In this paper, we present efficient asynchronous protocols that allow to build proactive cryptosystems secure against a mobile fail-stop adversary. Such systems distribute the power of a public-key cryptosystem among a set of servers, so that the security and functionality of the overall system is preserved against an adversary that crashes and/or eavesdrops every server repeatedly and transiently, but no more than a certain fraction of the servers at a given time. The building blocks of proactive cryptosystems - to which we present novel solutions - are protocols for joint random secret sharing and for proactive secret sharing. The first protocol provides every server with a share of a random value unpredictable by the adversary, and the second allows to change the shared representation of a secret value. Synchronous protocols for these tasks are well-known, but the standard method for adapting them to the asynchronous model requires an asynchronous agreement sub-protocol. Our solutions are more efficient as they go without such an agreement sub-protocol. Moreover, they are the first solutions for such protocols having a bounded worst-case complexity, as opposed to only a bounded average-case complexity.
Mesoporous Silica Nanoparticles: Synthesis, Biocompatibility and Drug Delivery

In the past decade, mesoporous silica nanoparticles (MSNs) have attracted more and more attention for their potential biomedical applications. With their tailored mesoporous structure and high surface area, MSNs as drug delivery systems (DDSs) show significant advantages over traditional drug nanocarriers. In this review, we overview the recent progress in the synthesis of MSNs for drug delivery applications. First, we provide an overview of synthesis strategies for fabricating ordered MSNs and hollow/rattle‐type MSNs. Then, the in vitro and in vivo biocompatibility and biotranslocation of MSNs are discussed in relation to their chemophysical properties including particle size, surface properties, shape, and structure. The review also highlights the significant achievements in drug delivery using mesoporous silica nanoparticles and their multifunctional counterparts as drug carriers. In particular, the biological barriers for nano‐based targeted cancer therapy and MSN‐based targeting strategies are discussed. We conclude with our personal perspectives on the directions in which future work in this field might be focused.
A Comparative Study of Different Strategies using adaptive Differential Evolution for Best Scheduling in Architectural Level Synthesis

This paper is a comparative study for optimal scheduling in architectural level synthesis using five different strategies in Differential Evolution. In this paper the comparison is performed using Hardware Abstraction Layer (HAL) benchmark scheduling problem using Integer Linear Programming method. The paper implements adaptive scaling factor for mutation operation and variable cross over operation in differential evolution. The experiment results evaluate the performance parameters optimal resource schedule, convergence time among the five strategies are presented.
Realization of YAFFS2 in the Embedded System

Aiming at the characteristics of a large amount of system programs and real-time storage of a great deal of data for a long time,while the small capacity storage of current embedded system can not meet the requirements,the solution of combining big page NAND FLASH with YAFFS2 file system is put forward based on the characteristics of FLASH which can repeatedly erase and permanently preserve data.The problem of the system′s mass storage is solved satisfactoryly by the transplantation of the Bootloader and embedded Linux kernel,and the establishment of YAFFS2 file system.The results verify the feasibility of the program.
Synthesis and Characterization of Altaicadispirolactone

Abstract Altaicadispirolactone was synthesized via a simple route. In this route, levulinic acid was used as a starting material, and bromination followed by hydrolysis and BF3 · OEt2‐catalyzed cyclization were carried out. A single‐crystal ORTEP drawing has been created and more detailed crystallographic data of the compound has been obtained from X‐ray analysis.
The transition to syntax : influences on children’s constructional complexity

The complexity of children's l i n g u i s t i c constructions i n conversation during the t r a n s i t i o n from single-word to multiword speech was measured i n s i x conditions produced by manipulating the adult i n t e r a c t i o n v a r i a b l e s , f a m i l i a r i t y , attention, and conversational c o n t r o l . Subjects were four c h i l d r e n , ages 1 ;9 to 2;3, and t h e i r mothers. The children's constructions were categorized according to three l e v e l s of complexity (single words, v e r t i c a l constructions, h o r i z o n t a l constructions), i n four tasks (high attention, low attention, high c o n t r o l , low c o n t r o l ) , during dialogues with t h e i r mothers, then with strangers. While t h e i r proportion of complex to l e s s complex constructions was not r e l a t e d to adult f a m i l i a r i t y or a t t ention, c h i l d r e n produced s i g n i f i c a n t l y more complex constructions (p = .005) when they c o n t r o l l e d the conversation. Further analyses of the children's frequency of constructions demonstrated that the c h i l d r e n talked more to t h e i r mothers than to strangers, and more given high adult attention than low adult attention. These findings have important implications for c l i n i c a l language sampling and therapy procedures. Table of
Sequence learning through PIPE and automatic task decomposition

Analog gradient-based recurrent neural nets can learn complex prediction tasks. Most, however, tend to fail in case of long minimal time lags between relevant training events. On the other hand, discrete methods such as search in a space of event-memorizing programs are not necessarily affected at all by long time lags: we show that discrete "Probabilistic Incremental Program Evolution" (PIPE) can solve several long time lag tasks that have been successfully solved by only one analog method ("Long Short-Term Memory" — LSTM). In fact, sometimes PIPE even outperforms LSTM. Existing discrete methods, however, cannot easily deal with problems whose solutions exhibit comparatively high algorithmic complexity. We overcome this drawback by introducing filtering, a novel, general, data-driven divide-and-conquer technique for automatic task decomposition that is not limited to a particular learning method. We compare PIPE plus filtering to various analog recurrent net methods.
Multilevel analysis : an introduction to basic and advanced multilevel modeling

Multilevel theories, multi-stage sampling, and multilevel models -- Statistical treatment of clustered data -- The random intercept model -- The hierarchical linear model -- Testing and model specification -- How much does the model explain? -- Heteroscedasticity -- Missing data -- Assumptions of the hierarchical linear model -- Designing multilevel studies -- Other methods and models -- Imperfect hierarchies -- Survey weights -- Longitudinal data -- Multivariate multilevel models -- Discrete dependent variables -- Software.
Multiobjective clonal selection algorithm for solving forecasting problems

The multiobjective modified clonal selection algorithm based on the use of the notion “Pareto dominance”, which can be applied for the development of the forecasting models on the base of the strictly binary trees has been offered. It is suggested to use the affinity indicator based on the average forecasting error rate, and the tendencies discrepancy indicator in the role of the objective functions of this algorithm. The multiobjective modified clonal selection algorithm can be applied for solving problems of individual and groups’ forecasting. The experimental results which confirm the efficiency of the offered algorithm in comparison with the basic modified clonal selection algorithm have been given.
A study of execution strategies for openCypher on Apache Flink

The concept of big data has become popular in recent years due to the growing demand of handling datasets of large sizes. A lot of new frameworks have been proposed to deal with the problem of processing, analysis and storage of big data. As one of them, Apache Flink is an open source platform allowing for distributed stream and batch data processing. Cypher, a declarative query language developed by Neo4j, shows its significant strengths when it encounters graph database compared to traditional relational query languages. However, by now the newest released version of Cypher still has limitations on its data parallelism and scalability. In this thesis, we first formulate an algebra for expressing Cypher queries. Then we describe the implementation of basic operators of Cypher algebra on Flink that allows the representation of a subset of Cypher queries. To our knowledge, there is no previous work in this field. Based on our observations, a cost-based query optimizer and a rule-based query optimizer are proposed to build efficient query plans. We compare the performance of these two query optimizers and finally analyze the advantages and disadvantages of these two optimization strategies. A Study of Execution Strategies for openCypher on Apache Flink iii
The integrals in Gradshteyn and Ryzhik. Part 30: Trigonometric functions

The table of Gradshteyn and Ryzhik contains many integrals that involve trigonometric functions. Evaluations are presented for integrands containing products of trigonometric functions and products of trigonometric functions and Legendre polynomials, logarithms, Bessel functions, and the Gauss hypergeometric function.
Mapping surface roughness and sediment texture of an estuarine intertidal flat using ERS-2 SAR imagery

Synoptic information on surface characteristics of estuarine intertidal flats, such as surface roughness and sediment texture, is required to support coastal management. This study aims to derive such information from space-borne Synthetic Aperture Radar. Estimates of the backscatter coefficient σ 0 were extracted from ESA ERS-2 SAR PRI imagery (acquired during low tide), of an intertidal flat in the Westerschelde, southwest Netherlands. The data were related to matching field measurements of surface roughness (RMSz) and mud content. A significant positive relationship was found between surface roughness and the backscatter coefficient. Surface roughness was also significantly correlated with mud content, with surface ripples being more pronounced in sand than in mud. This resulted in a significant negative correlation between mud content and the backscatter coefficient. The relationships found are used to map the surface characteristics from ERS-2 SAR imagery.
Evaluation of DVB-H Broadcast Systems Using New Radio Channel Models

The commonly used channel model for mobile reception has been the 6-tap Typical Urban (TU6) model developed by the European COST207 project in 1989. The CELTIC WingTV project discovered that TU6 does not model the DVB-H channel, particularly pedestrian use cases, very well. An extensive field measurement campaign was carried out and new channel models were created based on the measurements in 2006. The new models cover pedestrian indoor, pedestrian outdoor, vehicular urban and motorway use cases and are used for evaluation of DVB-H broadcast systems in this report. Simulations were performed for different modulation modes and code rates and the simulation results were compared to laboratory and field measurements. It was concluded that the use of Multi Protocol Encapsulation Forward Error Correction (MPE-FEC) at the link layer is not needed in the pedestrian use cases, whereas the vehicular use cases show considerable MPE-FEC coding gains. The study on parameter selection leads to five recommended options for combinations of modulation, convolutional and MPE-FEC code rates for networks covering all modeled use cases.
Computing with Nearby Mobile Devices: A Work Sharing Algorithm for Mobile Edge-Clouds

As mobile devices evolve to be powerful and pervasive computing tools, their usage also continues to increase rapidly. However, mobile device users frequently experience problems when running intensive applications on the device itself, or offloading to remote clouds, due to resource shortage and connectivity issues. Ironically, most users’ environments are saturated with devices with significant computational resources. This paper argues that nearby mobile devices can efficiently be utilised as a crowd-powered resource cloud to complement the remote clouds. Node heterogeneity, unknown worker capability, and dynamism are identified as essential challenges to be addressed when scheduling work among nearby mobile devices. We present a work-sharing model, called Honeybee, using an adaptation of the well-known work stealing method to load balance independent jobs among heterogeneous mobile nodes, able to accommodate nodes randomly leaving and joining the system. The overall strategy of Honeybee is to focus on short-term goals, taking advantage of opportunities as they arise, based on the concepts of proactive workers and opportunistic delegator. We evaluate our model using a prototype framework built using Android and implement two applications. We report speedups of up to four with seven devices and energy savings up to 71 percent witheight devices.
Heuristic Evaluation of Prototypes (individual)

Goals The goal of this assignment is to learn how to perform a heuristic evaluation of a real user interface design. Overview You have been hired as a consultant to another group in the class. They are building a new user interface for their course project, but they would like some outside assistance in finding some problems with their prototype interface. Evaluation You will perform a heuristic evaluation (individually) of their user interface using only the materials they turned in for their last project report (" Interactive Prototype " write-up & working demo). Using their tasks, scenarios, interface design, screen shots, and interactive prototype you will apply Nielsen's heuristics to the user interface. You should be able to get all of this information from their web page. Read their report first and then examine their prototype (i.e., run it). Your evaluation will use both the information in the written report and the prototype. Please use the second set of heuristics from my lecture slides on heuristic evaluation (also described in Nielsen's chapter) and the numbering scheme from my lecture slides (e.g., 2-1, 2-2, etc.). You will produce a report showing the problems in the interface. Report Your report will list each of the problems found in the following format: problem# [heuristic violated] description of problem and reasoning why you think this violates the heuristic For example: 1. [H2-4 Consistency & Standards] The interface used the string " Save " on the first screen for saving the user's file, but used the string " Write file " on the second screen. Users may be confused by this different terminology for the same function. 2. [H2-3 User Control & Freedom] The interface brings the user into a set of preference screens when they select " New User " , but doesn't allow the user out of the dialog until they fill out all four screens. There is no way to cancel from any of the screens if a user came into the first screen by accident.
Validation of the probabilistic methodology to generate actual inhabitants' behavior schedules for accurate prediction of maximum energy requirement

A data set of myriad and time-varying inhabitant-behavior schedules with a 15-minute time resolution, generated by the authors in a previous study, is validated through a comparison analysis. We show three comparisons. The first and second compare the estimated demand with a time series of actual utility demand. The comparisons indicate that the generated data and its algorithm, described by the authors, have an appropriate robustness. Another comparison between the estimate and the annual averaged daily water demand of a residential area, consisting of 9,327 residences, also shows an acceptable consistency.
An Unsupervised Classification Technique for Detection of Flipped Orientations in Document Images

Detection of text orientation in document images is of preliminary concern prior to processing of documents by Optical Character Reader. The text direction in document images should exist generally in a specific orientation, i.e., text direction for any automated document reading system. The flipped text orientation leads to an unambiguous result in such fully automated systems. In this paper, we focus on development of text orientation direction detection module which can be incorporated as the perquisite process in automatic reading system. Orientation direction detection of text is performed through employing directional gradient features of document image and adapts an unsupervised learning approach for detection of flipped text orientation at which the document has been originally fed into scanning device. The unsupervised learning is built on the directional gradient features of text of document based on four possible different orientations. The algorithm is experimented on document samples of printed plain English text as well as filled in pre-printed forms of Telugu script. The outcome attained by algorithm proves to be consistent and adequate with an average accuracy around 94%.