Miracle-dz/UniFAR-FTUs huggingface dataset:
International Journal of Innovative Technology and Exploring Engineering (IJITEE)

5166 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number L27711081219/2019©BEIESP DOI: 10.35940/ijitee.L2771. 1081219  Abstract: In this paper, 8x8x8 3D-DCT/IDCT processor based on CORDIC architecture for high data rate of image processing and video coding with reduced hardware has been presented. It uses two stages of CORDIC DCT processor i.e. one is 1D-DCT and another one is 2D-DCT processor based on fully pipelined unfolded CORDIC architecture with RAM buffer. The one-dimensional DCT is useful in processing of speech waveforms. For images and video signal processing, we need a 3D version of the DCT/IDCT data, especially in coding for compression and decompression, for its best performance. This processor performs both the DCT and IDCT simultaneously with the help of CORDIC algorithm of both 3D-DCT and IDCT which has boost the speed of the processor. Ease the use of less computation based unfolded CORDIC architecture in the processor reduces complexity and power consumption. With the working frequency approximately 414 MHz less power dissipation, low latency and high throughput can be obtained. The processor has been implemented on Xilinx ISE 14.7 and design is simulated in DE-2 board. This processor has not only reduces the complication but also increases the speed which lead to broad use in image and video processing.
Evaluation of the Patients, Doctors and Nurses View Points about Patient Bill of Rights in Rasht Public Hospitals

Background & Objective: With the aim to clarify the rights of the patients on the basis of medical ethic norms, Patient Bill of Rights in five categories was developed in Iran for the first time, during 2002. The main objective of this study was to determine the views of patients, physicians and nurses about this aspect of medical ethics and its necessity to comply in Rasht public hospitals. Materials & Methods: In this cross-sectional study the data were collected by filling a reliable and validated questionnaire consisting of demographic and 25 specific questions about the rights of patients, these questions were answered by 185 patients, 22 nurses and 14 doctors. Each of the criteria necessary to use was measured by the Likert scale from zero )com-pletely disagree) to five (fully agree). SPSS software 16 and one way ANOVA tests were used for data analysis. Result: The results showed that all groups were agreeing with the necessity to have a bill and consider the patients’ rights during treatment )P<0.05(. But the most controversial point were related to the rights of patient to have access to their information and the right to choose and decide )P<0.05(. However, 68.2 percent of physicians, 80.05 percent of nurses, and 93 percent of patients were agreed with the Bill of Rights. Conclusion: Although all the groups were agreed with the patient’s Bill of rights )P<0.05(, It seems it is necessary to re-consider the issue of providing the necessary information to the patient and give attention to their choices and decisions by the medical health service providers.
Person Attribute Extraction from the Textual Parts of Web Pages

We present a web mining system that clusters persons sharing the same name and also extracts bibliographical information about them. The input of our system is the result of web search engine queries in English or in Hungarian. For system evaluation in English, our system (RGAI) participated in the third Web People Search Task challenge [1]. The chief characteristics of our approach compared to the others are that we focus on the raw textual parts of the web pages instead of the structured parts, we group similar attribute classes together and we explicitly handle their interdependencies. The RGAI system achieved top results on the person attribute extraction subtask, and average results on the person clustering subtask. Following the shared task annotation principles, we also manually constructed a Hungarian person disambiguation corpus and adapted our system from English to Hungarian. We present experimental results on this as well.
μ-Oxido-bis[(chloroacetato-κO)triphenylantimony(V)]

The Sb atom in the centrosymmetric title complex, [Sb2(C6H5)6(C2H2ClO2)2O], has a distorted trigonal–bipyramidal geometry. The bridging oxide O atom occupies one of the axial sites, while the O atom of the chloroacetate ligand occupies the other.
Does malaria control impact education? Evidence from Roll Back Malaria in Africa

Relying on microeconomic data, we examine the impact of the Roll Back Malaria (RBM) control campaigns on the educational attainment of primary school children in 14 Sub-Saharan African countries. Combining a difference-in-differences approach with an IV analysis, we exploit exogenous variation in pre-campaign malaria prevalence and exogenous variation in exposure to the timing and disbursements of the RBM campaign. In all 14 countries, the RBM campaign reveals itself as a particularly cost-effective strategy to improve primary school children's educational attainment.
Cross-Organizational and Cross-Border IS/IT Collaboration: A Literature Review

The topic of collaboration in cross-organizational and cross-border settings is an emerging subfield of information systems research. This paper presents a compressive literature review of 52 research papers, published from 2000 to 2007, in four leading journals. The focus of the analysis are topics of investigation, sources of data, and the underlying theories. The results indicate that most of the research still focuses on a limited number of technical issues related to inter-organizational systems adoption. The identified research gaps which represent promising research opportunities are discussed.
Efficient Rate-Distortion Optimized Media Streaming

This thesis considers the problem of finding optimal transmission strategies in ratedistortion optimized media streaming over a packet erasure channel with random delay. A compressed media stream, such as an audio or video stream, that is split into a set of usually interdependent data units, is to be sent to a receiver for instant playback. The data unit dependencies are modeled as a directed acyclic graph. The goal is to find transmission strategies that minimize the expected playback distortion for a given transmission rate and the loss and delay characteristics of the channel. We show that the problem can be solved in two steps. The first step is to find all optimal transmission policies for a single data unit, the second step is to combine these optimal transmission policies into optimal transmission strategies for a group of interdependent data units. We develop algorithms for both steps. For the first step, we propose branch and bound algorithms that are exact and faster than all previously proposed methods. We also propose branch and bound algorithms for the second step. They are much slower than previously proposed methods, but they are the only algorithms that are exact for any data unit dependency structure. For the special case where the dependencies between data units can be represented as a tree, we propose more efficient dynamic programming algorithms that are exact as well. We develop two heuristics to make these dynamic programming algorithms suitable for application in a practical streaming system. One heuristic reduces the computational complexity of the algorithms, the other one constructs trees for arbitrary dependency structures. Although exactness is lost by the use of these heuristics, experimental results show that the solutions found are better than the solutions found by previously proposed heuristic methods. In addition to channel simulations, the methods presented in this thesis are also evaluated in a practical streaming system on an Internet connection.
Adipocyte microinfiltration in the face or tissue restructuration with fat tissue graft

L'auteur presente son experience de la microgreffe de tissu adipeux pour la restructuration tissulaire des volumes de la face, qu'il prefere nommer microinfiltration adipocytaire ou MIA de la face. La graisse du corps est recoltee sans traumatisme par liposuccion a la seringue puis est conditionnee avec un minimum de manipulations et delicatement mise en place en un tressage de cylindres graisseux par des microcanules aux courbures anatomiques brevetees. Cette technique, nommee par Coleman Lipostructure®, permet de conserver les greffons au sein des tissus environnants: muscle, peau, perioste ou tissu conjonctif. Cette procedure la differencie du concept de « filling » decrit en 1989 par P. Fournier sous le nom de « liposculpture ». En traitant la microinfiltration adipocytaire comme une greffe tissulaire, et en respectant la cellule graisseuse dans sa fragilite et sa particularite, l'auteur rapporte une serie de resultats tres satisfaisants avec un recul de plus de 3ans.
Hybrid Tracking for Augmented Reality GIS Registration

This paper describes the work to resolve registration problem of augmented reality geographic information system (ARGIS). ARGIS is composed of AR system and 3DGIS, 3DGIS can provide detailed models and 3D map of the real world for AR system, so ARGIS is actually an outdoor augmented reality system. In this paper, we present a hybrid tracking method for registration in ARGIS, by using data from GPS receiver and inertial sensors, observer position and orientation can be approximately determined in 3DGIS; therefore a 2D screen image can be generated from 3DGIS. This screen image should be similar to real world image taken by a camera at the same position and direction in the real world. Therefore, the main work of the registration in ARGIS is to match real image with screen image. We introduce virtual marks to make the match result to be stable and fast, and accordingly to realize precise registration. Experiment shows that the method is efficient and promising.
ERP Revelations: The Dyamics of Contextual Forces of ERP Implementation

This paper reports the findings of an in-depth case study of implementing Enterprise Resource Planning Systems (ERP) in a long-established multinational company within the telecommunication sector. The company streamlined its operations through an ambitious business process redesign initiative and introduced an ERP system. The study examines the emergence of the ERP system and the mangle of simultaneous changes to the system and to the company context, along with the intentions and actions of the individuals involved. The study seeks to understand the ERP implementation process, in particular, the link between the ERP implementation process and the underlying and often subtle influences within the context. By drawing on the case study the paper offers a theoretical conceptualization of triggers and consequences of the cycles of control and drift of ERP implementation.
Incremental Tag Suggestion for Landmark Image Collections

In recent social media applications, descriptive information is collected through user tagging, such as face recognition, and automatic environment sensing, such as GPS. There are many applications that recognize landmarks using information gathered from GPS data. However, GPS is dependent on the location of the camera, not the landmark. In this research, we propose an automatic landmark tagging scheme using secondary regions to distinguish between similar landmarks. We propose two algorithms: 1) landmark tagging by secondary objects and 2) automatic new landmark recognition. Images of 30 famous landmarks from various public databases were used in our experiment. Results show increments of tagged areas and the improvement of landmark tagging accuracy.
Mathematical Software: Proceedings of the First International Congress of Mathematical Software Beijing, China 17-19 August 2002

Software Engineering Problems for Mathematical Software: Designs of Programming languages for Mathematics Data Structures for Mathematics Standards to Allow Cooperation Review of Internal Structures of Systems Tricks in Real Implementations Mathematics and Media (Including User Interfaces) Mathematics Related to Mathematical Software (Experiments, Algorithms) High Performance Computing Applications of Mathematical Software Presentation of Mathematical Software and other papers.
Improving Innovative Work Behavior and Organizational Performance through Workplace Spirituality and Perceived Organizational Support

Business organizations enter an environment that is very difficult to predict. Improving employee behavior in innovation and the performance of the organization for creating competitive advantages is very urgent for the sustainability business organization. Workplace spirituality and perceived organizational support are two factors that can be used to boost the innovative work of the employee and organizational performance. The purposes of this research were (1) to explain and describe how to improve innovative work behavior and organizational performance using workplace spirituality (2) to explain and describe how to improve innovative work behavior and organizational performance through perceived organizational support. This research considered as descriptive research. Data collection method used library research and the Internet. The results of this study were (1) in improving innovative work behavior and organization performance through workplace spirituality can be done by creating a meaningful company condition, creating a sense of community, and creating an alignment of values. (2) In improving innovative work behavior and organizational performance through perceived organizational support can be done by creating corporate justice, providing support from corporate leaders and creating organizational rewards and good working conditions. Keywords—workplace spirituality; perceived organizational support; innovative work behavior; organizational performance
STUDIES OF ORDERED NANOPARTICLE MONO- AND MULTILAYERS

Surfactant stabilized colloidal nanoparticles represent an important class of nano-materials due to their low size dispersion and moderate production costs. The production of monodisperse (< 12%) metal nanoparticles (diameter 6-12 nm) was elaborated. Large area ordered nanoparticle mono (2D)and multilayer (3D) assemblies (up to 25 cm 2 ) were prepared by a modified Langmuir-Schaefer deposition. The grazing-incidence small-angle X-ray scattering (GISAXS) technique was applied for analysis of the 2D and 3D nanoparticle assemblies. Appropriate simulation software has been developed for GISAXS evaluation including 3D nanoparticle assemblies. Using the GISAXS technique the vertical correlation of the nanoparticle position in the nanoparticle multilayer was studied. The examples of the presence and absence of the vertical ordering in nanoparticle multilayers are presented.
Challenges in Electrochemical Aptasensors and Current Sensing Architectures Using Flat Gold Surfaces

In recent years, reagentless aptamer biosensors, named aptasensors, have shown significant advancements. Particularly, electrochemical aptasensors could change the field of biosensors in this era, where digitalization seems to be a common goal of many fields. Biomedical devices are integrating electronic technologies for detecting pathogens, biomolecules, small molecules, and ions, and the physical-chemical properties of nucleic acid aptamers makes them very interesting for these devices. Aptamers can be easily synthesized and functionalized with functional groups for immobilization and with redox chemical groups that allow for the conversion of molecular interactions into electrical signals. Furthermore, non-labeled aptamers have also been utilized. This review presents the current challenges involved in aptasensor architectures based on gold electrodes as transducers.
Content-Independent Speaker Recognition System based on Neural Networks

In this research, we tried to build the content-independent speaker recognition system with neural networks. We built the speaker recognition system with RNN, CNN and RNN-CNN to distinguish the voice of 2 speakers. The results showed that for all of the 3 networks, the accuracy is obviously higher than random choice. It is proved that neural network is an effective approach to extract the
A STUDY ON CONTENT-ORIENTED CODING SCHEME AND DECODER DOWNLOADABLE SYSTEM

Content-oriented coding is the one that takes the characteristics of the image content into account. Natural and synthetic images have different characteristics. However, JPEG/ MPEG employs DCT regardless of the image content. Thus, their coding schemes are not optimized for synthetic images; such as animation images and computer graphics. As a promising application of the content-oriented coding, we have been studying animation image coding that is mainly based on line and region extraction. Currently, a fixed coding algorithm has been used for all kind of images in the broadcasting application. An approach to switch coding algorithm for image contents has a chance to provide better coding efficiency as a whole than the conventional one. Thus, it is important to establish a certain mechanism distributing different decoders depending on the contents for real time applications. In this paper, we propose a scheme to improve coding efficiency of animation images and mechanism to download necessary decoders in real time.
List-decodeable Linear Regression

We give the ﬁrst polynomial-time algorithm for robust regression in the list-decodable setting where an adversary can corrupt a greater than 1 / 2 fraction of examples. For any α < 1 , our algorithm takes as input a sample { ( x i , y i ) } i ≤ n of n linear equations where αn of the equations satisfy y i = (cid:104) x i , (cid:96) ∗ (cid:105) + ζ for some small noise ζ and (1 − α ) n of the equations are arbitrarily chosen. It outputs a list L of size O (1 /α ) - a ﬁxed constant - that contains an (cid:96) that is close to (cid:96) ∗ . Our algorithm succeeds whenever the inliers are chosen from a certiﬁably anti-concentrated distribution D . As a corollary of our algorithmic result, we obtain a ( d/α ) O (1 /α 8 ) time algorithm to ﬁnd a O (1 /α ) size list when the inlier distribution is standard Gaussian. For discrete product distributions that are anti-concentrated only in regular directions, we give an algorithm that achieves similar guarantee under the promise that (cid:96) ∗ has all coordinates of the same magnitude. To complement our result, we prove that the anti-concentration assumption on the inliers is information-theoretically necessary. To solve the problem we introduce a new framework for list-decodable learning that strengthens the “identiﬁability to algorithms” paradigm based on the sum-of-squares method.
A New Look at the Structures of Old Sepsis Actors by Exploratory Data Analysis Tools

Sepsis is a life-threatening condition that accounts for numerous deaths worldwide, usually complications of common community infections (i.e., pneumonia, etc), or infections acquired during the hospital stay. Sepsis and septic shock, its most severe evolution, involve the whole organism, recruiting and producing a lot of molecules, mostly proteins. Proteins are dynamic entities, and a large number of techniques and studies have been devoted to elucidating the relationship between the conformations adopted by proteins and what is their function. Although molecular dynamics has a key role in understanding these relationships, the number of protein structures available in the databases is so high that it is currently possible to build data sets obtained from experimentally determined structures. Techniques for dimensionality reduction and clustering can be applied in exploratory data analysis in order to obtain information on the function of these molecules, and this may be very useful in immunology to better understand the structure-activity relationship of the numerous proteins involved in host defense, moreover in septic patients. The large number of degrees of freedom that characterize the biomolecules requires special techniques which are able to analyze this kind of data sets (with a small number of entries respect to the number of degrees of freedom). In this work we analyzed the ability of two different types of algorithms to provide information on the structures present in three data sets built using the experimental structures of allosteric proteins involved in sepsis. The results obtained by means of a principal component analysis algorithm and those obtained by a random projection algorithm are largely comparable, proving the effectiveness of random projection methods in structural bioinformatics. The usefulness of random projection in exploratory data analysis is discussed, including validation of the obtained clusters. We have chosen these proteins because of their involvement in sepsis and septic shock, aimed to highlight the potentiality of bioinformatics to point out new diagnostic and prognostic tools for the patients.
Vertex Entropy as a Critical Node Measure in Network Monitoring

Understanding which node failures in a network have more impact is an important problem. Current understanding, motivated by the scale free models of network growth, places emphasis on the degree of the node. This is not a satisfactory measure; the number of connections a node has does not capture how redundantly it is connected into the whole network. Conversely, the structural entropy of a graph captures the resilience of a network well, but is expensive to compute, and, being a global measure, does not attribute any specific value to a given node. This lack of locality prevents the use of global measures as a way of identifying critical nodes. In this paper we introduce local vertex measures of entropy which do not suffer from such drawbacks. In our theoretical analysis we establish the possibility that our local vertex measures approximate global entropy, with the advantage of locality and ease of computation. We establish properties that vertex entropy must have in order to be useful for identifying critical nodes. We have access to a proprietary event, topology and incident dataset from a large commercial network. Using this dataset, we demonstrate a strong correlation between vertex entropy and incident generation over events.
Application of hybrid compression and converging technology in wireless sensor network routing protocol in China

In order to give full play to the advantages of wireless sensor and make use of the restriction of it, it is very important to study and design the proper routing protocol and data fusion. In this paper, the basic structure, characteristics and classification of wireless sensor networks were discussed systematically, and several typical routing protocols were introduced and compared. Based on the analysis of existing network layer routing protocols and key technologies, the network layer routing protocols and their key technologies in wireless sensor networks were studied. Finally, the conclusions that the data compression rate is basically a fixed value, and the influence of the depth of the ternary tree is very small, which can greatly increase the scalability of the network were drawn.
Relation Prediction for Unseen-Entities Using Entity-Word Graphs

Knowledge graphs (KGs) are generally used for various NLP tasks. However, as KGs still miss some information, it is necessary to develop Knowledge Graph Completion (KGC) methods. Most KGC researches do not focus on the Out-of-KGs entities (Unseen-entities), we need a method that can predict the relation for the entity pairs containing Unseen-entities to automatically add new entities to the KGs. In this study, we focus on relation prediction and propose a method to learn entity representations via a graph structure that uses Seen-entities, Unseen-entities and words as nodes created from the descriptions of all entities. In the experiments, our method shows a significant improvement in the relation prediction for the entity pairs containing Unseen-entities.