Miracle-dz/UniFAR-FTUs huggingface dataset:
WIDIPAY: A CROSS-LAYER DESIGN FOR MOBILE PAYMENT SYSTEM OVER LTE DIRECT

Long term evolution direct, plus its features of device-to-device networking and proximate discovery, are new and emerging technologies able to come out of the shadow to render a whole new perspective at mobile payments. In this work, we propose a new mobile payment system using long term evolution direct and its features. A sensitive mobile payment system would require high security requirements in order to be trusted by the users and the businesses. These requirements are taken into account in our proposed system design and solutions to security considerations are provided. The system’s security and usability features are designed for implementation from physical to application layer to address the identified issues. Within the scope of this work, we provided the conceptual design solutions to allow the system to be as solid and secure as possible while they are convenient enough not to degrade user’s experience when using the system.
Digital Video Forgeries Detection Based on Textural Features

This paper proposes a digital video tampering method which uses textural features of video frames.For a video with still background or slow and continuous movement,the correlation of interframe textural features is large and it would become smaller to some extent if tampered.This paper finds out the outliers according to the correlation of the interframe GLCM.This method is unlimited for video format,applied to any kind of video format.Experimental results show that this method can effectively detect video frame tampering including frame insertion and frame substitution of diverse-sourced in the similar background.
Likelihood window, energy window, and Bayesian window for scatter rejection in gamma cameras

All gamma cameras used in nuclear medicine have finite energy resolution. Therefore, they cannot perfectly discriminate scattered from unscattered radiation. Different scatter correction methods have been developed to reduce this effect, but it is better to reject scatter events in data acquisition instead of doing scatter correction afterwards. Most conventional ways of rejecting scatter events use energy windows (EWs). An alternative introduced by Milster et al. (1990) is the likelihood window (LW). The authors use this method in their modular gamma scintillation camera that has a 2/spl times/2 array of photomultipliers (PMTs) coupled to a NaI(Tl) crystal. The authors have developed yet another scatter rejection scheme, the Bayesian window (BW). In contrast to the LW and EW, the BW takes into account the simulated or actual scatter spectrum in making a decision to accept or reject a particular photon. The authors compare the effectiveness of scatter rejection by BW, LW, and EW. <<ETX>>
New reduction strategy of large-scale training sample set for SVM

It has become a bottleneck to use Support Vector Machine(SVM) due to such problems as slow learning speed,large buffer memory requirement,low generalization performance and so on,which are caused by large-scale training sample set and outlier data immixed in the other class.Concerning these problems,this paper proposed a new reduction strategy for large-scale training sample set according to the analysis on the structure of the training sample set based on the point set theory.This new strategy gets the potential support vectors and removes the non-boundary outlier data immixed in the other class by using fuzzy clustering.That can greatly reduce the scale of the training sample set and improve the generalization performance by effectively avoiding over-learning caused by outlier data,and finally speed up learning rate without reducing the classification accuracy.
DanNet: the challenge of compiling a wordnet

This paper is a contribution to the discussion on compiling computa tional lexical resources from conventional dictionaries. It describes the theoretical as well as practical problems that are encountered when reusing a conventional dictionary for compiling a lexical-semantic resource in terms of a wordnet. More specifically, it describes the methodological issues of compiling a wordnet for Danish, DanNet, from a monolingual basis, and not? as is often seen? by applying the translational expansion method with Princeton WordNet as the English source. Thus, we apply as our basis a large, corpus-based printed dictionary of modern
Gender and speciality in business management education

Abstract Undergraduate university enrolment in Canada is characterized by a higher proportion of women to men, with a pattern of gender segregation across some disciplines. Within some disciplines, there is also a pattern of internal sex segregation whereby women and men still sort themselves into gendered sub-fields, a pattern that is particularly evident in undergraduate business management programs. This study set out to understand why this segregation occurs. The study found that men and women use the same criteria in selecting a business major, including beliefs about success and fit, as well as advice from referent others. However, they attach different weight to these factors in a pattern that is gendered. Resume L’effectif universitaire de premier cycle au Canada est caracterise par un ratio plus eleve de femmes par rapport aux hommes, mais avec un modele de segregation entre les sexes dans certaines disciplines. En effet, a l’interieur de certaines disciplines existe un modele de segregation fondee sur le sexe, ou les femmes et les hommes classent encore leurs professions en sous- categories en fonction de leur sexe. Cela est particulierement evident dans les programmes de premier cycle en gestion d’entreprise, et la presente etude visait a comprendre pourquoi cela se produit. L’etude a revele que les hommes et les femmes utilisent les memes criteres dans le choix d’une majeure en etudes commerciales, surtout en ce qui a trait aux croyances quant a la reussite et aux aptitudes, ainsi qu’aux conseils obtenus d’autres references. Toutefois, les femmes et les hommes attachent une importance differente a ces facteurs selon leur sexe.
TFT, Tests For Triplestores

—In March 2013, the W3C recommended SPARQL 1.1 to retrieve and manipulate decentralized RDF data. Real-world usage requires advanced features of Recommendation SPARQL 1.1. As these are not consistently implemented, we propose a software named TFT (Tests For Triplestores) to test the interoperability of the SPARQL endpoint of RDF database sys-tems. To help the developers and end-users of RDF databases, we perform daily tests daily on Jena-Fuseki, Marmotta-KiWistore, 4Store and three other commercial databases. With these tests, we have built a scoring system named SPARQLScore and share our results on the website http://sparqlscore.com.
Preparation and Application of Perchloric Acid Supported on Alumina (Al2O3‐HClO4) to the Synthesis of α‐(α‐Amidobenzyl)‐β‐naphthols

Preparation of perchloric acid supported on alumina and its primary application as a solid supported heterogeneous catalyst to the synthesis of α-(α-amidobenzyl)-β-naphthols by a one-pot, three-component condensation of benzaldehydes, β-naphthol and acetamide or benzamide under thermal solvent-free conditions were described. The present methodology offers several advantages such as simple procedure, shorter reaction time, and excellent yields.
Solvent-Free Synthesis of 3,5-di(Hetero)Aryl-1,2,4-Thiadiazoles by Grinding of Thioamides under Oxidative Conditions

An efficient and facile synthesis of 3,5-di(hetero)aryl-1,2,4-thiadiazoles by oxidative dimerisation of thioamides by grinding with NBS under solvent-free conditions at room temperature has been developed. The efficiency of this reaction was demonstrated by the compatibility with trifluoromethyl, methyl, methoxy, chloro, pyridyl and thienyl groups. This method has notable advantages in terms of short reaction times, high yields and is a more practical alternative to the existing methods to access these compounds.
Error correction method of 6-HTRT parallel mechanics

The method of error correction is one of key techniques of parallel robot. A new method of end error correction of 6-HTRT parallel robot is presented for engineering and researching on correlative theory of 6-HTRT parallel robot. The method need calculate many kinematics equations of parallel robot such as position back solution, velocity Jacobin, position forward solution and error Jacobin. New methods presented for solving these questions are simpler and fitter for programming and calculating, because former methods are too complex to use in engineering. These questions may be solved by iterative method of numerical value which has fast velocity of calculating. These new methods may be used in other mechanism of parallel robot too, and so have wider using value. The experimental results demonstrate that the system may satisfy entirely high technical request and fit for engineering in new measures.
Fingerprints, Facial Recognition and Cancer

Images are unstructured data and are large in computer data storage size. Standard processes for Fingerprint Analysis, Facial Recognition and Treatment of Histopathological images for Diagnosis and Prognosis are utilized to show that an image can be processed to deliver structured data. This structured data is usually subjected to Machine Learning or Artificial Intelligence Analysis run on the associated server. The images themselves could be stored at locations where accession need not be as fast. The latest Artificial Intelligence tool (Deep Learning) is quite impressive and has been used in quite a few applications. The promise of its use with histopathological images could revolutionize the field of Breast Cancer prognosis and perhaps, even better treatments.
Research and Implementation of Interactive Walkthrough in 3D Scene

The paper presents a frame work of interactive walkthrough in 3D scene and focuses mainly on the implementing techniques of walkthrough in 3D space, including walkthrough by keyboard, walkthrough along path, recording path of walkthrough, converting video to files, collision detection. The problem of dithering when walking along the linear spline path and reaching a corner is solved. These techniques have been applied in the developed system and do well.
A Novel Content Based Medical Image Retrieval using SURF Features

Objective: Content Based Image Retrieval (CBIR) has been one of the most vivid research areas in the field of computer vision over the last 10 years. In the medical field, images especially digital images are produced in ever-increasing quantities and used for diagnostics and therapy. Content Based Medical Image Retrieval is an important tool for doctors in their daily activity. Findings: This work describes a method for medical images annotation based on the SURF (Speeded up Robust Features) features. The proposed technique effectively uses most of the information from image is backbone of an efficient Content Based Image Retrieval system for medical databases. In this work the SURF features are used to improve the retrieval accuracy. Methods: The method applies the SURF algorithm in the detection, description, extracting references images and matching feature points in the image respectively. In the process of feature point matching, the false matching points are eliminated through this algorithm. Applications: SURF is fast and robust interest point detector which is used in many computer vision applications. The experimental evaluation is carried out for lung images using SURF features and proposed method provides better outcome.
A WORD VECTOR BASED QUANTIZATION MODEL OF CHINESE WORD SENSE

A word vector based Chinese word sense quantization model is proposed, which can be used to solve problems such as auto acquisition and quantization of word sense information. The modeling method of the model and its applications in the Chinese word sense disambiguation are further described. And then, the model's ability to discriminate word sense is evaluated by constructing pseudoword. The experiment shows that this model has a good representation for word sense. As the construction of model is done via the statistic of large scale rough corpora, huge workload of manually quantization word senses is avoided. So this model can be applied to many word sense related NLP tasks.
A study into the layers of automated decision-making: emergent normative and legal aspects of deep learning

ABSTRACT The paper dissects the intricacies of automated decision making (ADM) and urges for refining the current legal definition of artificial intelligence (AI) when pinpointing the role of algorithms in the advent of ubiquitous computing, data analytics and deep learning. Whilst coming up with a toolkit to measure algorithmic determination in automated/semi-automated tasks might be proven to be a tedious task for the legislator, our main aim here is to explain how a thorough understanding of the layers of ADM could be a first good step towards this direction: AI operates on a formula based on several degrees of automation employed in the interaction between the programmer, the user, and the algorithm. The paper offers a fresh look at AI, which exposes certain vulnerabilities in its current legal interpretation. To highlight this argument, analysis proceeds in two parts: Part 1 strives to provide a taxonomy of the various levels of automation that reflects distinct degrees of human–machine interaction. Part 2 further discusses the intricate nature of AI algorithms and considers how one can utilize observed patterns in acquired data. Finally, the paper explores the legal challenges that result from user empowerment and the requirement for data transparency.
Research progress and prospect of UAV applications in transportation information collection

Based on the flight tests and subsequent studies of unmanned aerial vehicle(UAV),the opportunities and challenges of UAV in traffic information collection,processing and application were analyzed,and the application future of UAV in traffic planning and simulation,road surveillance,emergency dispatch,urban congestion analysis and so on was prospected.Analysis result shows that the traffic information collection method using UAV is effective for continuous traffic information collection and complements existing methods.Traffic information is automatically derived from UAV videos with the development of dynamic video processing technology.UAV traffic information can be used to study emergency responses,car-following,lane-changing behavior,traffic congestion and so on.However,the adaptability of UAV dynamic video processing technology needs to be improved.The research on car-following,lane-changing and traffic congestion using UAV information needs empirical testing.Some important research direction in the future includes the establishment of UAV-ground emergency communication and coordination system,and UAV-vehicle-road coordination communication system.4 figs,30 refs.
Facile Synthesis of Ba1‐xKxFe2As2 Superconductors via Hydride Route.

Ba1-xKxFe2As2 (0 ≤ x ≤ 1) superconductors are prepared by high-energy ball milling of BaH2, KH, and FeAs (containing 6% FeAs2 as impurity) and subsequent annealing (Nb container in evacuated silica tubes, 773—1173 K, 2 d).
The Architecture Of The Mind

Thank you for reading the architecture of the mind. Maybe you have knowledge that, people have search numerous times for their chosen readings like this the architecture of the mind, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious virus inside their desktop computer. the architecture of the mind is available in our book collection an online access to it is set as public so you can download it instantly. Our book servers spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the the architecture of the mind is universally compatible with any devices to read.
Review of Parallel Agent-based Simulation

As an effective approach to study complex systems,the method of Agent-based Modeling and Simulation(ABMS) is used widely in many research fields,but as the scale and complexity of its applications enlarge,the execution speed becomes an obstacle to implement ABMS.Parallel Agent-based Simulation(PABS) aims at reducing the execution time through executing concurrently the Agent models distributed on different process units,which is a direct approach to improve the execution speed.According to the principles of ABMS,the new characteristics of PABS that are different from Parallel Discrete Event Simulation were proposed.The overview about PABS was elaborated from the aspects of time synchronization algorithms,load balancing and communication optimizing.PABS based on general purpose graphics processing units was discussed.At last,some future research directions about PABS were proposed.
Similarity Measurement Based on Thesaurus

During the course of developing knowledge based systems,the similarity measurement of char data type feature is often employed,and using the measurement based on Keywords,the omittance and inaccuracy of measurement is occurred.To resolve this problem,taking the material feature's effect on similarity measurement of aircraft assembly process planning knowledge as an example,the conceptual similarity measurement of character is researched and a kind of similarity measurement based on thesaurus is proposed.The configuration of thesaurus is researched and a model of measurement thesaurus is given.The similarity measurement algorithm based on thesaurus is developed.
Quantified Self & Mobile Health Monitoring

The rapid evolution of mobile phones from mere vessels for voiceand textbased communication to personal assistants with a treasure chest of advanced features has created a new paradigm in mobile applications. The computational power and ubiquity of such devices has generated plenty of interest from the healthcare sector, particularly via the recent parallel development of body worn sensors that can communicate with them wirelessly. There is a strong incentive, both from an economic and an altruistic perspective, to develop mobile applications that enable self-help, patient homecare, and remote disease management. However, very little research exists at present in the field of affecting health change behavior in people through such mobile applications. This thesis proposes a body worn sensor-based mobile platform for the physiotherapeutic treatment of patients suffering from specific back disorders and back pain at home. In particular, this thesis focuses on developing a user interface characterized by persuasive, encouraging and motivational aspects that ensure adherence and compliance with respect to physiotherapeutic exercise regimes prescribed by a physiotherapist.
Design and Implement of GPS/GSM and MSP430-Based Patrolling Hand-hold Terminal

In order to solve the problem of supervising the optical fiber patrolling work, based on GPS and GSM, using the CPU of ultra low power consumption microprocessor MSP430, we developed Patrolling Hand-hold Terminal. The terminal captures the subscriber's current information of location and time through GPS, and sends SMS to the server in the management center through GSM network. The Terminal has the advantages of low power consumption and small size, which make it easy to carry and having a long stand-by time, so it is suitable for outdoor works. Although it is designed for optical fiber patrolling, the Terminal is suitable for any occasion that needs to supervise patrolling workers or gather geographical position information.
Semantic Segmentation of Large-Scale Urban 3D Data with Low Annotation Cost

We present a novel method for the semantic segmentation of 3D data in large-scale urban environment. Our method significantly reduces the intensive labeling cost in previous works by automatically generating training data from the input data. The automatic generation of training data begins with the initialization of training data with weak priors in the urban environment, followed by a filtering scheme to remove mislabeled training samples. We formulate the filtering as a binary labeling optimization problem over a conditional random filed that we call object graph, simultaneously integrating spatial smoothness preference and label consistency between 2D and 3D. Toward the final parsing, with the automatically generated training data, a Conditional Radom Field (CRF) based parsing method that integrates the coordination of image appearance and 3D geometry is adopted to perform the parsing of large-scale urban scenes.
GRACE TECHNICAL REPORTS An Algebraic Approach to Bidirectional Model Transformation

Bidirectional model transformation plays an important role in maintaining consistency between two models, and has many potential applications in software development, including model synchronization, round-trip engineering, software evolution, multiple-view software development, and reverse engineering. However, unclear bidirectional semantics, weak bidirectionalization method, and lack of systematic development framework are known problems that prevent it from being practically used. To remedy this situation, in this paper, we propose a novel algebraic framework for bidirectional model transformation, by integrating the state-of-the-art technologies on bidirectional tree transformations and algebraic graph querying. We make a significant extension from bidirectional tree transformation to bidirectional graph transformation, and give a powerful automatic bidirectionalization method to derive a backward graph transformation from a forward graph transformation. Moreover, we demonstrate how our algebraic framework can support systematic development of efficient large-scale bidirectional model transformations in a compositional manner. Our experimental results show promise of the new approach.
Location Update In Mobile Ad Hoc Network Using Markov Model

The location in a mobile ad-hoc network, where each node needs to maintain its location information. which frequently updating its location information within its neighboring region, which is called neighborhood update (NU). and updating its location information to certain distributed location server in the network, which is called location server update (LSU). The operation costs in location updates and the performance losses of the target application due to location application costs which imposes question for nodes to decide the optimal strategy to update the location information, where the optimality is used for minimizing the costs. The location update decision problem is modeled as a Markov Decision Process (MDP). The monotonicity properties of optimal NU and LSU operations with respect to location application cost under a general cost setting. Separable cost structure shows the location update decisions of NU and LSU. Which can be independently carried out without loss of optimality that is a separation property. From the separation property of the problem structure and the monotonicity properties of optimal actions which finds that 1) there always exists a simple optimal update rule for LSU operations 2) for NU operations. If no prior knowledge of the MDP model is available, then also it introduces a model-free learning approach to find a near-optimal solution for the problem. KeywordsJava markov decision process, Least square policy iteration, Location server update, Location update, Mobile ad hoc network, Markov decision process, Neighborhood update.