Miracle-dz/UniFAR-FTUs huggingface dataset:
Attendance Monitoring System Using Face Recognition

Initially the database which contains the images of all the student’s will be created. The model is fixed in the class in such a way that all the student’s faces are captured clearly. Once the teacher enters/finishes the class then they have to login to the model then the camera will take the picture of whole class. Then image will be cropped into individual student and cropped image will be updated on the main server automatically. So that every student has the clarity of their attendance. In other words there is a transparency between student and teacher about attendance. Including to this, model also provide several features such as Automatic attendance percentage calculation and if a student absent for one class automatic message will be sent to the respective proctors and if a student absent for consecutive three classes automatic message will send to the respective proctors as well as parents. Status of attendance will be sent to the parents as well as students for every month. This system is more secure than the existing system and also requires less time to take the attendance.
ISOMORPHIC FACTORISATIONS. I: COMPLETE GRAPHS

An isomorphic factorisation of the complete graph Kj, is a partition of the lines of Kp into t isomorphic spanning subgraphs G; we then write G\Kj, and G G K^/t. If the set of graphs Ky/t is not empty, then of course t\p(p — l)/2. Our principal purpose is to prove the converse. It was found by Laura Guidotti that the converse does hold whenever (/,/>) » 1 or (t,p — 1) «= 1, We give a new and shorter proof of her result which involves permuting the points and lines of Kp. The construction developed in our proof happens to give all the graphs in K6/3 and K,/3. The Divisibility Theorem asserts that there is a factorisation of JÇ into t isomorphic parts whenever / dividesp(p — l)/2. The proof to be given is based on our proof of Guidotti's Theorem, with embellishments to handle the additional difficulties presented by the cases when t is not relatively prime top orp — 1.
Low-rank separable states are a set of measure zero within the set of low-rank states

It is well known that the set of separable pure states is measure zero in the set of pure states. We extend this fact and show that the set of rank-r separable states is measure 0 in the set of rank-r states provided r is less than ${\ensuremath{\prod}}_{i=1}^{p}{n}_{i}+p\ensuremath{-}\ensuremath{\sum}{n}_{i}. $
Improvements in accuracy of single camera terrain classification

Autonomous terrain classification is an important requirement for robotic applications for the outdoor and more so for off-road systems. Different technique have been developed in recent years mainly relying on either color features or on texture-based features for classification. We present an approach which combines the two approaches and delivers an overall increase in performance and accuracy. We describe the computational framework, training dataset, off-line learning and real-time classification results of our system. We report overall average classification accuracies in excess of 98% in a fair experimental setup along with confusion matrices. Our method gives a noticeable improvement in accuracy for classifying similar terrain classes over the current state of the art that uses only texture for classification with acceptable overhead for real-time applications.
Proficient D-HEED Protocol for Maximizing the Lifetime of WSN and Comparative Performance Investigations with Various Deployment Strategies

In this paper, work has been extended to prolong the lifetime and energy proficiency of wireless sensor network. An idea of deterministic HEED has been proposed that take care of cluster head which has not been elected in 1/pi rounds. Here the comparative investigations have been reported to ascertain the performance of HEED, Multilevel Heterogeneous-Hybrid Energy Efficient Distributed Protocol (MH-HEED) and the Deterministic-HEED (D-HEED) for Wireless Sensor Network (WSN) in case of different deployment strategies. The results envisage that there is increase of about 364.3%, 268.7% & 300% comparing D-HEED over H-HEED, whereas this increase is about 25%, 22.9% &15.38% over MH-HEED in case of circular, grid and rectangular deployment strategies respectively.
Mining defect reports for predicting software maintenance effort

Software Maintenance is the crucial phase of software development lifecycle, which begins once the software has been deployed at the customer's site. It is a very broad activity and includes almost everything that is done to change the software if required, to keep it operational after its delivery at the customer's end. A lot of maintenance effort is required to change the software after it is in operation. Therefore, predicting the effort and cost associated with the maintenance activities such as correcting and fixing the defects has become one of the key issues that need to be analyzed for effective resource allocation and decision-making. In view of this issue, we have developed a model based on text mining techniques using the statistical method namely, Multi-nominal Multivariate Logistic Regression (MMLR). We apply text mining techniques to identify the relevant attributes from defect reports and relate these relevant attributes to software maintenance effort prediction. The proposed model is validated using `Camera' application package of Android Operating System. Receiver Operating Characteristics (ROC) analysis is done to interpret the results obtained from model prediction by using the value of Area Under the Curve (AUC), sensitivity and a suitable threshold criterion known as the cut-off point. It is evident from the results that the performance of the model is dependent on the number of words considered for classification and therefore shows the best results with respect to top-100 words. The performance is irrespective of the type of effort category.
Transposition game

We introduce a two-player game, in which each player extends a given sequence by picking a free element in a domain D ⊂ R. The aim of the players is to control the parity of the number of transpositions necessary to put the final sequence in order. We will see that the winner can be the last player, the second last player, the first player, the second player, the person who wants the parity to end up even or the person who wants the parity to end up odd. A special case of the game can be reduced to a game with nontrivial winning strategy, but describable in so simple a way that children can understand it and enjoy playing it.
AN APPROACH TO THE STUDY OF A DEVELOPING ECONOMY BY OPERATIONAL GAMING

Abstract : The possible use of operational gaming, or simulation involving human players, to examine an economy as a whole is considered. It is believed that this operations research technique could become an extremely useful tool for the study of a developing economy. In the present state of the art it is not going to provide, with confidence, direct recommendations on what to do about matters of national policy. Rather it is an educational device, providing both ideas and insights, useful for the generation and preliminary comparison of alternative economic policies.
On the Maximum Likelihood Approach for Source and Network Localization

We consider the source and network localization problems, seeking to strengthen the relationship between the Weighted-Least-Square (WLS) and the Maximum-Likelihood (ML) solutions of these problems. To this end, we design an optimization algorithm for source and network localization under the principle that: a) the WLS and the ML objectives should be the same; and b) the solution of the ML-WLS objective does not depend on any information besides the set of given distance measurements (observations). The proposed Range-Global Distance Continuation (R-GDC) algorithm solves the localization problems via iterative minimizations of smoothed variations of the WLS objective, each obtained by convolution with a Gaussian kernel of progressively smaller variances. Since the last (not smoothed) WLS objective derives directly from the ML formulation of the localization problem, and the R-GDC requires no initial estimate to minimize it, final result is maximum-likelihood approach to source and network localization problems. The performance of the R-GDC method is compared to that of state-of-the-art techniques such as semidefinite programming (SDP), nonlinear Newton least squares (NLS), and the Stress-of-a-MAjorizing-Complex-Objective-Function (SMACOF) algorithms, as well as to the Cramér-Rao Lower Bound (CRLB). The comparison reveals that the solutions obtained with the R-GDC algorithm is insensitive to initial estimates and provides a localization error that closely approaches that of the corresponding fundamental bounds. The R-GDC is also found to achieve a complexity order comparable to that of the SMACOF, which is known for its efficiency.
p53 and K-ras mutations in lung cancers from former and never-smoking women.

Somatic p53 mutations are common in lung cancer. Active cigarette smoking is positively correlated with the total frequency of p53 mutations and G:C to T:A transversions on the nontranscribed (DNA coding) strand. Mutational hotspots within the p53 gene, e.g., codon 157, have been identified for tobacco-related lung cancer, whereas these same mutations are found rarely in other cancers. Such data implicate specific p53 mutations as molecular markers of smoking. Because limited data exist concerning the p53 mutation frequency and spectra in ex-smokers and nonsmokers, we have analyzed p53 and K-ras mutations in 126 lung cancers from a population-based case-control study of nonsmoking (n = 117) or ex-smoking (n = 9) women from Missouri with quantitative assessments of exposure to environmental tobacco smoke. Mutations in the p53 gene were found in lung cancers from lifetime nonsmokers (19%) and ex-smokers (67%; odds ratio, 9.08; 95% confidence interval, 2.06-39.98). All deletions were found in tumors from patients who were either ex-smokers or nonsmokers exposed to passive smoking. The G:C to A:T transitions (11 of 28; 39%) were the most frequent p53 mutations found and clustered in tumors from lifetime nonsmokers without passive smoke exposure. The incidence of K-ras codon 12 or 13 mutations was 11% (14 of 115 analyzed) with no difference between long-term ex-smokers and nonsmokers. These and other results indicate that p53 mutations occur more commonly in smokers and ex-smokers than in never-smokers. Such comparisons provide additional evidence of genetic damage caused by tobacco smoke during lung carcinogenesis.
An ECMAScript compiler for the .NET framework

Since the publication of the standard that describes the multi-language framework known as common language infrastructure (CLI), it has been a challenge letting non class-based programming languages being run on the CLI. ECMAScript, being a prototype-based, object-oriented, functional programming language, belongs to this category. Running ECMAScript programs in the CLI offers a scripting language with the efficiency of a strong typed language but keeping its dynamic nature. Features like first class functions, late binding, and dynamic objects are not included in CLI by default, so the purpose of this compiler is to show that those features can be implemented using the CLI. Among the characteristics that we measured are the ability to store functions in data structures, passing them as parameters and returning them as values, and the possibility of adding new properties to already defined objects. It's possible to implement first class functions as well as dynamic objects with a cost in the size of the code generated, but also increases the flexibility of the programs that make use of them, allowing the use of software patterns which are rarely used in conventional programming languages.
A review on gesture recognition using kinect

Kinect provides an interesting interaction between user and device with controller-free entertainment environment. It has been used widely in various fields; research, surveillance, medical, entertainment and etc. It is necessary for user to communicate and control a device in natural and efficient way in human-robot interaction based. Hand-controllers and electromechanical device have been used by humans to control robots or machines but there were some constraints in several factors of interaction. As of that, gesture recognition techniques were introduced to overcome those problems. Three sensors in Kinect; an infrared camera, an infrared laser projector and a color camera are used to track and recognize skeletal and human body. In this paper, analysis on gesture recognition in Kinect will be discussed. Several techniques will be compared and the best gesture recognition technique in term of accuracy and efficiency will be chosen in the end of study. At the end of the study, a technique will be proposed to increase the precision of the human gesture recognition using Kinect for better performance in human-robot interaction.
Barcelona Economics Working Paper Series Does Money Matter in Shaping Domestic Business Cycles? an International Investigation (with Appendices) Does Money Matter in Shaping Domestic Business Cycles? an International Investigation

We study the contribution of money to business cycle ‡uctuations in the US, the UK, Japan, and the Euro area using a small scale structural monetary business cycle model. Constrained likelihood-based estimates of the parameters are provided and time instabilities analyzed. Real balances are statistically important for output and in ‡ation ‡uctuations. Their contribution changes over time. Models giving money no role provide a distorted representation of the sources of cyclical ‡uctuations, of the transmission of shocks and of the events of the last 40 years. the participants of the TRIO 2008 conference and of several seminars for comments and suggestion, and Paolo Surico and Matteo Ciccarelli for helping us with the collection of the data. The …nancial support of the Spanish Ministry of Education through the grants SEJ2006-02235 and ECO2009-08556 and of the Barcelona Graduate School of Economics is gratefully acknowledged.
MADIDS: a novel distributed IDS based on mobile agent

When traditional IDS (Intrusion Detection System) is used to detect and analyze the great flow data transfer in high-speed network, it usually causes the computation bottleneck. This paper presents a new Mobile Agent Distributed IDS (MADIDS) system basing on the mobile agents. This system is specifically designed to process the great flow data transfer in high-speed network. In MADIDS, the agents that are set at each node process the data transfer by distributed computation. Meanwhile by using the reconfiguration quality of the mobile agents, the load balance of distributed computation can be dynamically implemented to gain the high-performance computing ability. This ability makes the processing of great flow data transfer possible. MADIDS can effectively solve the detection and analysis performance bottleneck caused by the great flow data transfer in high-speed network. And the performance of IDS is enhanced. In this paper, we construct the infrastructure and theoretical analysis model of MADIDS. The deficiencies of MADIDS and future research works are also indicated.
Prolongs Survival of Tumor-Bearing Mice Relaxin-Expressing , Fiber Chimeric Oncolytic Adenovirus

Selective replication of oncolytic viruses in tumor cells provides a promising approach for the treatment of human cancers. One of the limitations observed with oncolytic viruses currently used in the treatment of solid tumors is the inefficient spread of virus throughout the tumor mass following intratumoral injection. Data are presented showing that oncolytic adenoviruses expressing the relaxin gene and containing an Ad5/Ad35 chimeric fiber showed significantly enhanced transduction and increased virus spread throughout the tumor when compared with non–relaxin-expressing, Ad5based viruses. The increased spread of such viruses throughout tumors correlated well with improved antitumor efficacy and overall survival in two highly metastatic tumor models. Furthermore, nonreplicating viruses expressing relaxin did not increase metastases, suggesting that high level expression of relaxin will not enhance metastatic spread of tumors. In summary, the data show that relaxin may play a role in rearranging matrix components within tumors, which helps recombinant oncolytic adenoviruses to spread effectively throughout the tumor mass and thereby increase the extent of viral replication within the tumor. Expressing relaxin from Ad5/Ad35 fiber chimeric adenoviruses may prove a potent and novel approach to treating patients with cancer. [Cancer Res 2007;67(9):4399–407]
An efficient FPGA implementation of a DT-CNN for small image gray-scale pre-processing

This paper presents an 8-bit FPGA implementation of a Discrete Time Cellular Neural Network (DTCNN) suitable for small image gray-scale pre-processing (simple operations with high computational burden). It uses Split&Shift techniques to have a 31 × 31 grid that processes more than 2500 images per second. As this work evolves from a previous binary DTCNN implementation, results are compared in terms of area occupancy, routing complexity and processing time. Several design tech­niques have been applied to optimize the VHDL implementation on an Altera Stratix II-EP2S60F484C5 FPGA device. Moreover, as technology independent description allows easy migration to other devices or vendors, the benefits of FPGA technology evolution are discussed, focusing on DTCNN implementations.
The potentials of Network Coding for improvement of Round Trip Time in wireless Narrowband RF communications

This paper shows the potentials of Network Coding (NC) for improvement of Round Trip Time (RTT) in practical wireless Narrowband RF communications (for remote monitoring of broadcasting Television and radio FM station). We illustrate how RTT changes versus number of hops using narrow band radios modem & Routers (RipEX unit), as a means of transmission between source and destination. As well as, we will illustrate the effect of Forward Error Correction (FEC) on the RTT. The measurements and simulations results show that the applying of NC significantly improves RTT.
Bitrate guarantees strategies for customer virtual networks dynamic reconfiguration

Application-specific Quality of Service (QoS) and additional Service Level Agreement (SLA) parameters to guarantee the committed service quality and avoid service interruption may be crucial in emerging applications and services. Moreover, among the wide range of services over IP transport networks, those requiring bandwidth-on-demand and related to network functions virtualization (NFV) are of particular interest. IETF is working on the Abstraction and Control of Transport Networks (ACTN) framework to facilitate network resources virtualization to support NFV. Customers can request on-demand connectivity between their end-points (EPs) to reconfigure customer virtual network (CVN) topology dynamically. In addition to CVN reconfiguration, QoS constraints and service guarantees can be requested to satisfy application-specific requirements. In this work we study two different approaches to satisfy the committed bitrate guarantees in CVN links. Exhaustive simulation results show that the diversity strategy highly improves performance and provides remarkable CAPEX savings.
The Impact of Time on the Accuracy of Sentiment Classifiers Created from a Web Log Corpus

We investigate the impact of time on the predictability of sentiment classification research for models created from web logs. We show that sentiment classifiers are time dependent and through a series of methodical experiments quantify the size of the dependence. In particular, we measure the accuracies of 25 different time-specific sentiment classifiers on 24 different testing timeframes. We use the Naive Bayes induction technique and the holdout validation technique using equal-sized but separate training and testing data sets. We conducted over 600 experiments and organize our results by the size of the interval (in months) between the training and testing timeframes. Our findings show a significant decrease in accuracy as this interval grows. Using a paired t-test we show classifiers trained on future data and tested on past data significantly outperform classifiers trained on past data and tested on future data. These findings are for a topic-specific corpus created from political web log posts originating from 160 different web logs. We then define concepts that classify months as examplar, infrequent thread, frequent thread or outlier; this classification reveals knowledge on the topic's evolution and the utility of the month's data for the timeframe.
Imaging of Nucleic Acids with Atomic Force Microscopy

Keywords: Atomic force microscopy AFM DNA dynamics DNA nanostructures Holliday junctions RNA assembly RNA nanostructures High-speed AFM a b s t r a c t Atomic force microscopy (AFM) is a key tool of nanotechnology with great importance in applications to DNA nanotechnology and to the recently emerging field of RNA nanotechnology. Advances in the methodology of AFM now enable reliable and reproducible imaging of DNA of various structures, topologies, and DNA and RNA nanostructures. These advances are reviewed here with emphasis on methods utilizing modification of mica to prepare the surfaces enabling reliable and reproducible imaging of DNA and RNA nanostructures. Since the AFM technology for DNA is more mature, AFM imaging of DNA is introduced in this review to provide experience and background for the improvement of AFM imaging of RNA. Examples of imaging different structures of RNA and DNA are discussed and illustrated. Special attention is given to the potential use of AFM to image the dynamics of nucleic acids at the nanometer scale. As such, we review recent advances with the use of time-lapse AFM. Nucleic acid nanotechnology is a branch of nanotechnology that utilizes the ability of nucleic acids to self-assemble into complex three-dimensional (3D) structures. The field of DNA nanotechnol-ogy was established in 80's by pioneering works of N. Seeman in which he demonstrated the possibility to assemble 3D DNA structures such as a cube from DNA oligomers of the well-defined structures (reviewed in [1]). The key elements for the DNA nano-technology are three-way and four-way DNA junctions. These are biologically important DNA structures formed during DNA replica-tion and recombination, respectively. Unlike DNA, which exists primarily as a double helix, RNA molecules are single stranded, so the formation of branched RNA molecules is a rule rather than exception. Loops in branched RNA molecule interact with each other to form a three-dimensional biologically important RNA structure. Unraveling principles by which such structures are formed, stabilized and transit from one into another is a problem of great importance for molecular biology. In addition, understanding the self-assembly principles of RNA open the prospects for engineering of RNA molecules with defined structural properties and desired functionality. This is the area of interest of the recently emerging field of RNA nanotechnology [2–4]. Among different nanoimaging techniques atomic force microscopy (AFM) is the very attractive due to its versatility in imaging of various DNA and RNA nanostructures and the ability …