Miracle-dz/UniFAR-FTUs huggingface dataset:
LSDH: A Hashing Approach for Large-Scale Link Prediction in Microblogs

One challenge of link prediction in online social networks is the large scale of many such networks. The measures used by existing work lack a computational consideration in the large scale setting. We propose the notion of social distance in a multi-dimensional form to measure the closeness among a group of people in Microblogs. We proposed a fast hashing approach called Locality-sensitive Social Distance Hashing (LSDH), which works in an unsupervised setup and performs approximate near neighbor search without high-dimensional distance computation. Experiments were applied over a Twitter dataset and the preliminary results testified the effectiveness of LSDH in predicting the likelihood of future associations between people.
Investigations on Modeling and Simulation of Printed Folded Dipole Antenna

We have modeled and simulate asymmetric microstrip folded dipole antenna on substrate materials and study the antenna performances. The conventional wire dipole antenna configurations are converted into corresponding microstrip version. The complementary nature of parallel coplanar strip line and waveguide models have been used to model the dipole antenna. The transmission line parameters namely, even-odd mode effective dielectric constant and characteristic impedance have been analyzed. We study the effect of dielectric material on radiation characteristics of the printed folded dipole antenna, such as effective dielectric constant, characteristics impedance, input impedance and bandwidth. The antenna shows bandwidth improvement below 3 GHz frequency with asymmetric form of strip folded dipole.
EFFECTIVE THRESHOLDING OF ANCIENT DEGRADED MANUSCRIPT FOLIO IMAGES

Thresholding is an essential procedure used in image segmentation and binarization applications. In this paper, segmentation methods applied on document images for separating the text from background presents pure binarization and filtering combined with image processing algorithms. This paper describes a contrast based thresholding method for old degraded manuscript images. It is an approach for degraded manuscript and document images by introducing an estimation of the threshold value. This technique effectively segments the texts from badly degraded document background. The method is suitable for segmentation of document images with complex and uneasy background having unreadable text. Proposed method performs segmentation using contrast estimating a threshold and exhaustively uses discrete gray level values. The proposed method broadly evaluated on more than 100 degraded manuscript images. The result shows the readable text in the improved images produced by the proposed method. Experiments confirm the effectiveness of the proposed method compared to standard thresholding methods. In research, the proposed method produced better results than standard thresholding methods for original manuscript images.
Nonlinear adaptive control for teleoperation systems transitioning between soft and hard tissues

Teleoperation systems in the medical usage, allows a surgeon to perform a remote distance operation with or without magnification. There is an increasing need to provide telerobots with the ability to interact with unknown and hybrid environments to detect the abnormalities and also performing the diagnostic procedures. In such environments it is challenging to guarantee the whole system stability. In this research, a nonlinear adaptive control for one degree of freedom endoscopic teleoperation system has been proposed. The force and position controllers are designed for both master and slave sides. Lyapunov theory has been used to guarantee stability and performance of the system, in presence of unknown environmental stiffness. Numerical simulations are presented on teleoperation system to demonstrate the effectiveness of the proposed scheme.
Cloning and Characterization of EF-Tu and EF-Ts from Pseudomonas aeruginosa

Elongation factors (EF) facilitate many steps in the process of the biosynthesis of proteins. EF‐Tu in particular plays a central role in the GTP‐dependent placement of aminoacylated tRNA at the A site on the ribosome. EF‐Ts acts by catalyzing the change of EF‐Tu from a GDP‐bound inactive state to a GTP‐bound active state.
Implicit Coordination with Shared Belief: A Heterogeneous Robot Soccer Team Case Study

A striking aspect of human coordination is that we achieve it with little or no communication. We achieve this implicit coordination by taking the perspective of others and inferring their intentions. In contrast, robots usually coordinate explicitly through the extensive communication of utilities or intentions. In this paper we present a method that combines both approaches: implicit coordination with shared belief. In this approach, robots first communicate their beliefs about the world state to each other, using a CORBA-based communication module. They then use learned utility prediction models to predict the utility of each robot locally. Based on these utilities, an action is chosen. Within a heterogeneous soccer team, with robots from both the Munich and Ulm research groups, we apply implicit coordination with shared belief to a typical task from robotic soccer: regaining ball possession. An empirical evaluation demonstrates that the redundancy of implicit coordination with shared belief leads to robustness against communication failure and state estimation inaccuracy.
An Energy Efficient Network Life Time Enhancement Proposed Clustering Algorithm for Wireless Sensor Networks

Wireless sensor networking is an emerging technology that promises a wide range of potential applications in both civilian and military areas. A wireless sensor network (WSN) typically consist of a large number of low cost, low power and multi-functional sensor nodes that are deployed in a region of interest. Wireless sensor networks face many challenges caused by communication failures, storage and computational constraints and limited power supply. In WSN, the nodes are battery driven and hence energy saving of sensor nodes is a major design issue. Energy efficient algorithms must be implemented so that network lifetime should be prolonged. Lifetime of a network can be maximized through clustering algorithms, where cluster is responsible for sending the data to the base station and not all the nodes are involved in data transmission . various clustering algorithms are deployed in past few years. In this paper we are proposing an algorithm which is a combination of Bacterial foraging optimization algorithm (BFO) which is a Bio-Inspired algorithm and LEACH and HEED protocols which enhances the lifetime of a network by dissipating minimum amount of energy.
Temperature dependence of optical dephasing in an organic polymer glass (PMMA) from 300 K to 30 K

The temperature dependence of the optical dephasing mechanism in an organic polymer glass, polymethylmethacrylate (PMMA), was studied from 300 K to 30 K using the dye IR144 as a probe. Transient grating and three pulse photon echo measurements were made, and the three pulse photon echo peak shift (3PEPS) was recorded as a function of temperature. The peak shift data reveal time constants of ∼6 fs and ∼60 fs, along with vibrational beats and a long-time constant value for the peak shift. The 6 fs component is attributed to intramolecular vibrations and the 60 fs component to librational degrees of freedom of the PMMA itself. This contribution appears slightly underdamped and the fitted spectral density matches well with the Raman spectrum of PMMA. The two ultrafast decays are insensitive to temperature. For temperatures above 80 K the long-time peak shift increases linearly as temperature decreases but at 80 K the shift levels off and decreases for temperatures between 80 and 30 K. Fit values for the inhom.
Classifying Unsolicited Bulk Email (UBE) using Python Machine Learning Techniques

Email has become one of the fastest and most economical forms of communication. However, the increase of email users has resulted in the dramatic increase of spam emails during the past few years. As spammers always try to find a way to evade existing filters, new filters need to be developed to catch spam. Generally, the main tool for email filtering is based on text classification. A classifier then is a system that classifies incoming messages as spam or legitimate (ham) using classification methods. The most important methods of classification utilize machine learning techniques. There are a plethora of options when it comes to deciding how to add a machine learning component to a python email classification. This article describes an approach for spam filtering using Python where the interesting spam or ham words (spam-ham lexicon) are filtered first from the training dataset and then this lexicon is used to generate the training and testing tables that are used by variety of data mining algorithms. Our experimentation using one dataset reveals the affectivity of the Naive Bayes and the SVM classifiers for spam filtering.
Searching Continuous State Spaces Eeectively Using Critical Points Keywords: Search or Optimization, Multi-agent Simulation Tracking Number: A396 the Problem: Deening States in Continuous Domains the Solution: Critical Points

Many artiicial intelligence techniques rely on the notion of a \state" as an abstraction of the actual state of the world, and an \operator" as an abstraction of the actions that take you from one state to the next. Much of the art of problem solving depends on choosing the appropriate set of states and operators. However, in realistic, and therefore dynamic and continuous search spaces, nding the right level of abstraction can be dif-cult. If too many states are chosen, the search space becomes intractable; if too few are chosen, important interactions between operators might be missed. If the state boundaries are not at the right place, the results of the search will not be meaningful in the real world. We present the idea of critical points as way of dynamically deening state boundaries; new states are generated as part of the process of applying operators. In addition to allowing the use of standard search and planning techniques in continuous domains, critical points enable the incorporation of multiple agents, dynamic environments, and non-atomic variable length actions into the search algorithm. We conclude with examples of implemented systems that show how critical points are used in practice. Many conventional artiicial intelligence techniques rely on clearly deened state spaces and operators to transition from one state to the next. Classical search and problem solving algorithms (see (Korf 1988) for a survey), theorem provers, and STRIPS-based planners (Fikes & Nilsson 1971; 1993) share the assumption that the world can naturally be divided into states, and that what happens as we move from one state to the next is something that can safely be abstracted away. For simple and discrete problems, deening the state space is indeed often quite straightforward. However, realistic continuous spaces pose a much more diicult problem. In a continuous search space, for example the domain of robot path planning, there is in principle an innnite number of ways to partition the search space into states. The choice of states is intimately linked to the choice of operators, since the operators aaect changes in state. When choosing an operator set, one is also implicitly stating that these are the actions that should be considered atomic. The formulation of the problem space gives rise to an interesting trade-oo. If the operators are too primitive, and correspondingly the state space large, the solution to a given problem will involve a deeper search …
Do we really know that the EU´s Single Market Programme has fostered competition? Testing for a decrease in markup ratios in EU industries.

Using a sample of 10 European countries and 17 industries covering the period 1981 to 1999, we test whether the EU's Single Market Programme had a significant procompetitive effect in terms of a reduction in firms' markups over marginal costs. In the framework of the markup estimation method suggested by Roeger (1995), we employ a panel approach for each of the sectors to test for both an instantaneous structural change between 1989 and 1993 as well as a continuous change in parameters using smooth transition analysis. The results do not indicate a pervasive pro-competitive effect of the Single Market. While markup reductions are found for aggregate manufacturing as of 1993, it is also suggested that markups increased in several sectors in the pre-completion period around the end of the 80s. This is likely to be due to strong increase in concentration and average firm size at the EU level in the second half of the 1980s. After all, the Single Market's net effect on markups is likely to be negligible if not positive. (author's abstract)
Daedalus: A sUAV for Human-Robot Interaction

This paper presents an interface for enabling a sUAV robot (Daedalus) to communicate and simulate emotional states. As significance is the result of the interpretation of emotional states, an experimental study was performed to evaluate and recognize emotion-state responses from people when interacting with the sUAV. Four expressions were programmed combining Daedalus’ interaction features such as head movement and eye color display. During the assessment, subjects were asked to recognize the significance of the expressions performed by the robot and assign an emotional state of the robot through card selection. Our research aims to investigate the impact of simulating emotional states in robots, and its potential during interaction. Results presented are part of an experimental study for setting future exploratory research concerning human-robot interaction.
I Know What You Coded Last Summer: Mining Candidate Expertise from GitHub Repositories

Resumes and social recommendations are often high-level indicators of a candidate's technical skillset. In this paper, we present a method to create a more detailed technology skill profile of a candidate based on her code repository contributions. For this purpose, we annotate user contributions to GitHub code repositories with technology tags found in Stack Overflow questions and answers (Q&A) in an unsupervised manner. We also present SkillMap, a visual representation of candidate skill profile, for quick review and comparison with other candidate profiles. We create SkillMaps for 66 Java programmers and present a preliminary qualitative assessment though manual analysis and interviews of technical recruiters.
Pseudo-Boolean Heuristics for 0-1 Integer Linear Programming

Many Integer Linear Programming (ILP) problems contain significant subproblems exclusively composed of 0-1 (binary) variables. Much effort has gone in to special solvers for 0-1 ILP, as well as specialized versions of 0-1 ILP. The boolean satisfiability problem (SAT), is fundamental to many fields, including Artificial Intelligence, Formal Verification, and Computer Aided Design, and can be viewed as a specialized 0-1 ILP problem. Recent developments in cutting plane generation for the SAT problem has resulted in large performance improvements, which has resulted in the SAT problem being much more widely applied. One such area is Pseudo-Boolean Programming (PBP), which is a somewhat less restricted variant of 0-1 ILP. Recent PBP solvers have found SAT based techniques to be of use, which is interesting, given the very restricted form of the SAT problem. However, not enough attention has been paid to how SAT based techniques for PseudoBoolean Programming complement ILP solvers such as CPLEX. In this work, we explore the use of a modern PBP solver, Minisat+, integrated as a heuristic into CPLEX. Although some papers on PBP solvers do compare thmeselves against modern ILP solvers like CPLEX and Xpress-MP, overall there is a paucity of comparison between ILP and PBP solvers in the literature. This is likely due to the relative isolation between the SAT community, which evolved out of Computer Science theory and Artificial Intelligence, and the Operations Research community, which views ILP problems as a complication of Linear Programming. The work on SAT based PBP solvers recently has been connected with the SAT community, for example, the 2005 PB Competition was held as a track of the 2005 SAT Competition [1]. The 2005 PB Competition did not even include any ILP solvers, since it was focused on SAT-based solvers. This is strange, since ILP solvers do very well when directly benchmarked against PBP solvers, for example [2], [3], [4].
On Diversity and Multiplexing Gain of Multiple Antenna Systems with Transmitter Channel Information

We quantify the multiplexing-diversity tradeoff of a multiple-input multiple-output (MIMO) system, when the channel state information (CSI) is known perfectly at the receiver and partially at the transmitter. The partial knowledge of CSI at the transmitter consists of the quantized value of one of the eigenvalues and perfect knowledge of eigenvectors of the channel matrix. The key result is that while multiplexing gain cannot be increased beyond minimum number of transmit and receive antennas, diversity order for each multiplexing gain can be substantially increased by using only a few bits of feedback at the transmitter. For example, with 1 bit of feedback in a 2× 3 system, for multiplexing gains of 0, 1, and 2, diversity gains of 42, 6, and 2 can be achieved, respectively. Thus, while the tradeoff between diversity advantage and multiplexing gain is still present, its behavior is significantly changed by channel knowledge at the transmitter. The major reason for this different tradeoff can be attributed to addition of long-term power control, which allows the transmitter to switch between modes for reducing outage and increasing throughput based on signal to noise ratio along different eigenvalues.
Is Bilateralism Bad?

In the 1980s the process of trade liberalization through multilateral negotiation seems to have run aground. In its place there have been a number of bilateral and regional moves toward liberalization. Some have been concerned that these local deals may, by undermining the multilateral process, actually reduce world trade and welfare. This paper develops a simple model of the effects of regional trading blocs, and shows that consolidation of the world into a smaller number of such blocs may indeed reduce welfare, even when each bloc acts to maximize the welfare of its members. Indeed, for all plausible parameter values world welfare is minimized when there are three trading blocs. More complex versions of the model offer softer results, but the main thrust is still to validate concern over the effects of bilateral and regional trade deals.
I see you: How to improve wearable activity recognition by leveraging information from environmental cameras

In this paper we investigate how vision based devices (cameras or the Kinect controller) that happen to be in the users' environment can be used to improve and fine tune on body sensor systems for activity recognition. Thus we imagine a user with his on body activity recognition system passing through a space with a video camera (or a Kinect), picking up some information, and using it to improve his system. The general idea is to correlate an anonymous ”stick figure” like description of the motion of a user's body parts provided by the vision system with the sensor signals as a means of analyzing the sensors' properties. In the paper we for example demonstrate how such a correlation can be used to determine, without the need to train any classifiers, on which body part a motion sensor is worn.
On the Incorporation of Secure Filter in ICMetrics Group Communications

Secure group communications present a unique environment where there can be multiple clients and hosts are trying to communicate securely within the group. As the number of clients and hosts increases the complexity of the communication security also increases. Group communications are based on a dynamic environment where the clients may join or leave the group at any moment. Hence it is important to ensure that only permitted entities have access to the group and those that have left the group or are not part of the group have no access to the group communications. This paper explores the delineation of a secure communication filter function that is applicable to group communications and is based on the latest Integrated Circuits Metrics (ICMetrics). The proposed scheme is based on the use of hash functions. To test the scalability of the scheme it has been implemented using SHA1 and SHA2.
Detecting and Describing Historical Periods in a Large Corpora

Many historic periods (or events) are remembered by slogans, expressions or words that are strongly linked to them. Educated people are also able to determine whether a particular word or expression is related to a specific period in human history. The present paper aims to establish correlations between significant historic periods (or events) and the texts written in that period. In order to achieve this, we have developed a system that automatically links words (and topics discovered using Latent Dirichlet Allocation) to periods of time in the recent history. For this analysis to be relevant and conclusive, it must be undertaken on a representative set of texts written throughout history. To this end, instead of relying on manually selected texts, the Google Books Ngram corpus has been chosen as a basis for the analysis. Although it provides only word n-gram statistics for the texts written in a given year, the resulting time series can be used to provide insights about the most important periods and events in recent history, by automatically linking them with specific keywords or even LDA topics.
Estimation of microbial nitrogen flow to the duodenum of cattle based on dry matter intake and diet composition.

The objectives of this study were: 1) to evaluate the National Research Council equation used to predict microbial N flow to the duodenum in lactating cows, and 2) to determine whether improved equations could be developed by using dietary parameters used in the field. Treatment means from 55 trials with lactating and nonlactating cattle with duodenal cannulas were subjected to the backward elimination procedure of multiple regression. Variation within and among trials was accounted for by weighting the observations and including trial effects in all models. The equations to predict microbial N flow based on net energy for lactation (NEL) intake were different from the equation based on NEL intake used by the dairy National Research Council. Dry matter intake (DMI) estimated microbial N flow as well as did NEL intake, indicating that DMI drives predictions based on NEL intake. When multiple dietary factors [i.e., DMI; dietary percentages of crude protein, forage, and neutral detergent fiber; and all two-way interactions] were included, the resulting equation [microbial N (grams per day) = 16.1 + 22.9 x DMI (kilograms per day) - 0.365 x DMI2 - 1.74 x dietary neutral detergent fiber (percentage of dry matter)] tended to fit the data better than the equations based on NEL intake but not better than the equation based on DMI alone. The multiple-factor equation appeared to be the best overall equation for prediction; in contrast to the equation based on DMI, this equation is sensitive to diet composition. An asymptotic multiple-factor equation was developed, which may be more appropriate when extrapolating beyond the data range.