Miracle-dz/UniFAR-FTUs huggingface dataset:
SentiTFIDF – Sentiment Classification using Relative Term Frequency Inverse Document Frequency

Sentiment Classification refers to the computational techniques for classifying whether the sentiments of text are positive or negative. Statistical Techniques based on Term Presence and Term Frequency, using Support Vector Machine are popularly used for Sentiment Classification. This paper presents an approach for classifying a term as positive or negative based on its proportional frequency count distribution and proportional presence count distribution across positively tagged documents in comparison with negatively tagged documents. Our approach is based on term weighting techniques that are used for information retrieval and sentiment classification. It differs significantly from these traditional methods due to our model of logarithmic differential term frequency and term presence distribution for sentiment classification. Terms with nearly equal distribution in positively tagged documents and negatively tagged documents were classified as a Senti-stop-word and discarded. The proportional distribution of a term to be classified as Senti-stop-word was determined experimentally. We evaluated the SentiTFIDF model by comparing it with state of art techniques for sentiment classification using the movie dataset.
Fastest parallel molecular algorithms for the elliptic curve discrete logarithm problem over GF(2n)

Cryptography based on Elliptic Curves (ECC) has emerged as an effective alternative to the existing public-key cryptosystems (RSA and DSA). Its success was due both to the fact that no fast algorithms were known to break it and that exceptional security levels could be obtained by using short keys. The Elliptic Curve Discrete Logarithm (ECDL) problem is the cornerstone of much of present-day ECCs. It was classifed as a computationally intractable problem and, consequently, as a reliable and unbreakable cryptosystem. In a recent work, Li et al. built a molecular computer designed to solve it over GF(2n). It was based on two DNA-inspired al gorithms: a parallel adder and a parallel multiplier, working in O(n) and O(n2) respectively, where n is the input size. In this paper, we first present two faster biological implementations, working in O(log(n)) and O(n • log(n))respectively (worst case). Then, we propose our model as a reference parallel solution of the ECDL problem and finally we highlight the computational power of such natureinspired paradigm.
Parallel Processing with MPI for Inter-band Registration in Remote Sensing

Inter-band registration is an essential processing method that is used to generate satellite imagery products with raw data obtained from a high-resolution satellite. The processing method requires considerable time owing to its high computational cost as well as the large-scale data to be processed. In this paper, we present a parallel inter-band registration method on windows-based clusters as part of an effort to reduce the total execution time during product generation. We use a blade system as clusters and the MPICH2 library for the parallel programming tool. We logically divide roles of the nodes into one root node, three sub-root nodes, and several compute nodes. We divide the inter-band registration into sequential and parallel processing areas to design the nodes suitable for inter-band registration. The root node and sub-root nodes control the sequential processing area and exchange data with compute nodes in the parallel processing area. In addition, we introduce an object-oriented pseudo code for easy parallelization using a Message Passing Interface (MPI). We apply our system on the KOMPSAT-2 product generation process. The experimental result shows that our system reduces the total execution time from 330 seconds to 79 seconds.
The Impact of Modelling Rate Heterogeneity among Sites on Phylogenetic Estimates of Intraspecific Evolutionary Rates and Timescales

Phylogenetic analyses of DNA sequence data can provide estimates of evolutionary rates and timescales. Nearly all phylogenetic methods rely on accurate models of nucleotide substitution. A key feature of molecular evolution is the heterogeneity of substitution rates among sites, which is often modelled using a discrete gamma distribution. A widely used derivative of this is the gamma-invariable mixture model, which assumes that a proportion of sites in the sequence are completely resistant to change, while substitution rates at the remaining sites are gamma-distributed. For data sampled at the intraspecific level, however, biological assumptions involved in the invariable-sites model are commonly violated. We examined the use of these models in analyses of five intraspecific data sets. We show that using 6–10 rate categories for the discrete gamma distribution of rates among sites is sufficient to provide a good approximation of the marginal likelihood. Increasing the number of gamma rate categories did not have a substantial effect on estimates of the substitution rate or coalescence time, unless rates varied strongly among sites in a non-gamma-distributed manner. The assumption of a proportion of invariable sites provided a better approximation of the asymptotic marginal likelihood when the number of gamma categories was small, but had minimal impact on estimates of rates and coalescence times. However, the estimated proportion of invariable sites was highly susceptible to changes in the number of gamma rate categories. The concurrent use of gamma and invariable-site models for intraspecific data is not biologically meaningful and has been challenged on statistical grounds; here we have found that the assumption of a proportion of invariable sites has no obvious impact on Bayesian estimates of rates and timescales from intraspecific data.
Transcriptional variation in the malaria parasite Plasmodium falciparum

Malaria genetic variation has been extensively characterized, but the level of epigenetic plasticity remains largely unexplored. Here we provide a comprehensive characterization of transcriptional variation in the most lethal malaria parasite, Plasmodium falciparum, based on highly accurate transcriptional analysis of isogenic parasite lines grown under homogeneous conditions. This analysis revealed extensive transcriptional heterogeneity within genetically homogeneous clonal parasite populations. We show that clonally variant expression controlled at the epigenetic level is an intrinsic property of specific genes and gene families, the majority of which participate in host–parasite interactions. Intrinsic transcriptional variability is not restricted to genes involved in immune evasion, but also affects genes linked to lipid metabolism, protein folding, erythrocyte remodeling, or transcriptional regulation, among others, indicating that epigenetic variation results in both antigenic and functional variation. We observed a general association between heterochromatin marks and clonally variant expression, extending previous observations for specific genes to essentially all variantly expressed gene families. These results suggest that phenotypic variation of functionally unrelated P. falciparum gene families is mediated by a common mechanism based on reversible formation of H3K9me3-based heterochromatin. In changing environments, diversity confers fitness to a population. Our results support the idea that P. falciparum uses a bet-hedging strategy, as an alternative to directed transcriptional responses, to adapt to common fluctuations in its environment. Consistent with this idea, we found that transcriptionally different isogenic parasite lines markedly differed in their survival to heat-shock mimicking febrile episodes and adapted to periodic heat-shock with a pattern consistent with natural selection of pre-existing parasites.
Full expansion of the heat trace for cone differential operators

The operator e−tA and the heat trace Tr e−tA, for t > 0, are investigated in the case when A is an elliptic differential operator on a manifold with conical singularities. Under a certain spectral condition (parameter–ellipticity) we obtain a full asymptotic expansion in t of the heat trace as t → 0+. As in the smooth compact case, the problem is reduced to the investigation of the resolvent (A− λ)−1. The main step will consist in approximating this operator family by a parametrix to A − λ using a suitable parameter–dependent calculus. Introduction In this paper the operator e for t > 0 is investigated on manifolds with conical singularities. The operator A is assumed to be an elliptic differential operator of arbitrary positive order, not necessarily self–adjoint, but satisfying an analog of Agmon’s condition (parameter–ellipticity) in a sector {λ ∈ C | 0 < φ0 < | arg(λ − c0)| ≤ π} for some π/2 > φ0 > 0 and c0 > 0. Our aim is to describe in a precise way the resolvent (A − λ) for |λ| → ∞ as well as the operator e (heat operator) and its trace Tr e (heat trace) as t→ 0. From the analytic point of view a cone is a product (0, c) × X together with a metric of the form dr + rgX(r), where gX(r) is a smooth family of Riemannian metrics on the ‘cone base’ X. Here, X is assumed to be a smooth compact manifold without boundary. For this reason, the analysis on a manifold with conical singularities takes place on a manifold with boundary B with the mentioned product structure near ∂B = X. The natural differential ∗This work was supported by Max-Planck-Gesellschaft, Bonn
Expanding the Training Data Space Using Emerging Patterns and Genetic Methods

Classification is a major problem in machine learning. Many classifiers have been developed recently. However, the performance of these classifiers is proportional to the knowledge obtained from the training data. As a result, traditional classifiers can not perform very well when the training data space is very limited. In this paper, we propose a new approach to expand the training data space (ETDS) using emerging patterns (EPs) [4] and genetic methods (GMs) [7]. EPs are those itemsets whose supports in one class are significantly higher than their supports in the other classes. GMs are evolutionary methods that incorporate computational techniques inspired by biology [8]. We combine the power of EPs and GMs to expand the training data space before applying standard classifiers. The expansion process is performed by generating more training instances using four techniques. An extensive experimental evaluation carried out on a number of datasets shows that our approach has a great impact on the performance of many traditional classifiers.
LCL-Filter Design for Robust Active Damping in Grid-Connected Converters

Grid-connected converters employ LCL-filters, instead of simple inductors, because they allow lower inductances while reducing cost and size. Active damping, without dissipative elements, is preferred to passive damping for solving the associated stability problems. However, large variations in the grid inductance may compromise system stability, and this problem is more severe for parallel converters. This situation, typical of rural areas with solar and wind resources, calls for robust LCL-filter design. This paper proposes a design procedure with remarkable results under severe grid inductance variation. The procedure considers active damping using lead-lag network and capacitor current feedback. Passive damping is also discussed. The design flow, with little iteration and no complex algorithms, selects the proper ratios between the switching and resonance frequency, the grid and converter inductance, and the filter capacitance and total inductance. An estimation for the grid current total harmonic distortion (THD) is also proposed. Simulation and experiments validate the proposals.
A Novel Approach for Opinion Spam Detectionin E-Commerce

:هلاقم هصلاخ The World Wide Web has brought an enormous improvement in the lives of people, during the last couple of decades. Nowadays, most companies and businesses exploit Ecommerce to sell their products and services, to discover the market trend and to analyze their competitor’s activities. Opinion spams are those fake and untruth opinions which target companies or products to fame or defame them. However, to the best of our knowledge, previous works never considered both behavioural and linguistic features simultaneously. In this paper, we propose an iterative algorithm to detect fake reviews, review spammers and group of spammers at the same time. To accomplish this goal, we propose a new graph structure which considers all the features and entity relationships between reviews and reviewers. Experimental results prove that our algorithm outperforms all the other baseline approaches in terms of accuracy.
Localization of Anchor Nodes for Wireless Sensor Networks

Many localization methods for wireless sensor networks (WSN) have been proposed by far. These methods are usually aimed at how to locate unknown nodes or how to improve performance of localization under a certain density of anchor nodes. However, localization method for anchor nodes is limited to GPS or hand-placing method merely. It is imperative to explore another method that is efficient and cost-effective to realize localization of anchor nodes. And how new anchor nodes replace old anchor nodes is also a problem because of power consuming. This paper addresses the problem of locating anchor nodes in WSN and presents a new method to locate anchor nodes. The method presented herein relies on magnetic localization technique. Based on the magnetic dipole model, the algorithm of locating anchor nodes is derived. Also, the method can resolve easily the problem that new anchor nodes replace old anchor nodes. The simulation results show its performance.
On the Smoothness of Linear Value Function Approximations

Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efﬁciently by hybrid approximate linear programming (HALP). The main idea of the approach is to approximate the optimal value function by a set of basis functions and optimize their weights by linear programming. It is known that the solution to this convex optimization problem minimizes the L 1 -norm distance in between the optimal value function and its approximation. In this paper, we relate this measure to the max-norm error of the same value function. We believe that this theoretical analysis may help to understand the quality of HALP approximations in continuous domains.
Interoperability issue between IPv4 and IPv6 in OpenFlow enabled network: IPv4 and IPv6 transaction flow traffic

In recent years the usage of the Internet and the hosting of virtual machines in a data center have been increasing in a dramatic manner which leads to IPv4 address depletion issue. Consequently, the transition from IPv4 to IPv6 has become inevitable and fairly urgent. Software-Defined Networking (SDN) is one of the recently emerging networking paradigm which separate the control and data plane logic into SDN controller and switch respectively. OpenFlow is the protocol, which is used to establish the communication between the controller and switch. However, the communication between IPv4 and IPv6 hosts is still a challenging issue, due to the inherent limitation of IPv6 support in various versions of OpenFlow Protocols. Hence, in this research paper, we studied the interoperability issues between IPv4 and IPv6 communication in an SDN enabled environment. We explored the dual-stack and tunneling mechanisms to resolve the interoperability and OpenFlow versioning support issues. The experiments were carried out by enabling the switches in OpenFlow 1.0 and OpenFlow 1.3 modes. The real-time and simulation results reported in this paper indicated that the interoperability issues between IPv4 and IPv6 can be solved using dual-stack and tunneling techniques.
The impact of time separation on coordination in global software teams: a conceptual foundation

While there has been much research on the study of global virtual teams and global software teams, there has been practically no research on the nuances of time separation. We present three converging perspectives on this topic: (a) a view from practices and tactics of global teams; (b) a theoretical view from coordination theories; and (c) a view from our prior research in which we modeled coordination costs for time-separated dyads. Practice suggests that time separation arises not only from time-zone differences but also from factors such as nonoverlapping weekend days and holidays, shifts, and different working schedules. It also suggests that teams employ various coping tactics when faced with time separation—synchronous, asynchronous, and education. Theory suggests that communication is necessary to coordinate and that effectiveness of communication is hampered, both in quality and timeliness, when teams are separated by time. Our model, based on coordination theory, suggests that coordination costs contain four main components—communication, clarification, delay, and rework—and that the various aspects of time-separated work have different effects on each of these components. Our convergent view from these three perspectives shows that distance separation is symmetric—i.e. distance (A, B) = distance (B,A)—while time separation is asymmetric, which affects the planning of team interactions; that the timing of activities matters in time-separated contexts but not in contexts with only distance separation; and that vulnerability costs (i.e. resolving misunderstandings and rework) increase with time separation. Copyright © 2004 John Wiley & Sons, Ltd.
Development of a Multifunctional Cosmetic Prosthetic Hand

An innovative artificial hand is presented, which can help to restore both motor and sensory capabilities of upper extremity amputees. All requisite components of the revolutionary prosthesis fit into the small volume of the metacarpus. A new high-power actuating technology has been developed for maximizing the benefit in using the prosthetic hand by increasing the number of grasping patterns. An optional sensory feedback system has been designed for the prosthesis, which is based on mechanical vibration. First clinical trials with the prosthetic hand revealed a high acceptance, as the force necessary to hold an object securely was reduced significantly.
Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning

Dead-reckoning (DR) algorithms, which use self-contained inertial sensors combined with gait analysis, have proven to be effective for pedestrian navigation purposes. In such DR systems, the primary error is often due to accumulated heading drifts. By tightly integrating global navigation satellite system (GNSS) Doppler measurements with DR, such accumulated heading errors can usually be accurately compensated. Under weak signal conditions, high sensitivity GNSS (HSGNSS) receivers with block processing techniques are often used, however, the Doppler quality of such receivers is relatively poor due to multipath, fading and signal attenuation. This often limits the benefits of integrating HSGNSS Doppler with DR. This paper investigates the benefits of using Doppler measurements from a novel direct vector HSGNSS receiver with pedestrian dead-reckoning (PDR) for indoor navigation. An indoor signal and multipath model is introduced which explains how conventional HSGNSS Doppler measurements are affected by indoor multipath. Velocity and Doppler estimated by using direct vector receivers are introduced and discussed. Real experimental data is processed and analyzed to assess the veracity of proposed method. It is shown when integrating HSGNSS Doppler with PDR algorithm, the proposed direct vector method are more helpful than conventional block processing method for the indoor environments considered herein.
Development of an autonomous rough-terrain robot

In this paper, we discuss the development process of a mobile robot intended for environmental observation applications. The paper describes how a standard tele-operated Explosive Ordnance Disposal (EOD) robot was upgraded with electronics, sensors, computing power and autonomous capabilities, such that it becomes able to execute semi-autonomous missions, e.g. for search & rescue or humanitarian demining tasks. The aim of this paper is not to discuss the details of the navigation algorithms (as these are often task-dependent), but more to concentrate on the development of the platform and its control architecture as a whole.
Evaluation of Some School Applications in Turkish National Education according to Students’ Viewpoints

The purpose of this study is to evaluate students’ perspectives according to various variables about use of smart boards and tablet computers in class rooms, academic performance tasks, distribution of course books, and changes made in exam grading regulation at high schools which came into effect as of academic year 2013-2014 under Faith Project. Formulation and application of measurement techniques and data collection were performed with high school students in Duzce province. A correlational comparative survey method was applied with quantitative research approach in this study. Statistical Package Program SPSS 20.0 was used in data analysis. Descriptive statistics analysis was performed to evaluate frequency values, percentages and arithmetic average values, while, One-Way Variance Analysis (ANOVA) and t -test were used for unrelated sampling. A sample of 606 students was selected from various high schools in Duzce during academic year 2015-2016. Students’ viewpoints on the categories defined in measurement scale were determined generally as “I am indecisive” or “I agree”. Resultantly, no significant differences were found in students’ opinions according to gender and residential area variables. On the other hand, significant differences were detected in students’ perspectives on use of smart boards, performance tasks and course books distribution according to the school type variable. Use of smart board was found to be considered more positively in Anatolian high schools, while, performance task and course book distribution were considered more positively in vocational schools. Moreover, it was also found that students’ viewpoints on use of tablet computers and distribution of course books showed significant differences according to the variable of class size. Students’ viewpoints on use of smart board and tablet computers, performance task, and distribution of course books were found to be viewed more positively in classes with strength of 21-25 students.