Miracle-dz/UniFAR-FTUs huggingface dataset:
VietSentiLex: a sentiment dictionary that considers the polarity of ambiguous sentiment words

The ability to analyze sentiment is a major technology to analyze social media process. The sentiment analysis involves reading and understanding what is being said about a brand as well as advertising cam-paigns in online services to determine the nature of a product. Because the Viet-namese language has few resources for applying machine learning tasks, use of sentiment dictionaries is required. In this study, a sentiment dictionary called ”Viet-SentiLex” is introduced for the aforementioned task in the Vietnamese language. Most notably, , In this study, instead of applying scores for every word, ambiguous words are considered more carefully as it is periodically positive or negative. Related words such as target nouns or verbs are used as contextual information for a sentiment word. Experiments to compare the performance of our dictionary to others are conducted. We prove that our dictionary has a high potential in predicting the polarity of reviews as compared to other dictionaries. In addition, various challenges and disadvantages of this dictionary are also outlined for future improvement until VietSentiLex can be a commercial product.
SECURED AND OPTIMAL RETRIEVAL OF DATA IN CLOUD THROUGH COMPUTATIONAL TECHNIQUES

Within the Cloud computing system, it is essential to provide storage and security solution for users and the enterprises. It provides greater benefits like elasticity and flexibility. The Compromises of data occur due to attacks by the users. In this, we propose a secured and optimal retrieval of data in cloud through computational techniques. We ensure the security of the sensitive data through efficient fragmentation algorithm. Here, the data is fragmented and storing the fragmented pieces in multiple cloud nodes by ensuring each node stores a single fragment. It replicates and retrieves the fragmented data over the multiple cloud spaces. The fragmented data are stored in a cloud node with a certain distance by means of Mersenne Twister computational technique and this prohibits the attacker to guess the location of fragmented data pieces. It beats the assaults of finding the area of information and the bargain of hub containing the information is less. This does not depend on the cryptography procedures for security of information with the goal that it minimizes the expense of costly techniques. Furthermore, this likewise guarantees the internet getting to and altering of the record should be possible.
Extraction of Road Network from High Resolution Remote Sensed Imagery with the Combination of Gaussian Markov Random Field Texture Model and Support Vector Machine

Extracting road network from high resolution remotely sensed imagery is much difficult than from the other resolution because high resolution imagery exhibits more complex spectral character.To distinguish them from other spa-tial objects,novel classification tools should be applied in which support vector machine(SVM)is outstanding in its fast training speed and strong capability in non-linear classification tasks.A road network extracting method combining Gaus-sian Markov random field texture model(GMRF)and SVM is proposed.This method can be divided into two main steps:firstly,GMRF is used to obtain the6texture features values of sample pixels,and SVM is trained and then used to clas-sify the whole image with these features into road patches vs.non road patches.After that,the patches are initially con-nected with some morphological operations,and their axes are extracted with thinning operation and then vectorized.Se-condly,a heuristic connecting strategy is used to connect and group the axes of the road patches into final road network.Experiments of road network extracting from IKONOS imagery validate our method.
Spine-Limb Coordination Controller for a Sprawling Posture Robot

Many animals actively use their spine during locomotion. By properly coordinating it with the limbs, their locomotion capabilities can be vastly improved in both kinematics and dynamics. Researchers are trying to use the same principles in robots. The robotic spine often comes in a form of an (over)actuated kinematic chain, which either directly creates contacts with an environment (snake robots), or connects two (or more) girdles (attachment points for the legs). Its role and control depend a lot on the spine configuration and the robot type. In control of snake robots that allow 3D motion, the usual approach is to directly drive joints with carefully designed parametrized wave functions [1] or to define desired body shape in Cartesian space and fit the robot kinematics to it [2]. Navigation-oriented control of planar (2D) snake robots often utilizes a predecessor-follower control scheme [3]. Segmented spines are still fairly underutilized in legged robots. Most of the research focuses on improving robot performance by utilizing a low degree of freedom spine (active or passive) with a bending in sagittal (vertical) plane [4]. Salamander robots in [5] and [6] utilize a segmented spine that allows bending in transverse (horizontal) plane. Role of the spine is to allow for multimodal locomotion. In water it propels the robot using an anguilliform swimming gait while on land it extends limbs’ reach and improves turning capabilities. Salamander robots in [5] for both swimming and walking are controlled in joint space by coupled phase oscillators. The behavior of the spine and synchronization between spine and limbs are solely determined by coupling weights and intrinsic frequencies of phase oscillators. Such approach does not take into account the posture of a robot in Cartesian space, which is important for precise control of (i) leg trajectories with respect to the robot’s body, (ii) coordination between limbs and the spine and (iii) overall robot’s posture.
PROVIDING A SOLUTION TO IMPROVE PRE-COPY METHOD FOR MIGRATING VIRTUAL MACHINES IN CLOUD INFRASTRUCTURE

Cloud computing can be defined as a new computing model which suggests solutions for providing information technology services analogous to utility services such as power electricity, telephone. Thanks to the virtualization technology, most of Cloud datacenters use this technology for performance improvement. This technology transforms a physical server to several virtual machines. With regard to this property, virtual machines can be transferred from one place to another place that is called migration. PreCopy is one of the main methods in migration techniques. An important problem in this method is that when the memory pages are changed (dirty pages) faster than sending pages to a destination, the process of migration will take a long time that is the case in transferring virtual machines. In this paper, a solution is proposed that sets up the speed of virtual machines in terms of CPU frequency and makes a balance between senders and receivers in pre-copy algorithm. The results show that the proposed method has better performance compared to the pre-copy method and decreases the total migration time around 25% and the total amount of transferred data around 47%.
DUAL PROXY GAUSSIAN PROCESS STACK: INTEGRATING

Ages in ocean sediment cores are often inferred using either benthic δO or planktonic C of foraminiferal calcite. Existing probabilistic dating methods infer ages in two distinct approaches: ages are either inferred directly using radionuclides, e.g. Bacon [1]; or indirectly based on the alignment of records, e.g. HMM-Match [2]. In this paper, we introduce a novel algorithm for integrating these two approaches by constructing Dual Proxy Gaussian Process (DPGP) stacks, which represent a probabilistic model of benthic δO change (and its timing) based on a set of cores. While a previous stack construction algorithm, HMM-Match, uses a discrete age inference model based on Hidden Markov models (HMMs) [3] and requires a number of records enough to sufficiently cover all its ages, DPGP stacks with time-varying variances are constructed with continuous ages obtained by particle smoothing [4, 5] and Markov-chain Monte Carlo (MCMC) [6] algorithms, and can be derived from a small number of records by applying the Gaussian process regression [7]. As an example of the stacking method, we construct a local stack from 6 cores in the deep northeastern Atlantic Ocean and compare it to a deterministically constructed δO stack of 58 cores from the deep North Atlantic [8]. We also provide two examples of how dual proxy alignment ages can be inferred by aligning additional cores to the stack.
7 Model Predictive Control in Discrete Manufacturing Shopfloors

1Consiglio Nazionale delle Ricerche (CNR), Institute of Industrial Technologies and Automation (STIIMA), Research Institute, Via Alfonso Corti 12, 20133 Milano, Italy 2Synesis, SCARL, Via Cavour 2, 22074 Lomazzo, Italy 3Scuola Universitaria Professionale della Svizzera Italiana (SUPSI), Dalle Molle Institute for Artificial Intelligence (IDSIA), Galleria 2, Via Cantonale 2C, CH-6928 Manno, Switzerland E-mail: alessandro.brusaferri@itia.cnr. it; giacomo.pallucca@itia.cnr. it; franco.cavadini@synesis-consortium.eu; giuseppe.montalbano@synesis-consortium.eu; dario.piga@supsi.ch
Deadline Inhibited Workflow Scheduling Method for Centre Based Genetic and Firefly Algorithms

Today, the cloud computing is a new model of computing paradigm that processes huge volume of facts and statistics that are from distant locations. Using cloud services, individuals can have access to software applications, platform and hardware. In recent days, as the volume of data is growing with every passing day, the associated cost is also getting increased. So, here lies the challenge for the cloud solution providers to provide solutions according to Service Level Agreements (SLAs) as well as maintaining Quality of Service (QoS) parameters of users. So, there lies a requirement for an efficient scheduling algorithm for tasks to manage the increasing costs of data and applications. The primary goal of our research is to develop a Deadline Constrained Task Scheduling algorithm using center based GA and firefly algorithms (CGF). In this paper, we have developed a Deadline Constrained Workflow Scheduling algorithm using Genetic and Particle Swarm Optimization algorithms with QoS parameters that addresses the above discussed problem.
Understanding and Securing Device Vulnerabilities through Automated Bug Report Analysis

Recent years have witnessed the rise of Internet-of-Things (IoT) based cyber attacks. These attacks, as expected, are launched from compromised IoT devices by exploiting security ﬂaws already known. Less clear, however, are the fundamental causes of the pervasiveness of IoT device vulnerabilities and their security implications, particularly in how they affect ongoing cybercrimes. To better understand the problems and seek effective means to suppress the wave of IoT-based attacks, we conduct a comprehensive study based on a large number of real-world attack traces collected from our honeypots, attack tools purchased from the underground, and information collected from high-proﬁle IoT attacks. This study sheds new light on the device vulnerabilities of today’s IoT systems and their security implications: ongoing cyber attacks heavily rely on these known vulnerabilities and the attack code released through their reports; on the other hand, such a reliance on known vulnerabilities can actually be used against adversaries. The same bug reports that enable the development of an attack at an exceedingly low cost can also be leveraged to extract vulnerability-speciﬁc features that help stop the attack. In particular, we leverage Natural Language Processing (NLP) to automatically collect and analyze more than 7,500 security reports (with 12,286 security critical IoT ﬂaws in total) scattered across bug-reporting blogs, forums, and mailing lists on the Internet. We show that signatures can be automatically generated through an NLP-based report
THE LONG RUN AND SHORT RUN RELATIONSHIP BETWEEN POVERTY AND LITERACY RATE IN PAKISTAN

This study investigates the long and short run relationship between poverty and literacy rate in Pakistan. For this purpose, the time series data from 1971 to 2013 is used. The sources of this secondary data are World Bank Development Indicators. Augmented Dickey Fuller test is used to check the stationarity of data. Poverty and literacy rates are found stationary at first difference. Johansen co integration is used to trace the long run relationship between poverty and literacy rate in Pakistan. The results indicate that poverty is reduced by 0.75 per cent due to one per cent increase in the literacy rate. Moreover, short run relationship between poverty and literacy rate is investigated with VECM and found no relationship in the short run.
Caporale Style Consistency and Mutual Fund Returns : The Case of Russia March 2019

This paper carries out style analysis for Russian mutual funds using monthly data from the National Managers’ Association over the period January 2008-December 2017; specifically, it applies the RSBA method developed by Sharpe (1992) for evaluating the impact of style on returns, and uses the Style Drift Score (SDS) introduced by Idzorek (2004) as a measure of a fund’s style drifting activity. The main findings can be summarised as follows. In the Russian case there is a significant positive relationship between style consistency and profitability of funds. Further, Russian funds are characterised by a high level of style drift, namely deviations from the investment strategy declared at the time of registration as required by Russian law. JEL classification: C23, G14, G19
Organization Culture “Octapace”

Organisational culture is defined as a culture of underlying thoughts, beleifs, values, assumptions and the methods of interaction which contribute towards social and psychological environment thus, culture of organization includes expectations,philosophies and experiences which acts as guiding principles that studies the impact of behavior, attitudes and perception of people. It is done to cover the gap of the external as well as internal environment.It helps in expressing the self images, feelings, interactions and communications to meet the future as well as individual expectation . Culture is based on shared values, beleifs, customs, thoughts and written ,unwritten rules which are considered in order to bridge up the gaps of people working. Thus, openness, confrontation,trust authenticity,proactiveness, autonomy collaboration and experimenting are some of the values used by organisation in order to study and observe the cultures of people working in organizations so that the smooth functioning of the organisations are done. These are the values which helps in covering the gaps in organization for achievement of missionary and visionary goals and objectives set by different organisations. This approach is used in various human resource organisations in order to employ right people, at right place at right time of requirement. Thus it studies and influences people by analyzing the corporate, workplace and business culture. It includes the organization’s symbols, languages, assumptions, habits and attitudes of people working in the environment.
An Analysis of Airborne GaSamma Ray Spectrometric Data of Gabal Umm Naggat Granitic Pluton , Central Eastern Desert , Egypt

The present work deals with the analysis of the airborne gamma ray spectrometric data of Gabal Umm Naggat granites, Central Eastern Desert, Egypt. It shows distinct spectral pattern of the radioelement zoning which is related to the associated mineralogical variation of such granitic pluton. The pluton is divided into three spectral domains: northern, middle and southern. The northern domain (A) is characterized by high radioelements contents and high ratios. It is characterized by high Zr, Nb, Y, Th, U and HREE in the most albitized granite varieties. The middle domain (B) is K, Th rich reflects the alkali feldspar rich granite. The southern domain (C) is characterized by high three radioelements contents, but lower than the northern one. Such zonation is evidenced by the results of geochemical analysis of previous works. To assess the potentiality of the gamma ray spectrometric signatures of areas of change associated with hydrothermal Nb-Ta-Sn occurrences, two approaches such as residual anomaly method on the basis of lithologic normalization (Th-normalized approach) and the Fparameter of Effimov approach are applied. Low anomalous potassium (Kd) that connected with high anomalous uranium variation (Ud), and high F-parameter anomaly strip highlight areas of change associated with hydrothermal Nb-Ta-Sn occurrences.
Location Privacy Preserving Mechanisms

Location privacy is not an issue every user thinks of when using Google Maps, a fitness tracker or his GPS navigation system. Yet location privacy is an important part of one’s anonymity while using location-based services. If location privacy is compromised, an adversary can draw sensitive conclusions about the user or use the gained information for his advantage. In the recent years, different approaches have been developed aiming to provide location privacy for different use cases. This paper aims to give an overview over the functionality, features and drawbacks of several important approaches: cloaking, mix zones, dummy queries, peer-to-peer systems and private information retrieval.
The Influence of Cr 3 C 2 and VC as Alloying Additives on the Microstructure and Properties of Reactive Sintered WCCo Cermets

Investigated WC-Co cermets were produced via reactive sintering. In case of reactive sintering the elemental powders of tungsten, carbon black as graphite source and cobalt at first activated throw high energy milling and then the carbide synthesis is taking place in the same cycle with liquid phase sintering of the cermets. Because there is a lack of information about the influence of alloying additives on the reactive sintered WC-Co cermets, small amount of chromium carbide or vanadium carbide was added to the powders. To investigate the influence of carbon content in initial powder mixture on the microstructure and properties of reactive sintered WC-Co cermets alloyed with Cr3C2 and VC cermets with different carbon content were produced. The hardness, transverse rupture strength and erosion resistance of alloyed WC-Co cermets depending on carbon content in initial powder mixture is exhibited.
Comparison of Parameter Estimation Methods for Single-Microphone Multi -Frame Wiener Filtering

The multi-frame Wiener filter (MFWF) for single-microphone speech enhancement is able to exploit speech correlation across consecutive time-frames in the short-time Fourier transform (STFT) domain. To achieve a high speech correlation, typically an STFT with a high time-resolution but a low frequency-resolution is applied. The MFWF can be decomposed into a multi-frame minimum power distortionless response (MFMPDR) filter and a single-frame Wiener postfilter. To implement the MFWF using this decomposition, estimates of several parameters are required, namely the speech correlation vector, the noisy speech correlation matrix, and the power spectral densities at the output of the MFMPDR filter. Correlations can be estimated either directly in the low frequency-resolution STFT filterbank, indirectly by estimating periodograms in a high frequency-resolution filterbank and applying the Wiener-Khinchin theorem, or in a combined way. In this paper, we compare the performance of different estimators for the required parameters. Experimental results for different speech material, noise conditions, and signal-to-noise ratios show that using a combined estimator for the speech correlation vector yields the best results in terms of speech quality compared to existing direct and indirect estimators.
Is development of the renewable energy sector crucial for the electricity consumption-growth nexus in the EU countries ?

The aim of the study is to assess the impact of development of the renewable energy sector in the EU on the relationship between renewable and non-renewable electricity consumption and economic growth in the period 1995-2015. In order to identify countries with reverence of development of their renewable energy sector statistical clustering methods are applied. The relations between renewable and non-renewable electricity consumption and economic growth are investigated within the panel VAR framework. The results reveal that the level of development of the renewable energy sector is crucial for linkages between electricity consumption and economic growth. In a group of countries with a relatively high level of development of the renewable energy sector, renewable electricity consumption and economic growth are mutually dependent. Additionally, the increase in economic growth leads to a short-term increase in renewable electricity consumption. At the same time, the rise in renewable electricity consumption is helpful in increasing economic activity. In the remaining countries renewable electricity consumption and economic growth are
Adaptive Information Flow Mechanisms and Management for Power Grid Contingencies

GridStat is a QoS-managed publish-subscribe framework for data delivery for the electric power grid. Grid-Stat’s Data Plane delivers data updates through a network of middleware-level Status Routers. Subscriptions are managed by GridStat’s hierarchical QoS Management Plane. The path allocation computations are typically done of-ﬂine and beforehand, but are complex, not only due to the multiple QoS constraints but the number of status routers that would be involved an entire power grid. In a crisis, many entities may suddenly wish to add a large number of subscription requests, which would in practice over-whelm the subscription allocation mechanisms. In this paper we present a mechanism called modes, which lets Grid-Stat change routing tables quickly. Modes can be either global, or only active at a given scope within the hierarchy. We present the design and experimental evaluation of Grid-Stat modes and of two different mode change algorithms that provide different tradeoffs of performance and consistency.