Polarity Assignment Research Articles

Polarity assignment method (PAM), ANN, Neural networks strategy for the data of PAM for the single degree of freedom flexible joint robot

This paper “describes” the investigation of the stability of a single Degree of Freedom (DOF) flexible robotic arm by the diagrams shown below. The derived model is based on Euler- Lagrange approach. Exploration of a flexible robotic arm with using state-of-the-art controllers is essential for intelligent applications. These robot arms have joints that work independently of each other in order to create a smooth connection between joints. They still ensures the natural properties like a real human arm. The use of polarity assignment method “helps” the system to achieve desired output signals which has not been thoroughtly studied before for this system. The author can also compare the effectiveness of control methods for this system to find the most effective method for control strategies. In particular, ANN ( artificial neural network) is the most modern technique currently applied to this system to investigate the security and stability of the system through this program. This is new and it has never been used before for a system of this type. Neural networks strategy has been implemented in this paper as an application of artificial intelligence. It has successfully performed a mission in re-simulating functions of another control method: Polarity assignment method. Simulation results are done by Matlab.

Unified Maximum Voltage Utilization Controls for Half-Centralized Open-End Winding Permanent-Magnet Motor Systems

In order to extend the speed range and reduce power electronics devices of the primary permanent-magnet linear motor traction system, a half-centralized open-end winding topology is studied in this article, in which <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> movers are supplied by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> +1 voltage-source inverters. In order to maximize the speed range, two unified maximum voltage utilization control (UMVUC) methods are proposed for the studied traction system, which can be easily implemented for any number of movers. The first UMVUC is named as the original UMVUC, and it requires a heavy computation burden, which makes the implementation difficult when the number of movers is large. For the linear motor system, the relative positions of all movers are approximately constant. Based on this feature, the second UMVUC named as simplified UMVUC is proposed, which can significantly reduce the computation burden. In order to suppress the zero-sequence current (ZSC) and reduce the switching loss, a zero-sequence polarity assignment method is employed in the proposed UMVUCs. An experiment platform is developed, and the effectiveness of the proposed UMVUCs has been validated by experimental results.

АНАЛИЗ ТОНАЛЬНОСТИ ТЕКСТОВЫХ ОТЗЫВОВ С ПРИМЕНЕНИЕМ ТОНАЛЬНЫХ СЛОВАРЕЙ И КАРДИНАЛЬНОСТИ НЕЧЕТКОГО МНОЖЕСТВА

Sentiment or opinion analysis aims to determine the polarity of people's opinions in relationto any product, service, event or any person. One of the most common methods used in sentimentanalysis of text content is natural language processing. Sentiment analysis of natural languagetext can be assessed using numerous methodologies such as machine learning algorithms andstatistical tools, while the application of fuzzy logic is not common. The use of fuzzy logic waschosen for the following reasons. First, fuzzy logic handles linguistic uncertainty well. This way ofdefining the problem leads to a reduction in bias, both positively and negatively. Secondly, learning approaches based on fuzzy rules are fundamentally different from those learning approachesthat are widely used in sentiment classification, such as support vector machines, naive Bayes,etc., as they relate to generative learning, i.e. i.e. the goal of learning is to assess the degree towhich an instance belongs to each individual class. The proposed model for sentiment analysis oftext reviews is based on the use of tone lexicons using fuzzy logic and consists of four main stages.The steps include tokenization, word bag model formulation, sentiment fuzzy score formulation,and polarity assignment. In the proposed model, the power of the fuzzy set is used as a measure ofthe evaluation of the indicators of the polarity of words. Word polarity values are obtained byapplying two sentiment lexicons: SentiWordNet and AFINN. Two versions of the model were createddepending on the type of vocabulary used: based on SentiWordNet and AFINN. Comparisonof the presented approach based on fuzzy logic with other dictionary-based methods demonstratesthe superiority of the developed models based on the application of fuzzy logic.

MELex: The Construction of Malay-English Sentiment Lexicon

Currently, the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon. Thus, this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis. In this study, a new lexicon for sentiment analysis is constructed. A detailed review of existing approaches has been conducted, and a new bilingual sentiment lexicon known as MELex (Malay-English Lexicon) has been generated. Constructing MELex involves three activities: seed words selection, polarity assignment, and synonym expansions. Our approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia, Malay, and English, with the accuracy achieved, is 90%. It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case projects. This finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian context. The novel aspects of this paper are two-fold. Firstly, it introduces the new technique in assigning the polarity score, and second, it improves the performance over the classification of mixed language content.

High-Resolution Late Devonian Magnetostratigraphy From the Canning Basin, Western Australia: A Re-Evaluation

Late Devonian time was a period of rapid upheaval in the Earth system, including climate change, sea level changes, widespread ocean anoxia, and the Frasnian-Famennian mass extinction; the cause(s) of these changes remain(s) uncertain. The Lennard Shelf of the Canning Basin in Western Australia contains carbonate reef sections spanning much of the Late Devonian Epoch and has been sampled for paleomagnetic analysis with studies by Hansma and colleagues in 2015 and Playton and colleagues in 2016. However, previous paleomagnetic directions were scattered and their use for magnetostratigraphy has been questioned. Here, rock magnetic data and magnetostratigraphy for a late Devonian drill-core from the Lennard Shelf were analyzed. Three magnetostratigraphic interpretations were made using different paleopoles that showed good correlation with each other and the earlier interpretations by Playton and colleagues in 2016. Additionally, the rock magnetic data revealed the samples contain various mixtures of detrital and diagenetic minerals, the former of which should be viable recorders of primary magnetic signatures. Even in samples with these detrital phases, paleomagnetic data were often noisy and produced ambiguous polarity assignments, likely due to the anomalously weak Devonian field. Because of this ambiguity and the absence of a robust paleopole, broader correlations for this critical time-period will be difficult without additional paleomagnetic data from the late Devonian Period. Expanded data for this interval could eventually shed light on the timing, causes, and rates of the Frasnian-Famennian mass extinction and other environmental shifts in the late Devonian Epoch.

Graph based sentiment analysis using keyword rank based polarity assignment

Decision making by analyzing the underlying sentiment has become one of the challenging task with the explosion of rich source of user generated, diverse contents on the web. Sentiment analysis can ease the process of obtaining an overall sentiment by processing millions of reviews or documents altogether. A review or any textual data consists of numerous keywords, which hold different weightage based on various factors. An efficient ranking technique for those keywords is proposed in this paper in order to aid in the sentiment analysis process. A co-occurrence graph based statistical approach is adopted in this paper to find the global rank of the keywords. A novel node weighting technique is proposed, which will be used for the improvisation of the state of art method: Node and Edge Rank (NE-Rank) along with degree, to rank the keywords. The algorithm considers five different influential parameters to propose the node weighting technique. Also, a keyword may hold bi-polarity and depict different polarity according to the domain of application. Therefore, this paper proposes a novel, well organized and efficient sentiment analysis model using a graph based keyword ranking and domain specific rank based polarity assignment algorithm. The role or impact of an important keyword will be always more in comparison to a weaker one for determining the polarity of the review. Thus, the rank based polarity assignment technique is proposed with the use of the global ranks of keywords, to solve the domain dependency problem of the keywords. The proposed model is evaluated and validated using four different existing models for four different customer review datasets.

Performing opinion mining and analytical study for cashless transactions

Cashless economy and digital payments are one of the hot topics of research that are gaining enormous popularity day by day. It is primarily due to their ability to combat issues of corruption, back money, illegal transactions and counterfeit money. With the increase in number of options of digital payments, people are inclining themselves towards ease of payment. This paper focuses on two aspects: firstly, it provides an analytical study performed in the field of cashless transactions and digital payments. Secondly, it finds out the opinion of the people about cashless transactions using a hybrid approach of type 2 fuzzy logic and hesitant fuzzy sets for polarity assignment. A sentiment analysis on 'cashless economy' has been carried out using data obtained from Twitter in the form of tweets.

Predominant polarity in bipolar I and II disorders: A five-year follow-up study.

Patients with bipolar disorder (BD) differ in their relative predominance of types of episodes, yielding predominant polarity, which has important treatment implications. However, few prospective studies of predominant polarity exist. In the Jorvi Bipolar Study (JoBS), a regionally representative cohort of 191 BD I and BD II in- and outpatients was followed for five years using life-chart methodology. Differences between depressive (DP), manic (MP), and no predominant polarity (NP) groups were examined regarding time ill, incidence of suicide attempts, and comorbidity. At baseline, 16% of patients had MP, 36% DP, and 48% NP. During the follow-up the MP group spent significantly more time euthymic, less time in major depressive episodes, and more time in manic states than the DP and NP groups. The MP group had significantly lower incidence of suicide attempts than the DP and NP group, lower prevalence of comorbid anxiety disorders but more psychotic symptoms lifetime and more often (hypo)manic first phase of the illness than the DP group. Classification of predominant polarity was influenced by the timeframe used. The retrospective counting of former phases is vulnerable to recall bias. Assignment of dominant polarity may necessitate a sufficient number of illness phases. Predominant polarity has predictive value in predicting group differences in course of illness, but individual patients' classification may change over time. Patients with manic polarity may represent a more distinct subgroup than the two others regarding illness course, suicide attempts, and psychiatric comorbidity.

Sentiment Classification of Tweets with Non-Language Features

In recent years, mining social media sites like Twitter, Facebook have become a hot research focus. Twitter is one of the most fashionable microblogging services that permit users to express their views on e-commerce websites, sports, politics, modern technologies, movies, spirituality and so on. Sentiment can be considered as a natural expression of viewer’s perception. It is extremely difficult to identify the sentiment/opinion about a specific product or event by collecting and compiling microblog tasks manually. It is only fair to develop a system which collects, compile and analyse microblog tasks to arrive on insights that helps to take an action against an event. The system can monitor and evaluate in real time online views, to demonstrate how the whole world is reacting to a concept/ideology/event. Developing such a system which assigns polarity to a tweet is a hard task. In this paper we propose a scoring methodology to find the sentiment polarity of the Twitter messages. Emotions, shortened words and non-language features are integrated to increase the significance of the score computed for assigning the polarity for the tweets. The experimental results show that the proposed method enhances the accuracy of the assignment of polarity to tweets.

Learning patterns for discovering domain-oriented opinion words

Sentiment analysis is a challenging task that attracted increasing interest during the last years. The availability of online data along with the business interest to keep up with consumer feedback generates a constant demand for online analysis of user-generated content. A key role to this task plays the utilization of domain-specific lexicons of opinion words that enables algorithms to classify short snippets of text into sentiment classes (positive, negative). This process is known as dictionary-based sentiment analysis. The related work tends to solve this lexicon identification problem by either exploiting a corpus and a thesaurus or by manually defining a set of patterns that will extract opinion words. In this work, we propose an unsupervised approach for discovering patterns that will extract domain-specific dictionary. Our approach (DidaxTo) utilizes opinion modifiers, sentiment consistency theories, polarity assignment graphs and pattern similarity metrics. The outcome is compared against lexicons extracted by the state-of-the-art approaches on a sentiment analysis task. Experiments on user reviews coming from a diverse set of products demonstrate the utility of the proposed method. An implementation of the proposed approach in an easy to use application for extracting opinion words from any domain and evaluate their quality is also presented.

Loosely coupled multi-bit flip-flop allocation for power reduction

Merging 1-bit flip-flops into multi-bit flip-flops in the post-placement stage is one of the most effective techniques for minimizing clock power. In this work, we introduce a new style of multi-bit flip-flop, called loosely coupled multi-bit flip-flop (LC-MBFF). The merit of LC-MBFF is that the logically constituent 1-bit flip-flops in LC-MBFF can be physically apart (i.e., no relocation), providing no need to set aside white space. Utilizing LC-MBFFs, we propose a multi-bit flip-flop allocation algorithm which fully explores the diverse allocation of LC-MBFF structures to maximally reduce clock power consumption. Experimental results with ISCAS89 and IWLS2005 benchmark circuits show that our proposed allocation algorithm using the newly designed multi-bit flip-flops is able to reduce on average the clock power by 8.51% while the best known multi-bit flip-flop allocation algorithm [7] reduces by 5.37%. Additionally, we extend our algorithm to support the multi-bit flip-flop allocation for circuits with clock polarity assignment.

군용 통신망에서의 주파수 및 편파 지정 알고리즘 튜토리얼

본 논문에서는 군용 통신망에 대한 주파수 지정 문제를 그래프 이론 관점에서 접근하여 해결하는 방법을 소개한다. 선행 연구에서 제안한 알고리즘을 본 문제에 맞게 구현하였으며, 새로운 알고리즘을 제안하여 얻은 해의 성능이 최적의 값에 거의 근접함을 증명하였다. 또한, 이중 편파 안테나의 편파를 동시에 배정하여 주파수 지정 문제 해의 성능을 극대화하는 알고리즘을 소개하였다. In this paper we introduce a graph theory approach to solve the frequency assignment problem(FAP) for military communication network. Prior algorithms are implemented adaptively to the problem, and enhanced algorithms are proposed to show that their results approximately approached the optimum performance. We also proposed polarization assignment algorithms to enhance the FAP performances.

Clock buffer polarity assignment under useful skew constraints

Clock trees, which deliver the clock signal to every clock sink in the whole system, switch actively at high frequency, which makes them one of the most dominant sources of noise. While many clock polarity assignment (PA) techniques were proposed to mitigate the clock noise, no attention has been paid to the PA under useful skew constraints. In this work, we show that the clock PA problem under useful skew constraints is intractable and propose a comprehensive and scalable clique search based algorithm to solve the problem effectively. In addition, we demonstrate the applicability of our solution by extending it for PA under delay variation environment. Through experiments with ISPD'10 benchmark circuits, we show that our proposed clock PA algorithm is able to reduce the peak noise by 10.9% further over that of the conventional global skew bound constrained PA. Finally, we compare our PA technique against decoupling capacitor embedding technique which is a commonly used method for noise reduction.

그래프 이론 기반의 편파 및 주파수 지정 알고리즘

그래프 이론 기반의 편파 및 주파수 지정 알고리즘

Joint assignment of frequency and polarization to minimize the chromatic number

Abstract In this letter, we propose graph theory-based heuristics for jointly assigning frequency and antenna polarization in a cluster-based tactical communication environment (e.g., military communications). In addition to considering the frequency assignment problem (which is an NP-hard problem), we also consider the polarization assignment issue. A practical antenna and a 3D ray tracing-based simulator are exploited to measure the interference. We show that the suggested heuristics are nearly optimal in terms of chromatics and their low complexity makes them suitable for practical usage.

Multi-focused Proofs with Different Polarity Assignments

In this work, we will reason on how a given focused proof, where atoms are assigned with some polarity, can be transformed into another focused proof, where the polarity assignment to atoms is changed. This will allow, in principle, transforming a proof obtained using one proof system into a proof using another proof system. More specifically, using the intuitionistic focused system LJF restricted to Harrop formulas, we define a procedure, introducing cuts, for transforming a focused proof where an atom is assigned with positive polarity into another focused proof where the same atom is assigned negative polarity and vice-versa. Then we show how to eliminate these cuts, obtaining a very interesting result: while the process of eliminating a cut on a positive atom gives rise to a proof with one smaller cut, in the negative case the number of introduced cuts grows exponentially. We end the paper by showing how to use maximal multi-focusing identify proofs in LJF, giving rise to a 1-1 translation between maximal proofs in LJF and proofs in the natural deduction system for intuitionistic logic NJ, restricted to Harrop formulas.

Sentimenduen analisia euskaraz

Nowadays, opinion texts play an important role, in fact, people read opinions before they do an activity, buy a product or take a decision. However, the amount of opinion text is increasing rapidly and reading all opinions about a subject is unfeasible. ‘Sentiment analysis’ is a part of Natural Language Processing whose aim is to process opinion texts. This work is a part of ‘sentiment analysis’ and presents a first approximation to the assignment of polarity to texts written in Basque. Rhetorical Structure Theory has been used to assign different weights to text spans and an analysis has been performed at the lexical level. This method has been compared with other approaches and the results are promising.

A Fine-Grained Clock Buffer Polarity Assignment for High-Speed and Low-Power Digital Systems

The clock buffer polarity assignment is one of the effective design schemes to mitigate the power/ground noise caused by the clock signal propagation in high-speed digital systems. This paper overcomes a set of fundamental limitations of the conventional clock buffer polarity assignment methods, which are: 1) the unawareness of the signal delay (i.e., arrival time) differences to the leaf clock buffering elements; 2) the ignorance of the effect of the current fluctuation of nonleaf clock buffering elements on the total peak current waveform; and 3) the inability of supporting low-power digital designs with multiple (dynamically operating) power modes. Clearly, not addressing 1 and 2 in the polarity assignment may cause a severe inaccuracy on the peak current estimation, which results in unnecessarily high peak current. Moreover, without tackling 3, designs may suffer from clock skew violation in some of the power modes, affecting circuit speed or reliability. To overcome the limitations, we propose a completely new fine-grained approach to the clock buffer polarity assignment combined with buffer sizing, formulating the problem into a multiobjective shortest path problem and solving it effectively for designs with a single power mode, while exploiting the flexibility of our multiobjective shortest path formulation for designs with multiple power modes. Through experiments using benchmark circuits, it is shown that the proposed approach is able to produce designs with 17% lower peak current and 20% lower power noise on average, compared with the results produced by the best ever known method.

Intensity Integrated Laplacian-Based Thickness Measurement for Detecting Human Metaphase Chromosome Centromere Location

Accurate detection of the human metaphase chromosome centromere is an important step in many chromosome analysis and medical diagnosis algorithms. The centromere location can be utilized to derive information such as the chromosome type, polarity assignment, etc. Methods available in the literature yield unreliable results mainly due to high variability of morphology in metaphase chromosomes and boundary noise present in the image. In this paper, we have proposed a multistaged algorithm which includes the use of discrete curve evolution, gradient vector flow active contours, functional approximation of curve segments, and support vector machine classification. The standard Laplacian thickness measurement algorithm was enhanced to incorporate both contour information as well as intensity information to obtain a more accurate centromere location. In addition to segmentation and width profile measurement, the proposed algorithm can also correct for sister chromatid separation in cell images. The proposed method was observed to be more accurate and statistically significant as compared to a centerline-based method when tested with 226 human metaphase chromosomes.

Design Methodologies for Reliable Clock Networks

This paper overviews clock design problems related to the circuit reliability in deep submicron design technology. The topics include the clock polarity assignment problem for reducing peak power/ground noise, clock mesh network design problem for tolerating clock delay variation, electromagnetic interference aware clock optimization problem, adjustable delay buffer allocation and assignment problem to support multiple voltage mode designs, and the state encoding problem for reducing peak current in sequential elements. The last topic belongs to finite state machine (FSM) design and is not directly related to the clock design, but it can be viewed that reducing noise at the sequential elements driven by clock signal is contained in the spectrum of reliable circuit design from the clock source down to sequential elements.