A Survey on Causal Discovery Methods for Temporal and Non-Temporal Data

Causal Discovery (CD) is the process of identifying the cause-effect relationships among the variables from data. Over the years, several methods have been developed primarily based on the statistical properties of data to uncover the underlying causal mechanism. In this study we introduce the common terminologies in causal discovery, and provide a comprehensive discussion of the approaches designed to identify the causal edges in different settings. We further discuss some of the benchmark datasets available for evaluating the performance of the causal discovery algorithms, available tools to perform causal discovery readily, and the common metrics used to evaluate these methods. Finally, we conclude by presenting the common challenges involved in CD and also, discuss the applications of CD in multiple areas of interest

Morphological Characterization of Deepwater Rice Genotypes

The experiments was conducted to study the early establishment morphological characters of advanced deep water rice.The parameters such as plant height, number of leaves, and number of effective & non-effective tillers were studied with different DAS as treatment in field condition. The genotype BR224-2B-2-5, BR5915-B-7, Bazzail-65 &Gabura showed more plant height at 30 DAS & 60 DAS. But HBJ.A.IV & Bazail-65 showed more plant height at 90 DAS & 120 DAS. BR224-2B-2-5 & BR5915-B-7 showed more leaves and tillers at early stage (60 DAS). But HBJ.A.IV &Birpala showed better performance for same characters at later stage (90 DAS, 120 DAS & 150 DAS). The advanced genotype BR224-2B-2-5 is able to establish significantly at early stage as it showed vigorous growth against stress condition present at early stage. HBJ.A.IV and Birpala have potential of producing more leaves and tillers throughout the growth stages and HBJ.A.IV and Birpala is the tall type DWR cultivar as it produced more seedling height and plant height than others. The yield of the genotype BR224-2B-2-5 and BR5915-B-7 are 3.07 t ha-1 and 2.71 t ha-1 respectively. Finally, the advanced genotype BR224-2B-2-5 may be a good source to meet the future challenge

Cotton in the new millennium: advances, economics, perceptions and problems

Cotton is the most significant natural fibre and has been a preferred choice of the textile industry and consumers since the industrial revolution began. The share of man-made fibres, both regenerated and synthetic fibres, has grown considerably in recent times but cotton production has also been on the rise and accounts for about half of the fibres used for apparel and textile goods. To cotton’s advantage, the premium attached to the presence of cotton fibre and the general positive consumer perception is well established, however, compared to commodity man-made fibres and high performance fibres, cotton has limitations in terms of its mechanical properties but can help to overcome moisture management issues that arise with performance apparel during active wear. This issue of Textile Progress aims to: i. Report on advances in cotton cultivation and processing as well as improvements to conventional cotton cultivation and ginning. The processing of cotton in the textile industry from fibre to finished fabric, cotton and its blends, and their applications in technical textiles are also covered. ii. Explore the economic impact of cotton in different parts of the world including an overview of global cotton trade. iii. Examine the environmental perception of cotton fibre and efforts in organic and genetically-modified (GM) cotton production. The topic of naturally-coloured cotton, post-consumer waste is covered and the environmental impacts of cotton cultivation and processing are discussed. Hazardous effects of cultivation, such as the extensive use of pesticides, insecticides and irrigation with fresh water, and consequences of the use of GM cotton and cotton fibres in general on the climate are summarised and the effects of cotton processing on workers are addressed. The potential hazards during cotton cultivation, processing and use are also included. iv. Examine how the properties of cotton textiles can be enhanced, for example, by improving wrinkle recovery and reducing the flammability of cotton fibre

Automated Facial Expression Recognition Using Gradient-Based Ternary Texture Patterns

Recognition of human expression from facial image is an interesting research area, which has received increasing attention in the recent years. A robust and effective facial feature descriptor is the key to designing a successful expression recognition system. Although much progress has been made, deriving a face feature descriptor that can perform consistently under changing environment is still a difficult and challenging task. In this paper, we present the gradient local ternary pattern (GLTP)—a discriminative local texture feature for representing facial expression. The proposed GLTP operator encodes the local texture of an image by computing the gradient magnitudes of the local neighborhood and quantizing those values in three discrimination levels. The location and occurrence information of the resulting micropatterns is then used as the face feature descriptor. The performance of the proposed method has been evaluated for the person-independent face expression recognition task. Experiments with prototypic expression images from the Cohn-Kanade (CK) face expression database validate that the GLTP feature descriptor can effectively encode the facial texture and thus achieves improved recognition performance than some well-known appearance-based facial features

A Digital Personal Assistant using Bangla Voice Command Recognition and Face Detection

Though speech recognition has been a common interest of researchers over the last couple of decades, but very few works have been done on Bangla voice recognition. In this research, we developed a digital personal assistant for handicapped people which recognizes continuous Bangla voice commands. We employed the cross-correlation technique which compares the energy of Bangla voice commands with prerecorded reference signals. After recognizing a Bangla command, it executes a task specified by that command. Mouse cursor can also be controlled using the facial movement of a user. We validated our model in three different environments (noisy, moderate and noiseless) so that the model can act naturally. We also compared our proposed model with a combined model of MFCC &amp; DTW, and another model which combines crosscorrelation with LPC. Results indicate that the proposed model achieves a huge accuracy and smaller response time comparing to the other two techniques.ISBN för värdpublikation: 978-1-7281-5852-5, 978-1-7281-5853-2</p

An Interactive Computer System with Gesture-Based Mouse and Keyboard

Researchers around the world are now focused on to make our devices more interactive and trying to make the devices operational with minimal physical contact. In this research, we propose an interactive computer system which can operate without any physical keyboard and mouse. This system can be beneficial to everyone, especially to the paralyzed people who face difficulties to operate physical keyboard and mouse. We used computer vision so that user can type on virtual keyboard using a yellow-colored cap on his fingertip, and can also navigate to mouse controlling system. Once the user is in mouse controlling mode, user can perform all the mouse operations only by showing different number of fingers. We validated both module of our system by a 52 years old paralyzed person and achieved around 80% accuracy on average.ISBN för värdpublikation: 978-3-030-68153-1, 978-3-030-68154-8</p

A Review on Recent Advancements in FOREX Currency Prediction

In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny from researchers all over the world. Due to its vulnerable characteristics, different types of research have been conducted to accomplish the task of predicting future FOREX currency prices accurately. In this research, we present a comprehensive review of the recent advancements of FOREX currency prediction approaches. Besides, we provide some information about the FOREX market and cryptocurrency market. We wanted to analyze the most recent works in this field and therefore considered only those papers which were published from 2017 to 2019. We used a keyword-based searching technique to filter out popular and relevant research. Moreover, we have applied a selection algorithm to determine which papers to include in this review. Based on our selection criteria, we have reviewed 39 research articles that were published on “Elsevier”, “Springer”, and “IEEE Xplore” that predicted future FOREX prices within the stipulated time. Our research shows that in recent years, researchers have been interested mostly in neural networks models, pattern-based approaches, and optimization techniques. Our review also shows that many deep learning algorithms, such as gated recurrent unit (GRU) and long short term memory (LSTM), have been fully explored and show huge potential in time series prediction.Validerad;2020;Nivå 2;2020-09-24 (alebob)</p

Towards an Understanding of Tailoring Scrum in Global Software Development: A Multi-case Study

There is growing interest in applying Scrum practices in Global Software Development to leverage the advantages of both. However, the effective use of Scrum practices largely depends on close interactions between project stakeholders. The distribution of project stakeholders in GSD provides significant challenges related to project collaboration processes that may limit the use of Scrum. However, project managers increasingly seek to use the Scrum model in their distributed projects. While there is an emerging body of industrial experience, there are limited empirical studies that discuss Scrum tailoring in GSD. The paper reports a multi-case study that investigates the impact of key project contextual factors on the use of Scrum practices in GSD. This study is relevant to researchers and practitioners who are seeking ways to use Scrum in GSD and improve project effectiveness. Categories and Subject Descriptor