Miracle-dz/UniFAR-FTUs huggingface dataset:
Shape & Texture Based Image Retrieval from Fuzzy Clustered Data

The large amount of image database, as well as its enormous deployment in various applications, the need for Content Based Image Retrieval (CBIR) development arose. This is an effective tool for search and retrieval of images. Color, shape and texture are primary low level image features exploited in CBIR. This paper presents a strategy for shape and texture based image retrieval from Fuzzy clustering. The combination of both extracted feature is used for image retrieval from the database. Firstly, a fuzzy clustering process is used to discover a set of images of semantic categories. Then the shape of the object contained in an image is extracted using Canny edge detector. The texture feature is calculated by applying GLCM matrix on a transformed image. The derived set of image features is used in order to retrieve images similar to a query image submitted by the user. The result shows that combination of image features for retrieval of images improves the efficiency of the system.
Achieving High Performance for Big Data Analytics

Irregular algorithms such as graph algorithms, sorting, and sparse matrix multiplication, present numerous programming challenges that include scalability, load balancing, and efficient memory utilization. In this age of Big Data we face additional challenges since the data is often streaming at a high velocity and we wish to make near real-time decisions for real-world events. For instance, we may wish to track Twitter for the pandemic spread of a virus. Analyzing such data sets requires combing algorithmic optimizations and utilization of massively multithreaded architectures, accelerator such as GPUs, and distributed systems. My research focuses upon designing new analytics and algorithms for continuous monitoring of dynamic social networks. Specifically, we deal with load balancing, scheduling, avoiding redundant computations, and utilizing network properties for designing dynamic graph algorithms.
From Subhuman to Human Kind: Implicit Bias, Racial Memory, and Black Males in Schools and Society

ABSTRACT This paper argues that implicit racial bias regarding black males is a manifestation of a long trajectory of Western racial memory and anti-blackness where black males have been considered subhuman or as human kinds. The author draws from theological, scientific, and social science literature to illustrate how racial discourses have historically constructed black males as subhuman or as human kinds (Hacking, 1995). The central argument of this paper is that current practices in schools and society that engage in racial bias are tied to durable racial discourses of power that have consistently rendered black males as feared and dangerous.
Omission of Causal Indicators: Consequences and Implications for Measurement

ABSTRACT One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant causal indicator does not affect downstream estimates relating the focal latent variable to other variables in the model, which challenges the current stance in the literature. Further, we argue that this occurrence presents a fundamental challenge to the causal-indicator literature, in that the lack of negative consequences is not consistent with the tenet that latent variables derive their meaning from the set of causal indicators included in a research model. Rather, though causal indicators help identify the focal latent variable, its meaning is derived from its position as a common factor of other downstream variables—latent or observed—to which it is related.
Question Answering over Linked Data (QALD-5)

With the increasing amount of semantic data available on the web there is a strong need for systems that allow common web users to access this body of knowledge. Especially question answering systems have received wide attention, as they allow users to express arbitrarily complex information needs in an easy and intuitive fashion (for an overview see [4]). The key challenge lies in translating the users' information needs into a form such that they can be evaluated using standard Semantic Web query processing and inferencing techniques. Over the past years, a range of approaches have been developed to address this challenge, showing signicant advances towards answering natural language questions with respect to large, heterogeneous sets of structured data. However, only few systems yet address the fact that the structured data available nowadays is distributed among a large collection of interconnected datasets, and that answers to questions can often only be provided if information from several sources are combined. In addition, a lot of information is still available only in textual form, both on the web and in the form of labels and abstracts in linked data sources. Therefore approaches are needed that can not only deal with the specific character of structured data but also with finding information in several sources, processing both structured and unstructured information, and combining such gathered information into one answer. The main objective of the open challenge on question answering over linked data (QALD) is to provide up-to-date, demanding benchmarks that establish a standard against which question answering systems over structured data can be evaluated and compared. QALD-4 is the fourth instalment of the QALD open challenge, comprising three tasks: multilingual question answering, biomedical question answering over interlinked data, and hybrid question answering.
Design and control of an underactuated cybernetic artificial hand

In this paper some research efforts towards the realization of a cybernetic hand prosthesis are presented with specific focus on the biomechatronic design and the preliminary electromyography-based control system. In particular, the analysis of the natural low level control mechanisms and of the cognitive feedback information has been used for designing the CYBERHAND prosthetic hand. An experimental setup of the CYBERHAND system including an electromyography-based control system, a preliminary low level control system and the first biomechatronic hand has been integrated and presented in this paper
Symbolic computations for random fields using second order perturbation method

The main idea is to show the application of symbolic computations in analysis of engineering systems with random parameters. The general computational methodology is based on the stochastic second order perturbation method and its implementation in the mathematical package MAPLE 6. The entire approach is displayed on the example of simple single degree of freedom dynamical system with random spring stiffness. The results of symbolic computations are derived numerically in the form of probabilistic moments of the structural response computed for the whole analysis time domain. The general methodology can be applied to all these engineering problems where the response can be derived symbolically in deterministic case, while input parameters of the system are random variables, fields or processes characterized by the probability density function (PDF) of any type.
Selection of classification boundaries using the logistic regression

We propose the method for selecting classification boundaries for the logistic regression model, by applying the sparse regularization. We can investigate which combination of classification boundaries are truly necessary for the multinomial logistic model by encouraging some of coefficient parameters themselves or their differences toward exactly zeros. The model is estimated by the maximum penalized likelihood method with the fused lasso type penalty. We also introduce some model selection criteria for evaluating models estimated by the penalized likelihood method. Simulation and real data analysis show insights that the proposed method goes well.
Oxylipin Biosynthesis Genes Positively Regulate Programmed Cell Death during Compatible Infections with the Synergistic Pair Potato Virus X-Potato Virus Y and Tomato Spotted Wilt Virus

ABSTRACT One of the most severe symptoms caused by compatible plant-virus interactions is systemic necrosis, which shares common attributes with the hypersensitive response to incompatible pathogens. Although several studies have identified viral symptom determinants responsible for systemic necrosis, mechanistic models of how they contribute to necrosis in infected plants remain scarce. Here, we examined the involvement of different branches of the oxylipin biosynthesis pathway in the systemic necrosis response caused either by the synergistic interaction of Potato virus X with Potato virus Y (PVX-PVY) or by Tomato spotted wilt virus (TSWV) in Nicotiana benthamiana. Silencing either 9-lipoxygenase (LOX), 13-LOX, or α-dioxygenase-1 (α-DOX-1) attenuated the programmed cell death (PCD)-associated symptoms caused by infection with either PVX-PVY or TSWV. In contrast, silencing of the jasmonic acid perception gene, COI1 (Coronatine insensitive 1), expedited cell death during infection with compatible viruses. This correlated with an enhanced expression of oxylipin biosynthesis genes and dioxygenase activity in PVX-PVY-infected plants. Moreover, the Arabidopsis thaliana double lox1 α-dox-1 mutant became less susceptible to TSWV infection. We conclude that oxylipin metabolism is a critical component that positively regulates the process of PCD during compatible plant-virus interactions but does not play a role in restraining virus accumulation in planta.
Development of pedestrian behavior model taking account of intention

In order for robots to safely move in human-robot coexisting environment, they must be able to predict their surrounding people's behavior. In this study, a pedestrian behavior model that produces humanlike behavior was developed. The model takes into account the pedestrian's intention. Based on the intention, the model pedestrian sets its subgoal and moves toward the subgoal according to virtual forces affected by other pedestrian and environment. The proposed model was verified through pedestrian observation experiments.
Using three AOSE toolkits to develop a sample design

At the 8th Agent-Oriented Software Engineering Workshop, the developers of tools supporting three popular agent-oriented methodologies (Tropos, Prometheus and Organization-based Multiagent Systems Engineering (O-MaSE)) demonstrated their tools using a common multi-agent system design case study: the Conference Management System. The methodologies are representative of the state-of-the-art in agent-oriented software methodologies, as they are some of the earliest and most mature agent-oriented methodologies currently available. The paper briefly summarises the three methodologies and their associated tools and then works through the analysis, architectural design and detailed design phases of the Conference Management system case study using each methodology and tool. The paper compares the models and concepts used during each phase and provides a discussion on the similarities and differences between them.
XMM-NEWTON DISCOVERY OF AN X-RAY FILAMENT IN COMA

XMM-Newton observations of the outskirts of the Coma cluster of galaxies confirm the existence of warm X-ray gas claimed previously and provide a robust estimate of its temperature (~ 0.2 keV) and oxygen abundance (~ 0.1 solar). Associating this emission with a 20 Mpc infall region in front of Coma, seen in the skewness of its galaxy velocity distribution, yields an estimate of the density of the warm gas of ~ 50 Pcritical . Our measurements of gas mass associated with the warm emission strongly support its nonvirialized nature, suggesting that we are observing the warm-hot intergalactic medium (WHIM). Our measurements provide a direct estimate of the O, Ne and Fe abundance of the WHIM. Differences with the reported Ne/O ratio for some OVI absorbers hints to different origin of the OVI absorbers and the Coma filament.
To Classify Opinion of Different Domain Using Machine Learning Techniques

— With the introduction of web 2.0 people is more familiar with internet. Peoples buy their product and post their opinion on merchant sites. Opinion mining is the task of identifying whether the opinion expressed in a article is constructive or unconstructive about a given topic . In this paper we apply machine learning techniques i.e. Naïve Bayes and Support vector machine of different domain. However we get the best results of SVM in compare to Naïve Bayes in our data set.
Broadband Active Receiving Patch With Resistive Equalization

The active integrated antenna (AIA) concept has been applied to design a broadband receiver front-end. A design procedure for active broadband patch antennas based on resistive equalization is presented. The use of the AIA has allowed the design of efficient RF front-ends by increasing its effective gain, noise figure, and merit . In addition to improving the classical parameters, the resistive equalization technique allows enlarging the bandwidths of the active antenna parameters versus the corresponding ones in passive antennas. A receiving patch antenna (with one amplifying stage) with a measured noise figure lower than 0.6 dB in a bandwidth over 38% and an effective gain improvement of 13 dB over the corresponding passive antenna has been achieved. The -parameter has also been measured for both the active and passive antenna, resulting in a relative planar of 16 dB/K, with a ripple of 0.5 dB, over a 30% bandwidth for the active antenna versus a of 22 dB/K for a typical front-end with a passive antenna over 20% bandwidth.
A wireless dynamic gesture user interface for HCI using hand data glove

In this paper, DG5 hand data glove is used to design an intelligent and efficient human-computer interface to interact with VLC media player. It maps the static keyboard with dynamic human hand gestures with 22 Degree of Freedom (DoF) to interact more natural way with computer. The result is very much appreciated showing the confusion matrix of various gestures used. In this paper, 10 complex gestures are used, that is Play, Pause, Forward, Backward, Next, Previous, Stop, Mute, Full Screen, and Null gestures. To study about the human-hand gestures four different age groups are taken, User A (20-30 years), User B (31-45 years), User C (46-60 years), and User D (61-above years). The decision tree a powerful learning algorithm is used to classify these gestures correctly. This enhances the user's interaction level with immersion feeling in augmented reality to 98.88% of accuracy rate.
Character Strengths and Life Satisfaction of High School Students

Character strengths are important personal qualities that are proposed to be productive and critical for lifelong optimal human development. This study investigated the distribution of the Values in Action character strengths among high school students and their relationship with satisfaction with life of the students. Using data from a sample of 210 students, results indicated that the top seven strengths were forgiveness, self-regulation, kindness, leadership, hope, love of learning and fairness whiles the least five were creativity, bravery, perseverance, curiosity and appreciation of beauty. Judgment, zest, love, kindness, prudence and humor independently significantly correlated with subjective wellbeing. Regression results showed that bravery, judgment, prudence, gratitude and humor made significant contribution in explaining subjective wellbeing with bravery making the largest unique contribution. Females scored significantly higher than males on five strengths. Implications of the findings for research, practice and emerging adulthood development of character strengths are discussed.
Gene Editing With Crispr/Cas9: A New Therapeutic Hope for Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a devastating disease resulting in progressive muscular weakness throughout life leading to death. This disease affects 1 in 3500 boys, who will die from cardiopulmonary failure in their early adulthood. Treatment options have been limited to palliative approaches. CRISPR/ Cas9, a novel gene therapy has recently showed a great potential in animal trials to correct the primary genetic lesion of DMD. These recent studies have put into question whether such trials should be translated into higher mammalian or even human studies.
Modeling Cooperative Diversity in a Wireless Relay Channel

Cooperative diversity is an attractive new way to increase throughput, reduce energy requirements and provide resistance to channel fading effects in wireless networks. Because of its distributed nature, this new approach to spatial diversity allows a network of relatively simple, single-antenna devices to achieve many of the celebrated advantages of physical antenna arrays. The objective of this work is to investigate the various strategies for cooperative diversity and to develop a modeling framework in which these strategies can be evaluated and new strategies can be developed. In this paper I present a Synchronous Dataflow (SDF) model for cooperative diversity in the wireless relay channel and an implementation designed in National Instruments’ (NI) LabView development environment.
Decoding the Genomic Architecture of Mammalian and Plant Genomes: Synteny Blocks and Large-scale Duplications

Motivation: The existing synteny block reconstruction algorithms use anchors (e.g., orthologous genes) shared over all genomes to construct the synteny blocks for multiple genomes. This approach, while efficient for a few genomes, cannot be scaled to address the need to construct synteny blocks in many mammalian genomes that are currently being sequenced. The problem is that the number of anchors shared among all genomes quickly decreases with the increase in the number of genomes. Another problem is that many genomes (plant genomes in particular) had extensive duplications, which makes decoding of genomic architecture and rearrangement analysis in plants difficult. The existing synteny block generation algorithms in plants do not address the issue of generating non-overlapping synteny blocks suitable for analyzing rearrangements and evolution history of duplications. Results: In this paper we present a new synteny block generation algorithm based on the ABruijn graph framework that overcomes these difficulties. We applied our algorithm to derive nonoverlapping synteny blocks in Arabidopsis thaliana. We also generalized this approach to synteny block generation for multiple genomes. The algorithm was applied to human-mouse-rat-dog-chicken genomes and it is able to recover synteny blocks missed by algorithms requiring 5-way anchors.
Tempo: specializing systems applications and beyond

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Modelling User Navigation

This paper proposes the use of neural networks as a tool for studying navigation within virtual worlds. Results indicate that the network learned to predict the next step for a given trajectory. The analysis of hidden layer shows that the network was able to differentiate between two groups of users identified on the basis of their performance for a spatial task. Time series analysis of hidden node activation values and input vectors suggested that certain hidden units become specialised for place and heading, respectively. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction applications are discussed.
The /spl mu/PP ASIC: design, methodologies and tools for a pay phone system-on-a-chip based on an ARM core and design reuse

This paper describes the /spl mu/PP (Microcontroller for Pay Phones) ASIC, a system-on-a-chip solution based on the present Spanish pay phone system. The design integrates an ARM embedded microprocessor, several third party blocks and new custom modules developed in house, using ARM's Advanced Microprocessors Bus Architecture (AMBA). The system has been designed for low power consumption and management. Design reuse, aided by the use of new management tools, and co-design, allowed an important reduction in global design time.
A flexible camera positioning strategy for robot-based visual inspection applications

This paper presents a flexible camera positioning strategy to deal with unknown object poses in a visual inspection application. The object's CAD model is used in a view-based strategy to estimate the object pose. An effective lookup table method is adopted to speed up the estimation. The principal component analysis (PCA) is used to reduce the lookup table size and save memory space. Compared with those edge-based approaches which require good initial pose estimation, our method can find the initial pose in a large range without any initial guess. With the pose estimation precise Eye-in-Hand camera positioning is realized by homography-based visual servo to inspect the object. The inspection strategy with unknown object poses is described in detail. Experiments are carried out to evaluate the system performances.
Automated program verification made SYMPLAR: symbolic permissions for lightweight automated reasoning

Research in automated program verification against specifications written in first-order logic has come a long way. Ever-faster Satisfiability Modulo Theories (SMT) solvers [Barrett et al. 2010] promise to verify program instructions quickly against specifications. Unfortunately, aliasing still prevents automated program verification tools from easily and soundly verifying interesting programs. This paper introduces the use of symbolic permissions as the basis for sound automated program verification. Symbolic permissions provide a simple alias control mechanism with expressiveness similar to the well-known fractional permissions [Boyland 2003]. The paper shows that symbolic permissions can be enforced with a linear refinement typechecking procedure. Once permissions are checked, aliasing can essentially be ignored for the purposes of program verification, which allows taking full advantage of SMT solvers for doing the heavy verification lifting. The paper shows that a verification tool based on symbolic permissions can easily verify a design pattern with inherent aliasing challenges.
Effect of Dust Deposition on Stomatal Conductance and Leaf Temperature of Cotton in Northwest China

The Xinjiang Region in Northwest China is known as the “dust center” of the Eurasian mainland. Dust on the leaf surface affects overall plant development. While emphasis was on studying the impacts of industrial dust particles on crop development, the effect of natural dust deposition on the physiological parameters of cotton had not been studied before. The objective of this study was to examine the effects of dust deposits on cotton leaves and to estimate their impact on crop development and yield. For this purpose, an experiment was set up having two treatments and a control. In Treatment 1, cotton leaves were cleaned with water at three-day intervals or after a natural dust fall. In Treatment 2, 100 g·m−2 of dust was applied at 10-day intervals. The control received neither additional dust nor cleaning. In all of the treatments, stomatal conductance, leaf temperature, biomass and yield were measured. The results show a 28% reduction in yield and 30% reduction in stomatal conductance of the dust treatment compared to the control treatment. This indicates blocking of the stomata on the top of the leaf surface. In addition, the canopy temperature of the dust-applied leaves was always higher than the control and treatment.