Miracle-dz/UniFAR-FTUs huggingface dataset:
Forepart Based Captcha Segmentation And Recognition Using Dft

CAPTCHAs (Completely Automated Public Turing Test to Tell Computers and Humans Apart) have been widely used across the Internet to defend against malicious bot programs and hence it act as a type of challenge-response test used in computing as an attempt to ensure that the response is generated by a person. Researchers are advancing in the field of; making CAPTCHA more complex so that hackers find it difficult for breaking them. However merged characters are the major cause of recognition errors for humans as well as for bots. Different websites use varieties of CAPTCHA. Based on the style and orientation of characters, we have classified some of the CAPTCHAs into four classes which include CAPTCHA with complex background, BotBlock and BotDetect CAPTCHA, google CAPTCHAs, and overlapped CAPTCHAs. The different methods used for segmentation and recognition of these CAPTCHAs include Connected Component Method(CCT), Colour Inversion technique, Forepart Prediction(FP) and masking, and Discrete Fourier Transform(DFT). In this paper we have segmented the first three classes of CAPTCHAs using various techniques, and the fourth class contains the class with overlapped characters and we could segment and recognise them using a navel technique called Discrete Fourier Transform with a success ratio of 80%.
Analysis of the Opsin Repertoire in the Tardigrade Hypsibius dujardini Provides Insights into the Evolution of Opsin Genes in Panarthropoda

Screening of a deeply sequenced transcriptome using Illumina sequencing as well as the genome of the tardigrade Hypsibius dujardini revealed a set of five opsin genes. To clarify the phylogenetic position of these genes and to elucidate the evolutionary history of opsins in Panarthropoda (Onychophora + Tardigrada + Arthropoda), we reconstructed the phylogeny of broadly sampled metazoan opsin genes using maximum likelihood and Bayesian inference methods in conjunction with carefully selected substitution models. According to our findings, the opsin repertoire of H. dujardini comprises representatives of all three major bilaterian opsin clades, including one r-opsin, three c-opsins, and a Group 4 opsin (neuropsin/opsin-5). The identification of the tardigrade ortholog of neuropsin/opsin-5 is the first record of this opsin type in a protostome, but our screening of available metazoan genomes revealed that it is also present in other protostomes. Our opsin phylogeny further suggests that two r-opsins, including an “arthropsin,” were present in the last common ancestor of Panarthropoda. Although both r-opsin lineages were retained in Onychophora and Arthropoda, the arthropsin was lost in Tardigrada. The single (most likely visual) r-opsin found in H. dujardini supports the hypothesis of monochromatic vision in the panarthropod ancestor, whereas two duplications of the ancestral panarthropod c-opsin have led to three c-opsins in tardigrades. Although the early-branching nodes are unstable within the metazoans, our findings suggest that the last common ancestor of Bilateria possessed six opsins: Two r-opsins, one c-opsin, and three Group 4 opsins, one of which (Go opsin) was lost in the ecdysozoan lineage.
Intentional resolution of privacy protection in database systems

Traditionally, privacy protection in database systems is understood to be the control over what information a given user can get from a database. This paper is concerned with another, independent, dimension of privacy protection, the control over what a user is allowed to do with a piece of information supplied to him by the database. The ability to condition the supply of information on its intended use is called here “intentional resolution” of privacy protection. The practical importance of intentional resolution is demonstrated by several examples, and its realization is discussed. It is shown that intentional resolution can be achieved, but that it involves a radical change from the traditional approach to the process of user-database interaction. In particular, it appears to be necessary for the database to impose a certain amount of control over the internal behavior of users' programs which interact with it. A model for user-database interaction which admits such a control is developed.
The cross-field DBN for image recognition

In this paper, a new cross-field deep belief network (DBN) model is designed to recognize images. The bottom layer of model is shared to capture low-level features while the high-layer neurons are detached to capture high-level features of the specific fields. The cross-field unlabeled sample sets are used to train the model due to the shared neurons, which can improve the recognition performance in current internet environment with large scale cross-field unlabeled images. The cross-field DBN is realized by Numpy and Theano, and tested by Mixed National Institute of Standards and Technology (MNIST) data set of handwriting characters and Columbia Object Image Library (COIL) data set of object images. The simulation shows that the cross-field DBN has better performance than traditional DBN due to the help of cross-field unlabeled training data. In addition, the training of sample set after binarization can greatly improve recognition performance.
Understanding Users Intent by Deducing Domain Knowledge Hidden in Web Search Query Keywords

Search Engines are used by people on a daily basis to retrieve information from the web. When an ambiguous word is present in a query, specific sense of the keyword is not considered during the search process. Search engines return a large amount of web pages as results from all the possible contexts. Users tend to browse only few pages. Improving quality of retrieved results is a challenge and needs research. There is no attempt made by search engines to establish the context/domain/intent of the query keyword, before forwarding query to the engine. Current research trends in word sense disambiguation and availability of huge knowledge bases like BabelNet which encompasses WordNet and Wikipedia, together with WordNet Domains in which senses are annotated with domain labels indicates scope for developing methods capable of performing semantic analysis of search engine queries. In this paper, an algorithm for automatically establishing context in web search queries using modern automatic word sense disambiguation technique is proposed. Further, it is illustrated how Query Expansion can be performed using the interactive feedback and deduced domain of the query keyword. The domain knowledge and query expansion helps retrieve high quality results, specific to the user’s intent.
Mother-Child and Teacher-Child Relationships and Their Associations with School Adjustment in Pre-School

Citation: Nur, İ. , Aktaş-Arnas, Y. , Abbak, B. S. , & Kale, M. (2018). Mother-child and teacher-child relationships and their associations with school adjustment in pre-school. Educational Sciences: Theory & Practice, 18, 201–220. http://dx.doi. org/10.12738/estp.2018. 1.0608 1 Correspondence to: İmray Nur (PhD), Department of Child Development, Osmaniye Korkut Ata University, Osmaniye Turkey. Email: imraynur@osmaniye.edu. tr 2 Department of Pre-School Education, Çukurova University, Adana Turkey. Email: yasare@cu.edu. tr 3 Department of Child Development, Çukurova University, Adana Turkey. Email: bsabbak@cu.edu. tr 4 Department of Child Development, Çağ University, Mersin Turkey. Email: mustafakale@cag.edu. tr Abstract This research aims to investigate the contributions of Turkish pre-school children’s levels of positive/ conflicting relationships with their mothers and close/conflicting relationships with their teachers in predicting their adjustment to school. The sample of the study consists of 190 six-year-old children attending public pre-schools in Adana (a city in southern Turkey), as well as their mothers and teachers. For the data analysis, hierarchical regression analysis has been conducted. The results of the study show the positive relationship established with the mother and teacher to be related to an increase in children’s school-adjustment behaviors. A positive relationship has been noted for positive mother-child relationships with children’s cooperative participation, self-directedness, and total school adjustment. The results indicate a positive link for closeness in the teacher-child relationship with school liking, cooperative participation, self-directedness, and total school adjustment. Additionally, a positive relationship has been observed for the conflictive teacher-child relationship with school avoidance. An inverse relationship has also been observed for the conflictive teacher-child relationship with cooperative participation, self-directedness, and school adjustment. As conflicts with a teacher increase, the child’s school adjustment decreases.
Effect of salinity on osmolytes and relative water content of selected rice genotypes

Reduction in relative water content (RWC) and photosynthesis (dry matter) is a common effect of salinity stress. In the present study, 7 days old rice plants were exposed to 0 (control) and 100 mM NaCl salinity for 7 days to determine the osmolytes accumulation and relative water content (RWC) in leaves. We observed that shoot dry matter, relative water content and K content decreased significantly with the increasing of salinity. In contrast, Na and proline content excessively increased in the leaves of salinity stressed plant. The results revealed that both the organic (proline) and inorganic (K) osmolytes accumulation may be responsible for stress alleviation by retaining water in cell.
Online farming based on embedded systems and wireless sensor networks

The agricultural scenario seems to be one of the most promising application areas for WSN due to the necessity of providing the agricultural production chain in terms of precision and quality. This involves a careful system design, since requirements are very strict, battery life-time maximization, robustness, recovery strategies, network flexibility and re-configurability. This paper implements zigbee based wireless sensor network in agriculture such as monitoring of environmental conditions like weather, soil moisture content, soil temperature, soil fertility, weed detection, water level, monitoring growth of the crop, precision agriculture, automated irrigation facility and storage of agricultural products. The aim of this project is to monitor and maintain the farm from any part of the world through internet. Monitoring is done with the help of wireless sensor networks and all the control process is done with the help of the microcontrollers. Wireless cameras are used to feed live video of the farm to any part of the world. With the help of this project, modern technologies and new ideas can be implemented in the farm sector of our country. A farmer can see the real condition of his farm and also control his farm from any part of the world by logging into farming website. This makes the Indian farmers feel comfortable and reduces the risks involved in irrigation. The idea has the potential to attract entrepreneurs to invest in the agricultural sector.
Evolution Strategies Based Particle Filters for Simultaneous State and Parameter Estimation of Nonlinear Stochastic Models

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distri- bution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which deteriorates the filter performance, and apply it to simultaneous state and parameter estimation of nonlinear state space models. Results of numerical simulation studies illustrate the applicability of this approach.
Estimating Emotion for Each Personality by Analyzing BVP

This research estimates emotions of university students from their BVP (blood volume pulse). Negative emotion of university students causes school dropout, which is becoming a serious problem in Japan. It is indispensable for school staffs and counselors to know when and where students have negative emotion in the campus. Since BVP signals along with emotion changes vary with personality types, we build a model dependent on personality type, to estimate student emotion from characteristics of blood volume signals. Experimental results show that the model for each personality type improves the accuracy of emotion estimation for new students. Positive or negative emotion estimated from BVP signals contributes to enhancement of campus environment by school counselors.
Induction by Hypoxia of Heterologous-Protein Production with the KlPDC1 Promoter in Yeasts

ABSTRACT The control of promoter activity by oxygen availability appears to be an intriguing system for heterologous protein production. In fact, during cell growth in a bioreactor, an oxygen shortage is easily obtained simply by interrupting the air supply. The purpose of our work was to explore the possible use of hypoxic induction of the KlPDC1 promoter to direct heterologous gene expression in yeast. In the present study, an expression system based on the KlPDC1 promoter was developed and characterized. Several heterologous proteins, differing in size, origin, localization, and posttranslational modification, were successfully expressed in Kluyveromyces lactis under the control of the wild type or a modified promoter sequence, with a production ratio between 4 and more than 100. Yields were further optimized by a more accurate control of hypoxic physiological conditions. Production of as high as 180 mg/liter of human interleukin-1β was obtained, representing the highest value obtained with yeasts in a lab-scale bioreactor to date. Moreover, the transferability of our system to related yeasts was assessed. The lacZ gene from Escherichia coli was cloned downstream of the KlPDC1 promoter in order to get β-galactosidase activity in response to induction of the promoter. A centromeric vector harboring this expression cassette was introduced in Saccharomyces cerevisiae and in Zygosaccharomyces bailii, and effects of hypoxic induction were measured and compared to those already observed in K. lactis cells. Interestingly, we found that the induction still worked in Z. bailii; thus, this promotor constitutes a possible inducible system for this new nonconventional host.
TrueMobile: A Mobile Robotic Wireless and Sensor Network Testbed

Simulation has been the dominant research methodology in wireless and sensor networking. When mobility is added, the frequency of real-world experimentation becomes tiny. However, it is becoming clear that simulation models do not sufficiently capture radio and sensor irregularity in a complex, real-world environment, especially indoors. Unfortunately, the high costs in labor, equipment, and tedium of truly mobile experimental infrastructure in real-world environments typically present an insurmountable barrier to such experimentation. We describe our experience in creating an initial testbed to lower those barriers. Our system, called “TrueMobile,” already deployed for public use, provides the first remotelyaccessible mobile wireless and sensor testbed. Robots carry motes and single board computers running Linux through a fixed field of sensor-equipped motes, all running the user’s selected software. In real-time, interactively or driven by preprogrammed events, remote users can position the robots, control all the computers and network interfaces, and log data. TrueMobile provides simple path planning, a visionbased tracking system accurate to 1 cm, live maps, and webcams. Precise positioning and automation allow quick and painless evaluation of location and mobility effects on wireless protocols, location algorithms, and sensor-driven applications. We present TrueMobile’s design and implementation, evaluate key aspects of its performance, and describe a few experiments demonstrating its generality and power.
A Statistical Data Fusion Technique in Virtual Data Integration Environment

Data fusion in the virtual data integration environment starts after detecting and clustering duplicated records from the different integrated data sources. It refers to the process of selecting or fusing attribute values from the clustered duplicates into a single record representing the real world object. In this paper, a statistical technique for data fusion is introduced based on some probabilistic scores from both data sources and clustered duplicates.
A new GTS allocation scheme for IEEE 802.15.4 networks with improved bandwidth utilization

The IEEE 802.15. 4 standard enables device level wireless connectivity in personal area networks. Its medium access control (MAC) protocol supports the exclusive use of a wireless channel through guaranteed time slot (GTS). However, the bandwidth underutilization problem occurs in GTSs when the used bandwidth is less than the available. In this paper, a new GTS scheme is presented to allow more devices to share the bandwidth within the same period. The evaluation and analysis reveals that the bandwidth utilization is improved.
Distance Encoded Product Quantization

Many binary code embedding techniques have been proposed for large-scale approximate nearest neighbor search in computer vision. Recently, product quantization that encodes the cluster index in each subspace has been shown to provide impressive accuracy for nearest neighbor search. In this paper, we explore a simple question: is it best to use all the bit budget for encoding a cluster index in each subspace? We have found that as data points are located farther away from the centers of their clusters, the error of estimated distances among those points becomes larger. To address this issue, we propose a novel encoding scheme that distributes the available bit budget to encoding both the cluster index and the quantized distance between a point and its cluster center. We also propose two different distance metrics tailored to our encoding scheme. We have tested our method against the-state-of-the-art techniques on several well-known benchmarks, and found that our method consistently improves the accuracy over other tested methods. This result is achieved mainly because our method accurately estimates distances between two data points with the new binary codes and distance metric.
DISCO: Describing Images Using Scene Contexts and Objects

In this paper, we propose a bottom-up approach to generating short descriptive sentences from images, to enhance scene understanding. We demonstrate automatic methods for mapping the visual content in an image to natural spoken or written language. We also introduce a human-in-the-loop evaluation strategy that quantitatively captures the meaningfulness of the generated sentences. We recorded a correctness rate of 60.34% when human users were asked to judge the meaningfulness of the sentences generated from relatively challenging images. Also, our automatic methods compared well with the state-of-the-art techniques for the related computer vision tasks.
Does the Prospect of Fulfilling Belonging Affect Social Responses to Rejection? A Conceptual Replication Attempt

Historically, one of the biggest paradoxes in the rejection literature was that rejected people sometimes behaved antisocially and at other times prosocially. Researchers responded to this paradox by demonstrating that the prospect of fulfilling belonging predicted these varied responses. A close inspection of the foundational studies, however, revealed small sample sizes relative to today’s standards. Hence, we conducted a conceptual replication of the prospect of fulfilling belonging hypothesis using a high-powered 2-day preregistered study. On Day 1, we manipulated the prospect of fulfilling belonging through a profile exchange with a confederate. On Day 2, we manipulated rejection using a recall paradigm and then measured prosocial and antisocial responses toward the confederate. Rejected participants who expected the confederate to fulfill belonging showed similar levels of prosocial and antisocial responses compared with those who did not. These results suggest that the prospect of fulfilling belonging hypothesis needs further refinement.
Designing and Applying an Education IaaS System based on OpenStack

This paper designs and implements an IaaS (Infrastructure as a Service) system by using OpenStack. To bring deduplication storage of VM images, this paper uses LiveDFS as the file system in image storage backend. And in order to offer stable persistent volumes to VM instances, this paper develops a distributed block-level storage system called ORTHRUS which is integrated into this IaaS system. Additionally, this paper deploys Ganglia monitoring system in the IaaS system to monitor all the physical nodes VM instances. At last, this paper designs and implements a high-performance service, a net disk service and an education management service on this IaaS system.
We the minority-of-minorities: a narrative inquiry of black female academics in the United Kingdom

Abstract This article highlights the additional marginalisation of black female academics within the UK academy of higher education. The article engages with the narratives of eight such women as they navigate their careers as a minority-of-minorities within high-ranking institutions. The literature on black academic severe under-representation, intersectionality theory and the author’s own experience as a black female academic is used abductively to story the narratives and engage the reader towards an emancipatory aim. Critically, it highlights the additional marginalisation of black academics due to racism and the double marginalisation of black females based primarily on their race and gender. The findings both confirm and richly contextualise the literature from an insider perspective. The narratives provide implications for policy and further research.
A Survey : Ontology Based Information Retrieval For Sentiment Analysis

The rapidly growing data on the web has created a big challenge for directing the user to the web pages in their areas of interest. Sentiment analysis or Opinion mining plays an important role in finding the area of interest based on user’s previous actions. Social networking portals have been widely used for expressing opinions in the public domain. Text based sentiment classifiers often prove inefficient. Semantic web is the solution for Searching relevant information from huge repository of unstructured web data. Semantic web leads the idea of ontology as background knowledge represents the concepts and the relationship in specialized domain. The basic idea behind this survey is to take domain ontology for providing more elaborate sentiment scores. We discuss an approach where information retrieved from web and ontology is created before sentiment classification and focuses on how to classify the semantic orientation of text.
On the connectivity of wireless networks with multiple directional antennas

The network connectivity is one of important measures of the performance of wireless networks. However, most of current studies on the network connectivity only consider either an SOMN network, where each node is mounted with a single omni-directional antenna, or an SDA network, where each node is mounted with a single directional antenna. Using multiple directional antennas instead of a single directional antenna can potentially improve the network performance. In this paper, we investigate the connectivity of a novel network, in terms of an MDA network, where each node is mounted with multiple directional antennas. We found that MDA networks have much stronger network connectivity than other existing networks (such as SOMN and SDA networks), and its connectivity degree heavily depends on the number of antennas, the beamwidth of each antenna and the path loss factor. The enhancement mainly owes to the usage of multiple antennas and the longer transmission range of directional antennas.