Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Online Change-point Detection in Video Sequences

We present the Cumulative Sum (CUSUM) stopping rule, applied to Computer Vision problems, to automatically detect changes in either parametric or nonparametric distributions, online or off-line. Our approach is based on using the previously received data of the sequence to detect a change in data that are to be received. We assume that no significant change has occurred up to an unknown time instance. Then a change in the distribution of the observations occurs and the objective is to estimate this instance. We test the hypotheses of no change occurs vs. a change occurs at the current frame, which is done by the CUSUM stopping rule. We apply our framework to the case of continuous 3D hand tracking, where the high dofs, the fast finger articulations, the large rotations and the frequent occlusions often cause error accumulation. Also we illustrate the performance of our approach in video segmentation, and specifically in segmentation of fingerspelling in American Sign Language (ASL) videos.
Sposobnost učenja dviju kompetitivnih vrsta gušterica Podarcis siculus i Podarcis melisellensis

Italian wall lizard, Podarcis siculus (Rafinesque, 1810) and Dalmatian wall lizard, Podarcis melisellesis (Braun, 1877) are two species from family Lacertidae. Podarcis siculus is widespread in Italy, but spreads also on Adriatic islands, while Podarcis melisellesis is spread over coastal belt from northwest coast of Italy to nortwestern Albania. When these two species share the same habitat, Podarcis siculus overpower Podarcis melisellesis as the dominant competitor. In this Graduation thesis I have studied learning as one of the factors influencing the competition between these two species. The research was carried out on total of 56 individuals. Prior to the experimental procedure, the animals passed the three-day habituation and then they were tested for ten days in the eighth radial labyrinth. The results have shown that females of P. siculus move more and change their behavior after the seventh day, suggesting some form of spatial recognition. Also, the results showed that males of P. melisellensis showed a trend of increasing entering in goal zone, which indicate level of spatial recognition. But, overall, this study has shown that learning is not crucial factor which can affects dominance of one species over the other, also it indicates that both of this species are not the best model examples for learning, as only two parameters have been statistically and ecologically significant.
ENRICHING THE E-LEARNING CONTENTS USING INTERLINKING

Interlinking e-Learning resources on the Web enriches the contents and help learners to reach more qualified resources. Due to the acceptance of the Linked Data approach by many e-Learning repositories, creating links between e-Learning contents and useful information on the Web of Data can lead to the enrichment of the contents in the repositories. This paper focuses on the text enrichment aspect of interlinking, where we discuss how the descriptions of learning objects as part of the metadata can be enriched when they are connected to the LOD datasets. A case study on Open Discovery Space (as an e-Learning repository) is also presented in this research.
Comparative Study of Intel R200, Kinect v2, and Primesense RGB-D Sensors Performance Outdoors

Recent emergence of affordable consumer RGB-D sensors have pushed efforts to use these sensors for a variety of applications under different environmental conditions. Sensors, such as the Microsoft Kinect v2, Asus Xtion Pro Live, and the Intel Realsense R200, are easily accessible RGB-D sensors each utilizing time-of-flight (ToF), structured-light (SL), and active stereo vision (ASV) technologies, respectively, to calculate depth data. All three sensors utilize near-infrared (NIR) light projection (750–1400nm) to obtain depth data. This paper compares all three sensors for capturing 3D surface data of simple objects outdoors where there’s strong sunlight NIR interference. The primary contribution of this paper is to provide a practical evaluation of the quality of the 3D data returned of object’s surfaces from the sensors under strong NIR interference. In general, in terms of capturing 3D surface data of objects outdoors, the Kinect v2 is better than the R200. This is highly dependent on object distance as well as strength of the NIR interference. The Intel R200 sensor is capable of capturing depth data of objects at further ranges than the Kinect v2 but cannot capture depth data of homogeneously textured surfaces. The Asus Xtion cannot capture 3D data outdoors. Under indoor conditions, the Kinect v2 and the Asus Xtion perform better at capturing 3D surface data of objects than the Intel R200.
Control of Green House pests

Insect pests are the major threats to production and productivity of greenhouse crops worldwide. Presence of warm, humid conditions and abundant food under protected structures provide a stable environment and habitat for pest development. Protected cultivation/Greenhouse technology has been in use for crop production for more than fifty countries all over the world. China is believed to have adopted a plastic greenhouse concept to a great extent. Japan, with about 42,000 ha. (hectare) under plastic and glass cover land holdings with shorter growing seasons in Holland and Japan have been the reason behind adopting Protected cultivation /greenhouse for intensive crop production.
Sensor validation for turbofan engines using an autoassociative neural network

This paper develops a novel sensor validation approach for the F100 turbofan engine by using an autoassociative neural network. The proposed approach utilizes dimensionality reduction to develop the neural network for sensor failure detection and data recovery. In the autoassociative neural network, the redundant sensor information is compressed, mixed and reorganized into a smaller number of network nodes in the first part of the network. The compressed information is then used to regenerate the original redundant data at the output. Due to the information mixture, if some sensors fail, other sensor data still provide enough information to generate the good estimates to replace the faulty measurements. The simulation results demonstrate the applicability of the proposed scheme.
Morphological traits and yield of Ajowan affected by different irrigation intervals and growth regulators

Two field experiments were carried out to evaluate the effect of salicylic acid and abscisic acid applications on some morphological traits and yield of ajowan ( Carum copticum L.) under different watering conditions. Irrigation intervals (irrigation after 70, 100, 130 and 160 mm evaporation from class A pan) were located in main plots and exogenous applications of water (control), salicylic acid (0 and 1 mM) and abscisic acid (0 and 50 micro-molar) were allocated to sub plots. Water stress negatively affected the morphological traits of the Ajowan. Stem diameter, branches per plant, leaves number per plant, biological yield and grain yield per plant of Ajowan were considerably improved by application of salicylic acid and abscisic acid. Salicylic acid treatment was more effective than abscisic acid treatment, in this study, salicylic acid treatment increased the stem diameter and leaves number per plant more than abscisic acid and caused a yield enhancement in Ajowan plants. In general, foliar spray of salicylic acid and abscisic acid could alter morphological traits and yield of Ajowan.
Genetic diversity of different breeds of Kazakh sheep using microsatellite analysis

Abstract A total of 75 individuals from five sheep populations in Kazakhstan were investigated based on 12 STR (short tandem repeat, also known as microsatellite) markers in order to study their genetic structure and phylogenetic relationship based on genetic distances. These sheep had a high level of genetic diversity. In total, 163 alleles were found in all the populations using 12 microsatellite loci. The mean number of alleles, effective number of alleles, and polymorphism information content (PIC) values per loci were 13.4, 5.9, and 0.78, respectively. Comparing the allelic diversity between the populations, the highest genetic diversity was observed in the Edilbay-1 sheep breed (8.333±0.644), and the lowest parameter was for Kazakh Arkhar-Merino (7.083±0.633). In all populations, there is a deficiency of heterozygosity. The largest genetic diversity was found in loci INRA023 and CSRD247 with 16 alleles, and the smallest polymorphism was noted for the locus D5S2 with 8 alleles. The level of observed heterozygosity was in the range 0.678±0.051 for Kazakh Arkhar-Merino and 0.767±0.047 for Kazakh fat-tailed coarse wool. The expected heterozygosity level range was from 0.702±0.033 for Kazakh Arkhar-Merino to 0.777±0.023 for Edilbay-1. When 12 microsatellite loci are compared, the OarFCB20 locus showed the highest level of genetic variability. Excess of heterozygosity was observed at three loci; MAF065, McM042, and OarFCB20. The highest genetic distance was observed between Kazakh Arkhar-Merino and Edilbay-1, whereas the genetic distance between Edilbay-1 and Edilbay-2 is the smallest using Nei's standard genetic distance. The Edilbay-1 sheep breed possesses the largest genetic diversity among these five populations.
Fraction and Spatial Organization of Tumor-Infiltrating Lymphocytes Correlating with Bladder Cancer Patient Survival

Recent studies based on deep learning on pathology images have shown the potential prognostic role of Tumor-infiltrating lymphocytes (TILs) in many cancer types. In general, most of these studies focused on detecting, quantifying and identifying TILs and spatial organization in entire whole slide images (WSIs) including both non-cancer and cancer regions. In this work, we hypothesize that TILs present in cancer regions not entire WSIs could have prognostic values. Here we present an automatic technique based on convolutional neural networks (CNN) that detects both cancer and TILs regions, and explores fraction and spatial organization of TILs in the detected cancer region from WSIs. A novel set of quantitative histological image features reflecting TILs fraction and spatial organization is extracted and used to stratify patients with distinct survival outcomes. In experiments using 277 different patient pathology slides selected from The Cancer Genome Atlas (TCGA) bladder cancer cohort, we show that bladder cancer patient survival is significantly correlated with our designed TIL-related image features, with a log-rank test p value below 0.05. Our method is extensible to histopathology images of other organs for predicting patient survival via TIL analysis.
New Material Concepts for Forgings

—After a thousand years of steel processing, many centuries of experimental development and intensive scientific research applying the most innovative techniques in the 19th and 20th centuries it might seem that the potential of steels has reached its maximum. Yet, new possibilities of modifying steel structure and thus influencing its properties keep appearing [1-4]. This article introduces the authors' new findings about steels and their treatment, which could influence the overall image of die forging and push the limits of forged products in the near future. Low cost alloyed steels with tensile strength of about 2000 MPa and ductility over 10 % for die forging produced by a straightforward procedure with low energy consumption in mind seem to be a promising start.
NCeSS Project: Data Mining for Social Scientists

We will discuss the work being undertaken on the NCeSS data mining project, a one year project at the University of Manchester which began at the start of 2007, to develop data mining tools of value to the social science community. Our primary goal is to produce a suite of data mining codes, supported by a web interface, to allow social scientists to mine their datasets in a straightforward way and hence, gain new insights into their data. In order to fully define the requirements, we are looking at a range of typical datasets to find out what forms they take and the applications and algorithms that will be required. In this paper, we will describe a number of these datasets and will discuss how easily data mining techniques can be used to extract information from the data that would either not be possible or would be too time consuming by more standard methods.
HOW EFFECTIVE IS DATA RESOURCE MANAGEMENT?Reassessing Strategic Objectives

Abstract For more than a decade, data base management systems (DBMSs) have been proclaimed as the panacea for data integration and redundancy problems. Are organizations reaping the benefits of data base technology? What specific data resource management tasks have they failed to address effectively? A study of 276 organizations seeks to address these questions and to describe and diagnose the data resource management problems that corporations face today.
Using Wikipedia Knowledge and Query Types in a New Indexing Approach for Web Search Engines

_____________________________________________________________________________ The Web is comprised of a vast quantity of text. Modern search engines struggle to index it independent of the structure of queries and type of Web data, and commonly use indexing based on Web‘s graph structure to identify high-quality relevant pages. However, despite the apparent widespread use of these algorithms, Web indexing based on human feedback and document content is controversial. There are many fundamental questions that need to be addressed, including: How many types of domains/websites are there in the Web? What type of data is in each type of domain? For each type, which segments/HTML fields in the documents are most useful? What are the relationships between the segments? How can web content be indexed efficiently in all forms of document configurations? Our investigation of these questions has led to a novel way to use Wikipedia to find the relationships between the query structures and document configurations throughout the document indexing process and to use them to build an efficient index that allows fast indexing and searching, and optimizes the retrieval of highly relevant results. We consider the top page on the ranked list to be highly important in determining the types of queries. Our aim is to design a powerful search engine with a strong focus on how to make the first page highly relevant to the user, and on how to retrieve other pages based on that first page. Through processing the user query using the Wikipedia index and determining the type of the query, our approach could trace the path of a query in our index, and retrieve specific results for each type. We use two kinds of data to increase the relevancy and efficiency of the ranked results: offline and real-time. Traditional search engines find it difficult to use these two kinds of data together, because building a real-time index from social data and integrating it with the index for the offline data is difficult in a traditional distributed index. As a source of offline data, we use data from the Text Retrieval Conference (TREC) evaluation campaign. The web track at TREC offers researchers chance to investigate different retrieval approaches for web indexing and searching. The crawled offline dataset makes it possible to design powerful search engines that extends current methods and to evaluate and compare them. We propose a new indexing method, based on the structures of the queries and the content of documents. Our search engine uses a core index for offline data and a hash index for real-time
A Survey on Data Mining Methods for Malware Detection

Malware is any type of malicious software that has the capability to enter into system without authorization of the users. Thus malware detection is the important issue in the computer security. Signature based detection is more popular method to detect the malware attack but main drawback of this method is that it is not used to detect the Zero-day attack. We need to update the database regularly and human experts are needed to create the new signature. The drawbacks of Signature based malware detection is minimized by using heuristic method. Heuristic method is used to detect zero-day attacks. There are various methods used to detect the malware like n-gram method, Finite state automaton method, Control Flow Graph method, N-gram analysis at byte level etc. These methods having their various advantages and disadvantages. This study enlightens the various methods used to detect malwares.
Prevention of Mother-to-Child Transmission of HIV in Pregnant Malawian Adolescents

Author(s): Scarr, Ellen Marie | Advisor(s): Rankin, Sally H | Abstract: The HIV/AIDS epidemic is one of the most significant public health challenges of our times. Interventions have slowed the number of deaths from AIDS and allowed those infected to live longer than was previously possible. While most HIV infections continue to be transmitted via heterosexual sex, vertical transmission from mother to child remains the primary cause of pediatric HIV infections. Prevention of mother-to-child transmission (PMTCT) of HIV is a major focus, with rapid scale up of programs designed to initiate antiretroviral therapy (ART) in all pregnant women. One group of vulnerable pregnant females is adolescents; few studies have included pregnant HIV-infected adolescents. The purpose of this study was to determine HIV prevalence in a population of pregnant adolescents and elicit the barriers and facilitators of the uptake of PMTCT services in those who were HIV-infected. A mixed methods study was conducted in Blantyre, Malawi. A survey questionnaire sought demographic and reproductive health information; in-depth interviews were conducted with those who revealed their HIV infection. The interview questions sought to elicit the barriers and facilitators of adhering to PMTCT protocols faced by these participants. The survey questionnaire determined that the study population had an HIV prevalence of 7.8%, higher than in the general Malawian adolescent population. Those who were orphaned and had a history of forced sexual encounter(s) were more likely to be HIV-infected. The interviews with HIV-infected pregnant adolescents found that all had revealed their HIV status to at least one family member; two who were married had not told their husbands. All identified the support they received as important to their adherence to ART. Few barriers to adherence were identified: several mentioned the stigmatization of HIV, but such fears did not preclude their adhering to the PMTCT protocols. As children who were perinatally infected with HIV live into adolescence, pregnancy will become more common in this population. Identifying the characteristics of adolescent pregnancy complicated by HIV allows health care providers to capitalize on the strengths of this population to prevent HIV infection in their children.
Recent Advances in Hormonal Regulation and Cross-Talk during Non-Climacteric Fruit Development and Ripening

Fleshy fruits are characterized by having a developmentally and genetically controlled, highly intricate ripening process, leading to dramatic modifications in fruit size, texture, color, flavor, and aroma. Climacteric fruits such as tomato, pear, banana, and melon show a ripening-associated increase in respiration and ethylene production and these processes are well-documented. In contrast, the hormonal mechanism of fruit development and ripening in non-climacteric fruit, such as strawberry, grape, raspberry, and citrus, is not well characterized. However, recent studies have shown that non-climacteric fruit development and ripening, involves the coordinated action of different hormones, such as abscisic acid (ABA), auxin, gibberellins, ethylene, and others. In this review, we discuss and evaluate the recent research findings concerning the hormonal regulation of non-climacteric fruit development and ripening and their cross-talk by taking grape, strawberry, and raspberry as reference fruit species.
Big Data-Survey

Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.
Comorbidities in asthma and chronic obstructive pulmonary disease among adult inhabitants of Silesian Voivodeship, Poland

Przewlekła obturacyjna choroba płuc (POChP) i astma to przewlekłe choroby układu oddechowego, których częstość występowania rośnie. Wraz z wiekiem może dojść do nakładania się obydwu chorób (asthma-COPD overlap syndrome – ACOS). Brak stosownych danych w Polsce uzasadnia badanie sytuacji epidemiologicznej w tym zakresie. Celem pracy była ocena częstości występowania chorób współtowarzyszących astmie i POChP oraz oszacowanie możliwości nakładania się obydwu chorób w woj. śląskim wraz z oceną kosztów leczenia szpitalnego w ramach środków Narodowego Funduszu Zdrowia (NFZ). W badaniu przeanalizowano wtórne dane epidemiologiczne dotyczące rejestrowanych przez NFZ świadczeń medycznych w woj. śląskim w latach 2006–2010. Oceniono czasowe zróżnicowanie standaryzowanych współczynników opisujących liczbę nowych zachorowań na POChP oraz astmę wśród osób dorosłych (wiek ≥ 19 lat) oraz przeanalizowano strukturę chorób współistniejących. Liczba nowych zachorowań na astmę i POChP utrzymywała się na wysokim poziomie, odpowiednio od 392,3 (2008 r.) do 469,6 (2007 r.)/100 000 i od 470,7 (2010 r.) do 656,9 (2007 r.)/100 000 dorosłych mieszkańców. Spośród chorób współistniejących dominowały choroby układu sercowo-naczyniowego, przewlekłe i infekcyjne choroby układu oddechowego oraz choroby metaboliczne. Astma i POChP częściej współwystępowały u osób starszych, co zostało potwierdzone u 5% chorych. Średni jednostkowy koszt leczenia szpitalnego astmy i POChP wynosił odpowiednio 2533,63 PLN i 2013,15 PLN.Liczba pierwszorazowych hospitalizacji z powodu POChP jest 2-krotnie większa niż z powodu astmy. Hospitalizacja pacjentów wiąże się z koniecznością leczenia chorób współistniejących, najczęściej chorób sercowo-naczyniowych. Zespół ACOS dotyczył 5% chorych. Chociaż jednostkowy koszt leczenia pacjenta z astmą jest większy niż chorego z POChP, to mniejsza liczba hospitalizowanych przekłada się na 2-krotnie mniejszy roczny koszt leczenia choroby w stosunku do kosztu leczenia POChP.
Data hiding in audio by using image steganography technique

A Steganography method of embedding textual information in an audio file is presented in this paper. In the existing technique, first the audio file is sampled and then an appropriate bit of each alternate sample is altered to embed the textual information. As a Steganography approach the perceptual quality of the host audio signal was not to be degraded. In the proposed technique, first the secrete data is embedded into the image and that image is embedded into the audio.