Miracle-dz/UniFAR-FTUs huggingface dataset:
Mammographic breast density and hormonal therapy during postmenopause

Mammografia stała się podstawowym narzędziem diagnostycznym i skryningowym w ocenie zmian gruczołu piersiowego. Pozwala na wykrycie niebadalnego nowotworu, ponadto jest jedyną metodą wykrywającą skupiska mikrozwapnień. Zmniejszenie śmiertelności z powodu raka sutka możliwe jest dzięki wykrywaniu choroby w postaci bardzo małych guzków i umożliwieniu tym samym podjęcia szybkiego i skutecznego leczenia. Ultrasonografia (USG) rzadko wykrywa zmiany mniejsze niż 1 cm. W tomografii komputerowej (TK) dawka promieniowania jest duża, a warstwy są zbyt grube, by wykryć wczesne ogniska raka. Wykorzystanie rezonansu magnetycznego (RM) nie przyniosło oczekiwanych efektów ze względu na duże koszty i małą dostępność badania dla pacjentek. Mammografia stała się więc najsilniejszą bronią w walce z rakiem piersi. Zmniejsza śmiertelność z powodu tego nowotworu, wykrywając bardzo małe zmiany, i pozwala na mniej radykalne leczenie. W połączeniu z badaniem fizykalnym i biopsją umożliwia uniknięcie niekoniecznych zabiegów operacyjnych. Z punktu widzenia lekarza istotne jest otrzymanie wiadomości umożliwiających podjęcie właściwych działań terapeutycznych. Gruczoł piersiowy budują tkanki: tłuszczowa, włóknista/łączna i gruczołowa. Mammografia wykorzystuje Streszczenie
ENHANCING THE ATTRIBUTES OF SOFTWARE QUALITY OF COMPONENT BASED SOFTWARE USING SOFT COMPUTING TECHNIQUES

Quality of the software is essential for maximizing the confidence level in developing software as well as in the software engineering field. Quality of software products plays an integral part in the success of any business. Characteristics of quality related to software would be gauged for testing the quality of the software. Software quality includes most essential characteristics and features of a product or activity that would be on the basis on the meeting the desired requirements. Software quality attributes plays a main role in success of any project. Thus such type of attributes has to be gauged or estimated for successful project. There are many attributes there are estimated the quality of the software in terms of characteristics such as correctness, integrity, interoperability, scalability, trackability, tailorability, reliability, maintainability, portability, efficiency, flexibility, reusability, usability and so on. The main objective of the research is to enhance the software quality attributes of component based system using soft computing techniques. This study develops a model for enhancing the attributes of software quality using artificial neural network. Software quality attributes selected for this study are reliability, reusability and maintainability. This study proposes a model to enhance the software quality attributes of CBS. It was found out that the proposed model outperforms well than the existing techniques such as neural-fuzzy, genetic algorithm and neural network.
Identification of a gene expression profile associated with progression-free survival (PFS) in relapsed or metastatic (RM) head and neck squamous cell cancer (HNSCC) patients (pts) treated with first-line cetuximab and platinum therapy.

6027 Background: First-line chemotherapy with platinum and cetuximab is usually offered to RM-HNSCC pts. In the Extreme trial a median PFS time of 5.6 months was reported. However, a small fraction of pts achieves a prolonged PFS (> than 12 months). Until now, no recognized predictive biological factor has been identified. Methods: A group of 14 pts treated with a first-line platinum and cetuximab with a PFS exceeding 12 months (long PFS) and a group of 26 pts with a PFS less than 5.6 months (short PFS) were selected. Tumor specimens of the recurrence (25 cases) or, if not available, of the primary tumor were collected. In order to identify molecular profiles deregulated between the 2 groups, a gene expression microarray analysis was performed using the Whole-Genome DASL assay and HumanHT-12_v4 BeadArray chips (lllumina). Results: The 2 groups were well balanced in regard to recognized prognostic factors (performance status, weight loss, prior radiotherapy, tumor grade, site of primary tumor, residual dis.
Moving Obstacle Avoidance in Indoor Environments

— This paper deals with a problem of autonomous mobile robot navigation among dynamic obstacles. The velocity obstacle approach (VO) is considered an easy and simple method to detect the collision situation between two circular-shaped objects using the collision cone principle. The VO approach has two challenges when applied in indoor environments. The first challenge is that in the real world, not all obstacles have circular shapes. The second challenge is that the mobile robot cannot sometimes move to its goal because all its velocities to the goal are located within collision cones. For indoor environments some unobserved moving objects may appear suddenly in the robot path; particularly when the robot crosses a corridor or passes an open door. The contributions of this paper are that a method has been proposed to extract the collision cones of non-circular objects, where the obstacle size and the collision time are considered to weigh the velocities of the robot, and the virtual obstacle principle has been proposed to avoid unobserved moving objects. The experiments were conducted within indoor environments to validate the control algorithm proposed in this paper, and results obtained showed the mobile robot successfully avoided both static and dynamic obstacles.
A Comparative Study Of Various Routing Protocol For VANETs

— Vehicular Ad hoc Network (VANET) is most active research area that provides wireless communication between vehicles moving at high speeds. These networks are self-organized in nature and a key component for future intelligent transportation system (ITS). It is a subclass of mobile ad hoc networks (MANET) but with some different characteristics like high mobility of vehicles, constrained mobility, highly dynamic topologies, frequent disconnections of networks, bandwidth limitation, no power constraints, sufficient storage and unpredictable node density. It is difficult to develop an efficient routing protocol for VANETs. In this research paper, we have discussed some existing ad hoc routing protocols AODV, DYMO and OLSR. Also, we have presented the comparative study of these routing protocols along with their advantages and disadvantages.
Single phase solar inverter

In this paper, a grid connection of single-phase PV inverter system is presented, which can deal with solar energy and performs power conditioning. To draw maximum power from the solar system we use maximum power point tracking technology for PV arrays. This MPPT technology based on the maximum power point varies with irradiation and temperature linearly. The control of a grid-connected inverter is investigated. There are two key control issues that need to be examined. The first is the control of the AC side of the converter to ensure that sinusoidal output waveforms are produced. And the output from the PV panel is controlled by the boost converter. The second key issue that needs to be examined is the current that is fed from the PV panels to the inverter. The ripple on this current must be minimized as much as possible so that the inverter can be implemented with maximum power point tracking techniques (MPPT) that will enable it to extract the maximum power that is available from the PV panels at any given time.
The Relationship Between Personality Traits and Preference for Musical Genres Among Students of Redeemer’s University, Ede.

The study examined the relationship between personality and preference for musical genres among students of Redeemer’s University, Nigeria. It was reasoned that if a correlation was found it may benefit psychologists working with young people, specifically providing a greater understanding of how their personality relates with their choice of music. The study was conducted using quantitative method, that is the use of questionnaires to collect data. The Big Five Inventory (BFI) was used to assess participants personality type and a modified version of the sample test of musical preference (STOMP) were administered to participants. The participants were selected using convenient sampling and consisted of 200 university students studying at Redeemer’s University, Ede, Osun state Nigeria. Pearson Product Moment Correlation, Independent sample t test and Multiple Regression were used to analyzed the data. The result of this study indicated that there was a significant relationship between personality trait and preference for musical genres. There was no significant difference between male and female on preference for musical genres. Age was found not to be associated with preference for musical genres. Finally, factors influencing musical genres was found to predict preference for musical genres. Implications for educators and further research are discussed. Keywords: Music, genre, personality, student.
Reemergence of Foot and Mouth Disease in Andaman and Nicobar Islands, India

Foot-and-mouth disease (FMD) is an acute highly contagious viral disease of cloven-hoofed animals which has been discovered more than 100 years ago. The causative organism is a RNA virus belongs to the Aphthovirus genus, Picornaviridae family. The disease is endemic in India and every year the economic loss due to direct and indirect cause is more than USD 4 billion annually. The Andaman & Nicobar Islands also suffered due to the outbreak of FMD in the year 2005 which was due to serotype O. However, in the present study the reemergence of FMD virus almost after a gap of 13 years has been reported from the South Andaman district of the A & N Islands. The outbreak was confirmed as serotype O and is mainly affected more than 800 cattle, goat and buffalo population. The reemergence of the FMD virus in the islands has posed a serious concern to the livestock of this island which is now being considered as almost free from many of the dreaded disease. Based on the epidemiological investigation it could be concluded that the virus might have entered through the transport of straws which is being used as packing materials for vegetable and fruits from mainland.
Different Techniques for Cataract Detection

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Cataract is an eye disease that caused by opacity of lens. This will leads to complete loss of vision. Mostly cataracts are affected to aged peoples. In this modern era, so many techniques are used for detecting cataract. In this paper, various techniques for the diagnosis of cataract are focused.
ASSOCIATION RULE MINING WITH APRIORI AND FPGROWTH USING WEKA

Association rule mining is considered as a Major technique in data mining applications. It reveals all interesting relationships, called associations, in a potentially large database. However, how interesting a rule is depends on the problem a user wants to solve. Existing approaches employ different parameters to guide the search for interesting rules. Class association rules which combine association rule mining and classification are therefore concerned with finding rules that accurately predict a single target (class) variable. The key strength of association rule mining is that all interesting rules are found. The number of associations present in even moderate sized databases can be, however, very large – usually too large to be applied directly for classification purposes. Therefore, any classification learner using association rules has to perform three major steps: Mining a set of potentially accurate rules, evaluating and pruning rules, and classifying future instances using the found rule set. In this work, we make a comparison of association rule mining algorithms. We use two most popular algorithms namely Apriori and filtered Associator using SPECT heart dataset available Tunedit Machine Learning Repository .
Posterior Lumbar Inter-body fusion with pedicle and screw fixation Guided by spinal Neuronavigation for the Treatment of Spondylolithesis. Advantage and disadvantage.

Background: To assess accuracy, time efficiency, safety, and outcome of using the neuronavigation system in posterior lumbar inter-body and pedicle screws fixation. Methods: This is a retrospective study which has been done between May 2009 and may2011. During this period, there were 20 cases with lytic or degenerative Spondylolithesis, which required posterior interbody and pedicle screws fixation. Pedicle screws were placed utilizing the image-guidance system in all 20 patients. The accuracy of screw placement was assessed by intraoperative neurophysiological monitoring, assisted fluoroscopy, postoperative computerized tomography, x rays and clinical follow up after 6 weeks 3, 6, 9 and 12 months. Conclusion: The accuracy of pedicle screws placement using neuronavigation was better than using fluoroscopy with reduction of fixation complications as implant failure, pedicle cortex violation, and neural injury. Navigated minimal invasive cases had faster recovery and shorter hospital stay because of less muscle retraction and less tissue damage. (Mahmoud Farid B. A. ; Omar Abdelhay Eldanasory. Posterior Lumbar Inter-body fusion with pedicle and screw fixation Guided by spinal Neuronavigation for the Treatment of Spondylolithesis. Advantage and
Ubiquitous Health Monitoring: Empirical Survey for the Delivery of Health Intercessions through Mobile Phone

Mobile phones are playing a prominent role for the involvement of human health from past few years. Scientists and researchers have used mobile devices as the platform for promoting physical activities and healthy diet plans, calorie counters, sending timely reminders for upcoming appointments for the patients, encouraging smokers who are willing to quit smoking, monitoring symptoms of chronic diseases and wide spectrum of other health problems. This paper provides the state of art research survey and overview of rapidly growing work in this field. We also discuss the mobile technologies and various features that make them a promising platform though which the mobile phone and health intercessions can be acquired. Finally we summarize the area for future research that could help in understanding the requirements for the development of mobile phones health intercessions.
Extraction of Web Information with Implementation of Internet Intelligent Agent System Via Supervised Learning Approach

— The Searching and Extraction of valid and useful information from previously known websites as well as previously unknown multiple heterogeneous sites in internet environment for the purpose of handling large volumes of web information without switching and searching multiple sites which totally reduces the searching time and online deals in effective way. The web information extraction and comparison can be described with help of supervised learning approach such as Bayesian Classification, Expected Maximization algorithm and IF-THEN rules of Rule induction method. The importance of Internet Intelligent Agent system is help the users to conclude and analyze the web information that afforded by the same type of websites in internet and shorten the time of secured online deals.
Colonoscopy use by Primary Care Physicians and Colorectal Cancer Incidence and Mortality

We first studied factors associated with the rate of colonoscopy by primary care physicians (PCPs) in Ontario between the years 1996 and 2005. Next, we conducted an Instrumental Variable Analysis (IVA) to estimate the effect of colonoscopy on colorectal cancer (CRC) incidence and mortality on average-risk subjects aged 50-74 years. Finally, we explored two study cohorts, one by including subjects who had the outcomes during the exposure period (unselected cohort) and the other cohort by excluding those subjects (restricted cohort). We estimated the absolute risk reduction associated with colonoscopy in preventing CRC incidence and mortality using traditional regression analysis, propensity score analysis and IVA. PCPs who were Canadian medical graduates and with more years of experience were more likely to use colonoscopy. PCPs were more likely to use colonoscopy if their patient populations were predominantly women, older, had more illnesses, and if their patients resided in less marginalized neighborhoods (lower unemployment, fewer immigrants, higher income, higher education, and higher English/French fluency). Using PCP rate of discretionary colonoscopy as an instrumental variable, receipt of colonoscopy was associated with a 0.60% absolute reduction in 7-year CRC incidence and a 0.17% absolute reduction in 5-year risk of death due to CRC. The
A Comprehensive Study of Major Techniques of Facial Expression Recognition

— Facial Expression Recognition is one of the challenging and active research topic in the recent years. Facial Expression Recognition System comprises the detection of face, facial feature extraction and classification of facial expression from still images. This paper summarizes the major techniques to recognize the facial expressions from still images. The techniques included in this paper are Principal Component Analysis, Singular Value Decomposition, Neural Network, Cloud Model, Fuzzy Model and K-Means Clustering Algorithm. The performance of these techniques is good enough and almost effective also except fuzzy model. Fuzzy model does not classify the expressions exactly. The main purpose of this research work is to present the major techniques of automatic facial expression recognition in a single view.
A literature survey on missing value imputation methods in data mining

: Preprocessing is one decisive stage in data mining. The most important step in pre-processing is handling missing data. Managing missing data has different strategies such as deletion of incomplete data and imputation (filling) of missing values through depends on statistical and machine learning (ML) procedures. Most of the data mining algorithm cannot work with an incomplete dataset. In such a case, missing values create a problem with real data in the world. Missing value Imputation is a challengeable task in many sectors. Some of them perform their handling imputations in different ways. Missing value imputation determines the quality of datasets. A high accuracy data analysis is essential because it deals with real-world decision making. It performs different kinds of data mining operations. This survey analyses the various missing value imputation methods and its performances. It consists of imputation methods like single and multiple imputations. The imputation algorithms like mean, K-nearest neighbor, Naive Bayes classification, MIAEC are discussed in this survey.
A Morphological based Technique for Features Extraction from the Face Color Images

— Feature extraction is the process of indicating the relevant properties of patterns that determine certain characteristics of objects. Facial features extraction is related to representation of face features including shape, color and texture which are the main face components to recognize the facial expressions. The Geometric features type which includes the extraction of feature points is a simple in terms of computational cost for the analysis and classification of facial images than the Appearance type if a limited number of feature points are selected and extracted in the recognition process. On the other hand, the algorithms of feature extraction based on the Geometric methods are not as robust as Appearance type. As a result in this research a Geometric technique has been proposed to analyze the accuracy of facial features extraction from static images.
GAIA Service Catalogs: A Framework for the Construction of IT Service Catalogs

— The high amount of IT services offered to organizations for boosting and maintaining their business goals makes it difficult to determine the quantity, description and the attributes of these services. This paper presents a framework to support the construction of IT Service Catalogs. The framework consists of a diagnostic assessment questionnaire, a maturity model and a set of services that guide the organization in the construction of an IT Service Catalog.
Automatic Diabetic Assessment for Diabetic Retinopathy Using Support Vector Machines

Diabetic retinopathy become the common disease in most of the countries. Many classifiers are used to classify the extracted features to identify the presence of normal and abnormal retinal images. Microanuerysms, Hemorrhages and exudates are the major symptoms for detecting the proliferative and non-proliferative diabetic retinopathy. In this proposed work, an automated assessment system has been developed for the diabetic retinopathy using the classifier support vector machine which gives the higher accuracy in detecting the micro aneurysms (MAs), hemorrhages (HA) and exudates. In this work, the combination of Support Vector Machine with the Bayesian, probabilistic neural network, clustering, Artificial neural network has been discussed which improves the overall accuracy of the classification.
A MODEL FOR TALENT IDENTIFICATION IN CRICKET BASED ON OWA OPERATOR

Talent identification in sports is a challenging and significant task which is considered highly subjective. However, several attempts have been made in the past to reduce the subjectivity in this task. In this paper we have reviewed several talent models which have been proposed in the past. We have also presented a brief summary of each of these models focusing on their modus-operandi. The paper also identifies essential parameters for talent assessment in cricket. A model based on Ordered Weighted Averaging Aggregation (OWA) operator has also been proposed. The paper also presents an example demonstrating the application of the proposed algorithm on sample data.
A Review on production and purification of Polysialic acid (PSA):

Polysialic acid is new potential biopolymer which is used to control the drug delivery in biomedical applications. Polysialic acid (PSA) is a capsular polysaccharide, which is isolated from some bacterial cells by aerobic fermentation. This review article presents an overview of cultivation parameters and state of art advances in PSA production. Bioreactors such as batch and fed batch used for PSA production are presented. Yield of PSA from cells and substrate in batch and fed batch mode are studied and compared. Studies on the effect of parameters such as nutrients requirement and pH for improving PSA production are getting attention. Downstream steps required for PSA purification are also briefly discussed.
Wnt/β-Catenin Pathway on Cocaine-Induced Neuroadaptations: A Novel Target for Therapeutic Opportunities?

Received: December 08, 2016; Accepted: December 26, 2016; Published: December 30, 2016 Drug addiction is a chronic and enduring phenomenon that has been extensively investigated in the last decades. Over the years, different animal models have been designed to contribute to the elucidation of the neurobiological processes involved in relapse behavior and to evaluate potential pharmacotherapies that may prevent or reduce the risk of relapse [1]. Animal models such as behavioral sensitization, conditioned place preference and intravenous selfadministration have been extensively used. The primary difference in these models is the way in which the drug is administered; while the importance of the impact of non-contingent vs contingent drug administration for the molecular basis of addiction is a subject of continuous debate. However, recently it has been described that animal models of addiction (behavioral sensitization vs selfadministration) remarkably overlap in terms of neurocircuitry as well as in the molecular changes underlying their respective behavioral responses [2].