Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitigating Relation Completion Problem in Database Application

: Document retrieval and information retrieval is task of retrieving relevant documents according to user query. Given relation X, relation completion occurs at linking entity pairs between two entity set under the relation X. In Pattern based searc h, it may produce results that are unspecific or ambiguous when taken out of context i.e. it gives more results relevant as well as partially relevant. That means it produces a relation completion problem when extracting any relation. This implementation solves a major problem in context aware relation extraction method using text based information recovery, using the limited set of query terms given by user and extracting small set of relevant documents in a large document set. We propose search queries formulation for each query entity based on some information so that to detect target entity from the set of retrieved documents. Proposed met hod utilizes contextual information formed by word relationships contained in the document collection. And auxiliary information is given by context terms evaluated through the expression of a relation. If the retrieved document is less than top K documents KNN algorithm is applied on tree structure, to retrieve top K relevant documents. Document relevance is determined by comparing the similarity of search and document tree structure, the disclosed system attains greater search precision by retrieving relevant documents based on context and facilitating easier way search specification.
COMPARSION OF VARIOUS DETECTION TECHNIQUES OF MULTI INPUT MULTI OUTPUT INTERLEAVE DIVISION MULTIPLE ACCESS SYSTEMS

: Different interleavers are employed in Interleave Division Multiple Access (IDMA) instead of using different signatures as in a conventional code-division multiple-access (CDMA) scheme. Multiple Input Multiple Output (MIMO) system exploits multiple antennas at transmitter and receiver to mitigate the fading effect. To offer the promising communication beyond 3G and 4G wireless communication, IDMA systems combined with multiple antennas. Traditional MIMO system provides benefit of spatial diversity. In addition, the usage of multiple transmitter and receiver antennas can significantly improve the wireless communication performance. In this paper, comprehensive review of the MIMO-IDMA system is performed based on various multi user detection techniques is presented.
MULTI-KEYWORD RANKED SEARCH MODEL FOR ENCRYPTED CLOUD DATA

Now a days the popularity of cloud computing is increasing rapidly, So more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. To outsource the sensitive data it should be encrypted for privacy requirements ,which obsoletes data utilization like keyword-based document retrieval. In this paper, to support dynamic update operations like deletion and insertion of documents, we present a "Multi-keyword ranked search model for encrypted cloud data". Ranked search can enable quick search search for the most relevant data , sending back only the top-k most relevant documents can effectively decrease network traffic. Specially the widely used TF-IDF model are combined in index construction and query generation. Due the use of special tree-based index structure "Greedy Depth First search", the proposed scheme can achieve sub-linear search time and deal with deletion and insertion of documents flexibly. The secure KNN algorithm is utilized to encrypt the index and query vectors.
Sucrose-Free Milk Chocolate Sweetened with Different Bulking Agents: Effects on Physicochemical and Sensory Properties

In the present study, the effects of substituting sucrose with maltitol and xylitol as bulking agents in compound milk chocolate were examined in relation to their physico-chemical, rheological and sensory characteristics. Standard reference chocolate was made using sucrose. The Casson mathematical model was the best fitting model for predicting rheological properties. Compared with chocolate sweetened with sucrose, significant differences in Casson viscosity, yield value and hardness were observed for sucrosefree chocolates. Generally, there was no major difference between chocolate formulations containing high concentration of maltitol and conventional chocolate concerning the following parameters: moisture content, mean particle size and sensory properties. However, sucrose replacement with the high ratios of xylitol had higher moisture content, greater Casson viscosity and an increased flow behaviour index. These findings illustrate that it is possible to manufacture chocolate using high concentration of maltitol without affecting its important physico-chemical characteristics and sensory attributes.
Separation of Low Frequency Part and High Frequency Part using Image Decomposition

: One of the crucial factors in a diverse application is the better image quality. The quality of the image and the execution of the vision system deteriorate due to weather conditions like snow, mist, haze, rain and snow. Rain is one of the major contributors for the dynamic bad weather. Reduction in the quality of image is due to intensity variation causes difficulty to view. The intensity variation depends on different parameters. To maintain the quality of image, it is required that image should be without noise. Most of the rain streak removal has been done on video based approaches and with collection of training images. Rain streak removal widely used in various applications so it is necessary to develop algorithm to remove rain streaks from the images with preserving the original details. In this method, the detection and removal of rain streaks in an image is based on image decomposition which depends on Morphological Component Analysis (MCA) by performing dictionary learning.
Novel Algorithm for High Utility Itemset Mining: A Review

: High utility mining means mining or finding the high utility itemsets like the itemsets having high profit from the database. Efficiently mining high utility itemsets has very much importance in various applications. Many algorithms are developed for mining high utility itemsets, but these algorithms generate large number of candidate high utility itemsets. In this paper we are implementing an algorithm named Pattern-Mining Using Utility-Tree for high utility itemsets with an efficient tree data structure and a pruning strategy. Our algorithm generates less candidate itemsets as compared to existing high utility mining algorithms.
An IOT Design to Predict Mechanical Failure in Vehicles and Effective Replacement

560 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number:F10990476S519/19©BEIESP Abstract:As there is an increasing need for monitoring the mechanical failures in the vehicle to ensure the high safety of the customers by avoiding possible accidents, researches have been going on using IoT. However, many failures occur on vehicles due to lots of reasons, here proposed an IoT based framework to address the way to quick and effective recovery from most of the common critical failures. In this work a set of sensors and microcontrollers (MC) are used to continuously monitor the critical factors of the vehicles, the data gathered by the sensors are mined to predict the possible future failure prediction. This research shows a positive outcome to predict the possibility of failures with higher accuracy.
Review on human stress monitoring system using wearable sensors

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Chronic stress is regularly found among particular in modern society. However, as it is not able to for physicians to continuously monitor stress levels, its diagnosis is significant. Wireless body sensor networks provide opportunities to everywhere detect and monitor mental stress levels, with improved diagnosis, and provide early treatment. We discuss tradeoffs in system design and sensor selection with related to stress balance information content and wearability. The development of a wearable sensor system to monitor a number of physiological relation of mental stress. Using output signals collected from the wearable sensor, a some selected number of physiological features that show good relation with determine mental stress. However, stress in modern life tends to be spreading widely throughout an area, as it arises mainly from psychological rather than physical effects. As physiological responses to stress are repeated over and over, the result can have more long-term effects on our health. This paper reviews the latest reported systems on stress monitoring of humans based on wearable sensors and issues to be noticed to tackle the challenges.
Implementation Of Railway Crack Detection And Monitoring System

In this paper problem about a railway analysis is detection of cracks in the structure. Indian railway is the fourth world largest railway network in the world and manual Inspection and detection of cracks on these railways tracks is very tedious process and consumes a lot of time and human resource. A large proportion of derailments and service disruptions are cause by track-related issues. Increases in axle loads, vehicles primary yaw suspension stiffness, wheel-rail iconicity and capacity have resulted in greater damage to the track. This work aims in designing railway track crack detection autonomous vehicle using Microcontroller, ultrasonic Sensors which detects the cracks along its path. Ultrasonic sensor detects the crack and objects and sends this information to the microcontroller and stop the train immediately. Index Terms – Crack, Detection, Ultrasonic Sensors, Microcontroller, Proteus Software ——————————  ——————————
Design styles of Asymmetric nMOS and their Simulation

— Scaling down of the MOSFET has been done extensively to meet the need for high speed devices. Symmetric MOSFET with LDD structure could not mitigate the short channel effects, as the device was scaled down to deep sub-micrometer regime. Asymmetric MOSFET design styles were thus adopted to achieve increased device speed. In this paper, two asymmetric MOSFETs are designed and simulated using device simulator (SILVACO) - one with LDD at drain side only and second with unequal junction depths.
Enhancing lifetime of WSN through RA-LEACH (Revised ACO based LEACH algorithm)

— The nodes in a Wireless Sensor Network (WSN) are generally grouped in clusters to improve the longevity and efficiency of the network. Since the nodes have limited power capabilities and finite computation power, it becomes imperative to design algorithms to conserve the limited resources of the WSN in order to enhance the up time of the network. In this paper, a revised version of Ant Colony Optimization based LEACH protocol (RA-LEACH) is compared with LEACH protocol [1], with focus on the energy consumption by the nodes. The proposed RA-LEACH protocol while electing Cluster Heads (CHs) takes into consideration the following parameters – the ratio of the residual energy at each node with its original energy and the ratio of the distance of the node from the Base Station (BS) with the distance of the farthest node. From the simulation results, it is evident that change in the threshold calculations, improves the original design of LEACH algorithm in terms of minimizing energy consumption and improving the network lifetime.
Vancomycin-Resistant Enterococci Colonization among Hospitalized Patients and Associated Risk Factors in Trinidad and Tobago

High-density Vancomycin-resistant Enterococci (VRE) colonization of the patient gastrointestinal tract (GIT) facilitates the transmission of multi drug resistant enterococci in hospital wards through fecal contamination. We performed a survey on hospitalized patients to determine VRE fecal colonization including the risk factors for such using univariate and multivariate analysis. We analyzed 2,066 rectal swabs from three regional tertiary hospitals in the country. Standard laboratory and molecular techniques including loop mediated amplification method (LAMP), Polymerase Chain Reaction (PCR) and pulse field gel electrophoresis (PFGE) were used to detect VRE, virulent genes (esp and hyl) and the clonal relatedness of VRE isolates. VRE fecal colonization was documented in 6.2% (129/2,066) screened patients. The VRE colonization isolates were mainly E. faecium and E. faecalis and were all (100%) resistant to ciprofloxacin, erythromycin, levofloxacin, rifampin and vancomycin but 100% susceptible to daptomycin, teicoplanin and linezolid respectively. Prior hospitalization and antibiotic use, diabetes mellitus disease, previous exposure to vancomycin, cephalosporins and quinolones use by univariate analysis were significantly associated with colonization. All vancomycin resistant E. faecium were vanA genotype while the E. faecalis were vanB genotype; and all possessed the enterococci surface protein (esp) gene. Molecular finger printing identified one clone of E. faecalis and five distinct clones for E. faecium. VRE colonization in hospitalized patients, if compared with rates from some other countries is relatively low in Trinidad and Tobago. Molecular analyses suggest existence of inter and intra hospital clonal spread of E. faecium with predominant vanA gene and a single clonal spread of vanB E. faecalis strains which carry a high rate of esp genes.
The frequency of high signal intensity on T2-weighted MRI at the iliacus muscle enthesis of the iliac fossa: evidence of enthesopathy?

Poster: "ECR 2013 / C-1438 / The frequency of high signal intensity on T2-weighted MRI at the iliacus muscle enthesis of the iliac fossa: evidence of enthesopathy? " by: "J. R. Ledsam1, K. Fukuda2, T. Yonenaga2; 1Leeds/UK, 2Tokyo/JP"
Analysis of Frequent pattern using Association rule mining and providing privacy - A review paper

The most widely used analysis methods in data mining is frequent itemset and association rule mining used is several applications. Privacy is given to vertically partitioned data when the data client want to learn about the frequent itemsets and association rule mining. if any sensitive data is leaked from third party then the owners not ready to send their data to sites.by using the secure outsourced database data can have more privacy and security.Mainly the secured data privacy is given using homomorphic encryption and by using secured association mining cloud aided itemset solution can be useful. Abstract—the most widely used analysis methods in data mining is frequent itemset and association rule mining used is several applications. Privacy is given to vertically partitioned data when the data client want to learn about the frequent itemsets and association rule mining. if any sensitive data is leaked from third party then the owners not ready to send their data to sites.by using the secure outsourced database data can have more privacy and security.Mainly the secured data privacy is given using homomorphic encryption and by using secured association mining cloud aided itemset solution can be useful.
Neural Network Based Expression Recognition Using Active Facial Patches

: Facial expression, being a fundamental mode of communicating human emotions, finds its applications in human-computer interaction (HCI), health-care, surveillance, driver safety, deceit detection etc. For effective facial expression recognition, the extraction of discriminative features from facial patches is necessary. So, here a technique based on the appearance features of selected facial patches is used for expression recognition. A few prominent facial patches, depending on the position of facial landmarks, are extracted which are active during emotion elicitation and the features from these active patches are given to artificial neural network (ANN) to discriminate different expressions. The method is found to perform well consistently on JAFFE database using MATLAB software.
A Future For Beef

Here, the quality of the meat is described in terms of the naturalness of the environment and feed used in its production. That link, still dominant in the mind of today's consumer, is given scant regard in an industry driven by the economics of competition. Technology has delivered beef, pork and lamb at affordable prices in developed countries but at a high price in loss of perceived wholesomeness.
AN ONTOLOGY-BASED TEXT MINING METHOD TO CONSTRUCT D-MATRIX FOR FAULT DETECTION AND DIAGNOSIS USING GRAPH COMPARISON ALGORITHM

: Fault dependency (D)-matrix is a systematic analytic model to catch the different system-level fault diagnostic information consisting of conditions between recognizable symptoms and failure modes connected with a system. Constructing a D-matrix from earlier principles and redesigning it utilizing the space learning is a difficult task and time intensive assignment. Further, in-time augmentation of D-matrix through the revelation of new symptoms and failure modes watched for the first run through is a testing assignment. An ontology based D-matrix[1] depict an ontology based text mining strategy for consequently constructing and redesigning a D-matrix by mining countless repair verbatim (normally written in unstructured text) gathered during the diagnosis scenes. The system constructs the fault diagnosis ontology consisting of concepts and relationships commonly saw in the fault diagnosis space. Next, utilize the content mining calculations that make utilization of this ontology to distinguish the fundamental ancient rarities, for example, parts, symptoms, failure modes, and their conditions from the unstructured repair verbatim content. In our methodology, we first construct the D-Matrices from [1] for different datasets. Next, we generate graph model for each generated d-matrix and used only common patterns from generated graph and develop new graph. And, after this procedure, we create D-matrix depending upon data given by the similarity graph.
A STUDY OF PRIVACY-PRESERVING WHILE SHARING SENSITIVE INFORMATION

— Modern society is increasingly dependent on (and fearful of) massive amounts and availability of electronic information. There are numerous everyday scenarios where sensitive data must be sometimes reluctantly or suspiciously shared between entities without mutual trust. This prompts the need for mechanisms to enable limited (privacy-preserving) information sharing. A typical scenario involves two parties: one seeks information from the other that is either motivated, or compelled to share only the requested information. This paper highlights two main technical challenges:
Floppy Baby Syndrome: A Comprehensive Review of the Chromosomal Abnormalities and Gene Mutations

One of the most difficult tasks the general pediatric neurologist is asked to undertake is the evaluation of the hypotonic child [1]. Sometimes compared to a rag doll, a ‘floppy infant’ is a term used to define an infant that presents with poor muscle tone, affecting the limbs, trunk and the cranial-facial musculature [2]. Floppy infants are typically seen as exhibiting poor control of movement, delayed motor skills and hypotonic motor movement patterns [3]. There is a vast majority of factors that lead to the development of hypotonia in an infant some being genetic in nature while others are metabolic, or due to acute or chronic illnesses Due to the substantially large list of causes that can cause hypotonia in an infant, the diagnosis of hypotonia in the first year of life is a common diagnostic and management challenge for pediatricians and neonatologists [4]. The consequences of floppy infant syndrome range from hip dislocations, arthrogryposis, flexion deformity of all limbs, to respiratory and feeding difficulties [5]. In the process of evaluating floppy infant syndrome and attempting to narrow down to the primary cause of floppy infant syndrome (FIS), it is imperative to, firstly, determine whether the cause of FIS is peripheral or central. Overall, central hypotonia is more common than peripheral hypotonia amongst FIS infants [4]. Based on research, central hypotonia accounts for 60% to 80% of cases of hypotonia, whereas peripheral hypotonia is the cause in about 15 30% of cases [6]. Abstract
Scientific Opinion on Dietary Reference Values for pantothenic acid

Following a request from the European Commission, the Panel on Dietetic Products, Nutrition and Allergies (NDA) derived Dietary Reference Values (DRVs) for pantothenic acid. Pantothenic acid is a water-soluble vitamin, which is a component of coenzyme A (CoA) and acyl-carrier proteins. Pantothenic acid is ubiquitous and deficiency is rare. There are no suitable biomarkers that can be used to derive the requirement for pantothenic acid. Data available on pantothenic acid intakes and health consequences are very limited and cannot be used to derive DRVs for pantothenic acid. As there is insufficient evidence available to derive an Average Requirement and a Population Reference Intake, an Adequate Intake (AI) is proposed. The setting of AIs is based on observed pantothenic acid intakes with a mixed diet and the apparent absence of signs of deficiency in the EU, suggesting that current intake levels are adequate. The AI for adults is set at 5 mg/day. The AI for adults also applies to pregnant women. For lactating women, an AI of 7 mg/day is proposed, to compensate for pantothenic acid losses through breast milk. For infants over six months, an AI of 3 mg/day is proposed by extrapolating from the pantothenic acid intake of exclusively breast-fed infants aged zero to six months, using allometric scaling and reference body weight for each age group, in order to account for the role of pantothenic acid in energy metabolism. The AI for children and adolescents is set at 4 and 5 mg/day, respectively, based on observed intakes in the EU. © European Food Safety Authority, 2014
Word Sense Disambiguation by Domain Specification using Babelnet

Over the decades many approaches have been carried out in order to resolve the problem of Word sense disambiguation (WSD). WSD is a process of identifying correct sense of polysemy word. The current research trends in Babelnet, which is huge knowledge base which integrates Wikipedia and WordNet along with WordNet domain. In this paper, we propose an algorithm which automatically identifies the domain of each word. Senses of a word have been annotated with Babelnet which follows state-of-art approach. Further the algorithm has been proposed for converting SemCor into gold standard corpus. The analysis has been done on this gold corpus and results shows that average precision obtained is 0.5 and recall obtained is 0.4.
Liveness Detection Using Eye Blink A case Study

The eye blinking is a natural protection system which defends the eye from environmental exposure. The spontaneous eye blink is considered to be a suitable indicator for fatigue diagnostics during many, different tasks of human being activity. Here we consider eye blink as an evidence of liveness to exclude using some fakes, mainly 2D photographs, to spoof [1] face recognition systems. Different techniques have been developed in this field. Some of the techniques are: Eye blink detection from video with dynamic ROI fixation[10], Gray scale [15] intensity based algorithm, cascaded Ad-boost and HMM. The results demonstrate that the measurement of an eye blink parameter provides reliable information for detection of liveness of a person [11]. Here we present a case study on the existing techniques of eye blink based liveness detection.