Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinicopathologic Significance of G Protein-Coupled Receptor 81 in Hepatocellular Carcinoma

Background/ Aims: Lactate functions as a metabolic key player in cancer in various aspects. G-protein coupled receptor 81 (GPR81), a cell surface lactate receptor, is involved in the metabolism of lactate. However, only a few studies have been conducted on GPR81 expression in cancer, especially hepatocellular carcinoma (HCC). The present study aims to identify the clinical significance of GPR81 expression in HCC and its role as a prognostic factor. Methods: Tissues were obtained from 197 patients who had undergone surgery for HCC. GPR81 expression level was assessed by immunohistochemistry. And the function of GPR81 on HCC cell growth and mobility was explored through cell line studies. Results: GPR81 was overexpressed in the HepG2, Huh7, SNU182 and SK-Hep1 HCC cell lines and HCC tissues compared with that in the THLE-2 normal liver cell lines. Furthermore, high GPR81 expression levels were correlated significantly with disease recurrence. In addition, because of significant differences in cancer proliferation, migration, and invasion depending on the GPR81 expression level in various HCC cell line studies, GPR81 is believed to play a role in promoting aggressive cancer cell behavior. Conclusions: As such, GPR81 expression level was determined to be a useful prognostic factor for predicting HCC progression. The present study is the first to report on GPR81 expression in HCC and its significance. Henceforth, GPR81 is expected to become a highly valuable candidate for future target therapy. 1Department of Pathology 2Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea 3Department of Internal Medicine, Kyung pook National University School of Medicine, Daegu, Korea *Corresponding author Yu Na Kang, Department of Pathology, Keimyung University School of Medicine, 1095 Dalgubeoldae-ro, Dalseogu, Daegu 42601, Korea, E-mail: yunakang@dsmc.or. kr Submitted: 02 Aug 2017; Accepted: 10 Aug 2017; Published: 17 Aug 2017
FEATURE BASED BREAST CANCER DETECTION USING MAMMOGRAPHIC IMAGES

After HIV, the second leading cause of death for women all over the world is breast cancer. Cancer is the tremendous growth of cells that originates in the blood tissue. The tumor may be cancerous (malignant) or non cancerous (benign). Early detection increases the chances of survival and reduces the death rate. This paper presents a novel approach to detect the mammogram images using histogram of oriented gradients (HOG) and classified by support vector machines (SVM) which classifies the breast cancer using support vectors. The above method is generally used for textural pattern analysis and human detection. Hence to increase the classification efficiency a pre-processing technique called CLAHE (Contrast Limited Adaptive Histogram Equalization) is proposed. Graph based computation is introduced for the existing methodology and the outcome is studied. This approach reduces the computation time and increases the accuracy.
Survey on image extraction from unstructured big data (video) using HMM

: Big data is the collection of both structured and unstructured data that is so large and fast moving. Surveillance video is the highest source of unstructured big data. Foreground extraction is performed to extract images from videos only in HEVC compression format, but Videos are represented in any codec standards. The images or videos should be extracted efficiently from the unstructured big data. To perform efficient extraction Hidden Markov Model (HMM) can be used. HMM is a probabilistic model and it includes both foreground and background extractions.
Insider Threats in Wireless Sensor Networks and Their Countermeasures

-Wireless sensor networks tend to have a wide range of applications in our day to day life. In future, they can be used to survey our health, our home, the roads we follow, the office or the industry we work in or even the aircrafts we use, in an attempt to enhance our safety. But, these networks themselves are prone to security attacks. The list of security attacks is already very large and keeps on increasing with the expansion of these networks. A powerful tool for the detection of faulty or malicious nodes is the trust management schemes. Having detected the misbehaving nodes, their neighbours can use this information to avoid relying on them, either for data forwarding, data aggregation or any other cooperative function. There are a variety of trust models and most of them focus on defending against certain insider attacks. This paper discusses several security vulnerabilities that the trust mechanisms have. We also examine how inside attackers can exploit these security holes, and propose approaches that can mitigate the weaknesses of trust mechanisms.
PROVIDING EFFICIENT ROUTE DISCOVERY USING REACTIVE ROUTING IN WIRELESS SENSOR NETWORKS

Providing reliable and efficient route for communication under fading channel is one of the major challenges in WSN, especially in the industrial wireless sensor networks(IWSNs). In this work we present the Reliable Reactive Routing to increase the resilience to link dynamics for WSN/WSN. Reactive Routing protocols provide reliable and energy efficient packet delivery against the unreliable wireless by utilizing the local path diversity. In this work we are introducing based back off scheme during the route-discovery phase to find a robust guide path, which can provide more forwarding nodes. In this biased back off scheme we are using guide path, using this guide path data packets are moving towards the destination through node’s cooperation without utilizing the local information.
Content based Intelligent Image Retrieval Based on Super Pixel with Wavelet Transform

: In this paper we proposes Intelligent Content-Based Image Retrieval (ICBIR) based on super pixel with multi-resolution image. Super pixel plays an important role in image retrieval since instead single pixels a group of pixel in an image called super pixel. Super pixel has computationally efficient, representational effective and near-complete future and completely meaningful. The super pixel formed in multiresolution environment. Based on super pixel color and texture features are extracted and the formed feature vector. We constructed image database based on feature vector. Cosine distance method is incorporated to find the distance between query image and target image in image database. The proposed method is very efficient since we proposed super pixel concept which provide fast and memory efficient because of feature are extracted in multiresolution environment. The proposed method is implemented in Vistex and corel database images. The precision and recall performance method are incorporated to measure accuracy of proposed methods. The proposed method obtains better result when compared to that of the existing techniques.
Classification of Splat and GLCM Features in Fundus Images for Retinal Hemorrhage Detection

— Image mining is the process of searching and discovering valuable information, knowledge in large volume of data. It is applied in Data mining, Image processing, Artificial Intelligence. Diabetic Retinopathy (DR) is eye disorder that affect retina, at severe stage it become vision loss. Early detection of DR is helpful to improve the screening system to prevent vision loss. Retinal hemorrhage is one kind of major abnormality to find the Non-Proliferative Diabetic Retinopathy (NPDR). The objective of our proposed work is to detect retinal hemorrhage for automatic screening of DR using Support Vector Machine (SVM) classifier. To detect retinal hemorrhage, retinal fundus images are taken from Messidor dataset. After pre-processing, retinal images using pixel of same color and intensity, the image is partitioned into non-overlapping area that covers the entire image. Splat and GLCM feature are extracted to improve the classification accuracy. In order to classify the given input images, different classes must be represented using relevant and significant features with the help of selection method that is processed by filter and wrapper approaches. Then hemorrhage affected retina is detected by SVM classifier. Finally classification accuracy is compared with K-Nearest Neighbor (KNN) classifier.
A New Pulse Duty Cycle Control Method with Pulse Frequency Modulation for Light Load Applications

LEDs are likely to be used for general lighting applications due to their high efficiency and longer life. To cover wide output range on lighting application some of control methods are adopts. In the proposed method, the interleaved DCM fly back converter is favoured. DCM operation can accomplish high PF for wide output power range. To achieve high efficiency, new pulse duty cycle control method with pulse frequency modulation for an interleaved single-stage fly back ac–dc converter is proposed. The proposed converter provides high efficiency under heavy loads with low ac line condition and under light loads with high ac line condition. As a result, the recital of the proposed circuit is validated by the simulation results using MAT LAB software with PDPFM control method. Experimental results show the functionality of the on the whole system.
Students Performance Prediction through Educational Data Mining - An Uncomplicated Review

- Educational Data mining (EDM) is a new active research area. It focuses on applying data mining methods to the educational dataset to discover useful information. One of the most interesting tasks of EDM is to predict the performance of students. Many researchers all over the world have experimented and published their research work on students’ performance prediction. The main objective of this survey paper is to bring out the methodology used by the researchers and the key findings of those research work in a simple and an uncomplicated way.
Frequency analysis of Digital Integrator based on the Optimization Techniques

:- In this paper, the use of optimization techniques for the design and analysis of digital integrator is presented. Different nature inspired optimization algorithm are developed, here we are using genetic algorithm for the design of digital integrator. Genetic algorithms are stochastic search techniques inspired by the principles of natural selection and natural genetics. Filter coefficients are globally optimized using genetic algorithm. Here, we consider the magnitude response of the integrator as the performance controlling parameter. The Results reveals that the magnitude response of the design integrator closely approaches the ideal integrator response. The simulation result shows the magnitude response of propose integrator with different filter order and optimized filter coefficient. Theoretical analysis and simulation results prove that the proposed integrator outperforms the existing integrators by different authors in terms of magnitude response.
Compartment Syndrome–Presentations and Principles

The seminal paper of Richard von Volkmann in 1872 inspired and moulded the early knowledge, understanding and awareness of the global orthopaedic fraternity to the gravity compartment syndrome (CS) posed as a result of grievous orthopaedic insult [1-3]. However, despite the invent and progress of glorious investigative, diagnostic and imaging modalities through the turn of the century, CS is still regarded a shadow in the darkness given its lack of awareness. The gravity of dealing with such an elusive diagnosis culminates in high rates of litigation.
A Neural Network Based Approach for Semantic Clustering of Short Texts

: The clustering of short texts such as MSN (Microsoft Network) news titles by their meaning is a challenging task. The semantic hashing approach encodes the meaning of a text into a compact binary code. Thus, to tell if two texts have similar meanings, we only need to check if they have similar codes. The encoding is created by a deep neural network, which is trained on texts represe nted by word-count vectors (bag-of-word representation). To cluster short texts by their meanings, we propose to add more semantic signals to short texts. Specifically, for each term in a short text, we obtain its concepts and co-occurring terms from a probabilistic knowledgebase to enrich the short text. A simplified deep learning network is introduced which consist of 3-layer stacked auto-encoders for semantic hashing. Comprehensive experiments show that, with more semantic signals, this simplified deep learning model is able to capture the semantics of short texts, which enables a variety of applications including short text retriev al, classification and general purpose text processing.
Tool Wear Studies On Mild Steel Turning By Pramod Kumar et al

The present works involves the study of thermal and wear behaviour of tool and work interface. Experiments were conducted on a Turn master 35 automatic lathe. Various cutting forces, temperature at tool tip, thickness and weight of chips formed during machining along with the tool wear data were recorded. The influence of cutting parameters was studied. Based on the experimental data plots are obtained. Finite element analysis was done using ANSYS software tool and was used to find the tool tip deflection, counterplots. Thermal analysis was done to determine the temperature distribution over machining interface. Good agreement was found between the predicted and measured cutting forces.The analysis provides new insight into the chip formation and temparature distribution over tool tip and work interface in mild steel turning. As turning of mild steel rod using HSS is one among the major machining operations in manufacturing industry and tool wear results obtained would significantly contribute to the cutting parameters optimization during manufacturing of some of the parts for automobile and other structural related sectors.
Microwave Bandpass Filter Integrated with Notch Response for Wide-band Applications

This paper presents the design of wide-band bandpass filter using microstrip structure at 3-6GHz with fractional bandwidth of 66.67% based upon short-circuited stubs structure of 5th degree. In order to avoid the interference from existing system that operates in the frequency band, the folded stepped impedance resonator (SIR) was introduced to generate a narrow notch band at 5.2GHz. Pin diode is employ as switching mechanism for the notch response. This design is simulated by Advance Design System (ADS) software and using Roger Duroid 4350B with a dielectric constant of 3.48, substrate thickness 0.508mm and loss tangent 0.0019. The achieved return loss is better than 15dB and insertion loss is less than 1dB.The designed filter can be used in microwave communication systems such as wireless communication devices and military applications (radar system).
SECURING GOOGLE PLAY STORE FROM FAKE REVIEWS AND MALWARE ATTACK BY ANALYZING THE USER BEHAVIORS

— In this digital age, smart phones are become one of the important equipment for each and every people irrespective of their financial or social status. By increasing the popularity of the smart phones, the applications that runs on smart phones are also becomes popular and highly demanding. Google Play, the most popular Android app market which working with 87 K apps, 2.9 M reviews
Influence of Interstitial Hydraulics on Plume Size and Shapes in Coastal Subsurface Foreshores

— A non-invasive method called Visual Scaling Technique (VST) was applied to determine advective development of injected dye solution in estuarine beach-sand. It comprises site-survey, solute-injection, plume-recovery and data recording processes. Full 2-D plume-images of the contaminated area were captured using digital camera and details of the tail and topmost widths, plume vertical size, total travel height and subsidence depth measured. The geometric impressions of the plumes were found to vary with location detailing groundwater flow directions, hence contaminant pathways. The means of the plume development records in space was contrasted using time series, sequence and spectral plot models to find distinguishable periodic fluctuation components. It shows that groundwater and tidal water interstitial hydraulics influenced the shapes of the plumes. The time series and sequence plots show that no equal spacing and hint of seasonal variations were noticed except prominent fluctuations which identify with real time series. The spectral plots of the sizes and shapes of the plumes show upwardly varying daily growth of a time series but periodic fluctuation components could not be clearly distinguished. The spectral density appears to smoothen out the fluctuations arising from the non-periodic components of the data with the lowest frequency identified with the peak at 0.0417. The data therefore, confirm the existence of daily periodic components and that no other periodicities are identifiable. The model fits (seasonality and trend-cycle) in all cases fitted the observed data well, and it can be stated that both the seasonal adjusted series and trend-cycle models give the best exponential smoothing to the observed data.
Hybrid Operating System in Smart Phone

—Operating system (OS) is the backbone in any smart phone. With every passing year, newer and latest versions of OSs are being brought in the market. The application and design developers of mobile OS are trying to bring the best of it in every newer version. This paper provides a survey on the current OS used in smart phones and a comparison of most commonly used and newly designed OS in smart phones market. Our contribution is twofold. Firstly, we conduct a survey asking users about their smart phone preferences which yield some interesting results. Secondly, we propose the design of a hybrid OS for smart phone which combines the paramount features of the on hand OSs.
A Vision Based Lane Marking Detection, Tracking and Vehicle Detection on Highways

- Changing street conditions is an important issue in the applications in mechanized route of vehicles essentially because of vast change in appearance in lane markings on by variables such substantial movement and changing daylight conditions of the specific time of day. A path identification framework is an imperative segment of numerous computerized vehicle frameworks. In this paper, we address these issues through lane identification and vehicle recognition calculation to manage testing situations, for example, a lane end and flow, old lane markings, and path changes. Left and right lane limits will be distinguished independently to adequately handle blending and part paths utilizing a strong calculation
Survey on color lines model for eliminating specular reflection

Detection of highlights is a prominent issue in computer vision, graphics. Many algorithms in image processing assume diffuse only reflections and deem specular reflections to be outliers. However, in the real world, the presence of specular reflections is inevitable since there are many dielectric inhomogeneous objects which have both diffuse and specular reflections. Hence, detection, and sometimes removal, of specular reflection (highlights) in an image may be critical. Proposed work takes help of global color-lines information to effectively recover specular and diffuse reflection. Our critical observation is that each image pixel lies along a color line in normalized RGB space and the different color lines meaning distinct diffuse chromaticities intersect at one point, known to be the illumination chromaticity. Pixels along the same color line, spread over the entire image and their distances to the illumination chromaticity give the number of specular reflection components. With such non-local overall information from these color lines, our method can effectively separate specular and diffuse reflection components in a pixel-wise way. We also present an efficient algorithm for complete removal of the highlights and it is suitable for real-time applications.
ANGIOPOIETIN-LIKE 4 (ANGPTL4) AND CANCER

Angiopoietin-like 4 (ANGPTL4) is one of the many secreted proteins predominantly expressed adipose tissues as well as the liver, and plays a central role in both metabolic and non-metabolic processes including energy homeostasis and angiogenesis. Recently, it is demonstrated that ANGPTL4 is involved in tumorigenesis and progression of human cancers. But, the biological features, roles and mechanisms of ANGPTL4 in the tumorigenesis, development and progression of human cancers aren’t thoroughly elucidated. Therefore, identification of special biological behaviors, further understanding the roles and mechanism of ANGPTL4 in tumorigenesis and development of human cancer is of very significant. This review pays key attention to the physical, chemical and structure of ANGPTL4 and its role in different types of cancers, specially, focuses on the expression of ANGPTL4 in relation to tumorigenesis, development and progression of human cancer.
Use of Thermal Sensors for Fall Detection in a Simulated Toilet Environment

Falls are likely to occur in a toilet. However, people typically are alone when they use the toilet; thus, if a fall occurs, it may be difficult to ask for help. Therefore, we constructed a fall detection system using a thermal image sensor that cannot distinguish details, such as a face, and has high suitability for the toilet environment. In this study, we investigate the influence of the sensor position on the fall discrimination rate. Sensors were installed at four locations and normal toilet movements and falling postures were recorded using eight healthy adults. Discrimination formulas were prepared using thermal images obtained for four subjects, and discrimination rates of falling postures were calculated for the remaining four subjects, which were then compared relative to sensor positions. The highest discrimination rate (95.7%) was obtained with the sensor installed in front of the toilet at the height of the body center of the subject sitting on the toilet. The lowest discrimination rate (60.2%) was obtained with the sensor installed in front of the toilet and close to the ceiling with respect to the subject sitting on the toilet. To detect falls using thermal imaging, sensor positions should be based on various factors, such as whether the entire body can be imaged relative to the falling posture without depending only on the height and direction or whether the difference between normal activity and falling posture is clear, including the environment of the toilet and the assumed fall situation.
Improving Efficiency of IDS using alert Correlation

— Intrusion Detection Systems are designed to monitor a network environment and generate alerts whenever abnormal activities are detected. However, the number of these alerts can be very large making their evaluation a difficult task for a security analyst. Alert management techniques reduce alert volume significantly and potentially improve detection performance of an Intrusion Detection System. To Improve the effectiveness and efficiency of an Intrusion Detection System by significantly reducing the false positive alerts and increasing the ability. Proposed technique addresses the issues relating the optimality of decision-making through correlation in multiple sensors framework. The process is based on through Dempster Shafer rule. Moreover, the reliability factor for any Intrusion Detection System is also addressed accordingly in order to minimize the chance of false diagnose of the final network state. A considerable number of simulations are conducted in order to determine the optimal performance of the proposed prototype. In this paper we are introduce combines evidence from two homogenous and one heterogeneous ids using dempster-shafer algorithm I