Performance Analysis of Hoeffding Trees in Data Streams by Using Massive Online Analysis Framewor

Present work is mainly concerned with the understanding of the problem of classification from the data stream perspective on evolving streams using massive online analysis framework with regard to different Hoeffding trees. Advancement of the technology both in the area of hardware and software has led to the rapid storage of data in huge volumes. Such data is referred to as a data stream. Traditional data mining methods are not capable of handling data streams because of the ubiquitous nature of data streams. The challenging task is how to store, analyse and visualise such large volumes of data. Massive data mining is a solution for these challenges. In the present analysis five different Hoeffding trees are used on the available eight dataset generators of massive online analysis framework and the results predict that stagger generator happens to be the best performer for different classifiers

Analysis of Speech in Human Communication

The human communication has a vitalmode called speech which results from the voice along with knowledge of language. The voice of each person is distinct because individual-specific vocal cord anatomy, vocal cavity, and oral and nasal cavities. It forms a basic block for copious knowledge into various analysis like lexical analytics, natural language processing, text mining, sentiment and satire. Apart from linguistics analysis, the physics of voice contributes to uniquely cognize as a signal. The paper aims at understanding a computer program called ‘PRAAT’ to analyze and synthesize a phonetics by computer. The work carried out in the paper focuses on presenting the comparative analysis real time voice data sample and the benchmark voice data in praat for all the parameters of the voice analysis. The results are promising and make a way to build decision making solutions to patterns of voice, recognition and reproduction processes using the facts of analytics

Adaptive High Beam Control in Vehicles using Image Processing

The numbers of accidents occurring in night are increasing day by day because of the improper illumination on the bended streets and also because of the blindness caused to the driver by high intensity beam coming from the front coming vehicle.With the end goal to give improved evening time security measures, this work means to plan and assemble a headlight by adjusting a traditional static headlamp by keeping in mindthe expenses and unwavering quality. Also, to switch the headlight to dipper when there’s a vehicle approaching from front reaches within a defined range

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Extraction of image resampling using correlation aware convolution neural networks for image tampering detection

Detecting hybrid tampering attacks in an image is extremely difficult; especially when copy-clone tampered segments exhibit identical illumination and contrast level about genuine objects. The existing method fails to detect tampering when the image undergoes hybrid transformation such as scaling, rotation, compression, and also fails to detect under small-smooth tampering. The existing resampling feature extraction using the Deep learning techniques fails to obtain a good correlation among neighboring pixels in both horizontal and vertical directions. This work presents correlation aware convolution neural network (CA-CNN) for extracting resampling features for detecting hybrid tampering attacks. Here the image is resized for detecting tampering under a small-smooth region. The CA-CNN is composed of a three-layer horizontal, vertical, and correlated layer. The correlated layer is used for obtaining correlated resampling feature among horizontal sequence and vertical sequence. Then feature is aggregated and the descriptor is built. An experiment is conducted to evaluate the performance of the CA-CNN model over existing tampering detection methodologies considering the various datasets. From the result achieved it can be seen the CA-CNN is efficient considering various distortions and post-processing attacks such joint photographic expert group (JPEG) compression, and scaling. This model achieves much better accuracies, recall, precision, false positive rate (FPR), and F-measure compared existing methodologies

Regression Model for Edu-data in Technical Education System: A Linear Approach

Mining educational data is an emerging interdisciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions which is referred to as Edu-Data. Data mining is concerned with the analysis of data for finding patterns which are previously unknown and are presently useful for future analysis. The technique of mining Edu-data is referred to as Edu-mining. On the other hand statistics is a mathematical science concerned with the collection, analysis, interpretation or explanation, and presentation of data which plays a very important role in the process of data mining. The paper aims at developing a simple linear regression model for Edu-data using the statistical approach. The results obtained helps the management to predict the semester results and also helps in proper decision making processes in Technical Education System. It is also found that the predictions were almost nearing to the actual values. The present work is first of its kind in literature

Emotion Detection System Using Image Processing Techniques: A Case Study

When we investigate the last 10 years from a technological point of view, one thing becomes very apparent; technology has infiltrated all parts of human lives in every way imaginable to us, the number of devices in a person's home exceed the number of people itself, the time has come we can no longer ignore the presence of such devices since they hold immense computational power. In this project we want to bring about a very frequently discussed topic of automatically being able to detect human emotions. The project is developed as an android application. The proposed system is being developed using latest technologies such as OpenCV, Haar features, Android Studio, the project aims at face detection as well as emotion detection efficiently, quickly and in minimum amount of steps. The project can detect a wide range of emotions and the unique feature would be that it can detect the person’s level and percentage of different emotions he/she is experiencing

RNA secondary structure-based design of antisense peptide nucleic acids for modulating disease-associated aberrant tau pre-mRNA alternative splicing

Alternative splicing of tau pre-mRNA is regulated by a 5' splice site (5'ss) hairpin present at the exon 10–intron 10 junction. Single mutations within the hairpin sequence alter hairpin structural stability and/or the binding of splicing factors, resulting in disease-causing aberrant splicing of exon 10. The hairpin structure contains about seven stably formed base pairs and thus may be suitable for targeting through antisense strands. Here, we used antisense peptide nucleic acids (asPNAs) to probe and target the tau pre-mRNA exon 10 5'ss hairpin structure through strand invasion. We characterized by electrophoretic mobility shift assay the binding of the designed asPNAs to model tau splice site hairpins. The relatively short (10–15 mer) asPNAs showed nanomolar binding to wild-type hairpins as well as a disease-causing mutant hairpin C+19G, albeit with reduced binding strength. Thus, the structural stabilizing effect of C+19G mutation could be revealed by asPNA binding. In addition, our cell culture minigene splicing assay data revealed that application of an asPNA targeting the 30 arm of the hairpin resulted in an increased exon 10 inclusion level for the disease-associated mutant C+19G, probably by exposing the 5'ss as well as inhibiting the binding of protein factors to the intronic spicing silencer. On the contrary, the application of asPNAs targeting the 5' arm of the hairpin caused an increased exon 10 exclusion for a disease-associated mutant C+14U, mainly by blocking the 5'ss. PNAs could enter cells through conjugation with amino sugar neamine or by cotransfection with minigene plasmids using a commercially available transfection reagent.MOE (Min. of Education, S’pore)Published versio

Human NK cell deficiency as a result of biallelic mutations in MCM10

Human natural killer cell deficiency (NKD) arises from inborn errors of immunity that lead to impaired NK cell development, function, or both. Through the understanding of the biological perturbations in individuals with NKD, requirements for the generation of terminally mature functional innate effector cells can be elucidated. Here, we report a cause of NKD resulting from compound heterozygous mutations in minichromosomal maintenance complex member 10 (MCM10) that impaired NK cell maturation in a child with fatal susceptibility to CMV. MCM10 has not been previously associated with monogenic disease and plays a critical role in the activation and function of the eukaryotic DNA replisome. Through evaluation of patient primary fibroblasts, modeling patient mutations in fibroblast cell lines, and MCM10 knockdown in human NK cell lines, we have shown that loss of MCM10 function leads to impaired cell cycle progression and induction of DNA damage–response pathways. By modeling MCM10 deficiency in primary NK cell precursors, including patient-derived induced pluripotent stem cells, we further demonstrated that MCM10 is required for NK cell terminal maturation and acquisition of immunological system function. Together, these data define MCM10 as an NKD gene and provide biological insight into the requirement for the DNA replisome in human NK cell maturation and function