Miracle-dz/UniFAR-FTUs huggingface dataset:
A Phase I Study of Humanized Anti-CD40 Immunotherapy with SGN-40 in Non-Hodgkin’s Lymphoma.

The vast majority of B-cell malignancies express CD40, a member of the TNF receptor family. This receptor, along with the cognate ligand (CD154), mediates cell survival and proliferation of normal B-cells and can regulate apoptosis as well as survival in transformed cells, making this pathway an appealing target for B-cell lymphoma. Both in vitro and in vivo preclinical studies support the development of anti-CD40 immunotherapy for non-Hodgkin’s lymphoma (NHL). Accordingly, a phase I single-arm dose escalation trial was initiated to test the safety, pharmacokinetics, and antitumor activity of SGN-40, a humanized anti-CD40 antibody, in patients with NHL. The protocol was designed to treat patients with follicular, mantle cell, diffuse large B-cell, small lymphocytic, and marginal zone lymphomas in cohorts using SGN-40 infusions at doses of 2, 4, 8, or 16 mg/kg/week for four weeks. We report results for cohort 1 (n = 6) treated at 2 mg/kg/week. Four of 6 patients completed the planned 4 weekly infusions. No grade 4 toxicity was observed. Two grade 3 toxicities were seen, both in the same patient (unilateral conjunctivitis and ipsilateral loss of vision in a patient with pre-existing macular degeneration). Grade 2 loss of balance was also seen in the same patient. Imaging studies with CT and MRI did not reveal a stroke or leptomeningeal disease nor were there inflammatory or malignant cells in the CSF. All these adverse events resolved over six weeks, including vision which returned to baseline acuity. The only other severe adverse event reported was a deep venous thrombosis in the setting of bulky ipsilateral pelvic adenopathy, which was considered to be unrelated to SGN-40. Dose escalation was temporarily suspended to evaluate these unexplained toxicities and the report of severe headaches, attributed to cytokine release reaction, at the next dose level (i.e. 4 mg/kg) in a parallel phase I protocol for multiple myeloma. Although none of the NHL patients in this study developed headaches or clinical symptoms, several patients demonstrated a significant increase in plasma cytokine levels (i.e. TNF-alpha, IL-6) following the first infusion but not subsequent treatments with SGN-40, raising the possibility that a first-dose cytokine release effect may be involved in the grade 3 toxicities observed. Pharmacokinetic samples for the NHL patients were collected and are currently being analyzed. Preliminary antitumor activity at the 2 mg/kg dose is reflected in one patient who had stable disease as determined by serial CT scans and in another patient who had subjective improvement in B symptoms during therapy but was found to have disease progression based on CT scans 4 weeks after completing therapy. An amended protocol is actively accruing patients that will address the concern for first-dose cytokine release and allow continued dose escalation. Clinical and pharmacokinetic data from these additional cohorts will be presented.
Comparative Analysis Between BPSK and QPSK Modulation Technique Based on BER Analysis using V-BLAST Based MMSE Technique

: The rich-scattering wireless channel is capable of huge theoretical capacities. The multiple input multiple output (MIMO) antenna system provides very promising gain in capacity without increasing the use of frequency spectrum, throughput, and power consumption in wireless communication. This also shows less sensitivity to fading, hence it leads to a breakthrough in the data rate of wireless communication systems. There are many schemes that can be used to MIMO systems such as space-time block code, space-time trellis code, and the Vertical Bell Labs Space-Time Architecture (V-BLAST). The V-BLAST is an ordered successive cancellation method applied to receiver and at every stage the stream with the highest SNR is decoded. In this proposes paper the analysis and performance of general MIMO system V-BLAST architecture with MMSE technique is used for linear detectors in fading channels with different antenna selections and digital modulation methods. In this proposed paper a comparative analysis between bpsk and qpsk modulation technique is given.
Power Quality Improvement of DFIG using FLC Based Variable Wind Turbines by IPC Method

43 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. Abstract: Because of the wind speed variation, breeze shear along with tower shadow effects, grid connected wind generators are the options for power fluctuations which could produce sparkle during constant operation. This paper presents a type of an MW-level varying speed windmill with a new doubly feasted induction generator to analyze the Flicker emission along with mitigation difficulties. Fuzzy logic controller (FLC) was designed to obtain maximum power extraction at low wind speeds to limit power extraction at 1.5MW nominal power set point. The Fuzzy logic based IPC (Individual Pitch Control) scheme is proposed along with the individual message controller is made using generator active power along the wind turbine. A 1.5MW horizontal axis breeze turbine model was designed for tuning as well as simulation performance is studied and the results show the damping of this generator active power by IPC is an efficient means for flicker minimization of varying speed wind generators during constant operation.
Analysis of Five Phase Inverter with different SVPWM Switching Techniques for Induction Motor Drive

238 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: G5148058719/19©BEIESP  Abstract: Multi-phase Induction motor drives (MPIMD) with numerous advantages dominates three-phase drives and emerges as a potential contender and viable solution for the high power electric drive applications. When multi-phase AC drives fed from voltage source inverters (VSIs) requires a suitable PWM method of control. This paper investigates the performance of 5-φ induction motor drive with various space vector PWM (SVPWM) techniques. First, a 5-φ VSI model is presented in terms of space vectors. Next, modified SVPWM switching techniques are introduced based on medium, large and the combination of medium and large vectors, which provide its working with reduced %THD in the output voltages. The proposed scheme uses the full DC bus voltage, and the output response superior with low lower order harmonics than the conventional SVPWM methods. The performances of the 5-φ VSI fed IM drive tested with various switching techniques, and the results observed in terms of harmonic contents present in the output voltage waveform. MATLAB/Simulink software results included in this paper to show and verify the theoretical concepts.
Computer Aided Design for Cocoa Beans Processing Yield Prediction

Ability of Cocoa Beans Processing Industries to predict the yield of Cocoa Beans before processing will be a great advantage. This knowledge will aid: proper planning as per resources allocation, predicting profit margin and decision making on acceptability of contract (by considering cost of production and profit margin). The approach taken in this research was to identify the parameters needed for processing Cocoa Beans yield such as: actual mass of Cocoa Beans to process; mass of foreign material; mass of shell removed; quantity of Cocoa nibs to be processed; mass of butter and mass of Cake from Cocoa Liquor obtained from ground nibs; consideration was also given to material wastes at each processing stage. These identified parameters were used to develop mathematical models, from which computer algorithm and software were also developed. The developed software was tested and validated for performance evaluation using Visual Basic programming language because of its friendliness and versatility. The software, when used in OLAM Cocoa Processing Industry in Akure, Ondo State, Nigeria, 21.5 tonnnes mass of Cocoa Beans was processed. The model predicted yield for Butter to be 6873.359 kg and that of Cake to be 8569.649 kg. In actual sense from the factory floor when the same mass of Cocoa Beans (21.5 tonnes) was processed a yield of 7005.25 kg and 9130.261 kg of Butter and Cake were realized respectively. This result proved this model to be 95.71 % efficient. Hence, this can now serve as a useful tool for both prospecting and existing Cocoa Processing Industries in their visibility study and production planning respectively.
Opportunistic Routing Protocols In Human Working Day Model Delay Tolerant Networks

: Delay-tolerant Networks are used to enable communication in sparse mobile ad-hoc networks and other weak as well as challenged environments where traditional networking fails and new routing and application protocols are required. Experiences with DTN routing and application protocols has shown that their performance is extremely dependent on the mobility and node characteristics. Opportunistic routing protocol drives to improve wireless performance by making a good use of communication opportunities arising by chance. DTN protocols evaluation across many scenarios requires suitable simulation tools. This project presents the opportunistic networking routing simulator specifically designed for evaluating DTN routing and application protocols. Also provides users to create scenarios based on different synthetic movement as well as real-world traces. It offers a framework for implementing routing and application protocols with six well-known routing protocols
Reliable Stereo Matching With Depth Measurement in Video Frames Using FPGA

– The emerging market of digital 3-D film productions in HD resolution leads to the need for high-quality equipment in the production chain. First, the images are treated in order to improve their pixel to pixel correspondence and reduce illumination differences. After that, stereo matching is addressed using different methods with emphasis on local ones like the sum of absolute distances and normalized cross correlation. A low-complexity depth-reliability-based stereo matching algorithm and an efficient scanline memory-merging implementation scheme are proposed. A bidirectional depth propagation flow is then adopted to fill the unreliable segments by using reliable information. Moreover, a set of predefined function-specific reliability variables are extracted to further improve depth quality in the occluded and smooth regions, which can reduce 39% bad pixels obtained by applying the basic 7 × 7 window-based matching. The proposed scanline memory-merging scheme along with data prefetching can lead to 32.7% savings on the scanline memory area and relax the requirements of external frame buffer size and bandwidth.
ROTATION INVARIANT FACE RECOGNITION USING RLBP, LPQ AND CONTOURLET TRANSFORM

: Rotation invariant face recognition is an important area of research because of its many real-world applications, especially in creating a more robust recognition system for commercial and government technologies. Their diffusion is mainly supported by governments, forensics and law enforcement agencies with the aim of improving the public security or in general a sense of security; in fact, the biometric identification does not directly improve the security but acts as deterrent to illegal activities. In this work, we also consider illumination variable database. In this first we located face as region of interest. Only LBP and LPQ features have been used for feature extraction. There are variants of LBP features i.e. RLBP (Rotated local binary pattern) etc. which has been proved better. The existed work has been implemented on only those datasets which have face in them. After this LDA has been used to reduce feature set by taking negative log-likelihood from each Contour let-WLD, RLBP and LPQ descripted image histograms. After this KNN has been used for classification purposes. The experimental results show excellent accuracy rates in overall testing of input data.
AN EFFICIENT MODELLING AGRICULTURAL PRODUCTION USING ARTIFICIAL NEURAL NETWORK (ANN)

– Data mining is the process of extracting important and useful information from large sets of data. The goal of the data mining process is to extract knowledge from an existing data set and transform it into a unique human understandable format for some advance use. Data mining in agriculture is in relation to novel research field. Some efficient techniques can be developed and tailored for solving complex agricultural problems using data mining. Agriculture and allied activities constitute the single largest component of India’s gross domestic product, contributing nearly 25% of the total and nearly 60% of Indian population depends on this life’s precise profession. Due to vagaries of climate factors the agricultural productivities in India are continuously decreasing over a decade. The reasons for this were studied mostly using regression analysis. In this paper an attempt has been made to compile the research findings of different researchers who used agriculture data. This paper summarizes the application of data mining techniques such as k-means, bi clustering, k nearest neighbor, Neural Networks, Support Vector Machine and Naïve Bayes Classifier in the agriculture field.
Analyzing Factors Affecting Repurchase Intention During Gezi Park Brand Protests

During the Gezi Park protests, some major brands were criticized within social media either for what they did or did not and social pressure to boycott those brands was highly apparent. Many newspaper articles highlighted that negative WOM during the protests might have affected consumers’ brand related knowledge. This notion is further supported by previous research. What happened during and after Gezi Park protests creates a perfect environment to analyze this effect. In addition, it was believed that only a portion of the consumers were highly affected by the protest calls. Consequently, this study aims to understand whether consumers have really changed their intention to buy from of a bank and a domestic coffee chain due to protest calls. The study also analyzes whether only a proportion of the consumers were affected and whether their trust, loyalty, awareness, perceived quality, and self-construal, and the company’s perceived social responsibility played a significant role in this change. A hierarchical logistic regression procedure (Forward Wald) with 357 usable cases was used with likelihood of change in purchase as the dependent variable. The results indicate that for the domestic coffee shop only perceived social responsibility plays a role in the change of consumers’ purchase intention. However, for the bank within the study, perceived social responsibility is found to be an insignificant contributor, whereas loyalty and awareness are found to be significant contributors to consumers’ purchase decisions. Perceived quality/trust and consumers’ self-construal are found to have no effect on the change of consumers’ intention for both brands under study.
Glaucoma Detection And Segmentation Using Retinal Images

— Glaucoma is an eye disease . It is detected from retinal images using some classifiers like Support vector machine, random forest, Dual sequential minimal optimization, Naïve bayes and artificial neural networks. Some features are obtained from retinal images using 2D-DWT. These features are used for classification. Different wavelet features are obtained from the three filters symlets (sym3), daubechies (db3) and biorthogonal (bio 3.3,bio 3.5,bio 3.7) wavelet filters. These features are used for classifying and detecting normal and glaucomatous retinal images.The glaucomated retinal image is then threshold based segmented to highlight the affected portion.
Implementation of in cast Congestion Control for TCP

:TCP incast is a recently identified network transport pathology that affects many-to-one communication patterns in datacenters Network and techniques for provides performance improvement in terms of throughput and window size variations. When multiple synchronized servers simultaneously send data to a single receiver in parallel means congestion occurs. In this paper, we study TCP in-cast congestion may severely degrade their performances by increasing response time also we study among TCP goodput, receive window and round trip time (RTT). Our idea is to develop an ICTCP (In cast congestion Control for TCP) scheme at the receiver side. It is caused by a complex interplay between datacenter networks, the underlying switches, network topology, and TCP. This was originally designed for wide area networks. Sender side TCP uses a congestion window to do congestion avoidance. The congestion window indicates the large amount of data that can be sent out on a connection without being acknowledged. TCP identify congestion when it fails to receive an acknowledgement for a packet within the estimated timeout. In particular, our technique adjusts TCP receive window proactively before packet loss occur. The problem mainly affects computing paradigms in which distributed processing cannot progress until all parallel threads in a stage complete.
Energy Efficient Allocation for Cloud System Using Evolutionary Algorithm

— In recent years, high-performance computing service for research and application is improvement quickly. The computer systems serving for high-performance computing is growing up. The advent of cloud computing has changed the way that manages and uses computer system resources. Therefore, scheduling techniques become important tools in cloud computing. In this article, we will introduce a scheduling technique to reduce energy consumption for cloud systems using evolutionary algorithm. The effectiveness of the algorithm is shown by experimental results. Thereby, demonstrating the energy-aware ability of evolutionary algorithm in comparison with related researchs.
Area and Delay Efficient Digital Comparator

Quantum-dot cellular automata (QCA) tend to be an attractive emerging technology suitable for the development of ultra-dense low-power high-performance digital circuits. Efficient solutions have recently been proposed for several arithmetic circuits,such as adders, multipliers, and comparators. This paper proposes a new design approach oriented to the implementation of binary comparators in QCA. The proposed work uses novel implementation strategies, methodologies and new formulations of basic logic equations to make the comparison function applied to comparator efficient. The new strategy has been exploited in the design of two different comparator architectures and for several operands word lengths.The comparators are proposed here exhibit significantly higher speed and reduced overall area. The existing and proposed comparators are synthesized using Xilinx and performance is evaluated in terms of number of gates and delay.
Effects of Al2O3 Nanoparticles on Compressive and Diametral Tensile Strength of Zinc Polycarboxylate Cement

The effects of 3 wt% and 5 wt% Al2O3 nanoparticles on compressive and diametral tensile strength of zinc polycarboxylate cement were investigated. Materials and Methods: 3 wt% and 5 wt% Al2O3 nanoparticles addition zinc polycarboxylate cements were used for this study. Specimens were divided in three groups (n=10) for compressive and diametral tensile tests. Group 1. Zinc polycarboxylate cement without nanoparticle (control group) Group 2. Zinc polycarboxylate cement with 3 wt% Al2O3 nanoparticles Group 3. Zinc polycarboxylate cement with 5 wt% Al2O3 nanoparticles. Specimens having a diameter of 4 mm and a height of 6 mm and specimens having a diameter of 4 mm and a height of 2 mm were prepared for compressive and diametral tensile tests respectively. Compressive and diametral tensile tests were performed using an universal test machine. Results: Compressive strength decreased in 3 wt% Al2O3 nanoparticles addition zinc polycarboxylate cement compared to control group (p<0.05). There was no significiant difference between compressive strengths of 5 wt% Al2O3 nanoparticles addition zinc polycarboxylate cement and control group (p>0.05). For diametral strength, there was no significant difference between 3 wt% and 5 wt% Al2O3 nanoparticles addition zinc polycarboxylate cement (p>0.05). Control group showed the higher diametral tensile strength than the other groups (p<0.05). Conclusion: The lowest compressive strength occured in 3 wt% Al2O3 nanoparticles addition zinc polycarboxylate cement. For diametral strength, there was no difference between 3 wt% and 5 wt% Al2O3 nanoparticles addition zinc polycarboxylate cement.
An Efficient Approach to Optimize the Performance of Massive Small Files in Hadoop MapReduce Framework

— The most popular open source distributed computing framework called Hadoop was designed by Doug Cutting and his team, which involves thousands of nodes to process and analyze huge amounts of data called Big Data. The major core components of Hadoop are HDFS (Hadoop Distributed File System) and MapReduce. This framework is the most popular and powerful for store, manage and process Big Data applications. But drawback with this tool related to stability and performance issues for small file applications in storage, manage and processing the data. Existing approaches deals with small files problem are Hadoop archives and SequenceFile. However, existing approaches doesn’t give an optimized performance to solve small files problems on Hadoop. In order to improve the performance in storing, managing and processing small files on Hadoop, we proposed an approach for Hadoop MapReduce framework to handle the small files applications. Experimental result shows that proposed framework optimizes the performance of Hadoop in handling of massive small files as compared to existing approaches.
Review of Energy Aware Cloud Computing

With the rapid growth of cloud computing developers are being concern about the massive data centres. The huge amount of power consume by the data centres does also the production of heat and carbon footprints on the environment. power efficiency and minimizing energy consumption of Data centres. This paper presents a study of the researches and methods that have been proposed to increase the power efficie
Parsing of HTML Document

The Websites are an important source of data now days. There has been different types of information available on it. This information can be extremely beneficial for users. Extracting information from internet is challenging issue. However the amount of human interaction that is currently required for this is inconvenient. So, the objective of this paper is try to solve this problem by making the task as atomic as possible. Existing methods addressing the problem can be classified into three categories. Methods in the first category provide some languages to facilitate the construction of data extraction systems. Methods in the second category use machine learning techniques to learn wrappers (which are data extraction programs) from human labeled examples. Manual labeling is timeconsuming and is hard to scale to a large number of sites on the Web. Methods in the third category are based on the idea of automatic pattern discovery. For extracting information from web firstly we have to determine the meaningfulness of data. Then automatically segment data records in a page, extract data fields from these records, and store the extracted data in a database. In this paper, we are given method for an extracting data from SEC site by using automatic pattern discovery. KeywordsParsing engine, Information Extraction, Web data extraction, HTML documents, Distillation of data.