Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple fanout static routing network for field programmable printed circuit boards

A multiple fanout static routing scheme is described which is capable of overcoming most of the limitations of Field Programmable Printed Circuit Boards (FPPCBs) encountered with existing routing schemes. The new static routing scheme is then evaluated by implementing several ISCAS benchmark circuits on an FPPCB with this new routing scheme and is found to perform much more efficiently than the FPPCBs with the other routing schemes.
Insights from Machine Learning Techniques for Predicting the Efficiency of Fullerene Derivatives‐Based Ternary Organic Solar Cells at Ternary Blend Design

Ternary organic solar cells (OSCs) have progressed significantly in recent years due to the sufficient photon harvesting of the blend photoactive layer including three absorption‐complementary materials. With the rapid development of highly efficient ternary OSCs in photovoltaics, the precise energy‐level alignment of the three active components within ternary OSC devices should be taken into account. The machine‐learning technique is a computational method that can effectively learn from previous historical data to build predictive models. In this study, a dataset of 124 fullerene derivatives‐based ternary OSCs is manually constructed from a diverse range of literature along with their frontier molecular orbital theory levels, and device structures. Different machine‐learning algorithms are trained based on these electronic parameters to predict photovoltaic efficiency. Thus, the best predictive capability is provided by using the Random Forest approach beyond other machine‐learning algorithms in the dataset. Furthermore, the Random Forest algorithm yields valuable insights into the crucial role of lowest unoccupied molecular orbital energy levels of organic donors in the performance of ternary OSCs. The outcome of this study demonstrates a smart strategy for extracting underlying complex correlations in fullerene derivatives‐based ternary OSCs, thereby accelerating the development of ternary OSCs and related research fields.
IMUNODIAGNÓSTICO PARA A ARTRITE-ENCEFALITE CAPRINA EM REBANHOS DO SEMIÁRIDO BAIANO, BRASIL

ABSTRACT. de Lima C.C. V. , Costa J.N. , Souza T.S. , Martinez P.M. , Costa Neto A.O. , Azevedo D.A. A. , Pinheiro R.R. & Brito R.L. L. [Immunodiagnostic for caprine artrithis encephalitis in flocks of semi-arid region in the State of Bahia, Brazil]. Imunodiagnostico para a artrite-encefalite caprina em rebanhos do semiarido baiano, Brasil. Revista Brasileira de Medicina Veterinaria, 35(4):358-364, 2013. Programa de Pos-Graduacao em Ciencia Animal nos Tropicos, Escola de Medicina Veterinaria e Zootecnia, Universidade Federal da Bahia, Av. Adhemar de Barros, 500, Salvador, BA 40170-110, Brasil. E-mail: carlacvlima@gmail.com This work had the purpose of standardizing the technique of indirect immunosorbent assay (i-Elisa) for the diagnosis of caprine arthritis-encephalitis (CAE) in flocks of Microregion of Juazeiro, and to compare the results obtained with other techniques. To attain our goal, we evaluated 693 blood serum samples of goats from 46 farms in this Microregion (Campo Alegre de Lourdes, Casa Nova, Curaca, Juazeiro, Pilao Arcado, Remanso, Sento Se and Sobradinho). About the seroprevalence obtained in i-Elisa, 1.59% (11/693) of the animals showed they possess the anticorps against the CAE’s virus and 15.22% (7/46) of the properties had seropositive animal. Results of commercial AGID demonstrated that only 0.29% (2/693) of the samples were positive. Standard Elisa showed 100% sensitivity and 98.7% specificity, with kappa of 0.30 compared to the commercial AGID. Of the 693 samples, 65 were used in techniques of Immunoblotting (IB) and different AGID kits. There was no difference in the results obtained in the AGID kits, and IB demonstrated higher sensitivity than i-Elisa. Therefore, it is recommended to use different techniques such as AGID and Elisa in order to improve the diagnosis of CAE control programs.
SDX

BGP severely constrains how networks can deliver traffic over the Internet. Today's networks can only forward traffic based on the destination IP prefix, by selecting among routes offered by their immediate neighbors. We believe Software Defined Networking (SDN) could revolutionize wide-area traffic delivery, by offering direct control over packet-processing rules that match on multiple header fields and perform a variety of actions. Internet exchange points (IXPs) are a compelling place to start, given their central role in interconnecting many networks and their growing importance in bringing popular content closer to end users. To realize a Software Defined IXP (an "SDX"), we must create compelling applications, such as "application-specific peering"---where two networks peer only for (say) streaming video traffic. We also need new programming abstractions that allow participating networks to create and run these applications and a runtime that both behaves correctly when interacting with BGP and ensures that applications do not interfere with each other. Finally, we must ensure that the system scales, both in rule-table size and computational overhead. In this paper, we tackle these challenges and demonstrate the flexibility and scalability of our solutions through controlled and in-the-wild experiments. Our experiments demonstrate that our SDX implementation can implement representative policies for hundreds of participants who advertise full routing tables while achieving sub-second convergence in response to configuration changes and routing updates.
Fpga Design And Implementation Of A Scan Conversion Graphical Sub-System

One Major modeling primitive in the field of Computer Graphics is a planar polygon. This polygon can have an arbitrary number of vertices and different shapes. In this paper a graphic sub-system is designed and implemented using Field Programmable Gate Array ( FPGA ). One of the main tasks of the hardware designed is scan-converting convex planar polygons required to update an image in the image memory or video RAM which is used as a Frame Buffer. A facility to read the pixels (Picture Elements), from the frame buffer, for display on the monitor of the computer is also included in the design.
Analysis and Synthesis of Head Motionfor Life like Conversational Agents

This study aims to investigate which and what motions of lifelike conversational agents play essential role to make the agents natural. Some preliminary experimental results and future plan are shown. Embodying conversational agents is intended to imitate paralinguistic channel or back channel which plays important role in human-human conversation. Although there have been not a few lifelike conversational agents developed, appearance and behaviour of the agents are far from being natural, and merits of embodying have not been realized that much. One of the main reasons is the lack of natural motions of the agents, including the motion of head, mouth, eyes and eye brows. To improve the quality of these motions, several pioneering works have been reported [1–3]. To tackle the problem, the present study was started conducting a subjective test of head motion and analysis of head motion using signal processing techniques.
Automatic Evaluation of Privacy Policy A Machine Learning Approach

Privacy is taking an increasingly prominent place in today’s digital world. People wish to control their private information when interacting with websites on the Internet. However, customer information is one of the keys to successful Internet business. Internet companies wish to gather and use as much customer information as possible in order to facilitate business, build competitive barrier and generate profits. In the middle of the conflicting notions, privacy policy serves as the main channel for the companies to disclose their practice for dealing with user’s private information. However, many surveys have shown that users seldom read the privacy policies and the current mechanisms to present website privacy policies have not been successful. The readability issue of privacy policies calls for automated ways of privacy policy evaluation to assist users to quickly gain insights about the privacy practice of the website. This research addresses the present gap in the communication and understanding of privacy policies, by creating an automated privacy policy evaluation framework that provides automatic categorization, analysis and grading of privacy policies. We advocate a machine learning approach towards privacy policy evaluation and lay the fundamental basis for this new approach. We present a privacy policy evaluation framework. The framework comprises several core components, such as privacy policy paragraph categorization, privacy policy grading, share statement understanding, as well as some accessorial components, such as privacy policy detection, search result extraction, text extraction, visualization, and web application interface. We define the common categories of privacy policies, label real-world privacy policies to form the datasets and implement all the aforementioned components. We investigate the application of text classification to categorize privacy policy paragraphs. We present extensions to this categorization scheme, such as twolayered classification, multi-label classification, grading and visualization. We propose two approaches for the task of share statement understanding, each with different variants. We extensively experiment with our proposed schemes and approaches on the privacy policy datasets. Our study results demonstrate that the machine learning approach is effective in building privacy policy evaluation systems that serve the purpose to assist users to better understand the privacy policies.
Turbo space-time receiver by kurtosis maximization for CCI/ISI reduction in cellular wireless communications

In this paper, Chi and Chen's computationally efficient fast kurtosis maximization algorithm (FKMA) for blind beamforming and equalization is applied to the design of the conventional cascade space-time receiver (CSTR) for blind co-channel interference and inter-symbol interference (ISI) reduction in cellular wireless communications using antenna arrays. However, the receiver performance is limited as the normalized kurtosis magnitude of the ISI-distorted signal of interest, denoted as gamma, is small. Then a blind turbo space-time receiver (TSTR) is further proposed that applies spatial and temporal processing using FKMA in a cyclic fashion to estimate the desired data sequence. The performance of the proposed blind TSTR is insensitive to the value of gamma, and therefore is superior to that of the blind CSTR. Finally, some simulation results are provided to support the efficacy of the proposed blind TSTR
WSN Applications: Automated Intelligent Traffic Control System Using Sensors

In this new Era the growing Vehicle population in all developing and developed country calls for a major improvement and innovation in the existing Traffic Signaling systems. The most widely used automated system uses a simple time based system which working on a time interval basis which is now inefficient for random and non uniform Traffic. Advance automated systems in testing use image processing techniques or advance communication system with an intelligent information gathering systems in vehicles to communicate with signal and ask for routing. This might be implementable in developing countries as they are more complex and expensive also. The Concept Proposed in this paper involves use of Wireless sensor network technology to sense presence of Traffic near any circle or junction and then able to route the Traffic based on Traffic availability or we can say density in desire direction. This system does not require any system in vehicles so can be implemented in any Traffic system quite easily with less time and less expensive also. This system uses Wireless sensor networks Technology to sense vehicles and a microcontroller based routing algorithm programmed for excellent Traffic management. Keywords—Intelligenttrafficsignals,intelligentrouting, smart signals,wireless sensornetworks.
Physical and Functional Characterization of Long Terminal Repeat of Equine Infectious Anemia Virus.

The U3 region of long terminal repeat (LTR) of equine infectious anemia virus (EIAV) contains transcriptional regulatory elements. To identify the elements in prototype (P), fetal donkey dermal cell-adapted (A), and two variant (V) EIAV LTRs, DNase I footprinting, gel shift, and transient gene expression assays were performed. The assays used U937 monocytic cells which can be induced into macrophages by 12-0-tetradecanoylphorboI-13-acetate (TPA). For study of API sites, c-Jun/APl was also used. Footprinting with nuclear extracts from TPA-induced and uninduced U937 cells localized methylated DNA-binding protein (MDBP), PEA2, API, PU.l, and CCAAT enhancer-binding protein (C/EBP) sites as common elements in 5' to 3' direction in the U3 region of the 4 LTRs. The hypervariable region between the PEA2 and API sites was footprinted to contain at least one of the PEA2, API, or PU. 1 elements. In particular, the U3 region of ALTR was footprinted to contain Oct-1, MDBP, PEA2, PEA2, API, PU.l, API, PU.l, and C/EBP sites. The Oct-1 motif exists only in ALTR. Footprinting of the 4 LTRs with purified c-Jun/APl and gel shift assays of oligonucleotides containing LTR API sites with either c-Jun/APl or U937 nuclear extracts supported the identification of the API sites by the footprinting with the nuclear extracts. Transient gene expression assays of the 4 wild-type LTRs and ALTR mutants were performed with TPA-induced and uninduced U937 cells. These assays identified the existence of a negative regulatory element (NRE) upstream of the MDBP site.
Value co-creation in sport entertainment between internal and external stakeholders

Purpose Co-creation as a collaborative process between organizations and customers generates unique value for both internal and external stakeholders for the company. Research generally examines and portrays customer-company co-creation as a balanced and harmonious relationship. However, a successful co-creation strategy involves understanding the shared interests of the parties and resolving tensions between internal and external stakeholders to avoid co-destruction. This study aims to draw on the intersection of organizational behavior and marketing literature and to examine shared interests and conflicting tensions involved in the co-creation in the context of sports entertainment. This context allows the researchers to unpack and present a more complex process of co-creation that fosters co-creativity and innovation. Design/methodology/approach Based on a qualitative case-based approach of a major university in the USA, the authors draw on interviews and observations from their athletic administration and fans engaged in a men’s Division I team through an entire season. Findings This qualitative study illustrates an alternative, more complex dilemma of co-creating emotional and symbolic value based on shared interests while reconciling conflicting internal and external stakeholder interests. The findings suggest a tug of war based on tensions, where management adopted contrasting managerial strategies ranging from attempting to reconcile tension through organic co-creation to controlled manufactured creation. Research limitations/implications Emotional and symbolic game experience value is an interdependent process which cannot be created without consumer engagement. Both emotional and symbolic values are enhanced during games to the extent consumers perceive participation in the creative pre-game stages. Originality/value This study draws on sports entertainment to identify sources of tension in co-creation and discuss type of solutions among internal and external stakeholders.
Parallel simulation of high-speed network multiplexers

The simulation of statistical multiplexers in high-speed networks requires excessively long simulation runs when extremely small cell loss ratios are considered. We present an approach that allows the fast parallel simulation of finite capacity statistical multiplexers driven by bursty ON/OFF sources. Our approach is based on two techniques: (1) the derivation of cell level statistics from a burst level simulation; and (2) the use of time-parallel methods without fix-up phases for the burst level simulation. Both techniques contribute to the overall simulation speedup. The latter technique allows speedup factors that are linear with respect to the number of processors. An implementation of the method using 16 processors on a KSR 1 multiprocessor simulates from two million to over one billion cell arrivals per second, or up to five orders of magnitude faster than an efficient conventional sequential simulation. <<ETX>>
Habitat enhancements rescue bee body size from the negative effects of landscape simplification

1Department of Entomology, Cornell University, Ithaca, New York 2Department of Entomology, Michigan State University, East Lansing, Michigan 3Department of Entomology, University of Manitoba, Winnipeg, MB, Canada 4Department of Entomology, New York State Agricultural Experiment Station, Geneva, New York 5Ecology, Evolutionary Biology, and Behavior Program, Michigan State University, East Lansing, Michigan
Blind polarimetric equalization of UWB SAR imagery

Polarimetric synthetic aperture radar (SAR) imagery is susceptible to degradation due to non-ideal responses in antennas and other hardware. While a number of polarimetric calibration procedures have been developed to compensate for these effects, most are limited to narrowband SAR systems. The few that are applicable to ultrawideband (UWB) SAR suffer from a dependence on high-quality antenna measurements or detailed electromagnetic scattering models of test targets. Here a blind polarimetric equalization (BPE) technique is developed that uses second-order statistics from clutter or targets of opportunity to estimate the SAR system response. These estimates are then used to remove crosstalk contamination and imbalances between polarimetric images. The novel frequency domain implementation makes BPE suitable for ultrawideband SAR systems. BPE is an image post-processing procedure that does not require changes to radar hardware, antenna measurements, or target predictions.
HUMAN DETECTION BASED ON A SEQUENCE OF THERMAL IMAGES USING DEEP LEARNING

Abstract. Human detection has been playing an increasingly important role in many fields in recent years. Human detection is a still challenging task because, for the group of people, each individual has his unique appearance and, body shape.Compared with the traditional method, the deep learning neural network has the advantages of shorter computing time, higher accuracy and easier operation. Therefore, deep learning method has been widely used in object detection. The current state of art in human detection is RetinaNet. Among all the deep learning approaches, RetinaNet gives the highest accuracy of human detection (Lin, Goyal, Girshick, He, & Piotr Dollar, 2018). The temporal component of video provides additional and significant clues as compared to the static image. In this paper, the temporal relationship of the images is utilized to improve the accuracy of human detection. Compared to using only an image, the accuracy of human detection is 21.4% higher when a sequence of images is applied.
Perception-based genetic algorithm for a mobile robot with fuzzy controllers

The paper deals with a genetic algorithm for acquiring adaptive behaviors of a fuzzy based mobile robot. If its environmental state is stable or fixed, the behaviors of the robot can be optimized by conventional genetic algorithms. Otherwise, the behavior should be tuned by adaptation and learning according to the change of its environment. However, it is difficult for the robot to maintain behaviors suitable to various environmental states in the dynamic environment. Therefore, the paper proposes a genetic algorithm based on the perceived information about the dynamic environment, which is called a perception based genetic algorithm. We apply the proposed method to collision avoidance behaviors of the mobile robot in a dynamic environment. Furthermore, we conduct several computer simulations. Simulation results show that the proposed method can maintain various behaviors according to environmental changes.
Dynamic surface EMG/force relation in human elbow flexion

A surface EMG (SEMG) to force model is presented. An SEMG processor was developed based on a mathematical model of recorded SEMG. The processed SEMG and joint angle are the inputs of the muscle model which is a Hill-type muscle model. An anatomy matrix, which allows the transformation from muscle forces to moments acting about the joint, was determined based on the segment-link model. The method by which to determine the parameter values of the muscle model and the scaling factor of the SEMG is discussed. Human elbow flexion is chosen to describe the method as well as to evaluate the performance of the SEMG/force model.
Shape-controllable nanofibrous membranes with well-aligned fibers and robust mechanical properties for PM2.5 capture

In this study, design and fabrication of novel shape-controllable and aligned nanofibrous membranes with self-cleaning and robust mechanical properties is presented. Smooth and uniform nanofibers can be fabricated by blending polyamide 66 (PA66) and poly (vinyl butyral) (PVB) with a mass ratio of 6/4 during electrospinning. Subsequently, the prepared nanofibrous membranes were placed in a vacuum drying oven at a given temperature (90 °C) for heat treatment, and the morphology of the composite nanofibers was controlled by an external tensile force. It was found that the treatment temperature and external tensile force greatly affected the pore structures and orientation of the nanofiber membranes. In addition, the hydrophobicity, pore structure and mechanical properties of well-aligned nanofibrous membranes are better than those of non heat-treatment nanofibers. Moreover, the PA66/PVB nanofibrous membranes are used as air filters, and show an excellent removal efficiency of up to 99.99% for PM2.5.
Diffusion of methylene blue in human dentin in the presence of glucose: in vitro study

The work is devoted to the determination of the diffusion coefficients of methylene blue (MB) in pure aqueous and 40%-glucose-aqueous solutions in human tooth dentinal sections in vitro using diffuse reflectance optical spectroscopy and the free diffusion model. The determination of the diffusion coefficient of MB in a biological tissue was based on the measurement of the temporal kinetics of changes in the diffuse reflectance spectrum. Obviously, the diffusion rate along the dentinal tubules should be the greatest, close to that in water, taking into account some reduction in speed due to interaction with the walls, since they are filled up with a liquid with a high water content. In addition, the density of the dentinal tubules is large enough, so we can expect that their contribution to the total diffusion will be significant. It was determined that the diffusion coefficientfor 0.001% MB in an aqueous solution is (6.74±1.32)·10−6 cm2 and in 40%-glucose solution is (3.89±0.85)·10−6 cm2/s.