Miracle-dz/UniFAR-FTUs huggingface dataset:
SHEDULING THE PACKET ROUTING USING NEURAL NETWORK FOR OPTIMIZING QUALITY OF SERVICE PARAMETERS

Computer network packet routing is an major important function in the computer based communication, The quality of service parameters efficiencies are highly depends on the how the packet travel and using which path. The strategically scheduling of routing can play major role in the network performance also essential to choose proper routing while designing the computer network. Artificial neural networks are basically known to as systems of connected "neurons" which are communicating through exchange messages between. The communication having the stastical figure known as weights that can be adjust based on experimental and real knowledge, which makes the neural network a adaptive to inputs and capable of learning. Using Hopfield artificial neural networks one can fast computation and leaning and with low energy in its basic stable formation. They are good contender for the implementation of neural routing algorithm. We are utilizing the Hopfield neural network for neural routing computation of shortest path in the network in this paper.
Expert views on current and future use of social media among crisis and emergency management organizations: Incentives and barriers

Our research explored the use of social media among crisis and emergency management organizations and we present the main incentives and barriers experts perceive in social media adoption by such organizations. The data were gathered via an international online questionnaire sent to crisis communication and management experts. The results indicate that crisis and emergency management organizations use social media specifically to disseminate information to citizens but also increasingly to receive it from citizens. They are motivated to use social media because of the possibility for communicating through them directly, rapidly, and widely, as well as for building responsible relationships and situational awareness. Lack of knowledge, time, and role models for implementation, as well as inflexible and old-fashioned organizational culture, were the main barriers mentioned for not utilizing social media. Based on the results, further effort should be put into promoting the dissemination of knowledge, best practices, and experiences of using social media across the various actors and organizations providing crisis response.
Waiting time and cell loss probability analysis for the buffered leaky bucket

The use of preventive congestion contro~ mechanisms has begun to receive increasing attention for app" r:ations . n high-speed communication networks. The . eaky bucket policing mechanism has been proposed for use as part of an overall preventive congestion control strategy in high-speed networks. We analyze approximately the waiting time distribution and the cell loss probability for the buffered leaky bucket policing mechanism, assuming that the source behaves as a two-state ou/off arrival process with arbitrary distributions for the time spent in each state. Our results indicate that if the token pool size of the leaky bucket is sufficiently large, then the mean cell delay becomes negligible, and also it becomes roughly independent of the cell queue size and the average burst length. However, the percentile of the cell delay can vary substantially depending on the average burst length, becoming proportional to the product of the cell queue size and the token interarrival time even for fairly small cell loss probabilities (i.e. 10 -5).
Optimization of perceptual steganography capacity using the human visual system and evolutionary computation

Efficient solutions for the purpose of delivery of information are called for by the revolution of internet. However concerns and problems over security, distribution of digital content and encapsulation of media artifacts have arisen as a result of these phenomenal developments. Hence, it has become necessary to seek capabilities to transport and secure multimedia with its meta-data in a safe way. Steganography has evolved as an enabler of multimedia applications keeping secret communication and embedded captioning secure. There is a tolerable outcome that occurs between imperceptibility and steganographic capacity that fit right into the mix. For instance, the more subtle elements are hidden within the cover object having higher capacity, the more degradation is exhibited towards the carrier file, resulting in an increase in the distortion attributed to the information being concealed and at the same time, decreasing the stego file quality. Suitable use of Evolutionary Algorithm and effective use of the weaknesses of Human Visual System in steganography are investigated in this thesis. Firstly, two high capacity steganography approaches are developed with the use of aforementioned features. The first method aims to overcome the limit capacity of edge based steganography in the spatial domain. The second method proposes a proper threshold selection for each coefficient which increase the capacity of transform domain. An estimate of the embedding rate based on image complexity is also proposed. Moreover, since peak signal-tonoise ratio (PSNR) is largely used as a measure of quality of images of stego, the reliability of current quality assessment metrics for stego images is also
A Laser Scanner System For Investigating Noninvasive Matching Strategies In Computer-assisted Orthopaedic Surgery

ABsTRAcr In this paper we investigate the possibility of using a non invasive technique in robotic orthopaedic surgery for matching body parts with a robot reference frame. It is based on a laser range tinder mounted on a Puma 560 robot arm and aims at recognizing some significant features of bones during in vitro simulations.
Simulation Input Modeling in the Absence of Data

Simulation models provide a powerful tool for analyzing real-world systems. These models are driven by input data, so when inputs are unknown and no data exists, the development of the simulation model becomes problematic. This research addresses the problem of modeling inputs in the absence of data, with the goal being to define and verify a formal group process for developing simulation model inputs when data is lacking. The recommended process modifies a Delphi process and employs a panel of subject area experts to provide estimates through several rounds of web-based surveys. After each round, the panelists' responses are analyzed, and a summary of the responses and comments from the previous round, as well as any supplemental information, is provided to the panelists to help them develop estimates in the next survey round. By sharing information, the panelists gain insight into the beliefs and opinions of their colleagues, resulting in a growing consensus about the questions addressed in the study. This process was implemented in the Colorectal Cancer Simulation Study to develop inputs for the simulation. As in this study and many other medical simulations, a number of inputs are unknown or uncertain because appropriate data does not exist or experiments cannot be performed to define the unknown inputs because of their grave nature. In this study, fifteen experts from the areas of gastroenterology, epidemiology, and microbiology were recruited to serve on the expert panel. Three rounds of webbased surveys were conducted to reach consensus on four different study objectives related to adenoma development and cancer progression. The final simulation model inputs were developed using the estimates and the VisiFit distribution-fitting software. To examine the flexibility, usefulness, and acceptability of the process, the expert panelists and the study's Advisory Board were sent evaluation surveys asking specifically about the group process and the resulting inputs developed. The panelists felt the process was flexible, required a minimal time commitment, and the web-based surveys were easy to use. The group dynamics throughout the surveying process allowed everyone to share information without worrying about dominance or groupthink. The information available during the process to support estimate development was adequate from the perspective of the panelists. Both the panelists and the Advisory Board found the inputs developed via the process to be consistent with real-world cases of adenoma development and cancer progression. They also believed the input estimates were more accurate than what one individual or an informal group could have developed. Since the group process was fully executed and a growing consensus of the estimates produced the final simulation model inputs, the process was clearly feasible. The cost of the process was easily justified because of the limited methods currently available to otherwise gain this information for use in the Colorectal Cancer Simulation Study. Because this information…
From OpenMI to HydroCouple: Advancing OpenMI to Support Experimental Simulations and Standard Geospatial Datasets

: HydroCouple is a cross-platform, component-based modeling interface definition that largely follows the Open Modeling Interface 2.0 (OpenMI) specification. HydroCouple provides advancements to better facilitate those experimental model investigations that fall into the so-called “embarrassingly parallel” class of simulations, including uncertainty assessment, ensemble forecasting, and optimization simulations. Additionally, HydroCouple explicitly incorporates low level interface definitions for multi-dimensional datasets and geospatial data formats including the Open Geospatial Consortium’s Simple Feature Access specification, raster datasets, and meshes that are widely used in the earth systems and environmental modeling field. In this paper, we describe these and other advances provided by the HydroCouple interface definitions. We also illustrate how these advances can be used to facilitate parallelized experimental model simulations that have so far been challenging in OpenMI and other component-based modeling frameworks.
Some Research Issues for Beyond 3G Mobile Systems

The developing tendency of mobile communication in detail is analysed, and some key research issues related to the Beyond 3G mobile systems are described briefly. Some research achievements regarding these topics are mentioned in WTI(wireless technology innovation) labs. Disscussions for the prediction of the next generation mobile systems are given.
A fast algorithm for finding better routes by AI search techniques

The shortest path problem is one of the most fundamental problems applicable in various fields, and has close relation to route navigation systems. This paper surveys algorithms for the two-terminal shortest path problem and proposes bidirectional A* algorithm based on a new approach. This algorithm is suitable for finding not only the shortest route but also better routes. The efficiency and the property of these algorithms are discussed through experiments applying them to an actual road network. <<ETX>>
Synthesis of Biodiesel from Palm Kernel Oil Using Mixed Clay-Eggshell Heterogeneous Catalysts

The synthesis and characterization of clay-eggshell mixed catalysts was carried out for the transesterification of palm kernel oil using methanol as solvent. Clay from anthill and waste chicken eggshells were powdered and mixed via incipient wet impregnation in 50-50, 80-20 and 20-80% proportions of clay to eggshell on mass basis. The resulting mixtures were oven dried at 120 0C and calcined in the furnance at 900 0C for 4 hours. The uncalcined raw clay sample was characterized via the X-ray fluorescence method while the as-synthesized catalyst samples were characterized via the Fourier Transform Infrared Radiation Spectroscopy and Scanning Electron Microscopy. The performance of the as-synthesized catalysts was tested in transesterification of palm kernel oil (PKO) via a 2 level factorial experimental design optimizing four variables including reaction time, reaction temperature, methanol/oil molar ratio and catalyst loading in which case the yield was the required response. The 50-50 catalyst attained a maximum yield of 56.2% at 70 0C, methanol/oil ratio of 12:1, reaction time of 180 min, catalyst loading of 5 wt. % compared to the 65.2% achieved with the 80-20 catalyst at 90 0C, methanol/oil ratio of 12:1, reaction time of 180 min., catalyst loading of 5 wt% and the 70.7% obtained for the 20-80 catalyst at 70 0C, methanol/oil ratio of 12:1, reaction time of 180 min, catalyst loading of 3 wt%, thus, indicating mixed effect of variables as fully discussed. The developed catalysts were found to be good for biodiesel production and have the ability of improved performance.
Learning to abstract : How short-term experience shapes neural sound representations

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Automatic Image Annotation by Fusing Semantic Topics

Automatic image annotation has become an important issue, due to the existence of a semantic gap. Based on probabilistic latent semantic analysis (PLSA), this paper presents an approach to annotate and retrieve images by fusing semantic topics. First, in order to precisely model training data, each image is represented as a bag of visual words. Then, a probabilistic model is designed to capture latent semantic topics from visual and textual modalities, respectively. Furthermore, an adaptive asymmetric learning approach is proposed to fuse these semantic topics. For each image document, the topic distribution of each modality is fused by multiplying different weights, which is determined by the entropy of the distribution of visual words. Consequently, the probabilistic model can predict semantic annotations for an unseen image because it associates visual and textual modalities properly. This approach is compared with several other state-of-the-art approaches on a standard Corel dataset. The experimental results show that this approach performs more effectively and accurately.
Web-based Mineral Information System of Thailand Using Free and Open Source Software and Open Geospatial Consortium

This paper introduces the technique of mineral resources information management and distribution. It is a Web-based Mineral Information System of Thailand using FOSS and OGC based web services and standards. It distributes the geospatial content on the web through the formulation of web services such as WMS and WPS, launched on a customized WebGIS portal. The web-based mineral information system plays a critical role in the national dissemination of mineral information. It also supports the activities of the WGMID of the ASOMM. The approaches of sharing mineral resources information, formulation of web services, and the setting up of a WebGIS portal for mineral information processing and dissemination are presented. The primary advantages of these approaches are its cost efficiency in the development and system maintenance, and the applicability of the server software and web-based system to other geosciences fields.
A portable vector-code for autonomous multigrid modules

The implementation is described of two multigrid algorithms for use as standard subroutines for the efficient solution of linear systems that arise from 7-point discretizations of elliptic PDEs on a rectangle. For both algorithms a tuned scalar-version and a tuned vector-version have been constructed and run on a CYBER 170, a CRAY I and a CYBER 205. The CPU-times are given and compared. The implementation is available in portable ANSI-FORTRAN.
Mental simulation of four visual object properties: similarities and differences as assessed by the sentence–picture verification task

ABSTRACT In the sentence–picture verification (SPV) task, people read sentences implying the shape/size/colour/orientation of objects. They then verify whether pictured objects, which either match or mismatch the implied visual information mentioned in the sentence. Faster verification times on matching trials (match advantage) are considered supportive to the notion that readers perform mental simulations during sentence comprehension. This study advances this work by applying a within-subjects design to the SPV-task, enabling us to directly address the strength of and correlation between the match advantages for the properties shape, size, colour, and orientation. Results showed varying match advantages with colour showing the strongest effect, and no match advantage for orientation. Shape, size, and colour were significantly correlated, whereas there were no significant correlations with orientation. These findings suggest that interpretations of match advantages could benefit from a re-evaluation of mental simulation accountsby distinguishing between intrinsic (shape, size, and colour) and extrinsic (orientation) object properties.
Design and Verification of Efficient On-Chip Debugger for Core-A

Nowadays, the SoC is watched by all over the world with interest. The design trend of the SoC is hardware and software co-design which includes the design of hardware structure in RTL level and the development of embedded software. Also the technology is toward deep-submicron and the observability of the SoC's internal state is not easy. Because of the above reasons, the SoC debug is very difficult and time-consuming. So we need a reliable debugger to find the bugs in the SoC and embedded software. In this paper, we developed a hardware debugger named OCD. It is based on IEEE 1140.1 JTAG standard. In order to verify the operation of OCD, it is integrated into the 32bit RISC processor - Core-A (Core-A is the unique embedded processor designed by Korea) and is tested by interconnecting with software debugger. When embedding the OCD in Core-A, there is 14.7% gate count overhead. We can modify the DCU which occupies 2% gate count in OCD to adapt with other processors as a debugger.
Novel image retrieval algorithm based on BTC

A novel image retrieval method based on Block Truncation Coding (BTC) was proposed. Firstly, the image was divided into non-overlapped and equally-sized blocks, and these blocks were coded by the method of BTC. Then, the keyblocks of image were defined according to the human visual feature and the color difference between pixels in the image blocks. At the same time, the different importance of each keyblock in describing the image was taken into account, and the weighted function was introduced. Finally, the technologies in Text Information Retrieval (TIR) were applied in Content-based Image Retrieval (CBIR). Experimental results show that the proposed method has reasonable and robust retrieval performance and is more effective in the image retrieval than the other algorithms discussed in the paper.
Estimation of muscle stiffness during one cycle of pedaling exercises using system identification

The aim of this study was to evaluate muscle stiffness during one cycle of pedaling exercises. Electrical stimulation was applied to the vastus lateralis muscle at various clank angles in a resting state and during pedaling exercises. The angles were -30°, +30°, and +90°. The angle of 0° corresponds to top center of the pedal, and the clockwise direction is positive. A mechanomyogram (MMG) was measured with a capacitor microphone. The MMG system was identified using a singular value decomposition method and the poles of the transfer function were calculated. The poles and mass of the vastus lateralis muscle were used to estimate the muscle stiffness. The muscle stiffness increased as the muscle activity increased. In conclusion, it was suggested that muscle stiffness during pedaling exercises changes depending on muscle activity.
In silico sequence and structural characterization of protein C enzyme in Macaca fascicularis

Protein C is an anti-thrombotic, anti-inflammatory serine protease, that is encoded by PROC gene in humans. Functional activated protein C (APC) levels are regulated by the serine protease inhibitor family of proteins, including α1antitrypsin and protein C inhibitor [1]. Although this enzyme has been well characterized in humans and in bovine, the assessment of this enzyme has not been carried out in other mammals, which would pave way for the understanding of the evolution of this enzyme. In this study, an in silico characterization of protein C enzyme has been accomplished in Macaca fascicularis, a primate, to study the sequence and structural features and also to identify new members of this enzyme in M. fascicularis. Keywords— Protein C, sequence, structure, Macaca fascicularis,
Random Pilot Signal Design and Channel Estimation Method based on Compressed Sensing Theory

A channel parameter estimation method adapted to a wireless communication system is proposed. The wireless communication system includes a transmitter and a receiver. The proposed method includes following steps. The transmitter transmits a plurality of pilot signals to the receiver by using one of a plurality of preconfigured sparse random pilot patterns. The receiver receives the pilot signals, performs a channel parameter estimation on the pilot signals by using a compressive sensing algorithm to obtain a multipath channel number, and selects a pilot pattern for a next cycle among the preconfigured sparse random pilot patterns according to the multipath channel number and a current pilot number. Additionally, the receiver transmits feedback information associated with the selected pilot pattern to the transmitter.
Illumination Control of LEDs in Visible Light Communication Using Manchester Code Transmission

In this paper, we introduce a new method for controlling the illumination of LEDs in visible light communication (VLC) by changing the duty cycle of Manchester code. When VLC data were transmitted in Manchester code, the average optical power of the LEDs was proportional to the duty cycle. In experiments, we controlled the illumination of a 3 × 3 LED array from 10% to 90% of its peak value by changing the duty cycle of the Manchester code. The synchronizing clocks required for encoding and decoding the Manchester code were supplied by pulse generators that were connected to a 220 V power line. All pulse generators made the same pulses with a repetition frequency of 120 Hz, and they were synchronized with the full-wave rectified voltage of the power line. This scheme is a very simple and useful method for constructing indoor wireless sensor networks using LED light.
Research on the Domain-Ontology-Based Semantic Similarity Computing

The paper presents some related knowledge on ontology and three kinds of computing models based on domain ontology.Aimed at the advantages and disadvantages of these models,as well as the characteristics of domain ontology,we put forward an improved domain-ontology-based semantic similarity computing model,which makes the information content and attribute of concept as two decision factors based on the distance-based computing model.It is proved that this model can reflect the semantic relationships among the concepts more precisely,and provide an effective quantification for them.