Miracle-dz/UniFAR-FTUs huggingface dataset:
An indexing-based approach for rapid and efficient product information integration and retrieval

Throughout a product's lifecycle, multiple stakeholders interact with each other to generate large amounts of disparate information about it. All of modern product development, particularly, in Original Equipment Manufacturers (OEMs), involves integrating such information that exists in a number of databases into a cohesive decision support solution, for various activities, such as Resource Management and Prototype Management. This integration is typically handled in the current environment using ad-hoc and manual combinations of data to address specific queries. This approach is error-prone, time consuming and limiting because every new analysis requires the definition of a specific combination of data. In this paper, as first step towards the ideal dynamic system for information integration and retrieval, we present a novel framework called CachingDB that consists of a centered database built of optimized data tables and index structures from the underlying product databases. We exemplify the multiple challenges, such as disparity of data types (structured, unstructured, and geometric) within and across the databases, redundancy of information, huge data set, rapid changes to the underlying data, and a wide variety of complex queries. We demonstrate the issues by and conclude with results of application to structured data (non-shape) stored in different databases for Prototype
Projection pursuit dynamic cluster model

Projection pursuit cluster(PPC) model is widely used in multifactor cluster analysis,but there are few problems needed to be solved in practice,and cutoff radius,which is an important parameter,is one of them.Aimed at the existing problems of PPC model and based on immune evolution algorithm,a projection pursuit dynamic cluster(PPDC) model,which combines dynamic cluster method with projection pursuit principle,is proposed for the first time in this study.As to PPDC model,the key of it lies in how to construct the projection index,and its operation process includes four steps.Compared with PPC model,PPDC model has its outstanding advantages,on one hand,it successfully avoids the problem of parameter calibration in PPC model,and on the other hand,the final cluster results can be output directly,and thus the subjectivity of PPC model is effectively eliminated.So PPDC model makes the cluster results more objective and definite,and besides that,it is also robust and easy to operate in practice.PPDC model is applied to study flood classification,and the test shows that PPDC model is feasible and effective,and it provides a powerful tool for the solution of similar problems.
Lab Manual - DD2427 Image Based Classication and Recognition

During the past decade, many methods and techniques have been gradually developed and applied to solve the problem. These include vector quantization with multiple codebooks, face templates and Principal Component Analysis (PCA). The latter technique is directly related to Eigenfaces and Fisherfaces. Here we will develop a face detection system based on the well-known work of Paul Viola and Michael Jones Viola and Jones [2001a]. This basically involves the interpretation of Haar-like features in a boosted cascade, see paper on the course homepage.
Assessment of the influence of urban stormwater runoff on the growth of Spiraea prunifolia var. simpliciflora

Plants applied to low impact development (LID) technologies reduce stormwater runoff pollutants through bioaccumulation of nutrients, heavy metals, and other pollutants during photosynthesis and respiration, and contributed to the restoration of natural water cycle through evapotranspiration. However, studies on the type of pollutants and environmental factors affecting Spiraea prunifolia var. simpliciflora growth LID technologies were still insufficient. Therefore, this study assessed the contaminants and environmental factors affecting the Spiraea prunifolia var. simpliciflora applied to LID techniques. In this study, a planter and a rain garden, which has different environmental conditions, were assessed. Amount of chlorophyll varied according to the TN and TP concentrations was also found to be essential for vegetation growth. In addition, it was also found that the influent concentration has a large influence on vegetation growth. The chlorophyll concentration was observed to be higher in the inflow part of both the planter and rain garden. The difference of chlorophyll content between the inflow part and outflow part was larger in the planter than that of the rain garden.
Towards cross-modal search and synchronization of music and video streams

With music markets shifting, the commercial use of music in video productions for film, TV or advertisement worldwide grows increasingly important. Our novel research project «SyncGlobal» addresses this global music licensing opportunity by developing adequate time-aware search technologies to efficiently handle sync licensing requests. The goal is to find the best acoustic or semantic matches to any video sequence from large-scale intercultural music catalogs with minimum human efforts involved. In this paper we outline conceptual issues and technology requirements derived from different application scenarios. We briefly introduce music and video segmentation, cross-modal semantic mapping strategies and time-aware music search techniques based on audio signal analysis
Clustering Feature Selection Method Based on Neighborhood Distance

To overcome the limitation of bad results on clustering and time-consuming of existing clustering algorithm to high-dimensional data,we provided an unsupervised feature selection algorithm based on neighborhood distance,then we clustered again on the selected feature subset.The use of the selected feature subset can improve clustering accuracy.The results of the experiment show that the method can find the valid features,and also improve the time-consuming problems in clustering on high-dimensional data.
Network Traffic Identification Based on Online Clustering

To solve the problem of network traffic identification online,a clustering algorithm and a traffic identification scheme is proposed.The scheme uses a few number of the initial data packets in the flows as a sub-flow,extracts the statistical features from sub-flows,and extracts the best feature subset of sub-flows by applying correlation-based filter approach.The network traffic flows are clustered by on-line density based spatial clustering of applications with noise algorithm,and mapped to application types by the dominant application in clusters.Experiments show that the scheme can identify new application types and encrypted flows,and can be implemented in online network traffic classification.
Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

BORDER SURVEILLANCE AND INTRUSION DETECTION USING A WIRELESS SENSOR NETWORK by MOSAD ALKHATHAMI August 2016 Advisor: Dr. Caisheng Wang Major: Electrical Engineering Degree: Doctor of Philosophy To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach.
Automatic machine learning-guided methods for 3D synapse quantification in confocal neuron images

Automatic Machine Learning-Guided Methods for 3D Synapse Quantification in Confocal Neuron Images Jonathan Sanders, M.S. Department of Computer Science Northern Illinois University, 2016 Jie Zhou, Ph.D., Director This thesis explores computational methods for automatically detecting and quantifying synapses in complex 3D neuronal images. The resulting approach is a novel combination of traditional image processing, machine learning algorithms, and multi-channel comparison methods designed to overcome the unique challenges posed by these images. The methods investigated combine the strengths of each of these components in order to produce an overall method that is capable of fully detecting the synapses in large 3D confocal neuron images with minimal interaction. Human annotation of 3D neuron images remains prohibitively difficult and subjective, and computational analysis tools are highly desirable in the expanding field of 3D neuronal imaging. Validation techniques were also designed and implemented in order to test these methods for this thesis, including construction of a gold standard set of manually annotated synapse images. These are unique in their own right as there are currently no other data sets available for comparison. These methods were tested on multiple partial dendritic tree 3D images and a complete 3D dendrite with good outcomes. Quantitative validation was performed using the gold standard set to check the accuracy of synapse quantification, also with favorable results. NORTHERN ILLINOIS UNIVERSITY DE KALB, ILLINOIS AUGUST 2016 AUTOMATIC MACHINE LEARNING-GUIDED METHODS FOR 3D SYNAPSE QUANTIFICATION IN CONFOCAL NEURON IMAGES BY JONATHAN WILLIAM SANDERS ©2016 Jonathan William Sanders A THESIS SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
Development and evaluation of android-based library stocktaking application using NFC Technology: a case study in Bina Nusantara University

Purpose The purpose of this paper is to develop and evaluate a mobile application to facilitate stocktaking in libraries implementing radio frequency identification. The case of Bina Nusantara University’s library is used in this study. In this kind of library, near field communication (NFC) tags are placed in the book for getting book information, borrowing or returning and theft prevention, so the application. Stocktaking is an important process to be performed periodically to monitor and maintain the quality of collections and to make these collections easily accessible for library users. However, stocktaking in libraries takes too much effort and needs to be more efficient. Design/methodology/approach The design of the mobile application using entity relationship diagram (ERD) includes a diagram and flowchart. An evaluation is done by comparing the stocktaking effort of the latest semester and the previous semester. In the latest semester, the stocktaking is done by a hybrid of the proposed mobile application and a legacy desktop application, whereas the stocktaking of the previous semester is done only using the legacy desktop application. Findings Evaluation of the usage of this mobile stocktaking application is 43 per cent more efficient compared to an older desktop application. Originality/value The authors report the development of Android-based mobile stocktaking application by using Android’s NFC feature and evaluate it in a real environment.
Deflicker Algorithm Based on Multi-frame Reference of Blocked Video

This paper proposes a deflicker algorithm based on multi-frame reference of blocked video.The algorithm estimates every block's flicker gain by considering the temporal change in multi-frames to adjust intensity of the current frame by using this flick-gain-model.We design a motion detector to correct motion blur caused by the adjustment of the flicker model.The algorithm can effectively remove video flicker and has low computation complexity therefore faster processing speed.
Multi-scaling Analysis of Social Network Users' Profiles

—Online social networks are extremely popular services on the Internet, having a relevant impact on the social, political and economical aspects of our daily lives. Being able to characterize social network users based on their temporal behavior and activity proﬁles can be useful to several engineering, management and design tasks. This paper characterizes the activity proﬁles of Facebook users, as well as their time evolution, based on data extracted using the Facebook Graph API and corresponding to social networking activity of 200 users during the years of 2011 and 2012. Using multiscale analysis based on a wavelet decomposition of the dataset, the proposed methodology is able to identify three main periodicity trends on the activity proﬁles: one of the identiﬁed proﬁles exhibits a visible periodicity around the 24 hours time scale (corresponding to users that have a daily interaction with Facebook), a second proﬁle exhibits relevant components in the complete frequency range (intensive interaction) and a third proﬁle includes important low periodicity components (users that tipically use Facebook in time periods higher than 24 hours). By looking at the temporal evolution of the different activity proﬁles, it is also possible to understand the dynamics of the proﬁle changes.
Improved algorithm of cluster head multi-hops based on LEACH

One of the key points of network routing design is power management.The paper summarizes the current transmitting routing model in wireless sensor networks,and finds that although the LEACH protocol is low power and adaptive lamination route algorithm,it might lead to overload of some cluster head nodes.Clustering algorithm is a kind of key technique used to reduce energy consumption.This article proposes a multi -hop routing improved algorithm based on the LEACH algorithm,and taking the optimization of the number of cluster heads into account,it can reduce energy consumption and prolong the lifetime of sense network through the use of multi-hop algorithm among cluster heads.Experimental result indicates it is effective.
Synthesis of 6-SubstitutedImidazo[2,1-b][1,3]thiazolesand 2-Substituted Imidazo[2,1-b][1,3]benzothiazolesvia Pd/Cu-Mediated Sonogashira Coupling

The reaction of iodobenzenes with 2-amino-3-(2-propynyl)-1,3-thiazolium bromide and 2-imino-3-(2-propynyl)-1,3-benzothiazole, catalyzed by Pd/Cu, leads to the formation of 6-substituted imidazo[2,1-b][1,3]thiazoles and 2-substituted imidazo[2,1-b][1,3]benzothiazoles, respectively.
Face Detection in a Mixed-Subject Document

Before you recognize anyone, it is essential to identify various characteristics variations from one person to another. among of this characteristics, we have those relating to the face. Nowadays the detection of skin regions in an image has become an important research topic for the location of a face in the image. In this research study, unlike previous research studies related to this topic which have focused on images inputs data faces, we are more interested to the fields face detection in mixed-subject documents (text + images). The face detection system developed is based on the hybrid method to distinguish two categories of objects from the mixed document. The first category is all that is text or images containing figures having no skin color, and the second category is any figure with the same color as the skin. In the second phase the detection system is based on Template Matching method to distinguish among the figures of the second category only those that contain faces to detect them. To validate this study, the system developed is tested on the various documents which including text and image. Full Text: PDF DOI: http://dx.doi. org/10.11591/ijece.v6i6. 12725
Antibacterial Activity and Structure Elucidation of Salicin from Stem Bark of Salix tetrasperma ROXB

Salix tetrasperma Roxb. (Family Salicacaeae) is a plant that used as traditional medicine for anti-inflammatory, analgesic, reduces fever, and itching medicine. In this study was carried out extraction, isolation, structure elucidation of salicin from Salix tetrasperma Roxb. stem bark and it’s antibacterial activity. The extraction method was used the maceration method by n- hexane, ethyl acetate, and methanol solvents. Isolation of compound from ethyl acetate extract of Salix tetrasperma Roxb. stem bark using chromatography methods and obtained white solid (15 mg). The structure was elucidated using spectroscopic analysis, including Ultraviolet (UV), Infrared (IR), Nuclear Magnetic Resonance (NMR) and comparative literature, identified as salicin compound with molecule formula C 13 H 18 O 7 . Antibacterial activity was evaluated against Escherichia coli and Staphylococcus aureus bacteria using disk diffusion method. This compound has a great an antibacterial activity against Staphylococcus aureus bacteria with clear zone diameter of 10.2 ± 0.3 mm. This shows that the Salix tetrasperma Roxb. stem bark has great potential as a source of antibacterial compound
The Research of the Key Technologies in Complex Local Navigation System Based on Binocular Stereovision

In this paper, binocular stereo vision platform, visual navigation for complex local range contains a lot of moving targets. The system includes a feature detection, projection reconstruction, motion analysis, clustering target four. Whereby the field of view may be obtained of the target group number, position, relative speed and direction of movement, and a comprehensive analysis of the nature of the target. The system uses real-world scenarios to test the performance of the system in most scenes to achieve the expected goal, improved method of the present system puts forward
Data Compressing in Nuclear Power Ultrasonic Nondestructive Detection

In nuclear power Ultrasonic nondestructive detection,because of the wide detection range and more probes,the amount of the acquireddata are reserved.Therefore,the design of data compression system plays an important role in ultrasonic nondestructive detection application in nuclear power.Methods of existing data compression are studied.Transferring the signal to be compressed from the one-dimensional space to two-dimensional space are presented.And then it carries out two-dimensional wavelet compression,realizes the two-dimensional signal and spatial signals compression.It analyses and compares with a one-dimensional compression of the signal.Experimental results prove that this scheme of the algorithm is effective.
Study on behavioral impedance for route planning techniques from the pedestrian s perspective: Part II - Mathematical approach

The theoretical foundations of the behavioral impedance domain are based on (1) a meta-model composed of analytical and mathematical approaches and (2) a taxonomy on the constraints involved in the decision-making process of a pedestrian during the route selection. The goal of this technical report is to present the mathematical model of the behavioral impedance domain. The partial least squares approach has been used to validate the meta-model analytical approach and develop the proposed mathematical model. This study contributes a mathematical model towards the implementation of behavioral impedance domain in geographic information systems for transportation through a constraint management module.
Photon State Tomography for Two-Mode Correlated Itinerant Microwave Fields

Continuous variable entanglement between two modes of a radiation field is usually studied at optical frequencies. As an important step towards the observation of entanglement between propagating microwave photons we demonstrate the experimental state reconstruction of two field modes in the microwave domain. In particular, we generate two-mode correlated states with a Josephson parametric amplifier and detect all four quadrature components simultaneously in a two-channel heterodyne setup using amplitude detectors. Analyzing two-dimensional phase space histograms for all possible pairs of quadratures allows us to determine the full covariance matrix and reconstruct the four-dimensional Wigner function. We demonstrate strong correlations between the quadrature amplitude noise in the two modes. Under ideal conditions two-mode squeezing below the standard quantum limit should be observable in future experiments.
A Privacy-Preserving Localization Service for Assisted Living Facilities

In this paper, we propose a novel localization service to monitor the position of residents in assisted living facilities. The service supports a configurable balancing between precision and privacy, in such a way that the right of the residents to move freely in the environment in which they live without being tracked is preserved. However, in case of need, they can always be quickly localized. To do this, we implement, on top of an RFID-based architecture, a probabilistic model guaranteeing that the probability of identifying a person in a given (sensitive) place is at most <inline-formula><tex-math notation="LaTeX">$k^{-1}$</tex-math><alternatives><mml:math><mml:msup><mml:mi>k</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math><inline-graphic xlink:href="buccafurri-ieq1-2646363.gif"/></alternatives></inline-formula>, where <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="buccafurri-ieq2-2646363.gif"/></alternatives></inline-formula> represents the required privacy level. This is obtained by ensuring that the EPC sent by RFID tags is not an identifier, but is equal to that of at least other <inline-formula><tex-math notation="LaTeX">$k-1$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>k</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="buccafurri-ieq3-2646363.gif"/></alternatives></inline-formula> people, each afferent to a different reader. We show that our method reaches the goal, resisting also attacks aimed at breaking privacy on the basis of humans’ movement models. Importantly, privacy is guaranteed against both misuse of the administrator and client-side eavesdropping attacks.
Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy

We propose a novel exponentially-modified Gaussian (EMG) mixture residual model. The EMG mixture is well suited to model residuals that are contaminated by a distribution with positive support. This is in contrast to commonly used robust residual models, like the Huber loss or $\ell_1$, which assume a symmetric contaminating distribution and are otherwise asymptotically biased. We propose an expectation-maximization algorithm to optimize an arbitrary model with respect to the EMG mixture. We apply the approach to linear regression and probabilistic matrix factorization (PMF). We compare against other residual models, including quantile regression. Our numerical experiments demonstrate the strengths of the EMG mixture on both tasks. The PMF model arises from considering spectroscopic data. In particular, we demonstrate the effectiveness of PMF in conjunction with the EMG mixture model on synthetic data and two real-world applications: X-ray diffraction and Raman spectroscopy. We show how our approach is effective in inferring background signals and systematic errors in data arising from these experimental settings, dramatically outperforming existing approaches and revealing the data's physically meaningful components.