Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Impacts of In-Home Virtual Activities on Daily Activity and Travel Behaviour : An Analysis Using Cairo Activity and Telecommunication Diary Data 2006

The boom in telecommunications technologies is expected to have great impact on the lifestyles of the individuals and their households and also on transportation system. Recent advances in information and communication technologies (ICTs) make it possible to conduct activities virtually, thus obviating the need for physical travel, at least for some types of activities. Further, ICT use may contribute towards reducing urban congestion and air-quality problems (by replacing travel with virtual activities); on the other hand they may also generate significant additional and induced travel due to increased connectivity and access to resources. Thus empirical insights on how the growing ICT use affects travel patterns and vice-versa have important application for planning, travel demand forecasting, and urban environment. So far, however, in transport research the effects of ICTs have mainly been analyzed by focusing on e-activity, especially e-shopping and telecommunicating. Although these studies allow essential insights, there is still no complete picture that shows the interrelationships between ICT use and individual activity and travel behavior. Further, to our knowledge, little attention has been directed to the understanding of how ICT affect activity participation and travel patterns of individuals in Egypt. The objective of this study is to investigate the effects of ICT on household members‟ daily activity-travel patterns using empirical activity and telecommunication diary survey conducted in Greater Cairo Region, in Egypt. In this paper, activity participation and travel behavior are compared between two population groups, those currently with Internet access at home and those without Internet access at home. Structural equation models (SEMs) are developed to determine the structural relationship between virtual in-home activity participation, out-of-home activity participation, Internet use patterns, and observed travel dimensions. The information analyzed includes personal and household socio-demographic, ICT ownership and familiarity, and the role of constraints on time, and vehicle availability on activity patterns among household members. With this approach significant relationships were found among socio-demographics, social roles, technological familiarity, activity participation and travel behavior. Furthermore, the results show that in-home virtual activity participation has both a substitution and complementary impacts on out-of-home activity and travel patterns. These results have Exploring the Impacts of In-Home Virtual Activities on Daily Activity and Travel Behaviour: An Analysis Using Cairo Activity and Telecommunication Diary Data 2006. Ahmed Ibrahem Mosa, Nobuaki Ohmori, and Noboru Harata 12 th WCTR, July 11-15, 2010 – Lisbon, Portugal 2 important implication for activity-travel demand estimation and forecasting, given the growing adoption and use of ICT among various segments of the population.
Real-time 3D Stereo Mapping in Complex Dynamic Environments !

This paper describes a real-time system for temporally accumulating shape and appearance statistics of the environment in a 3D voxel map using dense stereo camera range data in cluttered, dynamic scenes. Computationally efficient spatio-temporal statistics and viewing constraints are used to produce a 3D map that is robust to noise and outliers, without the need for explicitly tracking objects or computing optical or voxel flow. Accumulated voxel statistics are used to perform tasks such as terrain classification, object detection and tracking, or pedestrian detection. The system has been fielded extensively on a variety of platforms for a variety of applications, including on the Boston Dynamics Legged Squad Support System (LS3) vehicle for providing its day/night nearfield terrain mapping capability.
Extended Kalman filter design using bearing and time-to-go measurement for a homing missile guidance

In this paper, we construct a filter dynamics using bearing angle and time-to-go measurements obtained from sequential image frames of a passive seeker. Typically, estimation filter with bearing-only measurement is used for missile guidance. However, seeker images include much more information such as target size and its expansion rate. Time-to-go measurements can be calculated by target size in image and its expansion rate. Therefore, we construct a guidance filter with additional timeto-go information. Time-to-go measurements are calculated by several image process. The process are illustrated in detail. As shown in the numerical results, the state estimation errors are reduced by using time-to-go measurement. The performances of filters using bearing-only measurement and using bearing and time-to-go measurement are compared by Monte-Carlo simulation.
onded-particle model calibration using response surface ethodology

The bonded-particle model (BPM) is commonly used in numerical analysis of the mechanical behavior of rock samples. Constructing a BPM model requires specification of a number of microstructural parameters, including the parallel-bond tensile strength, parallel-bond cohesion strength, parallel-bond effective modulus, parallel-bond friction angle, and parallel-bond stiffness ratio. These parameters cannot be easily measured in the laboratory or directly related to either measurable or physical material parameters. Hence, a calibration process is required to choose the values to be used in simulations of physical systems. In this study, response surface methodology along with the central composite design approach is used to calibrate BPMs. The sensitivities of the microparameters related to the uniaxial compressive strength (UCS) and elasticity modulus (i.e., the macroscopic responses of the models) are thoroughly scrutinized. Numerical simulations are performed to carefully assess the performance of the model. It is found that the elasticity modulus is highly correlated with the parallel-bond effective modulus. In addition, the parallelbond tensile and cohesion strengths are the two most significant microparameters with a considerable effect on the UCS. The predicted values determined by the proposed approach are in good agreement with the observed values, which verifies the applicability of the proposed method. © 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
A Structuration View of E-negotiation System Use

E-negotiation systems (ENSs) have been designed to support online negotiations. Previous studies on ENSs focused on the users’ perceptions of the various system features and the impact of these features on the negotiation performance. Questions regarding these systems usefulness and the features’ usefulness remain insufficiently addressed. Most studies are based on experiments providing data for variance models with a very limited use of negotiation context. The context can be explicitly used in Giddens’s structuration theory which also allows for an approach that is complementary to variance modelling. This work aims to employ structuration in the investigation of ENS use and its effects on negotiators’ perception, behaviour and performance. E-negotiation is conceptualized as a structuration process that takes shape through the social construction of an e-negotiation protocol. A twolevel conceptual model is proposed together with a set of propositions explaining the negotiation structure effects, the system effects, the co-adaptation effects, and the time/space effects on negotiator’s perception, behaviour and performance.
THE ADSORBER COMPONENT ADDITION IN CHEMCAD SOFTWARE PALETTE FOR HELIUM PURIFICATION MODELLING AND SIMULATION

PENAMBAHAN KOMPONEN ADSORBER PADA PALETTE SOFTWARE CHEMCAD UNTUK PEMODELAN DAN SIMULASI PEMURNIAN HELIUM. Sistem pemurnian helium (SPH) adalah sistem yang sangat penting dalam reaktor RDE. Sistem ini berfungsi menghilangkan pengotor pada pendinginnya berbentuk partikel debu dan gas-gas. Pengotor tersebut antara lain debu karbon, N2, O2, H2, O2, CH4, CO, dan CO2. Salah satu komponen yang dibutuhkan pada SPH adalah komponen adsorber. Pada palette software ChemCAD, komponen adsorber belum tersedia, sehingga perlu ditambahkan. Penambahan dilakukan melalui fasiltas icon Excel pada palettenya dengan membuat coding proses terlebih dahulu menggunakan program Visual Basic. Tujuan penambahan komponen adsorber pada software ChemCAD adalah agar software ini dapat digunakan untuk memodelkan dan mesimulasikan proses pemurnian helium pada pendingin primer RDE. Metode yang digunakan pada pemodelan adsorber adalah prinsip penyerapan dengan metoda Langmuir. Setelah coding untuk komponen adsorber selesai dibuat dalam Visual Basic kemudian diintegrasikan ke software ChemCAD, dan digunakan untuk memodelkan proses penyerapan gas pengotor. Pada penelitian ini dilakukan simulasi untuk penyerapan pengotor oksigen pada kondisi kriogenik. Proses ini merupakan tahapan terakhir pada SPH RDE. Validasi hasil penambahan komponen adsorber pada ChemCAD dilakukan dengan membandingkan hasil simulasi untuk kasus yang sama dengan software SuperPro Designer. Berdasarkan hasil kedua simulasi diketahui bahwa perbedaaan rata-rata hasil running ChemCAD dan SuperPro Designer tidak lebih dari 0,02% (0,0001), sehingga komponen adsorber yang ditambahkan pada software ChemCAD valid dan dapat digunakan untuk pemodelan dan mensimulasikan sistem pemurnian helium pada reaktor RDE.
A Proposed Algorithms to Design Support Multimodal biometric System

This paper is an attempt to address the biometric security issue and improve the system accuracy through introducing a design for multimodal biometric verification system using multiple traits (Iris, fingerprint) and adding another phase called liveness detection to the phases of multimodal system the purpose of this phase is to protect the multimodal biometric systems against spoofing attacks. The system is tested in two levels, unimodal level and multimodal level (fusion level). in unimodal level two tests have been performed, one for iris verification phase performed on two types of database MMU DB (Multi Media University database) for 180 samples and CASIA DB (Chinese Academy of Sciences database) for 90 samples. and gave accuracy (99.44%) with FAR (False Acceptance Rate) of (0.0277) and FRR (False Reject Rate) (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB, and other for fingerprint verification phase performed on database collected from two types of database for 60 samples and gives accuracy of 95% with FAR of 0.1% and FRR of 0.05%. In multimodal level the system is tested on database composed of 60 samples for iris images and 60 samples for fingerprint images and gives an overall accuracy of 100% with FRR of 0%, and FAR of 0.0166%.
Regional optimization of air pollution in Greece via input-output analysis

This paper explores the use of a multi-region input-output based model for optimizing production on a per-sector basis, while taking into account regional environmental constraints on air pollution and economic impact. The basic model, informed by recently published empirical and environmental data for Greece (which is partitioned into five regions), is used to accomplish two things. First, we determine the regional economic impact of reducing each of a set of major air pollutants (including particulates, and gasses that contribute to global warming and acidification). This is done by solving an optimization problem where we ask to maximize regional GVP subject to constraints on energy use, final demand, and air pollution. Second, we explore the effects on the national and regional economies from localizing environmental policy to target the pollutant deemed most problematic in each region. Our analysis considers two pollution reduction scenarios which entail a 9% and 4.5% reduction, respectively, in the volume of each region’s “priority” pollutant. Depending on the pollutant under consideration, our analysis suggests that significant reductions may be possible with minimal effect on the regional or national gross value of production. Moreover, depending on the level of reductions sought, regulating a single pollutant may be sufficient to induce reductions in other pollutants as well, leading to more concise environmental policies. More specifically, at the aggregate level, the most intense fluctuations in both economic and environmental variables are observed under the more restrictive (9%) scenario. At the sectoral level, under both scenarios, secondary production sectors are subject to the most significant reductions in all regions, in contrast to the tertiary production sectors which are favoured the most by the optimal solution. JEL codes: Q51, C67, Q53.
Wage Discrimination in Germany Between Turkish Immigrants and German Natives : An Empirical Analysis of Labor Market Outcomes of Turkish Immigrants

Racial tensions still persist today in Germany, despite some progress over the years. Turkish immigrants have been coming to Germany, seeking work and opportunity, since the 1960s. At this time, Turkey and West Germany had signed a labor recruitment agreement in efforts to diminish the incredibly large demand for workers after the Berlin Wall fell. These “guest workers” were hired to complete industrial jobs, and therefore are considered unskilled and uneducated in the German labor market. The promise given by the German government was that these Turkish guest workers would boost national tax revenues and increase the country’s productivity levels. However, for many years after, Germans believed that these guest workers would return home after their employment finished (Spiegel, 2010). This was not the case.
AFTERSHOCK COLLAPSE VULNERABILITY ASSESSMENT OF AN OLDER REINFORCED CONCRETE FRAME

Buildings located in seismically-active regions may experience ground shaking from multiple earthquakes, such as mainshock-aftershock sequences. In mainshock-aftershock sequences, the seismic events generally occur in close succession, leaving insufficient time for repair or retrofit between the events. In such cases, seismic performance of a building during an aftershock may depend on the level of damage sustained by the building in mainshock. This study evaluates the aftershock collapse vulnerability of a non-ductile reinforced concrete moment frame building designed according to the 1967 Uniform Building Code. This type of reinforced concrete moment frames is relatively weak, and susceptible to shear and axial column failure (among other failure modes) due to inadequate reinforcement detailing and lack of capacity design requirements. Here, the reinforced concrete frame is modeled in two dimensions with zero-length springs on top of columns capable of capturing shear and axial failure modes. Incremental dynamic analysis on nonlinear analytical building models is used to generate damage and collapse fragility curves for intact and mainshock damaged buildings. The results show that the structure’s ability to withstand collapse and further damage are decreased as the extent of damage after the mainshock increases. This trend is similar to what has been observed for ductile RC frames. However, a modern ductile RC frame can undergo higher levels of damage before its aftershock collapse capacity is seriously compromised. In addition, the drop in collapse capacity, as a function of mainshock damage, is more precipitous for the non-ductile RC frame building.
An Interpretation of Vision-based Control for Rigid Body Motion : A Geometric Framework

This paper investigates the rigid body motion (involving both translation and rotation) control problem of vision-based robotic systems. Visual feedback systems of the eye-in-hand con guration typically use three coordinate frames which consist of a world frame, a target object frame and a camera (end-e ector) frame. In this control strategy, one of the control objectives is to track the moving target object in a three-dimensional workspace by image information. Hence the model of the relative rigid body transformation, which represents the position and orientation of the target object frame relative to the camera frame, can be described by the nonlinear systems on the group of rigid motions, which shall be denoted as SE(3). At rst, we consider a model of the relative rigid body motion based on a geometric framework [1], [2]. However, the relative rigid body motion can not be measured directly in visual feedback systems. Hence, we propose a nonlinear observer which will estimate the relative rigid body motion from image information. The estimation error and error model between the relative rigid body motion and the estimated relative rigid body motion can be derived based on a geometry approach. An interpretation of relation between the model of the estimation error and an expression of velocity can be provided thanks to this approach. The control error and error model between the estimated relative rigid body motion and the reference of the relative rigid body motion should be de ned to track the moving target object. A model of the visual feedback system consists of the control error model and the estimation one. For this system, we lead a structural passivity-like property. Moreover, stability and L2gain performance analysis are discussed based on passivity. The main contribution of this paper is that the interpretation of our proposed strategy [3] has been given based on a geometric framework.
OVER-REPORTING VS . OVERREACTING : COMMUTERS ’ PERCEPTIONS OF TRAVEL TIMES August 2014

We asked participants of a large-scale, real-life peak avoidance experiment to provide estimates of their average in-vehicle travel time for their morning commute. Comparing these reported travel times to the corresponding actual travel times, we find that travel times are overstated by a factor of 1.5 on average. We show that driverand link-specific characteristics partially explain the overstating. Using stated and revealed preference data, we investigate whether the driverspecific reporting errors are consistent with the drivers’ scheduling behavior in reality as well as in hypothetical choice experiments. For neither case, we find robust evidence that drivers behave as if they misperceived travel times to a similar extent as they misreported them, implying that reported travel times do neither represent actual nor perceived travel times truthfully. The results presented in this paper are thus a strong caveat against the uncritical use of reported travel time data in transport research and policy.
FULL FIELD STRAIN CHARACTERISTICS OF COMPOSITE LAMINATE WITH IMPACT DAMAGE UNDER IN-PLANE LOAD

The full-field measurement becomes more and more popular in the structural experiment [1]. The composite laminate is susceptible to transverse impact which may dramatically reduce the structural strength. The impact usually produces the local damage, and full field measurement can show the local response variation. The delamination in composite laminate subjected to bending load can be detection with deflectometry technique [2,3]. Kim, etc.[4] used this technique to measure the local stiffness reduction. The delamination is much easier to detect if it is bulged under the external load. Maranon etc.[5] proposed a method for subsurface delamination identification. In a vacuum chamber, the out-of-plane displacement due to the negative pressure was measured with the digital speckle pattern interferometry. The identification procedure consists steps of edge detection, delamination estimation and characterization (i.e. the location size, orientation and depth). Before the failure of the laminate with delamination subjected to compressive load, the delamination buckling may occur in the delaminated region[6], which also brings the variation in the strain field. In this paper, the numerical study is firstly carried out on the surface strain characteristics of laminate with impact damage, including fiber breakage and delamination. Then the strain fields of the composite specimen subjected to the in-plane tensile and compressive are measured using digital image correlation (DIC) technique. The influence of DIC parameter on the damage detection is discussed. 2 Numerical Study
MOLECULAR AND PHYLOGENETIC IDENTIFICATION OF MARINE MICROALGAE INFERRED BY 18 S RDNA GENE

Microalgae are microscopic organisms that are usually identified based on the morphological features. However traditional classification are complicated by high levels of morphological plasticity and convergence that will lead to uncertain identification especially at the species level. Therefore, molecular marker is advantageous to distinguish and correctly identify microalgae at the lowest taxonomic level based on the genetic information and phylogenetic analyses. In the present study, we have characterized five strains of microalgae that were deposited in Borneo Marine Research Institute based on 18S rDNA gene sequences. The BLAST results of microalgae sequences showed high percentage similarities that revealed the species as Chaetoceros gracilis (99.77%), Thalassiosira weissflogii (99.70%), Nannochloropsis oceanica (100%) and Isochrysis sp. (99.97%). Combination of both classical and genetic approach is vital to clearly identify microalgae at generic and species levels.
Detecção de pessoas em um ambiente industrial utilizando imagens de profundidade e classificadores profundos

This paper describes the development of an industrial safety system that requires automatic human detection. Two solutions based on top-view depth images are presented. The first one is based on traditional learning techniques using feature extraction and a Support Vector Machine classifier. The second solution uses deep learning methods for classification. The performance analysis of both solutions revealed that the deep learning methods outperform traditional learning techniques on this task, at the cost of requiring a larger training set and increased computational cost. Keywords— Human detection, depth images, deep learning, convolutional networks, machine learning, computer vision.
Initial Mask Processor Open / Close Morphological Transform Closest Connected Component RGB Refinement Network Refined Masks Depth Seeding Network Foreground Center Directions Depth Initial Masks RGB

In order to function in unstructured environments, robots need the ability to recognize unseen novel objects. We take a step in this direction by tackling the problem of segmenting unseen object instances in tabletop environments. However, the type of large-scale real-world dataset required for this task typically does not exist for most robotic settings, which motivates the use of synthetic data. We propose a novel method that separately leverages synthetic RGB and synthetic depth for unseen object instance segmentation. Our method is comprised of two stages where the first stage operates only on depth to produce rough initial masks, and the second stage refines these masks with RGB. Surprisingly, our framework is able to learn from synthetic RGB-D data where the RGB is non-photorealistic. To train our method, we introduce a large-scale synthetic dataset of random objects on tabletops. We show that our method, trained on this dataset, can produce sharp and accurate masks, outperforming state-of-the-art methods on unseen object instance segmentation. We also show that our method can segment unseen objects for robot grasping. Code, models and video can be found at https://rse-lab.cs. washington.edu/projects/unseen-object-instance-segmentation/.