Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion analysis for human-robot interaction

This paper is to present vision based motion analysis for human-robot interaction, which analyzes camera motion and human motion. Motion of camera is compensated by comparing edge features among consecutive image frames. Candidate regions of human motion are found by differencing between transformed tth image and t-1th image. Human motion is finally decided by image features and motion analysis. Gesture recognition module detects moving hand by motion analysis and skin color information obtained from face detection. The variation of hand location and the meaning gesture region are detected. We have experimented detection of moving object and gesture recognition with an active camera, which is pan/tilt/zoom and single camera that is mounted on mobile robot. Performance evaluation of gesture recognition has experimented using ETRI database and an encouraging recognition rate of 84% has been obtained.
From Attitudes to Actions: Predictors of Lion Killing by Maasai Warriors

Despite legal protection, deliberate killing by local people is one of the major threats to the conservation of lions and other large carnivores in Africa. Addressing this problem poses particular challenges, mainly because it is difficult to uncover illicit behavior. This article examined two groups of Maasai warriors: individuals who have killed African lions (Panthera leo) and those who have not. We conducted interviews to explore the relationship between attitudes, intentions and known lion killing behavior. Factor analysis and logistic regression revealed that lion killing was mainly determined by: (a) general attitudes toward lions, (b) engagement in traditional customs, (c) lion killing intentions to defend property, and (d) socio-cultural killing intentions. Our results indicated that general attitudes toward lions were the strongest predictor of lion killing behavior. Influencing attitudes to encourage pro-conservation behavior may help reduce killing.
A lightweight approach to 6-DOF plane-based egomotion estimation using inverse depth

Egomotion estimation is a fundamental building block for self-localisation and SLAM, especially when an accurate map is not available to the robot. This paper presents a real time plane-based approach to estimate the 6 degrees of freedom (DOF) pose of a moving Microsoft Kinect. An inverse depth formulation is used to robustly t multiple planes in the environment, which are then used to provide an egomotion estimate. Experiments presented demonstrate the algorithm’s accuracy, repeatability and ability to handle dierent motions and scene compositions. Despite using full resolution Kinect depth images, our approach runs at 10-13 frames per second.
Learning from Analyzing Linguistically Diverse Students’ Work: A Contribution of Preservice Teacher Inquiry

Abstract One task of Feiman-Nemser’s teacher learning model—develop tools and dispositions to study teaching—frames how we organized learning opportunities during teacher preparation. We explored how and to what degree preservice teachers used teacher inquiry to analyze linguistically diverse students’ work through an asset-based lens, beyond deficit perspectives, attending to student learning that was present. Preservice teachers reflected on practice and varied in how they integrated knowledge of students and linguistic diversity in inquiry.
" Efficient Secure Two-party Protocols "

This book provides a rigorous introduction to a smaller example of general secure multiparty computation (SMC), namely the case of two-party protocols. The approach is structured somewhat top-down: the authors first explain notions of security and security definitions for their chosen scenario, namely that of two-party protocols, with a static adversary, in the stand-alone model; then they look closer into a generic way of constructing SMC for any functionality (based on garbled circuits), explaining how the construction must be altered in order to provide for stronger adversaries; and finally they look at some concrete types of protocols, such as Sigma protocols, a limited type of oblivious transfer, and private list searching.
Persepsi Petugas Kesehatan Terhadap Peran Rekam Medis Elektronik Sebagai Pendukung Manajemen Pelayanan Pasien Di Rumah Sakit Panti Rapih

Latar Belakang: . Institute of Medicine merekomendasikan rekam medis elektronik (RME) sebagai pendukung manajemen pelayanan kesehatan pasien. Namun adopsi rekam medis elektronik saat ini hanya mencapai rata-rata pada 50% yang artinya rekam medis elektronik tidak dimanfaatkan secara maksimal fungsi dan fiturnya hanya untuk kebutuhan administrasi dan finansial rumah sakit. Memahami pandangan petugas kesehatan mengenai RME berpengaruh penting pada kesuksesan implementasi. Metode: Penelitian ini menggunakan desain studi kasus deskriptif dengan lokasi rumah sakit Panti Rapih Yogyakarta. Penelitian dilakukan dengan metode wawancara mendalam, observasi serta penyebaran kuesioner. Hasil: Masih terdapat masalah pada tingkat input dan proses dimana input data rekam medis yang lengkap masih sulit dan pada proses masih terdapat error yang mengganggu pelayanan. Berdasarkan kerangka UTAUT, masalah ini termasuk kategori kondisi fasilitas. Aspek ini memiliki korelasi yang kuat terhadap persepsi penggunaan (r= 0.78; p -value = 0.001). Persepsi penggunaan ini memiliki korelasi dengan persepsi kebermanfaatan (r=0.459 ;p-value= 0.047). Setelah itu, persepsi kebermanfaatan yang mempengaruhi perilaku penggunaan atau penerimaan (r= 0.569; p -value = 0.000) sehingga hubungan ini membentuk suatu alur. Kesimpulan: Untuk meningkatkan adopsi RME secara penuh aspek perilaku penggunaan atau penerimaan harus ditingkatkan. Aspek ini ditingkatkan dengan memperbaiki alur faktor yang mempengaruhinya
Virtual Viewing Time: The Relationship between Presence and Sexual Interest in Androphilic and Gynephilic Men

Virtual Reality (VR) has successfully been used in the research of human behavior for more than twenty years. The main advantage of VR is its capability to induce a high sense of presence. This results in emotions and behavior which are very close to those shown in real situations. In the context of sex research, only a few studies have used high-immersive VR so far. The ones that did can be found mostly in the field of forensic psychology. Nevertheless, the relationship between presence and sexual interest still remains unclear. The present study is the first to examine the advantages of high-immersive VR in comparison to a conventional standard desktop system regarding their capability to measure sexual interest. 25 gynephilic and 20 androphilic healthy men underwent three experimental conditions, which differed in their ability to induce a sense of presence. In each condition, participants were asked to rate ten male and ten female virtual human characters regarding their sexual attractiveness. Without their knowledge, the subjects’ viewing time was assessed throughout the rating. Subjects were then asked to rate the sense of presence they had experienced as well as their perceived realism of the characters. Results suggested that stereoscopic viewing can significantly enhance the subjective sexual attractiveness of sexually relevant characters. Furthermore, in all three conditions participants looked significantly longer at sexually relevant virtual characters than at sexually non-relevant ones. The high immersion condition provided the best discriminant validity. From a statistical point of view, however, the sense of presence had no significant influence on the discriminant validity of the viewing time task. The study showed that high-immersive virtual environments enhance realism ratings as well as ratings of sexual attractiveness of three-dimensional human stimuli in comparison to standard desktop systems. Results also show that viewing time seems to be influenced neither by sexual attractiveness nor by realism of stimuli. This indicates how important task specific mechanisms of the viewing time effect are.
Motion control design of the lower-limb mobile training robot

This paper aims at the development of the motion control design for a lower-limb mobile training robot that can provide adequate motion functions such as the passive and resistive motions of multiple joints for increasing training performances and for shortening training programs. In this paper, the motion control design includes the design of motion command generator and the design of motion control laws. A parametric curve interpolation algorithm is developed in the design of motion command generator to generate motion commands for the mobile training robot, and the kinematics and force-driven control of two-wheeled mobile robots are used to design the motion control laws. Moreover, by using the developed motion control design, three operation modes: continuous passive motion (CPM) mode, continuous active motion (CAM) mode, and hybrid motion (HM) mode, are designed for the applications of different training programs. Several tests are applied to evaluate the execution performances of the mobile training robot with the developed motion control design, and the experimental results indicate that the training robot is feasible for the applications of lower-limb training and rehabilitation.
CentroidM: a centroid-based localization algorithm for mobile sensor networks

In this paper, we present an adaptation of the well-known, range-free Centroid localization algorithm to deal with node mobility. This algorithm, which we call CentroidM, has the Centroid method as a stand. Positive features of the Centroid algorithm were kept while their limitations due to the dynamic characteristics of the network movement were mitigated. We consider a topology where a fraction of the nodes, called anchors, are static and are aware of their positions, while the remaining nodes are mobile. The proposed method splits the original sampling period of the Centroid algorithm into temporal windows in order to maintain a record of past information during movement. The selection of the anchor nodes is based on the received data within these temporal windows, allowing for the weighing of the anchors' coordinates. The method proved to increase the accuracy of the Centroid algorithm in static and mobile networks. The simulations were conducted under noisy environments and random mobility. Comparisons with the original algorithm show that our proposal achieves error reductions in the localization estimations up to 42% in the presence of movement and more than 30% for a static topology, leading to a significantly more accurate range-free localization process. Besides the concern regarding the accuracy of the method, the power consumption of the algorithm was addressed too. These benefits have increased 2.76 times the time spent by the CentroidM to run a localization process. However, simulation results showed it is possible to remove such overhead and still keep the achieved estimation gains near 10%.
Interactive subsurface scattering for translucent meshes

We propose a simple lighting model to incorporate subsurface scattering effects within the local illumination framework. Subsurface scattering is relatively local due to its exponential falloff and has little effect on the appearance of neighboring objects. These observations have motivated us to approximate the BSSRDF model and to model subsurface scattering effects by using only local illumination. Our model is able to capture the most important features of subsurface scattering: reflection and transmission due to multiple scattering.In our approach we build the neighborhood information as a preprocess and modify the traditional local illumination model into a run-time two-stage process. In the first stage we compute the reflection and transmission of light on the surface. The second stage involves bleeding the scattering effects from a vertex's neighborhood to produce the final result. We then show how to merge the run-time two-stage process into a run-time single-stage process using precomputed integral. The complexity of our run-time algorithm is O(N), where N is the number of vertices. Using this approach, we achieve interactive frame rates with about one to two orders of magnitude speedup compared with the state-of-the-art methods.
Correlation learning rule in floating-gate pFET synapses

We study the weight dynamics of the floating-gate pFET synapse and the effects of the pFET's gate and drain voltages on these dynamics. We show that we can derive a weight update rule such that the equilibrium weight value is proportional to the correlation between the gate and drain voltages. In particular, we want a rule of the form /spl tau/'/spl Delta/w/spl dot/=-/spl Delta/w+/spl eta/E[xy], where x is the signal on the gate terminal and y is the signal on the drain terminal. We obtain this rule by making a linear approximation to the weight dynamics around a given equilibrium point. We develop this approximation by considering the basic functional form of the system dynamics and then examining the effects of the gate and drain voltages on the specifics of this form.
Path-delay fingerprinting for identification of recovered ICs

The counterfeiting of integrated circuits (ICs) has been on the rise over the past decade, impacting the security and reliability of electronic systems. Reports show that recovered ICs contribute to about 80% of all counterfeit ICs in the market today. Such ICs are recovered from scrapped boards of used devices. Identification of such counterfeit ICs is a great challenge since these ICs have an identical appearance, functionality, and package as fresh ICs. In this paper, a novel path-delay fingerprinting technique is proposed to distinguish recovered ICs from fresh ICs. Due to degradation in the field, the path delay distribution of recovered ICs will become different from that found in fresh ICs. Statistical data analysis can effectively separate the impact of process variations from aging effects on path delay. Simulation results of benchmark circuits using 45 nm technology demonstrate the efficiency of this technique for recovered IC identification.
Variational Dirichlet Process Mixtures by Truncating Responsibilities

1 Variational Dirichlet Process mixtures Assume two infinite sets φ = {φ1, φ2, . } and v = {v1, v2, . , } of component parameter vectors and beta distributed random variables. Each φk is independently drawn from the prior pφ(φk|λ) with hyperparameter λ and each vk is independently drawn from B(vk|1, α) with hyperparameter α. Given these sets a Dirichlet Process (DP) mixture model is written as a mixture with infinite number of components
The effect of size scale parameters on the structural behavior of carbon nanotube based nano-actuator

In this work, the structural response of a carbon nanotube based nanoactuator under a parallel-plates electrostatic actuation is investigated assuming a strain gradient theory. The sixth-order partial differential equation governing the mode shapes and natural frequencies of beam using Euler-Bernoulli and strain gradient theories are derived. A Galerkin decomposition technique is utilized to convert the partial differential equation to ordinary differential equations representing the system mode shapes. The proposed approach is verified by comparing it to previously published works. The main advantage of the proposed technique based on the Galerkin method is its simplicity and also its low computational cost in analyzing the response of a carbon nanotube based actuator under the effect of initial curvature, size-dependent parameters, and any actuating loads. Additionally, the influences of the axial forces that may arise from any thermal effects were taken into consideration in the derived model. The results obtained based on strain gradient theory, are compared with the classical continuum theory. It is shown that the strain gradient theory leads to higher frequency in comparison with the classical one.
Faster than Nyquist-an enabler for achieving maximum spectral efficiency in coexistence scenarios?

In the context of spectrum sharing, a loss in spectral efficiency is incurred due to required guard bands needed for a desired co-channel interference level between systems. Our main interest is to show whether FTN signaling can recover the loss of spectral efficiency (SE) due to guard bands by adjusting the symbol duration and tolerating ISI in practical coexistence scenarios. In this paper, the SE of FTN signaling is investigated taking into account a practical multi-access channel, where a single-carrier system based on Nyquist or FTN signaling shares spectrum with a multi-carrier system. A single-user based on OQAM/OFDM system is considered as reference system. Simulation results show that by choosing an appropriate symbol duration, FTN signaling can recover the loss of SE at high SNRs. Furthermore, in coexistence scenarios with small guard bands, using FTN the SE curve is very close to that of the single-user reference system.
A Fuzzy-Based Approach for Partner Selection in Multi-Agent Systems

Traditional negotiation approaches pay intensive attention to decision making models in order to reach the optimal agreements, while placing insufficient efforts on the problem of partner selection. In this paper, a fuzzy-based approach for partner selection in multi-agent systems is proposed. By employing both the fuzzy logic and the extended dual concern model, agents can adapt their individual behaviors for partner selection in negotiation. The proposed approach has three merits, which are: (1) both the agent's own benefit and its potential partners' benefits are considered for partner selection in negotiation; (2) by employing the extended dual concern model, agents' attitudes to its potential partners are considered for partner selection in negotiation; and (3) by employing the fuzzy logic, the proposed partner selection approach can be applied in open and dynamic environments easily and flexibly, and the selection results are much more accurate and reasonable.
Mitigate I/O access pattern divergence with heterogeneous architecture in HDFS

Hadoop has become the de-facto big data processing framework. Since the success of Hadoop in large data set processing, more and more companies and organizations tend to build their analysis logics into Hadoop stack and share across different develop teams for cost-effective. Hadoop now undertakes not only the original batch computation but also lowlatency online queries. However the Hard Disk Drive (HDD) used in Hadoop storage system performs poorly when facing random request and disk contention. The isomorphic HDD storage layer in HDFS encounters the I/O access pattern divergence inevitably. To this end, a promising trend in storage system is to utilize hybrid and heterogeneous devices - Solid State Disks (SSD), which can help achieve very high I/O rates at acceptable cost. However, previous works mostly focus on separated data flow phases thus leading to poor applicability in different application scenes. In this paper, we present a novel heterogeneous architecture which can separate the I/O access into sequential pattern and random pattern. We mitigate the divergence of I/O access through heterogeneous storage system, i.e., HDD serves the sequential I/O request while SSD provides low-latency random file access. We evaluate our system using an actual implementation on a medium-sized cluster consisting of HDDs and different numbers of SSDs with workloads from a leading search engine company. Experiments show that our system outperforms the original system 17% in disk utilization and reduces 12% in job duration time in average.
Mean Shift and Kalman Filter based Human Face Tracking

Real-time human detection and tracking is a vast, challenging and important field of research. It has wide range of applications in human recognition, human computer interaction (HCI), video surveillance etc. The research for biometric authentication of a person has reached far but real-time tracking of human beings has not gained much importance. Keeping continuous track of person will allow identifying person at any time and monitoring the activities of a person. Face is vital parts of human being represent most important information. Face detection is done using skin color based methods. YCbCrcolor model is used to detect skin regions. Mean shift algorithm combined with Kalman filter is used for tracking. Mean shift and Kalman filter are effective algorithms for tracking.
The Diffusion of Protestantism in Northern Europe: Historical Embeddedness and Complex Contagions in the Adoption of the Reformation

In this article we use network theory to explain the adoption of the Protestant Reformation. We use new historical data on the connections between Hansa towns that allow us to conduct the first social network study of the Protestant Reformation. Based on an analysis of cities in central and Western Europe between 1517 and 1530, we find evidence for diffusion through both simple and complex contagion. Our operationalization of network data based on medieval Hansa Diets points to the complex association between tie weights (i.e., the strength of ties) and numbers of ties in network diffusion. Using optimal tuning parameters for simple adoption models, we show that a combination of strong ties and weak ties fostered Protestant adoption in northern cities.
Concept Discovery for Pathology Reports using an N-gram Model

A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. One of the leading systems in the cancer community is the Cancer Text Information Extraction System (caTIES), which was developed with caBIG-compliant data structures. caTIES embedded two key components for extracting data: MMTx and GATE. In this paper, an n-gram based framework is proven to be capable of discovering concepts from text reports. MetaMap is used to map medical terms to the National Cancer Institute (NCI) Metathesaurus and the Unified Medical Language System (UMLS) Metathesaurus for verifying legitimate medical data. The final concepts from our framework and caTIES are weighted based on our scoring model. The scores show that, on average, our framework scores higher than caTIES on 848 (36.9%) of reports. Furthermore, 1388 (60.5%) of reports have similar performances on both systems.
The socioeconomic impact of Arsenic poisoning in Bangladesh

The purpose of this paper is to propose a methodology to analyze the health effects, how people cope with the socioeconomic consequences of the disease and to predict the beneficial effects of various alternative mitigation methods and recommends governmental measures for prevention of Arsenic poisoning. This research has been evaluated by the Bangladeshi Health Care system for its ability to recognize, isolate, report and control cases of Arsenic. The statistics is provided through the latest Internet publications, literature on global and regional information on environment, and using the database of Bangladesh Demographic and Health Survey 2004. This research attempted to analyze how other international agencies are trying to prevent Arsenic in their countries, where the people are affected or infected by Arsenic. As preventive measures, surface water treatment including drinking or taking water from the pond, various educational program, support of Government and NGOs, using media materials and Pan American Center for Sanitary Engineering and Environmental Sciences (CEPIS) in Peru, called ALUFLOC and Danida and Water Aid developed technologies to remove Arsenic were mentioned.