Miracle-dz/UniFAR-FTUs huggingface dataset:
Yalongjiang River Has Had an Important Role in the Dispersal and Divergence of Rosa soulieana in the Hengduan Mountains of China

The Hengduan Mountains are the core of the Sino-Himalayan Floristic Region. Rosa soulieana Crép. is an important wild rose species that is widely distributed in the Hengduan Mountains. To provide better future utilization of this wild rose, and also to add some possible proof of the effect of geomorphological and ecological characteristics of the Hengduan Mountains on the current spatial distribution and genetic diversity of local species, the genetic diversity and genetic structure of 556 individuals from 37 populations of R. soulieana were studied using fluorescent amplified fragment length polymorphisms (AFLPs). R. soulieana showed a moderately high level of genetic diversity and a high level of genetic differentiation at the species level. The total percentage of polymorphic loci, total heterozygosity (Ht), Shannon index (I), and heterozygosity value within populations (Hs) were 97.8%, 0.253, 0.339, and 0.139, respectively. More than half of the total genetic variation (54.0%) occurred within populations, and the overall gene differentiation coefficient (Gst) was 0.451. The genetic differentiation among populations was positively and significantly correlated with geographic distance. The neighbor-joining cluster and the Bayesian analysis divided all the populations and individuals into 3 groups, and did not support the morphology based intraspecific varieties. The results confirmed that the ancient R. soulieana of the third group survived in northwestern Yunnan and Yalongjiang valley and then moved upnorth along the valley. The spatial distribution of the other two groups was the result of allopatric divergence due to long period of adaptation to the different climatic conditions of its distribution at either side of the Yalongjiang River.
3D Hand pose modeling from uncalibrate monocular images

Hand pose modeling is one of the most challenging research areas in Computer Animation due to the difficulty of hand model, which consist of more than 20 degrees of freedom and require the construction of a large high-dimensional database of poses. In this paper, we propose a method of 3D hand pose modeling based on a new set of constraints and optimization framework to reduce the ambignity between 2D joint location and 3D hand poses. Our method does not need prior knowledge of the bone length and camera parameters. Furthermore, a large high-dimension database used for searching is not needed to be constructed. An experiment was performed on the real data set captured from a webcam. the results shows that the proposed set of constraints are sufficient to reconstruct the hand poses with desirable accuracy.
Licensed under Creative Commons Attribution Cc by Intrusion Detection Using Data Mining Approach

Intrusion Detection is one of intelligent application in which data mining technique can be used. This paper presents data mining approach in Intrusion detection. Intrusion detection is nothing but the detection of action that attempts to compromise the system security factors such as integrity, availability of a resource, confidentiality. Intrusion detection does not involve the Intrusion prevention functionality. This paper represents the approach for expert system doing data mining embedded with Intrusion Detection System. Complete information about intrusion mechanism is required to generate the appropriate decision. This paper discusses the frame work for the data mining based IDS and architecture of Data Mining based IDS.
A Systematic Approach to Environmental Priority Strategies in Product Development (EPS) Version 2000-General System Characteristics

The EPS default method 1 Foreword The present version of the EPS system has been developed within CPM (Centre for the environmental assessment of Products and Material systems) a joint research environment at Chalmers University of Technology with participation from industry. The report is describing the general principles and default methodology of the EPS system. The system principles and methodology is based on earlier versions of the EPS system, in particular the version 1996. The present version has been given the number 2000. In comparison with the 1996 version the basic principles are the same, but the description is more detailed and the ISO standard language is adopted. Acknowledgement The EPS system, as it is presented in this report, has taken its form through contributions from many individuals and organisations. It has been a privilege to further the achievements from the Swedish Product Ecology project and much valuable input have come from the co-authors of the EPS system report of that project (Ryding et.al. 1995). Summary This report describes the EPS default methodology and the main principles of the EPS system. The present version of the EPS method is an Compared to the 1996 version, the EPS system principles are the same. The EPS default method is essentially the same, but, since ISO standards on LCA now are available, it is described in ISO terms (ISO 14040 – 14043). In addition the description is more detailed, and the database updated and extended. To some degree this is in line with requirements put forth by ISO and to some degree this is due to experiences made in the use of the EPS system. Although the main principles are the same, the elaboration of the descriptions means a new development of the system. As the EPS system becomes more and more developed and spread, the identity of the system shifts from being an informal concept of its creators to be defined by its documentation. As in many complex systems conflicts often arise between different principles and requirements. The EPS system has an outspoken hierarchy among its principles and rules to help in these situations. This hierarchy is based on a top-down principle giving highest priority to the usefulness of the system. The other subordinate main principles and characteristics of the of the EPS system are (in hierarchical order): • The 'index' principle, requiring ready-made indices for materials and processes representing weighted and …
Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface Application

In this study, we determine the optimal feature-combination for classification of functional near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two-class brain-computer interface (BCI). Using a multi-channel continuous-wave imaging system, mental arithmetic signals are acquired from the prefrontal cortex of seven healthy subjects. After removing physiological noises, six oxygenated and deoxygenated hemoglobin (HbO and HbR) features—mean, slope, variance, peak, skewness and kurtosis—are calculated. All possible 2- and 3-feature combinations of the calculated features are then used to classify mental arithmetic vs. rest using linear discriminant analysis (LDA). It is found that the combinations containing mean and peak values yielded significantly higher (p < 0.05) classification accuracies for both HbO and HbR than did all of the other combinations, across all of the subjects. These results demonstrate the feasibility of achieving high classification accuracies using mean and peak values of HbO and HbR as features for classification of mental arithmetic vs. rest for a two-class BCI.
Task-oriented optimal grasping by multifingered robot hands

The problem of optimal grasping of an object by a multifingered robot hand is discussed. Using screw theory and elementary differential geometry, the concept of a grasp is axiomated and its stability characterized. Three quality measures for evaluating a grasp are then proposed. The last quality measure is task-oriented and needs the development of a procedure for modeling tasks as ellipsoids in the wrench space of the object. Numerical computations of these quality measures and the selection of an optimal grasp are addressed in detail. Several examples are given using these quality measures to show that they are consistent with measurements yielded by the authors' experiments on grasping. >
Differential Absorption Microwave Radar Measurements for Remote Sensing of Barometric Pressure

As coastal regions around the world continue to grow and develop, the threat to these communities from tropical cyclones also increases. The predicted sea level rise over the next decades will certainly add to these risks. Developed low-lying coastal regions are already of major concern to emergency management professionals. While hurricane forecasting is available, improved predictions of storm intensity and track are needed to allow the time to prepare and evacuate larger cities. The predictions and forecasts of the intensity and track of tropical storms by regional numerical weather models can be improved with the addition of large spatial coverage and frequent sampling of sea surface barometry. These data are critically needed for use in models.
Prokrastinasi akademik dikalangan mahasiswa program studi bimbingan dan konseling

Prokrastinasi akademik merupakan perilaku menunda-nunda mengerjakan ataupun menyelesaikan tugas-tugas akademik. Penelitian ini bertujuan memberikan gambaran mengenai prokrastinasi akademik yang dialami oleh mahasiswa. Penelitian ini merupakan jenis penelitian deskriptif dengan pendekatan kuantitatif. Penelitian ini menggunakan alat pengumpul data berupa skala prokrastinasi akademik. Subyek yang digunakan dalam penelitian ini adalah mahasiwa prodi BK sejumlah 229 mahasiswa yang di ambil dengan cara simple random sampling. Analisis data dalam penelitian ini menggunakan teknik persentase. Hasil yang diperoleh dalam penelitian ini menggambarkan kondisi prokrastinasi akademik mahasiswa pada kategori sangat tinggi sebesar 6%, kategori tinggi 81%, kategori sedang 13%, kategori rendah 0%. Prokrastinasi akademik yang dialami oleh mahasiswa tersebut terdiri dari beberapa aspek antara lain keyakinan akan kemampuan, ganggaun perhatian, faktor sosial, manajemen waktu, inisiatif, pribadi, dan kemalasan.AbstractAcademic procrastination is a procrastinating behavior of doing or completing academic tasks. This study aims to provide an overview of the academic procrastination experienced by students. This research is a descriptive research with quantitative approach. This study uses data collection tool in the form of academic procrastination scales. The subjects used in this study are students of guidance and counseling program of 229 students taken by simple random sampling. Data analysis in this research using percentage technique. The results obtained in this study describes the condition of student academic procrastination in very high category of 6%, high category 81%, medium category 13%, low category 0%. The academic procrastination experienced by the student consists of several aspects such as belief in ability, attention disturbance, social factors, time management, initiative, personal, and laziness.
Characteristics of Networks of Interventions: A Description of a Database of 186 Published Networks

Systematic reviews that employ network meta-analysis are undertaken and published with increasing frequency while related statistical methodology is evolving. Future statistical developments and evaluation of the existing methodologies could be motivated by the characteristics of the networks of interventions published so far in order to tackle real rather than theoretical problems. Based on the recently formed network meta-analysis literature we aim to provide an insight into the characteristics of networks in healthcare research. We searched PubMed until end of 2012 for meta-analyses that used any form of indirect comparison. We collected data from networks that compared at least four treatments regarding their structural characteristics as well as characteristics of their analysis. We then conducted a descriptive analysis of the various network characteristics. We included 186 networks of which 35 (19%) were star-shaped (treatments were compared to a common comparator but not between themselves). The median number of studies per network was 21 and the median number of treatments compared was 6. The majority (85%) of the non-star shaped networks included at least one multi-arm study. Synthesis of data was primarily done via network meta-analysis fitted within a Bayesian framework (113 (61%) networks). We were unable to identify the exact method used to perform indirect comparison in a sizeable number of networks (18 (9%)). In 32% of the networks the investigators employed appropriate statistical methods to evaluate the consistency assumption; this percentage is larger among recently published articles. Our descriptive analysis provides useful information about the characteristics of networks of interventions published the last 16 years and the methods for their analysis. Although the validity of network meta-analysis results highly depends on some basic assumptions, most authors did not report and evaluate them adequately. Reviewers and editors need to be aware of these assumptions and insist on their reporting and accuracy.
Navigation for the blind using a wireless sensor haptic glove

This paper presents a prototype indoor navigation system for the blind based on wireless sensor network coupled with a haptic feedback glove. The system uses Received Signal Strength Indicator (RSSI) to continuously triangulate the position of the Vision Impaired (VI) person. A number of most relevant destinations can be assigned to pushbuttons on a haptic glove. Upon receiving input from the user via a pushbutton indicating the desired destination a path is routed. To aid in traversing to the destination the individual wears the haptic feedback glove embedded with vibrational motors and an ultrasonic sensor to gauge distance of nearby objects.
Clinical Supervision Instrument Development for Junior High School Teacher Based on Android

The instruments currently used are still paper and pencil based. This development research aims to produce a clinical supervision instrument for android and junior high school teachers are valid and reliable. Data collection was done by interview and observation. Content validity was obtained through 4 expert judgments, analyzed using Aiken's V formula. The construct validity was analyzed by Exploratory Factor Analysis (EFA) and Intraclass Correlation Coefficient (ICC), and reliability with Alpha Cronbach with the help of IBM SPSS 24.0 software. The results showed that the validity value of all instruments in the preparation stage until the closing stage obtained a score> 0.5. The result of field test shows that there are some statement items that are in valid criteria with value of Factor Factor> 0, 5. Aspects with valid statement items include Preparation stages with 5 statements and Alpha Cronbach values ​​obtained at 0.640, Learning Activity stages with 23 statements and Alpha Cronbach values ​​obtained by 0.962, and Closing stages with 4 statements and Alpha Cronbach values ​​obtained at 0.680. Based on the results of the study, it was found that supervisors and teachers were very appreciative with the instrument of android based clinical supervision and the supervisor felt easier to conduct clinical supervision activities to the subject teachers. The benefits of this research are supervisors can use the instrument in carrying out clinical supervision with practical, easy and valid while for teachers can be used as a reference in preparing learning activities.
Using Geometric Constraints for Fisheye Camera Calibration

This paper presents a technique to linearly calibrate a fisheye camera using the fact that the distortion is in the radial direction (angle preservation on the X-Y plane). First, a linear equation based on this constraint is proposed for estimating intrinsic/extrinsic parameters. The skewness in the intrinsic parameters is assumed to be zero in this paper. Second, a pure rotation for the fisheye camera is applied to recover the depth of the principal plane. Last, distortion parameters are estimated based on least squares polynomial fitting. Our method provides a linear and closed-form solution. Besides, all the parameters can be estimated in the least squares sense, which largely reduces the errors created by the existing noise in the measurement. Our method can be applied for both circular and full-frame imaging with a fisheye lens. In comparison with classical techniques, our method does not require precise scene arrangement or any prior information such as the field-of-view of the lens or the location of the camera center.
Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples.

BACKGROUND Mislabeled samples are a serious problem in most clinical laboratories. Published error rates range from 0.39/1000 to as high as 1.12%. Standardization of bar codes and label formats has not yet achieved the needed improvement. The mislabel rate in our laboratory, although low compared with published rates, prompted us to seek a solution to achieve zero errors. METHODS To reduce or eliminate our mislabeled samples, we invented an automated device using 4 cameras to photograph the outside of a sample tube. The system uses optical character recognition (OCR) to look for discrepancies between the patient name in our laboratory information system (LIS) vs the patient name on the customer label. All discrepancies detected by the system's software then require human inspection. The system was installed on our automated track and validated with production samples. RESULTS We obtained 1 009 830 images during the validation period, and every image was reviewed. OCR passed approximately 75% of the samples, and no mislabeled samples were passed. The 25% failed by the system included 121 samples actually mislabeled by patient name and 148 samples with spelling discrepancies between the patient name on the customer label and the patient name in our LIS. Only 71 of the 121 mislabeled samples detected by OCR were found through our normal quality assurance process. CONCLUSIONS We have invented an automated camera system that uses OCR technology to identify potential mislabeled samples. We have validated this system using samples transported on our automated track. Full implementation of this technology offers the possibility of zero mislabeled samples in the preanalytic stage.
Towards accurate and robust map-aid indoor human tracking

One critical issue in indoor human tracking is the design of map-aid algorithms that exploit indoor layout information. Most of current works adopt similar map-aid calibration techniques that eliminate invalid particles, which means particles propagating in inhumane manner. However, we find that these techniques have two serious problems in common, which we name acute sample impoverishment and observation noise vulnerability. To address these problems, we propose an Immune Location Factor Particle Filter (ILFPF) in this paper. The ILFPF overcomes the acute sample impoverishment problem through Clonal Selection Algorithm based re-sampling, which is robust against observation noise due to the introduction of Location Factor. Simulation results show that our proposed algorithm has an accuracy 36% higher than that of standard particle filter.
Measuring flexibility in single-ISA heterogeneous processors

Single-ISA heterogeneous processors are a promising method for enabling runtime power flexibility. Low-priority programs run on low-power cores, and high-priority programs run on high-power cores. In recent years, a number of methods for heterogeneous design space exploration have emerged. These methods search the design space for Pareto frontiers of cores that are optimal for power and speed. We demonstrate that a heterogeneous processor cannot be composed by simply selecting some cores from a Pareto-optimal set; the selection must give even coverage of the design space. We then define a metric — clumpiness — for measuring how well selected heterogeneous cores cover the design space.
A hybrid of singular value decomposition and regression analysis collaborative filtering with linear incremental update method

Collaborative filtering (CF) approach comprises of several well-known techniques which successful in creating personalized recommendations. Singular Value Decomposition (SVD) based technique is the dominant class of CF techniques. The techniques rooted from SVD concept mostly return the high accuracy recommendation results than others. These SVD-based techniques are come up with the concept of model-based CF techniques, in which the relationship of historical ratings between users and items are learned. The learning processes usually perform in off-line mode. The model parameters are assessed according to this off-line process for constructing the knowledge models which are further use in on-line recommendation environments. However, the accuracy of the SVD-based technique is reduced according to the increasing number of solutions that they have to evaluate compared with the steady number of knowledge that they have learned, namely users-items sparse problem. On the other hand, the memory-based CF techniques are also suggested in literatures. These techniques are relied on collecting knowledge about ratings between users and items in computational area and re-computing the entire knowledge every time when the recommendations are called for. Thus, the users-items sparse problem is not an obstructer for memory-based CF techniques, because the new knowledge is always encompassed to the fundamental knowledge. Even though, memory-based CF techniques do not cause of difficulty in the users-items sparse problem, they impractical for implementing in on-line environment. Because of memory-based CF techniques take a lot of time for estimating just only one recommendation result. Hence, this paper proposed a hybrid of SVD-based technique and memory-based technique for CF.
Usability heuristics for networked multiplayer games

Networked multiplayer games must support a much wider variety of interactions than single-player games because networked games involve communication and coordination between players. This means that designers must consider additional usability issues that relate to group play - but there are currently no usability engineering methods that are specifically oriented towards the needs of multiplayer games. To address this problem, we developed a new set of usability heuristics, called Networked Game Heuristics (NGH), which can be used in the design and evaluation of networked multiplayer games. The new heuristics were identified by analyzing problem reports from 382 reviews of networked PC games, covering six main genres. We aggregated problem reports into ten problem categories (covering issues from session management to cheating to training for novice players) and developed heuristics that describe how these usability problems can be avoided. We tested the new heuristics by having evaluators use them and an existing set to assess the usability of two networked games. Evaluators found more usability problems with NGH, and stated that the new heuristics were better for evaluating multiplayer game usability. Our research is the first to present networked game heuristics that are derived from real problem reports, and the first to evaluate the heuristics' effectiveness in a realistic usability test.