Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre‐referral general practitioner consultations and subsequent experience of cancer care: evidence from the English Cancer Patient Experience Survey

Prolonged diagnostic intervals may negatively affect the patient experience of subsequent cancer care, but evidence about this assertion is sparse. We analysed data from 73 462 respondents to two English Cancer Patient Experience Surveys to examine whether patients with three or more (3+) pre‐referral consultations were more likely to report negative experiences of subsequent care compared with patients with one or two consultations in respect of 12 a priori selected survey questions. For each of 12 experience items, logistic regression models were used, adjusting for prior consultation category, cancer site, socio‐demographic case‐mix and response tendency (to capture potential variation in critical response tendencies between individuals). There was strong evidence (P < 0.01 for all) that patients with 3+ pre‐referral consultations reported worse care experience for 10/12 questions, with adjusted odds ratios compared with patients with 1–2 consultations ranging from 1.10 (95% confidence intervals 1.03–1.17) to 1.68 (1.60–1.77), or between +1.8% and +10.6% greater percentage reporting a negative experience. Associations were stronger for processes involving primary as opposed to hospital care; and for evaluation than report items. Considering 1, 2, 3–4 and ‘5+’ pre‐referral consultations separately a ‘dose–response’ relationship was apparent. We conclude that there is a negative association between multiple pre‐diagnostic consultations with a general practitioner and the experience of subsequent cancer care.
Fast Shape Matching Using a Hybrid Model

A hybrid model is proposed to finish image shape matching from coarse to fine, which is composed of three parts: rough matching, accurate matching, and optimum matching search. According to the partial Hausdorff distance, a fast strategy for rough matching and a new improved partial Hausdorff distance for accurate matching are presented as the measures of the degree of shape similarity between the template and images. At the same time, a new genetic algorithm based on fuzzy logic, which can adaptively regulate the probabilities of crossover and mutation, is used to search the optimum shape matching quickly. The experimental results show that the model achieves the shape matching with higher speed and precision compared with the traditional matching algorithms and can be used in real-time image matching and pattern recognition.
Considering multiple options when interpreting spoken utterances

We describe Scusi? , a spoken language interpretation mechanism designed to be part of a robot-mounted dialogue system. Scusi? ’s interpretation process maps spoken utterances to text, which in turn is parsed and then converted to conceptual graphs. In order to support robust and (cid:3)exible performance of the dialogue module, Scusi? maintains multiple options at each stage of the interpretation process, and uses maximum posterior probability to rank the (partial) interpretations produced at each stage. The time and space requirements of maintaining multiple options are handled by means of an anytime search algorithm. Our evaluation focuses on the impact of the speech recognizer and the search algorithm on Scusi? ’s performance.
Fuzzy model-based servo control with constraints on both of inputs and states

This paper presents servo control for nonlinear systems with constraints on both of inputs and states using the fuzzy model-based control approach. In our previous paper, we proposed servo control with input constraint by introducing input difference between present input and final input. However, it is difficult to constrain both of state of the nonlinear systems and the control input at the same time since time-derivatives of state are used. In this paper, we construct the nonlinear error system based on error vector between state and the target point for servo control. By employing the error system representation and the input difference, servo control with constraints on both of inputs and states can be achieved. We derive LMI conditions for designing servo controller and for constraining control inputs and states. Servo controller with constraints is designed by simultaneously solving servo controller design condition and the constraint conditions. A design example illustrates the utility of this approach.
Artificial Target Location on Mars Exploration

A new location method is proposed to locate the artificial targets on curiosity rover. Firstly, considering the influence of dust particles and non-uniform illumination on Mars, median filtering and adaptive thresholding image segmentation based on integral image are used for edge detection. Then, a two-step location method is proposed to recognize and locate these artificial targets: least square ellipse fitting is used for preliminary location and Hough transform is used for precise location. Experiments are carried out based on artificial target images of curiosity rover, which indicate that the method proposed can be used on the targets with largely deformation, and the location accuracy is within 1 pixel. The method is robust to the dust adhesion, and illumination and shadows effect. It can satisfy the Mars exploration system requirements of resolution and robustness.
Quantifying the topology of large-scale structure

We propose and investigate a new algorithm for quantifying the topological properties of cosmological density fluctuations. We first motivate this algorithm by drawing a formal distinction between two definitions of relevant topological characteristics, based on concepts, on the one hand, from differential topology and, on the other, from integral geometry. The former approach leads one to concentrate on properties of the contour surfaces which, in turn, leads to the algorithms CONTOUR2D and CONTOUR3D familiar to cosmologists. The other approach, which we adopt here, actually leads to much simpler algorithms in both two and three dimensions. (The 2D algorithm has already been introduced to the astronomical literature.) We discuss the 3D case in some detail and compare results obtained with it to analogous results using the CONTOUR3D algorithm.
Robust Convolutional Neural Networks under Adversarial Noise

Recent studies have shown that Convolutional Neural Networks (CNNs) are vulnerable to a small perturbation of input called "adversarial examples". In this work, we propose a new feedforward CNN that improves robustness in the presence of adversarial noise. Our model uses stochastic additive noise added to the input image and to the CNN models. The proposed model operates in conjunction with a CNN trained with either standard or adversarial objective function. In particular, convolution, max-pooling, and ReLU layers are modified to benefit from the noise model. Our feedforward model is parameterized by only a mean and variance per pixel which simplifies computations and makes our method scalable to a deep architecture. From CIFAR-10 and ImageNet test, the proposed model outperforms other methods and the improvement is more evident for difficult classification tasks or stronger adversarial noise.
A Place to Call Home: What Immigrants Say Now about Life in America.

O verall, immigrants say they're quite satisfied with life in the United States, for themselves and their children. Discrimination against immigrants doesn't seem to be part of their daily lives, because while majorities say it exists, majorities also say they haven't experienced much discrimination personally. Right now, the biggest concern for immigrants is much the same as for native-born Americans: the economy and their own financial well-being. The economic tumult in our society is shaping some of their perceptions—and motivations. More than 7 in 10 (71 percent) report that if they could + do it all over again, they'd still come to the United States; indeed, equally large numbers (70 percent) say that they intend to make the United States their permanent home. That goes for their children as well. About three-quarters of immigrant parents (74 percent) say it's unlikely their children will want to live in their birth country, with a strong 58 percent saying it's " very unlikely. " Strong majorities say that the United States does a better + job than their birth country when it comes to offering the opportunity to earn a good living (88 percent), having a trustworthy legal system (70 percent), making good health care available (67 percent) and maintaining a good education system (62 percent). A s the United States begins another effort to overhaul immigration policy, it only makes sense to listen to the people who will be most affected by it: immigrants. To craft a just and practical policy, we need to see America through the immigrant's eyes. That's true whether you favor an open door or a higher fence. You can't hope to implement sound strategies unless you understand what brings people to the United States and what they think about the nation once they get here. Call Home, we've extended our sampling to gain a more detailed view of Hispanics and Muslims. Just as important, we can now see trend data on how immigrants view a tumultuous period in history. Our survey focused on key questions, such as: Do immigrants still see America + as the land of opportunity? How has the sagging economy and heated + immigration debate affected their outlook? What reform proposals do they favor? + What barriers do they face? + How much discrimination do they encounter? + Given the chance, would they do it all again? + This report was based on a …
Confidence-Based Concept Discovery in Relational Databases

Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. Several relational knowledge discovery systems have been developed employing various search strategies, heuristics, language pattern limitations and hypothesis evaluation criteria, in order to cope with intractably large search space and to be able to generate high-quality patterns. In this work, we improve an ILP-based concept discovery method, namely Confidence-based Concept Discovery (C2D) by removing the dependence on order of target instances in the relational database. In this method, the generalization step of the basic algorithm of C2D is modified so that all possible frequent rules in Apriori lattice can be searched in an efficient manner. Moreover, this improved version directly finds transitive rules in the search space. A set of experiments is conducted to compare the performance of proposed method with the basic version in terms of support and confidence.
Attitudes towards computer science-computing experiences as a starting point and barrier to computer science

In which way do computing experiences shape attitudes towards computer science? Why do they foster some students' commitment to the subject while they deter others? By using a qualitative research approach we observed that computing experiences have impacts on several dimensions: They affect the self-image with regard to computing, the world-image with regard to conceptions of the subject, and habits in computing. We determined different perceptions of computing (summarized as: use, professional use and design), which together with attitudes (attributions and concepts) of the field enable or inhibit pathways into the field.
An Overview of Anonymous Routing ALERT Protocol

In Mobile Ad-Hoc Network (MANET) ,for security purpose anonymous routing protocol used. This protocol hides nodes original identity from outsider, so that observer cannot threaten the security of network. There are few existing anonymous routing protocol available for MANET. From thse some are relying on hop-by-hop encryption or redundant traffic, but they are having high cost and provide low anonymity. Therefore to provide high anonymity protection with low cost, propose an Anonymous Location Based Efficient Routing Protocol. In this protocol, given network dynamically partition into zones. Every zone having nodes which are act as intermediate nodes.These nodes get randomly selected for routing so that observer cannot indentify route.For anonymity ALERT hides mainly source and destination identity using pseudonym which changes frequently. And ALERT also hide route between source and destination. With this ALERT also having stratergy against intersection attacks. Keywords— Mobile Ad-Hoc Network, Anonymity, Intersection attack etc.Introduction
Impaired Verbal and Nonverbal Emotion Recognition in Alexithymia

Although clinical observations suggest that alexithymic individuals have a deficit in their ability to recognize emotional stimuli and that this deficit is not simply due to a problem in verbal labeling, these two hypotheses have not been empirically confirmed.Three hundred eighty participants in a community survey without current or past histories of psychiatric disorder completed two independent measures of alexithymia [the Levels of Emotional Awareness Scale (LEAS) and the Toronto Alexithymia Scale (TAS-20)] and the Perception of Affect Task (PAT), a 140-item measure of the ability to match emotion stimuli. The PAT includes four subtasks that require the subject to match verbal or nonverbal emotion stimuli with verbal or nonverbal emotion responses. The subtasks include matching sentences and words (verbal-verbal), faces and words (nonverbal-verbal), sentences and faces (verbal-nonverbal), and faces and photographs of scenes (nonverbal-nonverbal). Across the entire sample, higher (alexithymic) TAS-20 and lower LEAS scores were both correlated with lower accuracy rates on each of the subtasks of the PAT (p <.001), accounting for 10.5% and 18.4% of the variance, respectively. Fifty-one subjects met TAS-20 criteria for alexithymia. Alexithymic individuals scored lower than other subjects on purely nonverbal matching, purely verbal matching, and mixed verbal-nonverbal matching (all p <.001). These results suggest that alexithymia is associated with impaired verbal and nonverbal recognition of emotion stimuli and that the hallmark of alexithymia, a difficulty in putting emotion into words, may be a marker of a more general impairment in the capacity for emotion information processing.
Comparison of the constant prediction time of collaborative filtering algorithms by using time contexts

This research presents the comparison of collaborative filtering techniques which are Tendencies Based Algorithm, Item mean algorithm, and Simple mean based algorithm. All these algorithms use the constant time in prediction process. To evaluate our proposed model, we use last.fm dataset including music listening history of each user. Each user's profile is split into several sub-profiles based on specified time ranges called “Time Contexts”. Thus the prediction is done using these Time Contexts instead of a single user profile. From our experiments, we have found that Tendencies Based Algorithm with Time Contexts is effective. It is given more accuracy and much more efficient computationally than tradition collaborative filtering algorithms.
Ranking scientists from the field of quantum game theory using p-index

The h-index is a very well known metric used to measure scientific throughput, but it also has well known limitations. In this paper we use a metric based on pagerank algorithm, which we call the p-index, to compare the performance of scientists. We use a real-world dataset to which we apply our analysis: a dataset of scientists from the field of quantum game theory. This dataset is cured by us for this study from Google Scholar. We show that whereas the popularly used h-index rewards authors who collaborate extensively and publish in higher volumes, the p-index rewards hardworking authors who contribute more to each paper they write, as well as authors who publish in high impact and well cited journals. As such, it could be argued that the p-index is a `fairer' metric of the productivity and impact of scientists. Of particular note is that the p-index does not use the so called `impact factors' of journals, the utility of which is debated ins scientific community. Rather, the p-index relies on the actual underlying citation network to measure the real impact of each paper. Furthermore, the p-index relies not only on the number of citations but also on the quality of citations of each paper. Using p-index, we highlight and compare the impact of real world scientists on the field of quantum game theory.
Increasing Diversity in Web Search Results

The Web is an open repository characterized by the enormous quantity and variety of the provided information. A major challenge when searching the Web is to detect this diversity, to reveal it to the user, and to make it exploitable. In this paper, we deal with the notion of diversity in the Web, aiming at constructing a diverse subset of results to answer an ambiguous query or a query for which dierent topics or types of results may exist. We view the problem of diversication as an attempt to achieve good coverage of the whole set of the query results. We consider dierent diversication objectives, as well as corresponding approximation algorithms. We also describe a strategy that relies on topic detection and clustering to diversify search results.
Tactile Feedback for Above-Device Gesture Interfaces: Adding Touch to Touchless Interactions

Above-device gesture interfaces let people interact in the space above mobile devices using hand and finger movements. For example, users could gesture over a mobile phone or wearable without having to use the touchscreen. We look at how above-device interfaces can also give feedback in the space over the device. Recent haptic and wearable technologies give new ways to provide tactile feedback while gesturing, letting touchless gesture interfaces give touch feedback. In this paper we take a first detailed look at how tactile feedback can be given during above-device interaction. We compare approaches for giving feedback (ultrasound haptics, wearables and direct feedback) and also look at feedback design. Our findings show that tactile feedback can enhance above-device gesture interfaces.
Gene Expression Pattern in Transmitochondrial Cytoplasmic Hybrid Cells Harboring Type 2 Diabetes-Associated Mitochondrial DNA Haplogroups

Decreased mitochondrial function plays a pivotal role in the pathogenesis of type 2 diabetes mellitus (T2DM). Recently, it was reported that mitochondrial DNA (mtDNA) haplogroups confer genetic susceptibility to T2DM in Koreans and Japanese. Particularly, mtDNA haplogroup N9a is associated with a decreased risk of T2DM, whereas haplogroups D5 and F are associated with an increased risk. To examine functional consequences of these haplogroups without being confounded by the heterogeneous nuclear genomic backgrounds of different subjects, we constructed transmitochondrial cytoplasmic hybrid (cybrid) cells harboring each of the three haplogroups (N9a, D5, and F) in a background of a shared nuclear genome. We compared the functional consequences of the three haplogroups using cell-based assays and gene expression microarrays. Cell-based assays did not detect differences in mitochondrial functions among the haplogroups in terms of ATP generation, reactive oxygen species production, mitochondrial membrane potential, and cellular dehydrogenase activity. However, differential expression and clustering analyses of microarray data revealed that the three haplogroups exhibit a distinctive nuclear gene expression pattern that correlates with their susceptibility to T2DM. Pathway analysis of microarray data identified several differentially regulated metabolic pathways. Notably, compared to the T2DM-resistant haplogroup N9a, the T2DM-susceptible haplogroup F showed down-regulation of oxidative phosphorylation and up-regulation of glycolysis. These results suggest that variations in mtDNA can affect the expression of nuclear genes regulating mitochondrial functions or cellular energetics. Given that impaired mitochondrial function caused by T2DM-associated mtDNA haplogroups is compensated by the nuclear genome, we speculate that defective nuclear compensation, under certain circumstances, might lead to the development of T2DM.
Multiobjective Optimization of an Industrial Ethylene Reactor Using a Nondominated Sorting Genetic Algorithm

Ethylene is produced in the largest volume among the monomers, and hence, any improvement in its production process can bring important benefits to both industry and consumers. In the present paper, an industrial ethylene reactor has been studied with a multiobjective optimization technique to find a scope for further improvements and to detect a range of optimal solutions. An industrial reactor unit using ethane as the feedstock was modeled, assuming a detailed freeradical mechanism for the reaction kinetics coupled with material, energy, and momentum balances of the reactant-product flow along the reactor. To carry out the multiobjective optimization for two and three objectives, the elitist nondominated sorting genetic algorithm, or NSGA-II, was chosen. Instead of a single optimum as in traditional optimization, a broad range of optimal design and operating conditions depicting tradeoffs of key performance parameters such as conversion, selectivity and ethylene flow rate was successfully obtained. The effects of design and operating variables on the optimal solutions are discussed in detail, and the generated results are compared with industrial data.
Distributed context aware train localization system

The current paper presents a conceptual architecture of a distributed train localization solution based on GNSS(Global Navigation Satellite System) and inertial sensors. The requirements attached to this application are stringent, due to the fact that they need to prove safety of life. Additionally this solution proposes a cost efficient hardware and software configuration which allows deployment on low traffic density lines by partially outsourcing services to the public. Extended use of MEMS(Microelectromechanical Systems) embedded into COTS(commercial off the shelf) products such as tablet PC's and mobile smartphones, leads to further cost reduction and consolidates the reusability of this solution.
TRAINING COACHING & COUNSELING TO SUPPORT QUALITY OF WORK LIFE (QWL)

The companies are trying to find workers who have the best potential. Workers with the best potential strongly support the company’s success in the future. The function of the organization is actually to build human resources competencies and be able to support the process of human empowerment. This situation is increasingly requires resources that are able to work more effectively. PT. X is a company engaged in the manufacturing of cement and concrete. Therefore, the company must be able to give attention to Quality of Work Life (QWL) to improve productivity.The selected constructs of QWL that we use are derived from the European Foundation for the Improvement of Living and Working Condition (EWON, 2002) who have used the dimensions widely in their QWL studies. Dimensions QWL are Health and Wellbeing, Job Security, Job Satisfaction, Competency Development, dan Work and Non Work Balance (Rethinam & Ismail, 2008). The methods used in the research was action research. The pre asesment result showed that job satisfaction, Health and Wellbeing, Work and Non Work Balace are not good enough. QWL program can help employees to be able to balance his personal life. To improve these three thing, the company has made a program. The Program is called Employee Asistance Program (EAP), a program designed as a media mentoring employees. To conduct the EAP program it is necessary that supervisors have the coaching and counseling skill. Managers and Supervisors have the autonoy and reponsibility to assist their subordinates while having the problems as well as motivating them to improve their performance.