snu-aidas/HVMap-dataset huggingface dataset:
Path Planning with Real Time Obstacle Avoidance

One of the most important areas of research on mobile robots is that of their moving from one point in a space to the other and that too keeping aloof from the different objects in their path i. e. real time obstacle detection. This is the basic problem of path planning through a continuous domain. For this a large number of algorithms have been proposed of which only a few are really good as far as local and global path planning are concerned as to some extent a trade of has to be made between the efficiency of the algorithm and its accuracy. In this project an integrated approach for both local as well as global path planning of a robot has been proposed. The primary algorithm that has been used for path planning is the artificial Potential field approach [1] and a* search algorithm has been used for finding the most optimum path for the robot. Obstacle detection for collision avoidance (a high level planning problem) can be effectively done by doing complex robot operations in real time and distributing the whole problem between different control levels. This project proposes the artificial potential field algorithm not only for static but also for moving obstacles using real time potential field values by creating sub-goals which eventually lead to the main goal of the most optimal complete path found by the A* search algorithm. Apart from these scan line and convex hull techniques have been used to improve the robustness of the algorithm. To some extent the shape and size of a robot has also been taken into consideration. The effectiveness of these algorithms has been
Blockchain-based sharing services : What blockchain technology can contribute to smart cities

Background: The notion of smart city has grown popular over the past few years. It embraces several dimensions depending on the meaning of the word “smart” and benefits from innovative applications of new kinds of information and communications technology to support communal sharing. Methods: By relying on prior literature, this paper proposes a conceptual framework with three dimensions: (1) human, (2) technology, and (3) organization, and explores a set of fundamental factors that make a city smart from a sharing economy perspective. Results: Using this triangle framework, we discuss what emerging blockchain technology may contribute to these factors and how its elements can help smart cities develop sharing services. Conclusions: This study discusses how blockchain-based sharing services can contribute to smart cities based on a conceptual framework. We hope it can stimulate interest in theory and practice to foster discussions in this area.
Advanced Metamorphic Techniques in Computer Viruses

Nowadays viruses use polymorphic techniques to mutate their code on each replication, thus evading detection by antiviruses. However detection by emulation can defeat simpl e polymorphism: thus metamorphic techniques are used which thoro ughly change the viral code, even after decryption. We briefly deta il this evolution of virus protection techniques against detectio n and then study the METAPHOR virus, today’s most advanced metamorphic virus. Keywords—Computer virus, Viral mutation, Polymorphism, Metamorphism, MetaPHOR, Virus history, Obfuscation, Viral gen etic techniques
Computer proficiency questionnaire: assessing low and high computer proficient seniors.

PURPOSE OF THE STUDY
Computers and the Internet have the potential to enrich the lives of seniors and aid in the performance of important tasks required for independent living. A prerequisite for reaping these benefits is having the skills needed to use these systems, which is highly dependent on proper training. One prerequisite for efficient and effective training is being able to gauge current levels of proficiency. We developed a new measure (the Computer Proficiency Questionnaire, or CPQ) to measure computer proficiency in the domains of computer basics, printing, communication, Internet, calendaring software, and multimedia use. Our aim was to develop a measure appropriate for individuals with a wide range of proficiencies from noncomputer users to extremely skilled users.


DESIGN AND METHODS
To assess the reliability and validity of the CPQ, a diverse sample of older adults, including 276 older adults with no or minimal computer experience, was recruited and asked to complete the CPQ.


RESULTS
The CPQ demonstrated excellent reliability (Cronbach's α = .98), with subscale reliabilities ranging from .86 to .97. Age, computer use, and general technology use all predicted CPQ scores. Factor analysis revealed three main factors of proficiency related to Internet and e-mail use; communication and calendaring; and computer basics. Based on our findings, we also developed a short-form CPQ (CPQ-12) with similar properties but 21 fewer questions.


IMPLICATIONS
The CPQ and CPQ-12 are useful tools to gauge computer proficiency for training and research purposes, even among low computer proficient older adults.
Comparing the effects of different individualized music interventions for elderly individuals with severe dementia

BACKGROUND
Individuals with dementia often experience poor quality of life (QOL) due to behavioral and psychological symptoms of dementia (BPSD). Music therapy can reduce BPSD, but most studies have focused on patients with mild to moderate dementia. We hypothesized that music intervention would have beneficial effects compared with a no-music control condition, and that interactive music intervention would have stronger effects than passive music intervention.


METHODS
Thirty-nine individuals with severe Alzheimer's disease were randomly and blindly assigned to two music intervention groups (passive or interactive) and a no-music Control group. Music intervention involved individualized music. Short-term effects were evaluated via emotional response and stress levels measured with the autonomic nerve index and the Faces Scale. Long-term effects were evaluated by BPSD changes using the Behavioral Pathology in Alzheimer's Disease (BEHAVE-AD) Rating Scale.


RESULTS
Passive and interactive music interventions caused short-term parasympathetic dominance. Interactive intervention caused the greatest improvement in emotional state. Greater long-term reduction in BPSD was observed following interactive intervention, compared with passive music intervention and a no-music control condition.


CONCLUSION
Music intervention can reduce stress in individuals with severe dementia, with interactive interventions exhibiting the strongest beneficial effects. Since interactive music intervention can restore residual cognitive and emotional function, this approach may be useful for aiding severe dementia patients' relationships with others and improving QOL. The registration number of the trial and the name of the trial registry are UMIN000008801 and "Examination of Effective Nursing Intervention for Music Therapy for Severe Dementia Elderly Person" respectively.
Breast shape (ptosis) as a marker of a woman's breast attractiveness and age: Evidence from Poland and Papua.

OBJECTIVES
A women's breast is a sex-specific and aesthetic bodily attribute. It is suggested that breast morphology signals maturity, health, and fecundity. The perception of a woman's attractiveness and age depends on various cues, such as breast size or areola pigmentation. Conducted in Poland and Papua, the current study investigated how breast attractiveness, and the further estimate of a woman's age based on her breast's appearance, is affected by the occurrence of breast ptosis (ie, sagginess, droopiness).


METHODS
In the Polish sample, 57 women and 50 men (N = 107) were presented with sketches of breasts manipulated to represent different stages of ptosis based on two different breast ptosis classifications. The participants were asked to rate the breast attractiveness and age of the woman whose breasts were depicted in each sketch. In Papua, 45 men aged 20 to 75 years took part in the study, which was conducted using only one of the classifications of breast ptosis.


RESULTS
Regardless of the classification used, the results showed that the assessed attractiveness of the breasts decreased as the estimated age increased with respect to the more ptotic breasts depicted in the sketches. The results for Papuan raters were the same as for the Polish sample.


CONCLUSIONS
Breast ptosis may be yet another physical trait that affects the perception and preferences of a potential sexual partner. The consistency in ratings between Polish and Papuan raters suggests that the tendency to assess ptotic breasts with aging and a loss of attractiveness is cross-culturally universal.
Data mining models for student careers

This paper presents a data mining methodology to analyze the careers of University graduated students. We present different approaches based on clustering and sequential patterns techniques in order to identify strategies for improving the performance of students and the scheduling of exams. We introduce an ideal career as the career of an ideal student which has taken each examination just after the end of the corresponding course, without delays. We then compare the career of a generic student with the ideal one by using the different techniques just introduced. Finally, we apply the methodology to a real case study and interpret the results which underline that the more students follow the order given by the ideal career the more they get good performance in terms of graduation time and final grade. 2015 Elsevier Ltd. All rights reserved.
A cluster validity index for fuzzy clustering

Cluster validity indexes have been used to evaluate the fitness of partitions produced by clustering algorithms. This paper presents a new validity index for fuzzy clustering called a partition coefficient and exponential separation (PCAES) index. It uses the factors from a normalized partition coefficient and an exponential separation measure for each cluster and then pools these two factors to create the PCAES validity index. Considerations involving the compactness and separation measures for each cluster provide different cluster validity merits. In this paper, we also discuss the problem that the validity indexes face in a noisy environment. The efficiency of the proposed PCAES index is compared with several popular validity indexes. More information about these indexes is acquired in series of numerical comparisons and also three real data sets of Iris, Glass and Vowel. The results of comparative study show that the proposed PCAES index has high ability in producing a good cluster number estimate and in addition, it provides a new point of view for cluster validity in a noisy environment. 2004 Elsevier B.V. All rights reserved.
On the Effectiveness of Minimal Context Selection for Robust Question Answering

Machine learning models for question-answering (QA), where given a question 1 and a passage, the learner must select some span in the passage as an answer, are 2 known to be brittle. By inserting a single nuisance sentence into the passage, an 3 adversary can fool the model into selecting the wrong span. A promising new 4 approach for QA decomposes the task into two stages: (i) select relevant sentences 5 from the passage; and (ii) select a span among those sentences. Intuitively, if 6 the sentence selector excludes the offending sentence, then the downstream span 7 selector will be robust. While recent work has hinted at the potential robustness 8 of two-stage QA, these methods have never, to our knowledge, been explicitly 9 combined with adversarial training. This paper offers a thorough empirical in10 vestigation of adversarial robustness, demonstrating that although the two-stage 11 approach lags behind single-stage span selection, adversarial training improves its 12 performance significantly, leading to an improvement of over 22 points in F1 score 13 over the adversarially-trained single-stage model. 14
Soft robotic glove for combined assistance and at-home rehabilitation

This paper presents a portable, assistive, soft robotic glove designed to augment hand rehabilitation for individuals with functional grasp pathologies. The robotic glove utilizes soft actuators consisting of molded elastomeric chambers with fiber reinforcements that induce specific bending, twisting and extending trajectories under fluid pressurization. These soft actuators were mechanically programmed tomatch and support the range of motion of individual fingers. They demonstrated the ability to generate significant force when pressurized and exhibited low impedance when un-actuated. To operate the soft robotic glove, a control hardware system was designed and included fluidic pressure sensors in line with the hydraulic actuators and a closed-loop controller to regulate the pressure. Demonstrations with the complete system were performed to evaluate the ability of the soft robotic glove to carry out gross and precise functional grasping. Compared to existing devices, the soft robotic glove has the potential to increase user freedom and independence through its portable waist belt pack and open palm design. © 2014 Elsevier B.V. All rights reserved.
Software project management with GAs

A Project Scheduling Problem consists in deciding who does what during the software project lifetime. This is a capital issue in the practice of software engineering, since the total budget and human resources involved must be managed optimally in order to end in a successful project. In short, companies are principally concerned with reducing the duration and cost of projects, and these two goals are in conflict with each other. In this work we tackle the problem by using genetic algorithms (GAs) to solve many different software project scenarios. Thanks to our newly developed instance generator we can perform structured studies on the influence the most important problem attributes have on the solutions. Our conclusions show that GAs are quite flexible and accurate for this application, and an important tool for automatic project management. 2007 Elsevier Inc. All rights reserved.
Abstract Cryptography

Cryptography Ueli Maurer ETH Zurich FOSAD 2009, Bertinoro, Aug./Sept. 2009. Abstract CryptographyCryptography Ueli Maurer ETH Zurich FOSAD 2009, Bertinoro, Aug./Sept. 2009. “I can only understand simple things.” JAMES MASSEY Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitabilityion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understandingion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Goals of this talk: • Introduce layers of abstraction in cryptography. • Ex mples of abstract definitions and proofs. • Announce new security framework “abstract cryptography” (with Renato Renner).ion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Goals of this talk: • Introduce layers of abstraction in cryptography. • Ex mples of abstract definitions and proofs. • Announce new security framework “abstract cryptography” (with Renato Renner). Motivating example: One-time pad 1 C , C , ... 1 ciphertext 1 2 key 2 1 key 2 1 2 2 addition modulo 2 M , M , ... M , M , ... plaintext plaintext K , K , ... K , K , ... Motivating example: One-time pad 1 C , C , ... 1 ciphertext 1 2 key 2 1 key 2 1 2 2 addition modulo 2 M , M , ... M , M , ... plaintext plaintext K , K , ... K , K , ... Perfect secrecy (Shannon): C and M statist. independent. One-time pad in terms of systems .
Branch-and-bound processing of ranked queries

Despite the importance of ranked queries in numerous applications involving multi-criteria decision making, they are not efficiently supported by traditional database systems. In this paper, we propose a simple yet powerful technique for processing such queries based on multi-dimensional access methods and branch-and-bound search. The advantages of the proposed methodology are: (i) it is space efficient, requiring only a single index on the given relation (storing each tuple at most once), (ii) it achieves significant (i.e., orders of magnitude) performance gains with respect to the current state-of-theart, (iii) it can efficiently handle data updates, and (iv) it is applicable to other important variations of ranked search (including the support for non-monotone preference functions), at no extra space overhead. We confirm the superiority of the proposed methods with a detailed experimental study. r 2006 Elsevier B.V. All rights reserved.
Comparison of the Full Outline of UnResponsiveness and Glasgow Liege Scale/Glasgow Coma Scale in an intensive care unit population.

BACKGROUND
The Full Outline of UnResponsiveness (FOUR) has been proposed as an alternative for the Glasgow Coma Scale (GCS)/Glasgow Liège Scale (GLS) in the evaluation of consciousness in severely brain-damaged patients. We compared the FOUR and GLS/GCS in intensive care unit patients who were admitted in a comatose state.


METHODS
FOUR and GLS evaluations were performed in randomized order in 176 acutely (<1 month) brain-damaged patients. GLS scores were transformed in GCS scores by removing the GLS brainstem component. Inter-rater agreement was assessed in 20% of the studied population (N = 35). A logistic regression analysis adjusted for age, and etiology was performed to assess the link between the studied scores and the outcome 3 months after injury (N = 136).


RESULTS
GLS/GCS verbal component was scored 1 in 146 patients, among these 131 were intubated. We found that the inter-rater reliability was good for the FOUR score, the GLS/GCS. FOUR, GLS/GCS total scores predicted functional outcome with and without adjustment for age and etiology. 71 patients were considered as being in a vegetative/unresponsive state based on the GLS/GCS. The FOUR score identified 8 of these 71 patients as being minimally conscious given that these patients showed visual pursuit.


CONCLUSIONS
The FOUR score is a valid tool with good inter-rater reliability that is comparable to the GLS/GCS in predicting outcome. It offers the advantage to be performable in intubated patients and to identify non-verbal signs of consciousness by assessing visual pursuit, and hence minimal signs of consciousness (11% in this study), not assessed by GLS/GCS scales.
Enhanced LSTM for Natural Language Inference

(1) Handcrafted features [BAPM15] 78.2 (2) LSTM [BGR+16] 80.6 (3) GRU [VKFU15] 81.4 (4) Tree CNN [MML+16] 82.1 (5) SPINN-PI [BGR+16] 83.2 (6) BiLSTM intra-Att [LSLW16] 84.2 (7) NSE [MY16a] 84.6 (8) Att-LSTM [RGH+15] 83.5 (9) mLSTM [WJ16] 86.1 (10) LSTMN [CDL16] 86.3 (11) Decomposable Att [PTDU16] 86.3 (12) Intra-sent Att+(11) [PTDU16] 86.8 (13) NTI-SLSTM-LSTM [MY16b] 87.3 (14) Re-read LSTM [SCSL16] 87.5 (15) btree-LSTM [PAD+16] 87.6
Multimodal deep learning for robust RGB-D object recognition

Robust object recognition is a crucial ingredient of many, if not all, real-world robotics applications. This paper leverages recent progress on Convolutional Neural Networks (CNNs) and proposes a novel RGB-D architecture for object recognition. Our architecture is composed of two separate CNN processing streams - one for each modality - which are consecutively combined with a late fusion network. We focus on learning with imperfect sensor data, a typical problem in real-world robotics tasks. For accurate learning, we introduce a multi-stage training methodology and two crucial ingredients for handling depth data with CNNs. The first, an effective encoding of depth information for CNNs that enables learning without the need for large depth datasets. The second, a data augmentation scheme for robust learning with depth images by corrupting them with realistic noise patterns. We present state-of-the-art results on the RGB-D object dataset [15] and show recognition in challenging RGB-D real-world noisy settings.
Detecting malicious tweets in trending topics using a statistical analysis of language

0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.12.015 ⇑ Corresponding author. E-mail addresses: juaner@lsi.uned.es (J. MartinezAraujo). Twitter spam detection is a recent area of research in which most previous works had focused on the identification of malicious user accounts and honeypot-based approaches. However, in this paper we present a methodology based on two new aspects: the detection of spam tweets in isolation and without previous information of the user; and the application of a statistical analysis of language to detect spam in trending topics. Trending topics capture the emerging Internet trends and topics of discussion that are in everybody’s lips. This growing microblogging phenomenon therefore allows spammers to disseminate malicious tweets quickly and massively. In this paper we present the first work that tries to detect spam tweets in real time using language as the primary tool. We first collected and labeled a large dataset with 34 K trending topics and 20 million tweets. Then, we have proposed a reduced set of features hardly manipulated by spammers. In addition, we have developed a machine learning system with some orthogonal features that can be combined with other sets of features with the aim of analyzing emergent characteristics of spam in social networks. We have also conducted an extensive evaluation process that has allowed us to show how our system is able to obtain an F-measure at the same level as the best state-ofthe-art systems based on the detection of spam accounts. Thus, our system can be applied to Twitter spam detection in trending topics in real time due mainly to the analysis of tweets instead of user accounts. 2012 Elsevier Ltd. All rights reserved.
Background modelling based on generative unet

Background Modelling is a crucial step in background/foreground detection which could be used in video analysis, such as surveillance, people counting, face detection and pose estimation. Most methods need to choose the hyper parameters manually or use ground truth background masks (GT). In this work, we present an unsupervised deep background (BG) modelling method called BM-Unet which is based on a generative architecture that given a certain frame as input it generates as output the corresponding background image — to be more precise, a probabilistic heat map of the colour values. Our method learns parameters automatically and an augmented version of it that utilises colour, intensity differences and optical flow between a reference and a target frame is robust to rapid illumination changes and camera jitter. Besides, it can be used on a new video sequence without the need of ground truth background/foreground masks for training. Experiment evaluations on challenging sequences in SBMnet data set demonstrate promising results over state-of-the-art methods.