Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimalist Jumping Robots for Celestial Exploration

In this paper we describe a novel approach to the design and deployment of small and minimally actuated jumping or hopping robots that are suitable for exploring the unstructured terrains of celestial bodies. We introduce the basic jumping mobility paradigm, as well as the evolution of our hopping robot concept by way of the main prototypes that we have developed. These prototypes show that a small number of actuators can control the vehicle's steering, hopping, and self-righting motions. The last prototype is equipped with wheels so that precision motion can be combined with gross hopping motion. Lessons learned during the development of these prototypes have general applicability to the design of jumping robots. In addition to reviewing the issues relevant to the design of jumping systems, in this paper we describe some of the key mechanisms that enable our approach, we summarize tests obtained with these systems, and we present our future plans of localization and sensing for hopping mobility.
Changing Classrooms into Knowledge Laboratories … A Possible Scenario Replacing Everyday Lectures? +++

Present day classroom practices can benefit from the use of new technologies and teaching methodologies. Using inquiry-based learning and knowledge-based techniques in classroom situations, the paper relates the experiments conducted over two semesters at the Singapore Maritime Academy. In the experiments, the lectures were replaced with student activities, which resulted in engagement of students with the content. Constructivist methods were used to develop knowledge-based artefacts, which could be reused and further refined through future classroom processes. Techniques used to capture student activities using software suit CmapTools are also described in detail.
Weighted Mutual Exclusion Bootstrapping for Domain Independent Lexicon and Template Acquisition

We present the Weighted Mutual Exclusion Bootstrapping (WMEB) algorithm for simultaneously extracting precise semantic lexicons and templates for multiple categories. WMEB is capable of extracting larger lexicons with higher precision than previous techniques, successfully reducing semantic drift by incorporating new weighting functions and a cumulative template pool while still enforcing mutual exclusion between the categories. We compare WMEB and two state-of-theart approaches on the Web 1T corpus and two large biomedical literature collections. WMEB is more efficient and scalable, and we demonstrate that it significantly outperforms the other approaches on the noisy web corpus and biomedical text.
An efficient vehicle queue detection system based on image processing

This paper describes a method for the real-time measurement of vehicle queue parameters in a video-based traffic monitoring experimental system. The method proposed here is based on vehicle presence detection and movement analysis in video sequences acquired by a stationary camera. Queues are detected and characterized by a severity index. Intensive experiments show the robustness of the method under varying illumination and weather conditions. The system is presently undergoing an on-field testing phase in a double ways road near Trento, Italy, where queues frequently occur.
MODELING HOUSEHOLD TIME ALLOCATION BEHAVIOR : COMPARATIVE ANALYSIS USING A LARGE-SCALE DATA FROM SURVEY ON TIME USE AND LEISURE ACTIVITIES IN JAPAN

Members in a household interact with each other when allocating their limited time resources to various activities, reflecting role specification and power structure within the household. For each member, some of activities are competitive in time allocation. In addition, each member might show different interest in or attach different importance to different activities. To reflect such complicated behavioral mechanisms, we developed two types of household time allocation models by integrating group decision-making theory and Becker’s time allocation theory. One assumes a multi-linear household utility function and another adopts an iso-elastic function. These two types of utilities explicitly reflect relative influence of each member in household decision and inter-member (or intra-household) interaction. In representing intra-household interaction, these two types of utility functions overlap functionally. Each member’s utility is further defined to incorporate relative importance of each activity and inter-activity interaction based on the multi-linear function. Using a largescale national time use data collected in Japan, the effectiveness of the two models was first empirically confirmed. It is found that there is no significant difference in model accuracy between the two models on one hand, but different intra-household interactions are estimated on the other. This might suggest that to reach the same decision outcomes (refer to the allocated time patterns, here), several types of household decision-making rules might be applicable. In addition, to examine the applicability of the models to policy analysis, some scenarios related to infrastructure improvement were assumed and their impacts on quality of life from the perspective of time use were quantitatively evaluated.
Reliability of islanded microgrids with stochastic generation and prioritized load

The potential to improve distribution system reliability is a primary motivation behind the development and deployment of microgrids. Previous studies have illustrated substantial reliability benefits of dispatchable distributed energy resources (DER). However, more analysis and new evaluation methodologies are needed for microgrids dominated by limited and stochastic distributed generation (SDG). The present paper introduces an evaluation methodology for islanded microgrids that realistically represents stochastic resources and explicitly examines the influence of supply-to-load correlation on reliability. Monte-Carlo simulation is used to model component failure and repair, while historical data is used for the stochastic resource. SDG output is allocated to loads based on a prioritized order that accounts for the dynamic reconfiguration of the microgrid in the case of a local fault. Voluntary load curtailment and its impact on reliability are also examined. Simulation results reveal that the priority order of a given load section on an islanded microgrid with limited SDG determines its dominant cause of interruption and has a major influence on reliability.
I. Agent Architectures A. Three-level Architectures B. the Triple-tower Architecture

Can anything in general be said about intelligent agent architectures? 1] Just as there are millions of species of animals, occupying millions of diier-ent niches, I expect that there will be many species of artiicial agents|each a specialist for one of a countless number of tasks. The exact forms of their architectures will depend on their tasks and their environments. For example , some will work in time-stressed situations in which reactions to unpredictable and changing environmental states must be fast and unequivocal. Others will have the time and the knowledge to predict the eeects of future courses of action so that more rational choices can be made. Even though there will probably never be a single, all-purpose agent architecture, there is one that I think might play a prominent role in many future systems. It can be viewed as an elaboration of the rst two levels of the popular three-level architectures that have been prominent in robotics research. One of the rst integrated intelligent agent systems was a collection of computer programs and hardware known as \Shakey the Robot" (Nilsson, 1984). Shakey's design was an early example of what has come to be called a three-level architecture. The levels correspond to diierent paths from sensory signals to motor commands. At the lowest level of such architectures are actions that use a short and fast path from sensory signals to eeectors. Important \reeexes" are handled by this pathway|such as \stop" when touch sensors detect a close object ahead. Servo control of motors for achieving set-point targets for shaft angles and so on are also handled by these low-level mechanisms. The intermediate level combines the low level actions into more complex behaviors|ones whose realization depends on the situation (as sensed and modeled) at the time of execution. This level uses more abstract (or more \coarse") perceptual predicates and more complex actions than do the lower ones. Whereas reeex actions are typically evoked by primitive sensory signals , the coordination of intermediate-level actions requires more elaborate perceptual processing. The third level usually involves systems that can generate plans consisting of a sequence of intermediate level programs. The three-level architecture has been used in a variety of robot systems. As a typical example, see (Connell, 1992). A generalization of the three-level architecture has been proposed by Albus and colleagues (Albus, 1991; Albus, McCain, Lumia, 1989). They envision hierarchies or \towers" of perceptual, modeling, …
Biocompatability of carbon nanotubes with stem cells to treat CNS injuries

Cases reporting traumatic injuries to the brain and spinal cord are extended range of disorders that affect a large percentage of the world's population. But, there are only few effective treatments available for central nervous system (CNS) injuries because the CNS is refractory to axonal regeneration and relatively inaccessible to many pharmacological treatments. The use of stem cell therapy in regenerative medicine has been extensively examined to replace lost cells during CNS injuries. But, given the complexity of CNS injuries oxidative stress, toxic byproducts, which prevails in the microenvironment during the diseased condition, may limit the survival of the transplanted stem cells affecting tissue regeneration and even longevity. Carbon nanotubes (CNT) are a new class of nanomaterials, which have been shown to be promising in different areas of nanomedicine for the prevention, diagnosis and therapy of certain diseases, including CNS diseases. In particular, the use of CNTs as substrates/scaffolds for supporting the stem cell differentiation has been an area of active research. Single-walled and multi-walled CNT's have been increasingly used as scaffolds for neuronal growth and more recently for neural stem cell growth and differentiation. This review summarizes recent research on the application of CNT-based materials to direct the differentiation of progenitor and stem cells toward specific neurons and to enhance axon regeneration and synaptogenesis for the effective treatment of CNS injuries. Nonetheless, accumulating data support the use of CNTs as a biocompatible and permissive substrate/scaffold for neural cells and such application holds great potential in neurological research.
Appendix K Meat , Milk , and Egg Transfer Coefficients

Meat, cow’s milk and eggs can become contaminated when food-producing animals inhale or ingest contaminated materials that then transfer into these food products. The transfer coefficients (Tco) presented in Tables K.1 and K.2 were derived from published studies investigating chemical concentrations in food products resulting from animal intake of the chemical. In most studies, the chemicals were mixed into the animal’s feed, although some studies investigated the bioaccumulation of chemicals from contaminated soil in poultry feed. The Tcos, expressed in day/kilogram (d/kg), represent the ratio of contaminant concentration in fresh weight animal product (in mg/kg, for example) to the daily intake of contaminant by the animal (in mg/day). Tcos were determined only for the main food-producing animal sources, including cow’s milk, eggs, and meat from cattle, pigs and chickens.
Learning through the Design of Interactive Storie: Exploring the Concept of Storyworld

Storytelling is widely recognized as a powerful tool to enhance learning, because of its support to meaning making and to the development of expressive (possibly multimodal) skills. An interesting variant to storytelling-based learning activities is the construction of storyworlds apt to support the development of interactive stories. This differs from the design of traditional story plots in that storyworlds represent collections of possibilities to be combined in various ways, rather then pre-defined sequences of events, from which different plots can emerge, at every use of the story, from the interaction between user and story-environment. This contribution aims to reflect on the process of constructing a story world, highlighting how this type of construction implies a different mental activity and skill development than traditional storytelling.
Minimally strict polymorphic functions

In this paper we show how to efficiently check whether a polymorphic function is minimally strict. A function is minimally strict if it is the minimal element of a specific less-strict ordering. We prove that we can check whether two polymorphic functions are related by the less-strict ordering by either checking it a) for an arbitrary monomorphic instance of the functions or b) for all shapes of the functions' argument type. A shape is a value of a monomorphic instance of a polymorphic data type where each polymorphic component is replaced by an element that identifies its position in the data structure. In contrast to recent publications that characterize polymorphic functions by monomorphic instances we consider non-termination and selective strictness, ie a language closer to Haskell.
Analysing real-time communications: controller area network (CAN)

The increasing use of communication networks in time-critical applications presents engineers with fundamental problems with the determination of response times of communicating distributed processes. Although there has been some work on the analysis of communication protocols, most of this is for idealised networks. Experience with single-processor scheduling analysis has shown that models which abstract away from implementation details are at best very pessimistic, and at worst lead to an unschedulable system being deemed schedulable. In this paper, we derive an idealised scheduling analysis for the CAN real-time bus, and then study two actual interface chips to see how the analysis can be applied. <<ETX>>
Bare Hand Gesture Recognition with a Single Color Camera

A bare hand gesture recognition system using only a single color camera without any marker is presented in this paper. The system is mainly composed of image pre-processing, skin segmentation, feature extraction and gesture classification. The image pre-processing module transforms the raw image into the desirable feature vector which mainly includes converting the color images into the hue images and reducing noise. The skin segmentation module localizes and segments the skin region from the whole image and eliminates the forearm region with the help of a wrist line. The feature extraction module extracts a set of distinct parameters to represent each gesture and distinguish the different gestures. To verify the performance of the designed system, the interaction game of scissors, rock and paper was played between the computer and users, and the application results indicate that the system could reach to a recognition rate of bare hand gestures 93.1% in the complex environment conditions.
Making use of damped noisy gradient in training neural network

Multilayer feed-forward neural network is widely used based on minimization of an error function. Back propagation is a famous training method used in the multilayer networks but it often suffers from the problems of local minima and slow convergence. These problems take place due to the gradient behavior of mostly used sigmoid activation function (SAF). Weight update becomes zero when activation of a unit tends to be unity or zero. To alleviate this problem, we propose a damped noisy gradient (DNG) in order to train a neural network (NN). A simple damped Gaussian noise is added intentionally in the gradient of the sigmoid activation function (AF). Validity of the proposed method is examined by performing simulations on real classification tasks such as the Heart disease, the Ionosphere, Wine, Horse, Glass and Soybean datasets. The algorithm is shown to work better than the original back-propagation (BP), the BP with logarithmic (LOG) and arctangent (ATAN) AFs.
DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH INSTRUMENT-WISE HIDDEN MARKOV MODELS

This paper describes a system for automatic transcription of drum instruments from polyphonic music signals. For each target drum instrument, a hidden Markov model (HMM) is created to describe the sound characteristics when the instrument is played. Also, a background model with only one state is created for each instrument to describe the sound when the target instrument is not played. The signal is divided into short (2048 samples), overlapping (75%) frames and a set of features is extracted from each frame. The most likely model sequence of sound presence and absence is determined by decoding the instrument-wise HMMs with token passing algorithm.
Study on the Method of Fuzzy Comprehensive Evaluation for the Independent Innovation Ability of Construction Enterprises

Based on the connotation of independent innovation ability of construction enterprises, an evaluation index system of independent innovation ability of construction enterprises is set up. Then, entropy method is applied to determine the weight of all indicators, and fuzzy comprehensive evaluation method is used to evaluate independent technical innovation capability of construction enterprises. Finally, an empirical analysis is carried out on a construction enterprise. The results show that the evaluation method proposed in this paper is feasible, and it can be carried out to evaluate the independent innovation ability of construction enterprises correctly.
Discovering topological patterns in time-series big graph

Discovering topological patterns in a Big Data Graph is an emerging research sub area of Data Mining domain area. There are systems which can discover generalized topological patterns in a Big Graph using static Big Data set. In case of underlying Big Data is dynamic then generated Big Graph will change. There is need to develop a technique to discover the most relevant categorical, topological patterns in the new Big Graph. This paper highlights development of technique for discovering most relevant, categorical topological patterns in a Big Graph generated on online-time-series dynamic Big Data.
BotPrint : Casual Robotic Evolution

This paper describes BotPrint, a system that allows novice users to design simple robots. Botprint combines both automated and interactive evolutionary algorithms to assist the players in designing a bot that is optimized by the system yet customized by the user. Players can switch between watching bots compete in a simulated arena, breeding new bots, and selecting and editing any bot. Modifications to a bot can be inserted back into the genetic algorithm, so hand-edited robots can be further evolved and optimized into new variants.
An item-based weighted collaborative recommended algorithm based on screening users' preferences

Facing the quality of the collaborative recommendation algorithm system, an item-based collaborative filtering recommendation algorithm based on screening users' preferences was put forward. First, users have a unified interest measure for the project, and have a selection for the project based on the fuzzy membership of interests to build to project preference vector which reflects the user characteristics, using the cosine distance between vectors, the users were classified based on the weighted Item-based collaborative filtering. Experiments show that the algorithm is better than the traditional collaborative filtering algorithms in improving the recommendation dependability and accuracy.
Competitive reinforcement learning in continuous control tasks

This paper describes a novel hybrid reinforcement learning algorithm, Sarsa Learning Vector Quantization (SLVQ), that leaves the reinforcement part intact but employs a more effective representation of the policy function using a piecewise constant function based upon "policy prototypes". The prototypes correspond to the pattern classes induced by the Voronoi tessellation generated by self-organizing methods like Learning Vector Quantization (LVQ). The determination of the optimal policy function can be now viewed as a pattern recognition problem in the sense that the assignment of an action to a point in the phase space is similar to the assignment of a pattern class to a point in phase space. The distributed LVQ representation of the policy function automatically generates a piecewise constant tessellation of the state space and yields in a major simplification of the learning task relative to the standard reinforcement learning algorithms for whom a discontinuous table look function has to be learned. The feasibility and comparative advantages of the new algorithm is shown on the cart centering and mountain car problems, two control problems of increased difficulty.
Wizard of Oz Prototyping: When and How?

Progress in speech and language processing and multimodal systems technologies has led to the fact that prototyping with the Wizard of Oz (WOZ) system simulation technique is increasingly being used in systems design. When prototyping with WOZ, one or more 'wizards' simulate part or whole of the performance of the system being designed, while interacting with users who preferably believe themselves to be using a real system. A series of WOZ iterations has the potential to deliver a more or less complete specification of the system's input/output behaviour which can then be safely implemented. This paper addresses the need for a systematic presentation, conceptualisation and discussion of the WOZ technique as a systems design method: when should WOZ be preferred to other prototyping techniques which are probably less demanding in resources? What is needed to set up WOZ experiments? When should a series of WOZ iterations start and stop? And what are the main problems in designing with WOZ? The paper is based on WOZ experience in unimodal systems design but it is hoped that its open-ended generalisations may be of use to designers of multimodal systems as well.
Content Based 3D Shape Retrieval A Survey

Large databases of 3-dimensional (3D) data are becoming available on the Internet, and in various domains such as Computer Aided Design (CAD), Molecular Biology (3D Protein Models), Computer Graphics, Medicine and Archeology to name a few. As the number and variety of the 3D models(3D shapes) continue to grow, there has been an increasing interest in applications to help people search in these large databases. Even though each model might have a file name or other textual data associated with it, most of the time such information will not be enough to fully describe what the model actually is. The solution is to use the content, namely the shape. In this paper, we give an overview of the recent research on Content Based 3D Shape Retrieval. First, general shape similarity and matching concepts are given. A review of the literature on 3D shape matching research within the content based retrieval framework is the main part of this paper. Then the issues affecting the shape retrieval performance issues are discussed.