Articles

Characterizing the technological evolution of smartphones: Insights from performance benchmarks

Han Q., Cho D.

ACM International Conference Proceeding Series

2016

Abstract:

Recent technological advancements in smartphone have paved the way for the rapidly growing mobile commerce. As smartphone vendors launch the products with a rich variety of technical features for different end-user market segments, understanding the evolution of these features is of vital importance to all stakeholders in the smartphone industry. We address this issue by exploring technical specifications of smartphones at both the feature and the device level. In particular, we introduce the benchmarks to operationalize the overall performance of smartphone models, such that multidimensional technical features can be quantitatively summarized into a single index. Through the analysis of a comprehensive dataset entailing technical features for smartphone models launched during the years 2012-2015, we show that although certain features have become the standard functionality, the smartphone industry is largely innovative and continues to evolve over time. We believe our findings may provide important insights into the future development and design strategies of smartphones.

Classification of unlabeled point sets using ansig

Rodrigues J.J., Xavier J.M.F., Aguiar P.M.Q.

Proceedings - International Conference on Image Processing, ICIP

2008

Abstract:

We address two-dimensional shape-based classification, considering shapes described by arbitrary sets of unlabeled points, or landmarks. This is relevant in practice because, in many applications, the points describing the shapes come from automatic processes, e.g., edge detection, thus without labels. Rather than attempting to compute point correspondences (a quagmire, when dealing with nontrivial shapes), we use what we call the analytic signature (ANSIG) of the shapes, a representation that has the key feature of being invariant to point labeling. Geometric transformations, such as translation, rotation, and scale, and different cardinality of point sets, are also dealt with by this representation. We demonstrate the capabilities of our representation with several shape classification experiments.

Classification with reject option using contextual information

Condessa F., Bioucas-Dias J., Castro C.A., Ozolek J.A., Kovacevic J.

Proceedings - International Symposium on Biomedical Imaging

2013

Abstract:

We propose a new algorithm for classification that merges classification with reject option with classification using contextual information. A reject option is desired in many image-classification applications requiring a robust classifier and when the need for high classification accuracy surpasses the need to classify the entire image. Moreover, our algorithm improves the classifier performance by including local and nonlocal contextual information, at the expense of rejecting a fraction of the samples. As a probabilistic model, we adopt a multinomial logistic regression. We use a discriminative random model for the description of the problem; we introduce reject option into the classification problem through association potential, and contextual information through interaction potential. We validate the method on the images of H&E-stained teratoma tissues and show the increase in the classifier performance when rejecting part of the assigned class labels.

Closing the Loop in Exergaming – Health Benefits of Biocybernetic Adaptation in Senior Adults

Munoz J. E., Cameirão M.S., Badia S., Gouveia E.R.

CHI PLAY '18 Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play

2018

Abstract:

Exergames help senior players to get physically active by promoting fun and enjoyment while exercising. However, most exergames are not designed to produce recommended levels of exercise that elicit adequate physical responses for optimal training in the aged population. In this project, we developed physiological computing technologies to overcome this issue by making real-time adaptations in a custom exergame based on recommendations for targeted heart rate (HR) levels. This biocybernetic adaptation was evaluated against conventional cardiorespiratory training in a group of active senior adults through a floor-projected exergame and a smartwatch to record HR data. Results showed that the physiologically-augmented exergame leads players to exert around 40% more time in the recommended HR levels, compared to the conventional training, avoiding over exercising and maintaining good enjoyment levels. Finally, we made available our biocybernetic adaptation software tool to enable the creation of physiological adaptive videogames, permitting the replication of our study.

Co-gasification of refused derived fuel and biomass in a pilot-scale bubbling fluidized bed reactor

Pio D., Tarelho L., Tavares A., Matos M., Silva V.

Energy Conversion and Management

2020

Abstract:

In this work, direct (air) co-gasification of refused derived fuel with biomass was demonstrated in an 80kWth pilot-scale bubbling fluidized bed reactor. The influence of the process operating parameters, namely average bed temperature between 785 and 829 °C, equivalence ratio between 0.21 and 0.36 and refused derived fuel weight percentage in the fuel mixture (0, 10, 20, 50 and 100 wt%) was analyzed. For the operating conditions used, the process was demonstrated as autothermal and operating under steady-state conditions, with no defluidization phenomena observed. The increase of the refused derived fuel weight percentage in the fuel mixture led to an increase of the methane and ethylene concentration in the producer gas and, consequently, an increase of the producer gas lower heating value, reaching a maximum value of 6.4 MJ/Nm3. In terms of efficiency parameters, cold gas efficiency was found between 32.6 and 53.5% and carbon conversion efficiency between 56.0 and 84.1%. A slight increase of the cold gas efficiency was observed with the increase of the refused derived fuel weight percentage in the fuel mixture. Thus, refused derived fuel co-gasification with biomass was shown as a highly promising process for the valorization of wastes as an energetic resource.

CoBots: Collaborative robots servicing multi-floor buildings

Veloso M., Biswas J., Coltin B., Rosenthal S., Kollar T., Mericli C., Samadi M., Brandao S., Ventura R.

IEEE International Conference on Intelligent Robots and Systems

2012

Abstract:

In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have been numerous and successful, and we build upon them. However, there are clearly many research challenges remaining until we can experience intelligent mobile robots that are fully functional and capable in our human environments.

Collaborative diffusive source localization in wireless sensor networks

Zejnilovic S., Gomes J., Sinopoli B.

European Signal Processing Conference

2012

Abstract:

We propose a collaborative, energy efficient method for diffusive source localization in wireless sensor networks. The algorithm is based on distributed and iterative maximum-likelihood (ML) estimation, which is very sensitive to initialization. As a part of the proposed method we present an approach for obtaining a “good enough” initial value for the ML recursion based on infinite time approximation and semidefinite programming. We also present an approach for determining the sensor node that initiates the estimation process. To improve the convergence rate of the algorithm, we consider the case where selected nodes collaborate with their neighbors. Simulation results are used to characterize the performance and energy efficiency of the algorithm. We also illustrate estimation accuracy/energy consumption trade-off by varying the communication radius of sensor nodes.

Collaborative sequential-based detection in wireless sensor networks

Zejnilovic S., Gomes J.P., Sinopoli B.

Conference Record - Asilomar Conference on Signals, Systems and Computers

2011

Abstract:

Due to limited power resources, energy efficiency is an important aspect of detection in wireless sensor networks. We propose a collaborative detection scheme, based on sequential hypothesis testing, where a randomly chosen node may initiate a collaboration, collecting observations from neighboring nodes to test the hypotheses. Our simulation results show that for large networks and high SNR, the proposed scheme leads to lower communication cost and similar performance when compared to a standard detection setup, where all the observations are collected in a fusion node. We also examine how the energy efficiency of this scheme evolves as a function of the network structure.

Com2: Fast automatic discovery of temporal (‘comet’) communities

Araujo M., Papadimitriou S., Gunnemann S., Faloutsos C., Basu P., Swami A., Papalexakis E.E., Koutra D.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2014

Abstract:

Given a large network, changing over time, how can we find patterns and anomalies? We propose Com2, a novel and fast, incremental tensor analysis approach, which can discover both transient and periodic/ repeating communities. The method is (a) scalable, being linear on the input size (b) general, (c) needs no user-defined parameters and (d) effective, returning results that agree with intuition. We apply our method on real datasets, including a phone-call network and a computer-traffic network. The phone call network consists of 4 million mobile users, with 51 million edges (phonecalls), over 14 days. Com2 spots intuitive patterns, that is, temporal communities (comet communities). We report our findings, which include large ‘star’-like patterns, nearbipartite- cores, as well as tiny groups (5 users), calling each other hundreds of times within a few days.