Miracle-dz/UniFAR-FTUs huggingface dataset:
MHealth and Serious Game Analytics for Cystic Fibrosis Adults

Cystic Fibrosis is the most common life limiting genetic disease affecting Caucasians. With life expectancy for these patients rising, there is need to investigate interventions for a CF adult that does not impede on their busy lifestyle. This research describes an mHealth game data analytics system. The proposed system incorporates a game where a user must blow into the microphone to control an object through obstacles. This Android app collects game performance data, well-being questionnaire data, and initial blow strength. This data is then analysed and graphically represented for data interpretation on a web tool. The data collected may trigger an alert SMS to be sent to the patient based on three criteria which can be customised through the web tool for a more individualised analysis. The mHealth app is created using Android, and data is from this app posted to a remote server and stored in a database for analysis. The web tool comprises of PHP, MySQL, HTML, JavaScript and Text API. On opening the app, the patient creates a profile and all subsequent data is stored under this profile for analysis. Default alert criteria is saved for each patient which can be edited by a CF multidisciplinary team member. By default, if the user records an increase in sputum volume, or decline in baseline, or decline in game performance five times consecutively, a SMS alert is sent to the patient. This proposed system is currently undergoing pilot testing with a small CF patient cohort. Comparative data for three CF patients who utilised the system over a two month period is also discussed here within. This research concludes that there is a need for mHealth data analysis systems for adults with CF. The system presented is found to be engaging among CF adult patients and can be incorporated into their daily lifestyle with ease. Questionnaire data recorded through the app regarding therapy compliance suggests a correlation with game performance. This correlation can serve as a practical example for the importance of therapy compliance. Additionally, it can demonstrate how non-compliance can lead to possible exacerbations.
Viewing the Meso-Scale Structures in Protein-Protein Interaction Networks Using 2-Clubs

Many current analyses on protein-protein interaction (PPI) networks concentrate on developing the algorithms for identifying the functional modules within the PPI networks. However, understanding the internal structure in the functional modules is needed to define their roles within the entire network. We propose the use of a two-club meso-scale structure that possesses refined inner topological structural properties, useful for deciphering the aforementioned obscure structural supporting evidences. In this paper, we: 1) illustrate the feasibility and advantages of modeling functional modules as two-clubs in PPI networks by taking statistics on the diameter distribution of benchmark functional modules within several golden standard sets; 2) categorize the two-clubs into six subcategories through the use of well-defined internal graph-theoretic characterizations; and 3) analyze these six subcategories based on factors, such as their structure, and various metrics, such as topological centralities, the numbers of involved transcription factors and essential genes, and the numbers of matched protein complexes or GO terms. Our structure-driven analysis allows us to predict the roles of identified functional modules from their network structure alone. Our subcategories of coteries and social circles serve as a classification scheme for determining which functional modules are central, regional, and satellite and which are coordinating. Experimental results show that in order to precisely control and examine the PPI networks for further research, a clear understanding of how the internal topology of modules affects their function is essential.
Aplicação de técnicas de mineração de textos para classificação de documentos : um estudo da automatização da triagem de denúncias na CGU

The Office of the Comptroller General (CGU) is the agency of the Federal Government in charge of assisting the President of the Republic in matters related to internal control activities, public audits, corrective and disciplinary measures, corruption prevention and combating and coordinating ombudsman’s activities. Through a complaints link of the CGU site, citizens have access to a form to file their complaints. These complaints must be screened and delivered to the coordination of CGU by subject. Nowadays the complaints screening is done manually and they are delivered to one of the 91 coordinating units of CGU. This large amount of categories is more complex in automatic text classification. Considering the complaints storage on the database now and the arrival of new complaints, combined with the time spent on manual sorting, the timely analysis of the reported occurrences it becomes increasingly difficult. This context can cause financial losses to Federal Public Administration as well as discouraging the use of the channel by the citizen. Complaints registered origins are municipalities present in all Brazilian states, generating a great impact on the entire national territory. This research intends to develop a proof of concept for an automatic model of complaints screening, using text mining. The best results were achieved using ranking based on the Huffman Tree algorithm. This proof of concept demonstrated the feasibility of automatical sorting without the loss of quality compared to manual sorting.
Wireless LC-Type Passive Humidity Sensor Using Large-Area RF Magnetron Sputtered ZnO Films

We report on a ZnO-based LC-type passive humidity sensor (HS) using a scalable, large-area thin-film semiconductor fabrication process. The reported sensor is capable of monitoring relative humidity (RH) remotely. The fabricated sensor is 30 mm in diameter and comprises an LC resonator formed via an octagonal planar inductor and a moisture sensitive interdigitated ZnO capacitor in series. A printed circuit board reader coil, which can sense the sensor output from <25 mm distance, is also reported. The HS is demonstrated to read 30%–90% of RH by interrogating the change in resonance frequency (<inline-formula> <tex-math notation="LaTeX">${f}_{R}$ </tex-math></inline-formula>) of the reader-senor system. The reading resolution was ±2.38% RH and the sensor sensitivity ranged from 53.33 kHz to 93.33 kHz for a 1% change in RH during measurements above 45% RH. Experimental results also showed that the fabricated sensor is operational for a range of 0 °C−75 °C as long as calibration is performed for temperature drifts of ≥±3 °C. The reported results are promising to expedite the deployment of novel inexpensive sensor, for example, in sealed locations to remotely monitor humidity without a need for on-sensor power.
FragDroid: Automated User Interface Interaction with Activity and Fragment Analysis in Android Applications

Recent years have witnessed the enormous growth of Android phones in the consumer market. On the other hand, as the most popular mobile platform, Android also attracts lots of attackers' attention. As a result, more and more Android malicious apps appear in the wild, which poses a serious threat to user's security and privacy. To such massive volume of Android malware, automated UI testing techniques have become the mainstream solutions because of the detection efficiency and accuracy. However, all existing UI testing techniques treat the Activity as the basic unit of UI interactions and cannot carry out a fine-grained analysis for Fragments. Due to the lack of Fragment-level analysis, the path coverage is usually quite limited. To fill this gap, in this paper, we propose FragDroid, a novel automated UI testing framework supporting both Activity and Fragment analysis. To achieve the Fragment-level testing, we design the Activity & Fragment Transition Model (AFTM) to simulate the internal interactions of an app, and ATFM could be utilized to generate test cases automatically through UI interactions. With the assist of AFTM, FragDroid achieves accessing most Activities and Fragments contained in the app along with the capability of detecting arbitrary API calls. We implemented a prototype of FragDroid and evaluated it on 15 popular apps. The results show FragDroid successfully covered 66% Fragments and the corresponding API calls of testing apps. Also, the traditional approaches have to miss at least 9.6% of API calls invoked in Fragments.
50K-C: A Dataset of Compilable, and Compiled, Java Projects

We provide a repository of 50,000 compilable Java projects. Each project in this dataset comes with references to all the dependencies required to compile it, the resulting bytecode, and the scripts with which the projects were built. The dependencies and the build scripts provide a mechanism to re-create compilation of the projects, if needed (to instruct source code for bytecode analysis, for example). The bytecode is ready for testing, execution, and dynamic analysis tools.
A Comparative Study on the Electrical Properties of Vertical ( $\bar{\sf2}01$ ) and (010)  $\beta$ -Ga2O3 Schottky Barrier Diodes on EFG Single-Crystal Substrates

This paper reports a comprehensive study on the anisotropic electrical properties of vertical (<inline-formula> <tex-math notation="LaTeX">$\overline {\textsf {2}}01$ </tex-math></inline-formula>) and (010) <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> Schottky barrier diodes (SBDs). The devices were fabricated on single-crystal substrates grown by an edge-defined film-fed growth method. The temperature-dependent current–voltage (I–V) and capacitance–voltage (C–V) characteristics were systematically measured, analyzed, and compared. The (<inline-formula> <tex-math notation="LaTeX">$\overline {\textsf {2}}01$ </tex-math></inline-formula>) and (010) SBDs exhibited on-resistances (<inline-formula> <tex-math notation="LaTeX">${R}_{{ \mathrm{\scriptscriptstyle ON}}}$ </tex-math></inline-formula>) of 0.56 and <inline-formula> <tex-math notation="LaTeX">$0.77~\textsf {m}\Omega \cdot \textsf {cm}^{{\textsf {2}}}$ </tex-math></inline-formula>, turn- ON voltages (<inline-formula> <tex-math notation="LaTeX">${V}_{{ \mathrm{\scriptscriptstyle ON}}}$ </tex-math></inline-formula>) of 1.0 and 1.3 V, Schottky barrier heights (SBHs) of 1.05 and 1.20 eV, electron mobilities of 125 and 65 cm<sup>2</sup>/(<inline-formula> <tex-math notation="LaTeX">$\textsf {V}\cdot ~\textsf {s}$ </tex-math></inline-formula>), respectively, with an on-current of ~1.3 kA/cm<sup>2</sup> and on/off ratio of ~10<sup>9</sup>. The (010) SBD had a larger <inline-formula> <tex-math notation="LaTeX">${V}_{{ \mathrm{\scriptscriptstyle ON}}}$ </tex-math></inline-formula> and SBH due to anisotropic surface properties (i.e., surface Fermi level pinning and band bending), as supported by X-ray photoelectron spectroscopy measurements. Temperature-dependent I–V also revealed the inhomogeneous nature of the SBH in both devices, where the (<inline-formula> <tex-math notation="LaTeX">$\overline {\textsf {2}}01$ </tex-math></inline-formula>) SBD showed a more uniform SBH distribution. The homogeneous SBH was also extracted: 1.33 eV for the (<inline-formula> <tex-math notation="LaTeX">$\overline {\textsf {2}}01$ </tex-math></inline-formula>) SBD and 1.53 eV for the (010) SBD. The reverse leakage current of the devices was well described by the two-step trap-assisted tunnelingmodel and the 1-D variable range hopping conduction model. The (<inline-formula> <tex-math notation="LaTeX">$\overline {\textsf {2}}01$ </tex-math></inline-formula>) SBD showed a larger leakage current due to its lower SBH and/or smaller activation energy, and thus a smaller breakdown voltage. These results indicate that the crystalline anisotropy of <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> can affect the electrical properties of vertical SBDs and should be taken into consideration when designing <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> electronics.
Transcribing Content from Structural Images with Spotlight Mechanism

Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal structure should also be preserved. Existing image recognition methods mainly work on images with simple content (e.g., text lines with characters), but are not capable to identify ones with more complex content (e.g., structured code), which often follow a fine-grained grammar. To this end, in this paper, we propose a hierarchical Spotlight Transcribing Network (STN) framework followed by a two-stage "where-to-what'' solution. Specifically, we first decide "where-to-look'' through a novel spotlight mechanism to focus on different areas of the original image following its structure. Then, we decide "what-to-write'' by developing a GRU based network with the spotlight areas for transcribing the content accordingly. Moreover, we propose two implementations on the basis of STN, i.e., STNM and STNR, where the spotlight movement follows the Markov property and Recurrent modeling, respectively. We also design a reinforcement method to refine our STN framework by self-improving the spotlight mechanism. We conduct extensive experiments on many structural image datasets, where the results clearly demonstrate the effectiveness of STN framework.
Generalized Score Functions for Causal Discovery

Discovery of causal relationships from observational data is a fundamental problem. Roughly speaking, there are two types of methods for causal discovery, constraint-based ones and score-based ones. Score-based methods avoid the multiple testing problem and enjoy certain advantages compared to constraint-based ones. However, most of them need strong assumptions on the functional forms of causal mechanisms, as well as on data distributions, which limit their applicability. In practice the precise information of the underlying model class is usually unknown. If the above assumptions are violated, both spurious and missing edges may result. In this paper, we introduce generalized score functions for causal discovery based on the characterization of general (conditional) independence relationships between random variables, without assuming particular model classes. In particular, we exploit regression in RKHS to capture the dependence in a nonparametric way. The resulting causal discovery approach produces asymptotically correct results in rather general cases, which may have nonlinear causal mechanisms, a wide class of data distributions, mixed continuous and discrete data, and multidimensional variables. Experimental results on both synthetic and real-world data demonstrate the efficacy of our proposed approach.
Dynamic Memory Dependence Predication

Store-queue-free architectures remove the store queue and use memory cloaking to communicate in-flight stores instead. In these architectures, frequent mispredictions may occur when the store to load dependencies are inconsistent. We present DMDP (Dynamic Memory Dependence Predication) which modifies the microarchitecture behavior for such loads to mitigate memory dependence mispredictions. When a given dependence is hard to predict, i.e., a given load occasionally depends on a particular store, but it is independent at other times, DMDP predicates the load so that the address of the load is compared with the address of the predicted store to compute a predicate. This predicate guides the load to obtain the value from either the cache or the colliding store. The predication provided by DMDP i) enables the loads and their dependent instructions to execute much earlier, ii) reduces the hardware complexity of store-queue-free mechanisms, and iii) reduces the number of mispredictions. DMDP outperforms a state-of-the-art store-queue-free architecture by 7.17% on Integer benchmarks and 4.48% on Float benchmarks in our Spec 2006 evaluation. We further show that despite executing extra predication instructions, DMDP is power efficient as it saves about 6.7% on EDP.
Variable Selection and Task Grouping for Multi-Task Learning

We consider multi-task learning, which simultaneously learns related prediction tasks, to improve generalization performance. We factorize a coefficient matrix as the product of two matrices based on a low-rank assumption. These matrices have sparsities to simultaneously perform variable selection and learn and overlapping group structure among the tasks. The resulting bi-convex objective function is minimized by alternating optimization, where sub-problems are solved using alternating direction method of multipliers and accelerated proximal gradient descent. Moreover, we provide the performance bound of the proposed method. The effectiveness of the proposed method is validated for both synthetic and real-world datasets.
Classification of Heart Sounds Using Softmax Regression and Convolutional Neural Network

This research explores a new approach in using deep learning neural network for heart sound classification. The Michigan heart sound and murmur database (MHSDB) provided by the University of Michigan Health System was used in this research. The heart sounds are segmented per heartbeat and each segment is converted to form an intensity map and classified using two methods: a simple Softmax Regression (SMR) network and a convolutional neural network (CNN). This approach removes the need to provide features for supervised machine learning methods. Instead, the features are determined automatically through training of the neural network models. The result proves that the CNN is able to provide much better classification accuracy than the Softmax Regression network. In addition, classification of periodic heart sounds provides better resolution in detecting abnormal heart sounds in early stage of heart disease. Due to its simplicity in implementation, this approach can be used for real-time classification of heart sounds in wearable devices and smartphones in settings beyond hospitals.
Slip Detection With a Biomimetic Tactile Sensor

Slip detection helps to prevent robotic hands from dropping grasped objects and would thus enable complex object manipulation. Here we present a method of detecting slip with a biomimetic optical tactile sensor—the TacTip—that operates by measuring the positions of internal pins embedded in its compliant skin. We investigate whether local pin movement is a strong signal of slip. Accurate and robust discrimination between static and slipping objects is obtained with a support vector machine (accuracy 99.88%). We then demonstrate performance on a task in which a slipping object must be caught. For fast reaction times, a modified TacTip is made for high-speed data collection. Performance of the slip detection method is then validated under several test conditions, including varying the speed at which slip onset occurs and using novel shaped objects. The proposed methods should apply to tactile sensors that can detect the local velocities of surface movement. The sensor and slip detection methods are also well-suited for integration onto robotic hands for deploying slip control under manipulation.
Properties and Design of Variable-to-Variable Length Codes

For the entropy coding of independent and identically distributed (i.i.d.) binary sources, variable-to-variable length (V2V) codes are an interesting alternative to arithmetic coding. Such a V2V code translates variable length words of the source into variable length code words by employing two prefix-free codes. In this article, several properties of V2V codes are studied, and new concepts are developed. In particular, it is shown that the redundancy of a V2V code cannot be zero for a binary i.i. d. source {X} with 0 < pX(1) < 0.5. Furthermore, the concept of prime and composite V2V codes is proposed, and it is shown why composite V2V codes can be disregarded in the search for particular classes of minimum redundancy codes. Moreover, a canonical representation for V2V codes is proposed, which identifies V2V codes that have the same average code length function. It is shown how these concepts can be employed to greatly reduce the complexity of a search for minimum redundancy (size-limited) V2V codes.
Virtual by Design: How a Work Environment can Support Agile Distributed Software Development

Even though agile methods have been flourishing in the last decades, their implementation in (globally) distributed arrangements still present hard challenges. Due to this tension, practices are either modified or added to compensate with the additional control required by the setup. In this paper, we present a case study about a company that managed to incrementally design a process that does not compromise the foundations of the agile philosophy by embracing the characteristics of distributed development. We show how a virtual work environment has been crafted by continuously improving practices and carefully selecting technologies to allow each team member to fully participate regardless of the actual physical location. Aware of the single nature limitation of the reported case, we present extensive information to frame the context allowing meaningful comparisons by researchers and providing concrete examples for practitioners.
Adaptive Spatial Modulation for Visible Light Communications With an Arbitrary Number of Transmitters

As a power- and bandwidth-efficient modulation scheme, the optical spatial modulation (SM) technique has recently drawn increased attention in the field of visible light communications (VLC). To guarantee the number of bits mapped by the transmitter’s index at each timeslot is an integer, the number of transmitters (i.e., light-emitting diodes) in the SM-based VLC system is often set be a power of two. To break the limitation on the required number of transmitters and provide more design flexibility, this paper investigates the SM-based VLC with an arbitrary number of transmitters. Initially, a channel-adaptive bit mapping (CABM) scheme is proposed, which includes three steps: bit mapping in the space domain, bit mapping in the signal domain, and channel adaptive mapping. The proposed CABM scheme allows operation with an arbitrary number of transmitters, and is verified to be an efficient scheme through numerical results. Based on the CABM scheme, the information-theoretical aspects of the SM-based VLC are analyzed. The theoretical expression of the mutual information is first analyzed. However, it is very hard to evaluate system performance. To obtain more insights, a lower bound of the mutual information is derived, which is in closed form. Both theoretical analysis and numerical results show that the gap between the mutual information and its lower bound is small. Finally, to further improve the system performance, the precoding scheme is proposed for the SM-based VLC. Numerical results show that the system performance improves dramatically when using the proposed precoding scheme.