Miracle-dz/UniFAR-FTUs huggingface dataset:
Stress recognition using connected devices: experimentation feedback

The research purpose is to study the impact’s use of connected devices on cardiovascular diseases. One of our objective is stress recognition during daily routine life. To achieve that a long term experimentation have been conducted. This longitudinal empirical research study aided by connected devices enabling psycho-physiological monitoring to study the correlation between emotional states including stress levels and prognosis of cardiovascular disease. In this paper, we will present the main participant’s feedback concerning the conducted experimentation using wearables sensors. This manuscript explains participant selection. It will not treat data conducted from this experiment or show numerical results. It is a statistical feedback concerning the experimentation protocol. We will clarify the protocol strengths and weaknesses. Our main motivation is to give an opinion to other research and to inspire them if they want to conduct a similar experimentation.
Stanford typed dependencies manual

The Stanford typed dependencies representation was designed to provide a simple description of the grammatical relationships in a sentence that can easily be understood and effectively used by people without linguistic expertise who want to extract textual relations. In particular, rather than the phrase structure representations that have long dominated in the computational linguistic community, it represents all sentence relationships uniformly as typed dependency relations. That is, as triples of a relation between pairs of words, such as “the subject of distributes is Bell. ” Our experience is that this simple, uniform representation is quite accessible to non-linguists thinking about tasks involving information extraction from text and is quite effective in relation extraction applications. Here is an example sentence:
The morphological analysis of Arabic verbs by using the surface patterns

In this article, we present a new system of morphological analysis using the surface patterns of the word to be analyzed. This approach required in the initial phase a classification of all Arabic verb roots by using the morphological rules of these last, and the second phase is the construction of data base of conjugated surface patterns. This system is capable to analyze all Arabic verbs by decomposing the word to the prefixes, suffixes and roots. This approach has been tested on a corpus of 4000 verbs, the results were encouraging, and the error rate is 4%.
RESEARCH REVIEW FOR DIGITAL IMAGE SEGMENTATION TECHNIQUES

Evaluating the previous work is an important part of developing segmentation methods for the image analysis techniques. The aim of this paper is to give a review of digital image segmentation techniques. The problems of digital image segmentation represent great challenges for computer vision. The wide range of the problems of computer vision may make good use of image segmentation. This paper study and evaluate the different methods for segmentation techniques. We discuss the main tendency of each algorithm with their applications, advantages and disadvantages. This study is useful for determining the appropriate use of the image segmentation methods and for improving their accuracy and performance and also for the main objective, which designing new algorithms.
Weighted Dynamic Time Warping for Grid-Based Travel-Demand-Pattern Clustering: Case Study of Beijing Bicycle-Sharing System

Many kinds of spatial–temporal data collected by transportation systems, such as user order systems or automated fare-collection (AFC) systems, can be discretized and converted into time-series data. With the technique of time-series data mining, certain travel-demand patterns of different areas in the city can be detected. This study proposes a data-mining model for understanding the patterns and regularities of human activities in urban areas from spatiotemporal datasets. This model uses a grid-based method to convert spatiotemporal point datasets into discretized temporal sequences. Time-series analysis technique dynamic time warping (DTW) is then used to describe the similarity between travel-demand sequences, while the clustering algorithm density-based spatial clustering of applications with noise (DBSCAN), based on modified DTW, is used to detect clusters among the travel-demand samples. Four typical patterns are found, including balanced and unbalanced cases. These findings can help to understand the land-use structure and commuting activities of a city. The results indicate that the grid-based model and time-series analysis model developed in this study can effectively uncover the spatiotemporal characteristics of travel demand from usage data in public transportation systems.
Cross-point Resistive Memory

Emerging computational resistive memory is promising to overcome the challenges of scalability and energy efficiency that DRAM faces and also break through the memory wall bottleneck. However, cell-level and array-level nonideal properties of resistive memory significantly degrade the reliability, performance, accuracy, and energy efficiency during memory access and analog computation. Cell-level nonidealities include nonlinearity, asymmetry, and variability. Array-level nonidealities include interconnect resistance, parasitic capacitance, and sneak current. This review summarizes practical solutions that can mitigate the impact of nonideal device and circuit properties of resistive memory. First, we introduce several typical resistive memory devices with focus on their switching modes and characteristics. Second, we review resistive memory cells and memory array structures, including 1T1R, 1R, 1S1R, 1TnR, and CMOL. We also overview three-dimensional (3D) cross-point arrays and their structural properties. Third, we analyze the impact of nonideal device and circuit properties during memory access and analog arithmetic operations with focus on dot-product and matrix-vector multiplication. Fourth, we discuss the methods that can mitigate these nonideal properties by static parameter and dynamic runtime co-optimization from the viewpoint of device and circuit interaction. Here, dynamic runtime operation schemes include line connection, voltage bias, logical-to-physical mapping, read reference setting, and switching mode reconfiguration. Then, we highlight challenges on multilevel cell cross-point arrays and 3D cross-point arrays during these operations. Finally, we investigate design considerations of memory array peripheral circuits. We also portray an unified reconfigurable computational memory architecture.
On a robust model-reference adaptive control system

A new type of model-reference adaptive control system is presented. The system state estimator of this adaptive system is described by the differential equation of the reference model with the feedback speeding up the estimator action during the tuning-up of the controller parameters and vanishing when the system performance approaches that of the reference model. This model-reference adaptive control system can be used to obtain the requested dynamics of the closed-loop system, which can be chosen within a wide range of speed with respect to the dynamics of the plant. Results of a simulation study show that the proposed controller can be used to control an unstable plant as well as to get a fast and well-damped response of a plant with a very small damping ratio and relatively high undamped natural frequency. The proposed approach to the estimation of the system state results in very fast estimator performance during the tuning process of the controller and in an estimation error approaching zero. This is because the estimated system performance and the estimator performance both approach that of the reference model. <<ETX>>
SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage

With the increasing democratization of electronic media, vast information resources are available in less-frequently-taught languages such as Swahili or Somali. That information, which may be crucially important and not available elsewhere, can be difficult for monolingual English speakers to effectively access. In this paper we present an end-to-end cross-lingual information retrieval (CLIR) and summarization system for low-resource languages that 1) enables English speakers to search foreign language repositories of text and audio using English queries, 2) summarizes the retrieved documents in English with respect to a particular information need, and 3) provides complete transcriptions and translations as needed. The SARAL system achieved the top end-to-end performance in the most recent IARPA MATERIAL CLIR+summarization evaluations. Our demonstration system provides end-to-end open query retrieval and summarization capability, and presents the original source text or audio, speech transcription, and machine translation, for two low resource languages.
An osmotic computing infrastructure for urban pollution monitoring

Urban pollution control systems suffer from the presence of fixed stations in a greater number than mobile monitoring devices. Data gathered from such stations provide detailed and reliable information, thanks to equipment quality and effective measuring protocols, but these sampled data are gathered from very limited areas and through discontinuous monitoring campaigns. Fortunately, the spread of technologies for mobility has fostered the development of new approaches like mobile crowdsensing (MCS), increasing the chances of using mobile devices, even personal ones, as suitable sensors for the urban monitoring scenario. Nevertheless, one of the open challenges is the management of integrated heterogeneous data flows, differing in terms of typology, technical specifications (eg, transmission protocols), and semantics. The osmotic computing paradigm aims at creating an abstract level between mobile devices/Internet‐of‐Things devices and a cloud platform, which enables opportunistic filtering and the addition of metadata for improving the data processing flow. This work focuses on the design and development of a middleware that integrates data coming from mobile and Internet‐of‐Things devices specifically deployed in urban contexts using the osmotic computing paradigm. Moreover, a component of the osmotic membrane has been developed for security management.
Mercury: a Model for Live Remote Debugging in Reflective Languages

Remote debugging facilities are a technical necessity for devices that have limited computing power to run an IDE (e.g., smartphones), lack appropriate input/output interfaces (display, keyboard, mouse) for programming (e.g mobile robots) or are simply unreachable for local development (e.g cloud-servers). Yet remote debugging solutions can prove awkward to use due to their distributed nature. Empirical studies show us that on average 10.5 minutes per coding hour (over five 40-hour work weeks per year) are spend for re-deploying applications while fixing bugs or improving functionality. Moreover current solutions lack facilities that would otherwise be available in a local setting because its difficult to reproduce them remotely. Our work identifies three desirable properties that an ideal solution for remote debugging should exhibit, namely: run-time evolution, semantic instrumentation and adaptable distribution. Given these properties we propose and validate Mercury, a live remote debugging model and architecture for reflective OO languages.
Supporting energy-efficient choices using Rasch-based recommender interfaces

2, 3 When analyzing ways in which people save energy, most researchers and policy makers conceptually differentiate between curtailment (e.g. unplugging chargers) and efficiency measures (e.g. installing PV cells). However, such a two-dimensional approach is suboptimal from both a conceptual and a policy perspective, as it does not consider individual differences that determine energy-saving behavior. We propose a different, one-dimensional approach, applying Campbell’s Paradigm through the Rasch model, in which both curtailment and efficiency measures are intermixed on a single scale and ordered according to their behavioral costs. By matching these behavioral costs to individual energy-saving attitudes, we investigate to what extent attitude-tailored energy-saving advice can help consumers to save energy. We present the results of two studies. The first study (N = 263) reliably calibrated a onedimensional Rasch scale that consists of 79 energy-saving measures, suitable for advice. The second study employed this scale to investigate how users (N = 196) evaluate attitude-tailored 2 Parts of this chapter appeared as: Starke, A. , Willemsen, M. C. , & Snijders, C. (2015). Saving Energy in 1-D: Tailoring Energy-saving Advice Using a Rasch-based Energy Recommender System. In DMRS (pp. 5–8). 3 At the time of publication, this chapter was submitted for review: Starke, A.D., Willemsen, M.C. , & Snijders, C.C. P. A unidimensional scale for attitude-tailored energy-saving advice in a web-based recommender system. Energy Research and Social Science. 38 | C h a p t e r 1 : A m e a s u r e m e n t s c a l e f o r a d v i c e energy-saving advice in a web-based energy recommender system. Results indicate that Rasch-based recommendations can be used to effectively tailor energy-saving advice and that such attitude-tailored advice is more adequate than a number of non-personalized approaches.
Uma ferramenta multiagente baseada em conhecimento para anotação de proteínas : um estudo de caso para o Fungo Saccharomyces cerevisiae

Identifying biological function of sequences is a key activity in genome projects. This task is done in the annotation step, which has two phases. In the manual phase, biologists use their knowledge and experience to determine the function for each sequence, based on the results produced by the automatic phase, where tools and data bases are used to predict functional annotation. This dissertation presents BioAgents-Prot, a knowledge based multiagent tool, which simulates biologists expertise to annotate proteins. BioAgents-Prot is defined with an approach of cooperative agents, where specialized intelligent agents work together to suggest proper manual annotation. The proposed three-layer architecture was implemented with Java Agent DEvelopment Framework-JADE and Drools (a rule-based inference engine). To assess performance, transcript annotations of the Saccharomyces cerevisiae fungus were compared to the annotations suggested by BioAgents-Prot. Using basic rules that represents the annotation reasoning, we obtained 95.84% of sensitivity, 93.22% of specificity, 98.40% of F1-score and 0.80 of MCC, which shows the usefulness of BioAgents-Prot in annotation step of transcriptome projects.
Securing the ADS-B Protocol for Attack-resilient Multiple UAV Collision Avoidance

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is being adopted for use in unmanned aerial vehicles (UAVs) as the primary source of information for emerging multi-UAV collision avoidance algorithms. The lack of security features in ADS-B leaves any processes dependent upon the information vulnerable to a variety of threats from compromised and dishonest UAVs. This could result in substantial losses or damage to properties. This research proposes a new distance-bounding scheme for verifying the distance and flight trajectory in the ADS-B packets from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify dishonest UAVs and avoid collisions. The scheme was implemented and tested in the SITL (Software In The Loop) simulator to verify its ability to detect dishonest UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.
Marketing and artificial intelligence: with neural net market segmentation example

While the domain of marketing has developed many hypothesizes and theories much of it is still heuristic based. both in research and practice, marketers must deal with problems in the data, partially proven hypotheses, etc. which results in such uncertainty that extensive experience and understanding of both research literature and proven practices is necessary to successfully operate in this field. This paper outlines some of the potential areas for artificial intelligence solutions to marketing problems. A neural net example segmented two vectors of demographic data into several identifiable regions. The neural net approach to discrimination is applicable to many similar business problems such as bond or bankruptcy classifications, credit ratings, etc.<<ETX>>
Spectral self-coherence restoral: a new approach to blind adaptive signal extraction using antenna arrays

A new approach to blind adaptive signal extraction using narrowband antenna arrays is presented. The approach has the capability to extract communication signals from cochannel interference environments using only known spectral correlation properties of those signals, i.e. without using knowledge of the content or direction of arrival of the transmitted signal, or the array manifold or background noise covariance of the receiver, to train the antenna array. The class of spectral self-coherence restoral (SCORE) objective functions is introduced, and algorithms for adapting antenna arrays to optimize these objective functions are developed. Using the theory of spectral correlation, it is shown by analysis and simulation that these algorithms maximize the signal-to-interference-and-noise ratio at the output of the narrowband antenna array when a single communication signal with spectral self-coherence at a known value of frequency separation, along with an arbitrary number of interferers without spectral self-coherence at that frequency separation, are impinging on the array. >
Dynamic request distribution for enhanced Quality of Service

The emergence of Web-services as an open components supporting ﬂexible and inexpensive set of distributed applications as well as exploiting them as a promising solution for integration with other application and providers of software-hardware resources is very much in demand. Using Web-services simpliﬁes and enhances system functionality because of the availability of programs interaction with each other through Internet using open protocols. Thereby it is necessary to provide QoS provision issues such as distribution of request streams, enhanced eﬃciency of operations at peak loads. One of the ways to tackle these issues is to apply dynamic request distribution which ensures continuity of data transfer and processing ignoring crashes and equipment failures, redis-tribution of data ﬂow to the available nodes in case of their loss. Abovementioned can be achieved using certain heuristics based on methods of Mathematical statistics and Probability modeling. Moreover, we provide analysis of methods and models developed for QoS provision.
Four-branch tree: highly efficient Boolean queries over encrypted cloud data

This work aims to design highly efﬁcient searchable encryption (SE) schemes to process Boolean queries over outsourced data ﬁles on untrusted public clouds while preserving users’ privacy. Many tree-based SE schemes support sub-linear conjunctive queries. However, all the trees suffer from a logarithmic multiplicative overhead in each search process. To make the tree work as efﬁciently as possible, we present a novel tree data structure called four-branch tree (FBTree). Our core design is to make a tree node have four branches, which help the searching process to access the desired tree nodes quickly. FBTree acts as an efﬁcient inverted index, but it is still a tree data structure. Based on this, two schemes are provided for different usage scenarios: one achieves nearly-optimal search complexity and strong adaptive security for the efﬁciency-ﬁrst environment, and the other is a sub-linear Boolean-query scheme via Oblivious RAM for security-ﬁrst settings. Several real datasets are used to evaluate FBTree performance. Testing results demonstrate that the FBTree structure has high efﬁciency and scalability for encrypted Boolean searches.
Register allocation and spill complexity under SSA

This report deals with the problem of choosing which variables to spill during the register allocation phase. Spilling is used when the number of variables is higher than the number of registers, and consists of storing the value of a variable in memory and loading it when necessary. The problem is that instructions dealing with memory are time-consumming. Hence the goal is to minimize the amount of spilled variables, which is a highly studied problem for compiler design, but nevertheless NP-complete. Meanwhile, a program under SSA form has the interesting property that on cases where spill is unnecessary, the problem of register allocation is not anymore NP-complete but polynomial. The interesting question is: can we solve the spilling problem under SSA, come back from SSA by splitting live-ranges as SSA does and finaly use classical register allocator? We show in this report that unfortunately many formulations of the spilling problem are also NP-complete under SSA form. In particular, the node-deletion approach used in most compilers remains NP-complete on most cases even on basic-blocks. The only polynomial solution has a too high complexity in practice. But this first advanced study on the complexity of the spill problem under SSA greatly helps to the understanding and gives directions for polynomial approximations. In this report, we also talk about the problem of splitting variables aggressively as in SSA. This shows the weakness of the "iterated register coalescing" regarding false interferences created by the adding of move instructions. We then implemented in a production compiler for st200 an interference graph based on liveness analysis and value numbering: two variables interfere if at one's definition the other is live and carries another value. The experiments we made and present in this report show that with such an interference graph aggressive splitting is not a problem.
Binary image reconstruction from four projections

Addresses the problem of reconstructing an image from two pairs of its orthogonal projections. The range and support information of the image function is utilised in conjunction with the available projections to develop an iterative reconstruction method; the iterative algorithm is an error energy reduction scheme. Reconstruction results for two classes of image functions are presented. <<ETX>>
A fast alignment-free bioinformatics procedure to infer accurate distance-based phylogenetic trees from genome assemblies

This paper describes a novel alignment-free distance-based procedure for inferring phylogenetic trees from genome contig sequences using publicly available bioinformatics tools. For each pair of genomes, a dissimilarity measure is first computed and next transformed to obtain an estimation of the number of substitution events that have occurred during their evolution. These pairwise evolutionary distances are then used to infer a phylogenetic tree and assess a confidence support for each internal branch. Analyses of both simulated and real genome datasets show that this bioinformatics procedure allows accurate phylogenetic trees to be reconstructed with fast running times, especially when launched on multiple threads. Implemented in a publicly available script, named JolyTree, this procedure is a useful approach for quickly inferring species trees without the burden and potential biases of multiple sequence alignments.