Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequential Waterfilling for Adaptive Data Rate allocation in LoraWAN

LoRaWAN (Long Range Wide Area Network) is emerging as an attractive network infrastructure for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative "sequential waterfilling" strategy for assigning Spreading Factors (SF) to End-Devices (ED). Our design relies on three complementary approaches: i) equalize the Time-on-Air of the packets transmitted by the system's EDs in each spreading factor's group; ii) balance the spreading factors across multiple access gateways, and iii) keep into account the channel capture, which our experimental results show to be very substantial in LoRa. While retaining an extremely simple and scalable implementation, this strategy yields a significant improvement (up to 38%) in the network capacity over the legacy Adaptive Data Rate (ADR), and appears to be extremely robust to different operating/load conditions and network topology configurations.
Hybrid Code Networks using a convolutional neural network as an input layer achieves higher turn accuracy

The dialogue management is a task of conversational artificial intelligence. The goal of the dialogue manager is to select the appropriate response to the conversational partner conditioned by the input message and recent dialogue state. Hybrid Code Networks is one of the models of dialogue managers, which uses an average of word embeddings and bag-of-words as input features. We perform experiments on Dialogue bAbI Task 6 and Alquist Conversational Dataset. The experiments show that the convolutional neural network used as an input layer of the Hybrid Code Network improves the model's turn accuracy.
How Do Pronouns Affect Word Embedding

: Word embedding has drawn a lot of attention due to its usefulness in many NLP tasks. So far a handful of neural-network based word embedding algorithms have been proposed without considering the effects of pronouns in the training corpus. In this paper, we propose using co-reference resolution to improve the word embedding by extracting better context. We evaluate four word embeddings with considerations of co-reference resolution and compare the quality of word embedding on the task of word analogy and word similarity on multiple data sets. Experiments show that by using co-reference resolution, the word embedding performance in the word analogy task can be improved by around 1.88 % . We ﬁnd that the words that are names of countries are affected the most, which is as expected.
An Algorithm for Creating Malicious Free Absolute Trust Peers in P2P Networks

: Peer-to-peer (P2P) computing or networking is a distributed application architecture that partitions tasks or workloads between peers. The peers evaluate other peers based on their past interactions and then aggregate this information in the whole network. However it may not be the true reflection of past behavior of the peers. Moreover such type of aggregation gives only the relative ranking of peers without any absolute evaluation of their past. This is more significant when all the peers responding to a query, are malicious. In such a situation only the peer came to know that who is better among them without knowing their rank in the whole network. Hence to mitigate the attacks by malicious peers and to motivate the peers to share the resources effectively and securely, in this paper, a new algorithm is proposed which accounts for the past behavior of the peers and will estimate the absolute value of the trust of peers. Consequently, good peers or malicious peers are identified. The proposed algorithm converges at some global consensus much faster by choosing suitable parameters. Because of its absolute nature it will equally load all the peers in network. It will also reduce the inauthentic download in the network which was not possible in existing algorithms.
A PRELIMINARY PHYLOGENETIC ANALYSIS OF METAPENAEOPSIS (DECAPODA: PENAEIDAE) BASED ON MITOCHONDRIAL DNA SEQUENCES OF SELECTED SPECIES FROM THE INDO-WEST PACIFIC

Abstract Phylogenetic relationships within Metapenaeopsis remain largely unknown. The modern revision of the genus suggests that the shape of the petasma, followed by the presence of a stridulating organ, are the most important distinguishing taxonomic features. In the present study, phylogenetic relationships were studied among seven Metapenaeopsis species from the Indo-West Pacific based on partial sequences of mitochondrial 16S rRNA and cytochrome c oxidase I (COI) genes. Mean sequence divergence was 6.4% for 16S and 15.8% for COI. A strikingly large nucleotide distance (10.0% for 16S and 16.9% for COI) was recorded between M. commensalis, the only Indo-West Pacific species with a one-valved petasma, and the other species with a two-valved petasma. Phylogenetic analyses using neighbor-joining, maximum parsimony, and maximum likelihood generated mostly identical tree topologies in which M. commensalis is distantly related to the other species. Two clades were resolved for the remaining species, one with and the other without a stridulating organ, supporting the main groupings of the recent taxonomic revision. Results of the present study also indicate that the deep-water forms represent a relatively recent radiation in Metapenaeopsis.
SEASONALITY AND SPATIAL DISTRIBUTION OF PERACARIDS ASSOCIATED WITH THE BRYOZOAN BUGULA NERITINA IN ALGECIRAS BAY, SPAIN

Abstract The fouling community at Algeciras Bay exhibits the general features of other warm-temperate fouling communities in which the bryozoan Bugula neritina is a major competitor for space during summer. This bryozoan was sampled in order to study spatio-temporal changes of the peracaridan fauna of Algeciras Bay (Strait of Gibraltar). The results of this work point out the relevance of studying the life cycle patterns of both the living substratum and its associated fauna prior to analyzing the possible classification or ordination of the stations. There was a good correlation between the height of B. neritina and temperature and between the colony dry mass and the number of peracaridan individuals. Numerical analyses allowed the identification of two groups of stations based on the distribution and abundance of the peracaridan faunas in Algeciras Bay, the internal and the external stations. The external stations had higher diversity, regarding both evenness and species richness, than in the internal stations, where some species, e.g., Jassa marmorata, Phtisica marina, Ischyrocerus inexpectatus, were strongly dominant. Seasonal variation of the substratum, Bugula neritina, and the peracaridan fauna which lives on it minimized the differences between external and internal stations. The ability to utilize B. neritina as living space can be a key to the success of some peracaridan species such as Jassa marmorata, Ischyrocerus inexpectatus, and Podocerus variegatus. Moreover, the temporal and spatial offset in the maximal density shown by some amphipod species might indicate the existence of biological relationships such as competition or predation.
GENETIC DIVERGENCE AMONG LOCAL POPULATIONS OF THE JAPANESE FRESHWATER CRAB GEOTHELPHUSA DEHAANI (DECAPODA, BRACHYURA, POTAMIDAE) FROM SOUTHERN KYUSHU, JAPAN

Abstract Genetic relationships among 37 local populations of Geothelphusa dehaani from southern Kyushu, Japan, were examined by electrophoretic analysis at 15 loci encoding 12 enzymes and a general protein. Local populations from the mainland of Kagoshima Prefecture, southern Kyushu, were genetically interrelated, independent of body coloration (red, blue, or two-tone types). Populations from the islands neighboring the Kagoshima mainland were differentiated into two genetic groups, which are distantly related to each other, also independent of body coloration, except for the populations from the Koshikijima Islands, west of Kagoshima mainland. One group of island populations was genetically associated with the mainland populations, both forming a clade of a mainland lineage. The other group, recognized as an island lineage, was highly differentiated from the mainland lineage. Both lineages, mainland and island lineages corresponding to blue and red color types, respectively, were sympatrically distributed on Koshikijima Islands, thus possibly suggesting a secondary contact. It is suggested that the observed genetic differentiation among local populations of G. dehaani in southern Kyushu possibly resulted from geographic isolation, consistent with the past geological process of island formations in the region.
A fine-grained framework for quantifying secure management of state in object-oriented programs

Abstract Mismanagement of programs’ run-time state can lead to serious security vulnerabilities, and in object-oriented languages, the program state can be particularly difficult to reason about. In this paper, we outline a framework for assessing the extent to which mutable state is used in object-oriented programs, with a longer term aim of measuring the degree to which it is correlated with reported security vulnerabilities. The notion of method purity is used to characterize uses of mutable state. In previous work, several different and conflicting schemes for identifying pure methods in statically typed object-oriented languages have been proposed. Most existing tools measure only the presence or absence of a particular type of purity. This paper introduces a finer-grained classification of purity in object-oriented languages, in which five broad levels are extended with details of which additional effects (such as reading of mutable state and use of system I/O) are performed by a method. A portion of real-world code is analyzed to identify the way in which particular programming idioms make use of state. We confirm that a variety of different levels of purity occur in the analyzed packages, sometimes occurring in combination with additional computational effects (such as logging, system input, or reading from non-local, mutable state). Analysis of 46 methods from 6 classes found that 50% exhibited some level of purity, including 32% with strict purity (complete prohibition on mutation of variables).
Primer for archival tag data processing using R

This report provides detailed steps for downloaded archival tag data processing in Microsoft Excel and R. Depth and temperature time series data from implanted archival tags in Greenland turbot (Reinhardtius hippoglossoides) are used as a case study. Steps outlined include formatting measurements and standardizing units and time zones. After initial error checking in Microsoft Excel, the procedures for importing, compiling, formatting, and saving data in R are described. Instructions and R code are provided to filter the data and calculate basic metrics. Code is provided to create and save data visualizations that aid in the understanding of the data, detecting patterns, and identifying errors.
On the interpretation of null arguments in L2 Japanese by European non-pro-drop and pro-drop language speakers

We report that (i) European pro-drop language learners of Japanese as a foreign language (L1 Spanish) (pro-drop JFLs) allowed a sloppy interpretation of null arguments beginning at the primary stage of L2 development, and that (ii) European non-pro-drop JFL learners (non-pro-drop JFLs) did not permit a sloppy interpretation with null arguments even at an advanced level. Under Ishino’s (2012) framework, we argue that the results for the pro-drop JFLs follow from positive L1 transfer, given that Spanish, their first language, permits a sloppy interpretation with null subjects in some well-defined contexts (Duguine, 2013, 2014), and also that the non-pro-drop advanced JFLs’ availability of null arguments stems from the addition of a D-feature to the feature bundles of the target language.
DEA Optimization with Neural Network in Benchmarking Process

The object of research that will be examined in this study is the problem of benchmarking by using Data Envelopment Analysis (DEA). The result of benchmarking obtained through the DEA method in the form of benchmarking values should be studies as a pattern when there is a new data can be directly predicted. On this side required a well-known application of Artificial Neural Networks in studying existing patterns. The results of this study are in the form of optimization is performed on DEA method to guarantee the principle of quality assurance in detecting early the quality of a new pattern emerging. Based on the result of the research, we can predict emerging new patterns that become in efficient.
PROTOTIPE PENGENDALI SUHU DAN KELEMBABAN UNTUK COLD STORAGE MENGGUNAKAN MIKROKONTROLER ARDUINO ATMEGA328 DAN SENSOR DHT11

Food losses didefinisikan sebagai penurunan kualitas dan kuantitas bahan pangan yang dikonsumsi oleh manusia. Hal ini terjadi karena sistem refrigerasi yang kurang baik dan pengolahan pasca panen yang kurang efektif. Salahsatu komponen penting dalam sistem refrigerasi bahan makanan adalah cold storage. Dalam penelitian ini, sebuah prototipe cold storage direalisasikan menggunakan komponen utama sensor DHT11 dan mikrokontroler ATMega328 serta dikoneksikan melalui telepon genggam pengguna melalui modul GSM. Cold storage ini dirancang memiliki suhu ruangan sebesar 14 o C dan kelembabannya antara 70 % dan 72 %. Data suhu dan kelembaban dapat dideteksi oleh sensor DHT11 dan nilainya ditampilkan dalam penampil LCD. Selain ditampilkan dalam penampil LCD, data sensor dan kelembaban dikirim ke telepon genggam pengguna melalui modul GSM. Jika suhu ruang atau kelembaban melebihi batas yang diinginkan, maka buzzer berbunyi dan pengguna dapat mematikan sistem melalui telepon genggam. Hasil pengujian menunjukkan suhu dan kelembaban dapat dijaga sesuai dengan yang diinginkan. Respon waktu untuk mencapai setpoint dari kondisi awal mulai berjalan membutuhkan 12 menit untuk suhu dan 15 menit untuk kelembaban. Suhu dan kelembaban berfluktuasi di sekitar nilai referensinya dengan nilai steady state error sebesar 1 o C untuk suhu dan 4% untuk kelembaban.
Exploring the influence of culture on collaborative learning

As on-line learning becomes more ubiquitous, and multi-ethnic on-line classrooms become more commonplace, it becomes more crucial to explore cultural communication issues and how we can design on-line learning environments that can facilitate productive learning experiences under these conditions. Our short term research focus is to develop automatic on-line assessment technologies and adaptive support technologies as infrastructure for supporting and studying collaborative learning in multiple cultures. The specific objective of our international collaboration has been to explore the intersection between the technology research area of text classification and the behavioral research area of collaborative learning process analysis. Beyond simply being an application of existing technology to a well defined framework for discourse analysis, this collaboration has yielded interesting new technical challenges and findings (Donmez et al., 2005; Rosé et al., 2005; Stegmann et al., 2006; Wang et al., 2007; Wang et al., submitted), questions about behavioral research methodology (Gweon et al., 2005), and finally questions about design of new forms of collaboration support that may be enabled by this technology (Gweon et al., 2006; Wang et al., 2007a; Kumar et al., 2007). Using our automatic process analysis technology, we have achieved almost human reliability on automatic application of an existing collaborative learning process analysis coding scheme (Weinberger & Fischer, 2006) to newsgroup style data from a number of large studies of script based support for computer supported collaborative learning in Germany (Donmez et al., 2005; Wang et al., 2007). Using this same analysis technology in conjunction with adaptive support agents (Wang et al., 2006; Kumar et al., 2006), we have run successful collaborative learning studies both in Taiwan (Wang et al., 2007a) and in the US (Kumar et al., 2007). This inter-disciplinary research endeavor brings together three large bodies of work, namely work on international standards for assessment of achievement in science and math education (Chang, 2005; Chang & Tsai, 2005) from the science education community, text classification technology (Rosé & VanLehn, 2005; Wang et al., 2007) in the language technologies community, and work on scripted collaboration (Weinberger, 2003; Weinberger & Fischer, 2006) in the computer-supported collaborative learning community. An important outcome of our research to date has been the development of the publicly available toolkit, TagHelper tools http://www.cs. cmu.edu/~cprose/TagHelper.html), which has been developed to support the analysis of verbal data using text classification technology.
Artificial Intelligence for Ecological and Evolutionary Synthesis

The grand ambition of theorists studying ecology and evolution is to discover the logical and mathematical rules driving the world’s biodiversity at every level from genetic diversity within species to differences between populations, communities, and ecosystems. This ambition has been difficult to realize in great part because of the complexity of biodiversity. Theoretical work has led to a complex web of theories, each having non-obvious consequences for other theories. Case in point, the recent realization that genetic diversity involves a great deal of temporal and spatial stochasticity forces theoretical population genetics to consider abiotic and biotic factors generally reserved to ecosystem ecology. This interconnectedness may require theoretical scientists to adopt new techniques adapted to reason about large sets of theories. Mathematicians have solved this problem by using formal languages based on logic to manage theorems. However, theories in ecology and evolution are not mathematical theorems, they involve uncertainty. Recent work in Artificial Intelligence in bridging logic and probability theory offers the opportunity to build rich knowledge bases that combine logic’s ability to represent complex mathematical ideas with probability theory’s ability to model uncertainty. We describe these hybrid languages and explore how they could be used to build a unified knowledge base of theories for ecology and evolution. case study you explore using the Salix tritrophic system.
The Student-Centred Paradigm and the Optimization of the Learning Process

The paper aims at identifying the perceptions of students in regards to the problematic and dysfunctional aspects identified by them within the learning process in Romania, as well as identifying the possible solutions that would lead to the amelioration of the educational practice, with the purpose of optimizing the schools results of pupils/students. The target group was represented by a group of students enrolled in technical faculties which were asked to elaborate on the two mentioned aspects, referencing both their experience as students, as well as that of pupils. The results obtained following the processing and analysis of the answers converge on the necessity of respecting the requirements characteristic to the paradigm of adapting school to the necessities and particularities of the pupils. We note the fact that the national educational policies support and promote the principle of adapting the school to the requirements and possibilities of the pupils, at the level of educational objectives and courses of action stated within certain documents of educational policy aimed at the pre-university and university level, through which the achievement of a high-quality education is endeavoured, particularly through: the reassessment of the role of the pupil, placing his needs, interests, and requirements at the forefront of the educational proceedings, and assuring equal opportunity throughout the entire educational process. The problematic aspects identified within the educational process remain, however, valid, representing a discrepancy between the documents of educational policy and the educational practice. © 2017 Published by Future Academy www.FutureAcademy. org.uk
Quantification of Parkinson Tremor Intensity Based On EMG Signal Analysis Using Fast Orthogonal Search Algorithm

The tremor injury is one of the common symptoms of Parkinson's disease. The patients suffering from Parkinson's disease have difficulty in controlling their movements owing to tremor. The intensity of the disease can be determined through specifying the range of intensity values of involuntary tremor in Parkinson patients. The level of disease in patients is determined through an empirical range of 0-5. In the early stages of Parkinson, resting tremor can be very mild and intermittent. So, diagnosing the levels of disease is difficult but important since it has only medication therapy. The aim of this study is to quantify the intensity of tremor by the analysis of electromyogram signal. The solution proposed in this paper is to employ a polynomial function model to estimate the Unified Parkinson's Disease Rating Scale (UPDRS) value. The algorithm of Fast Orthogonal Search (FOS), which is based on identification of orthogonal basic functions, was utilized for model identification. In fact, some linear and nonlinear features extracted from wrist surface electromyogram signal were considered as the input of the model identified by FOS, and the model output was the UPDRS value. In this research, the proposed model was designed based on two different structures which have been called the single structure and parallel structure. The efficiency of designed models with different structures was evaluated. The evaluation results using K-fold cross validation approach showed that the proposed model with a parallel structure could determine the tremor severity of the Parkinson's disease with accuracy of 99.25% ±0.41, sensitivity of 97.17% ±1.9 and specificity of 99.72% ±0.18.
A Data Acquisition System for the Cone Penetration Test

A data acquisition system has been developed at the University of Adelaide for the electric cone penetration test. The system utilises a portable, IBM compatible, personal microcomputer for data storage and post-processing and a microprocessor interface for data acquisition, analogue-to-digital conversion, signal amplification and multiplexing, pre-processing, data display and temporary storage. Various components of the data collection system are discussed including both hardware and software and benefits, limitations and accuracy of a microcomputer-based data acquisition system are examined.
Violent Interaction Detection in Video Based on Deep Learning

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.