Miracle-dz/UniFAR-FTUs huggingface dataset:
Neutralization of the Tap/Trill Contrast in the Bilingual Creole-Spanish Community of the Archipelago of San Andres, Colombia

This study examines the segmental duration of non-vibrant rhotics in a language contact scenario in the Western Caribbean, where an English-based Creole co-exists with Spanish: The Archipelago of San Andres, Colombia. The unexplored phenomenon of the neutralization of the tap/trill contrast merits a thorough analysis to examine the effects of language contact in this Creole-Spanish bilingual population. To do this, the segmental duration of 619 non-vibrant, intervocalic taps and trills were compared in three generations of Raizal Spanish (the bilingual Spanish variety) and contrasted with the duration of Continental Spanish (the monolingual variety spoken by Colombian immigrants from Continental Colombia). While there are language-specific differences in rhotic duration between Creole and Spanish, results show that Raizal Spanish has longer durations that differ from the monolingual Spanish variety. A cross-generational examination revealed that the neutralizations of the tap/trill contrast in older bilinguals, as third-generation speakers, are converging toward the monolingual variety, distancing themselves from the older second and first generations. This phenomenon signals a change in progress resulting from diverging variation patterns of duration in tap/trill segments in generations of bilingual Raizales. These findings suggest a changing sociolinguistic panorama in which stable bilingualism is taking place among younger individuals.
Model-based plant phenomics on morphological traits using morphometric descriptors

The morphological traits of plants contribute to many important functional features such as radiation interception, lodging tolerance, gas exchange efficiency, spatial competition between individuals and/or species, and disease resistance. Although the importance of plant phenotyping techniques is increasing with advances in molecular breeding strategies, there are barriers to its advancement, including the gap between measured data and phenotypic values, low quantitativity, and low throughput caused by the lack of models for representing morphological traits. In this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits. Geometric morphometric approaches pave the way to a general-purpose method applicable to single units. Hierarchical structures composed of an indefinite number of multiple elements, which is often observed in plants, can be quantified in terms of their multi-scale topological characteristics using topological data analysis. Theoretical morphological models capture specific anatomical structures, if recognized. These morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets. Moreover, we discuss the future possibilities that a system of model-based measurement and model refinement would solve the lack of morphological models and the difficulties in scaling out the phenotyping processes.
Cyber-Attack Prediction Based on Network Intrusion Detection Systems for Alert Correlation Techniques: A Survey

Network Intrusion Detection Systems (NIDS) are designed to safeguard the security needs of enterprise networks against cyber-attacks. However, NIDS networks suffer from several limitations, such as generating a high volume of low-quality alerts. Moreover, 99% of the alerts produced by NIDSs are false positives. As well, the prediction of future actions of an attacker is one of the most important goals here. The study has reviewed the state-of-the-art cyber-attack prediction based on NIDS Intrusion Alert, its models, and limitations. The taxonomy of intrusion alert correlation (AC) is introduced, which includes similarity-based, statistical-based, knowledge-based, and hybrid-based approaches. Moreover, the classification of alert correlation components was also introduced. Alert Correlation Datasets and future research directions are highlighted. The AC receives raw alerts to identify the association between different alerts, linking each alert to its related contextual information and predicting a forthcoming alert/attack. It provides a timely, concise, and high-level view of the network security situation. This review can serve as a benchmark for researchers and industries for Network Intrusion Detection Systems’ future progress and development.
Deep-Learning-based Fuzzy Symbolic Processing with Agents Capable of Knowledge Communication

The authors propose methods for reproducing deep learning models using a symbolic representation from learned deep reinforcement learning models and building agents capable of knowledge communication with humans. It is difficult for humans to understand the behaviour of agents using deep reinforcement learning, and to inform agents of the state of the environment and to receive actions from the agents. In this paper, fuzzified states of the environment and agent actions are represented by rules of first-order predicate logic, and models using symbolic representation are generated by learning such rules. By replacing deep reinforcement learning models with models using a symbolic representation, it is possible for humans to inform the state of the environment and add rules to the agents. As a result of the experiments, the authors can reproduce trained deep reinforcement learning models with high match rate for two types of reinforcement learning simulation environments. Using reproduced models, the authors build agents that can communicate with humans that have yet be realized thus far. This proposed method is the first case of building agents capable of knowledge communication with humans using trained reinforcement learning models.
An Analysis of Competency of Management Teachers in Using Different Teaching Methods in Affiliated Colleges in Bengaluru

Teaching methods can be categorised into two broad categories namely teacher – centered approach and a responsive, collaborative learner – centered approach. The purpose of this study was to understand the competence of management teachers in using different teaching methods in affiliated colleges in urban Bengaluru. The objectives of this study was to (i) To analyse the competence level of B-School faculty members in using the different teaching methods; (ii) To compare the teaching methods of male and female faculty members of B-School; (iii) To evaluate the teaching methods of B-School faculty with different age groups; (iv) To assess the teaching methods of B-School faculty having different designation; and (v) To identify the latent factors that comprises the different teaching methods. A structured self administered survey questionnaire was developed for data collection. The sampling frame for the study included permanent faculty members working in University affiliated B-Schools in urban Bangalore. As per the analysis lecture, assignments, seminar and case study methods were the frequently used teaching methods by the faculty methods; group discussion, individual/group project, and role play were frequently but not adequately used teaching methods while simulations, field studies and workshop were the least frequently used teaching methods.
Application of Mind Mapping in Poster Design Classroom Teaching and Practice Guiding

Mind mapping is an effective thinking tool of radiant thinking expression. In the poster design course, training of mind mapping encourages students in an open mind with arousing good ideas. At the same time, mind mapping makes mentality of design clear and expression of design accurate. So the efficiency of classroom teaching and design practice will be improved.
Super Resolution-Based Beam Selection With Hierarchical Codebook in mmWave Communication

Beamforming is regarded as a promising technique for future wireless communication systems. In this regard, codebook-based beamforming offers satisfactory performance with acceptable computational complexity; however, it requires a high power-consumed beam overhead. To achieve balance between the utilized beam overhead and the achieved spectral efficiency performance, we propose a super-resolution-based scheme using a hierarchical codebook. We consider beam sweeping as an inference problem, where low-resolution beam radiating responses are used as an input, and high-resolution beam sweeping responses are output. Simulation results confirm that the proposed scheme exhibits extraordinary performance-overhead tradeoffs as compared with state-of-the-art codebook-based beamforming designs.
[Solution] Matchmaker Paxos: A Reconfigurable Consensus Protocol

The paper presents Matchmaker Paxos/Multi-Paxos, a crash fault-tolerant consensus implementation and state machine replication system with vertical reconﬁguration. The main contribution is the reconﬁguration protocol, a critical component of Consensus implementations that is often overlooked by the research community, but that is critical in practice. Reviewers share the same common feedback, the paper is relevant and represents a valuable addition to the literature of high-performance reconﬁguration techniques for consensus. Abstract State machine replication protocols, like MultiPaxos and Raft, are at the heart of numerous distributed systems. To tolerate machine failures, these protocols must replace failed machines with new machines, a process known as reconﬁguration. Reconﬁguration has become increasingly important over time as the need for frequent reconﬁguration has grown. Despite this, reconﬁguration has largely been neglected in the literature. In this paper, we present Matchmaker Paxos and Matchmaker MultiPaxos, a reconﬁgurable consensus and state machine replication protocol respectively. Our protocols can perform a reconﬁguration with little to no impact on the latency or throughput of command processing; they can perform a reconﬁguration in a few milliseconds; and they present a framework that can be generalized to other replication protocols in a way that previous reconﬁguration techniques can not. We provide proofs of correctness for the protocols and optimizations, and present empirical results from an open source implementation showing that throughput and latency do not change signiﬁcantly during a reconﬁguration.
EFFECT OF WORK ENVIRONMENT AND EMPLOYEE ENGAGEMENT ON JOB PERFORMANCE OF PUBLIC RELATION STAFF IN LUXURY HOTELS IN JAKARTA

The aim of this study is to examine the relationship between working environment and employee engagement toward job performance of the employees of public relation (PR) staff in five-star hotels in province of Jakarta, Indonesia. From a preliminary survey of 100 customers to measure customers' perceptions of the performance indicatedthat 34% of respondents rated the performance of those employees in the is still poor and needs to be improved. This research using structural equation modeling as an analysis tools. Observed variables are work environment (6 indicators) and employee engagement (34 indicators) as exogeneous variable and job performance (15 indicators) as endogenous variable. The structural model analysis that measure the effect of work environment on job performanceshowedt value and regression coefficient are 4.78 and 0.64 respectively. Analysis result of the effect of employee engagement on job performance, obtained t value and regression coefficient are 5.39 and 0.75 respectively. The R² value of 0.565 shows how work environment and employee engagement can play a positive and significant role together to improve job performance of PR staff of five stars hotelsin province of Jakarta, Indonesia.
Sequential Models for Endoluminal Image Classification

Wireless Capsule Endoscopy (WCE) is a procedure to examine the human digestive system for potential mucosal polyps, tumours, or bleedings using an encapsulated camera. This work focuses on polyp detection within WCE videos through Machine Learning. When using Machine Learning in the medical field, scarce and unbalanced datasets often make it hard to receive a satisfying performance. We claim that using Sequential Models in order to take the temporal nature of the data into account improves the performance of previous approaches. Thus, we present a bidirectional Long Short-Term Memory Network (BLSTM), a sequential network that is particularly designed for temporal data. We find the BLSTM Network outperforms non-sequential architectures and other previous models, receiving a final Area under the Curve of 93.83%. Experiments show that our method of extracting spatial and temporal features yields better performance and could be a possible method to decrease the time needed by physicians to analyse the video material.
Köbner and Pastia Signs in Acute Hemorrhagic Edema of Young Children: Systematic Literature Review

Acute hemorrhagic edema of young children, a benign skin-limited vasculitis, predominantly affects children 2 years of age or younger. The prevalence and clinical features of the Köbner and Pastia signs have never been systematically investigated in this vasculitis. To address this issue, we analyzed the data contained in the Acute Hemorrhagic Edema Bibliographic Database, which incorporates all reports on hemorrhagic edema published after 1969. A total of 339 cases (236 males and 103 females; 11 (8–18) months of age; median and interquartile range) were documented with at least 1 photograph and therefore included in this analysis. The Köbner sign occurred in 24 cases (14 males and 10 females; 11 (7–17) months of age), the Pastia sign in 51 cases (39 males and 12 females; 11 (8–15) months of age), and both Köbner and Pastia signs in 8 cases (7 males and 1 female; 11 (7–17) months of age). The lower legs, thighs, waistline, and groin were the regions that were most commonly affected with the Köbner sign, while the ankle, feet, cubital fossa, and elbow were most affected with the Pastia sign. The Köbner and Pastia signs are clinically relevant; they occur in about every fourth child affected with hemorrhagic edema and do not influence the disease progression.
The magnitude and predictors of cervical squamous intraepithelial lesions among women in Enugu, Nigeria: a cross-sectional study of women in a low-resource setting

Introduction the prevalence of cervical squamous intraepithelial lesion is not well appreciated in most low-income countries. The study aimed to determine the level of awareness, prevalence and the pattern of squamous intraepithelial lesions and predictors for abnormal Pap smear reports (development of pre-malignant lesions of the cervix) among women attending various clinics in a tertiary health facility in Enugu, Nigeria. Methods a cross-sectional study of 207 female patients attending various clinics of Enugu State University Teaching Hospital, Parklane, Enugu between June and August 2017 was undertaken. Structured interviewer-administered questionnaires were used for data collection while cervical smears were collected from the patients and sent for cytology. Data analysis was done using the Statistical Package for the Social Sciences (SPSS) version 22.0. The results were presented as means, standard deviations, frequencies and proportions. Pearson´s Chi-square test was used to test for associations between categorical variables and statistical significance was set at a p-value of < 0.05. Results the levels of awareness of cervical cancer and the screening methods among the respondents were 76.8% and 36.7% respectively. The overall knowledge of cervical cancer and its screening was poor (6.8% and 29.0% respectively). The prevalence of pre-malignant lesions of the cervix among the respondents was 15.0% with low grade squamous intraepithelial lesion (LGSIL) having the highest frequency (38.7%). Among all the other risk factors for the development of premalignant lesions of the cervix among the respondents, a report of abnormal pap (positive) smear report was significantly associated with only age ≥35 years (χ2=5.723; p=0.017). The same age of 35 years and above also correctly predicted abnormal Pap smear reports among other factors (AOR = 3.02, 95% CI = 1.16 - 7.89, p = 0.024). Conclusion the awareness of cervical cancer and cervical cancer screening was high but the overall knowledge on cervical cancer and its screening was very poor among the respondents. The prevalence of pre-malignant lesions of the cervix was high, and the commonest abnormal smear was LGSIL. Only age 35 years and above correctly predicted the occurrence of abnormal Pap smear reports among the respondents.
Detection of Pathological Markers of Neurodegenerative Diseases following Microfluidic Direct Conversion of Patient Fibroblasts into Neurons

Neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease are clinically diagnosed using neuropsychological and cognitive tests, expensive neuroimaging-based approaches (MRI and PET) and invasive and time-consuming lumbar puncture for cerebrospinal fluid (CSF) sample collection to detect biomarkers. Thus, a rapid, simple and cost-effective approach to more easily access fluids and tissues is in great need. Here, we exploit the chemical direct reprogramming of patient skin fibroblasts into neurons (chemically induced neurons, ciNs) as a novel strategy for the rapid detection of different pathological markers of neurodegenerative diseases. We found that FAD fibroblasts have a reduced efficiency of reprogramming, and converted ciNs show a less complex neuronal network. In addition, ciNs from patients show misfolded protein accumulation and mitochondria ultrastructural abnormalities, biomarkers commonly associated with neurodegeneration. Moreover, for the first time, we show that microfluidic technology, in combination with chemical reprogramming, enables on-chip examination of disease pathological processes and may have important applications in diagnosis. In conclusion, ciNs on microfluidic devices represent a small-scale, non-invasive and cost-effective high-throughput tool for protein misfolding disease diagnosis and may be useful for new biomarker discovery, disease mechanism studies and design of personalised therapies.
Modeling Power Consumption of Applications Software Running on Servers

Reducing power consumption in computational processes is important to software developers. Ideally, a tremendous amount of software design efforts goes into considerations that are critical to power efficiencies of computer systems. Sometimes, software is designed by a high-level developer not aware of underlying physical components of the system architecture, which can be exploited. Furthermore, even if a developer is aware, they design software geared towards mass end-user adoption and thus go for cross-compatibility. The challenge for the software designer is to utilize dynamic hardware adaptations. Dynamic hardware adaptations make it possible to reduce power consumption and overall chip temperature by reducing the amount of available performance. However these adaptations generally rely on input from temperature sensors, and due to thermal inertia in microprocessor packaging, the detection of temperature changes significantly lag the power events that caused them. This work provides energy performance evaluation and power consumption estimation of applications running on a server using performance counters. Counter data of various performance indicators are collected using the CollectD tool. Simultaneously, during the test, a Power Meter (TED5000) is used to monitor the actual power drawn by the computer server. Furthermore, stress tests are performed to examine power fluctuations in response to the performance counts of four hardware subsystems: CPU, memory, disk, and network interface. A neural network model (NNM) and a linear polynomial model (LPM) have been developed based on process count information gathered by CollectD. These two models have been validated by four different scenarios running on three different platforms (three real servers.) Our experimental results show that system power consumption can be estimated with an average mean absolute error (MAE) between 11% to 15% on new system servers. While on old system servers, the average MAE is between 1% to 4%. Also, we find that NNM has better estimation results than the LPM, resulting in 1.5% reduction in MAE of energy estimation when compared to the LPM. The detailed contributions of the thesis are as follows: (i) develop a non-exclusive test bench to measure the power consumption of an application running on a server; (ii) provide a practical approach to extracting system performance counters and simplifying them to get the model parameters; (iii) a modeling procedure is proposed and implemented for predicting the power cost of application software using performance counters. All of our contributions and the proposed procedure have been validated with numerous measurements on a real test bench. The results of this work can be used by application developers to make implementation-level decisions that affect the energy efficiency of software applications.
The cooling performance of forced air ventilation garments in a warm environment: the effect of clothing eyelet designs

Abstract Heat stress is a common danger for people who work or exercise in hot environments. A Newton manikin was used to evaluate the cooling performance of five forced air ventilation garments (AVGs) with newly designed eyelet sizes and positions, including no eyelets (control), small eyelets at the mid-back, large eyelets at the mid-back, small eyelets at both the mid-back and upper front, large eyelets at both the mid-back and upper front (abbr. CON, B1, B2, FB1, FB2, respectively). The AVGs in fans turned on (Fan-On) and turned off (Fan-Off) were measured in a constant temperature mode (CT, 34 °C, 69% RH, and 0.20 m/s) and a thermoregulatory control mode (TMC, 30 °C, 69% RH, and 0.2 m/s) to simulate human exercising and resting. Air volume between the skin and clothing was also measured using a 3 D laser scanner. FB1 resulted the highest heat loss both in the chest zone (109.2 W/m2) and the stomach zone (77.1 W/m2) in the Fan-On conditions, and it also resulted the lowest torso skin temperature, mean skin temperature and core temperature. The air volume of the eyelet designs in Fan-On was all reduced when compared to that of CON, with FB2 having the greatest reduction by 14.5%. The eyelet designs significantly reduced clothing bulkiness (p < 0.05), but had no significant effect on the torso heat loss (p > 0.05).
DEVELOPMENT PROCEDURES FOR THE SYSTEMATIC MEASUREMENT OF PARTS AND COMPONENTS, FROM AN ANALYTICAL PROGRAMS OF REVERSE ENGINEERING PERSPECTIVE

Reverse engineering can be used to enhance the teaching of the Metrology of parts and components because it requires on the one hand, the contextualization of objects reference and, on the other hand, requires the systematic implementation of programs and procedures in geometrical and dimensional measurement processes. In this article, 4 basic procedures are shown. All related to an analytical research program from Reverse Engineering, which can be used by students to perform proper measurement of parts. These procedures are: 1) Preliminary analysis, generation and parameterization of primitives, 2) Selection of the measuring device and verification of its calibration process, 3) Measurement operation and 4) Data analysis and information representation. The systematic implementation of the program and its procedures ensures a correct measurement process and encourages and guides students to the systematic study of dimensional metrology and Reverse Engineering of parts and components. Index Terms - Engineering Education, Reverse Engineering, Metrology.