Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating FPGA architectures for System-on-Chip

This work describes the development of a System-on-Chip processor in the VTR flow and the investigation of a better FPG A architecture for a SoC processor. ODIN II, as a part of the VTR workflow, is modified to support the simulation of a SoC processor. In addition, the ability to support external logic memories was extended to the tool. The external memories are processed in a MIF file. The FPGA architecture specification file, as an input of the VTR workflow, requires exploration with different hard blocks, such as HB Memories, HB Adders and HB Multipliers. Experiments on simulating the SoC processor in the VTR flow for FPGAs show that an FPGA architecture with hard block (HB) Memories, 2-bit HB Adders and 36*36 HB Multipliers is better than other FPGA architectures for an ARM Core processor. The exploration of this work is also on supporting multiple SoC processors on FPGAs.
The Measurement, Treatment and Immunopathology of Leprosy Type 1 Reactions

Leprosy is a chronic granulomatous condition principally affecting the skin and peripheral nerves. It is caused by infection with the obligate intracellular pathogen Mycobacterium leprae. The host immune response of an infected individual determines the disease phenotype. The borderline states of the disease are complicated by immunologically mediated Type 1 reactions in up to 30% of people. Type 1 reactions cause inflammation of the skin and peripheral nerves and can lead to permanent nerve function impairment. The treatment of Type 1 reactions is with oral corticosteroids but there are few data concerning the optimal dose and duration of corticosteroid treatment. Clinical trials have been hampered due to a lack of a valid measure of disease severity. A clinical severity scale was developed and tested in Bangladesh and Brazil. It was shown to be valid and able to discriminate between mild and moderate and moderate and severe Type 1 reactions. It was also shown to be reliable with excellent inter-observer agreement. A double blind randomized controlled clinical trial of high dose intravenous methylprednisolone and prednisolone (total dose equivalent to 6.15 g of prednisolone) was compared to placebo infusion and prednisolone (total dose 2.52 g of prednisolone). There were no significant differences in the rate of adverse effects between the two study groups. A large proportion, almost 50%, of individuals in both arms required additional prednisolone. Only 20% of individuals with nerve function impairment completely recovered although another 50% did improve. Skin biopsies were taken from participants before and at two time points during corticosteroid therapy. These biopsies were stained with monoclonal antibodies directed against toll-like receptors 1, 2, 4 and 9. Toll-like receptor 2 is highly expressed in skin lesions of Type 1 reaction but high expression of toll-like receptor 1, 2 and 4 was found in non-reactional patients with borderline lepromatous and lepromatous leprosy. The expression in the skin of the toll-like receptors 1, 2 and 4 fell during corticosteroid therapy. The gene expression of toll-like receptor 2 and 4 fell during treatment and this change in gene expression was associated with disease outcome. The human acidic ribosomal protein P0 was validated as a control gene in PCR assays in this group of patients.
Enhancing the Stability of SEIG Connected Distribution System Using Reactive Power Control Capabilities of DFIG under Varying Wind Speeds

The increased level of penetration of wind generators into modern power system has significant effect on network operation. The time varying nature of wind speed has significant effect on performance of wind generator, therefore efficient mechanism for stabilizing the output of the wind generator is very much needed. Self-excited induction generators (SEIG) already existing in the network are sensitive to wind speeds. In this paper, a new method for voltage control of SEIG utilizing reactive power enhancing capabilities of doubly-fed induction generator (DFIG) is simulated and its effect on the network is analyzed for varying wind speeds. The choice of placing DFIG adjacent to SEIG or at another bus is also addressed in this paper with simulation results. The results show that this method of utilizing the reactive power capabilities of DFIG enhances voltage stability of SEIG as well as system stability.
Social media and democracy

Slowly approaching the second quarter of the 21st century, research on social media and its effects over democracy has quickly permeated across various fields in social sciences, particularly political communication. Based on accumulated evidence in this strand of literature, this paper briefly summarizes several established research areas. First, it highlights how social media facilitates individuals’ political expression. Second, it sheds light on how this enhanced communicative behavior has reinvigorated a more participatory society in democracy. Third, it examines social media’s democratic deficit mechanisms in regards to stagnant political knowledge acquisition. Finally, the paper offers a theoretical explanation to this lack of knowledge acquisition through the lenses of the ‘news-finds-me’ perception theory. Overall, the present manuscript explains specific ways in which social media helps and hinders the advancement of healthy democracies, thereby also providing promising guidelines for future research.
Internet Addiction: A Comparative Study Among Children in the State of Madhya Pradesh and Chhattisgarh

Background: The Internet is the leading and most resourceful foundation of information in the world today. Internet has become a part of many peoples, mostly young in everyday routine. There has been an explosive growth in the use of internet not only in India, but also worldwide in the last decade. Currently internet has become an important tool for education, entertainment and communication. Increased internet usage may lead to point of addiction, adverseintellectual, habituation, mental complications, corporal disturbance and social effects.India now has the world’s second-largest internet user population, with approximately, 460 million Internet users in 2017.This paper explores the research on how children and youth of depend on all type of gaining the knowledge and communication ininternet and then become addicts. Aim: The aim was study to find out the internet addiction among children in the state of Madhya Pradesh and Chhattisgarh, India. Method: A comparative study was conducted among children (n=70) of two district between Sagar (Madhya Pradesh) and Surajpur (Chhattisgarh), India, to assess the pattern of internet usage. Researcher have employed semi-structured interview schedule to collect primary data it’s includes like socio-economic profiles of the respondent with Young’s Internet Addiction Test Scale (IAT) and their age between 7-18 years old.The study time duration of January – May 2015 and data was analyzed using SPSS version 21.0. Result: Out of 70 participants 50% of the both districts. 42 (60%) were Males and 28 (40%) Females. Majority of 42 (60%) were 15- 79) severe addicts of internet, and most important these all are belonging from Sagar. 39 (55.72%) respondents as moderate (score 50-79) and 22 (31.43%) respondents were mild and safe (score <49). Keywords: interned addiction, internet usage, adverse effects, internet addiction disorder
Low‐power heterogeneous uncore architecture for future 3D chip‐multiprocessors

Uncore components such as on‐chip memory systems and on‐chip interconnects consume a large amount of energy in emerging embedded applications. Few studies have focused on next‐generation analytical models for future chip‐multiprocessors (CMPs) that simultaneously consider the impacts of the power consumption of core and uncore components. In this paper, we propose a convex‐optimization approach to design heterogeneous uncore architectures for embedded CMPs. Our convex approach optimizes the number and placement of memory banks with different technologies on the memory layer. In parallel with hybrid memory architecting, optimizing the number and placement of through silicon vias as a viable solution in building three‐dimensional (3D) CMPs is another important target of the proposed approach. Experimental results show that the proposed method outperforms 3D CMP designs with hybrid and traditional memory architectures in terms of both energy delay products (EDPs) and performance parameters. The proposed method improves the EDPs by an average of about 43% compared with SRAM design. In addition, it improves the throughput by about 7% compared with dynamic RAM (DRAM) design.
Many-Objective Nurse Scheduling using NSGA-II based on Pareto Partial Dominance with Linear Subset-size Scheduling

: This paper describes a nurse scheduling in Japanese standard general hospitals. In the standard general hospital in Japan basically three shift system is adopted for nurses working in there. We have compiled evaluations of the monthly nurse schedule into twelve penalty functions in the past work. These twelve penalty functions are translated to twelve objective functions in this paper. The nurse scheduling with twelve objective functions is solved as a multi-objective optimization problem by means of NSGA-II. The optimization is insufﬁcient when NSGA-II is applied to such an optimization problem with four or more objective functions, known as a many-objective optimization problem. One method for reducing this problem is a technique based on Pareto partial dominance. In this technique, the partial non-dominated sorting is executed by using a subset selected from all objective functions. In the conventional technique, the schedule of subset size over optimization has to be prepared beforehand in the form of a list. Moreover, the selection list brings a great inﬂuence on the result of optimization. Creating such a selection list is a heavy burden for the user. This paper proposes a technique of NSGA-II based on Pareto partial dominance with a linear subset-size scheduling. By embedding the subset-size scheduling into the algorithm, the user, namely the chief nurse, is released from the designing of the selection list.
Fault response comparison of LCC–MMC hybrid topologies and conventional HVDC topology

The modular multilevel converter (MMC) can be used to upgrade conventional line commutated converter-based HVDC systems (LCC-HVDC), construct the hybrid topologies of LCC and MMC to acquire better fault responses. In this study, the mechanisms of three kinds of hybrid topologies for dc fault clearance are firstly analysed. Then the fault responses of the three hybrid topologies and the conventional LCC-HVDC topology are detailedly compared, including dc line fault and ac faults at both rectifier side and inverter side. The comparison helps demonstrate the degree of improvement when MMC is adopted to upgrade the conventional LCC-HVDC.
Query-Based Sensors Selection for Collaborative Wireless Sensor Networks With Stochastic Energy Harvesting

We develop a new statistical decision making framework to select the optimal subset of sensors to activate, while meeting various quality of service criteria specified by users’ queries. The sensor nodes are powered solely by energy harvested from the environment and should be activated in an efficient and economical manner based on the available battery energy, which may not be directly observed by the decision maker. Our decision making framework consists of two aspects: the first is the estimation of the current available battery levels of each of the sensors and the second is a sensor selection policy. The energy estimation step is based on the Cumulative Energy Harvesting Process which is carried out over the collaborative wireless sensor networks. The sensor selection policy is based on the estimated battery levels and uses the Cross-Entropy method which efficiently solves the resulting combinatorial problem to select the sensor set which maximizes the utility function. We demonstrate and provide insights into the robustness and effectiveness of our framework under different operational conditions.
An exploration of second language collocation knowledge and development

Despite the wealth of LI collocation studies and the explosive growth in corpus linguistics in the last 20 years, relatively little research has been conducted into L2 collocation knowledge and development. Most L2 studies have involved isolated single interventions that have taken as their main research focus collocation errors or collocation types. The assumption is that (advanced) L2 learners should strive for native-like collocation ability and that their lack of collocation accuracy should be judged by a farremoved NS standard. Extremely little experimental work has been completed on the development of L2 collocation knowledge at lower levels of proficiency. Even less has been carried out into how learners themselves address developing their L2 collocation knowledge and what psycholinguistic and contextual factors might be involved. This research sets out to investigate how we can experimentally measure L2 collocation recognition knowledge and production knowledge. It also seeks to examine factors in learning that help or hinder the development of L2 collocation knowledge. From exploring L2 collocation knowledge from these three viewpoints, an experimentally grounded model of L2 collocation knowledge is proposed. This model has several implications for how we might understand the development and organization of the L2 lexicon in relation to L2 collocation knowledge.
Parametric early warning diagnostic method for rotating machinery diagnostics

The aim of the paper is to detect and identify diagnostic symptoms based on parametric modeling with the use of system identification methods in the scope of monitoring techniques intended for rotating machinery under transient operational conditions. The development effort should focus on early warning methods in order to increase detectability and performance of machines operation. The diagnostic symptoms may prove to be a powerful tool for the decision support systems based on easier interpretable parameters of a parametric model. The paper discusses the experimental results obtained with the use of a laboratory test rig as well as data from conducted numerical simulations.
A comparative quantitative & qualitative assessment in orthodontic treatment of white spot lesion treated with 3 different commercially available materials - In vitro study

Background To comparatively evaluate the esthetic improvement of white-spot lesions (WSLs) treated by: BiominF, CPP-ACP paste with fluoride & ICON resin infiltration, using Spectrophotometer & Diagnodent. Material and Methods The study was done using 72 sound permanent extracted premolars, divided into four groups (18 teeth per group). After taking the ethical approval the study was commenced. WSLs were created on human premolars and randomly assigned to four groups: Group A: Artificial Saliva, Group B: CPP-ACP with fluoride, Group C: BiominF, Group D: Resin infiltration (Icon). The color change (∆E) of each specimen was measured with a Spectrophotometer (VITA Easy Shade Compact), and fluorescence loss (∆Q) was measured by a laser fluorescence device (DIAGNOdent, Kavo, Biberach, Germany), at different time points after treatment: baseline (0 weeks), 2 weeks, 4 weeks, and 6 weeks. Results The ∆E and ∆Q baseline values for the four groups before the treatments did not differ significantly. Icon treatment improved the WSL color significantly and gave the lowest ∆E (5.12± 3.92) & ∆Q (1.64 ±0.72) compared with other treatments at end of 6 weeks (P< .01). In the BiominF and CPP-ACP with fluoride treatment groups, ∆Q & ∆E showed significant recovery compared with the baseline values (P< .05). Conclusions Within the limitations of the study, it can be concluded that all the three remineralizing agents used in the study could effectively remineralize artificial enamel caries and showed improvement in color change and fluoresence as compared to the baseline. Therefore they can be effectively used for the treatment of the white spot lesions. Key words:White spot lesions(WSL), Resin infiltration (ICON), BiominF, CPP-ACP with fluoride.
Parallel Deep Learning Ensembles for Human Pose Estimation

This paper presents an efficient method to detect human pose with monocular color imagery using a parallel architecture based on deep neural network. The network presented in this approach consists of two sequentially connected stages of 13 parallel CNN ensembles, where each ensemble is trained to detect one specific kind of linkage of the human skeleton structure. After detecting all skeleton linkages, a voting score-based post-processing algorithm assembles the individual linkages to form a complete human structure. This algorithm exploits human structural heuristics while assembling skeleton links and searches only for adjacent link pairs around the expected common joint area. The use of structural heuristics in the presented approach heavily simplifies the post-processing computations. Furthermore, the parallel architecture of the presented network enables mutually independent computing nodes to be efficiently deployed on parallel computing devices such as GPUs for computationally efficient training. The proposed network has been trained and tested on the COCO 2017 person-keypoints dataset and delivers pose estimation performance matching state-of-art networks. The parallel ensembles architecture improves its adaptability in applications aimed at identifying only specific body parts while saving computational resources.
CBGA-ES+: A Cluster-Based Genetic Algorithm with Non-Dominated Elitist Selection for Supporting Multi-Objective Test Optimization

Many real-world test optimization problems (e.g., test case prioritization) are multi-objective intrinsically and can be tackled using various multi-objective search algorithms (e.g., Non-dominated Sorting Genetic Algorithm (NSGA-II)). However, existing multi-objective search algorithms have certain randomness when selecting parent solutions for producing offspring solutions. In a worse case, suboptimal parent solutions may result in offspring solutions with bad quality, and thus affect the overall quality of the solutions in the next generation. To address such a challenge, we propose CBGA-ES+, a novel cluster-based genetic algorithm with non-dominated elitist selection to reduce the randomness when selecting the parent solutions to support multi-objective test optimization. We empirically compared CBGA-ES+ with random search and greedy (as baselines), four commonly used multi-objective search algorithms (i.e., Multi-objective Cellular genetic algorithm (MOCell), NSGA-II, Pareto Archived Evolution Strategy (PAES), and Strength Pareto Evolutionary Algorithm (SPEA2)), and the predecessor of CBGA-ES+ (named CBGA-ES) using five multi-objective test optimization problems with eight subjects (two industrial, one real world, and five open source). The results showed that CBGA-ES+ managed to significantly outperform the selected search algorithms for a majority of the experiments. Moreover, for the solutions in the same search space, CBGA-ES+ managed to perform better than CBGA-ES, MOCell, NSGA-II, PAES, and SPEA2 for 2.2, 13.6, 14.5, 17.4, and 9.9 percent, respectively. Regarding the running time of the algorithm, CBGA-ES+ was faster than CBGA-ES for all the experiments.
Reliability and validity of a taekwondo electronic body protector

The Protector and Scoring System was introduced in taekwondo to encourage transparency in scoring during competition. The system, which has been used in the past two Olympics, consists of two main components, the electronic body protector and socks. The few studies that have been conducted on the Protector and Scoring System have not been comprehensive and used questionable testing methods. The main objectives of this study were to methodologically examine the validity and reliability of a Protector and Scoring System body protector. To fulfil these objectives, a customized mechanical pendulum was built to test the Protector and Scoring System. The reliability of the pendulum was first determined by tracking the pendulum’s mean velocity at impact for 50 trials on two separate occasions. Data from both days were compared and showed no significant differences (p = 0.08). Mean kinetic energy of the pendulum was then calculated to be 55.52 J. For the experimental trial, the electronic body protector was divided into 12 sections. Each section was tested with the pendulum for 50 trials on two separate days. It was found that only three sections had no significant differences between the two days (p > 0.01), while the rest of the sections had significantly different readings between Day 1 and Day 2. Based on the homologous descriptive statistics, only two sections were in the same group, which translated to the Protector and Scoring System being only 16.7% reliable overall for both days. In terms of validity, an independent samples t-test was used to determine the differences between the calculated kinetic energy from the pendulum (the criterion) and the displayed kinetic energy on the Protector and Scoring System, and values were found to be significantly different (p < 0.01). Overall, the reliability and validity of the Protector and Scoring System was found to be questionable. The system needs to be examined exhaustively before being used in any future tournaments.
“Analyzing Specialized Verbs in a French-Italian-English Medical Corpus: A Frame-based Methodology”

The aim of this study is to investigate the semantics and syntax of verbs in French, Italian, and English medical discourse by exploring the relationship between verb semantics and argument realization. The verbs under consideration are common lexical units which have acquired the status of a term through their specialization of meaning, such as affect, involve, etc. Unlike terminological verbs (e.g. keratinize or lyophilize), they have a lower level of technicalness, and co-occur with arguments (usually terms) in syntagmatic units. The data are extracted from the parallel EMEA corpus including documents published by the European Medicines Agency. The description of the verbs is based on the theoretical model of Frame Semantics (Fillmore1977a-b, 1982, 1985; Fillmore and Atkins 1992) and on the FrameNet methodology (Ruppenhofer et al. 2010). The resultant analysis of the collected data reveals a sentence-level scenario (i.e., the Damaging frame) which groups together verbal forms which share similar syntactic and semantic valence patterns, both within and across languages.
Ultrasound-based carotid stenosis measurement and risk stratification in diabetic cohort: a deep learning paradigm.

Background Stroke is in the top three leading causes of death worldwide. Non-invasive monitoring of stroke can be accomplished via stenosis measurements. The current conventional image-based methods for these measurements are not accurate and reliable. They do not incorporate shape and intelligent learning component in their design. Methods In this study, we propose a deep learning (DL)-based methodology for accurate measurement of stenosis in common carotid artery (CCA) ultrasound (US) scans using a class of AtheroEdge system from AtheroPoint, USA. Three radiologists manually traced the lumen-intima (LI) for the near and the far walls, respectively, which served as a gold standard (GS) for training the DL-based model. Three DL-based systems were developed based on three types of GS. Results IRB approved (Toho University, Japan) 407 US scans from 204 patients were collected. The risk was characterized into three classes: low, moderate, and high-risk. The area-under-curve (AUC) corresponding to three DL systems using receiver operating characteristic (ROC) analysis computed were: 0.90, 0.94 and 0.86, respectively. Conclusions Novel DL-based strategy showed reliable, accurate and stable stenosis severity index (SSI) measurements.