Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Novel CMOS Based Inexact Subtractors and Dividers for Approximate Computing: An In-Depth Comparison with PTL Based Designs

Multimedia applications consume an immense amount of energy. These applications have division as one of the fundamental operations. Division is also one of the costliest operations in terms of energy consumption. Thus, various works have been done to address the issue of energy consumption in multimedia applications by using approximate dividers based on pass transistor logic (PTL). Since these applications have resilience towards erroneous computations huge energy benefits are obtained as a result of approximate computations with similar output quality. In this paper, we have shown that PTL based designs are not suitable for lower technology nodes. We performed an in-depth analysis using UMC 65nm and UMC 28nm to highlight the adverse effects of technology scaling on energy consumption and delay in PTL based design as compared to CMOS based designs. We also propose four different inexact CMOS subtractor (ICS) designs, as they are the basic repeated module in inexact restoring array dividers (IRADs). Our proposed ICS designs consume ~ 2× lesser dynamic energy, ~ 3× lesser static power and have ~ 2.5× lesser delay as compared to the existing PTL based designs in UMC 65nm. These benefits increase for UMC 28nm, which shows PTL based designs further worsens at lower technology nodes. IRADs also give about 50% reduction in energy consumption with only 3% degradation in Structural Similarity (SSIM) Index, an image quality metric in multimedia applications like change detection, background removal, and JPEG compression, as compared to exact restoring array divider (ERAD).
Millimeter-Wave Channel Measurements at 28 GHz in Digital Fabrication Facilities

The unprecedented amount of bandwidth available at the millimeter-wave band brings new opportunities for the next-generation factory automation. By supporting these frequencies, the communication technologies may significantly improve the safety and efficiency of manufacturing processes. This paper presents channel measurement results at 28 GHz in a factory environment. The primary channel properties such as path loss, delay, and angular spread are evaluated. Additionally, the distribution of the cross-polarization ratio is shown.
Welfare or Farewell? Mental health and stress in the workplace

Mental health problems, including stress, account for a high proportion of sickness absence and result in loss of employment. The paper presents findings from a recent qualitative research study into employers' policies and practices in relation to mental health and stress. A number of problems are identified in how employers perceive mental health, particularly in the distinction between Ohome' and Owork-based'problems and in how it is dealt with. These include managers' skills in dealing with mental health issues and in the availability of help, such as counselling. The paper identifies a range of measures which would improve current practice. These are seen to have wider benefits in improving employee well-being more generally.
A review of substance use among secondary school students in Nigeria: Implications for policies

Abstract The use and misuse of psychoactive substances among adolescents are increasing in Africa. While heavy episodic drinking among adolescents in Nigeria is growing, there are no written alcohol control policies to regulate the production and availability of alcohol. This article describes the patterns and determinants of alcohol use among Nigerian adolescents in secondary school. Nineteen quantitative studies published in peer-reviewed English language-based journals were reviewed. The results reveal more current and lifetime alcohol use among males than females. The findings also reveal that the motives for using alcohol include staying awake in order to study at night, drinking to forget one’s problems, drinking to alleviate anxiety and drinking to enjoy festivals. Similarly, the results reveal that peer pressure in the form of drinking to satisfy friends or to not be seen as different from one’s group predicted alcohol use, while multiple substance-related problems were reported among substance users. Amongst other factors, the non-existence of alcohol control policies, which increased alcohol availability, was associated with alcohol use. This article discusses the implications of these findings, the possible re-orientation of Nigerian adolescents, the formulation of effective alcohol policies and suggested further research.
Noise Reduction in Periodically Switching MOSFET Circuits Using Iteratively Found Synthesized Control Signals

In many modern power electronic systems, fast periodically switching semiconductors are utilized for system control and minimizing switching losses. The resulting steep switching waveforms may cause electromagnetic interference (EMI) that is mostly reduced with help of heavy passive filter circuits. One basic idea is to optimize EMC behavior and efficiency of power electronic devices by forming the switching waveforms with regard to steepness, overshoots, ringing and high frequency disturbances. Therefore, optimum control signals have to be found and synthesized. To do so, the nonlinear transmission behavior of semiconductor devices has to be considered. To start with, a basic MOSFET test circuit is regarded in this work. With help of an iterative search algorithm, a control signal is found that fits the MOSFET’s output signal to a desired waveform that optimizes EMI and minimizes switching losses. The capability of this method is shown by simulations and measurements.
Explaining Visual Classification using Attributes

The performance of deep Convolutional Neural Networks (CNN) has been reaching or even exceeding the human level on large number of tasks. Some examples are image classification, Mastering Go game, speech understanding etc. However, their lack of decomposability into intuitive and understandable components make them hard to interpret, i.e. no information is provided about what makes them arrive at their prediction. We propose a technique to interpret CNN classification task and justify the classification result with visual explanation and visual search. The model consists of two sub networks: a deep recurrent neural network for generating textual justification and a deep convolutional network for image analysis. This multimodal approach generates the textual justification about the classification decision. To verify the textual justification, we use the visual search to extract the similar content from the training set. We evaluate our strategy on a novel CUB dataset with the ground-truth attributes. We make use of these attributes to further strengthen the justification by providing the attributes of images.
Notificação espontânea de erros de medicação em hospital universitário pediátrico

Objecti ve: To analyze medication errors notified at a pediatric teaching hospital in Sao Paulo city. Methods: Retrospective and descriptive study in which 120 error events and 115 spontaneous notifications were analyzed, between January 2007 and December 2008. Results: The error rate was 1.15 per 1000 patients-day; 27.5% of notifications referred to the school age range and the Pediatric ICU was the sector with most notifications. The error type related to wrong infusion speed predominated (25%). The human factor dimension in the performance deficit category (54%) was the most frequent cause of error events. Conclusion: The safety culture is a continuous process in institutions and the notification of adverse events is part of the strategies. Improvement measures should be incorporated based on their analysis, whether related to the review of the work process or to team training
Electromechanical Impedance Measurement for De-Icing Applications based on Piezoelectric Actuators

A multifunction DAQ device offering precision, speed, low cost, and versatility, is used in this work as impedance meter, work frequency selector and generator for de-icing applications. Preliminary experimental measurements, first on a free piezoelectric disc and then when it is bonded to an aluminum panel, are performed, at room temperature, in order to assess the functionality of the proposed system. The results demonstrate the feasibility of the overall concept.
The Effects of Consumer Interests in Top Box Office Movies in Thailand: evidence from the pre-during-post-peak periods

This paper examined the information searches by consumers for movies from one-year Google Trends data and their relationship with the top box-office movies’ performance. Top five box-office movie data over a 53-week period were collected from boxofficemojo.com and Google Trends. Both Web search and YouTube search in the Arts & Entertainment category and the Online Communities category were explored. Two hundred sixty-five movies, listed in Thailand box office in 2017, were gathered for the analysis phase. Interest over time scores, showing relative search volume from Google Trends, represented the level of consumers’ interests in the movies over time. This study tried to investigate the impacts of consumer interests before, during, and after the peak period on the rank of the movie. Results partially supported the correlations between consumer interests in the pre-peak period and the movie rank, fully supported the correlations between consumer interests in the during-peak period and the movie rank, and supported the correlations between consumer interests in the post-peak period and the movie rank. Findings also indicated higher consumer interests in the during-peak period than the pre-peak period and higher consumer interests in the during-peak period than the post-peak period. In addition, there were an association between two movie ranks in consecutive week and a positive correlation between the latest movie rank and the time to be on the top box office chart.
Depression Angle Invariant SAR Target Recognition via Feature Transform

A variety of data-driven recognition methods have been applied to synthetic aperture radar target recognition. In practical applications, it is difficult to obtain sufficient data at different depression angles. Therefore, when the depression angles of the test data and the training data are very different, the performance of these methods is degraded. To address this problem, we propose a feature transform based method to transfer knowledge from simulated data to real data. We introduce a transform module that can transform target at different depression angles to each other in low-dimensional feature space. The module is trained on the mixed data set consisting of simulated data and real data so that the transform relationship can be shared between the two datasets. During test, according to the difference in depression angle, the feature of the test target is transformed into the space where the training data is located, thereby improving the recognition accuracy. The experimental results show that our method can effectively improve the target recognition accuracy under depression angles variation.
On the Impact of Refactoring on the Relationship between Quality Attributes and Design Metrics

Background: Refactoring is a critical task in software maintenance and is generally performed to enforce the best design and implementation practices or to cope with design defects. Several studies attempted to detect refactoring activities through mining software repositories allowing to collect, analyze and get actionable data-driven insights about refactoring practices within software projects. Aim: We aim at identifying, among the various quality models presented in the literature, the ones that are more in-line with the developer’s vision of quality optimization, when they explicitly mention that they are refactoring to improve them. Method: We extract a large corpus of design-related refactoring activities that are applied and documented by developers during their daily changes from 3,795 curated open source Java projects. In particular, we extract a large-scale corpus of structural metrics and anti-pattern enhancement changes, from which we identify 1,245 quality improvement commits with their corresponding refactoring operations, as perceived by software engineers. Thereafter, we empirically analyze the impact of these refactoring operations on a set of common state-of-the-art design quality metrics. Results: The statistical analysis of the obtained results shows that (i) a few state-of-the-art metrics are more popular than others; and (ii) some metrics are being more emphasized than others. Conclusions: We verify that there are a variety of structural metrics that can represent the internal quality attributes with different degrees of improvement and degradation of software quality. Most of the metrics that are mapped to the main quality attributes do capture developer intentions of quality improvement reported in the commit messages, but for some quality attributes, they don’t.
A Two-Phase Optimization Method of Generating Control Strategy for Air Traffic Flow

With the rapidly increasing of air traffic demand, the demand-capacity imbalances problem of sector is surfaced gradually, and typically occurred in the convection weather conditions. In this paper, given the sector capacity of different time periods, a two-phase optimization framework is proposed to generate flow control strategy for flights from different corridors to achieve the demand-capacity balance. In the first phase, the sector capacity of all time periods are taken as a whole, and then a dynamical programming-based method is proposed to allocate the overall sector capacity for different corridors, roughly. In the second phase, a backtracking method is taken to determine the optimal control strategy for all corridors with minimization of delay cost, where the control strategy includes two restrictions that the maximum allowed number of flights across a corridor and the minimal time interval between every two adjacent flights from the same corridor in each time period. In addition, a 0-1 combination algorithm is used to determine the maximum allowed number of flights in each time period for each corridor. Experimental results show that, compared with the Rate-based method and Need-based method, the proposed method can reduce the average delay cost by 9.1% and 5.2%, respectively.
Multi-UAV Formation Controller Design with Uncertain Dynamics

Aiming at the flight-instability of the closed-loop system in windy field of three fixed-wing unmanned aerial vehicles (UAVs) formation. In this paper, we design a multi-UAV formation controller to address the flight-stability of multiple UAVs. The problem of flight-stability can be converted to the analysis of dynamic response and steady-state error. The robust control compared with thin membrane control method, it can realize the high speed and close cooperative formation of precision combat. Adding thin membrane is not only capable of reducing the body vibration and steady-state tracking error, but also owns better robustness. The proposed controller can control leader’s speed so that follower can track leader in the case of decoupling, while maintaining the consensus of relative speed. The simulation results show that the designed controller integrates the advantages of robust control and thin membrane vibration attenuation. Moreover, this control method can not only improve the response speed, convergence time and stability of the control system, but also realize the aim of the precision cooperative combat ability.
Video Learning Material vs. Text-only Learning Material in E-learners’ Autonomous Language Learning

This study aims to investigate the effectiveness of some audio-visual learning materials in Chinese adult e-learners’ autonomous language learning. 60 participants were randomly assigned to two groups, with 30 members in each. One group was taken as the experimental group, and the other was deemed as the control group. The experimental group received 19 units of video learning materials about English grammar and the control group got 19 units of text-only learning materials. The post-test at the end of the two-month experiment indicated that the video learning materials had been more effective than the text-only materials. The questionnaire survey administered to the experimental group also showed that the video materials were welcomed by the majority of the participants.
Aspects of the reproductive biology and characterization of Sciaenidae captured as bycatch in the prawn trawling in the northeastern Brazil

Current retrospective analysis describes the laboratorial profile of patients hypothetically diagnosed with dengue at a First-Aid Health Unit in Recife, Pernambuco State, Brazil. Results of hemograms were assessed by counting platelets and transaminase dosages, in the first half of 2012. Further, 394 patients (252 females or 64% and 142 males or 34%) were listed, mostly during March and April. Hemograms with platelet counting was undertaken with 210 patients (53.3%) and hemogram plus transaminases dosages with 184 patients (46.7%). Thrombocytopenia, neutropenia and atypical lymphocytes occurred in both genders. Hematocrits were highest in males and transaminases were more altered in females. Patients attended at the health unit with clinical symptoms of classical dengue had a laboratory profile of non-specific exams which is a feature of infection by the dengue virus. Diagnosis could not be confirmed and the need of a fast test in the health unit services was mandatory. The above avoids dengue cases not being notified and treated or overestimated.
Ant Colony Based Energy Consumption Optimization for Mobile IoT Networks

In this paper, a new algorithm is proposed for computing the node disjoint optimal transmission energy consumption route for coded cooperative mobile IoT networks. Inspired by the potential benefits user cooperation can provide, we incorporate user cooperation to the mobile ad-hoc multi-hop IoT networks. Our results include a novel ant colony system-based node disjoint energy efficient routing algorithm. Ant colony system can approximate the optimal route by local information and is thus very suitable for mobile IoT network environment. In particular, ant algorithm makes history-sensitive choice and thus can significantly outperform the greedy algorithm. In addition, it can efficiently handle the case of multiple sources and multiple destinations. For a large IoT network, we investigate the multi-scale ant colony system and when compared to Dijkstra algorithm, such an algorithm usually shortens the run time by a factor of several hundred.
Comparison of adults with intellectual disabilities and mental health problems admitted to specialist and generic inpatient units

Accessible summary • This research was about people with learning disabilities who went into hospital when they had mental health problems. • We looked at when they went into ordinary mental health units and also into a special unit for people who also have learning disabilities. • We looked at what their mental health problems were and how long they stayed for. We looked at what types of places they were living in before they went to hospital and where they went to live afterwards. We found some differences in what happened to the people depending on where they stayed. • This research will help to find out where people with learning disabilities who also have mental health problems should be treated if they need to go to hospital. Summary This study aimed to compare the characteristics of service users with intellectual disabilities and mental health problems admitted to either a specialist or a generic inpatient unit in an area of South London. Socio-demographic and clinical characteristics of consecutive admissions over a 5.5-year period were recorded using a questionnaire. Key differences in psychiatric diagnosis, residence type and discharge destination were found between individuals using generic and specialist provision. Length of stay was significantly longer for specialist unit admissions. Admissions to the specialist unit were significantly more likely to reside with family prior to admission and admissions to generic units were significantly more likely to come from ‘other’ forms of residence such as hostels, prison and ‘no fixed abode’. At discharge the proportion of those admitted to the specialist unit who resided with their families reduced. At the same time the proportion of those living in supported accommodation increased although compared with those admitted to generic units they were still significantly more likely to return to the family home. Significantly, more adults admitted to generic units were diagnosed with an affective disorder. Specialist inpatient provision may be crucial in helping mainstream services meet the needs of individuals with intellectual disabilities and mental health problems.
Explicit Control of Implicit Parallelism in Decomposition-Based Evolutionary Many-Objective Optimization Algorithms [Research Frontier]

Over the past two decades, Evolutionary Multi-objective Optimization (EMO) algorithms have demonstrated their ability to find and maintain multiple trade-off solutions in two and three-objective problems, making EMO as one of the most emergent and exciting fields of research and application within Computational Intelligence (CI) area. The main reason for EMO's success is that the population-based EMO operators are able to establish an implicit parallel search within an evolving population to find multiple Pareto-optimal regions of the search space parallelly. For many-objective optimization problems involving a largedimensional objective space, the extent of implicit parallelism is argued here to be too generic, compared to the same in a lower-dimensional objective space. Decomposition-based EMO algorithms - a recent trend in EMO literature - which divide the overall computing task into a number of sub-tasks of focusing within a region of the search space have found to be successful in solving many-objective problems. In this paper, we study the effect of explicit control of an algorithm's implicit parallelism mechanism for achieving an enhanced performance of decomposition-based EMO algorithms. We consider three decomposition-based many-objective evolutionary algorithms (EAs) - MOEA/D, MOEA/D-M2M, and NSGA-III - for this purpose. We also investigate another explicit control strategy of suitably choosing a normalization method of objectives for improving the performance of MOEA/D and MOEA/ D-M2M methods, and report much improved performance than their original counterparts. The principles of this study are valid for any population-based search and optimization algorithms and can be extended to improve the performance other single-objective EA, EMO, and other relevant CI methods.
Distributed Fault Estimation for Time-Varying Multi-Agent Systems With Sensor Faults and Partially Decoupled Disturbances

This paper is concerned with the problem of distributed fault estimation for time-varying multi-agent systems (MASs) with sensor faults and partially decoupled disturbances. An augmented system is constructed where the augmented state vector contains system states and sensor faults, and assumptions on the fault are not necessary. By using the information of adjacent agents, an unknown input observer (UIO) for the $i$ th agent can be designed to decouple the disturbances as much as possible and attenuate the influence from the disturbances that cannot be decoupled. The desired parameters of the UIO can be derived via solving recursive linear matrix inequalities over a finite horizon. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results.