Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach for Complex Event Streams Processing and Forecasting

Building complex event representation and event forecasting are two important problems which are usually solved separately. In this work we propose general approach that allows to incorporate all available information about events, such as numeric, categorical and binary features and even some text descriptions. We propose ways to build latent representation of complex events using one of dimensionality reduction methods (matrix factorization, neural autoencoders) together with forecasting further occurrences of these events. The experimental results compare combinations of different methods for event representation and forecasting.
Applications of Phase Change Materials in Electrical Regime From Conventional Storage Memory to Novel Neuromorphic Computing

Phase-change materials, also well known as the Chalcogenide alloy, have received considerable attention during last two decades owing to its widespread applications in the field of the electrical storage market such as phase-change random access memory and phase-change probe memory. In addition to the storage devices, its unique electrical properties that can be dynamically tunable with respect to the electrical excitations lead to numerous novel applications represented by memristor and memristor-based neuromorphic electrical circuits. These emerging applications undoubtedly allows for a further exploitation of the potential of phase-change materials, and thus makes it advantageous over other storage medium like ferroelectric and magnetic materials. In order to help researchers understand the role of phase-change materials in these novel applications as well as their importance for citizen’s daily life, a comprehensive review that not only covers the traditional storage applications, but also the applications on these exotic devices becomes imperative. In this review, the chemical structure of phase-change materials and their remarkable electrical properties are first reviewed, followed by an introduction of their applications on the storage fields. The physical principles of various emerging electrical devices using phase-change materials are subsequently overviewed in association with their state-of-the-art progress. The prospect of phase-change materials for the future non-volatile electrical applications that are yet to be unraveled is finally envisaged.
Social thermoregulation in Apodemus flavicollis (Melchior, 1834)

Zmierzono zuzycie tlenu u 120 myszy wielkookich leśnych w zespolach o liczebności 2-5 osobnikow, w zakresie temperatur otoczenia 5-25°C. Zuzycie tlenu u A. flavicollis zalezy nie tylko od temperatury otoczenia, ale rowniez od liczebności grupy (Tabela 1). W badanym zakresie temperatur z wyjątkiem 25°C zuzycie tlenu przypadające na jednostke ciezaru ciala jest istotnie nizsze u osobnikow w grupach. Najnizsze zapotrzebowanie energetyczne zanotowano w grupach skladających sie z 5 osobnikow.
SADANet: Integrating Scale-Aware and Domain Adaptive for Traffic Sign Detection

It holds great implications for large-scale traffic scene understanding, to enable traffic sign detection in real environment. The large intra-category variance in features caused by instances of different spatial scales and appearances are the main problem. In this paper, a traffic sign detection framework using scale-aware and domain adaptive network (SADANet) was proposed, which seamlessly combines a multiscale prediction network (MSPN) with a domain adaptive network (DAN) in a tightly-coupled manner in order to tackle the challenge. Specifically, MSPN is dedicated to extracting the multiscale feature. It utilizes fully, the low-level location and high-level semantic information, and considers the combination of the context information and the instance specific content awareness in the scale transformation. DAN is dedicated to making features domain invariant without enough labeled test data. It aligns the domain distributions from the different scales effectively by leveraging the mapping relationship between the image representation and the multiscale features. Experimental results show that the SADANet is effective in traffic sign detection task and is also competitive when compared with the state-of-the-art methods.
Realization of Power Efficient FIR Filters using Hybrid Accurate-Inaccurate Adder Architecture

In this paper, two new inaccurate adder circuits are proposed. The proposed adder circuits are found to have less area and error rate. They are analyzed in terms of error metrics, delay, area, and power, and compared with those of conventional adders. A linear phase direct form finite impulse response filter is implemented using the proposed inaccurate adders, and performance is evaluated. It is shown that by using a combination of accurate and proposed inaccurate adders, the power consumption can be reduced, without much degradation in the filter performances.
Machine Learning Based Academic Stress Management System

Living with stress has become a part of our lifestyle. Stress is directly linked to cause long-term health problems [1]. Students are no exceptions; they undergo stress and strains in facing new situations, where the outcome is uncertain. Their academic performance is challenged by problems and managing time. Due to overwhelming problems they cannot Figure out their stress causing factors. As it is not possible for a physician to continuously monitor stress levels and diagnose it[5], this proposal deals with identifying the level of stress using wearable bio-sensors and providing constructive actions to be taken to overcome it effectively. We use intelligent Machine learning models to monitor students’ lifestyle. The outcome can be used to identify an ideal student who can portray as a role model in improving the academic growth of a student. An ideal student is the one who manages stress as well as obtains good grades in academics.
Spatio-Temporal Analysis For Gait Recognition: A Review

Human gait recognition is an emerging research topic for analyzing human walking behavior which can be utilized in the machine vision fields. In video surveillance, the benefit of gait recognition is detecting humans in a distanced manner under the low-resolution videotapes. In recent years, detecting and tracking the abnormality of human gait is a challenging task. Spatial and temporal parameters are generally recognized as key metrics in Gait analysis. Spatiotemporal data describes the object states over time, an event or a position in space. The major goal of this review is to offer a wide-ranging overview of historical research on the gait prediction framework. This paper also describes the overview of existing gait databases, gait recognition representation used in the updated gait classification model. The extensive survey on Spatio-temporal parameters for improving the overall accuracy to predict the gait abnormality which is determined from the various gait databases.
Management and Equalization of Energy Storage Devices for DC Microgrids Using a SoC-Sharing Function

This paper presents a method for Energy Storage Systems (ESSs) equalization and energy management in dc microgrids (MGs) with slow dynamic sources, such as Fuel Cells (FCs). The three main features of this method are the ESSs equalization, the energy management between the ESSs and the FC, and the ability to suppress fast transients of load, preventing damages in the FC. The equalization is performed using a State of Charge (<inline-formula> <tex-math notation="LaTeX">$SoC$ </tex-math></inline-formula>)-Sharing Function, which is based on a Sigmoid Function (SF). The <inline-formula> <tex-math notation="LaTeX">$SoC$ </tex-math></inline-formula>-Sharing Function is designed similarly to the droop controller, therefore, it is suitable for operation in droop based MGs. Additionally, the ability to suppress fast transients of load is performed by adding a low pass filter in the FC control loop. The main advantages of this method are the SF smooth behavior and the lack of need for a high-speed link of communication between the sources. To evaluate the MG stability, the Lyapunov’s Indirect Method is applied in the MG model considering different scenarios varying the <inline-formula> <tex-math notation="LaTeX">$SoC$ </tex-math></inline-formula> and load connected to the dc-link. Finally, the model is validated by comparing simulation and experimental results supplied by a lab-scale prototype.
Social barriers to pathogen transmission in wild animal populations

Diseases and pathogens are receiving increasing recognition as sources of mortality in animal populations. Immune system strength is clearly important in fending off pathogen attack. Physical barriers to pathogen entry are also important. Various individual behaviors are efficacious in reducing contact with diseases and pests. This paper focuses on a fourth mode of defense: social barriers to transmission. Various social behaviors have pathogen transmission consequences. Selective pressures on these social behaviors may therefore exist. Effects on pathogen transmission of mating strategies, social avoidance, group size, group isolation, and other behaviors are explored. It is concluded that many of these behaviors may have been affected by selection pressures to reduce transmission of pathogens. 84 refs., 1 tab.
Interactive Attention Model Explorer for Natural Language Processing Tasks with Unbalanced Data Sizes

Conventional attention visualization tools compromise either the readability or the information conveyed when documents are lengthy, especially when these documents have imbalanced sizes. Our work strives toward a more intuitive visualization for a subset of Natural Language Processing tasks, where attention is mapped between documents with imbalanced sizes. We extend the flow map visualization to enhance the readability of the attention-augmented documents. Through interaction, our design enables semantic filtering that helps users prioritize important tokens and meaningful matching for an in-depth exploration. Case studies and informal user studies in machine comprehension prove that our visualization effectively helps users gain initial understandings about what their models are "paying attention to. " We discuss how the work can be extended to other domains, as well as being plugged into more end-to-end systems for model error analysis.
Exploring the Effectiveness of Haptic Alarm Displays for Critical Care Environments

Noise in critical care units, in particular, from patient monitor alarms, is harmful for clinicians and patients alike. This has motivated research aimed at shifting the delivery of physiological vital sign information and annunciation of alarm events from visual and auditory devices to haptic transducers. We compare performance in perceiving and identifying the specific type and level of a vital sign that has entered a high or low state, i.e., an alarm event, using several designs of a vibrotactile display, against that of the traditional auditory alarm in conjunction with a graphical patient monitor. A distractor activity was used to simulate competing task demands in the clinical environment. Responses were assessed with respect to response time and accuracy. With sufficient anatomical separation of the actuators, certain vibrotactile information rendering strategies demonstrated performance that was not significantly different from that of the baseline condition, both in response time and accuracy. We conclude that vibrotactile delivery of patient vitals can support alarm-state vital sign identification competitive with graphical and auditory alarm display conditions, without significantly impacting performance on a parallel attention-demanding activity. This suggests the possibility of improving high-impact healthcare environments by replacing disturbing auditory alarms with vibrotactile information delivery to clinicians.
Estimation of Upper-Limb Energy Absorption Capabilities for Stable Human-Robot Interactions

Human-robot interactions are becoming more and more prevalent in various aspects of life, enhancing humans’ mobility, accessibility and health. However, safety measures need to be addressed when applying robotic-generated forces that put human users at risk. One way to improve safety and performance in robotic tasks is to include physiological information, such as damping properties of the arm, in the control system to help regulate the energy that is delivered to the user. In this work, we estimated the energy absorbing capabilities of the human arm, based on the metric Excess of Passivity (EOP), originally defined in [1]. We used data from healthy subjects to generate models that fit different levels of safety and stability. Variability in subjects’ EOP was a major finding in this study. For demanding applications such as robotic rehabilitation therapy, we suggest using a linear model with two EOP points. Such points are the mean values of EOP estimations at relaxed and rigid levels of hand-grasp forces. Two standard deviations were subtracted from each EOP point to consider the variability due to the neuromuscular changes in the human arm.
Thwarting ICMP Low-Rate Attacks Against Firewalls While Minimizing Legitimate Traffic Loss

Low-rate distributed denial of service (LDDoS) attacks pose more challenging threats that disrupt network security devices and services. Such type of attacks is difficult to detect and mitigate. In LDDoS attacks, attacker uses low-volume of malicious traffic that looks alike legitimate traffic. Thus, it can enter the network in silence without any notice. However, it may have severe effect on disrupting network services, depleting system resources, and degrading network speed to a point considering them as one of the most damaging attack types. There are many types of LDDoS such as application server and ICMP error messages based LDDoS. This paper is solely concerned with the ICMP error messages based LDDoS. The paper proposes a mechanism to mitigate low-rate ICMP error message attacks targeting security devices, such as firewalls. The mechanism is based on triggering a rejection rule to defend against corresponding detected attack as early as possible, in order to preserve firewall resources. The rejection rule has certain adaptive activity time, during which the rule continues to reject related low-rate attack packets. This activity time is dynamically predicted for the next rule activation period according to current and previous attack severity and statistical parameters. However, the rule activity time needs to be stabilized in a manner in order to prevent any additional overhead to the system as well as to prevent incremental loss of corresponding legitimate packets. Experimental results demonstrate that the proposed mechanism can efficiently defend against incremental evasion cycle of low-rate attacks, and monitor rejection rule activity duration to minimize legitimate traffic loss.
Regenerative Estimation of a Simultaneous Service Multiserver System with Speed Scaling

The paper deals with simultaneous service multi-server system, where customer occupies a random number of servers. The system also admits speed scaling mechanism by switching speed regimes at arrival/departure instants according to the corresponding transition probability matrices. Stability conditions for Markovian case of such a model were derived. Results of regenerative confidence estimation for the system in steady-state regime are presented.
Internet-Based Unobtrusive Tele-Monitoring System for Sleep and Respiration

This research is about new advances in the application of remote bio-signal monitoring technology. An unobtrusive IoT bio-signal measurement system is attached to a bed using a very thin strip sensor, then the user’s sleep efficiency and respiration rate can be measured with accuracy similar to that of an existing FDA-approved sleep tracker. In particular, in this study, we propose a ubiquitous central monitoring system that links an existing, personal use, unobtrusive measurement system to cloud-based systems via WiFi transmission. The proposed monitoring system simultaneously collects, stores, and displays the data from multiple devices using a web server as well as PC and mobile platforms such as personal smart devices. In this study, we implemented a system for the real-time transmission and display of data from multiple unobtrusive systems and validated that there were no problems associated with sending and receiving data at distances of 300 km with around a one-second delay. In addition, we evaluated the tele-monitoring system’s data processing time, CPU usage, and memory usage as the number of users was increased. Each user transmits an average of 810 bytes of data including information such as user id, time stamp, data for each channel, respiration rate and sleep status. We observed that the average data processing time was 0.15 seconds, average CPU usage was 5.01%, average memory usage was 0.1% assuming 10 users connected simultaneously. These results are expected to be useful in guiding future similar personal, public, and clinical applications of this technology.
The Effects of Noise, Early and Late Reflections on Speech Intelligibility

In this paper, an assessment of the combined effects of the noise, early and late reflections on speech (monosyllables of consonance-vowel-consonance type) intelligibility for binaural listening mode was made. Test signals were synthesized in two ways. In the first case, the noisy monosyllables (signal-to-noise ratio was varied from −15 dB to +5 dB) was filtered by two-channel room impulse responses for distances varied from 2 m to 10 m from the sound source in the middle size auditorium. In the second case, the room impulse responses were cut after 50 ms and used for filtering the same noised monosyllables. Filtered monosyllables were listened through headphones and entered into the computer using the keyboard. The results of testing showed that monosyllables intelligibility is the highest for 2 m distance and is the lowest in the middle of the room. A slight increase in speech intelligibility at the back wall can be explained by the combined action of direct sound and early reflections. The decrease in speech intelligibility in the middle of the room can be further explained by a decrease in the quality of the speech signal.
Efficient Router Architecture for Trace Reduction During NoC Post-Silicon Validation

The contemporary network-on-chips (NoCs) have highly complex architectures. So, robust post-silicon validation mechanism is required for error-proof NoC design. Traces of packet transactions are generated during NoC validation and are stored for fault analysis. Size of trace generated, directly translates into onchip storage cost and communication bandwidth requirement. Our work proposes a modified NoC router architecture which eliminates the redundant traces and only stores the meaningful traces. This results in reduction of total trace amount while maintaining the same level of system internal observability. The scheme is proved to be beneficial for short-lived communication faults (packet drop, direction fault etc.), and shows around 23% to 36% of trace reduction in case of a 8x8 mesh network for each cycle trace capture. The overhead introduced is nominal and can further be reduced in case of permanent network faults.
On Plants and Herbivores

Belsky's (1986) recent paper titled "Does herbivory benefit plants? A review of the evidence" represents a fundamental material fallacy characterized by Aristotle as plurimum interrogationum, the fallacy of many questions. By posing a question in a fashion demanding a single answer when only a complex answer can be correct, she developed an argument hat is neither internally consistent nor supportable by the scientific evidence. Her criticisms of the literature are too farreaching to be addressed fully in a note; I confine myself to major points that bear on my own research, review articles, and statements about plant-herbivore relations. I believe that commentary is also relevant o many of her statements about the publications of other scientists. I explicitly identify logical errors, papers uncited by Belsky that refute her principal points, a misrepresentation f the methods that I used in field studies, and errors of fact and interpretation that flow inevitably from her approach. 1. Regarding the benefit hat grasses might derive from grazing, I have nowhere written that the mere act of herbivory isbeneficial to any affected plant. I wrote, "Although these experiments indicate that compensatory growth responses of the plants are a significant factor in this ecosystem's energy flow, this does not imply that the relationship between the plants and herbivores is symbiotic by any conventional definition of that term" (McNaughton 1979b, p. 698). And, more recently, "Although the animals and plants are interdependent, compensatory growth of the grasslands did not compensate fully for removal by herbivores, and the grasses have evolved levels of silicification, an antiherbivore d fense, more pronounced than have been recorded in any other ecosystem. Thus, it is improper to conclude that grazing is strictly advantageous to the plants. " (McNaughton 1985a, p. 284.) These caveats notwithstanding, grasses (as species, ecotypes, or genotypes) that dominate grazed grasslands but disappear in the absence of the grazers (Clements 1920; Stapledon 1928; McNaughton 1979a,b, 1984) are obligate grazophiles (McNaughton 1979b) and would not exist in the absence of grazers. Belsky concluded, from species-composition changes when grazed ranges are fenced, "In each of these cases the individual plants depend upon the grazers to reduce the biomass of their competitors or prevent the build-up of senescent tissue in the community. Normal community processes such as competition and succession adequately explain the persistence or disappearance of these species. " (Belsky 1986, p. 884.) The first sentence quoted is as clear and comprehensive a statement of benefits accorded plants by animals as any I have read. The second sentence is, simply, a non sequitur. Its context also implies that herbivory isnot a normal community process. Rather, I believe, it is a lack of grazing and not its
Design of On-Board Battery Charger using Interleaved Bridgeless Type PFC and Phase Shifted Full Bridge Converter

With increase of DC micro grids and electrical vehicles (EV), battery charging application has gained a lot of prominence. Many of these systems are fed by utility. The AC/DC conversion is done by classical diode bridge rectification which causes low input power factor and adversely affects the utility supply. Thus input power factor correction is one of the major concerns. Also, switched mode power converter incurs high switching losses at high frequencies of operation. Reduction of switching frequency is not a solution to reduce the losses as higher frequencies yield in many advantages such as reduction in converter size. This paper describes systematic design of 1.5 kW high power factor bridgeless interleaved boost converter fed on-board battery charger for EVs. Phase shifted full bridge converter having zero voltage switching (ZVS) up to 50% of the rated load is integrated with the high power factor AC/DC stage. The detailed design methodology of PFC controller, and phase shifted full bridgeless converter for EV is given in this paper. To validate the design of power stage and controller, PSIM simulation has been carried out and results are provided. Results show that power factor is greater than 0.99 and THD is less than 2 % at full load which is under the IEC standard.