Miracle-dz/UniFAR-FTUs huggingface dataset:
Speeding Up Multivariate Time Series Segmentation Using Feature Extraction

Multivariate time series segmentation (also known as multiple change-point detection), is one of the important basic tasks in time series data mining. A time series is an ordered sequence of elements. A segment is a region of the time series where the observations are similar according to some measure. The aim of time series segmentation is to identify these regions. In the field of wearable device application, time series segmentation is applied to behavior switching discovering, activity recognition, dimension reduction and so on. With the widespread use of wearable devices, large amount of sensor data can be available. To effectively utilize this time series data, it is important to segment the data into homogeneous phases prior to build an appropriate model for the task, and it must be done at large scale. In this paper, a high accuracy and low time complexity time series segmentation method is proposed based on the time series feature extraction and segmented gaussian model, and applies it to the human activity data sets to discover activity switching.
Neural vs Statistical Machine Translation: Revisiting the Bangla-English Language Pair

Machine translation systems facilitate our communication and access to information, taking down language barriers. It is a well-researched area of Natural Language Processing (NLP), especially for resource-rich languages (e.g., language pairs in Europarl Parallel corpus). Besides these languages, there is also work on other language pairs including the Bangla-English language pair. In the current study, we aim to revisit both Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) approaches using well-known, publicly available corpora for the Bangla-English (Bangla to English) language pair. We reported how the performance of the models differ based on the data and modeling techniques; consequently, we also compared the results obtained with Google’s machine translation system. Our findings, across different corpora, indicates that NMT based approaches outperform SMT systems. Our results also outperform existing baselines by a large margin.
Performance Evaluation of the UWB-based CDS Indoor Positioning Solution

Ultra-wideband technology has become very popular for accurate indoor positioning due to its resilience to interference with other technologies or resulting from multipath propagation. In this context, the scope of this paper is to evaluate the UWB-based indoor localization kit developed by Control Data Systems for accurate positioning of an operator relative to an industrial equipment. The kit is based on the VN360 UWB Module integrating the Decawave DW1000 IC and consists of 4 UWB anchors with a predetermined relative position and one UWB tag (for the operator). The accuracy of the evaluated solution is performed in terms of positioning error variation relative to the distance between the tag and the system origin.
A Novel Anti-interception Waveform in LEO Satellite System

Low Earth Orbit (LEO) satellite communication system is widely used in military deployment, field surveys and anti-terrorism activities, which means the transmitted information often has high value and confidentiality. Therefore, the anti-interception performance of LEO satellite system is significant. Single-carrier Deep Spread Spectrum (SC-DSS) signal has inherent advantage in anti-interception because of its large spreading gain, however, series of problems also exist due to the increased bandwidth. Confronting this, we propose a Non-uniform Multicarrier Deep Spread Spectrum (NUMC-DSS) waveform to serve as a superior alternative of SC-DSS. At the transmitter, NUMC-DSS signal could intelligently adjust the bandwidth, central frequency as well as transmitted power of its sub-band to avoid fixed partial-band interferences and get rid of Doppler code offset. At receiver, NUMC-DSS employs selection combining strategy to counteract the adverse effect of dynamic interference. Performance analysis of NUMC-DSS system has been presented with detailed simulation results. Quantitatively, NUMC-DSS could accomplish accurate reception when the jamming-to-signal ratio (JSR) is equal to 50dB at the cost of 0.4dB loss, while SC-DSS signal fails in reception under the same condition.
Design of a Smartwatch for IoT Application under 5G Environment

In this paper, a novel design of a smartwatch for the Internet of Things (IoT) is proposed. The ergonomic features of its wearability have been investigated and analyzed. Based on the results, the exterior design is proposed. Meanwhile, an ultrawideband Vivaldi antenna is designed under the constraints of structural parameters. The operating bandwidth of the antenna starts from 22.9GHz to more than 50GHz, covering the whole 5G millimeter frequency band. The antenna performance with practical boundary conditions is also analyzed. With the integration with the 5G environment, all the devices connected in IoT are able to conveniently interact with users through the smartwatch.
Impact of Effective Mass on Transport Properties and Direct Source-to-Drain Tunneling in Ultrascaled Double Gate Devices: a 2D Multi-Subband Ensemble Monte Carlo study

In the simulation-based research of aggressively scaled CMOS transistors, it is mandatory to combine advanced transport simulators and quantum confinement effects with first-principle techniques, which are the state-of-the-art to calculate the electronic band structure of nanomaterials. In this work, we have calculated the effective masses in DGSOI transistors and FinFETs using density functional theory (DFT) and investigate their impact on direct Source-to-Drain tunneling (S/D tunneling) using a 2D Multi-Sub-band Ensemble Monte Carlo (MS-EMC) simulator. The results for a particular VDS= 0.5 V show that, in the subthreshold regime, the effective mass variation increases the tunneling probability for the DGSOI transistor leading to a current degradation, whereas this difference is reduced and even reversed for the FinFET.
Molecular Biology of the Plant Mitochondrion

Referee: Prof. C. J. Leaver, FRS, FRSE, Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX13RB UK The comparison of the mitochondrial genomes in plants shows that the gene complement can slightly vary between individual species. The differentially evolving DNA arrangements and sequences offer unique time windows upon the phylogeny of embryophytes. Genes in plant mitochondria are most often transcribed from their own promoters, many of which conform to a conserved type, probably the point of entry for a nuclear-encoded phage-type RNA polymerase. Primary transcripts undergo various RNA processing steps during maturation, including RNA editing, cis- and trans-intron splicing and 5′- and 3′-trimming. RNA half-life regulation via 3′-mediated access for nucleases is an important factor in determining RNA availiability. This includes mRNA destabilization by the addition of non-encoded polyA tails. Present research interests focus on elucidating the regulatory and the metabolic networks integrating the organelle into the plant cell and we outline our visions of the future directions of research in plant mitochondria.
Ecosystem Management Challenges Ecologists

The acceptance of ecosystem management as a guiding paradigm in federal resource management agencies (GAO 1994) presents challenges to ecologists. In this essay, we identify some of those challenges and provide examples of how some are being addressed in an Ecosystem Management Demonstration Project in the Nantahala National Forest, North Carolina. The Ecological Society of America's report on the scientific basis of ecosystem management (Christensen et al. 1996) meets the first challenge, which is to provide a definition of ecosystem management that reflects the consensus of the scientific community and demonstrates the scientific underpinnings of this approach. Further progress in ecosystem management requires application and further development and refinement of these concepts in real world management settings. Earlier management approaches have also been guided by application of ecological principles (e.g., Hornbeck and Swank 1992, Swank and Van Lear 1992). However, ecosystem management differs from prior management concepts in several important ways (Christensen et al. 1996):
Electronically-Steerable Transmitarray Antennas for SATCOM Terminals: a System Perspective

The possibility of using electronically-steerable transmitarrays for future SATCOM-on-the-Move ground terminals operating at K-/Ka-bands is investigated here. Starting from realistic antenna specifications, the trade-offs between antenna architecture complexity, phase-control resolution over the radiating aperture, aperture efficiency, side lobe levels, and beam scanning performance are discussed at the antenna system level and evaluated through numerical simulations. Two designs of linearly-polarized 2-bit reconfigurable unit-cells controlled by four p-i-n diodes are proposed for downlink and uplink bands. By opportunely combining orthogonally-polarized designs based on the proposed cells, two transmitarrays achieving switchable circular polarization and fulfilling the targeted specifications are presented.
Research on Test and Evaluation Method of L3 Intelligent Vehicle Based on Chinese Characteristics Scene

With the development of autonomous driving technology, the L3 intelligent and connected vehicle gradually takes the vector production stage, and test verification is an essential part to measure its functionality. There is no relevant guidance method at present. Based on the natural driving scene database of China Automotive Technology and Research Center, this paper uses LGBM decision tree model to extract the typical features of the scene, and outputs the final high complexity scene according to the weight of each tree. At the same time, combined with CIDAS accident scene and parameter recombination scenario, this paper proposes a kind of scene design method and evaluation method for L3 intelligent vehicle function test. Finally, the verification is carried out on the intelligent and connected vehicle VIL test platform. The results show that the method has good consistency with the actual vehicle test results.
Schrödinger Equation Based Quantum Corrections in Drift-Diffusion: A Multiscale Approach

In this work, we report the development of a 3D drift-diffusion (DD) simulator for ultrascaled transistors with quantum corrections based on the solution of the Schrödingerequation. In a novel multi-scale simulation approach we use effective masses from tight-binding calculations, carrier mobility from the semi-classical Kubo-Greenwood formalism, and quantum corrections based on self-consistent Poisson-Schrödinger solution. This scheme has been implemented into the University of Glasgow TCAD tool called NESS (Nano Electronic Simulation Software). The approach is validated with respect to non-equilibrium Green’s function (NEGF) simulations in the case of nanowire field effect transistors with different cross-sectional shapes.
Ceiling Priority for Synchronous Communication in Real-Time Systems

Software complexity has increased in real-time systems such as automotive electronic control units (ECUs), as many functions are required for such systems. As software complexity has increased, component-based development has been broadly used to decouple software components for reusability, modifiability, and extensibility. Synchronous communication is frequently used between components in component-based development such as AUTomotive Open System ARchitecture (AUTOSAR). Previous studies on scheduling algorithms did not investigate the blocking and priority inversion problem in synchronous communication between tasks. We have observed that synchronous communication has same problem with resources sharing such as critical sections and semaphores, which have been investigated in many studies. The priority inversion also exists in synchronous communication between tasks since all consumer tasks communicating with the same provider tasks must wait until the provider tasks respond. We propose Ceiling Priority for Synchronous Communication (CPSC) for priority assignment and schedulability analysis based on rate-monotonic scheduling. The proposed algorithm was used for automotive battery management system (BMS) based on AUTOSAR and a multiprocessor in multi-criticality real-time systems.
Data Set For Sentiment Analysis On Bengali News Comments And Its Baseline Evaluation

The biggest challenge of Bengali language processing is creating a strong data set to do research on. The main focus of this paper is to introduce an authentic and credible data set and this dataset is open for all to be used for educational purposes1 for Bengali sentiment analysis where the data was extracted from a well known online news portal’s user comments. Here comments on various news were scraped, and for detecting the true sentiments of the sentences, five labels of sentiments were used. An online crowd sourcing platform was used for data annotation. To ensure the credibility and validity of the data set, every entry of the data set was tagged three times. Three models of text classification were used for baseline evaluation to check the validity of the data set. This data set might be of valuable help for future works and researches on Bengali sentiment analysis.
Correlation Structured Low-Rank Subspace Clustering

High-dimensional data is usually drawn from the union of multiple low-dimensional subspaces. The task of subspace clustering is to cluster high-dimensional data into their corresponding subspace. Subspace clustering algorithm based on spectral clustering is one of the important methods of subspace clustering. This method is proposed by the spectral clustering framework. This type of method is usually divided into two steps, namely learning the affinity matrix and obtaining the segmentation matrix by spectral clustering. However, the results obtained this way are often sub-optimal. Meanwhile many state-of-the-art algorithms do not consider consistency of correlation data, resulting in the affinity matrix either too dense to make the algorithm contain a lot of erroneous information, or too sparse to make the algorithm lose correlation information. In this paper, we propose Correlation Structured Low-Rank Subspace Clustering (CSLRSC). The CSLRSC is based on the model of low rank representation by adding new $l_{1}$ norm to solve the problem that the affinity matrix established by the previous method is too dense. Adding the structured norm to the model can integrate affinity matrix learning and spectral clustering into one step to obtain an approximate optimal solution of the algorithm. The experimental results that we obtain on Extended Yale B face dataset, MINIST hand-write dataset, and ORL dataset show that our algorithm is superior to others.
A Novel Self-Docking and Undocking Approach for Self-Changeable Robots

In this paper, an efficient self-docking and self-undocking approach that can be applied to any self-changeable robot is reported. The changeable robot is a concept to extend the concept of reconfiguration in literature, and the name is first coined in this paper. The new feature of the approach is the self-search of a target module with which the remaining robot docks with and then to complete the docking. The new feature is realized by developing modules on which there are built-in cameras and distance sensors. A deep learning method based on CNN (Convolutional Neural Network) was employed to enhance the intelligence level of the docking and undocking system. The experiment was carried out to test the effectiveness of the approach based on a proprietary self-changeable robot.
Genetic and demographic responses of mosquitofish (Gambusia holbrooki) populations exposed to mercury for multiple generations

Genetic and demographic responses of mosquitofish were examined after multiple generations of exposure to mercury. Previous studies of acute lethal exposures of mosquitofish to either mercury or arsenic demonstrated a consistent correlation between time to death and genotype at the glucosephosphate isomerase‐2 (Gpi‐2) locus. A mesocosm study involving mosquitofish populations exposed to mercury for 111 d showed significant female sexual selection and fecundity selection at the Gpi‐2 locus. Here the mesocosm study was extended to populations exposed to mercury for several (approx. four) generations. After 2 years, control and mercury‐exposed populations met Hardy–Weinberg expectations and showed no evidence of genetic bottlenecks. The mean number of heterozygous loci did not differ significantly between the mercury‐exposed and control populations. Significant differences in allele frequencies at the Gpi‐2 locus were observed between the mercury‐exposed and control populations. Relative to the initial and control allele frequencies, the Gpi‐2100 allele frequency was lower, the Gpi‐266 allele frequency increased, but the Gpi‐238 allele frequency did not change in mercury‐exposed populations. No significant differences were found in standard length, weight, sex ratio, or age class ratio between the control and mercury‐exposed populations. Allele frequency changes at the Gpi‐2 locus suggest population‐level response to chronic mercury exposure. Changes in allele frequency may be useful as indicators of population response to contaminants, provided that the population in question is well understood.
Power Consumption Analysis for Mobile MmWave and Sub-THz Receivers

Power consumption is one of the most significant technical barriers for practical millimeter wave (mmWave) communication devices for mobile applications. Communication in the higher mmWave bands above 100 GHz will face even greater challenges. This paper attempts to provide initial power estimates for mobile mmWave devices under realistic parameter values and state-of-the-art device performance characteristics to understand the performance of such systems today and guide research for the future. Power is estimated for a user equipment in a multicarrier New Radio (NR) system for both a 4×100 MHz system at 28 GHz similar to current 5G deployments as well as a hypothetical 8×200 MHz system at 140 GHz that may be used in future 6G systems. Importantly, the analysis considers power consumption of both the RF front-end components as well as portions of the digital baseband processing. Both analog and fully-digital beamforming are also evaluated.
Weak acids: dissociation in complex buffering systems and partitioning into oils.

A method is developed to predict pH changes in complex buffering systems resulting from the addition of weak acids. Such systems are often encountered in foods and microbiological growth media which contain proteins and proteinaceous digests. The ‘buffering capacity’ of the system is characterised by a strong acid titration curve, and the known dissociation constants of weak acids are used to predict pH changes resulting from the addition of either one or a mixture of weak acids to the system. Predictions by the method show close agreement with experimental data. The familiar Henderson–Hasselbalch equation describing the dissociation of weak acids is modified to account for partitioning of undissociated acid into an oil phase. The equation may be used in conjunction with the pH prediction method to calculate both the pH and the concentration of undissociated weak acid in the aqueous phase of an emulsion containing complex buffering species. The equations should find application wherever weak acids are used for microbiological control in complex systems such as foods and pharmaceutical preparations, for predicting pH changes resulting from microbial growth during the production of fermented food commodities (eg cheese and yoghurt) or during food spoilage, and in biotechnological processes ranging from industrial bioreactors to agricultural silage production. © 2000 Society of Chemical Industry
High Dynamic Target Fast Tracking Method Based on Vector Analysis and Kalman Filtering

A new Meanshift fast moving target tracking method is proposed for high dynamic fast moving target tracking. Based on vector analysis and Kalman filtering, this method can predict the moving position of the target in the next frame, and re-match the probability density function of the target model and the candidate model, so as to realize the persistent tracking of the high dynamic target. Experimental results show that the method is effective.
Rates of water turnover and energy expenditure of free‐living male common seals (Phoca vitulina)

The water and energy metabolism of free-living male common seals (Phoca vitulina) during the mating season was investigated using labelled water methods. All three seals, which were captured on two occasions, were in negative energy balance during the study. The daily energy expenditure of one animal, estimated using doubly-labelled water was 52·5 MJ. This is equivalent to six times the basal metabolic rate predicted from Kleiber's (1975) allometric equation. Rates of water turnover were slightly lower than predicted from the allometric equation of Richmond, Langham & Trujillo (1962). The observed rates of water turnover and energy expenditure are considerably higher than those of seals which fast during the mating season, and are consistent with the observed differences in behaviour between males of the common seal and other pinniped males during mating.
Towards Lexicon-free Bangla Automatic Speech Recognition System

This article presents a lexicon-free Automatic Speech Recognition (ASR) system for the Bangla language and investigates an open-source large Bangla ASR corpus, which proved by OpenSLR. The model has been trained using improved MFCC acoustic features with a deep LSTM as an acoustic model. We have tried two types of decoding techniques in the decoding or the last part of the ASR; one is using a joint decoder of Connectionist Temporal Classification (CTC) and a statistical Language Model (LM) for beam decoding, and another is CTC based greedy decoding. We have trained and investigated the performance of our ASR with non-augmented speech as an input. The achieved results are outstanding compares to the results obtained from past researches that have used the End-to-End approaches for Bangla ASR. On the test dataset, our End-to-End system has obtained different results using two distinct decoders. The obtained results are 39.61% WER and 18.50% CER using the greedy decoder and 27.89% WER and 12.31% CER, which are a little bit improved results, using the beam decoder. This achievement is state of the art for continuous Bangla ASR.
Modified Patch Antenna Design Using Moth Search Algorithm for RF Energy Harvesting Applications

Radio frequency energy harvesting is a well-promising technique to power wireless sensor network devices that require small amounts of energy to operate. It can be utilized as an alternative technique for power-constrained systems, such as wireless sensor networks with limited battery lifetime, by extending their energy supply. In outdoor environments, the dominant ambient radio wave sources are the broadcasting and the mobile communication networks. In this paper, we apply an optimization technique by utilizing Moth Search algorithm to design a modified microstrip patch antenna of three varying slots. The proposed antenna exhibits tuning operation in the LoRa (Long Range) and the cellular communications frequency bands of GSM-1800 and UMTS. Numerical results exhibit an acceptable performance of the proposed antenna for RF energy harvesting applications.