Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety-Critical Control of Euler-Lagrange Systems Subject to Position Constraints

This paper studies the safety-critical control problem for Euler-Lagrange (EL) systems subject to multiple position constraints. The major contribution lies in a new cascade design of safety-critical controllers. The outer-loop controller is developed based on quadratic programming (QP). A velocity-tracking controller is designed to form the inner loop. One major difficulty is caused by the possible non-Lipschitz continuity of the standard QP algorithm. To solve this problem, we propose a refined QP algorithm with reshaped feasible set and relaxation factor such that the outer-loop controller is locally Lipschitz. It is proved that the safety-critical control objective can be accomplished as long as the EL systems under consideration satisfy a mild initial condition. The proposed design is validated by simulation results on a 2-link planar manipulator.
A Bridgeless Rectifier with Improved Power Quality for Low Power SRM Drive

The paper presents a single switch-modified Cuk SEPIC-based bridgeless (SSCSBL) converter-fed SRM drive for applications requiring low power consumption. The dual output DC link is developed for the mid-point converter-fed four-phase SRM. The discontinuous current through inductor mode (DICM) functioning using AC input mains results in minimal control implementation complexity, which is cost-effective in SRM drive for low-power applications. The DICM requires a single voltage sensor rather than two sensor requirements in continuous conduction mode (CCM) operation. For 500 W SRM-based residential applications, an SSCSBL converter is designed to preserve the total harmonics distortion (THD) in AC mains in compliance with the IEC-61000-3-2 standards. The motor speed is controlled by the dual output DC link voltage of the SSCSBLC. The design and functioning of the developed converter are verified by the simulation results.
Exploring the Architecture of Multiple GEMM Accelerators in Heterogeneous Systems

General Matrix-Matrix Multiplication (GEMM) is a commonly used kernel in machine learning, scientific computing and many other applications. Designing a customized GEMM accelerator can bring obvious performance and power consumption benefits. In this paper, we first perform a detailed workload characterization for different sizes of GEMM kernels. Then, we make a comprehensive design space exploration to find the Pareto optimal architecture configurations. Lastly, we compare two versions of multiple GEMM accelerator systems with main-stream BLAS libraries (e.g., OpenBLAS, MKL and cuBLAS). The proposed GEMM acceleration hardware system shows higher energy efficiency than existing software implementations.
An Efficient Bi-Directional System with Reduced Switch Count for Wireless Charging in EV

In this article, an actively clamped boost ac-ac converter followed by a series-series compensation network for a bi-directional IPT(Inductive Power Transfer) system is proposed. The proposed converter is fulfilling the requirement of high-frequency ac signal generation for transferring power wirelessly, it also eliminates the bulky dc link capacitor as required by the conventional dual-stage (ac-dc-ac) IPT systems. The proposed system has the capability for the bi-directional power flow and is thus compatible with both V2G and G2V applications. The circuit configuration, design aspects, mathematical analysis, and steady-state operation are clarified in detail. Moreover, the viability of the system is confirmed by the simulation results with MATLAB/Simulink platform for a 1.2 KW system.
Institutional Profiles: Some Strategic Tools

In this paper we argue that both internal and external pressures and conditions urge contemporary higher education institutions to carefully think through their institutional profiles positions in domestic and global higher education contexts. We subsequently analyse strategic positioning from the strategic management literature and offer four tools — mapping, multi-dimensional ranking, benchmarking and degree profiling — to assist higher education institutions in their profiling and positioning strategies.
A Motion-Adaptive Parallax-Based Monocular Visual Odometry

Monocular odometry is the pivotal part of the visual simultaneous localization and mapping (SLAM) system. Since monocular odometry algorithms available now are built on some certain motion assumptions, they behave unstable severe and rapid motion, which easily reduces the number of reliable landmarks and causes more error. For this reason, a monocular visual odometry algorithm based on a parallax-based weight matrix with an adaptive feature matching is proposed in this paper. The adaptive feature matching algorithm can quickly and reliably establish feature matching under various motions, which ensures the real-time performance of the algorithm under fast and violent motion. The parallax-based weight matrix estimation can make high-parallax map points with high precision dominate the pose estimation and other map points more accurate in the optimization, which can enhance the accuracy of the result in real-time map update and optimization. The experiments are done on two public data sets KITTI and EUROC, in which our algorithm shows slightly better accuracy in location under normal conditions and much better robustness under fast motion and severe motion compared with ORB-SLAM.
MSA-UNet: Retinal vessel segmentation method based on multiple spatial attention mechanism

The high-precision segmentation of the macro and macro structure of the retina and its fine vascular structure is very important for the identification of some early developing eye diseases, such as diabetes and hypertension. In this article, we improve the original U-Net network and propose the MSA-UNet network, which introduces multiple spatial attention mechanisms. This network does not require a large amount of training data. We enhance and amplify the basic dataset to enable it to work efficiently in situations with limited data. MSA-UNet introduces multiple spatial attention mechanism modules in each of the U-Net decoder up-sampling phase inserts SA modules that infer the attention map along the spatial dimension and multiply the attention map with the input feature map for adaptive feature refinement, enabling each up-sampling phase to suppress unnecessary information. In addition, the network uses structured discard convolution fast instead of U-Net raw convolution blocks, which can effectively prevent network overfitting. We evaluate the MSA-UNet based on retinal vascular extraction (DRIVE) datasets. The results show that the proposed MSA-UNet achieves a more advanced performance on this datasets.
Clothing classification based on channel attention and token labeling

With the rapid development of e-commerce platforms, people need to classify massive clothing in a more detailed manner.However,existing models like CNN-based methods are not good at capturing long-distance dependencies because of limited perceptual fields while transformer-based methods lack strenth of capturing local feature details. In this paper, we propose a ECA-TL model that connects CNN to ViT models to get both global and local features for clothing classification. Firstly, we use ResNet to extract low-level semantic information and a light weight Efficient Channel Attention module(ECA) to obtain features with channel attention.Then the self-attention mechanism of ViT model is applied to capture global features while the training process is supervised by pre-generated local labels from the TokenLabeling module(TL). The experimental results show that our proposed method has a effective improvement on the prediction ability of the benchmark network with an accuracy of 87.78%.
Värdet av ökad avkylning i Örnsköldsviks fjärrvärmenät; The value of increased cooling in the district heating system in Örnsköldsvik

Ornskoldsviks fjarrvarmenat har cirka 3000 fjarrvarmekunder dar Horneborgsverket ar den primara produktionsenheten, som forutom fjarrvarme aven producerar el och industrianga. Som fjarrvarmeleverantor finns det generellt sett tre saker som kan studeras for att effektivisera fjarrvarmesystemet och uppna okad lonsamhet: reducera effekttoppar, maximera elgenerering vid kraftvarmeverk samt maximera varmeatervinning vid rokgaskondensering. Detta arbete har utforts i uppdrag av Ovik Energi med syftet att skapa en okad forstaelse for hur returtemperaturen paverkar distribution och produktion av fjarrvarme. Detta for att mojliggora okat resursutnyttjande och darmed aven okad lonsamhet for verksamheten. En sankt returtemperatur genom forbattrad avkylning i natet medfor att ytterligare energi kan atervinnas vid anlaggningens rokgaskondensering, att flodet i fjarrvarmenatet och darmed aven pumparbetet reduceras samt aven distributionsforluster i fjarrvarmekulvertarna minskar. Den potentiella vinsten av en sankning av returtemperaturen har beraknats utifran driftsdata fran 2012. Resultaten visar att en sankning av returtemperaturen med en grad innebar en besparing pa 900 000 Kronor pa arsbasis. Skulle returtemperaturen reducerats med 5 grader kan besparingen uppga till 4,3 miljoner kronor. Avkylning i termer av Q/W-vardet eller i termer av en onodig overkonsumtion av fjarrvarmevatten har beraknats for samtliga anslutna fjarrvarmekunder for januari 2013. Ovik Energis malsattning for Q/W-vardet ar 20 m 3 /MWh under de kallaste manaderna, vilket innebar att fjarrvarmecentralerna ska ha avkylning pa 44°C. Utifran foretagets malsattning och kundernas verkliga Q/W-varde beraknas overkonsumtionen som anger hur mycket extra volym fjarrvarmevatten som kundens fjarrvarmecentral har nyttjat gentemot flodesbehovet om malsattningen for Q/W-varde hade uppnatts. Ett anslutet sagverke ar den kund som har storst overkonsumtion och ar darmed den kund som i storst utstrackning bidrar till en forhojd returtemperatur. Hade sagverket uppnatt malsattningen om en avkylning pa 44°C hade den totala returtemperaturen reducerats med 0,6°C. Det ar dock inte endast stora fjarrvarmeforbrukare som paverkar returtemperaturen. De fyra villacentraler med samst funktion bidrar tillsammans med 0,2°C forhojd returtemperatur. For den studerade perioden, januari 2013, uppvisade 36 fjarrvarmecentraler en avkylning som var mindre an 20°C. Om dessa hade haft den onskade avkylningen om 44°C skulle den totala returtemperaturen reducerats med 1,1°C, vilket innebar en uppskattad arlig besparing pa ca en miljon kronor. Da avkylningen sker i kundernas fjarrvarmecentraler, rekommenderas Ovik Energi att paborja ett arbete riktat mot sina kunder, for att oka fjarrvarmecentralernas effektivitet. En annan atgard som bor vidtas ar att se over de i distributionsnatet inbyggda rundgangarna samt deras nyttjande for att utreda mojligheten till effektiviseringar. Anslutet till fjarrvarmenatet finns aven anlaggningar i Ovik Energis egen ago som kan…
Post refocusing algorithm for high resolution spaceborne SAR image processing in large rolling terrain

In spaceborne SAR image processing, focusing algorithms are applied with a uniform altitude throughout the observation area. The uniform altitude assumption shows good performance in most spaceborne SAR systems. However, in the high resolution (<0.5m) SAR systems, the defocusing becomes significant in areas with high topographic variations. This letter proposes a new post refocusing algorithm capable of improving the focusing quality of the image with large rolling terrain. Simulate data of spaceborne SAR system are used to demonstrate the performance of the proposed approach.
Uniform and Randomly Distributed Fuzzy Logic Based Clustering in Wireless Sensor Networks

The important aspect to consider in WSN would be extending the network lifetime. Due to the limited resources provided by sensors, there are limitations when using the battery power of sensor nodes. The limitation can be overcome by the utilization of clustering schemes, which leverage the power of sensors and can lead to a reduction in energy consumption. This paper introduces a novel approach called Uniform and Randomly Distributed Fuzzy Logic (URDFL) for clustering in WSN. The Cluster Heads selection (CH) is determined by considering aspects such as battery power, node centrality and distance to BS. This approach aims to enhance the network's lifespan and minimize energy consumption. Additionally, a unique cluster formation technique based on a fuzzy logic interference system is presented. Finally, the proposed work has been implemented and compared with the existing protocol, LEACH in WSN by MATLAB simulations.
Integration of Mobile Apps and Milesight AM319-913 at PT.Telkom Indonesia using LoRaWAN and Telkom IoT Platform

Monitoring indoor air quality is crucial due to the significant amount of time people spend indoors. Indoor pollution can have direct and indirect impacts on human health. Understanding pollutant levels is essential for effective indoor air management. By fact that most people spend their time indoors more than outdoor, monitoring indoor air quality is needed since pollution can affect human health directly, and indirectly. Knowing indoor pollutant level is stepping stone for better indoor air management. Our paper proposed LoRaWAN based air quality monitoring system with $\mathrm{C}\mathrm{O}_{2}, \mathrm{P}\mathrm{M}_{10}, \mathrm{P}\mathrm{M}_{2\cdot 5}$, HCHO, and TVOC sensor were developed at office room in Telkom Corpu Area-2. Sensed data is sent to IoT platform via LoRaWAN protocol, and then forward it to web dashboard, and mobile application via MQTT protocol. The result show that our system able to read level of pollutant with average RSSI from 90-95dB, and average SNR from 1-6 db.
On the Suitability of AI for Service-based Adaptive Supply Chains in Smart Manufacturing

Recent years witnessed a growing interest in the employment of intelligent techniques for the management of manufacturing processes in smart manufacturing. These processes may include tens of resources distributed among several different companies composing the supply chain. The status of the different resources evolves over time in terms of cost, quality, and probability of breakdunavailability, thus requiring the process to be adaptive and resilient to disruptions. Due to the high number of involved resources, making decisions manually soon become unfeasible, thus requiring automated techniques to solve the problem. In this paper, we discuss the potential and limitations of automated reasoning techniques for making modern supply chains adaptive and resilient by relying on the information provided by resources through their APIs.
Three-Dimensional Persistent Topology Generation and Optimal Control of Autonomous Underwater Vehicle Formation

Formation generation and control of autonomous underwater vehicle (AUV) is one of the hot topics in multi-robot formation research. Aiming at the problem of communication energy consumption of AUV formation, this paper first uses rigid graph to generate the optimal persistent formation topology of AUV formation, which effectively reduces the number of communication links and energy consumption of formation, and gives the formation topology generation algorithm. Then, considering AUV model, the optimal control method of formation is given by using reinforcement learning strategy iteration. Finally, the simulation results show the effectiveness of the algorithm.
Discrimination of Birds from Aircraft in a Video Sequence for EO Tracking Systems Using Deep CNN

Birds flying in front of cameras of Electro Optical tracking system distracts video tracker from tracking flying objects like aircrafts. This intrusion always challenges the operators during automatic tracking of aircrafts in test ranges. With the advent of CNN and consequently deep neural network, object classification became more accurate and robust. In this paper we have fine-tuned and configured one deep neural network to classify birds and aircraft in video sequences which is used as supplementary cue for conventional video tracker. A seeded region growing segmentation followed by feature based tracking using Kalman filter is used to localize the target position correctly. This is followed by a modified AlexNet for classification alongside a FFT based flapping motion detector. This method provides a very accurate classification which can aid the tracker not to lose track during an aircraft auto track. The experimental result with the curated dataset shows promising result in terms of speed and accuracy.
Journal of Cerebral Blood Flow and Metabolism Cerebral Glucose and Energy Utilization during the Evolution of Hypoxic-ischemic Brain Damage in the Immature Rat

The cerebral metabolic rate for glucose (CMRgI) and cerebral energy utilization (CEU) were as­ sessed in immature rats during recovery from cerebral hypoxia-ischemia. CMRgI was determined using a mod­ ification of the Sokoloff technique with 2-deoxy­ [ 1 4C]glucose (2-DG) as the radioactive tracer. CEU was determined using the Lowry decapitation technique. Seven-day postnatal rats underwent unilateral common carotid artery ligation, followed 4 h thereafter by expo­ sure to 8% oxygen at 37°C for 3 h. At 1, 4, or 24 h of recovery, the rat pups underwent those procedures nec­ essary for the measurement of either CMRgI or CEU. At 1 h of recovery, the CMRgI of the cerebral hemisphere ipsilateral to the carotid artery occlusion was 97% of the control rate (8.7 I-Lmol lOO g-I min-I) but was only 48% of the control in the contralateral hemisphere. At 4 h of recovery, the CMRgI was increased 49% above baseline in the ipsilateral hemisphere, decreasing thereafter to 84% of the control at 24 h. The CMRgI of the contralateral Cerebral hypoxia-ischemia sets in motion a cas­ cade of biochemical events that are initiated during the course of the metabolic insult and proceed well 279 hemisphere normalized by 4 h of recovery. An inverse correlation between endogenous concentrations of A TP or phosphocreatine and CMRgI in the ipsilateral hemi­ sphere was apparent at 4 h of recovery. CEU in the ipsi­ lateral cerebral hemisphere was 64 and 46% of the control (3.47 mmol �Plkglmin) at 1 and 24 h, respectively (p < 0.05) and 77% of the control at 4 h of recovery. CEU in the contralateral hemisphere was unchanged from the control at all measured intervals. Correlation of the alter­ ations in CMRgI with those in CEU at the same intervals indicated that substrate supply exceeds energy utilization during early recovery from hypoxia-ischemia. The dis­ crepancy combined with a persistent disruption of the cerebral energy state implies the existence of an uncou­ pling of mitochondrial oxidative phosphorylation as one mechanism for the occurrence of perinatal hypoxic­ ischemic brain damage. Key Words: Cerebral energy uti­ lization-Cerebral metabolic rate for glucose-Hypoxia­ ischemia-Immature rats. ischemic perturbations that culminates in brain damage is an "uncoupling of oxidative phosphory­ lation. " The phenomenon is characterized by an inability of mitochondria to regenerate chemical en­ ergy in the form of ATP; rather, any energy that is produced via electron transport and oxygen con­ sumption is …
The Archaeology of Pouerua

The Archaeology of the Pouerua is an important book in Pacific archaeology, the third and major book to emerge from the Pouerua Project, which was a major archaeological initiative of the 1980s, studying the extensive pa (native village) site on and around the volcanic cone at Pouerua, Northland, New Zealand. AUP has previously published two small books from this research, The Archaeology of the Kainga and The Archaeology of the Peripheral Pa. These are fairly technical studies but the first in particular has been used as a text and has sold very well. This crowning volume, The Archaeology of Pouerua, is a much larger book than the previous two. It studies the pa itself and the innovative attempt to use archaeological techniques to explore and understand socio-political process. The investigation revealed the pa as a fluid site with different functions changing over time; not a place of permanent settlement but rather a visible sign of power and dominance. The text is not aimed at a general readership but will be of detailed interest to researchers, teachers and students. Contents 1. Pouerua and Pa Site Archaeology 2. Pouerua and the Pouerua Project 3. Methodology 4. Summary of the Cultural Sequence on Pouerua 5. Area III Excavations 6. Area II Excavations 7. Area IV Excavations 8. Area I Excavations 9. Area V Excavations 10. Area VI Excavations 11. Area VII Excavations 12. Pulling the Sequence Together 13. Radiocarbon Dating the Cultural Sequence 14. Form of the Cone 15. Changing Use of Pouerua 16. Conclusion References Appendices Index
Underwater Wireless Laser-Based Communications Using Optical Phased Array Antennas

An underwater optical wireless communication system concept based on optical phased array antennas is presented. With this optical phased array, a laser beam can be electronically steered to adjust not only the azimuth and elevation angles, but also the beamwidth.The proposed concept simplifies pointing and acquisition challenges between non-aligned transceivers. The performance (in terms of the trade-off between achievable range, bit error rate, and data rate) is explored for different numbers of antenna elements and water types. Also, a suitable scanning method is suggested.
Land Cover and Land Use Classification Approach to Maintain the Green Environment in Smart Village

India is quickly digitizing and transforming into a more intelligent nation, including smart cities and automated power transmission and distribution networks rapidly integrating the grand scheme of things (smart metering, smart grids etc.). With about 6,000,000 villages across the country and 68% of the people living in rural areas, it is of the utmost importance to provide them with innovative technology to transform India into a smart nation. Several real-time applications, including monitoring environments, the military, surveillance, and geographic surveys, make substantial use of satellite image categorization. Thus, accurate satellite image categorization is required to improve classification accuracy. Classification of land cover relies heavily on the efficient implementation of satellite image classification using sentinel images. Recent techniques for deep learning facilitate the interpretation of temporal and spatial data for land cover categorization in remotely sensed locations. This study applies a classification approach utilizing a transfer learning model on Euro sat dataset to classify sentinel-2 images that yield in developing a thematic map. There are 27,000 categorized Sentinel-2 satellite images in the Euro sat collection, split over 13 spectral bands and ten classification levels. High computational and achievement are maximized and connected using data augmentation, early halting, and adaptive learning rates. Hence, the transfer learning model ResNet50 obtains 96% accuracy with a 90% to 10% ratio for splitting. Thus, the resulting categorization model is broadly accessible in observatory applications, which aids in developing the smart village.