Miracle-dz/UniFAR-FTUs huggingface dataset:
IIoT Low-Cost ZigBee-Based WSN Implementation for Enhanced Production Efficiency in a Solar Protection Curtains Manufacturing Workshop

Nowadays, the Industry 4.0 concept and the Industrial Internet of Things (IIoT) are considered essential for the implementation of automated manufacturing processes across various industrial settings. In this regard, wireless sensor networks (WSN) are crucial due to their inherent mobility, easy deployment and maintenance, scalability, and low power consumption, among other benefits. In this context, the presented paper proposes an optimized and low-cost WSN based on ZigBee communication technology for the monitoring of a real manufacturing facility. The company designs and manufactures solar protection curtains and aims to integrate the deployed WSN into the Enterprise Resource Planning (ERP) system in order to optimize their production processes and enhance production efficiency and cost estimation capabilities. To achieve this, radio propagation measurements and 3D ray launching simulations were conducted to characterize the wireless channel behavior and facilitate the development of an optimized WSN system that can operate in the complex industrial environment presented and validated through on-site wireless channel measurements, as well as interference analysis. Then, a low-cost WSN was implemented and deployed to acquire real-time data from different machinery and workstations, which will be integrated into the ERP system. Multiple data streams have been collected and processed from the shop floor of the factory by means of the prototype wireless nodes implemented. This integration will enable the company to optimize its production processes, fabricate products more efficiently, and enhance its cost estimation capabilities. Moreover, the proposed system provides a scalable platform, enabling the integration of new sensors as well as information processing capabilities.
Investigation of the aerodynamic effects of bio-inspired modifications on airfoil at low Reynolds number

A numerical study was performed to investigate flow behaviors around bio-inspired modified airfoils compared with NACA 4412 airfoil at Re=5.8x104 by solving the two-dimensional, RANS equations with k-ω STT turbulence model. The obtained results reveal a rather abrupt decrease of lift at stall for the NACA 4412 airfoil in contrast to the mild stall depicted by the top-modified airfoil. As compared to the experimental results of the profiled airfoil in the literature, the characteristic behavior of the variation in the lift coefficient shows resemblance. It is seen that from the velocity distribution results, fluid flowed smoothly along the streamlined nose of NACA 4412 airfoil until α=4⁰ and streamlines adhered well for both airfoils at low angles (0⁰, 2⁰). Smaller circulation bubbles were noticed to settle in the canyons of the corrugated cross-section of the top-modified airfoil. In the wake region of the modified airfoil, there is no obvious large flow separation or circulation region at low angles of attack. However, the blue regions of the dimensionless velocity over the NACA 4412 airfoil and bottom-modified airfoil were narrower than over the top-modified airfoil. The recirculation zone over the airfoil started to enlarge, and the rolling up of the trailing-edge vortex appeared. After α=12⁰, the adverse pressure gradient on the suction side of the airfoils became more intense. In the wake zones, it was seen that the circulation regions grew remarkably and became largest as the angle of attack rose to α=16⁰, which pointed out increased drag forces of airfoils.
Short run performance of initial public offerings in Nepal

This paper examines the under-pricing and performance of IPO for six months period using the model of under-pricing. Overall, 67 samples are analyzed out of 120 population identified from the period of 2014/15 to November 2020/21 using judgmental sampling and removal of outlying observations. Firm size, subscription rate, issue size, age of firm, issue manager reputation and market condition are taken as independent variables. Nepalese investors mainly prefer microfinance sector for investment and tends to be underpriced for longer period due to high demand for share. Observations are classified into two categories based on mean value of each predicting variable and NEPSE index. Significant difference on initial as well as monthly return has been observed between categories of subscription rate (high versus low) and age (matured versus young). Highly positive and significant correlation between the issue size and firm size shows large firm issue IPO in large size and negative significant correlation between issue size and subscription rate shows when issue size is low there will be high demand for shares. Significant relationship of subscription rate and age of firm for initial and first month return has been observed whereas only subscription rate was found significant after second month to sixth month. Study concludes that subscription rate is major determinant of under-pricing of IPOs in the Nepalese Stock Market.
Characterization of Walking in Mild Parkinson’s Disease: Reliability, Validity and Discriminant Ability of the Six-Minute Walk Test Instrumented with a Single Inertial Sensor

Although the 6-Minute Walk Test (6MWT) is among the recommended clinical tools to assess gait impairments in individuals with Parkinson’s disease (PD), its standard clinical outcome consists only of the distance walked in 6 min. Integrating a single Inertial Measurement Unit (IMU) could provide additional quantitative and objective information about gait quality complementing standard clinical outcome. This study aims to evaluate the test–retest reliability, validity and discriminant ability of gait parameters obtained by a single IMU during the 6MWT in subjects with mild PD. Twenty-two people with mild PD and ten healthy persons performed the 6MWT wearing an IMU placed on the lower trunk. Features belonging to rhythm and pace, variability, regularity, jerkiness, intensity, dynamic instability and symmetry domains were computed. Test–retest reliability was evaluated through the Intraclass Correlation Coefficient (ICC), while concurrent validity was determined by Spearman’s coefficient. Mann–Whitney U test and the Area Under the receiver operating characteristic Curve (AUC) were then applied to assess the discriminant ability of reliable and valid parameters. Results showed an overall high reliability (ICC ≥ 0.75) and multiple significant correlations with clinical scales in all domains. Several features exhibited significant alterations compared to healthy controls. Our findings suggested that the 6MWT instrumented with a single IMU can provide reliable and valid information about gait features in individuals with PD. This offers objective details about gait quality and the possibility of being integrated into clinical evaluations to better define walking rehabilitation strategies in a quick and easy way.
The impact of strategic thinking on organizational excellence: An empirical examination in Jordan’s ICT sector

This study empirically examines the impact of strategic thinking on organizational excellence in Jordan's Information and Communication Technology (ICT) sector. Adopting a quantitative methodology, this study surveys a sample of 270 individuals drawn from various ICT companies across Jordan. Utilizing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) for analysis, the study investigates the effects of different dimensions of strategic thinking on organizational excellence. The findings reveal that among the dimensions studied, dynamic and systematic thinking significantly and positively influenced organizational excellence. These results underscore the critical role that adaptive and methodical approaches to strategic thought play in enhancing organizational performance and competitiveness within the fast-paced ICT sector. The study not only contributes to the theoretical understanding of strategic thinking's relevance in organizational success but also offers practical insights for ICT companies aiming to achieve excellence in a dynamic business environment.
Trust System- and Multiple Verification Technique-Based Method for Detecting Wormhole Attacks in MANETs

The proliferation of wireless mobile devices has resulted in mobile ad hoc network (MANET) technologies, which enable the formation of networks without infrastructure assistance, gaining increased attention. The advancements in these technologies have also resulted in the variety of attacks targeting them becoming more diversified. Particularly, owing to their inability to ensure node reliability, MANETs are vulnerable to routing attacks such as wormhole attacks. Since wormhole attacks often do not directly damage networks, detecting them can be challenging. In response, we propose a novel multiple verification-based wormhole attack detection method that leverages the characteristics of such attacks. The proposed method measures the credit of each node based on a trust system. The trust levels of suspicious nodes are reduced during routing; those with trust levels below a certain threshold are considered malicious. This trust system was implemented using reinforcement learning, which improves the accuracy of the system over time. Simulation experiments in which the proposed method was applied to existing routing methods in a densely populated environment were conducted; the rate of traffic passing through paths with malicious nodes was significantly reduced.
The key role of the right posterior fusiform gyrus in music reading: an electrical neuroimaging study on 90 readers

In this study, we employed a combined electromagnetic recording technique, i.e., electroencephalogram (EEG)/event-related potentials (ERPs) plus standardized weighted low-resolution electromagnetic tomography (swLORETA), to investigate the neural mechanism subserving the orthographic processing of symbols in language and music. While much is known about word processing, the current literature remains inconclusive regarding music reading, as its mechanisms appear to be left lateralized in some cases (as suggested by music-alexia clinical case reports) and either right-sided or bilateral in others, depending on the study and the methodology used.In this study, 90 right-handed participants with varying musical abilities and sexes performed an attentional selection task that involved the recognition of target letters and musical notes, while their EEG signals were recorded from 128 sites.The occipito/temporal N170 component of ERPs (170–210 ms) was found strictly left-sided during letter selection and bilateral (with a right-hemispheric tendency) during note selection. Source reconstruction data indicated the preponderant engagement of the right posterior fusiform gyrus (BA19) for processing musical notes. Also involved were other brain regions belonging to the word reading circuit, including the left-sided visual word form area (VWFA) and frontal eye-fields (FEFs). This finding provides an explanation for the infrequent appearance of musical alexia cases (previously observed only in patients with left hemispheric lesions). It also suggests how musical literacy could be a rehabilitative and preventive factor for dyslexia, by promoting neuroplasticity and bilaterality in the reading areas.
Physico-Chemical Analysis of Ground Water in Angul-Talcher Region of Orissa, India

The study was carried out to assess the impacts of industrial and mining activities on the ground water quality in Angul-Talcher region of Orissa. The quality was assessed in terms of physio-chemical parameters. Ground water samples were collected from thirteen (13) open well at various locations in study area during pre and post monsoon season. The physico-chemical parameters such as pH, Electrical conductivity, TDS, Total hardness, Ca hardness, Mg hardness, Ca ion, Mg ion, Chloride, and COD were analyzed (APHA, 1998) to know the present status of the groundwater quality. Drinking water quality (IS: 10500) of pre-monsoon season was better than post monsoon season. Few water samples were slightly alkaline along with high dissolved solids. (The Journal of American Science. 2009;5(5):53-58). (ISSN 1545-1003).
Sulfated CXCR3 Peptide Trap Use as a Promising Therapeutic Approach for Age-Related Macular Degeneration

Background and Objectives: Chemokines have various biological functions and potential roles in the development or progression of neuroinflammatory diseases. However, the specific pathogenic roles of chemokines in the major cause for vision loss among the elderly, the leading cause of blindness in older individuals, remain elusive. Chemokines interact with their receptors expressed in the endothelium and on leukocytes. The sulfation of tyrosine residues in chemokine receptors increases the strength of ligand–receptor interaction and modulates signaling. Therefore, in the present study, we aimed to construct a human recombinant sulfated CXCR3 peptide trap (hCXCR3-S2) and mouse recombinant sulfated CXCR3 peptide trap (mCXCR3-S2) to demonstrate in vivo effects in preventing choroidal neovascularization (CNV) and chemotaxis. Materials and Methods: We generated expression vectors for mCXCR3-S2 and hCXCR3-S2 with GST domains and their respective cDNA sequences. Following overexpression in E. coli BL21 (DE3), we purified the fusion proteins from cell lysates using affinity chromatography. First, the impact of hCXCR3-S2 was validated in vitro. Subsequently, the in vivo efficacy of mCXCR3-S2 was investigated using a laser-induced CNV mouse model, a mouse model of neovascular age-related macular degeneration (AMD). Results: hCXCR3-S2 inhibited the migration and invasion of two human cancer cell lines. Intravitreal injection of mCXCR3-S2 attenuated CNV and macrophage recruitment in neovascular lesions of mouse models. These in vitro and in vivo effects were significantly stronger with CXCR3-S2 than with wild-type CXCR3 peptides. Conclusion: These findings demonstrate that the sulfated form of the CXCR3 peptide trap is a valuable tool that could be supplemented with antivascular endothelial growth factors in AMD treatment.
WhatsApp in Ethnographic Research: Methodological Reflections on New Edges of the Field

The mobile phone and the increasing worldwide use of smartphones with applications such as the instant messenger WhatsApp are revolutionising ethnographic research. Drawing on transnational, ethnographic research in Tanzania, the USA and Oman, this paper shows that WhatsApp constitutes a valuable tool in ethnographic research in three important fields of interaction and communication: first, between researchers and informants simultaneously in different places; secondly, as a tool to exchange with field assistants; and thirdly between researchers. Building on expanding theoretical reflections on transnational networks and practices this paper adds new insights to corresponding methodological consequences. It critically reflects on the usefulness of integrating WhatsApp into ethnographic research. It argues that by incorporating such technologies we can not only keep an actor-centred focus, but also support methodologically the theoretical shift from understanding the field as a ‘location’ to grasping the field as a ‘network’ – or even a transnational social field.
Combatting cultural ‘nerve gas’: maintaining traditional media and culture through local media production in Australia, Canada and Mexico

In Australia in the 1980s, large numbers of remote Indigenous radio stations were established due to a perception that the introduction of ‘mainstream’ satellite programming in remote areas would act as a form of cultural ‘nerve gas’ (Remedio, 2012: 295) that would threaten ‘the very isolation that had helped to preserve what remained of traditional language and culture’ (Guster, 2010: 9). There are parallels here with the development of remote media in Mexico and Canada, where local radio networks focusing on cultural content production were established in response to impending development and imposed sources of mass media. In each country, broadcasters in remote communities have, in recent years, been producing increasing amounts of hyper-local cultural and language-based content. This article examines the role played by Indigenous media in remote areas of Australia, Canada and Mexico in creating an alternative cultural voice for traditional communities and maintaining language and culture.
Performance Optimization of all Inorganic Perovskite Solar Cell Employing Ga2O3 and CuSCN Materials

In this study, we conduct an extensive examination of the performance of CsPbI<inf>3</inf>-based perovskite solar cells (PSCs) through rigorous numerical simulations. We explore a range of inorganic materials to assess their suitability for use as hole transport layers (HTL) and electron transport layers (ETL). The ETL candidates considered encompass ZnO, Ga<inf>2</inf>O<inf>3</inf>, TiO<inf>2</inf>, and PCBM, while our evaluation for potential HTL materials includes NIO, CuSCN, CuO<inf>2</inf>, and Spiro-OMeTAD. Our research highlights the superiority of CsPbI3-based PSCs when employing Ga<inf>2</inf>O<inf>3</inf> as the ETL and CuSCN as the HTL, surpassing the performance of other solar cell combinations. The optimized solar cell exhibits exceptional characteristics, including a high <tex>$J_{SC}$</tex> of 16.76 mA/cm<sup>2</sup>, <tex>$V_{OC}$</tex> of 1.13 V, FF of 87.82%, and an impressive efficiency of 16.62%. These findings hold substantial promise for guiding the development of high-performance, all-inorganic CsPbI3 PSCs.
Comparative Evaluation of VAEs, VAE-GANs and AAEs for Anomaly Detection in Network Intrusion Data

With cyberattacks growing in frequency and sophistication, effective anomaly detection is critical for securing networks and systems. This study provides a comparative evaluation of deep generative models for detecting anomalies in network intrusion data. The key objective is to determine the most accurate model architecture. Variational autoencoders (VAEs), VAE-GANs, and adversarial autoencoders (AAEs) are tested on the NSL-KDD dataset containing normal traffic and different attack types. Results show that AAEs significantly outperform VAEs and VAE-GANs, achieving AUC scores up to 0.96 and F1 scores of 0.76 on novel attacks. The adversarial regularization of AAEs enables superior generalization capabilities compared to standard VAEs. VAE-GANs exhibit better accuracy than VAEs, demonstrating the benefits of adversarial training. However, VAE-GANs have higher computational requirements. The findings provide strong evidence that AAEs are the most effective deep anomaly detection technique for intrusion detection systems. This study delivers novel insights into optimizing deep learning architectures for cyber defense. The comparative evaluation methodology and results will aid researchers and practitioners in selecting appropriate models for operational network security.
BigData Fusion for Trajectory Prediction of Multi-Sensor Surveillance Information Systems

Video surveillance information systems assist forensics to examine and analyze the evidence from crime scenes to develop objective findings in the investigation of crime. Often, the existing surveillance information systems exploit an array of security cameras and IoT devices monitoring the same crime scene from different points of view while the crime unfolds over a range of time. However, none can automatically and selectively merge big data streams connected to such systems to provide a holistic, end-to-end safety picture.This work proposes a trajectory prediction architecture framework within a multi-sensor surveillance system. We developed a novel position measurement technique using monocular depth perception networks with multi-camera setup using triangulation. We tested and compared our technique with a single camera sensor in our first experiment and as the multi-camera setup determines the position of our target more accurately, we used our measurement function in our second experiment. In our second experiment, we employed the Unscented Kalman Filter (UKF) for predicting the trajectory of the target, and proved that UKF has good potential for being used in surveillance systems. Lastly, we designed a general architecture framework for big data analysis in multi-sensor surveillance systems consisting the four layers: the Sensor Layer, the Single Sensor Computation Layer, the Data Fusion and Interpretation Layer, and the Human Interaction Layer.
Workload-aware Scheduling Techniques for General Purpose Applications on Graphics Processing Units

In the last decade, there has been a wide scale adoption of Graphics Processing Units (GPUs) as a co-processor for accelerating data-parallel general purpose applications. A primary driver of this adoption is that GPUs offer orders of magnitude higher floating point arithmetic throughput and memory bandwidth compared to their CPU counterparts. As GPU architectures are designed as throughput processors, they adopt a manycore architecture with 10 to 100s of cores, each with multiple vector processing pipelines. A significant amount of the die area is dedicated to floating point units, at the expense of not having hardware units used for memory latency hiding in conventional CPU architectures. The quintessential technique used for memory latency tolerance is exploiting data-level parallelism in the workload, and interleaving execution of multiple SIMD threads, to overlap the latency of threads waiting on data from memory with computation from other threads. With each architecture generation, GPU architectures are providing an increasing amount of floating point throughput and memory bandwidth. Alongside, the architectures support an increasing number of simultaneously active threads. We envision that to continue making advancements in GPU computing, workload-aware scheduling techniques are required. In the GPU computing work flow, scheduling is performed at three levels the system or chip level, the core level and the thread level. The work proposed in the research aims at designing novel workload aware scheduling techniques at each of the three levels of scheduling. We show that GPU computing workloads have significantly varying characteristics, and design techniques that monitor the hardware state to aide at each of the three levels of scheduling. Each technique is implemented in a cycle level GPU architecture simulator, and their effect on performance is analyzed against state of the art scheduling techniques used in GPU architectures.
Reactive Planner Synthesis Under Temporal Logic Specifications

This paper proposes a novel, reactive control scheme for autonomous vehicles that fulfills mission specifications as defined by Linear Temporal Logic (LTL) formulas. Our method designs a point-to-point local planner utilizing control Lyapunov functions, which searches for a trajectory that satisfies given mission specifications, providing a path for the vehicle’s low-level controller to follow. Two key characteristics of this local planner are: 1) its ability to generate a trajectory responsive to the current state; and 2) its reflection of the reference path procured from offline planning. Our method exhibits adaptability to disturbances and efficiently guides the vehicle to meet mission requirements. We furnish simulation experiments which manifest the robust performance of our algorithm in diverse scenarios, including evading obstacles and maintaining control amid external disturbances. The proposed approach consistently delivers high mission completion rates and robustness in facing external perturbations.