Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy demand prediction in smart buildings using advanced machine learning techniques

Reduction of energy consumption is essential to reduce energy waste. This is even more important in the building sector that accounts for 27% of total CO 2 emissions in Europe. In this work, we propose to use available data from a smart building in the NUIG campus (Ireland) to generate black-box models for energy demand prediction using advanced machine-learning techniques. In this paper, we present the first step for an accurate estimation of the energy consumption in buildings. Firstly, hierarchical clustering is used to find the most probable system health state. Secondly, the energy demand models for that state are used to estimate the intended energy consumption. Experimental results showed that the energy demand models specific for a state performs better than a general model for all the system states, confirming our initial hypothesis. This work can be the foundation to perform predictive maintenance based on the energy prediction. In the absence of system faults, a deviation in the energy consumption can be related to tear and wear problems, thus prompting the need for maintenance. Consequently, the reduction in energy consumption due to early detection of a degradation problem will also help to reduce maintenance costs.
CHARACTERIZATION AND MITIGATION OF INSUFFICIENCIES IN AUTOMATED DRIVING SYSTEMS

Automated Driving (AD) systems have the potential to increase safety, comfort and energy efficiency. Recently, major automotive companies have started testing and validating AD systems (ADS) on public roads. Nevertheless, the commercial deployment and wide adoption of ADS have been moderate, partially due to system functional insufficiencies (FI) that undermine passenger safety and lead to hazardous situations on the road. In contrast to system faults that are analyzed by the automotive functional safety standard ISO 26262, FIs are defined in ISO 21448 Safety Of The Intended Functionality (SOTIF). FIs are insufficiencies in sensors, actuators and algorithm implementations, including neural networks and probabilistic calculations. Examples of FIs in ADS include inaccurate ego-vehicle localization on the road, incorrect prediction of a cyclist maneuver, unreliable detection of a pedestrian in rainy weather using cameras and image processing algorithms, etc. The main goal of our study is to formulate a generic architectural design pattern, which is compatible with existing methods and ADS, to improve FI mitigation and enable faster commercial deployment of ADS. First, we studied the 2021 autonomous vehicles disengagement reports published by the California Department of Motor Vehicles (DMV). The data clearly show that disengagements are five times more often caused by FIs rather than by system faults. We then made a comprehensive list of insufficiencies and their characteristics by analyzing over 10 hours of publicly available road test videos. In particular, we identified insufficiency types in four major categories: world model, motion plan, traffic rule, and operational design domain. The insufficiency characterization helps making the SOTIF analyses of triggering conditions more systematic and comprehensive. To handle faults, modern ADS already integrate multiple AD channels, where each channel is
A HUMAN MACHINE INTERFACE SUGGESTED FROM NEUROSCIENTIFIC ANALYSIS OF HUMAN FACTOR

Honda aims for zero traffic collision fatalities involving Honda motorcycles and automobiles globally by 2050. To realize a zero traffic-incident society, we need to minimize human driver errors. Improper processing of information should trigger human errors during driving, however, despite its importance for our society, neural mechanisms during driving that can lead to catastrophic traffic consequences remain unclear. To clarify these, we have researched the relationships among drivers’ manipulation, gaze, and brain activation. In particular, we have focused on the human eye gaze because it is not only a passive input organ, but also reflects dynamic information processing in the brain. To investigate the human brain mechanisms involved in safe and secure driving, we scanned the human brain using functional magnetic resonance imaging(fMRI) while driving in an MRI-compatible driving-simulator. We introduce one of the experiments showing differential brain activation between safe drivers and control drivers manipulating a vehicle in ordinary traffic conditions. In this experiment, participants were healthy adults, and they manipulated the driving-simulator in the MRI scanner, while their
Swallowing difficulty and its association with nutritional risk among stroke patients in a primary healthcare facility

Background: Swallowing difficulty is common in stroke patients and is associated with prolonged inadequate food intake. This eventually leads to malnutrition and dehydration and contributes appreciably to stroke complications and mortality rates. The associated nutritional risk is often undetermined. Objective: To determine the prevalence of swallowing difficulty among stroke patients and its association with their dietary intake and nutritional risk. Methods: The study design was cross-sectional, involving 57 stroke inpatients recruited from the Polyclinic, Korle-Bu Teaching Hospital. Swallowing difficulty and dietary intake were assessed using the water swallowing test and 24-hour recall interviews respectively. Nutritional risk was determined using the Nutritional Risk Screening tool (NRS-2002). Data were analysed using SPSS version 21.0 at a 95% confidence interval. Significance was set at p < 0.05. Results: Mean age was 64.3 ± 15.9 years. The majority (57.9%) had swallowing difficulty with an 8-fold higher nutritional risk compared to those without swallowing difficulty [R 2 = 0.754; OR= 8.40; p = 0.010 (CI = 2.177 - 32.128)] after adjusting for age, gender, education and occupation. Median daily energy intake was significantly lower in the former [628kcal; (483-1003)] compared to the latter [(1,017 kcal; 600 - 1586); p = 0.025]. Conclusion: More than half of the participants had swallowing difficulty with a significantly higher nutritional risk and lower daily energy intake. Early routine assessment of nutritional risk, followed with timely appropriate interventions, is strongly advocated as part of standard operating procedures for stroke management in primary care to reduce stroke complications and mortality.
Search, Matching, and Online Platforms ∗

Recent technological advances offer solutions to alleviate search and information frictions in matching markets. Consequently, online platforms have emerged as dominant players in modern matching markets. We explore the incentives of an online platform to harness further technological advances through the lens of a dynamic two-sided search model with horizontally differentiated agents and platform-mediated search-and-matching. We find that the platform has incentives to invest in reducing search frictions, but lacks incentives to improve the quality of information it collects and shares about the compatibility of potential partners. Moreover, in equilibrium, reductions in search frictions and improvements in the quality of information both reduce the fees charged by the monopolistic platform and enhance consumer welfare.
The Mathematics of Voting and Elections : A Hands-On Approach

2. Review of Games of No Chance (1998, Edited by Richard Nowakowski), More Games of No Chance (2002, Edited by Richard Nowakowski), and Games of No Chance III (2009, Edited by Michael Albert and Richard Nowakowski. Review by William Gasarch. The mathematics behind games that do not involve any luck is deep. On the other hand you also want to learn how to WIN these games. These volumes contain several types of articlesmathematical, practical, natural games, unnatural games.
NAS: A Neural Attention-based SLAM for Autonomous Navigation in Unknown 3D Environments

Navigation in unknown 3D environments aims to progressively ﬁnd an eﬃcient path to a given target goal in unseen scenarios. A challenge is how to explore the navigation quickly and eﬀectively. An end-to-end learning approach is proposed to extract geometric shapes from RGB images, but it is not suitable for large environments due to its exhaustive exploration with exponential search space. Active Neural SLAM (ANS) presents a semantic map to maximize exploration coverage to tackle the object goal navigation task, but ANS still visits the explored areas frequently since the unproper local target selection. In this paper, we propose a neural attention SLAM (NAS) model to explore unknown 3D environments. Spatial attention is provided to quickly identify colorful obstacles (such as tea table or ﬂoor). We also leverage the priority of unknown regions in the short-term goal decision to avoid frequently exploration with a channel attention. The experimental results show that our model can build a more accurate map than ANS and other baseline methods with less running time. In terms of relative coverage, NAS achieves a 0.5 % improvement over ANS in overall and a 1.1 % improvement over ANS in large environments.
The effects of a mindfulness training intervention on fatigue and job satisfaction among emergency nurses: A quasi-experimental study

Background: Fatigue is a challenging problem for nurses working in the emergency department and makes them dissatisfied with their jobs. Objectives: This study examined the effects of a mindfulness training intervention on fatigue and job satisfaction in emergency nurses. Methods : A quasi-experimental study was conducted with 80 emergency department nurses in 2022. Participants were randomly assigned into an intervention group (n=40) and a control group (n=40). The intervention group received eight mindfulness training sessions, while the control group received no intervention. Data was collected using the Minnesota Satisfaction Questionnaire and the Multidimensional Fatigue Inventory a few days before the start and immediately after the end of the intervention. Descriptive statistics, t-test, paired t-test, and analysis of covariance (ANCOVA) were used to analyze the data. Results: The two groups did not differ significantly in their pretest fatigue mean scores. However, all posttest fatigue mean scores decreased in the intervention group, and the between-group differences were statistically significant (P < 0.05). The two groups also did not differ significantly in their pretest scores for internal, external, and general job satisfaction (P> 0.05). However, all posttest job satisfaction mean scores increased in the intervention group, and the between-group differences were statistically significant (P < 0.05). The ANCOVA showed that the nurses’ pretest scores had no significant effect on the posttest scores for fatigue and job satisfaction. Conclusion: This study supports the potential benefits of the mindfulness intervention in overcoming fatigue and improving job satisfaction of nurses working in emergency department. Nurses are recommended to learn and implement mindfulness-based interventions to reduce their fatigue and improve their job satisfaction.
Anomaly detection through stream processing

Anomaly detection is a crucial problem in many contexts. This project is about detecting abnormal events, which patterns are unknown, in the context of streaming data. For this purpose, we selected two data-driven methods (Adwin and PageHinkley) able to monitor for changes in a stream. With the help of several data-sets, we tested the performances and the main features of these algorithms. Evaluating and comparing the performances when there is not a well-defined ground truth available is complex. Thus, we have introduced some modification on the datasets that allowed a more rigorous evaluation of the algorithm’s performances while enabling comparisons. The experiments demonstrate that the Adwin is more flexible than the Page-Hinkley. Overall its performances are better that the Page-Hinkley ones. However, the Page-Hinkley is less expensive in terms of computational cost and memory. Moreover, it is able to obtain better performances in cases where it is possible to clearly separate the normal behavior of the stream from the abnormal one. Finally, the Adwin is not able to handle single outliers while the Page-Hinkley does.
UJI DIAGNOSTIK SENSITIVITAS DAN SPESIFISITAS PEMERIKSAAN FNAB DENGAN HISTOPATOLOGI SEBAGAI BAKU STANDAR DALAM MENDIAGNOSIS IBC (Invasive Breast Carcinoma)

Abstrak: Uji Diagnostik Sensitivitas Dan Spesifisitas Pemeriksaan Fnab Dengan Histopatologi Sebagai Baku Standar Dalam Mendiagnosis IBC (Invasive Breast Carcinoma). Tumor dapat terjadi pada jaringan payudara dan menyebabkan penyakit seperti kanker payudara dan karsinoma payudara. Selain kelenjar susu dan saluran kelenjar, tumor ini bisa menyebar ke jaringan lemak dan jaringan ikat payudara. Pertumbuhan kanker berpotensi bermetastasis. Metastasis mengacu pada penyebaran tumor. Tujuan penelitian ini adalah membandingkan keakuratan pemeriksaan FNAB untuk mendeteksi IBC (Invasive Breast Carcinoma) di RSUD Dr. H. Abdul Moeloek Bandar Lampung tahun 2022 dengan gold standard Histopatologi. Penelitian deskriptif analitik, yang berupaya memberikan penjelasan terhadap suatu fenomena merupakan metode yang digunakan. Investigasi ini menggunakan metodologi cross-sectional Penelitian ini menemukan bahwa pemeriksaan FNAB mempunyai sensitivitas sebesar 96.6% dan spesifisitas sebesar 100.0%. Temuan penelitian ini menunjukkan bahwa FNAB memiliki sensitivitas dan spesifisitas yang tinggi untuk mengidentifikasi kanker payudara. Sensitivitas dan spesifisitas pemeriksaan FNAB untuk histopatologi yang dilakukan di RSUD Dr. H. Abdoel Moeloek Bandar Lampung telah ditetapkan sebagai standar emas dalam pengujian diagnostik. Sensitivitas tes FNAB dihitung sebesar 96.6%, sedangkan spesifisitasnya dihitung sebesar 100%. Hal ini menunjukkan tingginya kegunaan diagnostik pemeriksaan FNAB dalam mendeteksi kanker payudara.
RETHINKING THE SOCIAL IN SOCIAL MEDIA

This paper makes an argument for the value of including sexual sites in definitions and analyses of social media. Building on interview data (four developer interviews and 56 user interviews) from three North European sexual platforms (Darkside, Alastonsuomi and Libertine.Center) devoted to nudity, sex, and kink, it examines the implications of defining sex platforms as social media and the analytical avenues that the inclusion of sexual sites opens up for understanding forms of sociability within them. We start by mapping the studied platforms as built infrastructures that shape and constrain sociality, with a particular focus on developer dialogue with the broader social media ecosystem. We then discuss how these built spaces are used and experienced as “socio-sexual silos” with a particular focus on notions of safety. Finally, we consider what this means for sociality on social media and propose “context promiscuity” as a conceptual aid for unpacking this.
Azimuthal Seismic Anisotropy in the Upper Crust of the Japanese Islands Induced by the 2011 Tohoku‐Oki Megathrust Earthquake

We investigated VP/VS changes in the upper crust of the Japanese islands after the 2011 MW9.0 Tohoku‐Oki megathrust earthquake. Abrupt VP/VS changes with azimuth‐dependent variations were observed after the megathrust earthquake. The VP/VS changes ranged between −0.0458 (±0.0012) and 0.0422 (±0.0033). Large localized VP/VS changes over regional distances suggested medium‐dependent deformation. Peak VP/VS changes were observed along paths subparallel or subperpendicular to the directions toward the megathrust earthquake. The VP/VS changes displayed characteristic 2θ variations as a function of the azimuth difference, suggesting azimuthal seismic anisotropy. The VP/VS ratio recovered gradually over time. Some regions presented permanent VP/VS changes. The azimuthal seismic anisotropy may have developed from preferential crack orientation as a consequence of the combined effects of lithospheric displacements and a depth‐dependent ambient stress field. It appears that recovery of the medium properties may take decades.
Role of Knowledge Management Process in Fostering Employee Performance: Assessing the Moderating Effect of Smart Technologies

Purposes-The Patients are considered Customers in the Healthcare sector. So, they expect high-quality services and the best employee performance. Patient’s awareness of the service's excellence in healthcare is considered one of the main factors in measuring the service's quality. Therefore, this study aims to examine the link of the knowledge management process (KMP) with the performance of the employees in the health cluster of Hail. This study also focuses on the moderating role of smart technologies between the Knowledge management process and employee performance in the case of the Hail health cluster. Design/Methodology/Approach- Data was collected from the employees of Hail health cluster, Saudi Arabia. The sample size for the data analysis is 380, and data is gathered from May to August 2023 with the help of a well-structured questionnaire. Findings are extracted with the help of Smart PLS. Findings- The results of the current study illustrate that the knowledge management process has a positive relationship with employee performance. Smart technologies help to increase the KMP and further enhance the performance of employees working in the health cluster in Hail. Research limitation/implications- This study has comprehensively examined (KMP) as an independent variable influencing employee performance. Still, upcoming examinations can use other measurements of knowledge management, such as knowledge management capabilities, knowledge management practices, etc. Furthermore, this study is limited to the service sector, so future studies can use this model for the manufacturing sector to analyse the accuracy of the model. Originality/Value - This research explains the relationship between Knowledge management processes, employee performance and smart technologies in the healthcare sector. This study attracts this sector to use smart technology because the use of technologies not only increases the knowledge management process but also enhances the work abilities of employees. Based on the findings, this study has a unique contribution in the dust of studies related to knowledge management, such as no study to date conducted using a combination of these variables. This study is the best literature for policymakers, health management and researchers.
Biodegradation potential of Aspergillus niger on crude oil contaminated soil.

The biodegradation potential of Aspergillus niger was investigated on soil experimentally contaminated with crude oil. The fungal load dynamics of Aspergillus niger and some chemical parameters of the contaminated soil were determined using standard microbiological and analytical methods. The parameters were determined at weekly intervals and at varying levels of crude oil concentration (10%, 20%, 30% and 40%) for a period of six weeks. There was a progressive increase in the fungal load dynamics (3.6x10 4 ±0.05cfu/g -1.43x10 5 ±0.06cfu/g; 4.2x10 4 ±0.02cfu/g 1.41x10 5 ±0.02cfu/g; 2.6x10 4 ±0.04cfu/g 1.32x10 5 ±0.05cfu/g and 3.5x10 4 ±0.01cfu/g 1.42x10 5 ±0.02cfu/g) from week one to week six at 10%, 20%, 30% and 40% crude oil concentrations respectively. The highest fungal load (1.43x10 5 ±0.06cfu/g ) was recorded on 10% crude oil concentration at week six while the lowest fungal load (2.6x10 4 ±0.04cfu/g) was recorded on 30% crude oil concentration at week one. The result of the total petroleum hydrocarbon (TPH) showed a progressive decrease ( 1642.02±0.047mg/kg 600.52 ± 0.047 mg/kg; 1286.80 ± 0.047mg/kg-397.98±0.047mg/kg; 1908.3±0.047mg/kg 759.28±0.047mg/kg and 2228. 7±0.047mg/kg 778.88±0.047mg/kg) from week one to week six at 10%, 20%, 30% and 40% crude oil concentrations respectively. Other parameters such as pH (5.74±0.124 6.50±0.047) and percentage nitrogen (0.103±0.020% 0.266±0.020%) showed progressive decrease and increase respectively as observed on the crude oil concentrations from week one to week six. All tests were done in triplicates. The result indicates the potential of Aspergillus niger in the degradation of crude oil as evidenced in the progressive reduction in the total petroleum hydrocarbon. The use of Aspergillus niger in the biodegradation of crude oil polluted soil is therefore recommended.
Relationship Between Corneal Astigmatism and Intraocular Pressure

Aim of the work: this study aimed to investigate the relationship between the Intraocular Pressure(IOP) readings measured by Goldmaan Tonometry and the amount of corneal astigmatism in healthy young subjects and to assess the reliability of the measurements obtained with the instruments. Method: intraocular pressure measurements were obtained by Goldmann Applanation Tonometer (GAT) (Haag-Streit International, Koeniz, Switzerland), while keratometry readings for corneal curvature were obtained by an Auto-Kerato-Refractometer (ARK-KR.8800, Topcon, Tokyo, Japan). An interval was kept between the keratometric measurements and the IOP measurements. The sequence of measurement was randomized with all participants. Three measurements were taken within ten minutes and the reading was set to one immediately after any measurement were taken. Result: the average age of the volunteers was 22.4 ± 1.5 years (mean age ± SD; range: 20–26 years). Mean Intraocular Pressure (IOP) of the right and left eyes in the first visit (Paired t-test: P = 0.6471) and second visit (Paired t-test: P = 0.5805). The session one means GAT ; IOP was 16.48 ± 3.33 mmHg and 16.59 ±3.47mmHg (right and left eye respectively), while in session two it was15.714±3.10 mmHg and 15.82 ± 2.76 (right and left eye respectively) . The mean corneal astigmatism was -0.24 ± 1.48D, -0.38 ± 1.53 D, right and left respectively in the first visit and -0.34 ± 1.44D, -0.40 ± 1.64D right and left eye second visit respectively. Conclusion: the GAT-IOP was less affected by the amount of corneal astigmatism and GAT-IOP was not significantly higher in eyes with greater corneal astigmatism and the repeatability results, although the differences were stastistically significant, they were not clinically significant.
Bio Fertilizers with Organic Manures: a Better Strategy for Sustainable Productivity

One of the major crop productivity constraints in the third world is the unavailability of crop nutrients in appropriate amount and form [1]. Modern agricultural practices emphasize widespread use of fertilizers which certainly increased grain yield in many countries in the last six decades. However, long term use of chemical fertilizers also led to a decline in crop yield and soil fertility in the intensive cropping system [2]. It is evident that over fertilization increases concentration of several plant nutrients in surface as well as ground water, which creates a potential health hazard. This has in turn paved the way for integrated plant nutrient management. The use of renewable resources and inputs is one the fundamental principles of sustainable agriculture that enables maximum crop productivity and minimal environmental risk [3]. Therefore, an increased yield with reduced environmental risk requires new cultivation strategies including biological fertilizer [4]. Bio fertilizer is a natural input that can be applied as a complement to, or as a substituent of chemical fertilizer in sustainable agriculture [5]. Integrated use of biofertilizers with natural manures offer a low capital investment and eco-friendly route to boosting farm productivity [6]. Chemical fertilizers have outstandingly boosted crop yields about three decades back. However, yields are currently getting low or stagnated. Moreover, poor-resource holder farmers in developing countries apply little or no fertilizer due to high cost of procurement.