Our Work

Abstract: Deep learning has great potential for environmental monitoring, yet real-world applications often face challenges from large-scale, multimodal, and noisy datasets. We introduce GreenNet, a f…

Abstract: Deep learning has great potential for environmental monitoring, yet real-world applications often face challenges from large-scale, multimodal, and noisy datasets. We introduce GreenNet, a flexible and open-source framework that makes it easier to build and scale deep learning models for remote sensing and environmental data. GreenNet offers reusable neural network modules, simple data integration tools, and built-in explainability features tailored for geospatial applications. To demonstrate its effectiveness, we apply it to case studies such as deforestation detection, urban heat island mapping, and air quality forecasting. These examples show that GreenNet delivers strong predictive performance while significantly reducing the effort needed to develop models. By connecting domain-specific data processing with modern deep learning techniques, GreenNet aims to make AI more accessible, reproducible, and interpretable for researchers and practitioners in environmental science.

Thermophotovoltaic (TPV) systems present a promising solid-state technology for direct conversion of infrared thermal radiation into electricity. However, conventional TPV devices rely heavily on expe…

Thermophotovoltaic (TPV) systems present a promising solid-state technology for direct conversion of infrared thermal radiation into electricity. However, conventional TPV devices rely heavily on expensive, rare III-V semiconductors or germanium (Ge) substrates, which restrict scalable commercial deployment. This paper presents a research and development proposal for a low-cost, high-efficiency, Germanium-Free Perovskite Thermophotovoltaic (TPV) solar cell architecture. The proposed design features a narrow-bandgap halide perovskite absorber integrated into a hole-transport-layer-free (HTL-free) cell configuration with a carbon top electrode. By integrating bandgap engineering, interfacial defect passivation, and optimized radiative spectral management, the system maximizes near-infrared (NIR) photon harvesting while minimizing non-radiative recombination losses. Optical and device physics simulations demonstrate high power conversion efficiencies under moderate thermal emitter temperatures (~1000–1400 K) with substantially reduced fabrication costs. This HTL-free perovskite TPV paradigm offers a durable, scalable, and economical blueprint for next-generation industrial waste-heat recovery, concentrated solar thermal energy harvesting, and thermal energy storage systems.

Maqolada pedagog xodimlarning kasbiy faoliyati davomida ularning sog’lig’iga yetkazilgan zararni qoplashning huquqiy mexanizmlari - mehnat va fuqarolik huquqi tutashgan nuqtada - tahlil qi…

Maqolada pedagog xodimlarning kasbiy faoliyati davomida ularning sog’lig’iga yetkazilgan zararni qoplashning huquqiy mexanizmlari - mehnat va fuqarolik huquqi tutashgan nuqtada - tahlil qilinadi. Muallif pedagoglik kasbiga xos, ammo milliy huquqiy adabiyotda deyarli e’tibordan chetda qolgan muammoni - ovoz apparatining kasbiy shikastlanishi (kasbiy disfoniya, surunkali laringit) misolida - butun maqola davomida izchil ochib beradi va bunday holatlarning “birdaniga yuz beruvchi shikastlanish” emas, balki asta-sekin to’planib boruvchi xarakterga ega ekanligi sababli amaldagi kompensatsiya tizimiga qanchalik yaxshi sig’ishini tanqidiy baholaydi. “Pedagogning maqomi to’g’risida”gi Qonun, Mehnat va Fuqarolik kodekslari, Vazirlar Mahkamasining ishchilarga yetkazilgan zararni qoplash qoidalari hamda tibbiy-mehnat ekspertizasiga oid normativ hujjatlar milliy va xorijiy huquqshunoslarning, jumladan Xalqaro Mehnat Tashkiloti materiallarining, ilmiy-nazariy qarashlari bilan qiyoslanadi. Muallif tomonidan pedagoglarning kasbiy kasalliklarini erta aniqlash va qoplashning maxsus, differensiallashtirilgan tartibini joriy etish modeli taklif etiladi.

RDF export of the ParliamentRAG knowledge graph covering the Italian Chamber of Deputies, 19th legislature: people (deputies, government members), parliamentary groups, committees, acts, EuroVoc topic…

RDF export of the ParliamentRAG knowledge graph covering the Italian Chamber of Deputies, 19th legislature: people (deputies, government members), parliamentary groups, committees, acts, EuroVoc topics, sittings, debates, full speech transcripts, ballots and 6.3M individual votes.Two files:parliamentrag_kg.ttl (Turtle): the structural KG — 863,837 triples;parliamentrag_votes.nt (N-Triples): the individual votes cast by each deputy in every electronic ballot.Ontology alignment: OCD (dati.camera.it), FOAF, W3C ORG, SKOS (EuroVoc), PROV-O, plus a small project namespace (https://w3id.org/parliamentrag/ontology#) for debate-structure terms aligned to Akoma Ntoso. Embeddings, retrieval chunks, user conversations and AI-generated summaries are not part of the export.Source data: open data of the Chamber of Deputies (dati.camera.it, CC-BY) and the EuroVoc thesaurus of the EU Publications Office. Derived graph released under CC-BY 4.0.Companion system described in: Tritella, Pozzi, Palmonari — "Who Speaks Matters: Authority-Aware Multi-View RAG over Italian Parliamentary Proceedings" (ISWC 2026).

This work encompasses our proposed algorithm for occlusion detection and reconstruction among rockfill particles in images, as well as a set of synthesized virtual images that are accompanied by occlu…

This work encompasses our proposed algorithm for occlusion detection and reconstruction among rockfill particles in images, as well as a set of synthesized virtual images that are accompanied by occlusion ground truth.

Abstract: Hands-on experience is essential in cybersecurity education. Without it, students learn the vocabulary but not the practical skills. OWASP Juice Shop is an intentionally vulnerable web appli…

Abstract: Hands-on experience is essential in cybersecurity education. Without it, students learn the vocabulary but not the practical skills. OWASP Juice Shop is an intentionally vulnerable web application that enables learners to practice real-world attack techniques—such as SQL injection, broken authentication, and Cross-Site Scripting (XSS)—without affecting live production systems. This review examines how Juice Shop has been incorporated into university courses, Capture the Flag (CTF) competitions, capstone projects, and hybrid learning environments. Drawing upon published studies, it evaluates what educational practices improve learning outcomes and which approaches are less effective. Existing research indicates that students generally demonstrate greater engagement, improved practical understanding, and better knowledge retention. However, integrating an open-ended penetration testing platform into a structured academic curriculum remains challenging, and not every implementation has produced consistent success. This review identifies effective practices, highlights current research gaps, and outlines future directions for cybersecurity education research.

This deposit accompanies the study "Machine-Learning Surrogates and Simulation-Validated Multi-Objective Optimisation of a BIPV Ceramic Textile Façade: Energy, Daylight and Thermal Comfort Trad…

This deposit accompanies the study "Machine-Learning Surrogates and Simulation-Validated Multi-Objective Optimisation of a BIPV Ceramic Textile Façade: Energy, Daylight and Thermal Comfort Trade-Offs Across European Climates". It quantifies how the binary weave pattern of a 28 x 12 Flexbrick ceramic lattice - with each brick optionally hosting one photovoltaic cell - governs building energy use, daylight, thermal comfort and photovoltaic yield. The deposit contains: Main dataset (data/): 2,560 cases (512 Sobol-sampled weave patterns x 5 European climates, 50 columns), CSV + Parquet, plus the geometry-only descriptor table, the bare-facade baseline KPIs with per-case deltas, the hourly load-matching indicators and the hourly PV series; Generalisation dataset: 1,950 cases spanning six architectural contexts (orientation east/west, room depth 3/7 m, window-to-wall ratio 30/75%); Optimisation results (results/): the six NSGA-III Pareto fronts (five per-climate plus the 23-pattern multi-climate robust front) and the 28-solution re-simulation validation; 65 trained surrogate models (random forest, XGBoost and MLP per indicator, plus context-aware "generalist" models); The full reproducible pipeline (EnergyPlus + Radiance + pvlib simulation, dataset assembly, surrogate training, SHAP interpretability, NSGA-III optimisation and validation), the base EnergyPlus building model and the EDA notebook; PNG previews of all 513 facade configurations; Supplementary Material source tables (surrogate performance, context transfer, sensitivity studies, NSGA-III convergence, symmetry/order correlations, thermal-mass/vented-cavity spot-check); A column-level data dictionary describing every variable with units, ranges and definitions. Each pattern was evaluated, for every climate (IWEC typical years for Berlin, Barcelona, Seville, Helsinki and Turin), with coupled EnergyPlus 22.2 (energy and comfort), Radiance (climate-based daylight modelling) and pvlib (vertical south-facing BIPV) simulations on a single-zone 3 x 5 x 3 m perimeter office (15 m2 floor, south window-to-wall ratio 54%, ideal-loads HVAC). All performance indicators are anchored to a simulated bare-façade (no-screen) baseline. The surrogate models use a leakage-safe, configuration-grouped train/test split, and the NSGA-III optima are validated by full re-simulation. Energy-use intensities are reported per floor area (15 m2). The raw per-job simulation output (tens of GB) is not included but is fully reproducible from the released code; the five IWEC weather files are referenced by name in the README (not redistributed, ASHRAE copyright). New in v1.3.0: optimisation and validation results (results/), load-matching indicators, per-case baseline deltas, hourly PV series, feature-importance tables; ZIP paths normalised. Data, models, the data dictionary and the previews are released under CC BY 4.0; the source code is released under the MIT License. Please cite both this dataset (DOI above) and the accompanying paper.

Abstract The impact of mothers mental health status on the wellbeing of children in the coastal communities of Akwa Ibom State, Nigeria was studied. The study was driven by the increasing concern of t…

Abstract The impact of mothers mental health status on the wellbeing of children in the coastal communities of Akwa Ibom State, Nigeria was studied. The study was driven by the increasing concern of the impact of maternal mental health issues on children's development, health, and wellbeing, specifically in socio-economically disadvantaged coastal communities. Specifically, the study evaluated the socio-economic status of mothers and its implications on children's wellbeing in coastal areas of Akwa Ibom State, the effect of maternal depression on children aged below five years and the effect of maternal anxiety disorders on children's wellbeing. This study used a descriptive survey design and a qualitative research approach. The methods used in the collection of data were In-Depth interviews (IDIs), Key Informant interviews (KIIs), and Focus group discussions (FGDs). A total of 120 participants comprising of mothers who were being treated in the Psychiatric Hospital Eket, Iquita General Hospital Oron, General Hospital Ituk Mbang, and some of the traditional mental health centres in Oron, Adadia and Oku Iboku were engaged. Thematic analysis was used to analyse the data based on the study objectives. The results indicated that maternal depression has a negative impact on children through emotional neglect, poor mother-child relationship, supervision, behavioural instability and developmental problems in children under 5 years. The study also revealed that the mothers' anxiety disorders result in inconsistent care and parenting, emotional insecurity, poor health-seeking practices, and susceptibility of children to neglect and abuse. It was also found that low SE status exacerbates maternal psychological distress, and restricts access to health, nutrition, education and other resources required for children's healthy development. The key factors cited as exacerbating maternal mental health problems and child wellbeing were poverty, unemployment, family instability and poor social support. The study finds that mothers' mental health status has a significant impact on the wellbeing of children in coastal communities of Akwa Ibom State. It suggests boosting community-based mental health services, establishing mental health screening as part of maternal and child health programmes and also introducing economic empowerment programmes for mothers to enhance both maternal mental health status and child wellbeing.   Keywords: Mothers, Mental health, Children’s wellbeing, Coastal areas, Depression, Anxiety