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Evolution of water resources in a context of variability and climate change: Case of the Bouregreg and Chaouia watershed
No full textThe Bouregreg and Chaouia river basin is one of basins most affected by variability and climate change. The insufficient rainfall recorded over the last decade had a considerable impact on the availability of water resources. The Sidi Mohamed Ben Abdellah dam reservoir has been characterized by a downward trend. And, if we add to this, the excessive use of this reservoir by a population exceeding 8,356,829 inhabitants, The dam alone no longer has the capacity to supply drinking and industrial water to the coastal cities from Kenitra to Casablanca. The main objective of this study is to quantify the rainfall deficit, statistically monitor spatio-temporal trends in precipitation in the Bouregreg and Chaouia watersheds, detect their impact on the evolution of surface water resources (1991-2024), and to highlight the strategy adopted to face water scarcity in the basin's large cities. The adoption of a cross-methodological approach based on descriptive statistics and spatial remote sensing made it possible to determine the main drought sequences, monitor the spatio-temporal trends in rainfall indices, and map the surface area occupied by water at the SMBA dam. The results obtained reveal a remarkably visible water shortage throughout the basin due to multiple climatic and anthropogenic factors
The Affect of Image Lighting in Determining Anchor Box for Vehicle Object Detection using Faster R-CNN
No full textEffective traffic management is a critical component in urban safety and the efficiency of road use. Modern traffic system to manage traffic uses the ability to detect traffic to better adjust traffic flow. Object detection can be used in such cases, where CCTV feed is used as a reference to locate and count vehicles. Data collection was carried out during both day and night situations. Faster R-CNN is one of such algorithms that has proven to be robust for object detection. It uses a two-stage process that makes use of anchor boxes to determine the existence of objects in an image. This research aims to find out the effects of differing lighting conditions on the road on the effect of the anchor box used for the model to get the best result. Under both day and night conditions, the best models used anchor size of [64x64; 128x128; 256x256; 512x512] and anchor ratio of [0.5; 1.0; 2.0]. Lighting conditions does not seem to affect the choice of the anchor box set. It is found that smaller and more varied anchor sizes lead to lower RPN loss. While a more diverse set of anchor ratios provides smaller detector loss
Water Quality Prediction using LSTM: A Deep Learning Approach at Wat Makham Station, Chao Phraya River, Thailand
No full textThis study develops a Long Short-Term Memory (LSTM) neural network for forecasting water quality parameters at the Wat Makham Station based on data collected from the Chao Phraya River, Thailand, for nine months. The study used IoT sensors to collect real-time values for ten water quality indicators: Turbidity (TURB_NTU), Optical Dissolved Oxygen (HDO), Dissolved Oxygen Saturation (HDO_SAT), Spatial Conductivity (SPCOND), Acidity/Basicity (pH), Total Dissolved Solids (TDS), Salinity (SALINITY), Temperature (TEMP), Chlorophyll (CHL), and Depth (DEPTH). The study identified water quality indicators through the implementation of an LSTM model following application of data cleansing techniques, using mainly the Interquartile Range (IQR) method for outlier detection. The results confirm that prediction accuracy varied across parameters. For stable indicators, very high prediction accuracy was achieved: for pH, MSE = 0.0064, MAPE = 0.89%, RMSE = 0.0800, and RMSPE = 1.12%; for salinity, MSE = 0.0006, MAPE = 10.55%, RMSE = 0.0246, and RMSPE = 41.14%. Temperatures were predicted with high confidence also: MAPE = 2.59% and RMSPE = 3.24%. In contrast, highly volatile parameters were difficult to predict; Turbidity MAPE = 32.87% and RMSPE = 109.22%; Chlorophyll MAPE = 38.64% and RMSPE = 190.15%
Geolocation Framework using Google Maps for Secure Distance-Based Carbon Savings Stamp in Work from Anywhere Models
No full textThe transition toward the WFA model marks a major change in organizational operations, supported by rapid digital innovation and the increasing need for flexible work arrangements. By utilizing cloud services, virtual collaboration platforms, and secure remote access systems to enable employees to perform their task efficiently regardless of geographic location. However, this model also brings new cybersecurity challenges. Threats such as social engineering attacks, the use of personal devices outside formal security controls, and exposure to unsecured public networks. Despite these risks, adopting remote working practices also contributes to environmental sustainability. Consequently, the adoption of flexible work models not only addresses productivity demands but also delivers tangible contributions to carbon-reduction initiatives. The reduction in carbon emissions derived from employee commuting distances can be further processed into a unique digital representation. Each unit of carbon savings is assigned a unique digital stamp, serving as a code for environmentally friendly work activities. This positive impact can be assessed with greater accuracy using technological tools, such as calculating the distance between home and the central office using the Google Maps API. Through this technological integration, the study proposes a geolocation-based WFA framework that ensures security and reliability within the digital work ecosystem
Level-dependent hearing protectors can switch the perception of sound direction
No full textLevel-dependent hearing protectors enable listeners to perceive soft to medium-level sounds, while protecting the ear against hazardous high-level signals. The impact of these devices on localization ability due to changes in interaural cues is mostly unknown. This study investigated the influence of two hearing protectors (earplug and earmuff) in passive and one active setting on localizing two common alarm signals in noise at two signal levels compared to open ears. A listening test with 16 normal-hearing participants was conducted inside a horizontal array of 48 loudspeakers. Additionally, the stimuli were recorded with an artificial head in the same setup to calculate the corresponding occurring interaural cues. The results showed that especially one of the devices under test altered the perception of target direction, even causing alarms from one side to be misperceived as coming from the opposite side of the head. The technical measurements support these findings by revealing large changes of interaural level differences with this device compared to open ears, mostly aligning with participant responses. These findings indicate the need to test electronic hearing protectors regarding altered interaural cues to avoid safety risks due to impaired localization. Moreover, measurements of these cues can help predicting the perceived sound direction by human listeners
Community-Based Urban Agriculture as a Strategy for Sustainable Food Security: Evidence of Yogyakarta, Indonesia
No full textUrban agriculture through a community-based approach will empower residents to transform underutilized space into productive food sources, thereby increasing the food security of households and the surrounding environment. This study examines the role of women farmer groups in optimizing urban home yard utilization in Yogyakarta City through a community-based approach to urban farming, contributing to local food security. Despite having underutilized yards and limited engagement, these women possess significant potential to enhance household and community resilience. Using a quantitative descriptive analysis method, the research sampled 48 respondents selected via Multistage Random Sampling. Findings indicate that women farmer groups play a moderate role as learning hubs, cooperative platforms, and production units in urban farming activities. Spearman Rank Correlation analysis reveals that key factors influencing their role include age, farming experience, participation levels, leadership, agricultural extension support, and government involvement. The study highlights how urban farming, when supported by community-based initiatives, can strengthen food security by empowering women, improving resource efficiency, and fostering collaborative local food production. These insights underscore the importance of policy and institutional support in scaling up urban farming for sustainable food systems in urban areas
Experimental study on the effect of austenitic stainless steel filler wires (AISI 308L & AISI 304L) on the metallurgical and mechanical properties of ferritic stainless steel AISI 409 welds
No full textThis study examines practical measures to mitigate crack formation in ferritic stainless-steel grade AISI 409 during Tungsten Inert Gas (TIG) welding. AISI 409 is widely used for mufflers and exhaust components. However, AISI 409 joints often developed fusion-line cracks following autogenous welding and the subsequent spinning process, resulting in over 20% rejection. To better understand how these failures occur, we examined the welding procedure, process parameters, and metallurgical aspects that may contribute to crack formation. As a corrective measure, AISI 409 plates were welded using AISI 308L and AISI 304L filler wires and then evaluated using Non-Destructive Testing, Metallography, Tensile Testing, and Fractography. The samples welded with AISI 308L showed a clear improvement in ductility, with elongation increasing by about 15%. This may be linked to its austenitic composition, which likely promotes a softer, more deformable weld metal. Fractography supported this observation, as the 308L joints exhibited a higher density of micro-voids, suggesting greater plastic deformation before fracture. Welds made with AISI 304L performed moderately better than the autogenous welds but did not match the improvements seen with 308L. Overall, the results point to a systematic route for improving weld integrity and significantly lowering rejection rates in AISI 409 components used in the automotive sector, which in turn supports better consistency and reliability in industrial applications
Multi-response optimization of bamboo/PALF–TiC hybrid composites for enhanced mechanical and tribological performance
No full textResearchers have developed alternative materials which incorporate diverse fillers and reinforcements in response to increasing requirement wear-resistant hybrid substances. Recent research had shown that hybrid composites made from a mix of natural fibers then ceramic fillers can improve tribological properties of materials used in automobiles and airplanes. A composite with improved tribological and mechanical characteristics at low cost can be achieved by combining natural fibers with ceramics using appropriate multi-response optimization approaches, despite the fact that natural fibers have certain drawbacks. This research delves into the wear behavior of a hybrid composite made of bamboo and PALF, filled with titanium carbide (TiC). Furthermore, this study employs a multi- response optimization method that integrates MOORA with the fuzzy model interference system. To find the lowest possible wear rate and coefficient of friction (COF), the Taguchi L27 orthogonal array (OA) was used in the experimental design. The investigation found that, the best working settings were 1 wt% TiC, 30 wt% reinforcement, 1.5 m/s sliding speed, 15 N load and 1500 m sliding distance with an Entropy - MOORA value of 0.804 and a MOORA fuzzy analysis (MFA) value of 0.801. The worn-out surface mechanisms, and tiny debris were all shown by scanning electron microscopy (SEM) to play a substantial role at achieving appropriate wear properties. In addition, mechanical properties were investigated in both wet and dry environments to determine optimal combination of particle hybrid composite
Synthesis and characterization of a new Azo dye and study of its adsorption mechanism on graphene oxide nanoparticles
No full textIn this study, a novel azo dye was successfully synthesized, and its molecular structure was confirmed using comprehensive spectroscopic analyses. The adsorption performance of the dye onto graphene oxide (GO) nanoparticles was systematically investigated to evaluate its potential as an effective nano-adsorbent for pollutant removal. Thermodynamic analysis revealed that the adsorption process was exothermic, indicating stable interactions between the dye molecules and the graphene oxide surface. Kinetic modeling demonstrated that the adsorption behavior followed a pseudo-second model, suggesting that chemisorption is the dominant mechanism controlling the adsorption rate. Overall, the results highlight the promising applications of graphene oxide nanoparticles as effective materials for removing dyes and organic pollutants from aqueous environments