Static Techniques Research Articles

The formation of exciplex and triplet-triplet transfer in organic room temperature phosphorescent guest-host materials.

Organic materials typically do not phosphoresce at room temperature because both intersystem crossing (ISC) and phosphorescence back to the electronic ground state are slow, compared to the nonradiative decay processes. A group of organic guest-host molecules breaks this rule. Their phosphorescence at room temperature can last seconds with a quantum efficiency of over 10%. This extraordinary phenomenon is investigated with comprehensive static and transient spectroscopic techniques. Time-resolved vibrational and fluorescence spectral results suggest that a singlet guest-host exciplex quickly forms after excitation. The formation of exciplex reduces the singlet-triplet energy gap and helps facilitate charge separation that can further diffuse into the host matrix. The heavy atoms (P or As) of the host molecule can also help enhance the spin orbital coupling of the guest molecule. Both boost the rate of ISC. After the singlet exciplex transforms into the triplet exciplex through the ISC process, UV-visible transient absorption spectroscopic measurements support that the triplet exciplex quickly transforms into the guest molecule triplet state that is at a lower energy level, thereby reducing the reverse ISC-induced triplet population loss. Finally, the long-lasting separated charges that diffused into the host matrix can diffuse back to the guest hole to form new triplets, and the dilution effect of the host molecules can effectively reduce the triplet quenching. All these factors contribute to the dramatic enhancement of phosphorescence at room temperature.

Evaluasi Trade-off Akurasi dan Kecepatan YOLOv5 dalam Deteksi Kebakaran pada Edge Devices

Real-time object detection using the YOLO (You Only Look Once) algorithm has shown promising performance in various computer vision applications. However, its application on devices with limited resources is still a challenge due to its high computational requirements. This study aims to optimize the YOLOv5 model for fire and smoke detection on Orange Pi Zero 3 devices using quantization techniques. Using a dataset of 2247 fire and smoke images, this study applies static quantization techniques to improve model efficiency. The methodology includes training of standard YOLOv5 models, conversion to ONNX format, and application of static quantization. Results show a significant improvement in computational efficiency, with a 42.2% reduction in model size and a 65.21% increase in inference speed. Despite a decrease in the mAP value by 25.6%, the optimized model was still able to perform object detection at a significantly higher speed. In conclusion, the quantization technique is effective in optimizing the YOLOv5 model for deployment on edge computing devices, despite the trade-off between speed and accuracy.

Blade tip clearance measurement method based on blade tip timing without the once per revolution sensor

Abstract The rotor blade tip clearance (BTC) of an aeroengine is a critical parameter that significantly impacts its performance and safety. Accurately determining dynamic BTC has been a focal point of research in experimental testing. Among the effective measurement methods for dynamic BTC, the laser triangulation method based on blade tip timing (BTT) stands out. However, this method typically relies on an once-per-revolution (OPR) sensor for rotor speed and blade serial number information during measurement, leading to increased installation and maintenance costs as well as additional measurement uncertainties. In response to this challenge, this paper presents two signal processing method that eliminate the need for an OPR sensor. The first method, referred to as "none OPR method 1," closely follows the measurement principles of the traditional method but employs a skewed dual light probe (SDLP) signal to extract rotational speed information, thus obviating the need for an OPR sensor. The second method, "none OPR method 2," introduces a novel data processing approach that enables BTC determination without any source of rotor speed information. Both methods utilize dynamic and static BTC matching techniques to identify blade serial numbers and achieve BTC measurement without an OPR sensor on a simulated rotor experimental bench. Comparative analysis with traditional method BTC measurements reveals that, under stable rotor speeds, all methods achieve similar levels of accuracy and repeatability errors within 0.025mm. However, when dealing with variable speed conditions, the traditional method's accuracy is significantly affected. None OPR method 1 mitigates the impact of rotor speed changes to some extent, while none OPR method 2 remains unaffected by such changes. Importantly, both none OPR methods demonstrate the capability to measure blade-by-blade tip clearances akin to the traditional method.

An approach based on data mining and genetic algorithm to optimizing time series clustering for efficient segmentation of customer behavior

In today's highly competitive market, organizations face significant challenges in accurately understanding and segmenting customer behavior due to the inherently dynamic and evolving nature of customer interactions over time. Traditional customer segmentation methods often neglect these temporal variations, leading to ineffective business strategies and missed opportunities. This research addresses this critical gap by introducing an innovative time series-based approach for customer behavior segmentation. By modeling each customer's behavior as a time series capturing key metrics such as purchase frequency, transaction amounts, and customer lifecycle costs the proposed method dynamically adapts to behavioral changes over time. To enhance segmentation precision, a genetic algorithm is employed to optimize feature weights, ensuring that the most relevant factors are emphasized. These optimized features are then clustered using spectral clustering to identify distinct and meaningful customer segments. The effectiveness of the proposed method is validated using 30 months of transactional data from a payment services company. The results demonstrate that the proposed approach, particularly when combined with spectral clustering and optimally weighted features, significantly surpassing the performance of traditional static segmentation techniques. This research not only provides a more accurate framework for uncovering hidden patterns in customer behavior but also delivers actionable insights for targeted marketing and personalized customer strategies.

The Additional Effect of Neurodynamic Slump and Suboccipital Muscle Inhibition to Passive Stretching of the Short Hamstring: A Single-Blind, Randomized Controlled Trial.

Hamstring shortening is a significant musculoskeletal condition affecting the posture and mobility of the spine and lower extremities. This study examined the impact of incorporating neurodynamic slump stretch and suboccipital muscle inhibition into passive static stretching on hamstring flexibility in individuals with short hamstrings. 117 female participants were classified into three groups: the control group, which received passive static stretch of the hamstring muscle; the neurodynamic slump group, which received neurodynamic slump stretch with passive static stretch; and the suboccipital muscle inhibition group, which received suboccipital muscle inhibition with passive static stretch, for three sessions a week, 10 min each, for four weeks. The outcome measures were the popliteal angle test (PAT), straight leg raising (SLR) test, and forward bending test (FBT) at baseline, immediately following the first session and after four weeks. Statistically significant differences were found within groups (p < 0.001) for all outcome measures. Between the groups, there was a more significant improvement in the PAT and the SLR tests, favoring the neurodynamic slump and suboccipital muscle inhibition groups in comparison with the passive static stretch group (p < 0.001) with no significant difference between the two groups after the first session and at four weeks of treatment. However, the FBT showed no significant differences immediately following the first session or at four weeks of treatment (p > 0.05). This study found that incorporating neurodynamic slump stretch and suboccipital muscle inhibition into passive static stretch techniques effectively treats short hamstrings in healthy individuals.

Treatment of inelastic material models within a dynamic ALE formulation for structures subjected to moving loads

AbstractThis article showcases the development of a dynamic Arbitrary Lagrangian Eulerian (ALE) formulation to account for inelastic material models within a finite element framework. Such a formulation is commonly utilized in research domains like fluid mechanics, fluid‐structure interaction, quasi static remeshing techniques, and quasi static load movement. The work at hand describes the application of the ALE formulation to efficiently analyse structures subjected to moving loads in the field of transient inelastic solid mechanics. In particular, structures such as pavements, gantry crane girders etc., which are subjected to moving loads, can be numerically simulated, and their transient response in the relevant region around the load can be obtained without relying on moving loads. The focus of this article is to facilitate the treatment of history variables stemming from inelastic material models. Of particular interest is the advection procedure required to transport the history variables through the mesh, as the material appears to flow through it. The mathematical framework necessary to treat this advection process is described in detail, considering a nonlinear viscoelastic material model on a neo‐Hookean base at finite deformations. Then, four methods for numerically achieving the advection are implemented within a transient finite element ALE formulation. These methods are compared against each other, and additionally with the conventional Lagrangian method for validation. The results demonstrate satisfactory agreement with conventional simulation methods, while offering a significant improvement in terms of computation speed. With the work at hand, the dynamic response of inelastic materials subjected to moving loads can be numerically simulated in a computationally efficient manner.

Reanimation Techniques of Peripheral Facial Paralysis: A Comprehensive Review Focusing on Surgical and Bioengineering Approaches.

Peripheral facial paralysis represents a disabling condition with serious psychological and social impact. Patients with peripheral facial paralysis have a disfigurement of the face with loss of harmony and symmetry and difficulties in everyday facial functions such as speaking, drinking, laughing, and closing their eyes, with impairment of their quality of life. This paralysis leads to impairment of facial expression, which represents one of the first means of communication, an important aspect of human interaction. This review aims to explore the reanimation techniques for managing peripheral facial paralysis. An analysis of static and dynamic techniques for facial reanimation is provided, including muscle flaps, nerve grafting techniques, and bioengineering solutions. Each technique showed its benefits and drawbacks; despite several options for facial reanimation, no technique has been detected as the gold standard. Therefore, each patient must be evaluated on an individual basis, considering their medical history, age, expectations, and treatment goals, to find the best and most fitting treatment.

Impact of Advanced High-Power Pain Threshold Static Ultrasound and Muscle Energy Technique on Pain Thresholds and Functional Improvement in Myofascial Trigger Points

bands and hypersensitive Trigger Points (TrPs), contributing to musculoskeletal pain. The objective of this study is to investigate and assess the effectiveness of Advanced High-Power Pain Threshold Static Ultrasound (AHPPTSU) and Muscle Energy Technique (MET) in altering pain thresholds and enhancing functional outcomes in individuals with myofascial trigger points. Methods: In this randomized clinical trial involving 86 individuals with TrPs in the upper trapezius muscle, the participants were divided into experimental and control groups. 33 males and 53 females, underwent six sessions of treatment over two weeks. A repeated measure Analysis of variance was used to compare baseline values and altered values at 1 and 2 weeks. Results: The study demonstrated that the Pressure Pain Threshold (PPT) and the Neck Pain Disability Index (NPDI) score, showed a significant improvements in participants receiving AHPPTUS in experimental group compared to the other group. Experimental group showed a significantly greater improvement in PPT (p=0.001) and both groups experienced a significant enhancement in function. However, when comparing the two groups, experimental group showed a significantly greater improvement (p=0.001). Importantly, no adverse effects were reported in either group. Conclusion: In the treatment of myofascial trigger point, AHPPTSU can be considered as an alternative therapy method, which is more effective than previously used High-Power Pain Threshold Static Ultrasound (HPPTSU) therapy and it also shortens the total treatment protocol to 2 weeks.

The effect of computer aided navigation techniques on the precision of endodontic access cavities: A systematic review and meta-analysis

AIM. To assess the impact of computer-assisted navigation techniques on the precision of endodontic access cavity preparation.MATERIALS AND METHODS. A systematic review was conducted following the PRISMA 2020 guidelines. Articles were searched for online using electronic databases, including Scopus, PubMed, Cochrane, and Web of Sciences. The success rate of root canal location using computer-aided navigation techniques in root canal access cavity preparation, along with the time required for cavity preparation and the extent of tooth substance removal were assessed in this review. After eliminating duplicate articles and applying inclusion criteria, 10 studies were chosen for analysis.RESULTS. Accuracy in location of root canal is significantly higher in the static and dynamic navigation group compared to the conventional group. Also, computer-aided static and dynamic navigation techniques removed significantly less tooth substance compared to conventional groups. Moreover, static navigation technique took significantly less time for access cavity preparation than conventional while there was no significant difference in the time taken for access cavity preparation between dynamic navigation technique and conventional technique.CONCLUSION. The root canal access cavities prepared using static and dynamic computer-aided navigation techniques are highly precise in detecting the root canal system, require less tooth substance removal, and take less time to complete.

Application of straw-derived biochar: a sustainable approach to improve soil quality and crop yield and reduce N2O emissions in paddy soil.

The burning of agricultural straw is a pressing environmental issue, and identifying effective strategies for the rational utilization of straw resources is decisive for achieving sustainable development. Owing to its high carbon content and exceptional stability, straw biochar produced via pyrolysis has emerged as a key focus in multidisciplinary research. However, the efficacy of biochar in mitigating nitrous oxide (N2O) emissions from paddy soils is not consistent. A 2-year field experiment was conducted and investigated the impact of biochar derived from two feedstocks (rice straw and wheat straw, pyrolyzed at 450°C) on N2O emissions, global warming potential (GWP), greenhouse gas intensity (GHGI), nitrogen use efficiency (NUE), crop yield, and soil quality. The static chamber technique was used for collecting N2O gas samples, and concentrations were analyzed through gas chromatography methods. The treatment combinations included BR0 (control), BR1 (NPK at the recommended dose, 120:60:40kgha-1), BR2 (wheat straw biochar, 5 t ha-1), and BR3 (rice straw biochar, 5 t ha-1). The results exhibited that cumulative N2O emissions from BR2 and BR3 treatments decreased by 10.55% and 13.75% respectively, compared to BR1. Lower GWP and GHGI were observed under both biochar treatments compared with BR1. The highest rice grain yield (3.48Mgha-1) and NUE (76.72%) were recorded from BR3, which also exhibitedthe lowest yield-scaled N2O emission. We observed positive correlations between soil nitrate, ammonia and water-filled pore spaces, while NUE showed negative correlations with N2O emissions. Significant (p < 0.05) improvements in soil quality were also detected in both the biochar treated plots, indicated by increased soil pH, water holding capacity, porosity, and nutrient contents. Overall, the results suggest that applying biochar at a rate of 5 t ha-1 in paddy soil is a viable nutrient management strategy with the potential to reduce reliance on inorganic fertilizers, mitigate N2O emissions, and contribute to sustainable food production.

Impact of a forage legume or nitrogen fertilizer application on ammonia volatilization and nitrous oxide emissions in Brachiaria pastures

ABSTRACT The largest proportion of greenhouse gas (GHG) emissions in the Agriculture sector of the Brazilian national GHG inventory is derived from the large (&gt;200 million head) herd of cattle. The greatest contribution to these emissions comes from the enteric methane from cattle, but the direct and indirect emissions of nitrous oxide (N 2 O) from cattle excreta and N fertilizer are responsible for approximately 9 % of all national anthropogenic GHG emissions. Ammonia (NH 3 ) can be volatilized from N fertilizer and cattle excreta and deposited in sites remote from the source, constituting an indirect source of N 2 O. This study aimed to determine whether direct N 2 O emissions and NH 3 volatilization from N-fertilized pastures were greater than those derived from a mixed grass-legume pasture without N fertilizer addition. Emissions of N 2 O and NH 3 from excreta and N fertilizer from a Palisade grass (Urochloa brizantha cv. Marandu) monoculture fertilized with 2 × 60 kg N ha -1 yr -1 urea were compared to those from a mixed Palisade grass-forage peanut (Arachis pintoi) pasture. Dung and urine were collected from these cattle, and NH 3 losses and N 2 O emissions from the excreta and from N fertilizer were monitored using static chamber techniques. Volatilization of NH 3 and N 2 O emissions were found to be greater from urine than from dung. Ammonia losses from excreta and urea fertilizer were low, not exceeding 6.8, 1.1, and 4.7 % of the N applied as urine, dung, and fertilizer, respectively. The N 2 O emissions showed a tendency to be greater for the urine from the N-fertilized compared to the mixed grass-legume pasture, and the N 2 O emissions from the urine of the N-fertilized pasture ranged from 0.08 to 0.94 % of applied urine N. The N 2 O emission from the N fertilizer was at maximum 0.46 % of the applied N. The direct N 2 O emissions and the loss of NH 3 by volatilization (indirect N 2 O emission) from the excreta of cattle grazing the mixed grass-legume pasture were similar to, or lower than, the grazed grass monoculture fertilized with 120 kg N ha -1 yr -1 . As the mixed pasture received no N fertilizer and hence no GHG emission from its manufacture or application, introducing forage peanut to the Urochloa brizantha pastures shows potential to be responsible for lower GHG emissions than the N fertilized grass pasture.

Automated Verification of Parametric Channel-Based Process Communication

A challenge of writing concurrent message passing programs is ensuring the absence of partial deadlocks, which can cause severe memory leaks in long running systems. Several static analysis techniques have been proposed for automatically detecting partial deadlocks in Go programs. For a large enterprise code base, we found these tools too imprecise to reason about process communication that is parametric, i.e., where the number of channel communication operations or the channel capacities are determined at runtime. We present a novel approach to automatically verify the absence of partial deadlocks in Go program fragments with such parametric process communication. The key idea is to translate Go fragments to a core language that is sufficiently expressive to represent real-world parametric communication patterns and can be encoded into Dafny programs annotated with postconditions enforcing partial deadlock freedom. In situations where a fragment is partial deadlock free only when the concurrency parameters satisfy certain conditions, a suitable precondition can often be inferred. Experimental results on a real-world code base containing 583 program fragments that are beyond the reach of existing techniques have shown that the approach can verify the absence of partial deadlocks in 145 cases. For an additional 228 cases, a nontrivial precondition is inferred that the surrounding code must satisfy to ensure partial deadlock freedom.

Symbolic testing of floating-point bugs and exceptions

Numerical software are susceptible to floating-point bugs and exceptions, which may lead to severe threats like denial of service attacks. Static analysis techniques such as symbolic execution are effective in detecting general bugs which often cause memory error or program crash. Unfortunately, these methods do not deal well with numerical code as they do not support floating-point constraints and math functions symbolically. In this paper, we propose a new analysis framework YUSE, which can detect floating-point bugs by constructing constraints and exploring paths which contain floating-point expressions. Specifically, we introduce interval computation and interval constraint propagation in non-relational numerical abstract domains, and symbolically model math functions, to accurately detect floating-point bugs and exceptions. Moreover, we leverage two-phase constraint solving to enhance YUSE’s performance. Experimental results show that YUSE outperforms two state-of-the-art tools, Frama-c and Fpse-study, in terms of effectiveness and efficiency, with 1.4× and 7.1× faster than Frama-c and Fpse-study, respectively. Moreover, YUSE found 20 new bugs in real-world software, 12 of which were assigned CVE IDs and 8 of which were confirmed by developers.

Automatic Refactoring Approach for Asynchronous Mechanisms with CompletableFuture

To address the inherent limitations of Future in asynchronous programming frameworks, JDK 1.8 introduced the CompletableFuture class, which features approximately 50 different methods for composing and executing asynchronous computations and handling exceptions. This paper proposes an automatic refactoring method that integrates multiple static analysis techniques, including visitor pattern analysis, alias analysis, and executor inheritance structure analysis, to conduct precondition checks. Distinct from existing Future refactoring methods, this approach considers custom executor types, thereby extending its applicability. Using this method, the ReFuture automatic refactoring plugin was implemented within the Eclipse JDT framework. The method was evaluated in terms of the number of refactorings, refactoring time, and error introduction, alongside a side-by-side comparison with the existing method. The refactoring outcomes for nine large applications, including ActiveMQ, Hadoop, and Elasticsearch, show that ReFuture successfully refactored 639 out of 813 potential code structures, achieving a refactoring success rate of 64.70% without introducing errors. This tool effectively facilitates the refactoring to CompletableFuture and enhances refactoring efficiency compared to manual methods.

Static reconfiguration method of photovoltaic array based on improved competence square

Partial shading can reduce the power output of a photovoltaic (PV) array due to mismatch losses. Therefore, various static and dynamic reconfiguration techniques have been proposed to address this problem. Although dynamic reconfiguration methods are fast and flexible, they face challenges such as complex hardware circuits and high costs. In contrast, static reconfiguration methods simplify control complexity, improve system stability, and significantly reduce costs. Among the existing static reconfiguration techniques, the competence square (CS) method, which changes the physical positions of PV panels without modifying the total cross tied (TCT) based electrical connections, has been introduced to enhance power generation. However, this arrangement faces drawbacks due to the lack of effective chromatic dispersion and insufficient power enhancement under shading conditions. This paper proposes an improved competence square (ICS) reconfiguration method to further improve the power output. The ICS method first reconfigures the PV array using the CS method, then applies the lo shu (LS) method for secondary reconfiguration to determine the optimal connections. This method is compared with TCT, CS and improved northern goshawk optimization (INGO) methods. Additionally, the performance of the proposed method is evaluated against various existing photovoltaic array configurations by comparing the global maximum power point (GMPP), fill factor (FF), mismatch loss (ML), and power enhancement (PE). The experiment shows that under shading conditions of square shading, rectangle shading, trapezoid shading, triangle shading, L-shaped shading, cross shading, discontinuous shading, and irregular shading, reconfiguring PV arrays using ICS consistently achieves the highest power improvement. Compared to TCT, the power output increases significantly by 16.6%, 2.1%, 18.0%, 16.0%, 19.1%, 5.0%, 4.0%, and 3.0%, respectively. Comparison results validate the proposed ICS method in enhancing the global maximum power under shaded conditions.

Study on the effect of particles in oilfield produced water on the deposition process of CaCO3

In crude oil production, scale deposition significantly reduces production output and elevates operational costs, posing a severe threat to production safety. While chemical methods have been extensively explored for the scaling and inhibition of inorganic salts, the inorganic scaling triggered by solid particle scaling in complex oilfield water has largely been overlooked. This study involves the introduction of particles into a supersaturated CaCO3 solution, utilizing static scale inhibition and conductivity techniques to examine their influence on the scaling process and crystallization rate. It is evident that solid particles expedite the deposition process of CaCO3. Moreover, the deposition rate of CaCO3 is influenced by factors such as the solid particle content, particle size, and stirring speed. It is noteworthy that the presence of solid particles solely impacts the formation rate of CaCO3 crystals, without altering the total deposition. Specifically, under conditions of 70°C, 250/min stirring speed, and 0.08% SiO2 addition, the deposition rate of CaCO3 is enhanced by 13.5%. The nucleus growth rate constant increases from 11.10 × 10-3min-1 to 14.52 × 10-3min-1 and the crystal growth rate constant increases from 3.02 × 10-3min-1 to 3.36 × 10-3min-1 at most. Observations made through scanning electron microscopy (SEM) and polarized light microscopy reveal that scaling occurs predominantly on the added solid particles in later stages, indicating that solid particles in supersaturated solutions serve as crystal nuclei, inducing the growth of CaCO3 crystals and thus accelerating scaling. This research provides valuable insights for the study of scaling in complex water environments.

Preserving Tradition, Embracing Innovation Mohsen Foroughi's Maison de'lIran

Iranian architecture has left its mark on world history, with its influence reaching the farthest corners of Europe through the creation of Byzantine architecture. The traditional architecture of Iran, as described by Professor Pirnia, is built upon five principles. These principles highlight the evolution of Iranian civilization over time. Mohsen Foroughi, an exemplary Iranian architect, has skillfully merged the essence of Iranian architecture with contemporary ideals, exemplified by his masterpiece, the "Maison de l’Iran" in Paris, designed in a modern style. In this study, we aimed to explore how Foroughi incorporated these five principles of Iranian architecture into his project in France. Employing a descriptive and analytical method, we assessed the physical and structural components of Iranian architecture, examining how Foroughi's work aligns with the principles and values of Iranian architecture. Our findings demonstrate that Foroughi is in line with traditional Iranian architectural values, contextual materials, and climate-friendly design in his works. Furthermore, Foroughi's expertise in Statics, Material Studies, and Structural techniques sciences enabled him to successfully execute large-scale projects. The Maison de l’Iran exemplifies his understanding of modern styles while honoring the principles of Iranian architecture. His work has been instrumental in shaping modern Iranian architecture, reflecting his artistic creativity and inspiration from Iran's architectural heritage.

Motion Planning for a Legged Robot with Dynamic Characteristics.

Legged soccer robots present a significant challenge in robotics owing to the need for seamless integration of perception, manipulation, and dynamic movement. While existing models often depend on external perception or static techniques, our study aims to develop a robot with dynamic and untethered capabilities. We have introduced a motion planner that allows the robot to excel in dynamic shooting and dribbling. Initially, it identifies and predicts the position of the ball using a rolling model. The robot then pursues the ball, using a novel optimization-based cycle planner, continuously adjusting its gait cycle. This enables the robot to kick without stopping its forward motion near the ball. Each leg is assigned a specific role (stance, swing, pre-kick, or kick), as determined by a gait scheduler. Different leg controllers were used for tailored tiptoe trajectory planning and control. We validated our approach using real-world penalty shot experiments (5 out of 12 successful), cycle adjustment tests (11 out of 12 successful), and dynamic dribbling assessments. The results demonstrate that legged robots can overcome onboard capability limitations and achieve dynamic mobility and manipulation.

Seismic Performance of Reinforced Concrete Frames on Sloped Ground Using Non-Linear Static Pushover Analysis

Nepal, renowned for its majestic Himalayan Ranges, is also highly vulnerable to seismic activity. Buildings on hill slopes often endure more significant damage during earthquakes than those on flat terrain. Traditional seismic analyses of buildings typically employ linear-static and dynamic methods, which might not fully represent the building's behavior under actual seismic conditions. This research addresses this gap by assessing the seismic performance of buildings on hill slopes using non-linear static analysis techniques. Specifically, the study evaluates the seismic response of 5-story buildings with stepback and stepback-setback configurations on slopes of 15°, 30°, and 45°. This evaluation is conducted through non-linear static analysis, also known as Pushover Analysis, using ETABSv20 software. Key performance metrics analyzed include the building's period, topstorey displacement, and base shear. The findings reveal that buildings with stepbacksetback configurations demonstrate superior seismic performance on the sloping ground compared to those with stepback configurations. This study underscores the importance of employing non-linear analysis methods to better understand and improve seismic resilience in hilly terrains.

Assessment of Ground Control Points Positional Shift and Management Practices: Evidences from Assosa Town, Western Ethiopia

This study assesses the positional shift of existing control points and management practices found in and around Assosa town. The static GPS measurement technique was used as an independent source and a point wise method were used to assess the positional shift and accuracy level evaluation. Due to unavailability of local CORS station, two first order GCPs were used as a reference during static GPS measurement. After measurement was conducted depending on the baseline length between control point marks, the STC desktop software and online CSRS-PPP post processing technique was used. Thus, the positional accuracy of selected GCPs of STC Post processing technique has a mean error of 0.324 m and whereas the GCPs of CSRS-PPP has a mean error of 0.571 m. Horizontal distance error obtained with the STC differential technique is ranging from 0 to 0.83 m which is inconsistent relative to the range 0.437 m to 0.815 m obtained from online CSRS-PPP solution. The positional accuracy of GCPs was also assessed using horizontal distance error of both processed techniques. The positional accuracy of GCPs at 95% confidence level is between -0.117 m and 0.765 m with STC and between 0.395 m and 0.747 m in online CSRS-PPP solution. Based on the result, the accuracy level of existing GCPs found in Assosa town, does not meet the FGDC accuracy. This was mainly associated with perception of communities on ground control point management activities. The study revealed almost low communities practice and control point management responsiveness. Finally, study suggested that there should be participatory guidance to establish and manage the ground control points.