A New Analysis Approach Incorporated with Analytic Hierarchy Process for The Software Application in A Multiple Tiers Environment

Despite the Information Technology (IT) era keeps evolving rapidly, many business operations are heavily relying on software application service to process the daily business transactions today. Therefore, software application service is unacceptable if it is unavailable during business hours. However, there are many possibilities can cause the software application service irresponsive. This is because the root cause can be possible to arise mostly in either within the software application layer, or other factors which are falling outside the software application layer. Under such complex situation, it is time consuming to identify the root cause and it is always unavoidable. The objective of Prescriptive Analytical Logic Model (PAL) is not focusing on only solving such problem. Indeed, it aims to minimize the duration spent on root cause analysis activities, and to decide the preferred resolution for the identified root cause. Hence, the algorithm inside the PAL has incorporated with Supervised Learning approach to identify the possible errors of the root cause, and adopted Analytic Hierarchy Process (AHP) to decide the preferred resolution based on the given priority to the errors.

The paper reports the investigation on the root cause of source-drain leakage in bulk FinFET devices. While the failing device was readily isolated by nanoprobing technique and the electrical analysis pinpointed the potential defect location inside the Fin channel, the identification of physical root cause went through extreme challenges imposed by the tiny-sized device and the unique FinFET 3D architecture. The initial TEM analysis was misled by the projection of a species in the lamella surface and thus could not explain the electrical data. Careful analysis on the device structure was able to identify the origin of the species and led to the discovery of the actual root cause. This paper will provide the analysis details leading to the findings, and highlight the role of electrical understanding in not only providing guidance for physical analysis but also revealing the true root cause of failure in FinFET devices.

Cloud-based services are surging into popularity in recent years. However, outages, i.e., severe incidents that always impact multiple services, can dramatically affect user experience and incur severe economic losses. Locating the root-cause service, i.e., the service that contains the root cause of the outage, is a crucial step to mitigate the impact of the outage. In current industrial practice, this is generally performed in a bootstrap manner and largely depends on human efforts: the service that directly causes the outage is identified first, and the suspected root cause is traced back manually from service to service during diagnosis until the actual root cause is found. Unfortunately, production cloud systems typically contain a large number of interdependent services. Such a manual root cause analysis is often time-consuming and labor-intensive. In this work, we propose COT, the first outage triage approach that considers the global view of service correlations. COT mines the correlations among services from outage diagnosis data. After learning from historical outages, COT can infer the root cause of emerging ones accurately. We implement COT and evaluate it on a real-world dataset containing one year of data collected from Microsoft Azure, one of the representative cloud computing platforms in the world. Our experimental results show that COT can reach a triage accuracy of 82.1%-83.5%, which outperforms the state-of-the-art triage approach by 28.0%-29.7%.

The Theory of Constraints was used as a method in a root cause analysis (RCA) to identify system performance bottlenecks, wherein the constraint with the strongest correlation with system performance is identified as the bottleneck. In the present study, this method was applied in a large district cooling plant to diagnose steam absorption chillers’ performance anomalies including performance deterioration, spikes, large variation, etc. Many root causes were identified through a ten months’ continuous diagnosis, such as drastic reduction in chilled water flow rate, faulty steam control valve, cooling demand reduction, etc. More than 30 anomalies were diagnosed and more than 80% diagnosis accuracy was achieved. The diagnosis results were verified by the plant operator, which proved the effectiveness of the Theory of Constraints as a method for root cause analysis in diagnosing anomalies in district cooling plant operations. It was however discovered that even though the operational component identification accuracy was high, the determination of the actual root cause still presents lots of challenges, due to the large set of domain knowledge and operation conditions required. A knowledge-based supporting tool may be needed as part of the RCA to facilitate a speedy and complete analysis to enable these anomalies to be resolved.

Background:Military hospitals are responsible for preserving, restoring and improving the health of not only armed forces, but also other people. According to the military organizations strategy, which is being a leader and pioneer in all areas, providing quality health services is one of the main goals of the military health care organizations. This study was aimed to evaluate the service quality of selected military hospitals in Iran based on the Joint Commission International (JCI) standards and comparing these hospitals with each other and ranking them using the analytic hierarchy process (AHP) technique in 2013.Materials and Methods:This was a cross-sectional and descriptive study conducted on five military hospitals, selected using the purposive sampling method, in 2013. Required data collected using checklists of accreditation standards and nominal group technique. AHP technique was used for prioritizing. Furthermore, Expert Choice 11.0 was used to analyze the collected data.Results:Among JCI standards, the standards of access to care and continuity of care (weight = 0.122), quality improvement and patient safety (weight = 0.121) and leadership and management (weight = 0.117) had the greatest importance, respectively. Furthermore, in the overall ranking, BGT (weight = 0.369), IHM (0.238), SAU (0.202), IHK (weight = 0.125) and SAB (weight = 0.066) ranked first to fifth, respectively.Conclusion:AHP is an appropriate technique for measuring the overall performance of hospitals and their quality of services. It is a holistic approach that takes all hospital processes into consideration. The results of the present study can be used to improve hospitals performance through identifying areas, which are in need of focus for quality improvement and selecting strategies to improve service quality.

Development of a novel methodology for root cause analysis and selection of maintenance strategy for a thermal power plant: A data exploration approach

After three decades of false hopes and failures, a pipeline of therapeutic drugs that target the actual root cause of Alzheimer's disease (AD) is now available. Challenging the old paradigm that focused on β-amyloid peptide (Aβ) aggregation in amyloid plaques, these compounds are designed to prevent the neurotoxicity of Aβ oligomers that form Ca2+ permeable pores in the membranes of brain cells. By triggering an intracellular Ca2+ overdose, Aβ oligomers induce a cascade of neurotoxic events including oxidative stress, tau hyperphosphorylation, and neuronal loss. Targeting any post-Ca2+ entry steps (e.g., tau) will not address the root cause of the disease. Thus, preventing Aβ oligomers formation and/or blocking their toxicity is by essence the best approach to stop any progression of AD. Three categories of anti-oligomer compounds are already available: antibodies, synthetic peptides, and small drugs. Independent in silico-based designs of a peptide (AmyP53) and a monoclonal antibody (PMN310) converged to identify a histidine motif (H13/H14) that is critical for oligomer neutralization. This "histidine trick" can be viewed as the Achilles' heel of Aβ in the fight against AD. Moreover, lipid rafts and especially gangliosides play a critical role in the formation and toxicity of Aβ oligomers. Recognizing AD as a membrane disorder and gangliosides as the key anti-oligomer targets will provide innovative opportunities to find an efficient cure. A "full efficient" solution would also need to be affordable to anyone, as the number of patients has been following an exponential increase, affecting every part of the globe.

This paper places a strong emphasis on the importance of applying Systematic Problem Solving approach and use of appropriate FA methods and tools to understand the “real” failure root cause. A case of wafer center cluster RAM fail due to systematic missing Cu was studied. It was through a strong “inquisitive” mindset coupled with deep dive problem solving that lead to uncover the actual root cause of large Cu voids. The missing Cu was due to large Cu void induced by galvanic effects from the faster removal rate during Cu CMP and subsequently resulted in missing Cu. This highlights that the FA analyst’s mission is not simply to find defects but also play a catalyst role in root cause/failure mechanism understanding by providing supporting FA evidence (electrically/ physically) to Fab.

In order to make sure that structures adhere to the necessary norms and laws, it is essential to evaluate the quality of building construction. According to several frameworks, the quality of a building’s construction can be assessed in a number of different circumstances. In order to provide building projects with excellent quality and competitive pricing, hard work is required. To raise the standard of building construction, a model was created. The goal of this project is to provide a model for raising building construction quality. This study used the analytical hierarchy process (AHP) technique, which includes the determination of consistency ratios, pairwise comparisons, normalization, and a comparison matrix. The difficulty of implementing quality was determined for each task using the AHP technique. This was multiplied by the quality factor to obtain the final quality level. The model was tested in three different situations, and it was discovered that quality application is challenging across all building operations. Using a quality evaluation technique, this study assessed the building construction quality in Saudi Arabia. Additionally, a pairwise comparison, normalization, and a comparison matrix were used to calculate the consistency ratio. The ultimate quality level was determined by multiplying the difficulty level for each activity, as determined using the AHP approach, by the quality factor. This study will therefore be helpful to those involved in Saudi Arabian building, including architects, engineers, quality experts, and others. Additionally, the tool aids in the decision making process for enhancing construction quality.

Forest fires are among the most major causes of global ecosystem degradation. The integration of spatial information from various sources using statistical analyses in the GIS environment is an original tool in managing the spread of forest fires, which is one of the most significant natural hazards in the western region of Syria. Moreover, the western region of Syria is characterized by a significant lack of data to assess forest fire susceptibility as one of the most significant consequences of the current war. This study aimed to conduct a performance comparison of frequency ratio (FR) and analytic hierarchy process (AHP) techniques in delineating the spatial distribution of forest fire susceptibility in the Al-Draikich region, located in the western region of Syria. An inventory map of historical forest fire events was produced by spatially digitizing 32 fire incidents during the summers of 2019, 2020, and 2021. The forest fire events were divided into a training dataset with 70% (22 events) and a test dataset with 30% (10 events). Subsequently, FR and AHP techniques were used to associate the training data set with the 13 driving factors: slope, aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Topographic Wetness Index (TWI), rainfall, temperature, wind speed, TWI, and distance to settlements, rivers and roads. The accuracy of the maps resulting from the modeling process was checked using the validation dataset and receiver operating characteristics (ROC) curves with the area under the curve (AUC). The FR method with AUC = 0.864 achieved the highest value compared to the AHP method with AUC = 0.838. The outcomes of this assessment provide constructive spatial insights for adopting forest management strategies in the study area, especially in light of the consequences of the current war.

System development outsourcing has become the important practices in many organizations which involve third parties contribution on IT implementation as well as software development. The reasons of the demanding in outsourcing implementation are because it reduces operation and development budget for Information Technology Department and improves service quality and operational efficiency. Although it comes with benefits to the organization, but there are risks that associated with it. The objectives of this study are: 1) to identify main risks in outsource software development, 2) to assess the outsourcing risks and 3) to test the risks related to supplier using AHP technique. A survey was conducted in Malaysia to identify main risks in software outsourcing and to access the risk’s level and severity. Then, the risks were analysed using Analytic Hierarchy Process (AHP) technique to evaluate the performance of the suppliers in outsourcing data collected in the organisation. In this study, the testing and evaluating method were carried out with the officers in The Rubber Industry Smallholders Development Authority or RISDA in Malaysia because this organization has experience in software developemt outsource for more than 15 years. They are considered as well experience and good knowledge in this area. Findings from this study suggest to the related organization the main risks identified during software development and risk analysis is used to manage risk effectively according to its severity and priority. One way to manage and control risk is by identifying risks associated with suppliers using multi criteria selection method.

Implementing Fuzzy Logic and AHP into the EFQM model for performance improvement: A case study

Trace visualization within the Software City metaphor: Controlled experiments on program comprehension

The Analytical Hierarchy Process (AHP) approach and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are two methods that are commonly used to handle multicriteria problems. The AHP technique uses a matrix of pairwise comparisons and a hierarchical approach to criteria in order to obtain the final criteria weights. In contrast, the TOPSIS approach incorporates the concepts of proximity to the ideal solution and preference. Next, TOPSIS uses the previously established criterion weights to compute each option's relative closeness score to the ideal answer. In order to determine how effectively the AHP and TOPSIS methodologies complement one another, this study aims to assess the protocols and underlying assumptions of the two approaches. When decision makers are aware of the benefits and drawbacks of each approach, they may choose the best course of action from a mix of the two. The results of the study indicate that the process may be streamlined, subjectivity can be reduced, and criterion weights can be stabilized by combining the AHP and TOPSIS approaches.The Analytical Hierarchy Process (AHP) approach and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are two methods that are commonly used to handle multicriteria problems. The AHP technique uses a matrix of pairwise comparisons and a hierarchical approach to criteria in order to obtain the final criteria weights. In contrast, the TOPSIS approach incorporates the concepts of proximity to the ideal solution and preference. Next, TOPSIS uses the previously established criterion weights to compute each option's relative closeness score to the ideal answer. In order to determine how effectively the AHP and TOPSIS methodologies complement one another, this study aims to assess the protocols and underlying assumptions of the two approaches. When decision makers are aware of the benefits and drawbacks of each approach, they may choose the best course of action from a mix of the two. The results of the study indicate that the process may be streamlined, subjectivity can be reduced, and criterion weights can be stabilized by combining the AHP and TOPSIS approaches.

This paper aims to identify the groundwater-potential zones in coastal zones of the Cuddalore district by integrating remote sensing, Geographic Information System (GIS), and Analytical Hierarchy Process (AHP) techniques. The thematic layers such as geomorphology, landuse/land cover, lineament density, geology, soil, drainage density, rainfall, and slope are considered for the identification of groundwater-potential zones. The groundwater-potential zones are categorized into five zones as ‘very good’, ‘good’, ‘moderate’, ‘poor’, and ‘very poor’. From the study, it is observed that the rainwater/surface water infiltration to the aquifer is high in the eastern region due to flat topography, and thus, these zones possess ‘very good’ and ‘good’ groundwater-potential zones. The groundwater potential in the central region of the study area possesses moderate infiltration capacity, which is suitable for agricultural practices. Moreover, it is also observed that the groundwater potential is ‘poor’ and ‘very poor’ in the northwest region due to steep slopes in which suitable recharge structures should be constructed in these zones to harvest the rainwater. Eventually, the obtained results are validated with existing bore wells in the study area, and it reveals that a GIS-based integrated method is an effective tool for the exploration of groundwater resources with high accuracy.