Search results for: appliance prioritization

Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

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Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: cloud computing, marketplace, virtualization, virtual appliance

Procedia PDF Downloads 293

Authors: Jan-Philipp Schiele, Karsten Schlinkmeier

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Allocation of scarce resources is a core process of traditional project portfolio management. However, with the popularity of agile methodology, established concepts and methods of portfolio management are reaching their limits and need to be adapted. Consequently, the question arises of how the process of resource allocation can be managed appropriately in scaled agile environments. The prevailing framework SAFe offers Weightest Shortest Job First (WSJF) as a prioritization technique, butestablished companies are still looking for methodical adaptions to apply WSJF for prioritization in portfolios in a more goal-oriented way and aligned for their needs in practice. In this paper, the relevant problem of prioritization in portfolios is conceptualized from the perspective of coordination and related mechanisms to support resource allocation. Further, an Action Design Research (ADR) project with case studies in a finance company is outlined to develop a practically applicable yet scientifically sound prioritization method based on coordination theory. The ADR project will be flanked by consortium research with various practitioners from the financial and insurance industry. Preliminary design requirements indicate that the use of a feedback loop leads to better team and executive level coordination in the prioritization process.

Keywords: scaled agility, portfolio management, prioritization, business-IT alignment

Procedia PDF Downloads 195

Authors: Belly Yordan

Abstract:

Orthodontic treatment can be done by using the fix and removable orthodontic appliance. The success of treatment depends on the patient’s age, the type of malocclusion, treatment of space discrepancy, patient’s oral hygiene, operator skills, and patient cooperation. This case report was aimed to show the success of orthodontic treatment in patients with skeletal class I relationship, class I angle dental malocclusion with anterior crowding and rotation by using a removable appliance with modification. The removable appliance used is standard with removable plate components such as passive clasp (Adam’s hook clasp) accompanied with some active clasps (labial bow, some springs, etc.). A button is used as an additional tool or combined with other tools to correct tooth in rotated position. The results obtained by the success of treatments which is shown in pre and post-treatment photos, the overjet was reduced, the arch form became normal, the tooth malposition became normal, and rotation was corrected. Facial profile appearance of the patient is getting better, and the dental coordination also became better. This case report is to prove that treatment with the removable appliance is quite successful with the robust wearing of appropriate retainers.

Keywords: success rate, anterior crowding, orthodontic treatment, removable appliances

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

Procedia PDF Downloads 296

Authors: Sara Mostowfi, Hassan Sadeghinaeini, Sana Behnamasl, Leila Ensaniat, Maryam Mostafaee

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Nowadays, most of product producers, e.g. home appliance, electronic machines and vehicles focus on quality and comfort, and promise consumers ease of use and pleasurable experiences during product using. Consumers make their purchase decisions according to two needs: functional and emotional needs. Functional needs are fulfilled by product functionality, besides emotional needs are related to psychologists’ aspects of production. Emotions are distinctive elements which should be added to products and services to lead them up. In this case, the authors’ survey conducted pleasurable and hedonomic aspects in products of a home appliance company in Iran. In this regard, three samples of home appliance were selected: mixer, rice cooker, iron. Fifteen women (20-60) participated in this study. Every user evaluated each product by questionnaire based on 7 point semantic differential scale. After analyzing the results with statistical methods, results showed that 90% of users aren’t satisfied with hedonic and pleasurable criteria in interaction with these products. They notified that regarding hedonomics and pleasurable criteria’s they will have better ease of use and functionality. Our findings show a significant association between products’ features and user satisfaction. It seems that industrial design has a significant impression on the company’s products and with regard the pleasurable criteria the company sales will be more successful.

Keywords: home appliance, interaction, pleasure, hedonomy, ergonomy

Procedia PDF Downloads 382

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: David Parmenter, Brian Millar

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Obstructive sleep apnoea is a common condition which is generally under-diagnosed. Poorly managed obstructive sleep apnoea carries serious health risks and can greatly impact on the sufferer's quality of life. This publication covers the aetiology, symptoms, and treatment of sleep apnoea. The treatment of Obstructive Sleep Apnoea is an emerging field, and the useful role of the Dental Team is relatively unknown, therefor this paper will highlight the role of the dental team in its treatment. The concept of mandibular advancement appliances, along with the clinical and laboratory stages for constructing them, are documented. It is the hope of the author that this publication will educate healthcare professionals on the role of dental practitioners in the multidisciplinary team for treating sleep apnoea. Objective: Individuals should be more aware of the demographic of patients at risk of sleep apnoea, how it is diagnosed and which group of sleep apnoea patients are suitable to refer for mandibular appliance therapy. Individuals should also be aware of what a mandibular advancement appliance is and how it helps treat obstructive sleep apnoea.

Keywords: sleep apnoea, snoring, sleep appliances, mandibular advancement appliance

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Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal

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Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.

Keywords: regression testing, software testing, test case prioritization, test suite optimization

Procedia PDF Downloads 337

Authors: Elbert S. Moyon, Edsel Matt O. Morales, Jaymer M. Jayoma, Kent C. Espejon, Jayson C. Dollete, Mark Phil B. Pacot

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This research paper focuses on the potential of using Web-GIS technology in prioritizing farm-to-market road projects by the Philippines’ Department of Agriculture (DA). The study aimed to explore the benefits of Web-GIS in addressing the limitations faced by the DA in terms of Farm to Market Road profiling and project prioritization, which include a lack of access to updated data, limited spatial analysis capabilities, and difficulties in sharing information between stakeholders. The research methodology involves a comprehensive literature review and a case study of a Web-GIS application developed for the DA, which was used to profile and prioritize farm-to-market road projects in the Philippines. The results showed that the Web-GIS technology provides the DA with an effective tool for analyzing and visualizing data, which can help in profiling and prioritizing road projects based on various criteria such as economic, social, and environmental impacts. The study also showed that Web-GIS technology could help in reducing the time and effort required for road project prioritization and improve communication between stakeholders.

Keywords: GIS, web application, farm-to-market road, FMR prioritization, Django, GeoServer

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Authors: Supachai Supmak, Yachai Limpiyakorn

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Mutation testing can be applied for the quality assessment of test cases. Prioritization of mutation test generation has been a critical element of the industry practice that would contribute to the evaluation of test cases. The industry generally delivers the product under the condition of time to the market and thus, inevitably sacrifices software testing tasks, even though many test cases are required for software verification. This paper presents an approach of applying a social network centrality measure, PageRank, to prioritize mutation test generation. The source code with the highest values of PageRank will be focused first when developing their test cases as these modules are vulnerable to defects or anomalies which may cause the consequent defects in many other associated modules. Moreover, the approach would help identify the reducible test cases in the test suite, still maintaining the same criteria as the original number of test cases.

Keywords: software testing, mutation test, network centrality measure, test case prioritization

Procedia PDF Downloads 111

Authors: Zeynep Karakoc, Hasan Ilhan Mutaf

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Plaque removal efficacy of different dental brushes and mouth wash during fixed orthodontic appliance therapy was evaluated in this single-blind, crossover and prospective study. Thirty orthodontic patients aged 18 and over undergoing fixed appliance therapy at the end of leveling stage were divided into three groups. Subjects brushed their teeth with a toothbrush under standardized conditions for a period of 30 days prior to inter-dental care products. The same procedure was repeated each time with a different, randomly assigned inter-dental care products in a crossover design. (Inter-dental brush, powered inter-dental brush and mouth wash). At start and end of each removal period, plaque indexes of participants were scored. Each brush achieved statistically significant plaque removal; however, there were no statistical differences among groups for all surfaces of teeth when the plaque score was evaluated. The mouth wash group presented significant improvement in reduction of visible plaque on mesial and distal surfaces of posterior teeth. (-60.9 %, P< .001) Plaque removal for right and left side of mouth showed no significant differences within groups, only mouth wash was more efficient in right side than left side. It is concluded that effectiveness of plaque removal may not be related to the kind of inter-dental products directly. However, toothbrush when used with inter-dental care products is significantly better at removing plaque deposits from fixed appliance patients.

Keywords: orthodontics, dental care, brush, plaque

Procedia PDF Downloads 242

Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Sat Sharma, Antonella Conflitti, Hilary Reiter

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Introduction: The study's purpose was to assess the efficacy of the oral appliance device O2Vent Optima + ExVent as compared to Optima in the treatment of OSA. Methods: A prospective, open-label study conducted at 3 sites included subjects with mild to moderate OSA (AHI ≥ 5 and ≤ 30). Screening Phase: A diagnostic in-lab PSG study was performed to confirm a diagnosis of mild to moderate OSA. Treatment I: Subjects used O2Vent Optima for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima. Treatment II: Subjects used O2Vent Optima + ExVent for 6 weeks and underwent an in-lab PSG sleep night while using the O2Vent Optima + ExVent Primary Effectiveness Measure: Change in AHI between baseline vs. O2Vent Optima MAD vs. O2Vent Optima + ExVent. Results: Treatment with Optima, Optima + ExVent reduced AHI from 22.5±6.4/hr to 12.6±4.5/hr to 5.9±2.7 (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima MAD vs. Optima + ExVent). The average reduction in AHI with Optima was 43%, and with Optima + ExVent was 72%. The lowest oxygen during sleep increased from 84.6±2.7% to 88.6±2.9% to 91.6±3.2% (p< 0.005 baseline vs. Optima and Optima + ExVent; p<0.05 Optima vs. Optima + ExVent). During the trial, patients on treatment with Optima and Optima + ExVent demonstrated no excessive adverse events or device malfunction. Conclusion: Treatment with O2Vent Optima and O2Vent Optima + ExVent significantly improved OSA compared to the baseline. An even greater benefit was observed with the addition of ExVent to the Optima in mild to moderate OSA.

Keywords: oral appliance, O2Vent, sleep dentistry, sleep apnea

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Authors: Musa Sekamatte

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Background: Zoonotic diseases continue to be a public health burden in countries around the world. Uganda is especially vulnerable due to its location, biodiversity, and population. Given these concerns, the Ugandan government in collaboration with the Global Health Security Agenda conducted a zoonotic disease prioritization workshop to identify zoonotic diseases of concern to multiple Ugandan ministries. Materials and Methods: The One Health Zoonotic Disease Prioritization tool, developed by the U.S. Centers for Disease Control and Prevention (CDC), was used for prioritization of zoonotic diseases in Uganda. Workshop participants included voting members representing human, animal, and environmental health ministries as well as key partners who observed the workshop. Over 100 articles describing characteristics of these zoonotic diseases were reviewed for the workshop. During the workshop, criteria for prioritization were selected, and questions and weights relevant to each criterion were determined. Next steps for multi-sectoral engagement for the prioritized zoonoses were then discussed. Results: 48 zoonotic diseases were considered during the workshop. Criteria selected to prioritize zoonotic diseases in order of importance were (1) severity of disease in humans in Uganda, (2) availability of effective control strategies, (3) potential to cause an epidemic or pandemic in humans or animals, (4) social and economic impacts, and (5) bioterrorism potential. Seven zoonotic diseases were identified as priorities for Uganda: anthrax, zoonotic influenza viruses, viral hemorrhagic fevers, brucellosis, African trypanosomiasis, plague, and rabies. Discussion: One Health approaches and multi-sectoral collaborations are crucial in the surveillance, prevention, and control strategies for zoonotic diseases. Uganda used such an approach to identify zoonotic diseases of national concern. Identifying these priority diseases enables the National One Health Platform and the Zoonotic Disease Coordinating Office to address the diseases in the future.

Keywords: national one health platform, zoonotic diseases, multi-sectoral, severity

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Authors: Dadasaheb R. Jawre, Maya G. Unde

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Prioritization of sub-watershed plays important role in watershed management. It shows the requirement of watershed to give a treatment for the green growth of the region and conservation of the sub-watersheds. There is a number of factors like topography of the region, climatic characteristics like rainfall and runoff, land-use land-cover, social factors which are related to the development of watershed for agricultural uses and domestic purposes in the region. The present research is throwing a focus on how morphometric parameters in association with GIS analysis will help in identifying the ranking of the sub-watersheds for further development which help of suggested watershed structures. Shevgaon and Pathardi tahsils are drought prone tahsils of Ahmednagar district in Maharashtra. These tahsils come under the semi-arid region. Sub-watershed prioritization is necessary for proper planning and management of natural resources for sustainable development of the study area. Less rainfall and increasing population pressure on the land as well as water resources lead to scarcity of the water in the region. Hence, researcher has selected Shevgaon and Pathardi tahsils for sub-watershed prioritization. There are seven sub-watersheds which selected for the present research paper. In the morphological analysis linear aspects, aerial aspects and relief aspects are considered for the prioritization. The largest sub-watershed is Erdha which is located at Karanji in Pathardi tahsil having an area of 145.06 km2 and smallest sub-watershed is Erandgaon which is located in Shevgaon tahsil having an area of 40.143 km2. For all seven sub-watersheds, seven morphometric parameters were considered for calculating the compound parameter values. Finally, compound parameter values are grouped into three groups such as, high priority (below 4.0), moderate priority (4.0 to 5.0) and low priority (above 5.0) according to the compound value Erandgaon, Chapadgaon and Tarak sub-watersheds comes under high priority group, Erdha and Domeshwar sub-watersheds come under moderate priority group and Chandani and Kasichi sub-watershed come under low priority group. Both the tahsils falls in drought prone area, after getting the watershed structure overall development of the region will take place.

Keywords: sub-watersheds, GIS and remote sensing, morphometric analysis, compound parameter value, prioritization

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Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

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Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

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Authors: Ezekiel Mwangi, Stephen Kimani, Agnes Mindila

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Usability is one of the key factors that determine the success or failure of any WebGIS (technology normally applied on the internet to analyze and present spatial data on the Internet). However, not all the usability attributes have the same impact on usability. It is, therefore, necessary to prioritize WebGIS usability elements and determine the ones that are more crucial to the success of the WebGIS. This research aims to identify the main elements of WebGIS usability, investigate the order of importance and priority of the usability elements of WebGIS, and propose a WebGIS development framework that incorporates the prioritization of the usability elements. This will be achieved through a literature review. The outcome of this research will help usability specialists and WebGIS developers in determining specific usability elements that should be accorded more emphasis during the design and development of WebGIS.

Keywords: framework, prioritization, usability, WebGIS

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Authors: Peter Sabev, Katalina Grigorova

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Test automation allows performing difficult and time consuming manual software testing tasks efficiently, quickly and repeatedly. However, development and maintenance of automated tests is expensive, so it needs a proper prioritization what to automate first. This paper describes a simple yet efficient approach for such prioritization of test cases based on the effort needed for both manual execution and software test automation. The suggested approach is very flexible because it allows working with a variety of assessment methods, and adding or removing new candidates at any time. The theoretical ideas presented in this article have been successfully applied in real world situations in several software companies by the authors and their colleagues including testing of real estate websites, cryptographic and authentication solutions, OSGi-based middleware framework that has been applied in various systems for smart homes, connected cars, production plants, sensors, home appliances, car head units and engine control units (ECU), vending machines, medical devices, industry equipment and other devices that either contain or are connected to an embedded service gateway.

Keywords: automated testing, manual testing, test automation, software testing, test prioritization

Procedia PDF Downloads 334

Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo, Jin-O Kim

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Home Energy Management System (HEMS) which makes the residential consumers contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it also represents impacts of the comfort level on the scheduling result.

Keywords: load scheduling, usage pattern, user’s comfort, copula function, branch and bound, electric heater

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Authors: Pijush Roy, Vinay Kumar Rai

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The present study highlights the estimation of soil loss and identification of critical area for implementation of best management practice is central to the success of soil conservation programme. The quantification of morphometric and Universal Soil Loss Equation (USLE) factors using remote sensing and GIS for prioritization of micro-watersheds in Asan River catchment, western Doon valley at foothills of Siwalik ranges in the Dehradun districts of Uttarakhand, India. The watershed has classified as a dendritic pattern with sixth order stream. The area is classified into very high, high, moderately high, medium and low susceptibility zones. High to very high erosion zone exists in the urban area and agricultural land. Average annual soil loss of 64 tons/ha/year has been estimated for the watershed. The optimum management practices proposed for micro-watersheds of Asan River basin are; afforestation, contour bunding suitable sites for water harvesting structure as check dam and soil conservation, agronomical measure and bench terrace.

Keywords: erosion susceptibility zones, morphometric characteristics, prioritization, remote sensing and GIS, universal soil loss equation

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Authors: M. Mokhber, J. Hedayati

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From the managerial perspective, it is important to devise an operational plan based on top priorities due to limited resources, diversity of measures and high costs needed to improve safety in infrastructure. Dealing with the high-risk corridors across Iran, this study prioritized the corridors according to statistical data on accidents involving fatalities, injury or damage over three consecutive years. In collaboration with the Iranian Police Department, data were collected and modified. Then, the prioritization criteria were specified based on the expertise opinions and international standards. In this study, the prioritization criteria included accident severity and accident density. Finally, the criteria were standardized and weighted (equal weights) to score each high-risk corridor. The prioritization phase involved the scoring and weighting procedure. The high-risk corridors were divided into twelve groups out of 50. The results of data analysis for a three-year span suggested that the first three groups (150 corridors) along with a quarter of Iranian road network length account for nearly 60% of traffic accidents. In the next step, according to variables including weather conditions particular roads for the purpose of winter safety measures were extracted from the abovementioned categories. According to the results ranking, ‎‏9‏‎ roads with the overall ‎length of about ‎‎‏1000‏‎ Km of high-risk corridors are considered as preferences of ‎safety measures‎.

Keywords: high-risk corridors, HRCs, road safety rating, road scoring, winter safety measures

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Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

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Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Sai Amulya Gollapalli, Dilip A. Patel, Parth Patel K., Lukman E. Mansuri

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Accumulation of moisture is one of the most worrisome aspects of a building. Architects and engineers tend to ignore its vitality during the designing and construction stage. Major fatalities in buildings can be caused by it. People avoid spending a lot of money on waterproofing. If the same mistake is repeated, no deep thinking is done. The quality of workmanship and construction is depleting due to negligence. It is important to do an analysis of the water maintenance issues happening in the current buildings and give a database for all the factors that are causing the defect. In this research, surveys are done with two waterproofing consultants, two client engineers, and two project managers. The survey was based on a matrix that was based on the causes of water maintenance issues. There were around 100 causes that were identified. The causes were categorized into six, namely, manpower, finance, method, management, environment, and material. In the matrices, the causes on the x-direction matched with the causes on the y-direction. 3 Likert scale was used to make a pairwise comparison between causes on each cell. Matrices were evaluated for the main categories and for each category separately. A final ranking was done by the weights achieved, and ‘cracks arriving from various construction joints’ was the highest with 0.57 relative significance, and ‘usage of the material’ was the lowest with 0.03 relative significance. Twelve defects due to water leakage were identified, and interviewees were asked to make a pairwise comparison of them, too, to understand the priorities. When the list of causes is achieved, the prioritization as per the stratification analysis is done. This will be beneficial to the consultants and contractors as they will get a primary idea of which causes to focus on.

Keywords: water leakage, survey, causes, matrices, prioritization

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Authors: Wenqi Liu, Reginald Bailey

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This study explores an advanced approach to enhancing B2B sales forecasting by integrating machine learning models with a rule-based decision framework. The methodology begins with the development of a machine learning classification model to predict conversion likelihood, aiming to improve accuracy over traditional methods like logistic regression. The classification model's effectiveness is measured using metrics such as accuracy, precision, recall, and F1 score, alongside a feature importance analysis to identify key predictors. Following this, a machine learning regression model is used to forecast sales value, with the objective of reducing mean absolute error (MAE) compared to linear regression techniques. The regression model's performance is assessed using MAE, root mean square error (RMSE), and R-squared metrics, emphasizing feature contribution to the prediction. To bridge the gap between predictive analytics and decision-making, a rule-based decision model is introduced that prioritizes customers based on predefined thresholds for conversion probability and predicted sales value. This approach significantly enhances customer prioritization and improves overall sales performance by increasing conversion rates and optimizing revenue generation. The findings suggest that this combined framework offers a practical, data-driven solution for sales teams, facilitating more strategic decision-making in B2B environments.

Keywords: sales forecasting, machine learning, rule-based decision model, customer prioritization, predictive analytics

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: David Nantes, George Gilbert

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There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

Procedia PDF Downloads 91