Terms Of Key Performance Indicators Research Articles

Measurement and analysis of annual solar spectra at different installation angles in central Europe

The solar spectra in outdoor installations is very seldom equal to that under standard test conditions. This points to the importance of measuring, analyzing and understanding the implications of solar spectra variations with respect to the performance of solar cells. In this work, we present and analyze one year of sun spectra measured at two different angles in central Europe, where the spectrometers were installed at the optimum inclination angle and in vertical orientation, the latter being relevant for building integrated photovoltaics. We report for the first time the differences between the two inclination angles in terms of key performance indicators, such as average photon energy, blue fraction and spectral factor. Moreover, we show the impact of these spectral changes on the maximum current density of ideal single-junction and tandem devices in tilted and vertical orientations. Red-shifted solar spectra were more often found at the vertical installation in comparison to the optimum installation angle, which translated into up to 30% lower current-mismatch losses in idealized tandem devices throughout the year.

Bit-Interleaved Multiple Access: Improved Fairness, Reliability, and Latency for Massive IoT Networks

Internet-of-Things (IoT) networks require massive connections in dense areas. Therefore, a resource efficient multiple access scheme seems inevitable to enable immense connectivity where multiple devices have to share the same resource block. Non-orthogonal multiple access (NOMA) has been considered as the strongest candidate in recent years. However, in this paper, by considering the practical implementation, we first provide a true power allocation (PA) constraint with finite alphabet inputs for conventional downlink NOMA and demonstrate that it cannot support massive connections in practical systems. To this end, we propose bit-interleaved multiple access (BIMA) scheme in downlink IoT networks. The proposed BIMA scheme implements bitwise multiaccess interleaving and deinterleaving at the transceiver ends and there are no strict PA constraints, unlike conventional NOMA, thus allowing a high number of devices in the same resource block. We provide a comprehensive analytical framework for BIMA by investigating all key performance indicators (KPIs) to present both information-theoretic (i.e., ergodic capacity EC and outage probability OP) and finite alphabet inputs (i.e., bit error rate BER) performance metrics with both instantaneous and statistical channel ordering. In addition, we define Jain’s fairness index and proportional fairness index in terms of all KPIs. Based on the extensive computer simulations, we reveal that BIMA outperforms conventional NOMA significantly, with a performance gain of up to 20-30 dB in terms of KPIs in some scenarios. In other words, compared to conventional NOMA schemes, the same KPIs are met in BIMA with 20-30 dB less transmit power, which is quite promising for energy-limited use cases. Moreover, this performance gain becomes greater when more IoT devices are supported. BIMA provides a full diversity order for all IoT devices and enables the implementation of an arbitrary number of devices and modulation orders, which is crucial for IoT networks where a huge number of devices should be supported in a single resource block in dense areas. In addition to the overall performance gain, BIMA guarantees a fairness system where none of the devices gets a severely degraded performance and the sum-rate is shared in a fair manner among devices. It guarantees QoS satisfaction for all devices. Finally, we provide an intense complexity and latency analysis for BIMA and demonstrate that it provides lower latency compared to conventional NOMA receivers, since it allows parallel computation at the receivers and no iterative operations are required. We show that compared to conventional NOMA receivers, BIMA reduces latency by up to 350% for specific IoT devices and 170% on average.

Single cell protein from methanotrophic bacteria as an alternative healthy and functional protein source in aquafeeds, a holistic approach in rainbow trout (Oncorhynchus mykiss) juveniles

Bacterial single cell protein (BSCP) obtained from methanotrophic bacteria was tested as an alternative protein source to fishmeal (FM) in compound diets for rainbow trout (Oncorhynchus mykiss) juveniles (initial body weight, BW = 11.3 ± 0.2 g, mean ± standard deviation). Different levels of FM replacement (0, 25, 50, 75 and 100%) by a BSCP (0, 3.75, 7.5, 11.25 and 15% of Uniprotein® Aqua) were tested in isoproteic (crude protein: 42%) and isolipidic (crude fat: 21%) extruded diets. The trial was divided in two different parts, a nutritional trial that lasted 83 days during which the impact of experimental diets was evaluated in terms of key performance indicators (KPIs) associated to fish growth performance and feed utilization, which was followed by a challenge with a pathogenic bacterium (Aeromonas salmonicida subsp. salmonicida) to evaluate the immunological competence of fish fed the experimental diets (15 days). At the end of the nutritional trial, somatic growth in terms of body weight (BW) responded quadratically (P < 0.05) to the dietary inclusion of BCSP with the lowest BW values (183.4 ± 4.5 g) recorded in fish fed 100% FM replacement with BSCP, whereas the rest of dietary groups showed similar BW values (191.3–201.2 g). Feed intake was not affected by the level of FM replacement by BSCP, whereas feed conversion ratio (FCR) slightly increased with increasing levels of BSCP (P < 0.05), even though the lowest FCR values were found in fish fed 50% FM replacement by BSCP (0.79 ± 0.01) in comparison to the control group (0.81 ± 0.01). When using quadratic linear regression, the optimal dietary FM replacement by BSCP in terms of BW values was estimated as 41.7%. The nutritional quality of the fillet was not altered with experimental diets; all dietary groups showed similar amino acid levels as well as their content in HUFA n-3 and n-6 that remained unaltered (P > 0.05) and lipid nutritional indexes (P > 0.05). No negative effects were observed in the histological organization of the liver nor the proximate intestine, neither in the lipid peroxidation levels nor activity of antioxidative stress enzymes in the liver from fish fed increased inclusion levels of BSCP (P < 0.05). The replacement of FM by the tested BSCP obtained from methanotrophic bacteria did not cause an imbalance or dysbiosis in the intestinal microbiota in rainbow trout regardless of the level of FM replaced. The replacement of FM by BSCP at 50% improved disease resistance in rainbow trout exposed to furunculosis when compared to the control diet (cumulative mortality = 83.3 ± 7.2% vs. 49.2 ± 15.6%; P < 0.05), which suggested that this ingredient may also have some immunomodulatory properties that would protect fish from infections, although their mode of action deserves further attention. Current results indicated that the tested BSCP from methanotrophic bacteria is a safe, functional, and sustainable alternative protein source for aquafeeds.

Analysis, Limitations, and Opportunities of Modular Multilevel Converter-Based Architectures in Fast Charging Stations Infrastructures

As fast and ultrafast charging stations (FCS/UFCS) increase their degree of penetration in the grid, it becomes beneficial to connect them directly at the medium-voltage (MV) level, as this reduces volume, losses, and cost. Recent solutions propose the replacement of the typical combination of the low-frequency transformer plus low-voltage rectifier by a solid-state transformer (SST), which can be composed, among other topologies, by a modular multilevel converter. This article proposes and discusses the application of the modular multilevel converter (MMC) in FCS infrastructures, utilized as an active front-end rectifier, either as part of an SST or for direct connection to the second stage, comprised of isolated dc/dc converters. Focus is given on the advantages and limitations of the converter operating as a step-down rectifier, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$U_\text{DC}&lt; \hat{U}_\text{AC}$</tex-math></inline-formula> . As different architectures are presented, first the MMC step-down constraints and optimum operation points are explored and discussed, then the architectures are evaluated in terms of key performance indicators, such as size, efficiency, and reliability. At the end, experimental results for a full-scale MV MMC are presented, validating the analysis carried throughout this article.

Insights into the performance of hybrid graphene oxide/MOFs for CO2 capture at process conditions by molecular simulations

Hybridization of metal organic frameworks (MOFs) with graphene oxide (GO) is used to improve the CO2 adsorption performance of MOFs, but the underlying mechanism of this process is still unclear. This study provides a general framework to understanding the mechanism of CO2 adsorption and separation on GO/CuBTC and GO/UTSA-16 in order to optimize the synthesis of the desired material. For this purpose, molecular models mimicking the experimentally available hybrid materials were developed and studied by molecular simulations. Once the models were validated with available experimental data, a systematic study on the effect of different structure variables was performed, searching for the best hybridization procedure for this application, in a predictive manner. It has been confirmed that the interface between GO and MOFs produces strong interactions with CO2, which, together with the smaller pore sizes, significantly enhances the adsorption performance at low pressures. Moreover, the performance of the most promising hybrid GO/MOFs structures from pure CO2 adsorption isotherms for separating CO2 from nitrogen were predicted by GCMC based on binary mixtures (15CO2:85 N2) and a temperature swing adsorption (TSA) process. Among the different materials/compositions explored, GO/CuBTC with the highest GO content (i.e., 65% wt.) and under the premise of no stacking of GO, shows the best results in terms of key performance indicators: CO2/N2 adsorption selectivity (120 at 313 K), working capacity (1.794 mmol/g at a desorption temperature of 443 K), and a specific energy consumption (0.534 GJ/tonne-CO2) comparable to amine scrubbing.

Performance Comparison between Handover Decision Algorithms for Horizontal Handover in Long Term Evolution Networks

Comparative Analyses of Handover Decision Algorithms (HODA) for horizontal handovers in Long Term Evolution Network (LTE-A) in terms of Key Performance Indicators (KPIs) were conducted using system level simulation in MATLAB. The KPIs analyzed were the users’ throughput, spectral efficiency, cell –edge Spectral efficiency, handover success rate , call drop Rate, Cumulative Distribution Function (CDF) of Received Signal Reference Power (RSRP), Average RSRP over Primary Component Carrier (PCC) and Secondary Carrier (SCC) and interruption time. . From the results obtained, the algorithm based on spectrum aggregation of carriers from wireless communication spectrum and television white space band referred to as the proposed-TVWS algorithm showed remarkable performance improvements in all the chosen KPIs when compared with MIF and CONV except in handover success rate at UEs speeds less than 70 km/hr of which MIF-HODA algorithm seemed to perform better. Therefore, the proposed-TVWS has yielded baseline certainty in the increase of wireless network quality of service in addition to the seamless network connectivity for the mobile users.

Process-oriented approach towards catalyst design and optimisation

Translation of catalysts developed in academia to industrial end-users remains a challenge due to a lack of knowledge about the impact of catalyst attributes on the whole process and vice versa. A systematic methodology is proposed that assesses these in terms of Key Performance Indicators (KPIs). As a case study, the dehydration of butanol to butenes and dibutyl ether is considered over H-ZSM5 and H-Beta catalysts. It is demonstrated that catalysts should be designed for complete conversion and high butene selectivity, as removal of unreacted 1-butanol requires a complex separation due to the thermo-physical properties of the product mixture.

Artificial Intelligence Control Logic in Next-Generation Programmable Networks

The new generation of programmable networks allow mechanisms to be deployed for the efficient control of dynamic bandwidth allocation and ensure Quality of Service (QoS) in terms of Key Performance Indicators (KPIs) for delay or loss sensitive Internet of Things (IoT) services. To achieve flexible, dynamic and automated network resource management in Software-Defined Networking (SDN), Artificial Intelligence (AI) algorithms can provide an effective solution. In the paper, we propose the solution for network resources allocation, where the AI algorithm is responsible for controlling intent-based routing in SDN. The paper focuses on the problem of optimal switching of intents between two designated paths using the Deep-Q-Learning approach based on an artificial neural network. The proposed algorithm is the main novelty of this paper. The Developed Networked Application Emulation System (NAPES) allows the AI solution to be tested with different patterns to evaluate the performance of the proposed solution. The AI algorithm was trained to maximize the total throughput in the network and effective network utilization. The results presented confirm the validity of applied AI approach to the problem of improving network performance in next-generation networks and the usefulness of the NAPES traffic generator for efficient economical and technical deployment in IoT networking systems evaluation.

Analisis Kinerja Jaringan GSM di Daerah Urban dan SubUrban

The rapid advancement of technology development in terms of mobile communication make the current cellular card provider such as GSM strive to provide better service to its customers. Good service that can be expressed by its performance that meets the Performance standards base Key Performance Indicators (KPI ). For that we need a form of meausurement reserach and analysis to determine the performanceof the GSM system in urban and sub urban areas which aims to look at the area where the GSM system performance better. The research was conducted at P.T Axiata tbk by taking 6 BYS as a sample of 3 BTS in urban ( 2 in Padang Bulan and 1 in Pringan) and 3 BTS in Suburban (in Tembung). From research conducted, then it can be data required to calculate and analyze the standard KPI based performance parameters, namely Call Setup Success Ratio (CSSR), Call Drop Ratio (CDR), Handover Success Ratio (HOSR) and TCH Failures Congestion Ratio (TCHFCR). Then calculate and analyzed the percentage of errors each parameter of the performance. Results of calculations and analysis in comparison with standard GSM performace under the terms of KPI. Based on the calculation/analysis of data and analysis of the percentage of errors need that the performance of GSM in Urban area s are better than in the Suburban area. This is indicated by the value of CSSR, CDR, HOSR and TCHFCR in Urban areas closer to the standard value of performance based KPI compared with the results in Sub urban areas. So also is based on the analysis of the percentage of errors in Urban areas are better yhan in the Su urban areas, because in Urban areas have a percentage errors is smaller.

Influence of Business-Operational Performances and Company Size on CO2 Emissions Decrease-Case of Serbian Road Transport Companies

This research includes the analysis and comparison of long-term values of key business parameters of profit-oriented companies in Serbia, which are engaged in road transport of cargo or passengers. This paper takes into account the decreasing emissions of CO2 and its relation to the size of business (in terms of transported cargo or number of passengers), and thus by the company’s business success (income, profit). In the empirical part of this research—ecological, operational, and business factors were analyzed on a sample of road carriers from Serbia, i.e., the most common type of organized transport of people or physical goods. Key difference was made between large and small companies engaged in transport activities, followed by difference between those companies which have business activities only in Serbia, or engage also in international activities in the Balkan region (or in the rest of world). The main goal of this paper is to determine statistically significant differences between transport companies in terms of key performance indicators, depending on whether they operate only domestically or abroad. In relation to company size, this paper examined the sustainability of operations in the case of the largest transport companies, which represent half of the total transport activity in the country (by number of people transported or the amount of transported cargo), compared to all small carriers with less than 50 employees. Future research involves extending this sample of road transport companies to all Balkan countries, which have not yet become a part of the European Union and including additional operational as well as environmental indicators that are not conventionally measured during vehicle inspections.

A KPI-Enabled NFV MANO Architecture for Network Slicing with QoS

Communication systems are used not only by voice or file exchange applications, but also by other types of applications due to the coexistence of multiple and different verticals. Each vertical has its own requirements in terms of key performance indicators (KPIs) for their applications. Mapping the verticals KPIs into network quality of service (QoS) parameters and enforcing it at the network level is a complex procedure. Network slicing allows the deployment of multiple virtual networks (one per vertical) to work in parallel with their specific QoS based on the KPIs. This article presents and experimentally validates a KPI-enabled network function virtualization (NFV) management and orchestration (MANO) architecture able to manage network slices, to monitor the vertical KPI requirements and react in case they are not met. We address this objective from a holistic perspective, defining the network QoS parameters that enable meeting vertical KPIs along all levels of the NFV MANO architecture: the NSs using the 5G QoS Identifier parameter, the NFV network services using service level agreements, and the networking and computing services with QoS parameters. Finally, the described architecture is validated through an experimental use case based on a vertical realtime communications application.

Repository of Deep Renovation Packages Based on Industrialized Solutions: Definition and Application

Renovation Wave aims to boost the uptake of deep renovation towards the CO2 emission targets for 2030. In this perspective, there is the need of technologies and solution sets for improving the deep renovation process as well as demonstrating the performances for supporting the stakeholders in the decision-making process. To cope with the issue, this work presents a methodology for setting up a repository of building deep renovation packages that integrates industrialised facade technologies and more traditional solutions. The performances feeding into the repository have been evaluated by means of transient detailed simulations on a set of reference buildings in representative European climate conditions. The renovation packages are evaluated in terms of key performance indicators dealing with five areas: energy, comfort, pollutant emissions, cost, and renovation time. The defined repository includes 289 assessed technology packages and associated performances across Europe, providing a comprehensive support to identify the most effective solutions according to the user needs. The paper presents the application of the repository with two examples of stakeholders’ decision-making paths for selecting the deep renovation packages according to different priorities and expected targets.

Predictive CDN Selection for Video Delivery Based on LSTM Network Performance Forecasts and Cost-Effective Trade-Offs

Owing to increasing consumption of video streams and demand for higher quality content and more advanced displays, future telecommunication networks are expected to outperform current networks in terms of key performance indicators (KPIs). Currently, content delivery networks (CDNs) are used to enhance media availability and delivery performance across the Internet in a cost-effective manner. The proliferation of CDN vendors and business models allows the content provider (CP) to use multiple CDN providers simultaneously. However, extreme concurrency dynamics can affect CDN capacity, causing performance degradation and outages, while overestimated demand affects costs. 5G standardization communities envision advanced network functions executing video analytics to enhance or boost media services. Network accelerators are required to enforce CDN resilience and efficient utilization of CDN assets. In this regard, this study investigates a cost-effective service to dynamically select the CDN for each session and video segment at the Media Server, without any modification to the video streaming pipeline being required. This service performs time series forecasts by employing a Long Short-Term Memory (LSTM) network to process real time measurements coming from connected video players. This service also ensures reliable and cost-effective content delivery through proactive selection of the CDN that fits with performance and business constraints. To this end, the proposed service predicts the number of players that can be served by each CDN at each time; then, it switches the required players between CDNs to keep the (Quality of Service) QoS rates or to reduce the CP's operational expenditure (OPEX). The proposed solution is evaluated by a real server, CDNs, and players and delivering dynamic adaptive streaming over HTTP (MPEG-DASH), where clients are notified to switch to another CDN through a standard MPEG-DASH media presentation description (MPD) update mechanism.

Driving sustainable construction development through post-contract key performance indicators and drivers

PurposeThis research examines what key performance indicators (KPIs) and drivers should be applied at the post-contract phase of construction development to monitor and drive project outcomes in sustainable design and construction. It supplements the previous research which focuses on pre-contract sustainable procurement of competent professionals. Consequently, optimal sustainability can be achieved for the overall sustainable development process.Design/methodology/approachA review of empirical work was conducted to consolidate the holistic aspects of sustainability that should be considered for design and construction and their project outcome KPI measures. Based on a country-wide questionnaire survey of the university estate sector in the UK, a quantitative hierarchical regression analysis was conducted to identify the performance drivers for those KPIs.FindingsThe empirical work review demonstrates that holistic sustainability for development can be measured by project outcome KPIs: economic sustainability by cost KPIs; functional, social and environmental sustainability by quality KPIs. The quantitative hierarchical regression analysis confirmed that these four aspects of sustainability could be significantly driven by task performance and contextual performance drivers, as supported by the job performance theory.Research limitations/implicationsThe investigation was undertaken within the context of university estates forming a unique public sector in the UK. The findings form a baseline upon which further research can be conducted in other organisations in the wider public and private sectors. Ultimately, holistic sustainability can be fully driven by construction professionals to achieve government and corporate construction strategy for the benefits of sustainable built environment.Practical implicationsThe findings inform project managers and construction professionals that they should apply clear, measurable cost and quality KPIs and focus on significant performance drivers in tandem to drive holistic sustainability for design and construction. Project staff should have a high commitment, technical expertise and experience, execute the project with proper design and management methods and provide a high level of trust and collaboration to the client. Clients, designers and contractors are key stakeholders in the development process so they should be consulted for forming the contract KPIs to monitor the sustainable project outcomes.Social implicationsThe generalised results confirm that task and contextual performance drivers can be applied as project management tools for managing the professional team members to achieve sustainability deliverables in terms of KPIs. Such findings will enhance the government or corporate construction strategy for managing and achieving holistic sustainability for construction developments.Originality/valueThis research identifies post-contract performance monitoring measures (cost and quality KPIs as well as task and contextual performance drivers) that can be adopted for driving sustainable design and construction for sustainable development.

Key performance indicator of sustainability in the Malaysian food supply chain

The food supply chain in Malaysia plays a significant function in the nation’s economy. Since the industry is dominated by small and medium sized enterprises (SME), the local food supply chain must satisfy consumer demand. In order to help Malaysia to become more self-sufficient, improvements in the supply chain in terms of key performance indicators (KPIs) are important. However, it is common that strategic and operational KPIs are different and a disparity often exists between them. To be more successful for measuring the entire supply chain, the linkage of strategic objectives to operational objectives must be aligned to ensure the appropriate KPIs measure a proper connection between what they do and what the business achieves. The objective of this article is to propose a preliminary key indicator to measure sustainable performance within the perspective of Malaysian food supply chain. Key indicators have been summarized based on the previous researches focusing on the issue between 2007 until 2018. An overall of nine perspectives on sustainable performance measures in the food supply chain involved employee, supplier, health and safety, community, customer, cost effectiveness, quality, compliance and efficiency. These perspectives can be classified into three hierarchies; namely, strategic, tactical and operational. This paper proposes integration of key indicators as a starting point to evaluate the generic performance of Malaysia food supply chain.

A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation.

The assessment of transformations in the retinal vascular structure has a strong potential in indicating a wide range of underlying ocular pathologies. Correctly identifying the retinal vessel map is a crucial step in disease identification, severity progression assessment, and appropriate treatment. Marking the vessels manually by a human expert is a tedious and time-consuming task, thereby reinforcing the need for automated algorithms capable of quick segmentation of retinal features and any possible anomalies. Techniques based on unsupervised learning methods utilize vessel morphology to classify vessel pixels. This study proposes a directional multi-scale line detector technique for the segmentation of retinal vessels with the prime focus on the tiny vessels that are most difficult to segment out. Constructing a directional line-detector, and using it on images having only the features oriented along the detector’s direction, significantly improves the detection accuracy of the algorithm. The finishing step involves a binarization operation, which is again directional in nature, helps in achieving further performance improvements in terms of key performance indicators. The proposed method is observed to obtain a sensitivity of 0.8043, 0.8011, and 0.7974 for the Digital Retinal Images for Vessel Extraction (DRIVE), STructured Analysis of the Retina (STARE), and Child Heart And health Study in England (CHASE_DB1) datasets, respectively. These results, along with other performance enhancements demonstrated by the conducted experimental evaluation, establish the validity and applicability of directional multi-scale line detectors as a competitive framework for retinal image segmentation.

Agent-Based Simulation of Value Flow in an Industrial Production Process

The current competitive environment demands companies to be more and more efficient. In order to increase manufacturing efficiency, two apparently independent approaches have emerged: lean strategies, focusing on identifying and minimizing non-added value activities, identifying wastes in the system and their elimination, and information tools for planning and controlling activities. In this paper, a manufacturing system was considered for which it was necessary to increase the production capacity in order to respond to the customer’s increased demand. A practical case study in the automotive industry for a medium-sized enterprise was considered. In order to investigate the production process parameters and to implement lean principles, Value Stream Mapping (current analysis and optimized solution) and Anylogic agent-based simulations were carried out. Based on this, the lean performances, specific for the target VSM, were evaluated in terms of key performance indicators. The benefits of integrating agent-based simulation in the design and analysis of the value flow in the production chain are the capitalization of the information offered by Value Stream Mapping and the possibility to choose the best one from the possible scenarios. It generates important time and cost reductions without further resource waste.

ANALYZING PERFORMANCE OF SCALE HOTELS OF AHMEDABAD, INDIA

Purpose: Ahmadabad is not only one of the largest city and former capital city of Gujarat but also emerged as an important economic and industrial hub of North India. A latest study by Association Chambers of Commerce of India (ASSOCHAM) states that the percentage share of investments in hospitality sector in Gujarat has reduced from 29 percent for 2012- 13 to 14.5 percent as on June 2016. Henceforth, this paper tends to analyze the hotel’s performance in Ahmadabad city in terms of Key Performance Indicators (KPIs), revenue generation, hotel’s room demand and supply.&#x0D; Methodology: The study is based on secondary data of Smith Travel Research, Global. It is a descriptive cum longitudinal study and its approach is deductive. Four reports of Smith Travel Research (STR) Global i.e. Trend report: Ahmedabad (Publication date August 16, 2017), Market pipeline report (STRG): Ahmedabad (Publication date August 16, 2017) Profitability report: Ahmedabad (Publication date August 16, 2017) and STR India hotel review report (Publication date August, 2017) have been used for this study. The data is further analyze by SPSS and AMOS Version 20.&#x0D; Main Findings: The findings of this papers supports that there is a significant growth in the room revenue earnings of scale hotels in Ahmedabad from January 2010 to June 2017. Paper also reveals that the percentage change in Average daily rate, Revenue per available room, Occupancy percentage and demand of rooms is higher than pan India and central India scale hotels.&#x0D; Implications: The findings of this paper may provide helpful information to the investors and hospitality professionals who want to invest, run or understand the behavior of the Ahmedabad hotel market.&#x0D; Limitations: However the present study is confine to the secondary data of 55 different scale hotels of Ahmedabad.&#x0D; Originality: Many statistical tool such as one way ANOVA, Tukey HSD, Kruskal- Wallis test and a Co variance model is used for the better inference of the study. A comparison of KPIs between Ahmedabad scale hotels versus pan and central India hotel is conducted to understand the potential of hotel market in Ahmedabad city. .

Hourly simulations of an hospital building for assessing the thermal demand and the best retrofit strategies for consumption reduction

In the framework of energy saving and environmental protection, the role of the energy consumption in buildings is crucial. For existing buildings and especially for public ones, it is mandatory to correctly select and realize suitable retrofitting interventions to reduce costs and increase the efficiency. In fact, innovative solutions for both the envelope and the plants renovation are often very expensive and the correct choice becomes critical for the sustainability from the economic point of view.The aim of the present paper is to propose a methodology to optimize the process of selection for the retrofit interventions, here applied to a case study of the Monoblocco Pavilion at the San Martino Hospital in Genova, Italy. The building thermal behaviour is dynamically simulated by means of an Energy Plus model in order to evaluate the energy needs for both heating and cooling purposes. The base case scenario is evaluated in terms of key performance indicators (KPIs) and compared with benchmark values in order to select the more suitable intervention actions. For the analysed case study, the innovative retrofit solutions are façade void insulated panels, smart rotating windows with different emissivity glass and sunlight carrying optical-fibres coupled with dimmed LED lighting system. The technologies are combined in different intervention packages that are then compared in term of energy saving and economic sustainability by means of the estimation of hourly values of energy consumption and the assessment of the Simply Pay Back Period (SPB) of the investment.

A systematic review of augmented reality applications in maintenance

Abstract Augmented Reality (AR) technologies for supporting maintenance operations have been an academic research topic for around 50 years now. In the last decade, major progresses have been made and the AR technology is getting closer to being implemented in industry. In this paper, the advantages and disadvantages of AR have been explored and quantified in terms of Key Performance Indicators (KPI) for industrial maintenance. Unfortunately, some technical issues still prevent AR from being suitable for industrial applications. This paper aims to show, through the results of a systematic literature review, the current state of the art of AR in maintenance and the most relevant technical limitations. The analysis included filtering from a large number of publications to 30 primary studies published between 1997 and 2017. The results indicate a high fragmentation among hardware, software and AR solutions which lead to a high complexity for selecting and developing AR systems. The results of the study show the areas where AR technology still lacks maturity. Future research directions are also proposed encompassing hardware, tracking and user-AR interaction in industrial maintenance is proposed.