Search results for: metric analysis

Authors: Seyedeh Belin Tavakoly Sany, H. Rosli, R. Majid, S. Aishah

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In this study, water monitoring was performed from Nov. 2012 to Oct. 2013 to assess water quality and evaluate the spatial and temporal distribution of physicochemical and biological variables in water. Water samples were collected from 10 coastal water stations of West Port. In the case of water-quality assessment, multi-metric indices and operational indicators have been proposed to classify the trophic status at different stations. The trophic level of West Port coastal water ranges from eutrophic to hypertrophic. Chl-a concentration was used to estimate the biological response of phytoplankton biomass and indicated eutrophic conditions in West Port and mesotrophic conditions at the control site. During the study period, no eutrophication events or secondary symptoms occurred, which may be related to hydrodynamic turbulence and water exchange, which prevent the development of eutrophic conditions in the West Port.

Keywords: water quality, multi-metric indices, operational indicator, Malaysia, West Port

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Authors: Ayse Ozbil, Gorsev Argin, Demet Yesiltepe

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Data for this cross-sectional study were drawn from questionnaires conducted in 10 elementary schools (1000 students, ages 12-14) located in Istanbul, Turkey. School environments (1600 meter buffers around the school) were evaluated through GIS-based land-use data (parcel level land use density) and street-level topography. Street networks within the same buffers were evaluated by using angular segment analysis (Integration and Choice) implemented in Depthmap as well as two segment-based connectivity measures, namely Metric and Directional Reach implemented in GIS. Segment Angular Integration measures how accessible each space from all the others within the radius using the least angle measure of distance. Segment Angular Choice which measures how many times a space is selected on journeys between all pairs of origins and destinations. Metric Reach captures the density of streets and street connections accessible from each individual road segment. Directional Reach measures the extent to which the entire street network is accessible with few direction changes. In addition, socio-economic characteristics (annual income, car ownership, education-level) of parents, obtained from parental questionnaires, were also included in the analysis. It is shown that surrounding street network configuration is strongly associated with both walk-mode shares and average walking distances to/from schools when controlling for parental socio-demographic attributes as well as land-use compositions and topographic features in school environments. More specifically, findings suggest that the scale at which urban form has an impact on pedestrian travel is considerably larger than a few blocks around the school.

Keywords: Istanbul, street network layout, urban form, walking to/from school

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Authors: Gabriel I. Loaiza Ossa, Carlos A. Cadavid Moreno, Juan C. Arango Parra

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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ= -1/2, as does the family of usual Gaussian distributions. In the present paper, firstly, we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ₁, θ₂; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the inverse q-Gaussian distribution family (q < 3) as the family obtained by replacing the usual exponential function with the Tsallis q-exponential function in the expression for the inverse Gaussian distribution and observe that it supports two possible geometries, the Fisher and the q-Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q-Fisher geometry of the inverse q-Gaussian distribution family, similar to the ones obtained in the case of the inverse Gaussian distribution family.

Keywords: base of changes, information geometry, inverse Gaussian distribution, inverse q-Gaussian distribution, statistical manifolds

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Authors: Seyed Habib A. Rahmati, Mohamad Hasan Sadeghpour, Parsa Fallah Sheikhlari

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Location quotient (LQ) is a comparison technique that represents emphasized economic structure of single zone versus the standard area to identify specialty for every zone. In another words, the exact calculation of this metric can show the main core competencies and critical capabilities of an area to the decision makers. This research focus on the exact calculation of the LQ for an Iranian Province called Qazvin and within a case study introduces LQ of the capable industries of Qazvin. Finally, through different graphs and tables, it creates an opportunity to compare the recognized capabilities.

Keywords: location quotient, case study, province analysis, core competency

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Authors: Brian Basvi

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A technique for analyzing a security's intrinsic value is called fundamental analysis. It involves looking at relevant financial, economic, and other qualitative and quantitative aspects. Earnings Per Share (EPS), a crucial metric in fundamental analysis, is calculated by dividing a company's net income by the total number of outstanding shares. With more than 70 listed businesses, the Zimbabwe Stock Exchange (ZSE) is the primary stock exchange in Zimbabwe. This study applies the EPS financial ratio and stock valuation techniques to historical stock data from 68 companies listed on the Zimbabwe Stock Exchange. According to a ZSE study, EPS significantly affects share prices that are listed on the market. The study's objective was to assess how fundamental analysis affected the idea of EPS in ZSE stock valuation. It concluded that EPS is an important consideration for investors when they make judgments about their investments. According to the study's findings, fundamental analysis is a useful tool for ZSE investors since it offers insightful information about a company's financial performance and aids in decision-making. Investors can have a better understanding of a company's underlying worth and prospects for future growth by looking into EPS and other basic aspects.

Keywords: fundamental analysis, stock valuation, EPS, share pricing

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Authors: Arash Yousefi

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Experts suggest that relying exclusively on parameters to convey a situation or establish a condition may not be adequate. Assessing and appraising incidents in a system based on accident parameters, such as accident frequency, lost workdays, or fatalities, may not always be precise and occasionally erroneous. The frequency rate of accidents is a metric that assesses the correlation between the number of accidents causing work-time loss due to injuries and the total working hours of personnel over a year. Traditionally, this has been calculated based on one million working hours, but the American Occupational Safety and Health Organization has updated its standards. The new coefficient of 200/000 working hours is now used to compute the frequency rate of accidents. It's crucial to ensure that the total working hours of employees are equally represented when calculating individual event and incident numbers. The accident severity rate is a metric used to determine the amount of time lost or wasted during a given period, often a year, in relation to the total number of working hours. It measures the percentage of work hours lost or wasted compared to the total number of useful working hours, which provides valuable insight into the number of days lost or wasted due to work-related incidents for each working hour. Calculating the severity of an incident can be difficult if a worker suffers permanent disability or death. To determine lost days, coefficients specified in the "tables of days equivalent to OSHA or ANSI standards" for disabling injuries are used. The accident frequency coefficient denotes the rate at which accidents occur, while the accident severity coefficient specifies the extent of damage and injury caused by these accidents. These coefficients are crucial in accurately assessing the magnitude and impact of accidents.

Keywords: incidents, safety, analysis, frequency, severity, injuries, determine

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Authors: D. S. Palimkar

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Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

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Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

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By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Richard Pincak

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Starting from a 4D spacetime model using a partially negative dimensional product manifold (PNDP-manifold), which emerges as a 2D spacetime, we developed an analysis of tidal forces and Hawking radiation near the event horizon of a Schwarzchild black hole. The modified 2D metric, incorporating the effects of the four-dimensional Weyl tensor, with the dilatonic field and the newly derived time relation \(2\alpha t = \ln \epsilon\), can enable a deeper understanding of quantum gravity. The analysis shows how the modified Hawking temperature and distribution of emitted particles are affected by additional fields, providing potential observables for future experiments.

Keywords: black holes, Hawking radiation, Weyl tensor, information paradox

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Authors: Maryam Azimi, Amin Banitalebi-Dehkordi, Yuanyuan Dong, Mahsa T. Pourazad, Panos Nasiopoulos

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While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video data set is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this data set is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to their tested metrics in the presence of the tested types of distortions.

Keywords: HDR, dynamic range, LDR, subjective evaluation, video compression, HEVC, video quality metrics

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Masrur Alam Khan

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The purpose of this study was to examine the dyadic interaction techniques that social media users utilize to reduce uncertainty in their day to day business engagements in the absence of their physical interaction. The study empirically tested assumptions of uncertainty reduction theory while addressing self-disclosure, seeking questions to develop consensus, and subsequently to achieve intimacy in very conducive environment. Moreover, this study examined the effect of dyadic interaction through social media among business community while identifying the strength of their reciprocity in relationships and compares it with those having no dyadic relations due to absence of social media. Using socio-metric survey, the study revealed a better understanding of their partners for upholding their professional relations more credible. A sample of unacquainted, both male and female, was randomly asked questions regarding their nature of dyadic interaction within their office while using social media (face-to-face, visual CMC (webcam) or text-only). Primary results explored that the social media users develop their better know-how about their professional obligations to reduce ambiguity and align with one to one interact.

Keywords: dyadic-interaction, social media, uncertainty reduction, socio-metric survey, self-disclosure, intimacy, reciprocity in relationship

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Authors: Luv Sharma

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Sex determination has been the most intriguing puzzle for forensic pathologists and anthropologists, for which efforts have been made for a long. Sexual dimorphism is well established in the adult pelvis, and it is known to provide the highest level of information about sexual dimorphism. This study was conducted to know whether this dimorphism exists in fetal bones or not. A total of 34 pairs of fetal pelvis bones (22 males and 12 Females), ages ranging from 4 months to full term, were collected from unidentified dead fetuses brought to the Department of Forensic Medicine for routine medicolegal autopsies to study for sexual dimorphism in the Department of Anatomy, Pt. BD Sharma PGIMS, Rohtak. Samples were divided into 2 age groups, and various metric parameters were recorded with the help of a digital vernier caliper. Data obtained was subjected to descriptive and discriminant functional analysis. Results of Descriptive and Discriminant Functional Analysis showed that sex determination can be done with 100% accuracy by using different combinations of parameters of fetal ilium. This study illustrates that sexual dimorphism exists from early fetal life after mid-pregnancy; it can be clearly established by discriminant functional analysis.

Keywords: Ilium, fetus, sex determination, morphometric

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: Ahmad Mohsin, Irfan Raza Naqvi, Syda Fatima Usamn

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Applications with higher fault tolerance index are considered more reliable and trustworthy to drive quality. In recent years application development has been shifted from traditional desktop and web to native and hybrid application(s) for the web and mobile platforms. With the emergence of Internet of things IOTs, cloud and big data trends, the need for measuring Fault Tolerance for these complex nature applications has increased to evaluate their performance. There is a phenomenal gap between fault tolerance metrics development and measurement. Classic quality metric models focused on metrics for traditional systems ignoring the essence of today’s applications software, hardware & deployment characteristics. In this paper, we have proposed simple metrics to measure fault tolerance considering general requirements for Web and Mobile Applications. We have aligned factors – subfactors, using GQM for metrics development considering the nature of mobile we apps. Systematic Mathematical formulation is done to measure metrics quantitatively. Three web mobile applications are selected to measure Fault Tolerance factors using formulated metrics. Applications are then analysed on the basis of results from observations in a controlled environment on different mobile devices. Quantitative results are presented depicting Fault tolerance in respective applications.

Keywords: web and mobile applications, reliability, fault tolerance metric, quality metrics, GQM based metrics

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Authors: A. Anandha Selvan, B. Malarvizhi

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In recent year the problem of space debris have become very serious. The mass of the artificial objects in orbit increased quite steadily at the rate of about 145 metric tons annually, leading to a total tally of approximately 7000 metric tons. Now most of space debris object orbiting in LEO region about 97%. The catastrophic collision can be mostly occurred in LEO region, where this collision generate the new debris. Thus, we propose a concept for cleaning the space debris in the region of thermosphere by passing the Extreme Ultraviolet (EUV) radiation to in front of space debris object from the re-orbiter. So in our concept the Extreme Ultraviolet (EUV) radiation will create the thermosphere expansion by reacting with atmospheric gas particles. So the drag is produced in front of the space debris object by thermosphere expansion. This drag force is high enough to slow down the space debris object’s relative velocity. Therefore the space debris object gradually reducing the altitude and finally enter into the earth’s atmosphere. After the first target is removed, the re-orbiter can be goes into next target. This method remove the space debris object without catching debris object. Thus it can be applied to a wide range of debris object without regard to their shapes or rotation. This paper discusses the operation of re-orbiter for removing the space debris in thermosphere region.

Keywords: active space debris removal, space debris, LEO, extreme ultraviolet, re-orbiter, thermosphere

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Elena M. Kopteva, Pavlina Jaluvkova, Zdenek Stuchlik

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The question of constructing a consistent model of the cosmological black hole remains to be unsolved and still attracts the interest of cosmologists as far as it is important in a wide set of research problems including the problem of the black hole horizon dynamics, the problem of interplay between cosmological expansion and local gravity, the problem of structure formation in the early universe etc. In this work, the model of the cosmological black hole is built on the basis of the exact solution of the Einstein equations for the spherically symmetric inhomogeneous dust distribution in the approach of the mass function use. Possible trajectories for massive particles and photons near the black hole immersed in the nonstatic dust cosmological background are investigated in frame of the obtained model. The reference system of distant galaxy comoving to cosmological expansion combined with curvature coordinates is used, so that the resulting metric becomes nondiagonal and involves both proper ‘cosmological’ time and curvature spatial coordinates. For this metric the geodesic equations are analyzed for the test particles and photons, and the respective trajectories are built.

Keywords: exact solutions for Einstein equations, Lemaitre-Tolman-Bondi solution, cosmological black holes, particle and photon trajectories

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Authors: Silvio Ricardo Rodrigues Sanches, Bianca Cogo Barbosa, Beatriz Regina Brum, Cléber Gimenez Corrêa

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To evaluate the quality of a segmentation algorithm, the authors use subjective or objective metrics. Although subjective metrics are more accurate than objective ones, objective metrics do not require user feedback to test an algorithm. Objective metrics require subjective experiments only during their development. Subjective experiments typically display to users some videos (generated from frames with segmentation errors) that simulate the environment of an application domain. This user feedback is crucial information for metric definition. In the subjective experiments applied to develop some state-of-the-art metrics used to test segmentation algorithms, the videos displayed during the experiments did not contain audio. Audio is an essential component in applications such as videoconference and augmented reality. If the audio influences the user’s perception, using only videos without audio in subjective experiments can compromise the efficiency of an objective metric generated using data from these experiments. This work aims to identify if the audio influences the user’s perception of segmentation quality in background substitution applications with audio. The proposed approach used a subjective method based on formal video quality assessment methods. The results showed that audio influences the quality of segmentation perceived by a user.

Keywords: background substitution, influence of audio, segmentation evaluation, segmentation quality

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Authors: P. Y. Tsyba, O. V. Razina, E. Güdekli, R. Myrzakulov

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In this paper, we consider the equation of motion for the F(R,T) gravity on their property of conformal invariance. It is shown that in the general case such a theory is not conformally invariant. Special cases for the functions v and u, in which the properties of the theory can appear, were studied.

Keywords: conformal invariance, gravity, space-time, metric

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Authors: Deepak K. Gupta, T. R. Ravindran

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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.

Keywords: spatial light modulator, optical trapping, aberration, phase modulation

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Authors: Alan Luo, Hunter N. B. Moseley

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Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from x-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for x-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across x-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.

Keywords: biomacromolecular structure, coenzyme, electron density discrepancy analysis, x-ray crystallography

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Authors: Mrinal Kanti Bhowmik, Debanjana Debnath Jr., Debotosh Bhattacharjee

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A facial expression is undeniably the human manners. It is a significant channel for human communication and can be applied to extract emotional features accurately. People in pain often show variations in facial expressions that are readily observable to others. A core of actions is likely to occur or to increase in intensity when people are in pain. To illustrate the changes in the facial appearance, a system known as Facial Action Coding System (FACS) is pioneered by Ekman and Friesen for human observers. According to Prkachin and Solomon, a set of such actions carries the bulk of information about pain. Thus, the Prkachin and Solomon pain intensity (PSPI) metric is defined. So, it is very important to notice that facial expressions, being a behavioral source in communication media, provide an important opening into the issues of non-verbal communication in pain. People express their pain in many ways, and this pain behavior is the basis on which most inferences about pain are drawn in clinical and research settings. Hence, to understand the roles of different pain behaviors, it is essential to study the properties. For the past several years, the studies are concentrated on the properties of one specific form of pain behavior i.e. facial expression. This paper represents a comprehensive study on pain assessment that can model and estimate the intensity of pain that the patient is suffering. It also reviews the historical background of different pain assessment techniques in the context of painful expressions. Different approaches incorporate FACS from psychological views and a pain intensity score using the PSPI metric in pain estimation. This paper investigates in depth analysis of different approaches used in pain estimation and presents different observations found from each technique. It also offers a brief study on different distinguishing features of real and fake pain. Therefore, the necessity of the study lies in the emerging fields of painful face assessment in clinical settings.

Keywords: facial action coding system (FACS), pain, pain behavior, Prkachin and Solomon pain intensity (PSPI)

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Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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Authors: Stephan Schiffer, Andreas Kain, Philipp Wilde, Maximilian Helbing, Bernard Bäker

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Automobile manufacturers progressively focus on a downsizing strategy to meet the EU's CO2 requirements concerning type-approval consumption cycles. The reduction in naturally aspirated engine power is compensated by increased levels of turbocharging. By downsizing conventional engines, CO2 emissions are reduced. However, it also implicates major challenges regarding longitudinal dynamic characteristics. An example of this circumstance is the delayed turbocharger-induced torque reaction which leads to a partially poor response behavior of the vehicle during acceleration operations. That is why it is important to focus conventional drive train design on real customer driving again. The currently considered dynamic maneuvers like the acceleration time 0-100 km/h discussed by journals and car manufacturers describe longitudinal dynamics experienced by a driver inadequately. For that reason we present the realization and evaluation of a comprehensive proband study. Subjects are provided with different vehicle concepts (electrified vehicles, vehicles with naturally aspired engines and vehicles with different concepts of turbochargers etc.) in order to find out which dynamic criteria are decisive for a subjectively strong acceleration and response behavior of a vehicle. Subsequently, realistic acceleration criteria are derived. By weighing the criteria an evaluation metric is developed to objectify customer-oriented transient dynamics. Fully-electrified vehicles are the benchmark in terms of customer-oriented longitudinal dynamics. The electric machine provides the desired torque almost without delay. This advantage compared to combustion engines is especially noticeable at low engine speeds. In conclusion, we will show the degree to which extent customer-relevant longitudinal dynamics of conventional vehicles can be approximated to electrified vehicle concepts. Therefore, various technical measures (turbocharger concepts, 48V electrical chargers etc.) and drive train designs (e.g. varying the final drive) are presented and evaluated in order to strengthen the vehicle’s customer-relevant transient dynamics. As a rating size the newly developed evaluation metric will be used.

Keywords: 48V, customer-oriented driving dynamics, electric charger, electrified vehicles, vehicle concepts

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Authors: K. M. S. Weerasinghe, A. H. K. Balasooriya, S. L. Ransingha, G. D. Krishantha, R. S. Brhakamanagae, L. C. Wijethilke

Abstract:

Tomato (Lycopersicon esculentum Mill.) is a major horticultural crop with an estimated global production of over 120 million metric tons and ranks first as a processing crop. The average tomato productivity in Sri Lanka (11 metric tons/ha) is much lower than the world average (24 metric tons/ha).To meet the tomato demand for the increasing population the productivity has to be intensified through the agronomic-techniques. Nutrition is one of the main factors which govern the growth and yield of tomato and the main nutrient source soil affect the plant growth and quality of the produce. Continuous cropping, improper fertilizer usage etc., cause widespread nutrient deficiencies. Therefore synthetic fertilizers and organic manures were introduced to enhance plant growth and maximize the crop yields. In this study, effects of macro and micronutrient supplementations on improvement of growth and yield of tomato were investigated. Selected tomato variety is Maheshi and plants were grown in Regional Agricultural and Research Centre Makadura under the Department of Agriculture recommended (DOA) macro nutrients and various combination of Ontario recommended dosages of secondary and micro fertilizer supplementations. There were six treatments in this experiment and each treatment was replicated in three times and each replicate consisted of six plants. Other than the DOA recommendation, five combinations of Ontario recommended dosage of secondary and micronutrients for tomato were also used as treatments. The treatments were arranged in a Randomized Complete Block Design. All cultural practices were carried out according to the DOA recommendations. The mean data was subjected to the statistical analysis using SAS package and mean separation (Duncan’s Multiple Range test at 5% probability level) procedures. Secondary and micronutrients containing treatments significantly increased most of the growth parameters. Plant height, plant girth, number of leaves, leaf area index etc. Fruits harvested from pots amended with macro, secondary and micronutrients performed best in terms of total yield; yield quality; to pots amended with DOA recommended dosage of fertilizer for tomato. It could be due to the application of all essential macro and micro nutrients that rise in photosynthetic activity, efficient translocation and utilization of photosynthates causing rapid cell elongation and cell division in actively growing region of the plant leading to stimulation of growth and yield were caused. The experiment revealed and highlighted the requirements of essential macro, secondary and micro nutrient fertilizer supplementations for tomato farming. The study indicated that, macro and micro nutrient supplementation practices can influence growth and yield performances of tomato fruits and it is a promising approach to get potential tomato yields.

Keywords: macro and micronutrients, tomato, SAS package, photosynthates

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Authors: Lina Psarra, Manogj Sundaresan, Purjeet Sutar

Abstract:

In response to the global imperative for sustainable solutions, this article proposes the development of a comprehensive circularity index applicable to a wide range of products across various industries. The absence of a consensus on using a universal metric to assess circularity performance presents a significant challenge in prioritizing and effectively managing sustainable initiatives. This circularity index serves as a quantitative measure to evaluate the adherence of products, processes, and systems to the principles of a circular economy. Unlike traditional distinct metrics such as recycling rates or material efficiency, this index considers the entire lifecycle of a product in one single metric, also incorporating additional factors such as reusability, scarcity of materials, reparability, and recyclability. Through a systematic approach and by reviewing existing metrics and past methodologies, this work aims to address this gap by formulating a circularity index that can be applied to diverse product portfolio and assist in comparing the circularity of products on a scale of 0%-100%. Project objectives include developing a formula, designing and implementing a pilot tool based on the developed Product Circularity Index (PCI), evaluating the effectiveness of the formula and tool using real product data, and assessing the feasibility of integration into various sustainability initiatives. The research methodology involves an iterative process of comprehensive research, analysis, and refinement where key steps include defining circularity parameters, collecting relevant product data, applying the developed formula, and testing the tool in a pilot phase to gather insights and make necessary adjustments. Major findings of the study indicate that the PCI provides a robust framework for evaluating product circularity across various dimensions. The Excel-based pilot tool demonstrated high accuracy and reliability in measuring circularity, and the database proved instrumental in supporting comprehensive assessments. The PCI facilitated the identification of key areas for improvement, enabling more informed decision-making towards circularity and benchmarking across different products, essentially assisting towards better resource management. In conclusion, the development of the Product Circularity Index represents a significant advancement in global sustainability efforts. By providing a standardized metric, the PCI empowers companies and stakeholders to systematically assess product circularity, track progress, identify improvement areas, and make informed decisions about resource management. This project contributes to the broader discourse on sustainable development by offering a practical approach to enhance circularity within industrial systems, thus paving the way towards a more resilient and sustainable future.

Keywords: circular economy, circular metrics, circularity assessment, circularity tool, sustainable product design, product circularity index

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Authors: Chia-Ling Li

Abstract:

The scope of this article includes the production of 10,000 metric tons of non-phthalate per annum. The production process will include hydrogenation, separation, purification, and recycling of unprocessed feedstock. Based on experimental data, conversion and selectivity were chosen as reaction model parameters. The synthesis and separation processes of non-phthalate and phthalate were established by using Aspen Plus software. The article will be divided into six parts: estimation of physical properties, integration of production processes, purification case study, utility consumption, economic feasibility study and identification of bottlenecks. The purities of products was higher than 99.9 wt. %. Process parameters have important guiding significance to the commercialization of hydrogenation of phthalate.

Keywords: economic analysis, hydrogenation, non-phthalate, process simulation

Procedia PDF Downloads 268