Search results for: packet loss probability estimation

Authors: Atul Dev, Pankaj Jha

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Dr. Genichi Taguchi looked at quality in a broader term and gave an excellent definition of quality in terms of loss to society. However the scope of this definition is limited to the losses imparted by a poor quality product to the customer only and are considered during the useful life of the product and further in a certain situation this loss can even be zero. In this paper, it has been proposed that the scope of quality of a product shall be further enhanced by considering the losses imparted by a poor quality product to society at large, due to associated environmental and safety related factors, over the complete life cycle of the product. Moreover, though these losses can be further minimized with the use of techno-safety interventions, the net losses to society however can never be made zero. This paper proposes an entirely new approach towards defining product quality and is based on Taguchi’s definition of quality.

Keywords: existing concept, goal post philosophy, life cycle, proposed concept, quality loss function

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Authors: Ashu Rastogi, Uttam Thakur, Jimmy Pathak, Rajesh Gupta, Anil Bhansali

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Introduction: Liraglutide is known to induce weight loss and metabolic benefits in obese individuals. However, its effect after sleeve gastrectomy are not known. Methods: People with obesity (BMI>27.5 kg/m2) underwent LSG. Subsequently, participants were randomized to receive either 0.6mg liraglutide subcutaneously daily from 6 week post to be continued till 24 week (L-L group) or placebo (L-P group). Patients were assessed before surgery (baseline) and 6 weeks, 12weeks, 18weeks and 24weeks after surgery for height, weight, waist and hip circumference, BMI, body fat percentage, HbA1c, fasting C-peptide, fasting insulin, HOMA-IR, HOMA-β, GLP-1 levels (after standard OGTT). MRI abdomen was performed prior to surgery and at 24weeks post operatively for the estimation of intrapancreatic and intrahepatic fat content. Outcome measures: Primary outcomes were changes in metabolic variables of fasting and stimulated GLP-1 levels, insulin, c-peptide, plasma glucose levels. Secondary variables were indices of insulin resistance HOMA-IR, Matsuda index; and pancreatic and hepatic steatosis. Results: Thirty-eight patients undergoing LSG were screened and 29 participants were enrolled. Two patients withdrew consent and one patient died of acute coronary event. 26 patients were randomized and data analysed. Median BMI was 40.73±3.66 and 46.25±6.51; EBW of 49.225±11.14 and 651.48±4.85 in the L-P and L-L group, respectively. Baseline FPG was 132±51.48, 125±39.68; fasting insulin 21.5±13.99, 13.15±9.20, fasting GLP-1 2.4± .37, 2.4± .32, AUC GLP-1 340.78± 44 and 332.32 ± 44.1, HOMA-IR 7.0±4.2 and 4.42±4.5 in the L-P and L-L group, respectively. EBW loss was 47± 13.20 and 65.59± 24.20 (p<0.05) in the placebo versus liraglutide group. However, we did not observe inter-group difference in metabolic parameters between the groups in spite of significant intra-group changes after 6 months of LSG. Intra-pancreatic fat prior to surgery was 3.21±1.7 and 2.2±0.9 (p=0.38) that decreased to 2.14±1.8 and 1.06±0.8 (p=0.25) at 6 months in L-P and L-L group, respectively. Similarly, intra-pancreatic fat was 1.97±0.27 and 1.88±0.36 (p=0.361) at baseline that decreased to 1.14±0.44 and 1.36±0.47 (p=0.465) at 6 months in L-P and L-L group, respectively. Conclusion: Liraglutide augments extra body weight loss after sleeve gastrectomy. A decrease in intra-pancreatic and intra-hepatic fat is noticed after bariatric surgery without additive benefit of liraglutide administration.

Keywords: sleeve gastrectomy, liraglutide, intra-pancreatic fat, insulin

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Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

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Authors: Zeyu Zhang, Guisheng Yin, Ziying Zhang, Liguo Zhang

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This paper mainly studies the path planning method based on ant colony optimization (ACO), and proposes heuristic integration ant colony optimization (HIACO). This paper not only analyzes and optimizes the principle, but also simulates and analyzes the parameters related to the application of HIACO in path planning. Compared with the original algorithm, the improved algorithm optimizes probability formula, tabu table mechanism and updating mechanism, and introduces more reasonable heuristic factors. The optimized HIACO not only draws on the excellent ideas of the original algorithm, but also solves the problems of premature convergence, convergence to the sub optimal solution and improper exploration to some extent. HIACO can be used to achieve better simulation results and achieve the desired optimization. Combined with the probability formula and update formula, several parameters of HIACO are tested. This paper proves the principle of the HIACO and gives the best parameter range in the research of path planning.

Keywords: ant colony optimization, heuristic integration, path planning, probability formula

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely. It depends on subspace decomposition of the covariance matrix to separate signal subspace from noise subspace. The decomposition normally is done by either Eigenvalue Decomposition (EVD) or Singular Value Decomposition (SVD) of the Auto-Correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. In this paper, the multipath channel estimation problem for a Slow Frequency Hopping (SFH) system using noise space based method is considered. An efficient method to estimate multipath the time delays basically is proposed, by applying MUltiple Signal Classification (MUSIC) algorithm which used the null space extracted by the Rank Revealing LU factorization (RRLU). The RRLU provides accurate information about the rank and the numerical null space which make it a valuable tool in numerical linear algebra. The proposed novel method decreases the computational complexity approximately to the half compared with RRQR methods keeping the same performance. Computer simulations are also included to demonstrate the effectiveness of the proposed scheme.

Keywords: frequency hopping, channel model, time delay estimation, RRLU, RRQR, MUSIC, LS-ESPRIT

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Julie A. LaRose

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Native American youth, ages 10-24, have the highest rate of suicide in the United States. The hopelessness experienced by the native American youth is linked to psychosocial reasons more than biological or intrapsychic reasons. Two significant social determinants of health that diminish their hope include historical trauma and cultural loss. Intergenerational grief is caused by historical trauma from hundreds of years of colonization, broken treaties, and forced migration, leading to land, resources, and sovereignty loss. Forced acculturation through boarding schools that native children were required to attend led to the loss of traditions and culture. The result is hopelessness. This paper reviewed peer-reviewed research literature, government reports, non-government organizations reports, and video and written publications by Native Americans. Building hope through healing historical trauma and embracing cultural traditions may reduce suicide rates among Native American youth.

Keywords: culture loss, historical trauma, Native American, suicide, suicide rates

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Authors: Vincenzo Russo, Rosella Giacometti

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The paper aims to assess the insurance industry's resilience under Solvency II against adverse scenarios. Starting from the economic balance sheet available under Solvency II for insurance and reinsurance undertakings, we assume that assets and liabilities follow a bivariate geometric Brownian motion (GBM). Then, using the results available under Margrabe's formula, we establish an analytical solution to calibrate the volatility of the asset-liability ratio. In such a way, we can estimate the probability of default and the probability of breaching the undertaking's Solvency Capital Requirement (SCR). Furthermore, since estimating the volatility of the Solvency Ratio became crucial for insurers in light of the financial crises featured in the last decades, we introduce a novel measure that we call Resiliency Ratio. The Resiliency Ratio can be used, in addition to the Solvency Ratio, to evaluate the insurance industry's resilience in case of adverse scenarios. Finally, we introduce a simplified stress test tool to evaluate the economic balance sheet under stressed conditions. The model we propose is featured by analytical tractability and fast calibration procedure where only the disclosed data available under the Solvency II public reporting are needed for the calibration. Using the data published regularly by the European Insurance and Occupational Pensions Authority (EIOPA) in an aggregated form by country, an empirical analysis has been performed to calibrate the model and provide the related results at the country level.

Keywords: Solvency II, solvency ratio, volatility of the asset-liability ratio, probability of default, probability to breach the SCR, resilience ratio, stress test

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Authors: Yuzhi Cai

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This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

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Authors: Suresh Palla

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This research paper presents the results of the study on the estimation of fly ash, slag and cement contents in blended and composite cements by novel selective dissolution method. Types of cement samples investigated include OPC with fly ash as performance improver, OPC with slag as performance improver, PPC, PSC and Composite cement confirming to respective Indian Standards. Slag and OPC contents in PSC were estimated by selectively dissolving OPC in stage 1 and selectively dissolving slag in stage 2. In the case of composite cement sample, the percentage of cement, slag and fly ash were estimated systematically by selective dissolution of cement, slag and fly ash in three stages. In the first stage, cement dissolved and separated by leaving the residue of slag and fly ash, designated as R1. The second stage involves gravimetric estimation of fractions of OPC, residue and selective dissolution of fly ash and slag contents. Fly ash content, R2 was estimated through gravimetric analysis. Thereafter, the difference between the R1 and R2 is considered as slag content. The obtained results of cement, fly ash and slag using selective dissolution method showed 10% of standard deviation with the corresponding percentage of respective constituents. The results suggest that this novel selective dissolution method can be successfully used for estimation of OPC and SCMs contents in different types of cements.

Keywords: selective dissolution method , fly ash, ggbfs slag, edta

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Ajay Agrawal, Pravin Shah, Shailaja Chhetri, Pappu Rijal

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Background and Objectives: Postpartum hemorrhage (PPH) is a common and occasionally life-threatening complication of labour. Cesarean section (CS) is associated with more blood loss than vaginal delivery. There is a trend for increasing CS rates in both developed and developing countries. This could increase the risk of morbidity and mortality, especially among anemic women. The objective of this study was to evaluate the effect of preoperative administration of Intravenous Tranexamic Acid (TA) on blood loss during and after elective CS delivery. Materials and Methods: It is a prospective, randomized controlled study. 160 eligible pregnant women of 37 or more POG planned for CS were randomized into two groups either to receive 10ml(1gm) of tranexamic acid intravenously or 10ml of normal saline. Blood loss was measured during and for 24 hours after operation. Results: The mean estimated blood loss was significantly lower in women treated with TA compared with women in the placebo group (392.13 ml ± 10.06 versus 498.69 ml ± 15.87, respectively; p < 0.001). The mean difference in pre-operative and post-operative hemoglobin levels was statistically significant in the tranexamic acid group than in the control group (0.31 ± 0.18 versus 0.79 ± 0.23, respectively; p < 0.001). Conclusion: Pre-operative use of tranexamic acid is associated with reduced blood loss during and after elective cesarean section. In a developing country like ours where PPH is a major threat to the life of the mothers, it seems to be a promising option.

Keywords: blood loss, cesarean section, postpartum hemorrhage, tranexamic acid

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Authors: Rafael Castilho Carvalho, Edjair de Souza Mota

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As the largest contributor to the biogeochemical functioning of the Earth system, the Amazon Rainforest has the greatest biodiversity on the planet, harboring about 15% of all the world's flora. Recognition and preservation are the focus of research that seeks to mitigate drastic changes, especially anthropic ones, which irreversibly affect this biome. Functional and low-cost monitoring alternatives to reduce these impacts are a priority, such as those using technologies such as Low Power Wide Area Networks (LPWAN). Promising, reliable, secure and with low energy consumption, LPWAN can connect thousands of IoT devices, and in particular, LoRa is considered one of the most successful solutions to facilitate forest monitoring applications. Despite this, the forest environment, in particular the Amazon Rainforest, is a challenge for these technologies, requiring work to identify and validate the use of technology in a real environment. To investigate the feasibility of deploying LPWAN in remote water quality monitoring of rivers in the Amazon Region, a LoRa-based test bed consisting of a Lora transmitter and a LoRa receiver was set up, both parts were implemented with Arduino and the LoRa chip SX1276. The experiment was carried out at the Federal University of Amazonas, which contains one of the largest urban forests in Brazil. There are several springs inside the forest, and the main goal is to collect water quality parameters and transmit the data through the forest in real time to the gateway at the uni. In all, there are nine water quality parameters of interest. Even with a high collection frequency, the amount of information that must be sent to the gateway is small. However, for this application, the battery of the transmitter device is a concern since, in the real application, the device must run without maintenance for long periods of time. With these constraints in mind, parameters such as Spreading Factor (SF) and Coding Rate (CR), different antenna heights, and distances were tuned to better the connectivity quality, measured with RSSI and loss rate. A handheld spectrum analyzer RF Explorer was used to get the RSSI values. Distances exceeding 200 m have soon proven difficult to establish communication due to the dense foliage and high humidity. The optimal combinations of SF-CR values were 8-5 and 9-5, showing the lowest packet loss rates, 5% and 17%, respectively, with a signal strength of approximately -120 dBm, these being the best settings for this study so far. The rains and climate changes imposed limitations on the equipment, and more tests are already being conducted. Subsequently, the range of the LoRa configuration must be extended using a mesh topology, especially because at least three different collection points in the same water body are required.

Keywords: IoT, LPWAN, LoRa, coverage, loss rate, forest

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Authors: S. B. Provost, Susan Sheng

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An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Rukhsana Kausar, Issam Malki

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The integration and assimilation of ethnic minority immigrants (EMIs) and their subsequent generations remains a serious unsettled issue in most of the host countries. This study conducts the labour market gender analysis to investigate specifically whether second generation of ethnic minority immigrants in the UK is gaining access to professional and managerial employment and advantaged occupational positions on par with their native counterparts. The data used to examine the labour market achievements of EMIs is taken from Labour Force Survey (LFS) for the period 2014-2018. We apply a multivalued treatment under ignorability as proposed by Cattaneo (2010), which refers to treatment effects under the assumptions of (i) selection – on – observables and (ii) common support. We report estimates of Average Treatment Effect (ATE), Average Treatment Effect on the Treated (ATET), and Potential Outcomes Means (POM) using three estimators, including the Regression Adjustment (RA), Augmented Inverse Probability Weighting (AIPW) and Inverse Probability Weighting- Regression Adjustment (IPWRA). We consider two cases: the case with four categories where the first-generation natives are the base category, the second case combine all natives as a base group. Our findings suggest the following. Under Case 1, the estimated probabilities and differences across groups are consistently similar and highly significant. As expected, first generation natives have the highest probability for higher career attainment among both men and women. The findings also suggest that first generation immigrants perform better than the remaining two groups, including the second-generation natives and immigrants. Furthermore, second generation immigrants have higher probability to attain higher professional career, while this is lower for a managerial career. Similar conclusions are reached under Case 2. That is to say that both first – generation and second – generation immigrants have a lower probability for higher career and managerial attainment. First – generation immigrants are found to perform better than second – generation immigrants.

Keywords: immigrnats, second generation, occupational attainment, ethnicity

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Authors: Y. B. Kirankumar, J. D. Mallapur

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Wireless Sensor Network (WSN) is an emerging technology, which has great invention for various low cost applications both for mass public as well as for defence. The wireless sensor communication technology allows random participation of sensor nodes with particular applications to take part in the network, which results in most of the uncovered simulation area, where fewer nodes are located at far distances. The drawback of such network would be that the additional energy is spent by the nodes located in a pattern of dense location, using more number of nodes for a smaller distance of communication adversely in a region with less number of nodes and additional energy is again spent by the source node in order to transmit a packet to neighbours, thereby transmitting the packet to reach the destination. The proposed work is intended to develop Energy Efficient Node Placement Algorithm (EENPA) in order to place the sensor node efficiently in simulated area, where all the nodes are equally located on a radial path to cover maximum area at equidistance. The total energy consumed by each node compared to random placement of nodes is less by having equal burden on fewer nodes of far location, having distributed the nodes in whole of the simulation area. Calculating the network lifetime also proves to be efficient as compared to random placement of nodes, hence increasing the network lifetime, too. Simulation is been carried out in a qualnet simulator, results are obtained on par with random placement of nodes with EENP algorithm.

Keywords: energy, WSN, wireless sensor network, energy approach

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Authors: Suraj Sam Issaka, Anita Asamoah, Abass Gibrilla, Joseph Richmond Fianko

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Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that can form in edible oils during repeated frying and accumulate in fried foods. This study assesses the chances of health risks (carcinogenic and non-carcinogenic) due to PAHs levels in popular finger foods (bean cakes, plantain chips, doughnuts) fried in edible oils (mixed vegetable, sunflower, soybean) from the Ghanaian market. Employing probabilistic health risk assessment that considers variability and uncertainty in exposure and risk estimates provides a more realistic representation of potential health risks. Monte Carlo simulations with 10,000 iterations were used to estimate carcinogenic, mutagenic, and non-carcinogenic risks for different age groups (A: 6-10 years, B: 11-20 years, C: 20-70 years), food types (bean cake, plantain chips, doughnut), oil types (soybean, mixed vegetable, sunflower), and re-usage frying oil frequencies (once, twice, thrice). Our results suggest that, for age Group A, doughnuts posed the highest probability of carcinogenic risk (91.55%) exceeding the acceptable threshold, followed by bean cakes (43.87%) and plantain chips (7.72%), as well as the highest probability of unacceptable mutagenic risk (89.2%), followed by bean cakes (40.32%). Among age Group B, doughnuts again had the highest probability of exceeding carcinogenic risk limits (51.16%) and mutagenic risk limits (44.27%). At the same time, plantain chips exhibited the highest maximum carcinogenic risk. For adults age Group C, bean cakes had the highest probability of unacceptable carcinogenic (50.88%) and mutagenic risks (46.44%), though plantain chips showed the highest maximum values for both carcinogenic and mutagenic risks in this age group. Also, on non-carcinogenic risks across different age groups, it was found that age Group A) who consumed doughnuts had a 68.16% probability of a hazard quotient (HQ) greater than 1, suggesting potential cognitive impairment and lower IQ scores due to early PAH exposure. This group also faced risks from consuming plantain chips and bean cake. For age Group B, the consumption of plantain chips was associated with a 36.98% probability of HQ greater than 1, indicating a potential risk of reduced lung function. In age Group C, the consumption of plantain chips was linked to a 35.70% probability of HQ greater than 1, suggesting a potential risk of cardiovascular diseases.

Keywords: PAHs, fried foods, carcinogenic risk, non-carcinogenic risk, Monte Carlo simulations

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Authors: Tsui-Tsai Lin

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Cooperative orthogonal frequency division multiplexing (OFDM) transmission, which possesses the advantages of better connectivity, expanded coverage, and resistance to frequency selective fading, has been a more powerful solution for the physical layer in wireless communications. However, such a hybrid scheme suffers from the carrier frequency offset (CFO) effects inherited from the OFDM-based systems, which lead to a significant degradation in performance. In addition, insertion of a cyclic prefix (CP) at each symbol block head for combating inter-symbol interference will lead to a reduction in spectral efficiency. The design on the CFO estimation for the cooperative OFDM system without CP is a suspended problem. This motivates us to develop a low complexity CFO estimator for the cooperative OFDM decode-and-forward (DF) communication system without CP over the multipath fading channel. Especially, using a block-type pilot, the CFO estimation is first derived in accordance with the least square criterion. A reliable performance can be obtained through an exhaustive two-dimensional (2D) search with a penalty of heavy computational complexity. As a remedy, an alternative solution realized with an iteration approach is proposed for the CFO estimation. In contrast to the 2D-search estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. Computer simulations have been presented to demonstrate the efficacy of the proposed CFO estimation.

Keywords: cooperative transmission, orthogonal frequency division multiplexing (OFDM), carrier frequency offset, iteration

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Authors: Dalvinder Kaur Mangal

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For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.

Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise

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Authors: Nana Saralidze, Nino Sharashenidze, Zurab Kevanishvili

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Hidden hearing loss may occur in humans exposed to prolonged high-level sound. It is the loss of ability to hear high-level background noise while having normal hearing in quiet. We compared the hearing of people who regularly listen 3 hours and more to personal music players and those who do not. Forty participants aged 18-30 years were divided into two groups: regular users of music players and people who had never used them. And the third group – elders aged 50-55 years, had 15 participants. Pure-tone audiometry (125-16000 Hz), auditory brainstem response (ABR) (70dB SPL), and ability to identify speech in noise (4-talker babble with a 65-dB signal-to-noise ratio at 80 dB) were measured in all participants. All participants had normal pure-tone audiometry (all thresholds < 25 dB HL). A significant difference between groups was observed in that regular users of personal audio systems correctly identified 53% of words, whereas the non-users identified 74% and the elder group – 63%. This contributes evidence supporting the presence of a hidden hearing loss in humans and demonstrates that speech-in-noise audiometry is an effective method and can be considered as the GOLD standard for detecting hidden hearing loss.

Keywords: mp3 player, hidden hearing loss, speech audiometry, pure tone audiometry

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Zatil Afifah Omar, Siti Nur Izati Azmi, Kathi Swaran, Navin Kumar

Abstract:

Lost circulation has always been one of the greatest problems faced by drilling companies during drilling operations due to excessive drilling Fluids losses. Loss of circulation leads to Huge cost and non-productive time. The objective of this study is to evaluate the sealing efficiency of a proprietary blend of synthetic rubber as loss circulation material in comparison with a conventional product such as calcium carbonate, graphite, cellulosic, and nutshells. Sand Bed Tester with a different proprietary blend of synthetic rubber compositions has been used to determine the effectiveness of the LCM in preventing drilling fluids losses in a lab scale. Test results show the proprietary blend of synthetic rubber have good bridging properties and sealing Off fractures of various sizes. The finish product is environmentally friendly with lower production lead time and lower production cost compared to current conventional loss circulation materials used in current drilling operations.

Keywords: loss circulation materials, drilling operation, sealing efficiency, LCM

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Authors: Babatunde Dosumu, Obuks Ejohwomu, Akilu Yunusa-Kaltungo

Abstract:

Cost estimation in construction is often difficult, particularly when dealing with risks and uncertainties, which are inevitable and peculiar to developing countries like Nigeria. Direct consequences of these are major deviations in cost, duration, and quality. The fundamental aim of this study is to develop a framework for assessing the impacts of risk on cost estimation, which in turn causes variabilities between contract sum and final account. This is very important, as initial estimates given to clients should reflect the certain magnitude of consistency and accuracy, which the client builds other planning-related activities upon, and also enhance the capabilities of construction industry professionals by enabling better prediction of the final account from the contract sum. In achieving this, a systematic literature review was conducted with cost variability and construction projects as search string within three databases: Scopus, Web of science, and Ebsco (Business source premium), which are further analyzed and gap(s) in knowledge or research discovered. From the extensive review, it was found that factors causing deviation between final accounts and contract sum ranged between 1 and 45. Besides, it was discovered that a cost estimation framework similar to Building Cost Information Services (BCIS) is unavailable in Nigeria, which is a major reason why initial estimates are very often inconsistent, leading to project delay, abandonment, or determination at the expense of the huge sum of money invested. It was concluded that the development of a cost estimation framework that is adjudged an important tool in risk shedding rather than risk-sharing in project risk management would be a panacea to cost estimation problems, leading to cost variability in the Nigerian construction industry by the time this ongoing Ph.D. research is completed. It was recommended that practitioners in the construction industry should always take into account risk in order to facilitate the rapid development of the construction industry in Nigeria, which should give stakeholders a more in-depth understanding of the estimation effectiveness and efficiency to be adopted by stakeholders in both the private and public sectors.

Keywords: cost variability, construction projects, future studies, Nigeria

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

Abstract:

Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Oscar Javier Herrera, Manuel Angel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: demand forecasting, empirical distribution, propagation of error, Bogota

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Authors: Zahra Esmaeily, Zahra Tajari, Shahrzad Daei, Mahshid Rezaei, Atefeh Eyvazkhani, Marjan Mansouri Dara, Ahmad Reza Dorosty Motlagh, Andriko Palmowski

Abstract:

Objective: Sarcopenia (SPA) is associated with frailty and disability in the elderly. Adherence to current dietary guidelines in addition to physical activity could play a role in the prevention of muscle wasting and weakness. The Healthy Eating Index-2015 (HEI) is a tool to assess diet quality as recommended in the U.S. Dietary Guidelines for Americans. This study aimed to investigate whether there is a relationship between HEI scores and the probability of SPA (PS) among the Tehran elderly. Method: A previously validated semi-quantitative food frequency questionnaire was used to assess HEI and the dietary intake of randomly selected elderly people living in Tehran, Iran. Handgrip strength (HGS) was measured to evaluate the PS. Statistical evaluation included descriptive analysis and standard test procedures. Result: 201 subjects were included. Those probably suffering from SPA (as determined by HGS) had significantly lower HEI scores (p = 0.02). After adjusting for confounders, HEI scores and HGS were still significantly associated (adjusted R2 = 0.56, slope β = 0.03, P = 0.09). Elderly people with a low probability of SPA consumed more monounsaturated and polyunsaturated fatty acids (P = 0.06) and ingested less added sugars and saturated fats (P = 0.01 and P = 0.02, respectively). Conclusion: In this cross-sectional study, HEI scores are associated with the probability of SPA. Adhering to current dietary guidelines might contribute to ameliorating muscle strength and mass in aging individuals.

Keywords: aging, HEI-2015, Iranian, sarcopenic

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