Search results for: stochastic subspace identification

Authors: Innocent Pangapanga-Phiri, Eric Dada Mungatana

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This study estimates the effect of climate-induced rural-urban migrants (RUM) on maize productivity. It uses panel data gathered by the National Statistics Office and the World Bank to understand the effect of RUM on the technical efficiency of maize production in rural Malawi. The study runs the two-stage Tobit regression to isolate the real effect of rural-urban migration on the technical efficiency of maize production. The results show that RUM significantly reduces the technical efficiency of maize production. However, the interaction of RUM and climate-smart agriculture has a positive and significant influence on the technical efficiency of maize production, suggesting the need for re-investing migrants’ remittances in agricultural activities.

Keywords: climate-smart agriculture, farm productivity, rural-urban migration, panel stochastic frontier models, two-stage Tobit regression

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Authors: Vivian Wu

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During the mating season, honeybee drones make mating fights to congregation areas where they face fierce competition to mate with a queen. Drones have developed distinct anatomical and functional features in order to optimize their chances of success. Flight activities of western honeybee (Apis mellifera) drones and foragers were monitored using radio frequency identification (RFID) to test if drones have also developed distinct flight behaviors. Drone flight durations showed a bimodal distribution dividing the flights into short flights and long flights while forager flight durations showed a left-skewed unimodal distribution. Interestingly, the short trips occurred prior to the long trips on a daily basis. The first trips of the day the drones made were primarily short trips, and the distribution significantly shifted to long trips as the drones made more trips. In contrast, forager trips showed no such shift of distribution. In addition, drones made short trips but no long mating trips on days associated with a significant drop in temperature and increase of clouds compared to the previous day. These findings suggest that drones may have developed a unique flight behavior making short trips first to survey the weather conditions before flying out to the congregation area to pursue a successful mating.

Keywords: apis mellifera, drone, flight behavior, weather, RFID

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Authors: Boukari Abdou Wakilou

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Benin is one of West Africa's major cotton-producing countries. Cotton is the country's main source of foreign currency and employment. But it is also one of the sources of soil degradation. The search for good agricultural practices is therefore, a constant preoccupation. The aim of this study is to measure the technical efficiency of cotton growers by comparing those who constantly grow cotton on the same land with those who practice crop rotation. The one-step estimation approach of the stochastic production frontier, including determinants of technical inefficiency, was applied to a stratified random sample of 261 cotton producers. Overall, the growers had a high average technical efficiency level of 90%. However, there was no significant difference in the level of technical efficiency between the two groups of growers studied. All the factors linked to compliance with the technical production itinerary had a positive influence on the growers' level of efficiency. It is, therefore, important to continue raising awareness of the importance of respecting the technical production itinerary and of integrated soil fertility management techniques.

Keywords: technical efficiency, soil fertility, cotton, crop rotation, benin

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Authors: Yeliz Karaca, Rana Karabudak

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Multifractal Denoising techniques are used in the identification of significant attributes by removing the noise of the dataset. Magnetic resonance (MR) image technique is the most sensitive method so as to identify chronic disorders of the nervous system such as Multiple Sclerosis. MRI and Expanded Disability Status Scale (EDSS) data belonging to 120 individuals who have one of the subgroups of MS (Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), Primary Progressive MS (PPMS)) as well as 19 healthy individuals in the control group have been used in this study. The study is comprised of the following stages: (i) L2 Norm Multifractal Denoising technique, one of the multifractal technique, has been used with the application on the MS data (MRI and EDSS). In this way, the new dataset has been obtained. (ii) The new MS dataset obtained from the MS dataset and L2 Multifractal Denoising technique has been applied to the K-Means and Fuzzy C Means clustering algorithms which are among the unsupervised methods. Thus, the clustering performances have been compared. (iii) In the identification of significant attributes in the MS dataset through the Multifractal denoising (L2 Norm) technique using K-Means and FCM algorithms on the MS subgroups and control group of healthy individuals, excellent performance outcome has been yielded. According to the clustering results based on the MS subgroups obtained in the study, successful clustering results have been obtained in the K-Means and FCM algorithms by applying the L2 norm of multifractal denoising technique for the MS dataset. Clustering performance has been more successful with the MS Dataset (L2_Norm MS Data Set) K-Means and FCM in which significant attributes are obtained by applying L2 Norm Denoising technique.

Keywords: clinical decision support, clustering algorithms, multiple sclerosis, multifractal techniques

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Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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Authors: Reni M. Sagayaraj, Anand Gnana S. Selvam, Reynald R. Susainathan

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In this paper, we consider stochastic queueing models for Steady-state behavior of a multi-phase M/M/1 queue in random evolution subject to catastrophe failure. The arrival flow of customers is described by a marked Markovian arrival process. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. This model contains a repair state, when a catastrophe occurs the system is transferred to the failure state. The paper focuses on the steady-state equation, and observes that, the steady-state behavior of the underlying queueing model along with the average queue size is analyzed.

Keywords: M/G/1 queuing system, multi-phase, random evolution, steady-state equation, catastrophe failure

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Pradeep Jawale, Sharad Supare, Sachin Kumar Jain, Nagesh Walke

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One can witness the constant development and redevelopment of cities throughout the world. Construction equipment vehicles (CEVs) are commonly used on the construction site. However, noise pollution from construction sites due to the use of CEV has become a major problem for many cities. The construction equipment employed, which includes excavators and bulldozers, is one of the main causes of these elevated noise levels. The construction workers possibly will face a potential risk to their auditory health and well-being due to the noise levels they are exposed to. Different countries have imposed exterior and operator noise limits for construction equipment vehicles, enabling them to control noise pollution from CEVs. In this study, the operator ear level noise of the identified vehicle is higher than the benchmark vehicle by 8 dB(A). It was a tough time for the NVH engineer to beat the interior noise level of the benchmark vehicle. Initially, the noise source identification technique was used to identify the dominant sources for increasing the interior noise of the test vehicle. It was observed that the transfer of structure-borne and air-borne noise to the cabin was the major issue with the vehicle. It was foremost required to address the issue without compromising the overall performance of the vehicle. Surprisingly, the steering pump and radiator fan were identified as the major dominant sources than typical conventional sources like powertrain, intake, and exhaust. Individual sources of noise were analyzed in detail, and optimizations were made to minimize the noise at the source. As a result, the significant noise reduction achieved inside the vehicle and the overall in-cab noise level for the vehicle became a new benchmark in the market.

Keywords: interior noise, noise reduction, CEV, noise source identification

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Authors: Sharat Chandra, Zilong Wang, Ru-Rong Ji, Andrey Bortsov

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Chronic pain (CP) therapeutic approaches have limited efficacy. As a result, doctors are prescribing opioids for chronic pain, leading to opioid overuse, abuse, and addiction epidemic. Therefore, the development of effective and safe CP drugs remains an unmet medical need. Voltage-gated sodium (Nav) channels act as cardiovascular and neurological disorder’s molecular targets. Nav channels selective inhibitors are hard to design because there are nine closely-related isoforms (Nav1.1-1.9) that share the protein sequence segments. We are targeting the Nav1.7 found in the peripheral nervous system and engaged in the perception of pain. The objective of this project was to screen a 1.5 million compound library for identification of inhibitors for Nav1.7 with analgesic effect. In this study, we designed a protocol for identification of isoform-selective inhibitors of Nav1.7, by utilizing the prior information on isoform-selective antagonists. First, a similarity search was performed; then the identified hits were docked into a binding site on the fourth voltage-sensor domain (VSD4) of Nav1.7. We used the FTrees tool for similarity searching and library generation; the generated library was docked in the VSD4 domain binding site using FlexX and compounds were shortlisted using a FlexX score and SeeSAR hyde scoring. Finally, the top 25 compounds were tested with molecular dynamics simulation (MDS). We reduced our list to 9 compounds based on the MDS root mean square deviation plot and obtained them from a vendor for in vitro and in vivo validation. Whole-cell patch-clamp recordings in HEK-293 cells and dorsal root ganglion neurons were conducted. We used patch pipettes to record transient Na⁺ currents. One of the compounds reduced the peak sodium currents in Nav1.7-HEK-293 stable cell line in a dose-dependent manner, with IC50 values at 0.74 µM. In summary, our computer-aided analgesic discovery approach allowed us to develop pre-clinical analgesic candidate with significant reduction of time and cost.

Keywords: chronic pain, voltage-gated sodium channel, isoform-selective antagonist, similarity search, virtual screening, analgesics development

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Authors: Ayesha S. Rahman, Khaled Haddad, Ataur Rahman

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At-site flood frequency analysis is used to estimate flood quantiles when at-site record length is reasonably long. In Australia, FLIKE software has been introduced for at-site flood frequency analysis. The advantage of FLIKE is that, for a given application, the user can compare a number of most commonly adopted probability distributions and parameter estimation methods relatively quickly using a windows interface. The new version of FLIKE has been incorporated with the multiple Grubbs and Beck test which can identify multiple numbers of potentially influential low flows. This paper presents a case study considering six catchments in eastern Australia which compares two outlier identification tests (original Grubbs and Beck test and multiple Grubbs and Beck test) and two commonly applied probability distributions (Generalized Extreme Value (GEV) and Log Pearson type 3 (LP3)) using FLIKE software. It has been found that the multiple Grubbs and Beck test when used with LP3 distribution provides more accurate flood quantile estimates than when LP3 distribution is used with the original Grubbs and Beck test. Between these two methods, the differences in flood quantile estimates have been found to be up to 61% for the six study catchments. It has also been found that GEV distribution (with L moments) and LP3 distribution with the multiple Grubbs and Beck test provide quite similar results in most of the cases; however, a difference up to 38% has been noted for flood quantiles for annual exceedance probability (AEP) of 1 in 100 for one catchment. These findings need to be confirmed with a greater number of stations across other Australian states.

Keywords: floods, FLIKE, probability distributions, flood frequency, outlier

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Authors: Tsung Chieh Ma, I-Ling Chen

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Disclosing family origins to adoptees is an important topic in the adoption process. Adoption agencies usually educate adoptive parents on how to disclose to adoptees, but many adoptive parents worry that the disclosure will affect the parent–child relationship. Thus, how adoptees would like to receive the disclosure and whether they subjectively feel that the parent–child relationship is affected are both topics worthy of further discussion. This research takes a qualitative approach and connects with adoption agencies to interview six adoptees who are now adults. The purpose of the interviews is to learn about their experience receiving disclosures and their subjective feelings after learning of their family origins. The aim is to reveal the changes disclosure brought to the parent–child relationship and whether common concerns are raised due to the adoptive status. We also want to know about factors that affect their identification with their adopted status so that we can consequently give advice to other adoptive families. in this study finds that adoptees see disclosure as a process rather than an isolated event. The majority want to be told their family origin as early and proactively as possible and expect to learn the reasons they were given up for adoption and taken in as adoptees. The disclosure does not necessarily influence the parent–child relationship, and adoptees care more about the positive experiences they had with adoptive parents in their childhood. Moreover, adopted children seek contact with their original family mostly to understand why they were given up for adoption. The effects of disclosure depend on how the adoptive parents or other significant people in the lives of adoptees interpret the identity of the adoptees. That is, their response and attitude toward the identity have a lasting impact on the adoptees. The study suggests that early disclosure gives adoptees a chance to internalize the experience in the process and find self-identification.

Keywords: adoption, adoptees, disclosure of family origins, parent–child relationship, self-identity

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Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

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Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

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Authors: Muhammad SAFDAR, Mehmet Ozaslan, Musarrat Abbas Khan

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Babesiosis is a haemoparasitic disease due to the multiplication of protozoan’s parasite, Babesia ovis in the red blood cells of the host, and contributes numerous economical losses, including sheep and goat ruminants. The early identification and successful treatment of Babesia Ovis spp. belong to the key steps of control and health management of livestock resources. The objective of this study was to construct a polymerase chain reaction (PCR) based method for the detection of Babesia spp. in small ruminants and to determine the risk factors involved in the spreading of babesiosis infections. A total of 100 blood samples were collected from 50 sheep and 50 goats along with different areas of Muzaffargarh, Pakistan, from randomly selected herds. Data on the characteristics of sheep and goats were collected through questionnaires. Of 100 blood samples examined, 18 were positive for Babesia ovis upon microscopic studies, whereas 11 were positive for the presence of Babesia spp. by PCR assay. For the recognition of parasitic DNA, a set of 500bp oligonucleotide was designed by PCR amplification with sequence 18S rRNA gene for B. ovis. The prevalence of babesiosis in small ruminant’s sheep and goat detected by PCR was significantly higher in female animals (28%) than male herds (08%). PCR analysis of the reference samples showed that the detection limit of the PCR assay was 0.01%. Taken together, all data indicated that this PCR assay was a simple, fast, specific detection method for Babesia ovis species in small ruminants compared to other available methods.

Keywords: Babesia ovis, PCR amplification, 18S rRNA, sheep and goat

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Authors: Nadezhda Kvatashidze, Elena Kharabadze

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It is broadly known that lease is a flexible means of funding enterprises. Lease reduces the risk related to access and possession of assets, as well as obtainment of funding. Therefore, it is important to refine lease accounting. The lease accounting regulations under the applicable standard (International Accounting Standards 17) make concealment of liabilities possible. As a result, the information users get inaccurate and incomprehensive information and have to resort to an additional assessment of the off-balance sheet lease liabilities. In order to address the problem, the International Financial Reporting Standards Board decided to change the approach to lease accounting. With the deficiencies of the applicable standard taken into account, the new standard (IFRS 16 ‘Leases’) aims at supplying appropriate and fair lease-related information to the users. Save certain exclusions; the lessee is obliged to recognize all the lease agreements in its financial report. The approach was determined by the fact that under the lease agreement, rights and obligations arise by way of assets and liabilities. Immediately upon conclusion of the lease agreement, the lessee takes an asset into its disposal and assumes the obligation to effect the lease-related payments in order to meet the recognition criteria defined by the Conceptual Framework for Financial Reporting. The payments are to be entered into the financial report. The new lease accounting standard secures supply of quality and comparable information to the financial information users. The International Accounting Standards Board and the US Financial Accounting Standards Board jointly developed IFRS 15: ‘Revenue from Contracts with Customers’. The standard allows the establishment of detailed revenue recognition practical criteria such as identification of the performance obligations in the contract, determination of the transaction price and its components, especially price variable considerations and other important components, as well as passage of control over the asset to the customer. IFRS 15: ‘Revenue from Contracts with Customers’ is very similar to the relevant US standards and includes requirements more specific and consistent than those of the standards in place. The new standard is going to change the recognition terms and techniques in the industries, such as construction, telecommunications (mobile and cable networks), licensing (media, science, franchising), real property, software etc.

Keywords: assessment of the lease assets and liabilities, contractual liability, division of contract, identification of contracts, contract price, lease identification, lease liabilities, off-balance sheet, transaction value

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Authors: Shefaa Mansour, Hassan Arafat, Shadi Hasan

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Management of reverse osmosis (RO) brine has become a major area of research due to the environmental concerns associated with it. This study worked on studying the feasibility of the direct contact membrane distillation (DCMD) system in the treatment of this RO brine. The system displayed great potential in terms of its flux and salt rejection, where different operating conditions such as the feed temperature, feed salinity, feed and permeate flow rates were varied. The highest flux of 16.7 LMH was reported with a salt rejection of 99.5%. Although the DCMD has displayed potential of enhanced water recovery from highly saline solutions, one of the major drawbacks associated with the operation is the fouling of the membranes which impairs the system performance. An operational run of 77 hours for the treatment of RO brine of 56,500 ppm salinity was performed in order to investigate the impact of fouling of the membrane on the overall operation of the system over long time operations. Over this time period, the flux was observed to have reduced by four times its initial flux. The fouled membrane was characterized through different techniques for the identification of the organic and inorganic foulants that have deposited on the membrane surface. The Infrared Spectroscopy method (IR) was used to identify the organic foulants where SEM images displayed the surface characteristics of the membrane. As for the inorganic foulants, they were identified using X-ray Diffraction (XRD), Ion Chromatography (IC) and Energy Dispersive Spectroscopy (EDS). The major foulants found on the surface of the membrane were inorganic salts such as sodium chloride and calcium sulfate.

Keywords: brine treatment, membrane distillation, fouling, characterization

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Authors: Ju-Hong Lee, Ding-Chen Chung

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This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

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Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: construction hazard, griddization computing, grid management, process

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Authors: Slimane Mokrani, Nabti El hafid

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Description of the subject: Currently, several efforts focus on the study of biodiversity, microbial biotechnology, and the use of ecological strategies. Objectives: The aim of this present work is to determine the functional diversity of bacteria in rhizospheric and non-rhizospheric soils of different plants. Methods: Bacteria were isolated from soil and identified based on physiological and biochemical characters and genotypic taxonomy performed by 16S rDNA and BOX-PCR. As well as the characterization of various PGPR traits. Then, they are tested for their effects on the stimulation of seed germination and the growth of Phaseolus vulgaris L. As well as their biological control activities with regard to the phytopathogenic bacterial isolate Xapf. Results and Discussion: The biochemical and physiological identification of 75 bacterial isolates made it possible to associate them with the two groups of fluorescent Pseudomonas (74.67%) and non-fluorescent Pseudomonas (25.33%). The identification by 16S rDNA of 27 strains made it possible to attribute the majority of the strains to the genus Pseudomonas (81.48%), Serratia (7.41%) and Bacillus (11.11%). The bacterial strains showed a high capacity to produce IAA, siderophores, HCN and to solubilize phosphate. A significant stimulation of germination and growth was observed by applying the Pseudomonas strains. Furthermore, significant reductions in the severity and intensity of the disease caused caused by Xapf were observed. Conclusion: The bacteria described in this present study endowed with different PGPR activities seem to be very promising for their uses as biological control agents and bio-fertilization.

Keywords: biofertilization, biological control, phaseolus vulgaris L, pseudomonas, Xanthomonas axonopodis pv. phaseoli var. fuscans and common blight

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Authors: A. Abbou, V. Makis, N. Salari

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We study the condition-based maintenance (CBM) problem of a system subject to stochastic deterioration. The system is composed of three units (or modules): (i) Module 1 deterioration follows a Markov process with two operational states and one failure state. The operational states are partially observable through periodic condition monitoring. (ii) Module 2 deterioration follows a Gamma process with a known failure threshold. The deterioration level of this module is fully observable through periodic inspections. (iii) Only the operating age information is available of Module 3. The lifetime of this module has a general distribution. A CBM policy prescribes when to initiate a maintenance intervention and which modules to repair during intervention. Our objective is to determine the optimal CBM policy minimizing the long-run expected average cost of operating the system. This is achieved by formulating a Markov decision process (MDP) and developing the value iteration algorithm for solving the MDP. We provide numerical examples illustrating the cost-effectiveness of the optimal CBM policy through a comparison with heuristic policies commonly found in the literature.

Keywords: reliability, maintenance optimization, Markov decision process, heuristics

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Authors: H. Mousavi, M. Sharifi, H. Pourvaziri

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Redundancy Allocation Problem (RAP) is a well-known mathematical problem for modeling series-parallel systems. It is a combinatorial optimization problem which focuses on determining an optimal assignment of components in a system design. In this paper, to be more practical, we have considered the problem of redundancy allocation of series system with interval valued reliability of components. Therefore, during the search process, the reliabilities of the components are considered as a stochastic variable with a lower and upper bounds. In order to optimize the problem, we proposed a simulated annealing based on cloud theory (CBSAA). Also, the Monte Carlo simulation (MCS) is embedded to the CBSAA to handle the random variable components’ reliability. This novel approach has been investigated by numerical examples and the experimental results have shown that the CBSAA combining MCS is an efficient tool to solve the RAP of systems with interval-valued component reliabilities.

Keywords: redundancy allocation problem, simulated annealing, cloud theory, monte carlo simulation

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Authors: Soudabeh Shemehsavar

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In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

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Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck, Jason Stanley, Leroy Whilby

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Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major threat to fruit and vegetable industries in the United States. The establishment of pest fruit fly in the agricultural industries and produce severe ecological and economic impacts on agricultural diversification and trade. Detection and identification of these agricultural pests in a timely manner will facilitate the possibility of eradication from newly invaded areas. Identification of larval stages to species level is difficult, but is required to determine pest loads and their pathways into the United States. The aim of this study is the New World genus, Anastrepha which includes pests of major economic importance. Mitochondrial cytochrome c oxidase I (COI) gene sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level. During phylogenetics analysis numerous nuclear mitochondrial pseudogenes (numts) were discovered in different specimens. The numts are nonfunctional copies of the mtDNA present in the nucleus and are easily coamplified with the mitochondrial COI gene copy by using conserved universal primers. This is problematic for DNA Barcoding, which attempts to characterize all living organisms by using the COI gene. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed.

Keywords: tephritid, Anastrepha fraterculus, COI, numts

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Authors: Seyed Reza Aghili, Tahereh Shokohi, Shirin Sadat Hashemi Fesharaki, Mohammad Ali Boroumand, Bahar Salmanian

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Introduction: Intravenous catheter-associated fungal infection as nosocomial infection continue to be a deep problem among hospitalized patients, decreasing quality of life and adding healthcare costs. The capacity of catheters in the spread of candidemia in heart failure patients is obvious. The aim of this study was to evaluate the prevalence and genetic identification of Candida species in heart disorder patients. Material and Methods: This study was conducted in Tehran Hospital of Cardiology Center (Tehran, Iran, 2014) during 1.5 years on the patients hospitalized for at least 7 days and who had central or peripheral vein catheter. Culture of catheters, blood and skin of the location of catheter insertion were applied for detecting Candida colonies in 223 patients. Identification of Candida species was made on the basis of a combination of various phenotypic methods and confirmed by sequencing the ITS1-5.8S-ITS2 region amplified from the genomic DNA using PCR and the NCBI BLAST. Results: Of the 223 patients samples tested, we identified totally 15 Candida isolates obtained from 9 (4.04%) catheter cultures, 3 (1.35%) blood cultures and 2 (0.90%) skin cultures of the catheter insertion areas. On the base of ITS region sequencing, out of nine Candida isolates from catheter, 5(55.6%) C. albicans, 2(22.2%) C. glabrata, 1(11.1%) C. membranifiaciens and 1 (11.1%) C. tropicalis were identified. Among three Candida isolates from blood culture, C. tropicalis, C. carpophila and C. membranifiaciens were identified. Non-candida yeast isolated from one blood culture was Cryptococcus albidus. One case of C. glabrata and one case of Candida albicans were isolated from skin culture of the catheter insertion areas in patients with positive catheter culture. In these patients, ITS region of rDNA sequence showed a similarity between Candida isolated from the skin and catheter. However, the blood samples of these patients were negative for fungal growth. We report two cases of catheter-related candidemia caused by C. membranifiaciens and C. tropicalis on the base of genetic similarity of species isolated from blood and catheter which were treated successfully with intravenous fluconazole and catheter removal. In phenotypic identification methods, we could only identify C. albicans and C. tropicalis and other yeast isolates were diagnosed as Candida sp. Discussion: Although more than 200 species of Candida have been identified, only a few cause diseases in humans. There is some evidence that non-albicans infections are increasing. Many risk factors, including prior antibiotic therapy, use of a central venous catheter, surgery, and parenteral nutrition are considered to be associated with candidemia in hospitalized heart failure patients. Identifying the route of infection in candidemia is difficult. Non-albicans candida as the cause of candidemia is increasing dramatically. By using conventional method, many non-albicans isolates remain unidentified. So, using more sensitive and specific molecular genetic sequencing to clarify the aspects of epidemiology of the unknown candida species infections is essential. The positive blood and catheter cultures for candida isolates and high percentage of similarity of their ITS region of rDNA sequence in these two patients confirmed the diagnosis of intravenous catheter-associated candidemia.

Keywords: catheter-associated infections, heart failure patient, molecular genetic sequencing, ITS region of rDNA, Candidemia

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Authors: Subham Kharel, Sudha Ravindranath, A. Vidya, B. Chandrasekaran, K. Ganesha Raj, T. Shesadri

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Digitization of urban features is a tedious and time-consuming process when done manually. In addition to this problem, Indian cities have complex habitat patterns and convoluted clustering patterns, which make it even more difficult to map features. This paper makes an attempt to classify urban objects in the satellite image using object-oriented classification techniques in which various classes such as vegetation, water bodies, buildings, and shadows adjacent to the buildings were mapped semi-automatically. Building layer obtained as a result of object-oriented classification along with already available building layers was used. The main focus, however, lay in the extraction of high-rise buildings using spatial technology, digital image processing, and modeling, which would otherwise be a very difficult task to carry out manually. Results indicated a considerable rise in the total number of buildings in the city. High-rise buildings were successfully mapped using satellite imagery, spatial technology along with logical reasoning and mathematical considerations. The results clearly depict the ability of Remote Sensing and GIS to solve complex problems in urban scenarios like studying urban sprawl and identification of more complex features in an urban area like high-rise buildings and multi-dwelling units. Object-Oriented Technique has been proven to be effective and has yielded an overall efficiency of 80 percent in the classification of high-rise buildings.

Keywords: object oriented classification, shadow extraction, high-rise buildings, satellite imagery, spatial technology

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Authors: Paul V. Thomas, Mostafa S. A. Elsayed, Denis Walch

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Airframe structural optimization at different design stages results in new mass and stiffness distributions which modify the critical design loads envelop. Determination of aircraft critical loads is an extensive analysis procedure which involves simulating the aircraft at thousands of load cases as defined in the certification requirements. It is computationally prohibitive to use a Global Finite Element Model (GFEM) for the load analysis, hence reduced order structural models are required which closely represent the dynamic characteristics of the GFEM. This paper presents the implementation of Component Mode Synthesis (CMS) method for the generation of high fidelity Reduced Order Model (ROM) of complex airframes. Here, sub-structuring technique is used to divide the complex higher order airframe dynamical system into a set of subsystems. Each subsystem is reduced to fewer degrees of freedom using matrix projection onto a carefully chosen reduced order basis subspace. The reduced structural matrices are assembled for all the subsystems through interface coupling and the dynamic response of the total system is solved. The CMS method is employed to develop the ROM of a Bombardier Aerospace business jet which is coupled with an aerodynamic model for dynamic aeroelasticity loads analysis under gust turbulence. Another set of dynamic aeroelastic loads is also generated employing a stick model of the same aircraft. Stick model is the reduced order modelling methodology commonly used in the aerospace industry based on stiffness generation by unitary loading application. The extracted aeroelastic loads from both models are compared against those generated employing the GFEM. Critical loads Modal participation factors and modal characteristics of the different ROMs are investigated and compared against those of the GFEM. Results obtained show that the ROM generated using Craig Bampton CMS reduction process has a superior dynamic characteristics compared to the stick model.

Keywords: component mode synthesis, craig bampton reduction method, dynamic aeroelasticity analysis, model order reduction

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Authors: Ju-Hong Lee, Ding-Chen Chung

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The paper deals with the optimal design of two-channel linear-phase (LP) quadrature mirror filter (QMF) banks using a metaheuristic based optimization technique. Based on the theory of two-channel QMF banks using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the group delay error of the designed QMF bank and the magnitude response error of the designed low-pass analysis filter. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a particle swarm optimization algorithm. The resulting two-channel QMF banks can possess approximately LP response without magnitude distortion. Simulation results are presented for illustration and comparison.

Keywords: quadrature mirror filter bank, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: Mochamad Beta Auditama, Yusuf Kurniawan

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A smartphone or tablet require a strong randomness to establish secure encrypted communication, encrypt files, etc. Therefore, random number generation is one of the main keys to provide secrecy. Android devices are equipped with hardware-based sensors, such as accelerometer, gyroscope, etc. Each of these sensors provides a stochastic process which has a potential to be used as an extra randomness source, in addition to /dev/random and /dev/urandom pseudorandom number generators. Android sensors can provide randomness automatically. To obtain randomness from Android sensors, each one of Android sensors shall be used to construct an entropy source. After all entropy sources are constructed, output from these entropy sources are combined to provide more entropy. Then, a deterministic process is used to produces a sequence of random bits from the combined output. All of these processes are done in accordance with NIST SP 800-22 and the series of NIST SP 800-90. The operation conditions are done 1) on Android user-space, and 2) the Android device is placed motionless on a desk.

Keywords: Android hardware-based sensor, deterministic process, entropy source, random number generation/generators

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Alina Svechkina, Boris A. Portnov

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In line with a rapid increase in pollution sources and enforcement of stricter air pollution regulation, which lowers pollution levels, it becomes more difficult to identify actual risk sources behind the observed morbidity patterns, and new approaches are required to identify potential risks and take preventive actions. In the present study, we discuss a probabilistic approach to the spatial identification of a priori unidentified environmental health hazards. The underlying assumption behind the tested approach is that the observed adverse health patterns (morbidity, mortality) can become a source of information on the geographic location of environmental risk factors that stand behind them. Using this approach, we analyzed sources of environmental exposure using data on mortality rates available for the year 2015 for NUTS 3 (Nomenclature of Territorial Units for Statistics) subdivisions of the European Union. We identified several areas in the southwestern part of Europe as primary risk sources for the observed mortality patterns. Multivariate regressions, controlled by geographical location, climate conditions, GDP (gross domestic product) per capita, dependency ratios, population density, and the level of road freight revealed that mortality rates decline as a function of distance from the identified hazard location. We recommend the proposed approach an exploratory analysis tool for initial investigation of regional patterns of population morbidity patterns and factors behind it.

Keywords: mortality, environmental hazards, air pollution, distance decay gradient, multi regression analysis, Europe, NUTS3

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Authors: Huixia Shi, Can Hu, Jun Zhu, Hongling Guo, Haiyan Li, Hongyan Du

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The identification of human body fluids during forensic investigations is a critical step to determine key details, and present strong evidence to testify criminal in a case. With the popularity of DNA and improved detection technology, the potential question must be revolved that whether the suspect’s DNA derived from saliva or semen, menstrual or peripheral blood, how to identify the red substance or aged blood traces on the spot is blood; How to determine who contribute the right one in mixed stains. In recent years, molecular approaches have been developing increasingly on mRNA, miRNA, DNA methylation and microbial markers, but appear expensive, time-consuming, and destructive disadvantages. Physicochemical methods are utilized frequently such us scanning electron microscopy/energy spectroscopy and X-ray fluorescence and so on, but results only showing one or two characteristics of body fluid itself and that out of working in unknown or mixed body fluid stains. This paper focuses on using chemistry methods Raman spectroscopy and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to discriminate species of peripheral blood, menstrual blood, semen, saliva, vaginal secretions, urine or sweat. Firstly, non-destructive, confirmatory, convenient and fast Raman spectroscopy method combined with more accurate matrix-assisted laser desorption/ionization time-of-flight mass spectrometry method can totally distinguish one from other body fluids. Secondly, 11 spectral signatures and specific metabolic molecules have been obtained by analysis results after 70 samples detected. Thirdly, Raman results showed peripheral and menstrual blood, saliva and vaginal have highly similar spectroscopic features. Advanced statistical analysis of the multiple Raman spectra must be requested to classify one to another. On the other hand, it seems that the lactic acid can differentiate peripheral and menstrual blood detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, but that is not a specific metabolic molecule, more sensitivity ones will be analyzed in a forward study. These results demonstrate the great potential of the developed chemistry methods for forensic applications, although more work is needed for method validation.

Keywords: body fluids, identification, Raman spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

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