Search results for: real-coded genetic algorithm

Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

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Authors: Adel Bessadok

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The theory of values postulates that each human has a set of values, or attractive and trans-situational goals, that drive their actions. The Basic Human Values as an incentive construct that apprehends human's values have been shown to govern a wide range of human behaviors. Individuals within and within societies have very different value preferences that reflect their enculturation, their personal experiences, their social places and their genetic heritage. Using a focus group composed by Islamic religious Preachers and a sample of 800 young students; this ongoing study will establish Moderate Islamic Values parameters. We analyze later, for the same students sample the difference between Moderate Islamic Values and Schwartz’s Basic Human Values. Keywords—Moderate Islamic Values, Basic Human Values, Exploratory Factor Analysis and Confirmatory Factor Analysis.

Keywords: moderate Islamic values, basic human values, exploratory factor analysis, confirmatory factor analysis

Procedia PDF Downloads 385

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

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

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

Procedia PDF Downloads 588

Authors: Murray David Schane

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Though years of clinical encounters with patients with autism spectrum disorders and those with a schizoid personality the many defining diagnostic features shared between these conditions have been explored and current neurobiological differences have been reviewed; and, critical and different treatment strategies for each have been devised. The paper compares and contrasts the apparent similarities between autism spectrum disorders and the schizoid personality are found in these DSM descriptive categories: restricted range of social-emotional reciprocity; poor non-verbal communicative behavior in social interactions; difficulty developing and maintaining relationships; detachment from social relationships; lack of the desire for or enjoyment of close relationships; and preference for solitary activities. In this paper autism, fundamentally a communicative disorder, is revealed to present clinically as a pervasive aversive response to efforts to engage with or be engaged by others. Autists with the Asperger presentation typically have language but have difficulty understanding humor, irony, sarcasm, metaphoric speech, and even narratives about social relationships. They also tend to seek sameness, possibly to avoid problems of social interpretation. Repetitive behaviors engage many autists as a screen against ambient noise, social activity, and challenging interactions. Also in this paper, the schizoid personality is revealed as a pattern of social avoidance, self-sufficiency and apparent indifference to others as a complex psychological defense against a deep, long-abiding fear of appropriation and perverse manipulation. Neither genetic nor MRI studies have yet located the explanatory data that identifies the cause or the neurobiology of autism. Similarly, studies of the schizoid have yet to group that condition with those found in schizophrenia. Through presentations of clinical examples, the treatment of autists of the Asperger type is revealed to address the autist’s extreme social aversion which also precludes the experience of empathy. Autists will be revealed as forming social attachments but without the capacity to interact with mutual concern. Empathy will be shown be teachable and, as social avoidance relents, understanding of the meaning and signs of empathic needs that autists can recognize and acknowledge. Treatment of schizoids will be shown to revolve around joining empathically with the schizoid’s apprehensions about interpersonal, interactive proximity. Models of both autism and schizoid personality traits have yet to be replicated in animals, thereby eliminating the role of translational research in providing the kind of clues to behavioral patterns that can be related to genetic, epigenetic and neurobiological measures. But as these clinical examples will attest, treatment strategies have significant impact.

Keywords: autism spectrum, schizoid personality traits, neurobiological implications, critical diagnostic distinctions

Procedia PDF Downloads 116

Authors: Adamu Usman, Grace Stanley Balami

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Pearl millet (Pennisetum glaucum L. R. Br.) is a cereal cultivated in arid and semi-arid areas of the world. It supports more than 100 million people around the world. Parasitic weed (Striga hermonthica Del. Benth) is a major constraint to its production. Estimated yield losses are put at 10 - 95% depending on variety, ecology and cultural practices. Potentials in selection of traits in pearl millets for grain yield have been reported and it depends on genotypic variability and heritability among landraces. Variability and heritability among cultivars could offer opportunities for improvement. The study was conducted to determine the genetic variability among cultivars and estimate broad sense heritability among grain yield and related traits. F1 breeding populations were generated with 9 parental cultivars, viz; Ex-Gubio, Ex-Monguno, Ex-Baga as males and PEO 5984, Super-SOSAT, SOSAT-C88, Ex-Borno and LCIC9702 as females through Line × Tester mating during 2017 dry season at Lushi Irrigation Station, Bauchi Metropolitan in Bauchi State, Nigeria. The F1 population and the parents were evaluated during cropping season of 2018 at Bauchi and Maiduguri. Data collected were subjected to analysis of variance. Results showed significant difference among cultivars and among traits indicating variability. Number of plants at emergence, days to 50% flowering, days to 100% flowering, plant height, panicle length, number of plants at harvest, Striga count at 90 days after sowing, panicle weight and grain yield were significantly different. Significant variability offer opportunity for improvement as superior individuals can be isolated. Genotypic variance estimates of traits were largely greater than environmental variances except in plant height and 1000 seed weight. Environmental variances were low and in some cases negligible. The phenotypic variances of all traits were higher than genotypic variances. Similarly phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV). High heritability was found in days to 50% flowering (90.27%), Striga count at 90 days after sowing (90.07%), number of plants at harvest (87.97%), days to 100% flowering (83.89%), number of plants at emergence (82.19%) and plant height (73.18%). Greater heritability estimates could be due to presence of additive gene. The result revealed wider variability among genotypes and traits. Traits having high heritability could easily respond to selection. High value of GCV, PCV and heritability estimates indicate that selection for these traits are possible and could be effective.

Keywords: variability, heritability, phenotypic, genotypic, striga

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Authors: Tanvi Rajesh Sanghavi

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Introduction: Neurodiversity is a concept which captures the different ways in which everyone's brain functions and is considered as part of normal variation. It is a strength-based approach which focuses on the individual's strengths and capabilities and believes in providing support wherever necessary. In many parts of the world, those diagnosed with autism spectrum disorder have been ostracized and ridiculed due to their sensory and communication differences. Hence, it becomes important for the teachers to have knowledge about autism and understand the needs of children with Autism. Need: India is rich in terms of culture, languages and religious diversity. It is important to study neurodiversity in such a population for better understanding of neurodiverse individuals and appropriate intervention. Aim & objectives: This study seeks teachers' knowledge of the causes, traits and educational requirements of children with autism spectrum disorder (ASD). It also aims to find out whether mainstream schools actually provide training programs to the teachers to manage such children along with the necessary accommodations. Method: The current study was a cross-sectional study conducted among school teachers. A total of 30 school teachers were taken for the study. The participants were enrolled after informed consent. The participants were directed to a google form consisting of objective questions. The first part of the questionnaire elicited information about school, teaching experience, qualification, etc. There were specific questions extracting details on attending/conducting sensitization and professional programs in regard to care for autistic children. The second part of the questionnaire consisted of some basic questions on the teacher’s understanding of diagnosis, traits, causes, road to recovery and understanding the educational and communication needs of autistic children from the teacher’s perspective. The responses were tabulated and analyzed descriptively. Results: Most of the teachers had 5–10 years of teaching experience. The majority of the teachers used the term “special child” for autistic children. Around 54.8% (17 teachers) of the total teachers felt that the parents of autistic children should teach their child to learn adaptive skills and 41.9% of the teachers felt that they should take medical intervention. About 50% of the teachers felt that the cause of autism is related to pre-natal maternal factors and about 40% felt that its cause is genetic. Only a small percentage of teachers felt that they were trained to manage the children with autism. More than 50% of the teachers mentioned that their schools do not conduct training programs for managing these children. Discussion & Conclusion: In this study, the knowledge and perspectives of teachers on children with ASD were studied. The most widely held contemporary belief is that genetic factors play a major part in the development of ASD, although the existing evidence is muddled, with numerous opposing perspectives on the nature of this mechanism. It is worth noting that any culture's level of humanity is mirrored in how that society "treats" its vulnerable population.

Keywords: autism, neurodiversity, awareness, education

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Authors: Sanjin Kršćanski, Josip Brnić

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Virtual Crack Closure Technique (VCCT) is a method used for calculating stress intensity factor (SIF) of a cracked body that is easily implemented on top of basic finite element (FE) codes and as such can be applied on the various component geometries. It is a relatively simple method that does not require any special finite elements to be used and is usually used for calculating stress intensity factors at the crack tip for components made of brittle materials. This paper studies applicability and accuracy of VCCT applied on standard metal specimens containing trough thickness crack, subjected to an in-plane bending load. Finite element analyses were performed using regular 4-node, regular 8-node and a modified quarter-point 8-node 2D elements. Stress intensity factor was calculated from the FE model results for a given crack length, using data available from FE analysis and a custom programmed algorithm based on virtual crack closure technique. Influence of the finite element size on the accuracy of calculated SIF was also studied. The final part of this paper includes a comparison of calculated stress intensity factors with results obtained from analytical expressions found in available literature and in ASTM standard. Results calculated by this algorithm based on VCCT were found to be in good correlation with results obtained with mentioned analytical expressions.

Keywords: VCCT, stress intensity factor, finite element analysis, 2D finite elements, bending

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Authors: Dali Gaganidze, Ekaterine Abashidze

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Potato is one of the main agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. In traditional potato growing regions (Svaneti, Samckhet javaheti and Tsalka), the yield is higher than 30-35 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (PCN) are harmful around the world. Yield losses caused by PCN are estimated up to 30%. Rout surveys conducted in two geographically distinct regions of Georgia producing potatoes - Samtskhe - Javakheti and Svaneti revealed potato cyst nematode Globodera rostochiensi. The aim of the study was the Phylogenetic analyses of Globodera rostochiensi revealed in Georgia by the amplification and sequencing of 28S gen in the D3 region and intergenic ITS1-15.8S-ITS2 region. Identification of all the samples from the two Globodera populations (Samtskhe - Javakheti and Svaneti), i.e., G. rostochiensis (20 isolates) were confirmed by conventional multiplex PCR with ITS 5 universal and PITSp4, PITSr3 specific primers of the cyst nematodes’ (G. pallida, G. rostochiensis). The size of PCR fragment 434 bp confirms that PCN samples from two populations, Samtskhe- Javakheti and Svaneti, belong to G. rostochiensi . The ITS1–5.8S-ITS2 regions were amplified using prime pairs: rDNA1 ( 5’ -TTGATTACGTCCCTGCCCTTT-3’ and rDNA2( 5’ TTTCACTCGCCGTTACTAAGG-3’), D3 expansion regions were amplified using primer pairs: D3A (5’ GACCCCTCTTGAAACACGGA-3’) and D3B (5’-TCGGAAGGAACCAGCTACTA-3’. PCR products of each region were cleaned up and sequenced using an ABI 3500xL Genetic Analyzer. Obtained sequencing results were analyzed by computer program BLASTN (https://blast.ncbi.nlm.nih.gov/Blast.cg). Phylogenetic analyses to resolve the relationships between the isolates were conducted in MEGA7 using both distance- and character-based methods. Based on analysis of G.rostochiensis isolate`s D3 expansion regions are grouped in three major clades (A, B and C) on the phylogenetic tree. Clade A is divided into three subclades; clade C is divided into two subclades. Isolates from the Samtckhet-javakheti population are in subclade 1 of clade A and isolates in subclade 1 of clade C. Isolates) from Svaneti populations are in subclade 2 of clade A and in clad B. In Clade C, subclade two is presented by three isolates from Svaneti and by one isolate (GL17) from Samckhet-Javakheti. . Based on analysis of G.rostochiensis isolate`s ITS1–5.8S-ITS2 regions are grouped in two main clades, the first contained 20 Georgian isolates of Globodera rostochiensis from Svaneti . The second clade contained 15 isolates of Globodera rostochiensis from Samckhet javakheti. Our investigation showed of high genetic variation of D3 and ITS1–5.8S-ITS2 region of rDNA of the isolates of G. rostochiensis from different geographic origins (Svameti, Samckhet-Javakheti) of Georgia. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia : Project # FR17_235

Keywords: globodera rostochiensi, PCR, phylogenetic tree, sequencing

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Authors: Xu Jie

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As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decisionmaking problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security). By modeling the multi-job collaborative cryptographic service scheduling problem as a multiobjective optimized job flow scheduling problem, and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing, and effectively solves the problem of complex resource scheduling in cryptographic services.

Keywords: multi-agent reinforcement learning, non-stationary dynamics, multi-agent systems, cooperative and competitive agents

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Authors: Baye Berihun Getahun, Mulugeta Atnaf Tiruneh, Richard G. F. Visser

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Resource-poor farmers practice low-input farming systems, and yet, most breeding programs give less attention to this huge farming system, which serves as a source of food and income for several people in developing countries. The high-input conventional breeding system appears to have failed to adequately meet the needs and requirements of 'difficult' environments operating under this system. Moreover, the unavailability of resources for crop production is getting for their peaks, the environment is maltreated by excessive use of agrochemicals, crop productivity reaches its plateau stage, particularly in the developed nations, the world population is increasing, and food shortage sustained to persist for poor societies. In various parts of the world, genetic gain at the farmers' level remains low which could be associated with low adoption of crop varieties, which have been developed under high input systems. Farmers usually use their local varieties and apply minimum inputs as a risk-avoiding and cost-minimizing strategy. This evidence indicates that the conventional high-input plant breeding system has failed to feed the world population, and the world is moving further away from the United Nations' goals of ending hunger, food insecurity, and malnutrition. In this review, we discussed the rationality of focused breeding programs for low-input farming systems and, the technical aspect of crop breeding that accommodates future food needs and its significance for developing countries in the decreasing scenario of resources required for crop production. To this end, the application of exotic introgression techniques like polyploidization, pan-genomics, comparative genomics, and De novo domestication as a pre-breeding technique has been discussed in the review to exploit the untapped genetic diversity of the crop wild relatives (CWRs). Desired recombinants developed at the pre-breeding stage are exploited through appropriate breeding approaches such as evolutionary plant breeding (EPB), rhizosphere-related traits breeding, and participatory plant breeding approaches. Populations advanced through evolutionary breeding like composite cross populations (CCPs) and rhizosphere-associated traits breeding approach that provides opportunities for improving abiotic and biotic soil stress, nutrient acquisition capacity, and crop microbe interaction in improved varieties have been reviewed. Overall, we conclude that low input farming system is a huge farming system that requires distinctive breeding approaches, and the exotic pre-breeding introgression techniques and the appropriate breeding approaches which deploy the skills and knowledge of both breeders and farmers are vital to develop heterogeneous landrace populations, which are effective for farmers practicing low input farming across the world.

Keywords: low input farming, evolutionary plant breeding, composite cross population, participatory plant breeding

Procedia PDF Downloads 58

Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

Procedia PDF Downloads 139

Authors: Jianfeng Hu

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Personal authentication based on electroencephalography (EEG) signals is one of the important field for the biometric technology. More and more researchers have used EEG signals as data source for biometric. However, there are some disadvantages for biometrics based on EEG signals. The proposed method employs entropy measures for feature extraction from EEG signals. Four type of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE) and spectral entropy (PE), were deployed as feature set. In a silhouettes calculation, the distance from each data point in a cluster to all another point within the same cluster and to all other data points in the closest cluster are determined. Thus silhouettes provide a measure of how well a data point was classified when it was assigned to a cluster and the separation between them. This feature renders silhouettes potentially well suited for assessing cluster quality in personal authentication methods. In this study, “silhouettes scores” was used for assessing the cluster quality of k-means clustering algorithm is well suited for comparing the performance of each EEG dataset. The main goals of this study are: (1) to represent each target as a tuple of multiple feature sets, (2) to assign a suitable measure to each feature set, (3) to combine different feature sets, (4) to determine the optimal feature weighting. Using precision/recall evaluations, the effectiveness of feature weighting in clustering was analyzed. EEG data from 22 subjects were collected. Results showed that: (1) It is possible to use fewer electrodes (3-4) for personal authentication. (2) There was the difference between each electrode for personal authentication (p<0.01). (3) There is no significant difference for authentication performance among feature sets (except feature PE). Conclusion: The combination of k-means clustering algorithm and silhouette approach proved to be an accurate method for personal authentication based on EEG signals.

Keywords: personal authentication, K-mean clustering, electroencephalogram, EEG, silhouettes

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Authors: Ayse Ozge Demir, Nihat Mert

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In this research, Kilis and Honamli goats are used, which are specific local genetic resources of Turkey. The herds were independent, but they had similar care and nutrition circumstances. From each breed 30 samples were taken, in all 120 samples were collected. Erytrocyte, all blood and serum samples were used for hemoglobine (Hb), glutathione (GSH) and Tf with Cp analysis, respectively. In the analysis of this samples, Hb and Tf bands were determined by electrophoresis. However, Cp and GSH levels were analyzed by the spectrophotometer. Three Hb phenotypes (AA, BB, AB) and Six Tf phenotypes (AA, AB, AC, BB, BC, CC) were determined in this study. In addition, both the observed and the expected values of polymorphic characteristic for 2 characters were presented according to the Hardy-Weinberg Equilibrium (HWE). Cp levels were detected as 0.822 ± 0.055 mg/dl and 1.793 ± 0.109 mg/dl in Kilis and Honamli herds, respectively. GSH levels were detected as, 42,486 ± 1,034 mg/dl and 33.515 ± 0.345 mg/dl in these breeds, respectively,. On the other hand, the high and low GSH levels (GSHH and GSHh) of herds were presented.

Keywords: electrophoresis, gene resource, goat, spectrophotometer

Procedia PDF Downloads 347

Authors: Yanping Liao, Congcong He, Ruigang Zhao

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The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

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Authors: Leonard Lipovich, Pattaraporn Thepsuwan, Anton-Scott Goustin, Juan Cai, Donghong Ju, James B. Brown

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Two-thirds of human genes do not encode any known proteins. Aside from long non-coding RNA (lncRNA) genes with recently-discovered functions, the ~40,000 non-protein-coding human genes remain poorly understood, and a role for their transcripts as de-facto unconventional messenger RNAs has not been formally excluded. Ribosome profiling (Riboseq) predicts translational potential, but without independent evidence of proteins from lncRNA open reading frames (ORFs), ribosome binding of lncRNAs does not prove translation. Previously, we mass-spectrometrically documented translation of specific lncRNAs in human K562 and GM12878 cells. We now examined lncRNA translation in human MCF7 cells, integrating strand-specific Illumina RNAseq, Riboseq, and deep mass spectrometry in biological quadruplicates performed at two core facilities (BGI, China; City of Hope, USA). We excluded known-protein matches. UCSC Genome Browser-assisted manual annotation of imperfect (tryptic-digest-peptides)-to-(lncRNA-three-frame-translations) alignments revealed three peptides hypothetically explicable by 'stop-to-nonstop' in-frame replacement of stop codons by amino acids in two ORFs of the lncRNA MMP24-AS1. To search for this phenomenon genomewide, we designed and implemented a novel pipeline, matching tryptic-digest spectra to wildcard-instead-of-stop versions of repeat-masked, six-frame, whole-genome translations. Along with singleton putative stop-to-nonstop events affecting four other lncRNAs, we identified 24 additional peptides with stop-to-nonstop in-frame substitutions from multiple positive-strand MMP24-AS1 ORFs. Only UAG and UGA, never UAA, stop codons were impacted. All MMP24-AS1-matching spectra met the same significance thresholds as high-confidence known-protein signatures. Targeted resequencing of MMP24-AS1 genomic DNA and cDNA from the same samples did not reveal any mutations, polymorphisms, or sequencing-detectable RNA editing. This unprecedented apparent gene-specific violation of the genetic code highlights the importance of matching peptides to whole-genome, not known-genes-only, ORFs in mass-spectrometry workflows, and suggests a new mechanism enhancing the combinatorial complexity of the proteome. Funding: NIH Director’s New Innovator Award 1DP2-CA196375 to LL.

Keywords: genetic code, lncRNA, long non-coding RNA, mass spectrometry, proteogenomics, ribo-seq, ribosome, RNAseq

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Authors: Natalia Buderatskaya, Igor Ilyin, Julia Gontar, Sergey Lavrynenko, Olga Parnitskaya, Ekaterina Ilyina, Eduard Kapustin, Yana Lakhno

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Introduction: It is known that cryopreservation of oocytes has peculiar features due to the complex structure of the oocyte. One of the most important features is that mature oocytes contain meiotic division spindle which is very sensitive even to the slightest variation in temperature. Thus, the main objective of this study is to analyse the resulting euploid embryos obtained from thawed oocytes in comparison with the data of preimplantation genetic screening (PGS) in fresh embryo cycles. Material and Methods: The study was conducted at 'Medical Centre IGR' from January to July 2016. Data were analysed for 908 donor oocytes obtained in 67 cycles of assisted reproductive technologies (ART), of which 693 oocytes were used in the 51 'fresh' cycles (group A), and 215 oocytes - 16 ART programs with vitrification female gametes (group B). The average age of donors in the groups match 27.3±2.9 and 27.8±6.6 years. Stimulation of superovulation was conducted the standard way. Vitrification was performed in 1-2 hours after transvaginal puncture and thawing of oocytes were carried out in accordance with the standard protocol of Cryotech (Japan). Manipulation ICSI was performed 4-5 hours after transvaginal follicle puncture for fresh oocytes, or after defrosting - for vitrified female gametes. For the PGS, an embryonic biopsy was done on the third or on the fifth day after fertilization. Diagnostic procedures were performed using fluorescence in situ hybridization with the study of such chromosomes as 13, 16, 18, 21, 22, X, Y. Only morphologically quality blastocysts were used for the transfer, the estimation of which corresponded to the Gardner criteria. The statistical hypotheses were done using the criteria t, x^2 at a significance levels p<0.05, p<0.01, p<0.001. Results: The mean number of mature oocytes per cycle in group A was 13.58±6.65 and in group B - 13.44±6.68 oocytes for patient. The survival of oocytes after thawing totaled 95.3% (n=205), which indicates a highly effective quality of performed vitrification. The proportion of zygotes in the group A corresponded to 91.1%(n=631), in the group B – 80.5%(n=165), which shows statistically significant difference between the groups (p<0.001) and explained by non-viable oocytes elimination after vitrification. This is confirmed by the fact that on the fifth day of embryos development a statistically significant difference in the number of blastocysts was absent (p>0.05), and constituted respectively 61.6%(n=389) and 63.0%(n=104) in the groups. For the PGS performing 250 embryos analyzed in the group A and 72 embryos - in the group B. The results showed that euploidy in the studied chromosomes were 40.0%(n=100) embryos in the group A and 41.7% (n=30) - in the group B, which shows no statistical significant difference (p>0.05). The indicators of clinical pregnancies in the groups amounted to 64.7% (22 pregnancies per 34 embryo transfers) and 61.5% (8 pregnancies per 13 embryo transfers) respectively, and also had no significant difference between the groups (p>0.05). Conclusions: The results showed that the vitrification does not affect the resulting euploid embryos in assisted reproductive technologies and are not reflected in their morphological characteristics in ART programs.

Keywords: euploid embryos, preimplantation genetic screening, thawing oocytes, vitrification

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

Procedia PDF Downloads 157

Authors: Nina Penkova, Kalin Krumov, Liliana Zashcova, Ivan Kassabov

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The insulating glass units (IGU) are widely used in the advanced and renovated buildings in order to reduce the energy for heating and cooling. Rules for the choice of IGU to ensure energy efficiency and thermal comfort in the indoor space are well known. The existing of internal loads - gage or vacuum pressure in the hermetized gas space, requires additional attention at the design of the facades. The internal loads appear at variations of the altitude, meteorological pressure and gas temperature according to the same at the process of sealing. The gas temperature depends on the presence of coatings, coating position in the transparent multi-layer system, IGU geometry and space orientation, its fixing on the facades and varies with the climate conditions. An algorithm for modeling and numerical simulation of thermal fields and internal pressure in the gas cavity at insulating glass units as function of the meteorological conditions is developed. It includes models of the radiation heat transfer in solar and infrared wave length, indoor and outdoor convection heat transfer and free convection in the hermetized gas space, assuming the gas as compressible. The algorithm allows prediction of temperature and pressure stratification in the gas domain of the IGU at different fixing system. The models are validated by comparison of the numerical results with experimental data obtained by Hot-box testing. Numerical calculations and estimation of 3D temperature, fluid flow fields, thermal performances and internal loads at IGU in window system are implemented.

Keywords: insulating glass units, thermal loads, internal pressure, CFD analysis

Procedia PDF Downloads 276

Authors: Benito Minjarez, Jesse Haramati, Yury Rodriguez-Yanez, Florencio Recendiz-Hurtado, Juan-Pedro Luna-Arias, Salvador Mena-Munguia

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During the last decades, the world has experienced a rapid industrialization and an expanding economy favoring a demographic boom. As a consequence, countries around the world have focused on developing new strategies related to the production of different farm products in order to meet future demands. Consequently, different strategies have been developed seeking to improve the major food products for both humans and livestock. Corn, after wheat and rice, is the third most important crop globally and is the primary food source for both humans and livestock in many regions around the globe. In addition, maize (Zea mays) is an important source of protein accounting for up to 60% of the daily human protein supply. Generally, many of the cereal grains have proteins with relatively low nutritional value, when they are compared with proteins from meat. In the case of corn, much of the protein is found in the endosperm (75 to 85%) and is deficient in two essential amino acids, lysine, and tryptophan. This deficiency results in an imbalance of amino acids and low protein content; normal maize varieties have less than half of the recommended amino acids for human nutrition. In addition, studies have shown that this deficiency has been associated with symptoms of growth impairment, anemia, hypoproteinemia, and fatty liver. Due to the fact that most of the presently available maize varieties do not contain the quality and quantity of proteins necessary for a balanced diet, different countries have focused on the research of quality protein maize (QPM). Researchers have characterized QPM noting that these varieties may contain between 70 to 100% more residues of the amino acids essential for animal and human nutrition, lysine, and tryptophan, than common corn. Several countries in Africa, Latin America, as well as China, have incorporated QPM in their agricultural development plan. Large parts of these countries have chosen a specific QPM variety based on their local needs and climate. Reviews have described the breeding methods of maize and have revealed the lack of studies on genetic and proteomic diversity of proteins in QPM varieties, and their genetic relationships with normal maize varieties. Therefore, molecular marker identification using tools such as mass spectrometry may accelerate the selection of plants that carry the desired proteins with high lysine and tryptophan concentration. To date, QPM maize lines have played a very important role in alleviating the malnutrition, and better characterization of these lines would provide a valuable nutritional enhancement for use in the resource-poor regions of the world. Thus, the objectives of this study were to identify proteins in QPM maize in comparison with a common maize line as a control.

Keywords: corn, mass spectrometry, QPM, tryptophan

Procedia PDF Downloads 293

Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

Procedia PDF Downloads 103

Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

Procedia PDF Downloads 405

Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

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Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

Procedia PDF Downloads 149

Authors: A. K. Borah, A. K. Singh

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In this paper we deal building blocks of the computer simulation of the multiphase flows. Whole simulation procedure can be viewed as two super procedures; The implementation of VOF method and the solution of Navier Stoke’s Equation. Moreover, a sequential code for a Navier Stoke’s solver has been studied.

Keywords: Bi-conjugate gradient stabilized (Bi-CGSTAB), ILUT function, krylov subspace, multifluid flows preconditioner, simple algorithm

Procedia PDF Downloads 530

Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

Procedia PDF Downloads 289

Authors: Shafait Hussain Ali

Abstract:

Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

Procedia PDF Downloads 108

Authors: Mubashir Hussain, Mu Lv, Xiaohan Dong, Zhiyang Li, Bin Liu, Nongyue He

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Detection and classification of microbes have a vast range of applications in biomedical engineering especially in detection, characterization, and quantification of bacterial contaminants. For identification of pathogens, different techniques are emerging in the field of biomedical engineering. Latest technology uses light scattering, capable of identifying different pathogens without any need for biochemical processing. Bacterial Pathogens Identification System (BPIS) which uses a laser beam, passes through the sample and light scatters off. An assembly of photodetectors surrounded by the sample at different angles to detect the scattering of light. The algorithm of the system consists of two parts: (a) Library files, and (b) Comparator. Library files contain data of known species of bacterial microbes in the form of binned plots, while comparator compares data of unknown sample with library files. Using collected data of unknown bacterial species, highest voltage values stored in the form of peaks and arranged in 3D histograms to find the frequency of occurrence. Resulting data compared with library files of known bacterial species. If sample data matching with any library file of known bacterial species, sample identified as a matched microbe. An experiment performed to identify three different bacteria particles: Enterococcus faecalis, Pseudomonas aeruginosa, and Escherichia coli. By applying algorithm using library files of given samples, results were compromising. This system is potentially applicable to several biomedical areas, especially those related to cell morphology.

Keywords: microbial identification, laser scattering, peak identification, binned plots classification

Procedia PDF Downloads 152

Authors: Adam Kurnicki, Bartłomiej Stanczyk, Bartosz Kania

Abstract:

This paper presents development of the light-weight manipulator with series elastic actuation for medical telediagnostics (USG examination). General structure of realized impedance control algorithm was shown. It was described how to perform force measurements based mainly on elasticity of manipulator links.

Keywords: telediagnostics, elastic manipulator, impedance control, force measurement

Procedia PDF Downloads 480

Authors: Gary Miller, Andriy Didenko, David Allison

Abstract:

The boundary of a region in the plane shrinks according to its curvature. A simple algorithm based upon this motion by curvature performed by a spreadsheet simulates the evaporation/dissipation behavior of oil spill boundaries.

Keywords: mathematical modeling, oil, evaporation, dissipation, boundary

Procedia PDF Downloads 513

Authors: S. Jalaja, A. M. Vijaya Prakash

Abstract:

Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.

Keywords: carry save adder Karatsuba multiplication, mid range Karatsuba multiplication, modified FFA and transposed filter, retiming

Procedia PDF Downloads 236

Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

Procedia PDF Downloads 216