Search results for: pedestrian target selection

Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

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The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides a more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking

Procedia PDF Downloads 92

Authors: Driss Cherqaoui, Nouhaila Ait Lahcen, Ismail Hdoufane, Mehdi Oubahmane, Wissal Liman, Christelle Delaite, Mohammed M. Alanazi

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The Ebola virus is a highly contagious and deadly pathogen that causes Ebola virus disease. The Ebola virus glycoprotein (EBOV-GP) is a key factor in viral entry into host cells, making it a critical target for therapeutic intervention. Using a combination of computational approaches, this study focuses on the identification of natural compounds that could serve as potent inhibitors of EBOV-GP. The 3D structure of EBOV-GP was selected, with missing residues modeled, and this structure was minimized and equilibrated. Two large natural compound databases, COCONUT and NPASS, were chosen and filtered based on toxicity risks and Lipinski’s Rule of Five to ensure drug-likeness. Following this, a pharmacophore model, built from 22 reported active inhibitors, was employed to refine the selection of compounds with a focus on structural relevance to known Ebola inhibitors. The filtered compounds were subjected to virtual screening via molecular docking, which identified ten promising candidates (five from each database) with strong binding affinities to EBOV-GP. These compounds were then validated through molecular dynamics simulations to evaluate their binding stability and interactions with the target. The top three compounds from each database were further analyzed using ADMET profiling, confirming their favorable pharmacokinetic properties, stability, and safety. These results suggest that the selected compounds have the potential to inhibit EBOV-GP, offering new avenues for antiviral drug development against the Ebola virus.

Keywords: EBOV-GP, Ebola virus glycoprotein, high-throughput drug screening, molecular docking, molecular dynamics, natural compounds, pharmacophore modeling, virtual screening

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Authors: Nasrullah khan

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Today business environment is very dynamic and most of organizations are in tough competition for their added values and sustainable hold in market. To achieve such objectives, organizations must have dynamic and creative people as optimized process. To get these people, there should strong human resource management system in organizations. There are multiple approaches have been devised in literature to hire more job relevant and more suitable people. This study proposed an ANP (Analytic Network Process) approach to hire faculty members for a university system. This study consists of two parts. In fist part, a through literature survey and universities interview are conducted in order to find the common criteria for the selection of academic staff. In second part the available candidates are prioritized on the basis of the relative values of these criteria. According to results the GRE & foreign language, GPA and research paper writing were most important factors for the selection of academic staff.

Keywords: creative people, ANP, academic staff, business environment

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Authors: Yu-Wen Huang, Yi-Cheng Chiang

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With urban development, lots of buildings are built around the city. The buildings always affect the urban wind environment. The accelerative situation of wind caused of buildings often makes pedestrians uncomfortable, even causes the accidents and dangers. Factors influencing pedestrian level wind including atmospheric boundary layer, wind direction, wind velocity, planting, building volume, geometric shape of the buildings and adjacent interference effects, etc. Planting has many functions including scraping and slowing urban heat island effect, creating a good visual landscape, increasing urban green area and improve pedestrian level wind. On the other hand, urban square is an important space element supporting the entrance to buildings, city landmarks, and activity collections, etc. The appropriateness of urban square environment usually dominates its success. This research focuses on the effect of tree-planting on the wind environment of urban square. This research studied the square belt of Taichung City Hall. Taichung City Hall is a cuboid building with a large mass opening. The square belt connects the front square, the central opening and the back square. There is often wind draft on the square belt. This phenomenon decreases the activities on the squares. This research applies tree-planting to improve the wind environment and evaluate the effects of two types of planting configuration. The Computational Fluid Dynamics (CFD) simulation analysis and extensive field measurements are applied to explore the improve efficiency of planting configuration on wind environment. This research compares efficiencies of different kinds of planting configuration, including the clustering array configuration and the dispersion, and evaluates the efficiencies by the SET*.

Keywords: micro-climate, wind environment, planting configuration, comfortableness, computational fluid dynamics (CFD)

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Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

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In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Tetsuki Taniguchi, Yoshio Karasawa

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This paper describes a node pair selection scheme in relay-aided multiple source multiple destination communication system based on stable marriage problem. A general case is assumed in which all of source, relay and destination nodes are equipped with multiantenna and carry out multistream transmission. Based on several metrics introduced from inter-node channel condition, the preference order is determined about all source-relay and relay-destination relations, and then the node pairs are determined using Gale-Shapley algorithm. The computer simulations show that the effectiveness of node pair selection is larger in multihop communication. Some additional aspects which are different from relay-less case are also investigated.

Keywords: relay, multiple input multiple output (MIMO), multiuser, amplify and forward, stable marriage problem, Gale-Shapley algorithm

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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Authors: Haythem H. Abdullah, Hesham Elkady

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With the fast increase in radio frequency identification (RFID) applications such as medical recording, library management, etc., the limitation of active tags stems from its need to external batteries as well as passive or active chips. The chipless RFID tag reduces the cost to a large extent but at the expense of utilizing the spectrum. The reduction of the cost of chipless RFID is due to the absence of the chip itself. The identification is done by utilizing the spectrum in such a way that the frequency response of the tags consists of some resonance frequencies that represent the bits. The system capacity is decided by the number of resonators within the pre-specified band. It is important to find a solution to enhance the spectrum utilization when using chipless RFID. Target identification is a process that results in a decision that a specific target is present or not. Several target identification schemes are present, but one of the most successful techniques in radar target identification in the oscillatory region is the extinction pulse technique (E-Pulse). The E-Pulse technique is used to identify targets via its characteristics (natural) modes. By introducing an innovative solution for chipless RFID reader and tag designs, the spectrum utilization goes to the optimum case. In this paper, a novel capacity enhancement scheme based on the E-pulse technique is introduced to improve the performance of the chipless RFID system.

Keywords: chipless RFID, E-pulse, natural modes, resonators

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Authors: Amna Ali Al-Saadi, Riken Homma, Kazuhisa Iki

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Despite the fact that many places have successes in achieving some aspects of sustainable urban development, there are no scientific facts to convince decision makers. Also, each of them was developed to fulfill the need of specific city only. Therefore, objective method to generate the solutions from a successful case is the aim of this research. The questions were: how to learn the lesson from each case study; how to distinguish the potential criteria and negative one; snd how to quantify their effects in the future development. Walkability has been selected as a goal. This is because it has been found as a solution to achieve healthy life style as well as social, environmental and economic sustainability. Moreover, it has complication as every aspect of sustainable development. This research is stand on quantitative- comparative methodology in order to assess pedestrian oriented development. Three analyzed area (AAs) were selected. One site is located in Oman in which hypotheses as motorized oriented development, while two sites are in Japan where the development is pedestrian friendly. The study used Multi- criteria evaluation method (MCEM). Initially, MCEM stands on analytic hierarchy process (AHP). The later was structured into main goal (walkability), objectives (functions and layout) and attributes (the urban form criteria). Secondly, the GIS were used to evaluate the attributes in multi-criteria maps. Since each criterion has different scale of measurement, all results were standardized by z-score and used to measure the co-relations among criteria. As results, different scenario was generated from each AA. MCEM (AHP-OWA)-GIS measured the walkability score and determined the priority of criteria development in the non-walker friendly environment. The comparison criteria for z-score presented a measurable distinguished orientation of development. This result has been used to prove that Oman is motorized environment while Japan is walkable. Also, it defined the powerful criteria and week criteria regardless to the AA. This result has been used to generalize the priority for walkable development. In conclusion, the method was found successful in generate scientific base for policy decisions.

Keywords: walkability, policy decisions, sustainable development, GIS

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Authors: Anh Duc Dang, Joachim Horn

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This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbours are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.

Keywords: formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems

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Authors: Benbellil-Tafoughalt Saida, Tababouchet Meriem

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Sexual selection is the most supported explanation for genital extravagance occurring in animals. In promiscuous species, population density, as well as climate conditions, may act on the sperm competition intensity, one of the most important mechanism of post-copulatory sexual selection. The present study is empirical testing of sexual selection's potential role on genitalia variation in the simultanuously hermaphroditic land snail Helixaperta (Pulmonata, Stylommatophora). The purpose was to detect the patterns as well as the origin of the distal genitalia variability and especially to test the potential effect of sexual selection. The study was performed on four populations, H. aperta, different in habitat humidity regimes and presenting variable densities, which were mostly low. The organs of interest were those involved in spermatophore production, reception, and manipulation. We examined whether the evolution of those organs is connected to sperm competition intensity which is traduced by both population density and microclimate humidity. We also tested the hypothesis that those organs evolve in response to shell size. The results revealed remarkable differences in both snails’ size and organs lengths between populations. In most cases, the length of genitalia correlated positively to snails’ body size. Interestingly, snails from the more humid microclimate presented the highest mean weight and shell dimensions comparing to those from the less humid microclimate. However, we failed to establish any relation between snail densities and any of the measured genitalia traits.

Keywords: fertilization pouch, helix aperta, land snails, reproduction, sperm storage, spermatheca

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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Authors: Jagannath Singh, Durga Prasad Mohapatra

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Software refactoring is very essential for maintaining the software quality. It is an usual practice that we first design the software and then go for coding. But after coding is completed, if the requirement changes slightly or our expected output is not achieved, then we change the codes. For each small code change, we cannot change the design. In course of time, due to these small changes made to the code, the software design decays. Software refactoring is used to restructure the code in order to improve the design and quality of the software. In this paper, we propose an approach for performing code refactoring. We use slice-based cohesion metrics to identify the target methods which requires refactoring. After identifying the target methods, we use program slicing to divide the target method into two parts. Finally, we have used the concepts of Aspects to adjust the code structure so that the external behaviour of the original module does not change.

Keywords: software refactoring, program slicing, AOP, cohesion metrics, code restructure, AspectJ

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Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

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Authors: Kai-Yao Huang, Tzong-Yi Lee, Pin-Hao Ho, Tzu-Hao Chang, Cheng-Wei Chang

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Background: Human cytomegalovirus (HCMV) infects much people around the world, and there were many researches mention that many diseases were caused by HCMV. To understand the mechanism of HCMV lead to diseases during infection. We observe a microRNA (miRNA) – miRNA interaction between HCMV and host during infection. We found HCMV miRNA sequence component complementary with host miRNA precursors, and we also found that the host miRNA abundances were decrease in HCMV infection. Hence, we focus on the host miRNA which may target by the other HCMV miRNA to find theirs target mRNAs expression and analysis these mRNAs affect what kind of signaling pathway. Interestingly, we found the affected mRNA play an important role in some diseases related pathways, and these diseases had been annotated by HCMV infection. Results: From our analysis procedure, we found 464 human miRNAs might be targeted by 26 HCMV miRNAs and there were 291 human miRNAs shows the concordant decrease trend during HCMV infection. For case study, we found hcmv-miR-US22-5p may regulate hsa-mir-877 and we analysis the KEGG pathway which built by hsa-mir-877 validate target mRNA. Additionally, through survey KEGG Disease database found that these mRNA co-regulate some disease related pathway for instance cancer, nerve disease. However, there were studies annotated that HCMV infection casuse cancer and Alzheimer. Conclusions: This work supply a different scenario of miRNA target interactions(MTIs). In previous study assume miRNA only target to other mRNA. Here we wonder there is possibility that miRNAs might regulate non-mRNA targets, like other miRNAs. In this study, we not only consider the sequence similarity with HCMV miRNAs and human miRNA precursors but also the expression trend of these miRNAs. Then we analysis the human miRNAs validate target mRNAs and its associated KEGG pathway. Finally, we survey related works to validate our investigation.

Keywords: human cytomegalovirus, HCMV, microRNA, miRNA

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Koirala Abarodh, Maghaiya Ujjwal, Guragain Phani Raj

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This analysis focuses on defining the spectrum evaluation model for telecom operators in terms of total cost of ownership (TCO). A quantitative approach for specific case analysis research methodology was used for identifying the results. Specific input parameters like target User experience, year on year traffic growth, capacity site limit per year, target additional spectrum type, bandwidth, spectrum efficiency, UE penetration have been used for the spectrum evaluation process and desired outputs in terms of the number of sites, capex in USD and required spectrum bandwidth have been calculated. Furthermore, this study gives a comparison of capex investment for target growth with and without addition spectrum. As a result, the combination of additional spectrum bands of 700 and 2600 MHz has a better evaluation in terms of TCO and performance. It is our recommendation to use these bands for expansion rather than expansion in the current 1800 and 2100 bands.

Keywords: spectrum, capex planning, case study methodology, TCO

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Giorgio Visentin, Inna S. Kalinina, Alexei A. Buchachenko

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In the ambit of intermolecular interactions, a combination rule is defined as a relation linking a potential parameter for the interaction of two unlike species with the same parameters for interaction pairs of like species. Some of their most exemplificative applications cover the construction of molecular dynamics force fields and dispersion-corrected density functionals. Here, an extended combination rule is proposed, relating the dipole-dipole dispersion coefficients for the interaction of like target species to the same coefficients for the interaction of the target and a set of partner species. The rule can be devised in two different ways, either by uniform discretization of the Casimir-Polder integral on a Gauss-Legendre quadrature or by relating the dynamic polarizabilities of the target and the partner species. Both methods return the same system of linear equations, which requires the knowledge of the dispersion coefficients for interaction between the partner species to be solved. The test examples show a high accuracy for dispersion coefficients (better than 1% in the pristine test for the interaction of Yb atom with rare gases and alkaline-earth metal atoms). In contrast, the rule does not ensure correct monotonic behavior of the dynamic polarizability of the target species. Acknowledgment: The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: combination rule, dipole-dipole dispersion coefficient, Casimir-Polder integral, Gauss-Legendre quadrature

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Authors: Fatima Chaudhary, Rehan Ul Haq

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Spatial and anthropogenic factors influencing nest-site selection in birds need to be identified for effective conservative practices. Environmental attributes such as food availability, predator density, previous reproductive success, etc., provide information regarding the site's quality. An artificial nest box experiment was carried out to evaluate the effect of various factors on nest-site selection, as it is hard to assess the natural cavities. The experiment was conducted whereby half of the boxes were filled with old nest material. Artificial nest boxes created with different materials and different sizes and colors were installed at different heights. A total of 14 out of 60 nest boxes were occupied and four of them faced predation. The birds explored a total of 32 out of 60 nests, whereas anthropogenic factors destroyed 25 out of 60 nests. Birds chose empty nest boxes at higher rates however, there was no obvious avoidance of sites having high ectoparasites load due to old nest material. It is also possible that the preference towards the artificial nest boxes may differ from year to year because of several climatic factors and the age of old nest material affecting the parasite's survival. These variables may fluctuate from one season to another. Considering these factors, nest-site selection experiments concerning the effectiveness of artificial nest boxes should be carried out over several successive seasons. This topic may stimulate further studies, which could lead to a fully understanding the birds' evolutionary ecology. Precise information on these factors influencing nest-site selection can be essential from an economic point of view as well.

Keywords: artificial nesting, nest box, old nest material, birds

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Manju Kanu, Subrata Sinha, Surabhi Johari

Abstract:

Viral proteins of Ebola viruses belong to one of the best studied viruses; however no effective prevention against EBOV has been developed. Epitope-based vaccines provide a new strategy for prophylactic and therapeutic application of pathogen-specific immunity. A critical requirement of this strategy is the identification and selection of T-cell epitopes that act as vaccine targets. This study describes current methodologies for the selection process, with Ebola virus as a model system. Hence great challenge in the field of ebola virus research is to design universal vaccine. A combination of publicly available bioinformatics algorithms and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertypes Human Leukocyte Antigen (HLA) alleles. MUSCLE and MOTIF tools were used to find out most conserved peptide sequences of viral proteins. Immunoinformatics tools were used for prediction of immunogenic peptides of viral proteins in zaire strains of Ebola virus. Putative epitopes for viral proteins (VP) were predicted from conserved peptide sequences of VP. Three tools NetCTL 1.2, BIMAS and Syfpeithi were used to predict the Class I putative epitopes while three tools, ProPred, IEDB-SMM-align and NetMHCII 2.2 were used to predict the Class II putative epitopes. B cell epitopes were predicted by BCPREDS 1.0. Immunogenic peptides were identified and selected manually by putative epitopes predicted from online tools individually for both MHC classes. Finally sequences of predicted peptides for both MHC classes were looked for common region which was selected as common immunogenic peptide. The immunogenic peptides were found for viral proteins of Ebola virus: epitopes FLESGAVKY, SSLAKHGEY. These predicted peptides could be promising candidates to be used as target for vaccine design.

Keywords: epitope, b cell, immunogenicity, ebola

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Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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Authors: Yousif Mohamed Y. Abdallah

Abstract:

This is an experimental study deals with detection, measurement and analysis of the periodic physiological organ motion during external beam radiotherapy; to improve the accuracy of the radiation field placement, and to reduce the exposure of healthy tissue during radiation treatments. The importance of this study is to detect the maximum path of the mobile structures during radiotherapy delivery, to define the planning target volume (PTV) and irradiated volume during both inspiration and expiration period and to verify the target volume. In addition to its role to highlight the importance of the application of Intense Guided Radiotherapy (IGRT) methods in the field of radiotherapy. The results showed (body contour was equally (3.17 + 0.23 mm), for left lung displacement reading (2.56 + 0.99 mm) and right lung is (2.42 + 0.77 mm) which the radiation oncologist to take suitable countermeasures in case of significant errors. In addition, the use of the image registration technique for automatic position control is predicted potential motion. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, individualized assessment of tumor mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a single CT scan with a margin of 10 mm is clearly inappropriate.

Keywords: respiratory motion, external beam radiotherapy, image processing, lung

Procedia PDF Downloads 536

Authors: Nipun Manirajan, Heeralal Gargama, Sushil Guhe, Manoj Prabhakaran

Abstract:

In railway industry, train sets are designed based on contractual requirements (mission profile), where reliability targets are measured in terms of mean distance between failures (MDBF). However, during the beginning of revenue services, trains do not achieve the designed mission profile distance (mileage) within the timeframe due to infrastructure constraints, scarcity of commuters or other operational challenges thereby not respecting the original design inputs. Since trains do not run sufficiently and do not achieve the designed mileage within the specified time, car builder has a risk of not achieving the contractual MDBF target. This paper proposes a constant failure rate based model to deal with the situations where mileage accumulation is not a part of the design mission profile. The model provides appropriate MDBF target to be demonstrated based on actual accumulated mileage. A case study of rolling stock running in the field is undertaken to analyze the failure data and MDBF target demonstration during low mileage accumulation. The results of case study prove that with the proposed method, reliability targets are achieved under low mileage accumulation.

Keywords: mean distance between failures, mileage-based reliability, reliability target appropriations, rolling stock reliability

Procedia PDF Downloads 267