Search results for: rapidly exploring random trees
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5268

Search results for: rapidly exploring random trees

4938 Conservation Status of a Lowland Tropical Forest in South-West, Nigeria

Authors: Lucky Dartsa Wakawa, Friday Nwabueze Ogana, Temitope Elizabeth Adeniyi

Abstract:

Timely and reliable information on the status of a forest is essential for assessing the extent of regeneration and degradation. However, when such information is lacking effective forest management practices becomes impossible. Therefore, this study assessed the tree species composition, richness, diversity, structure of Oluwa forest reserve with the view of ascertaining it conservation status. A systematic line transect was used in the laying of eight (8) temporary sample plots (TSPs) of size 50m x 50m. Trees with Dbh ≥ 10cm in the selected plots were enumerated, identified and measured. The results indicate that 535 individual trees were enumerated cutting across 26 families and 58 species. The family Sterculiaceae recorded the highest number of species (10) and occurrence (112) representing 17.2% and 20.93% respectively. Celtis zenkeri is the species with the highest number of occurrence of tree per hectare and importance value index (IVI) of 59 and 53.81 respectively. The reserve has the Margalef's index of species richness, Shannon-Weiner diversity Index (H') and Pielou's Species Evenness Index (EH) of 9.07, 3.43 and 0.84 respectively. The forest has a mean Dbh (cm), mean height (m), total basal area/ha (m2) and total volume/ha (m3) of 24.7, 16.9, 36.63 and 602.09 respectively. The important tropical tree species identified includes Diospyros crassiflora Milicia excels, Mansonia altisima, Triplochiton scleroxylon. Despite the level of exploitation in the forest, the forest seems to be resilience. Given the right attention, it could regenerate and replenish to save some of the original species composition of the reserve.

Keywords: forest conservation, forest structure, Lowland tropical forest, South-west Nigeria

Procedia PDF Downloads 317
4937 An Integrated Approach for Risk Management of Transportation of HAZMAT: Use of Quality Function Deployment and Risk Assessment

Authors: Guldana Zhigerbayeva, Ming Yang

Abstract:

Transportation of hazardous materials (HAZMAT) is inevitable in the process industries. The statistics show a significant number of accidents has occurred during the transportation of HAZMAT. This makes risk management of HAZMAT transportation an important topic. The tree-based methods including fault-trees, event-trees and cause-consequence analysis, and Bayesian network, have been applied to risk management of HAZMAT transportation. However, there is limited work on the development of a systematic approach. The existing approaches fail to build up the linkages between the regulatory requirements and the safety measures development. The analysis of historical data from the past accidents’ report databases would limit our focus on the specific incidents and their specific causes. Thus, we may overlook some essential elements in risk management, including regulatory compliance, field expert opinions, and suggestions. A systematic approach is needed to translate the regulatory requirements of HAZMAT transportation into specified safety measures (both technical and administrative) to support the risk management process. This study aims to first adapt the House of Quality (HoQ) to House of Safety (HoS) and proposes a new approach- Safety Function Deployment (SFD). The results of SFD will be used in a multi-criteria decision-support system to develop find an optimal route for HazMats transportation. The proposed approach will be demonstrated through a hypothetical transportation case in Kazakhstan.

Keywords: hazardous materials, risk assessment, risk management, quality function deployment

Procedia PDF Downloads 114
4936 A Quantitative Structure-Adsorption Study on Novel and Emerging Adsorbent Materials

Authors: Marc Sader, Michiel Stock, Bernard De Baets

Abstract:

Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

Procedia PDF Downloads 204
4935 Tool Damage and Adhesion Effects in Turning and Drilling of Hardened Steels

Authors: Chris M. Taylor, Ian Cook, Raul Alegre, Pedro Arrazola, Phil Spiers

Abstract:

Noteworthy results have been obtained in the turning and drilling of hardened high-strength steels using tungsten carbide based cutting tools. In a finish turning process, it was seen that surface roughness and tool flank wear followed very different trends against cutting time. The suggested explanation for this behaviour is that the profile cut into the workpiece surface is determined by the tool’s cutting edge profile. It is shown that the profile appearing on the cut surface changes rapidly over time, so the profile of the tool cutting edge should also be changing rapidly. Workpiece material adhered onto the cutting tool, which is also known as a built-up edge, is a phenomenon which could explain the observations made. In terms of tool damage modes, workpiece material adhesion is believed to have contributed to tool wear in examples provided from finish turning, thread turning and drilling. Additionally, evidence of tool fracture and tool abrasion were recorded.

Keywords: turning, drilling, adhesion, wear, hard steels

Procedia PDF Downloads 310
4934 Solving Process Planning, Weighted Earliest Due Date Scheduling and Weighted Due Date Assignment Using Simulated Annealing and Evolutionary Strategies

Authors: Halil Ibrahim Demir, Abdullah Hulusi Kokcam, Fuat Simsir, Özer Uygun

Abstract:

Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.

Keywords: process planning, weighted scheduling, weighted due-date assignment, simulated annealing, evolutionary strategies, hybrid searches

Procedia PDF Downloads 434
4933 Texture-Based Image Forensics from Video Frame

Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

Procedia PDF Downloads 403
4932 Investigating the Efficiency of Stratified Double Median Ranked Set Sample for Estimating the Population Mean

Authors: Mahmoud I. Syam

Abstract:

Stratified double median ranked set sampling (SDMRSS) method is suggested for estimating the population mean. The SDMRSS is compared with the simple random sampling (SRS), stratified simple random sampling (SSRS), and stratified ranked set sampling (SRSS). It is shown that SDMRSS estimator is an unbiased of the population mean and more efficient than SRS, SSRS, and SRSS. Also, by SDMRSS, we can increase the efficiency of mean estimator for specific value of the sample size. SDMRSS is applied on real life examples, and the results of the example agreed the theoretical results.

Keywords: efficiency, double ranked set sampling, median ranked set sampling, ranked set sampling, stratified

Procedia PDF Downloads 223
4931 Exploring Challenges Faced by Small Business Owners on Poverty Reduction in Rural Eastern Cape, South Africa

Authors: Akinwale Olusola Mokayode, Emaanuel Adu, Seriki Idowu Ibrahim

Abstract:

Small business can serve as a tool for poverty reduction in South Africa, but it requires adequate support and development for its continuous sustenance in spite of rigorous challenges, especially in the rural environment. This study explored the challenges faced by the small business owners in the rural Eastern Cape Province of South Africa. The objective of the study is to identify the challenges faced by small business owners in the case study area and to examine the effects of those challenges on poverty rate. Survey research design was adopted, with the distribution of structured questionnaire for data collection through a simple random sampling method. Descriptive and inferential statistics was used to analyse the data. Findings showed that small business owners face various challenges in their commercial operations. It was also made clearer that these challenges have effects on the poverty rate as well as crime rate. In conclusion, in other for small businesses to be effective instrument to tackle poverty, certain measure must be taken into considerations. This therefore necessitates recommendation from the researcher that potential and current business owners must seek valuable advice from the more experienced business tycoon and seek information about the business assistance programmes provided by government and private sectors.

Keywords: eastern cape, poverty, poverty reduction, rural, small business, sustainable livelihood

Procedia PDF Downloads 458
4930 Hydrodynamic Characteristics of Single and Twin Offshore Rubble Mound Breakwaters under Regular and Random Waves

Authors: M. Alkhalidi, S. Neelamani, Z. Al-Zaqah

Abstract:

This paper investigates the interaction of single and twin offshore rubble mound breakwaters with regular and random water waves through physical modeling to assess their reflection, transmission and energy dissipation characteristics. Various combinations of wave heights and wave periods were utilized in a series of experiments, along with three different water depths. The single and twin permeable breakwater models were both constructed with one layer of rubbles. Both models had the same total volume; however, the single breakwater was of trapezoidal type while the twin breakwaters were of triangular type. Physical modeling experiments were carried out in the wave flume of the coastal engineering laboratory of Kuwait Institute for Scientific Research (KISR). Measurements of the six wave probes which were fixed in the two-dimensional wave flume were collected and used to determine the generated incident wave heights, as well as the reflected and transmitted wave heights resulting from the wave-breakwater interaction. The possible factors affecting the wave attenuation efficiency of the breakwater models are the relative water depth (d/L), wave steepness (H/L), relative wave height ((h-d)/Hi), relative height of the breakwater (h/d), and relative clear spacing between the twin breakwaters (S/h). The results indicated that the single and double breakwaters show different responds to the change in their relative height as well as the relative wave height which demonstrates that the effect of the relative water depth on wave reflection, transmission, and energy dissipation is highly influenced by the change in the relative breakwater height, the relative wave height and the relative breakwater spacing. In general, within the range of the relative water depth tested in this study, and under both regular and random waves, it is found that the single breakwater allows for lower wave transmission and shows higher energy dissipation effect than both of the tested twin breakwaters, and hence has the best overall performance.

Keywords: random waves, regular waves, relative water depth, relative wave height, single breakwater, twin breakwater, wave steepness

Procedia PDF Downloads 284
4929 Facial Recognition on the Basis of Facial Fragments

Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

Abstract:

There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

Procedia PDF Downloads 331
4928 ANOVA-Based Feature Selection and Machine Learning System for IoT Anomaly Detection

Authors: Muhammad Ali

Abstract:

Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

Procedia PDF Downloads 95
4927 Using Combination of Different Sets of Features of Molecules for Improved Prediction of Solubility

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, molecular descriptors, machine learning, random forest

Procedia PDF Downloads 25
4926 On the Use of Analytical Performance Models to Design a High-Performance Active Queue Management Scheme

Authors: Shahram Jamali, Samira Hamed

Abstract:

One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

Procedia PDF Downloads 516
4925 Sensitivity Analysis of Principal Stresses in Concrete Slab of Rigid Pavement Made From Recycled Materials

Authors: Aleš Florian, Lenka Ševelová

Abstract:

Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

Procedia PDF Downloads 298
4924 Empowering Nigerian Rural Women through Ownership of Productive Resources

Authors: Sidiqat A. Aderinoye-Abdulwahab, Lateef L. Adefalu, Rashid S. Adisa, Felix O. Oladipo, Tawakalitu A. Dolapo

Abstract:

This study investigates whether the rural women in Nigeria have access to productive resources such as land, livestock, and capital in order to determine their level of socio-economic empowerment. The study adopted a case study design while employing qualitative and quantitative methods of data collection. A multi-stage sampling technique was used to identify 7 locations, where 88 women were selected based on simple random sampling technique. Focus group discussions and questionnaire were used to elicit information. Gender analysis framework was used to explore and analyse the data generated for the study. The study found that the rural women desire to engage in gainful economic activities. However, cultural barriers prevent them from adequately exploring livelihood-improving opportunities. It was established that ownership of productive resources such as land and livestock can enhance their livelihoods provided cultural and governance issues do not deter them from accessing the services. It was therefore recommended that appropriate policies that will favour the access and ownership of assets by women so as to empower them need to be in place. The study provides a nuanced perspective on the influence and relevance of possession of physical assets in enhancing women’s livelihood diversification and overall development of rural livelihoods.

Keywords: livelihoods, productivity, development, economic activities, socio-economic empowerment

Procedia PDF Downloads 236
4923 Low Cost Inertial Sensors Modeling Using Allan Variance

Authors: A. A. Hussen, I. N. Jleta

Abstract:

Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors

Procedia PDF Downloads 409
4922 A Three-Dimensional (3D) Numerical Study of Roofs Shape Impact on Air Quality in Urban Street Canyons with Tree Planting

Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi

Abstract:

The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.

Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM

Procedia PDF Downloads 328
4921 Coupling Random Demand and Route Selection in the Transportation Network Design Problem

Authors: Shabnam Najafi, Metin Turkay

Abstract:

Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

Procedia PDF Downloads 617
4920 Classification of Contexts for Mentioning Love in Interviews with Victims of the Holocaust

Authors: Marina Yurievna Aleksandrova

Abstract:

Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

Procedia PDF Downloads 159
4919 The Sawdust Cultivation of Lentinula edodes with Broussonetia kazinoki

Authors: Yeun Sug Jeong, Yeongseon Jang, Rhim Ryoo, Donha Choi, Sung-Suk Lee, Kang-Hyeon Ka

Abstract:

Broussonetia kazinoki (paper mulberry) is a plant native to Asia, and it grows at the foot of a mountain. Its bark is used as a raw material of Hanji, traditional Korean paper, and fruit is used as a medicinal material. However, inside the bark (woody part) is not used and discarded. We tried to use it for Lentinula edodes (oak mushroom) cultivation. It is commonly cultivated using oak trees and sawdust, but it could be grown with other trees. The woody part of paper mulberry was ground and mixed with oak sawdust by five different ratios. The 1.2 kg cylindrical bag media were prepared and water contents were adjusted to 65%. The media were autoclaved at 100℃ for 60 min and 121℃ for 90 min. Two strains of oak mushroom, NIFoS 2462 and NIFoS 2778 were inoculated and cultivated for 90 days in dark condition, and 40 days in light condition. Compared to the control, the mycelial growth period was long and the hardness of the media was low when paper mulberry sawdust was added. After incubation period, fruiting was stimulated at 18℃ and more than 85% humidity. After each flush, there was a resting period of 2 weeks. In the first flush, mushrooms were small, and a lot of small mushrooms were harvested. On the other hand, no mushrooms of 5 g or less were harvested in the secondary flush. The highest productivity was obtained in a 3:1 ratio of paper mulberry and oak sawdust. The size of NIFoS 2778 was uniform in each condition. On the other hand, NIFoS 2462 had smaller mushrooms in the media containing paper mulberry sawdust, but the appearance was not significantly different. This study showed that paper mulberry wood could be used to grow oak mushrooms and some oak sawdust could be substituted.

Keywords: Broussonetia kazinoki, cultivation, Lentinula edodes, oak mushroom

Procedia PDF Downloads 195
4918 Rounding Technique's Application in Schnorr Signature Algorithm: Known Partially Most Significant Bits of Nonce

Authors: Wenjie Qin, Kewei Lv

Abstract:

In 1996, Boneh and Venkatesan proposed the Hidden Number Problem (HNP) and proved the most significant bits (MSB) of computational Diffie-Hellman key exchange scheme and related schemes are unpredictable bits. They also gave a method which is a lattice rounding technique to solve HNP in non-uniform model. In this paper, we put forward a new concept that is Schnorr-MSB-HNP. We also reduce the problem of solving Schnorr signature private key with a few consecutive most significant bits of random nonce (used at each signature generation) to Schnorr-MSB-HNP, then we use the rounding technique to solve the Schnorr-MSB-HNP. We have come to the conclusion that if there is a ‘miraculous box’ which inputs the random nonce and outputs 2loglogq (q is a prime number) most significant bits of nonce, the signature private key will be obtained by choosing 2logq signature messages randomly. Thus we get an attack on the Schnorr signature private key.

Keywords: rounding technique, most significant bits, Schnorr signature algorithm, nonce, Schnorr-MSB-HNP

Procedia PDF Downloads 203
4917 HLB Disease Detection in Omani Lime Trees using Hyperspectral Imaging Based Techniques

Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

Abstract:

In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

Procedia PDF Downloads 49
4916 The Prognostic Value of Dynamic Changes of Hematological Indices in Oropharyngeal Cancer Patients Treated with Radiotherapy

Authors: Yao Song, Danni Cheng, Jianjun Ren

Abstract:

Objectives: We aimed to explore the prognostic effects of absolute values and dynamic changes of common hematological indices on oropharynx squamous cell carcinoma (OPSCC) patients treated with radiation. Methods and materials: The absolute values of white blood cell (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), hemoglobin (Hb), platelet (Plt), albumin (Alb), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at baseline (within 45 days before radiation), 1-, 3-, 6- and 12-months after the start of radiotherapy were retrospectively collected. Locally-estimated smoothing scatterplots were used to describe the smooth trajectory of each index. A mixed-effect model with a random slope was fitted to describe the changing rate and trend of indices over time. Cox proportional hazard analysis was conducted to assess the correlation between hematological indices and treatment outcomes. Results: Of the enrolled 85 OPSCC patients, inflammatory indices, such as WBC and ALC, dropped rapidly during acute treatment and gradually recovered, while NLR and PLR increased at first three months and subsequently declined within 3-12 months. Higher absolute value or increasing trend of nutritional indices (Alb and Hb) was associated with better prognosis (all p<0.05). In contrast, patients with higher absolute value or upward trend of inflammatory indices (WBC, ANC, Plt, PLR and NLR) had worse survival (all p<0.05). Conclusions: The absolute values and dynamic changes of hematological indices were valuable prognostic factors for OPSCC patients who underwent radiotherapy.

Keywords: hematological indices, oropharyngeal cancer, radiotherapy, NLR, PLR

Procedia PDF Downloads 144
4915 Exploring the Factors Affecting the Presence of Farmers’ Markets in Rural British Columbia

Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

Abstract:

Farmers’ Markets have become one of the important healthy food suppliers in both rural communities and urban settings. Farmers’ markets are evolving and their number has rapidly increased in the past decade. Despite this drastic increase, the distribution of the farmers’ markets is not even across different areas. The main goal of this study is to explore the socioeconomic, geographic, and demographic variables which affect the establishment of farmers’ market in rural communities in British Columbia (BC). Thus, the data on available farmers’ markets in rural areas were collected from BC Association of Farmers’ Markets and spatially joined to BC map at Dissemination Area (DA) level using ArcGIS software to link the farmers’ market to the respective communities that they serve. Then, in order to investigate this issue and understand which rural communities farmer’ markets tend to operate, a binary logistic regression analysis was performed with the availability of farmer’ markets at DA-level as dependent variable and Deprivation Index (DI), Metro Influence Zone (MIZ) and population as independent variables. The results indicated that DI and MIZ variables are not statistically significant whereas the population is the only which had a significant contribution in predicting the availability of farmers’ markets in rural BC. Moreover, this study found that farmers’ markets usually do not operate in rural food deserts where other healthy food providers such as supermarkets and grocery stores are non-existent. In conclusion, the presence of farmers markets is not associated with socioeconomic and geographic characteristics of rural communities in BC, but farmers’ markets tend to operate in more populated rural communities in BC.

Keywords: farmers’ markets, socioeconomic and demographic variables, metro influence zone, logistic regression, ArcGIS

Procedia PDF Downloads 169
4914 Glycation of Serum Albumin: Cause Remarkable Alteration in Protein Structure and Generation of Early Glycation End Products

Authors: Ishrat Jahan Saifi, Sheelu Shafiq Siddiqi, M. R. Ajmal

Abstract:

Glycation of protein is very important as well as a harmful process, which may lead to develop DM in human body. Human Serum Albumin (HSA) is the most abundant protein in blood and it is highly prone to glycation by the reducing sugars. 2-¬deoxy d-¬Ribose (dRib) is a highly reactive reducing sugar which is produced in cells as a product of the enzyme thymidine phosphorylase. It is generated during the degradation of DNA in human body. It may cause glycation in HSA rapidly and is involved in the development of DM. In present study, we did in¬vitro glycation of HSA with different concentrations of 2-¬deoxy d-¬ribose and found that dRib glycated HSA rapidly within 4h incubation at 37◦C. UV¬ Spectroscopy, Fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR) and Circular Dichroism (CD) technique have been done to determine the structural changes in HSA upon glycation. Results of this study suggested that dRib is the potential glycating agent and it causes alteration in protein structure and biophysical properties which may lead to development and progression of Diabetes mellitus.

Keywords: 2-deoxy D-ribose, human serum albumin, glycation, diabetes mellitus

Procedia PDF Downloads 186
4913 Measurement of in-situ Horizontal Root Tensile Strength of Herbaceous Vegetation for Improved Evaluation of Slope Stability in the Alps

Authors: Michael T. Lobmann, Camilla Wellstein, Stefan Zerbe

Abstract:

Vegetation plays an important role for the stabilization of slopes against erosion processes, such as shallow erosion and landslides. Plant roots reinforce the soil, increase soil cohesion and often cross possible shear planes. Hence, plant roots reduce the risk of slope failure. Generally, shrub and tree roots penetrate deeper into the soil vertically, while roots of forbs and grasses are concentrated horizontally in the topsoil and organic layer. Therefore, shrubs and trees have a higher potential for stabilization of slopes with deep soil layers than forbs and grasses. Consequently, research mainly focused on the vertical root effects of shrubs and trees. Nevertheless, a better understanding of the stabilizing effects of grasses and forbs is needed for better evaluation of the stability of natural and artificial slopes with herbaceous vegetation. Despite the importance of vertical root effects, field observations indicate that horizontal root effects also play an important role for slope stabilization. Not only forbs and grasses, but also some shrubs and trees form tight horizontal networks of fine and coarse roots and rhizomes in the topsoil. These root networks increase soil cohesion and horizontal tensile strength. Available methods for physical measurements, such as shear-box tests, pullout tests and singular root tensile strength measurement can only provide a detailed picture of vertical effects of roots on slope stabilization. However, the assessment of horizontal root effects is largely limited to computer modeling. Here, a method for measurement of in-situ cumulative horizontal root tensile strength is presented. A traction machine was developed that allows fixation of rectangular grass sods (max. 30x60cm) on the short ends with a 30x30cm measurement zone in the middle. On two alpine grass slopes in South Tyrol (northern Italy), 30x60cm grass sods were cut out (max. depth 20cm). Grass sods were pulled apart measuring the horizontal tensile strength over 30cm width over the time. The horizontal tensile strength of the sods was measured and compared for different soil depths, hydrological conditions, and root physiological properties. The results improve our understanding of horizontal root effects on slope stabilization and can be used for improved evaluation of grass slope stability.

Keywords: grassland, horizontal root effect, landslide, mountain, pasture, shallow erosion

Procedia PDF Downloads 139
4912 Elder Abuse: An Exploration of China, the United States, and Israel’s Perspectives on Elder Abuse and What Their Differences Reveal about Its Underreported Nature

Authors: Sydney Burnett

Abstract:

The history of the relationship between elder abuse and its tendency to go underreported is rooted in the oppressive nature of ageism and victimization. Approximately 8% of the world's population was aged sixty or over in 1950, whereas, in 2020, the number more than doubled to 16.9%. By 2050, that number is expected to reach 22%. Although difficult for individuals of any age to feel completely supported in society, this task proves especially difficult for the elderly demographic. And as the elderly population continues to grow, the systemic abuse and neglect that this group encounters, and thus its underreported nature, multiply at a similar rate. Although a recent increase in awareness has initiated stronger efforts towards addressing the meager resources, processes, and personnel present to manage elder abuse, both reported and unreported, the destructive complexities of ageism and victimization persist. Examining the byproducts of the rapidly growing elderly demographic in China, the United States, and Israel, in cohesion with the inherent challenges in the context of terminology, definition, and typologies of elder abuse should provide insight into the pernicious influences of elder abuse that contribute to the non-identification and non-recognition of elder maltreatment present in these three countries in different stages of development. This investigation aims to understand the intricacy of elder abuse and its correlation to a lack of acknowledgment as well as its consequences in society by exploring the variation between China, the United States, and Israel's attitudes surrounding the subject. Furthermore, the systemic abuse and neglect embedded in global ageism can be revealed by the differences between the three countries' approaches to reporting elder abuse.

Keywords: elder abuse, ageism, mistreatment, underreported

Procedia PDF Downloads 70
4911 On a Single Server Queue with Arrivals in Batches of Variable Size, Generalized Coxian-2 Service and Compulsory Server Vacations

Authors: Kailash C. Madan

Abstract:

We study the steady state behaviour of a batch arrival single server queue in which the first service with general service times is compulsory and the second service with general service times is optional. We term such a two phase service as generalized Coxian-2 service. Just after completion of a service the server must take a vacation of random length of time with general vacation times. We obtain steady state probability generating functions for the queue size as well as the steady state mean queue size at a random epoch of time in explicit and closed forms. Some particular cases of interest including some known results have been derived.

Keywords: batch arrivals, compound Poisson process, generalized Coxian-2 service, steady state

Procedia PDF Downloads 429
4910 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 61
4909 Mean Square Responses of a Cantilever Beam with Various Damping Mechanisms

Authors: Yaping Zhao, Yimin Zhang

Abstract:

In the present paper, the stationary random vibration of a uniform cantilever beam is investigated. Two types of damping mechanism, i.e. the external and internal viscous dampings, are taken into account simultaneously. The excitation form is the support motion, and it is ideal white. Because two type of damping mechanism are considered concurrently, the product of the modal damping ratio and the natural frequency is not a constant anymore. As a result, the infinite definite integral encountered in the process of computing the mean square response is more complex than that in the existing literature. One signal progress of this work is to have calculated these definite integrals accurately. The precise solution of the mean square response is thus obtained in the infinite series form finally. Numerical examples are supplied and the numerical outcomes acquired confirm the validity of the theoretical analyses.

Keywords: random vibration, cantilever beam, mean square response, white noise

Procedia PDF Downloads 366