Search results for: cloud effective radius
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10420

Search results for: cloud effective radius

8980 Evaluating the Location of Effective Product Advertising on Facebook Ads

Authors: Aulia F. Hadining, Atya Nur Aisha, Dimas Kurninatoro Aji

Abstract:

Utilization of social media as a marketing tool is growing rapidly, including for SMEs. Social media allows the user to give product evaluation and recommendations to the public. In addition, the social media facilitate word-of-mouth marketing communication. One of the social media that can be used is Facebook, with Facebook Ads. This study aimed to evaluate the location of Facebook Ads, to obtain an appropriate advertising design. There are three alternatives location consist of desktop, right-hand column and mobile. The effectiveness and efficiency of advertising will be measured based on advertising metrics such as reach, click, Cost per Click (CUC) and Unique Click-Through-Rate (UCTR). Facebook's Ads Manager was used for seven days, targeted by age (18-24), location (Bandung), language (Indonesia) and keywords. The result was 13,999 total reach, as well as 342 clicks. Based on the results of comparison using ANOVA, there was a significant difference for each placement location based on advertising metrics. Mobile location was chosen to be successful ads, because it produces the lowest CUC, amounting to Rp 691,- per click and 14% UCTR. Results of this study showed Facebook Ads was useful and cost-effective media to promote the product of SME, because it could be view by many people in the same time.

Keywords: marketing communication, social media, Facebook Ads, mobile location

Procedia PDF Downloads 354
8979 Effect of Punch Diameter on Optimal Loading Profiles in Hydromechanical Deep Drawing Process

Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

Abstract:

Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

Procedia PDF Downloads 431
8978 Drinking Water Quality Assessment Using Fuzzy Inference System Method: A Case Study of Rome, Italy

Authors: Yas Barzegar, Atrin Barzegar

Abstract:

Drinking water quality assessment is a major issue today; technology and practices are continuously improving; Artificial Intelligence (AI) methods prove their efficiency in this domain. The current research seeks a hierarchical fuzzy model for predicting drinking water quality in Rome (Italy). The Mamdani fuzzy inference system (FIS) is applied with different defuzzification methods. The Proposed Model includes three fuzzy intermediate models and one fuzzy final model. Each fuzzy model consists of three input parameters and 27 fuzzy rules. The model is developed for water quality assessment with a dataset considering nine parameters (Alkalinity, Hardness, pH, Ca, Mg, Fluoride, Sulphate, Nitrates, and Iron). Fuzzy-logic-based methods have been demonstrated to be appropriate to address uncertainty and subjectivity in drinking water quality assessment; it is an effective method for managing complicated, uncertain water systems and predicting drinking water quality. The FIS method can provide an effective solution to complex systems; this method can be modified easily to improve performance.

Keywords: water quality, fuzzy logic, smart cities, water attribute, fuzzy inference system, membership function

Procedia PDF Downloads 75
8977 Criticality Assessment of Power Transformer by Using Entropy Weight Method

Authors: Rattanakorn Phadungthin, Juthathip Haema

Abstract:

This research presents an assessment of the criticality of the substation's power transformer using the Entropy Weight method to enable more effective maintenance planning. Typically, transformers fail due to heat, electricity, chemical reactions, mechanical stress, and extreme climatic conditions. Effective monitoring of the insulating oil is critical to prevent transformer failure. However, finding appropriate weights for dissolved gases is a major difficulty due to the lack of a defined baseline and the requirement for subjective expert opinion. To decrease expert prejudice and subjectivity, the Entropy Weight method is used to optimise the weightings of eleven key dissolved gases. The algorithm to assess the criticality operates through five steps: create a decision matrix, normalise the decision matrix, compute the entropy, calculate the weight, and calculate the criticality score. This study not only optimises gas weighing but also greatly minimises the need for expert judgment in transformer maintenance. It is expected to improve the efficiency and reliability of power transformers so failures and related economic costs are minimized. Furthermore, maintenance schemes and ranking are accomplished appropriately when the assessment of criticality is reached.

Keywords: criticality assessment, dissolved gas, maintenance scheme, power transformer

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8976 Role of Feedbacks in Simulation-Based Learning

Authors: Usman Ghani

Abstract:

Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: simulation, feedback, training, hands-on, labs

Procedia PDF Downloads 377
8975 Dow Polyols near Infrared Chemometric Model Reduction Based on Clustering: Reducing Thirty Global Hydroxyl Number (OH) Models to Less Than Five

Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

Abstract:

Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

Procedia PDF Downloads 135
8974 Development and Characterization of Double Liposomes Based Dual Drug Delivery System for H. Pylori Targeting

Authors: Ashish Kumar Jain, Deepak Mishra

Abstract:

The objective of the present investigation was to prepare and evaluate a vesicular dual drug delivery system for effective management of mucosal ulcer. Inner encapsulating and Double liposomes were prepared by glass bead and reverse phase evaporation method respectively. The formulation consisted of inner liposomes bearing Ranitidine Bismuth Citrate (RBC) and outer liposomes encapsulating Amoxicillin trihydrate (AMOX). The optimized inner liposomes and double liposomes were extensively characterized for vesicle size, morphology, zeta potential, vesicles count, entrapment efficiency and in vitro drug release. In vitro, the double liposomes demonstrated a sustained release of AMOX and RBC viz 91.4±1.8% and 77.2±2.1% respectively at the end of 72 hr. Furthermore binding specificity and targeting propensity toward H. pylori (SKP-56) was confirmed by agglutination and in situ adherence assay. Reduction of the absolute alcohol induced ulcerogenic index from 3.01 ± 0.25 to 0.31 ± 0.09 and 100% H. pylori clearance rate was observed. These results suggested that double liposomes are potential vector for the development of dual drug delivery for effective treatment of H. pylori-associated peptic ulcer.

Keywords: double liposomes, H. pylori targeting, PE liposomes, glass-beads method, peptic ulcers

Procedia PDF Downloads 449
8973 Vaccine Development for Newcastle Disease Virus in Poultry

Authors: Muhammad Asif Rasheed

Abstract:

Newcastle disease virus (NDV), an avian orthoavulavirus, is a causative agent of Newcastle disease named (NDV) and can cause even the epidemics when the disease is not treated. Previously several vaccines based on attenuated and inactivated viruses have been reported, which are rendered useless with the passage of time due to versatile changes in viral genome. Therefore, we aimed to develop an effective multi-epitope vaccine against the haemagglutinin neuraminidase (HN) protein of 26 NDV strains from Pakistan through a modern immunoinformatic approaches. As a result, a vaccine chimaera was constructed by combining T-cell and B-cell epitopes with the appropriate linkers and adjuvant. The designed vaccine was highly immunogenic, non-allergen, and antigenic; therefore, the potential 3D-structureof multi epitope vaccine was constructed, refined, and validated. A molecular docking study of a multiepitope vaccine candidate with the chicken Toll-like receptor-4 indicated successful binding. An In silico immunological simulation was used to evaluate the candidate vaccine's ability to elicit an effective immune response. According to the computational studies, the proposed multiepitope vaccine is physically stable and may induce immune responses, whichsuggested it a strong candidate against 26 Newcastle disease virus strains from Pakistan. A wet lab study is under process to confirm the results.

Keywords: epitopes, newcastle disease virus, paramyxovirus virus, vaccine

Procedia PDF Downloads 120
8972 Organic Carbon Pools Fractionation of Lacustrine Sediment with a Stepwise Chemical Procedure

Authors: Xiaoqing Liu, Kurt Friese, Karsten Rinke

Abstract:

Lacustrine sediment archives rich paleoenvironmental information in lake and surrounding environment. Additionally, modern sediment is used as an effective medium for the monitoring of lake. Organic carbon in sediment is a heterogeneous mixture with varying turnover times and qualities which result from the different biogeochemical processes in the deposition of organic material. Therefore, the isolation of different carbon pools is important for the research of lacustrine condition in the lake. However, the numeric available fractionation procedures can hardly yield homogeneous carbon pools on terms of stability and age. In this work, a multi-step fractionation protocol that treated sediment with hot water, HCl, H2O2 and Na2S2O8 in sequence was adopted, the treated sediment from each step were analyzed for the isotopic and structural compositions with Isotope Ratio Mass Spectrometer coupled with element analyzer (IRMS-EA) and Solid-state 13C Nuclear Magnetic Resonance (NMR), respectively. The sequential extractions with hot-water, HCl, and H2O2 yielded a more homogeneous and C3 plant-originating OC fraction, which was characterized with an atomic C/N ratio shift from 12.0 to 20.8, and 13C and 15N isotopic signatures were 0.9‰ and 1.9‰ more depleted than the original bulk sediment, respectively. Additionally, the H2O2- resistant residue was dominated with stable components, such as the lignins, waxes, cutans, tannins, steroids and aliphatic proteins and complex carbohydrates. 6M HCl in the acid hydrolysis step was much more effective than 1M HCl to isolate a sedimentary OC fraction with higher degree of homogeneity. Owing to the extremely high removal rate of organic matter, the step of a Na2S2O8 oxidation is only suggested if the isolation of the most refractory OC pool is mandatory. We conclude that this multi-step chemical fractionation procedure is effective to isolate more homogeneous OC pools in terms of stability and functional structure, and it can be used as a promising method for OC pools fractionation of sediment or soil in future lake research.

Keywords: 13C-CPMAS-NMR, 13C signature, lake sediment, OC fractionation

Procedia PDF Downloads 299
8971 Post-Disaster Recovery and Impacts on Construction Resources: Case Studies of Queensland Catastrophic Events

Authors: Scott A. Abbott

Abstract:

This paper examines the increase in the occurrence of natural disasters worldwide and the need to support vulnerable communities in post-disaster recovery. Preparation and implementation of post-disaster recovery projects need to be improved to allow communities to recover infrastructure, housing, economically and socially following a catastrophe. With the continual rise in catastrophic events worldwide due to climate change, impacts on construction resources affect the ability for post-disaster recovery to be undertaken. This research focuses on case studies of catastrophic events in Queensland, Australia, to contribute to the body of knowledge and gain valuable insights on lessons learned from past events and how they have been managed. The aim of this research is to adopt qualitative data using semi-structured interviews from participants predominantly from the insurance sector to understand barriers that have previously and currently exist in post-disaster recovery. Existing literature was reviewed to reveal gaps in knowledge that needed to be tested. Qualitative data was collected and summarised from field research with the results analysed and discussed. Barriers that impacted post-disaster recovery included time, cost, and resource capability and capacity. Causal themes that impacted time and cost were identified as decision making, pre-planning, and preparedness, as well as effective communication across stakeholders. The research study applied a qualitative approach to the existing literature and case studies across Queensland, Australia, to identify existing and new barriers that impact post-disaster recovery. It was recommended to implement effective procurement strategies to assist in cost control; implement pre-planning and preparedness strategies across funder, contractor, and local governments; more effective and timely decision making to reduce time and cost impacts.

Keywords: construction recovery, cost, disaster recovery, resources, time

Procedia PDF Downloads 127
8970 Extraction of Dyes Using an Aqueous Two-Phase System in Stratified and Slug Flow Regimes of a Microchannel

Authors: Garima, S. Pushpavanam

Abstract:

In this work, analysis of an Aqueous two-phase (polymer-salt) system for extraction of sunset yellow dye is carried out. A polymer-salt ATPS i.e.; Polyethylene glycol-600 and anhydrous sodium sulfate is used for the extraction. Conditions are chosen to ensure that the extraction results in a concentration of the dye in one of the phases. The dye has a propensity to come to the Polyethylene glycol-600 phase. This extracted sunset yellow dye is degraded photo catalytically into less harmful components. The cloud point method was used to obtain the binodal curve of ATPS. From the binodal curve, the composition of salt and Polyethylene glycol -600 was chosen such that the volume of Polyethylene glycol-600 rich phase is low. This was selected to concentrate the dye from a dilute solution in a large volume of contaminated solution into a small volume. This pre-concentration step provides a high reaction rate for photo catalytic degradation reaction. Experimentally the dye is extracted from the salt phase to Polyethylene glycol -600 phase in batch extraction. This was found to be very fast and all dye was extracted. The concentration of sunset yellow dye in salt and polymer phase is measured at 482nm by ultraviolet-visible spectrophotometry. The extraction experiment in micro channels under stratified flow is analyzed to determine factors which affect the dye extraction. Focus will be on obtaining slug flow by adding nanoparticles in micro channel. The primary aim is to exploit the fact that slug flow will help improve mass transfer rate from one phase to another through internal circulation in dispersed phase induced by shear.

Keywords: aqueous two phase system, binodal curve, extraction, sunset yellow dye

Procedia PDF Downloads 358
8969 FSO Performance under High Solar Irradiation: Case Study Qatar

Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

Abstract:

Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

Procedia PDF Downloads 360
8968 Mooring Analysis of Duct-Type Tidal Current Power System in Shallow Water

Authors: Chul H. Jo, Do Y. Kim, Bong K. Cho, Myeong J. Kim

Abstract:

The exhaustion of oil and the environmental pollution from the use of fossil fuel are increasing. Tidal current power (TCP) has been proposed as an alternative energy source because of its predictability and reliability. By applying a duct and single point mooring (SPM) system, a TCP device can amplify the generating power and keep its position properly. Because the generating power is proportional to cube of the current stream velocity, amplifying the current speed by applying a duct to a TCP system is an effective way to improve the efficiency of the power device. An SPM system can be applied at any water depth and is highly cost effective. Simple installation and maintenance procedures are also merits of an SPM system. In this study, we designed an SPM system for a duct-type TCP device for use in shallow water. Motions of the duct are investigated to obtain the response amplitude operator (RAO) as the magnitude of the transfer function. Parameters affecting the stability of the SPM system such as the fairlead departure angle, current velocity, and the number of clamp weights are analyzed and/or optimized. Wadam and OrcaFlex commercial software is used to design the mooring line.

Keywords: mooring design, parametric analysis, RAO (Response Amplitude Operator), SPM (Single Point Mooring)

Procedia PDF Downloads 289
8967 Image Recognition Performance Benchmarking for Edge Computing Using Small Visual Processing Unit

Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

Abstract:

Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

Procedia PDF Downloads 155
8966 Trapping Efficiency of Highly Effective Slow Released Formulations of Biodegradable Waxes with Methyl Eugenol Against Bactrocera zonata

Authors: Waleed Afzal Naveed, Muhammd Dildar Gogi, Mubashir Iqbal, Muhammad Junaid Nisar, Muhammad Hamza Khaliq, Faisal Munir

Abstract:

Experiment was carried out to evaluate the performance of highly effective Slow-Released Formulations (SRF) of Methyl eugenol with Lanolin wax, Candellila wax, Bee-wax, Carnauba wax and paraffin wax in the orchard of University of Agriculture Faisalabad, Pakistan against fruit flies. The waxes were mixed with methyl eugenol in 1:9 ratio. The results revealed that SRF of Candellila, Paraffin, Bees and Carnauba wax attracted 13.77, 11, 8.15 and 7.23 flies/day/trap which was 2.6, 2, 1.5 and 1.4 times higher than standard respectively and exhibited 41.42%, 32.05%, 20.98% and 12.87% attractive index respectively, proved moderately attractive slow-released formulation to B. zonata and was catagorized as Class-II slow-released formulation (AI = 11-50%). However, SRF of Lanolin wax trapped 1.81 flies/day/trap which was 3 times less than standard and exhibited -61.86% attractive index proved little or non attractive slow-released formulation and was categorized as Class-I slow-released formulation for B. zonata (AI < 11%).

Keywords: biodegradable waxes, slow-released formulation, Bactrocera zonata, methyl euginol

Procedia PDF Downloads 259
8965 Investigating the Challenges and Opportunities for M-Government Implementation in Saudi Arabia

Authors: Anan Alssbaiheen, Steve Love

Abstract:

Given the lack of research into potential opportunities and challenges which are likely to be associated with the implementation of mobile services in developing countries including Saudi Arabia, the research reported here investigated the challenges and opportunities which are associated with the implementation of mobile government services in Saudi Arabia. By collecting data through surveys from 103 Saudi citizens and 46 employees working at the Ministry of Communication and Information Technology Saudi Arabia, this study indicates that the high level of mobile penetration in the country offers an opportunity for Saudi Arabian government to offer mobile government services in the country. The results also suggest that though a large percentage of populations do not have access to mobile technologies, there is still a strong desire among users for the provision of mobile government services. Moreover, the results suggest that effective implementation of mobile government services would help to increase the technological development of Saudi Arabia. However, there are certain challenges which may prevent the effective implementation of such services. First, there does not appear to be a sufficient level of understanding among the Saudi Arabian population about the benefits which are associated with mobile government services. Secondly, the results suggest that the implementation of the services needs to be closely tailored and personalised to the individual needs of target users. Finally, the lack of access to mobile technologies would be a challenge to the successful introduction of these services.

Keywords: challenges, e-government, mobile government, opportunities

Procedia PDF Downloads 414
8964 Infrastructure Change Monitoring Using Multitemporal Multispectral Satellite Images

Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

Procedia PDF Downloads 135
8963 The Challenges of Business Incubations: A Case of Malaysian Incubators

Authors: Logaiswari Indiran, Zainab Khalifah, Kamariah Ismail

Abstract:

Business incubators have now been recognized as effective tools in providing business assistance to start-up firms. In both developed and developing countries, the number of incubators is growing tremendously. As the birth rate of incubators increases, so do its challenges. Malaysia, as one of the developing countries in the Asian continent, has also established a number of business incubators to breed and foster the growth and survival of start-up firms. Thus, this study discusses the incubation model applied in Malaysia and the challenges faced by these incubators using secondary data including policies, previous literature, and reports related to Malaysian incubators. The findings of this study call the government to rethink the key role of incubator managers and staffs, internal structure of the incubator concept and process, intellectual properties management, strategic alliances with universities-industries and funding supports in enhancing the support provided by the business incubators in Malaysia. The key challenges highlighted in this study signal important policy lessons for other developing countries that aim to create and map an effective business incubator ecosystem.

Keywords: business incubators, incubation challenges, funding support, incubator managers, internal structure, start-up firms

Procedia PDF Downloads 275
8962 Effect of Steam Explosion of Crop Residues on Chemical Compositions and Efficient Energy Values

Authors: Xin Wu, Yongfeng Zhao, Qingxiang Meng

Abstract:

In China, quite low proportion of crop residues were used as feedstuff because of its poor palatability and low digestibility. Steam explosion is a physical and chemical feed processing technology which has great potential to improve sapidity and digestibility of crop residues. To investigate the effect of the steam explosion on chemical compositions and efficient energy values, crop residues (rice straw, wheat straw and maize stover) were processed by steam explosion (steam temperature 120-230°C, steam pressure 2-26kg/cm², 40min). Steam-exploded crop residues were regarded as treatment groups and untreated ones as control groups, nutritive compositions were analyzed and effective energy values were calculated by prediction model in INRA (1988, 2010) for both groups. Results indicated that the interaction between treatment and variety has a significant effect on chemical compositions of crop residues. Steam explosion treatment of crop residues decreased neutral detergent fiber (NDF) significantly (P < 0.01), and compared with untreated material, NDF content of rice straw, wheat straw, and maize stover lowered 21.46%, 32.11%, 28.34% respectively. Acid detergent lignin (ADL) of crop residues increased significantly after the steam explosion (P < 0.05). The content of crude protein (CP), ether extract (EE) and Ash increased significantly after steam explosion (P < 0.05). Moreover, predicted effective energy values of each steam-exploded residue were higher than that of untreated ones. The digestible energy (DE), metabolizable energy (ME), net energy for maintenance (NEm) and net energy for gain (NEg)of steam-exploded rice straw were 3.06, 2.48, 1.48and 0.29 MJ/kg respectively and increased 46.21%, 46.25%, 49.56% and 110.92% compared with untreated ones(P < 0.05). Correspondingly, the energy values of steam-exploded wheat straw were 2.18, 1.76, 1.03 and 0.15 MJ/kg, which were 261.78%, 261.29%, 274.59% and 1014.69% greater than that of wheat straw (P < 0.05). The above predicted energy values of steam exploded maize stover were 5.28, 4.30, 2.67 and 0.82 MJ/kg and raised 109.58%, 107.71%, 122.57% and 332.64% compared with the raw material(P < 0.05). In conclusion, steam explosion treatment could significantly decrease NDF content, increase ADL, CP, EE, Ash content and effective energy values of crop residues. The effect of steam explosion was much more obvious for wheat straw than the other two kinds of residues under the same condition.

Keywords: chemical compositions, crop residues, efficient energy values, steam explosion

Procedia PDF Downloads 250
8961 Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

Procedia PDF Downloads 139
8960 Efficient Callus Induction and Plant Regeneration from Mature Embryo Culture of Barley (Hordeum vulgare L.) Genotypes

Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

Abstract:

Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS1 and MS2), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS1 is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS1 is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: barley, callus, embryo culture, mature embryo

Procedia PDF Downloads 326
8959 Cryptographic Resource Allocation Algorithm Based on Deep Reinforcement Learning

Authors: Xu Jie

Abstract:

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

Keywords: cloud computing, cryptography on-demand service, reinforcement learning, workflow scheduling

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8958 Computational Model for Predicting Effective siRNA Sequences Using Whole Stacking Energy (ΔG) for Gene Silencing

Authors: Reena Murali, David Peter S.

Abstract:

The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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8957 Machine Learning Classification of Fused Sentinel-1 and Sentinel-2 Image Data Towards Mapping Fruit Plantations in Highly Heterogenous Landscapes

Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

Abstract:

Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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8956 A Proposal to Tackle Security Challenges of Distributed Systems in the Healthcare Sector

Authors: Ang Chia Hong, Julian Khoo Xubin, Burra Venkata Durga Kumar

Abstract:

Distributed systems offer many benefits to the healthcare industry. From big data analysis to business intelligence, the increased computational power and efficiency from distributed systems serve as an invaluable resource in the healthcare sector to utilize. However, as the usage of these distributed systems increases, many issues arise. The main focus of this paper will be on security issues. Many security issues stem from distributed systems in the healthcare industry, particularly information security. The data of people is especially sensitive in the healthcare industry. If important information gets leaked (Eg. IC, credit card number, address, etc.), a person’s identity, financial status, and safety might get compromised. This results in the responsible organization losing a lot of money in compensating these people and even more resources expended trying to fix the fault. Therefore, a framework for a blockchain-based healthcare data management system for healthcare was proposed. In this framework, the usage of a blockchain network is explored to store the encryption key of the patient’s data. As for the actual data, it is encrypted and its encrypted data, called ciphertext, is stored in a cloud storage platform. Furthermore, there are some issues that have to be emphasized and tackled for future improvements, such as a multi-user scheme that could be proposed, authentication issues that have to be tackled or migrating the backend processes into the blockchain network. Due to the nature of blockchain technology, the data will be tamper-proof, and its read-only function can only be accessed by authorized users such as doctors and nurses. This guarantees the confidentiality and immutability of the patient’s data.

Keywords: distributed, healthcare, efficiency, security, blockchain, confidentiality and immutability

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8955 Low Frequency Sound Intervention: Therapeutic Impact and Applications

Authors: Heidi Ahonen

Abstract:

Since antiquity, many cultures have seemingly known the power of low frequencies, incorporating them in healing practices through drumming, singing, humming, etc. Many music therapists recognize there is something in music that is transformative enough to make a difference in people’s lives. This paper summarizes the key findings of several low-frequency research with various client populations conducted by the author. Utilizing low-frequency sound (30 or 40 Hz) may have diverse therapeutic impacts: (1) Calming effect – decreased agitation (autism, brain injury, AD, dementia) (2) Muscle relaxation (CP & spasticity & pain/after surgery patients, MS, fibromyalgia) (3) Relaxation/stress release (anxiety, stress, PTSD, trauma, insomnia) (4) Muscular/motor functioning/ decrease of tremor (CP, MS, Parkinson) (5) Increase in alertness, cognitive awareness & short-term memory function (brain injury, severe global developmental delay, AD) (6) Increased focus (AD, PTSD, trauma). The paper will conclude by presenting ideas informing the clinical practice. Future studies need to investigate what frequencies are effective for particular client populations and why, what theories can explain the effect, and finally, something that has been long debated - is it auditive or kinaesthetic stimulation or the combination of both that is effective?

Keywords: low frequency, 40 Hz, sound, neuro disability

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8954 Grand Paris Residential Real Estate as an Effective Hedge against Inflation

Authors: Yasmine Essafi Zouari, Aya Nasreddine

Abstract:

Following a long inflationary period from the post-war era to the mid-1980s (+10.1% annually), France went through a moderate inflation period between 1986 and 2001 (+2.1% annually) and even lower inflation between 2002 and 2016 (+1.4% annually). In 2022, inflation in France increased rapidly and reached 4.5% over one year in March, according to INSEE estimates. Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. Considering a mixed-asset portfolio composed of housing assets (residential real estate in 150 Grand Paris communes) as well as financial assets, and using both correlation and regression analysis, results confirm the attribute of the direct housing investment as an inflation hedge especially particularly against its unexpected component. Further, cash and bonds were found to provide respectively a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant positive hedge against expected inflation.

Keywords: direct housing, inflation, hedging ability, optimal portfolio, Grand Paris metropolis

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8953 Treatment of the Modern Management Mechanism of the Debris Flow Processes Expected in the Mletiskhevi

Authors: G. Chakhaia, S. Gogilava, L. Tsulukidze, Z. Laoshvili, I. Khubulava, S. Bosikashvili, T. Gugushvili

Abstract:

The work reviewed and evaluated various genesis debris flow phenomena recently formatted in the Mletiskhevi, accordingly it revealed necessity of treatment modern debris flow against measures. Based on this, it is proposed the debris flow against truncated semi cone shape construction, which elements are contained in the car’s secondary tires. its constituent elements (sections), due to the possibilities of amortization and geometric shapes is effective and sustainable towards debris flow hitting force. The construction is economical, because after crossing the debris flows in the river bed, the riverbed is not cleanable, also the elements of the building are resource saving. For assessment of influence of cohesive debris flow at the construction and evaluation of the construction effectiveness have been implemented calculation in the specific assumptions with approved methodology. According to the calculation, it was established that after passing debris flow in the debris flow construction (in 3 row case) its hitting force reduces 3 times, that causes reduce of debris flow speed and kinetic energy, as well as sedimentation on a certain section of water drain in the lower part of the construction. Based on the analysis and report on the debris flow against construction, it can be said that construction is effective, inexpensive, technically relatively easy-to-reach measure, that’s why its implementation is prospective.

Keywords: construction, debris flow, sections, theoretical calculation

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8952 A Review of the Effects of Exercise in Preventing Migraine Headaches

Authors: Afsaneh Soltani, Zahra Mohajer

Abstract:

Migraine is one of the most common chronic neurological diseases. Migraines affect different aspects of life. Severe migraine headaches lead to dysfunction, a reduced presence at work, and decreased ability to think and make decisions. Non-pharmacological treatments play a very important role in controlling and preventing migraine headaches. A healthy lifestyle helps control migraine headaches. Migraine headaches can be reduced by following these steps: Avoiding stress, eating regularly and avoiding hunger and thirst, avoiding stimulants such as chocolate, caffeine, and cigarettes, following a regular bedtime routine, or avoiding sleep deprivation. Exercise a lot, and do regular exercise (and prevent obesity). Non-pharmacological treatment is especially important in pregnant women and children because in these cases, medical treatments are not preferred due to the many side effects. Exercise is one of the most effective and uncomplicated non-pharmacological alternatives in the treatment of migraine headaches. Exercising for episodic migraines is a safe, effective, and promising complementary treatment option. Numerous studies have shown that aerobic exercise reduces the severity and duration of migraine headaches. Effective aerobic exercise includes cycling and brisk walking. Exercise improves the quality of life and reduces the use of medication in people with migraines. Patients who exercise have fewer migraine days, resulting in better personal, social, and occupational performance. Several studies have shown that pain intensity and frequency in patients who exercise regularly decreased significantly after exercise compared to controls who did not exercise. According to a study, regular exercise reduces the levels of interleukins, especially IL-12P70, which reduces anxiety and reduces the number of days of migraine in patients. An article has shown that endurance exercise reduces the number of migraine days and also increases cerebrovascular health in migraine patients. According to studies, the minimum duration of exercise to achieve a positive effect of exercise in patients with migraine is 3 months (12 weeks) and 40 minutes three times a week.

Keywords: exercise, headache, migraine, physical activity

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8951 Bio Ethanol Production From the Co-Mixture of Jatropha Carcus L. Kernel Cake and Rice Straw

Authors: Felix U. Asoiro, Daniel I. Eleazar, Peter O. Offor

Abstract:

As a result of increasing energy demands, research in bioethanol has increased in recent years all through the world, in abide to partially or totally replace renewable energy supplies. The first and third generation feedstocks used for biofuel production have fundamental drawbacks. Waste rice straw and cake from second generation feedstock like Jatropha curcas l. kernel (JC) is seen as non-food feedstock and promising candidates for the industrial production of bioethanol. In this study, JC and rice husk (RH) wastes were characterized for proximate composition. Bioethanol was produced from the residual polysaccharides present in rice husk (RH) and Jatropha seed cake by sequential hydrolytic and fermentative processes at varying mixing proportions (50 g JC/50 g RH, 100 g JC/10 g RH, 100 g JC/20 g RH, 100 g JC/50 g RH, 100 g JC/100 g RH, 100 g JC/200 g RH and 200 g JC/100 g RH) and particle sizes (0.25, 0.5 and 1.00 mm). Mixing proportions and particle size significantly affected both bioethanol yield and some bioethanol properties. Bioethanol yield (%) increased with an increase in particle size. The highest bioethanol (8.67%) was produced at a mixing proportion of 100 g JC/50g RH at 0.25 mm particle size. The bioethanol had the lowest values of specific gravity and density of 1.25 and 0.92 g cm-3 and the highest values of 1.57 and 0.97 g cm-3 respectively. The highest values of viscosity (4.64 cSt) were obtained with 200 g JC/100 g RH, at 1.00 mm particle size. The maximum flash point and cloud point values were 139.9 oC and 23.7oC (100 g JC/200 g RH) at 1 mm and 0.5 mm particle sizes respectively. The maximum pour point value recorded was 3.85oC (100 g JC/50 g RH) at 1 mm particle size. The paper concludes that bioethanol can be recovered from JC and RH wastes. JC and RH blending proportions as well as particle sizes are important factors in bioethanol production.

Keywords: bioethanol, hydrolysis, Jatropha curcas l. kernel, rice husk, fermentation, proximate composition

Procedia PDF Downloads 96