Search results for: data source

Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

Procedia PDF Downloads 149

Authors: Sreejith Jayachandran, Mojtaba Ghods, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software; meanwhile, some people forget to do their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience, while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. Engineers and medical experts have come together to give birth to a new device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. Various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data is collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud, and stores it there, and the processed digital data is instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors and other health staff can collect this data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate this data for awareness of the patient's current health status. Moreover, the system is connected to a Global Positioning System (GPS) module. In emergencies, the concerned team can position the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud, and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the RHMS is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system (11×10×10) cm³ with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured with 100 GBP, which can be used not only for health systems, it can be used for numerous other uses including aerospace and transportation sections.

Keywords: embedded technology, telemonitoring system, microcontroller, Arduino UNO, cloud storage, global positioning system, remote health monitoring system, alert system

Procedia PDF Downloads 90

Authors: Weera Weerasophon

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The purpose of this research was to study Tourists’s satisfaction strategies case of Tourists who attended and shopped in Chatuchak weekend market (Bangkok) in order to improve service operation of Chatuchak weekend market to serve tourists’ need to impress them. The researcher used the marketing mix as a main factor that affect to tourist satisfaction. This research was emphasized as quantitative research as 400 of questionnaires were used for collecting the data from international tourists around Chatuchak weekend market that questionnaires divided in to 3 parts as a personal information part, satisfaction of marketing/services and facilities and suggestion part. After collecting all the data that would be processed in statistic program of SPSS to use for analyze the data later on. The result is described that most of international tourists satisfied Chatuchak weekend market in the level of 4 as more satisfaction for example friendly staff, Chatuchak information, price of product, facilities and service by the way, the environment of Chatuchak weekend market is the most satisfaction level.

Keywords: Chatuchak, satisfaction, Thailand tourism, marketing mix, tourists

Procedia PDF Downloads 360

Authors: D. Wattanasiriwech, S. Wattanasiriwech

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In this paper, attempt to synthesize designed cordierite-mullite system with various ratios was performed using a solid-state method. Alumina, quartz, magnesia, and talc were used as starting materials for the synthesis. Talc was added for two purposes; to assist the reaction progress and to be the Mg source. The raw materials were mixed and fired at 1350°C for 2 h and 1400°C for 2 and 4 h. The resulting phase compositions were analysed using the Reference Intensity Ratio (RIR) semi-quantitative analysis method. The highest amount of cordierite up to Cordierite phase 96% could be obtained at the firing scheme of 1400°C for 4 h in the C100-M0. Mullite could not be formed at the selected scheme if talc did not present so no pure mullite was observed in the selected firing regime. The highest amount of mullite co-existed with cordierite and other phases were 74%.

Keywords: RIR semi-quantitative analysis, cordierite-mullite system, solid state synthesis, X-Ray diffraction

Procedia PDF Downloads 169

Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

Procedia PDF Downloads 383

Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

Procedia PDF Downloads 225

Authors: Kiyanoush Ghalavand

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We have a complex paradox in the agriculture and environment sectors in the age of technology. In the one side, the achievements of the science and information ages are shaping to come that is very dangerous than ever last decades. The progress of the past decades is historic, connecting people, empowering individuals, groups, and states, and lifting a thousand people out of land and poverty in the process. Floods are the most frequent natural hazards damaging and recurring of all disasters in Iran. Additionally, floods are morphing into new and even more devastating forms in recent years. Khuzestan and Lorestan Provinces experienced heavy rains that began on March 28, 2019, and led to unprecedented widespread flooding and landslides across the provinces. The study was based on both secondary and primary data. For the present study, a questionnaire-based primary survey was conducted. Data were collected by using a specially designed questionnaire and other instruments, such as focus groups, interview schedules, inception workshops, and roundtable discussions with stakeholders at different levels. Farmers in Khuzestan and Lorestan provinces were the statistical population for this study. Data were analyzed with several software such as ATLASti, NVivo SPSS Win, ،E-Views. According to a factorial analysis conducted for the present study, 10 groups of factors were categorized climatic, economic, cultural, supportive, instructive, planning, military, policymaking, geographical, and human factors. They estimated 71.6 percent of explanatory factors of flood management obstacles in the agricultural sector in Lorestan and Khuzestan provinces. Several recommendations were finally made based on the study findings.

Keywords: chaos theory, natural hazards, risks, environmental risks, paradox

Procedia PDF Downloads 146

Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

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BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

Procedia PDF Downloads 154

Authors: Ebobo Urowoli Christiana

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The Nigerian Prison Service statistics of 2007; 2009 revealed that though crime in the past was ascribed to men, but today there is a steady increase in the population of women involved in crime. This study focused on the investigation of female criminality in Lagos State: A case of Armed Robbery. Its major objective was to find out if there is an increase or decrease in female involvement in armed robbery and its growth rate. The major research question is 'Is there an increase in the perpetration of armed robbery by females in Lagos State?' the null hypotheses is 'There is no significant increase in the perpetration of armed robbery by females in Lagos State.' As a result, this study adopted the survey design, purposive sampling method and a sample size of 120 respondents. The rational choice theory was used to explain the reason for female involvement in armed robbery. Both primary and secondary data was generated for this study; the primary data was collected from the criminal records in Lagos State Police Command, Panti while the Quantitative data was collected using the questionnaire from 120 female detainees and inmates. The data collected was analyzed using the simple frequency tables and percentages and chi square was used to test for relationships. The study revealed a persistent rise in the prevalence of female armed robbery and recommended that youths should be equipped with educational/vocational skills in order to lead responsible lives.

Keywords: criminality, armed robbery, female, police commands, panti, nature

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

Procedia PDF Downloads 548

Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

Procedia PDF Downloads 168

Authors: Panupong Makvichian

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Global Navigation Satellite System (GNSS) is nowadays a common technology that improves navigation functions in our life. Additionally, GNSS is also being employed on behalf of an accurate atmospheric sensor these times. Meteorology is a practical application of GNSS, which is unnoticeable in the background of people’s life. GNSS Precise Point Positioning (PPP) is a positioning method that requires data from a single dual-frequency receiver and precise information about satellite positions and satellite clocks. In addition, careful attention to mitigate various error sources is required. All the above data are combined in a sophisticated mathematical algorithm. At this point, the research is going to demonstrate how GNSS and PPP method is capable to provide high-precision estimates, such as 3D positions or Zenith tropospheric delays (ZTDs). ZTDs combined with pressure and temperature information allows us to estimate the water vapor in the atmosphere as precipitable water vapor (PWV). If the process is replicated for a network of GNSS sensors, we can create thematic maps that allow extract water content information in any location within the network area. All of the above are possible thanks to the advances in GNSS data processing. Therefore, we are able to use GNSS data for climatic trend analysis and acquisition of the further knowledge about the atmospheric water content.

Keywords: GNSS, precise point positioning, Zenith tropospheric delays, precipitable water vapor

Procedia PDF Downloads 198

Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

Procedia PDF Downloads 361

Authors: Farrukh Jamil, Ala'a H. Al-Muhtaseb, Lamya Al-Haj, Mohab A. Al-Hinai

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Date pits are major agricultural waste produced in Oman. Current work was conducted to produce jet fuel and green diesel from hydrodeoxygenation of Date pits oil in the presence of Pd/C catalyst. The hydrodeoxygenation of Date pits oil occurred to be highly efficient at following mild operating conditions such as conditions temperature 300°C pressure 10bar with continuous stirring at 500rpm. Detailed product characterization revealed that large fraction of paraffinic hydrocarbons was found which accounts up to 91.1 % which attributed due to efficient hydrodeoxygenation. Based on the type of components in product oil, it was calculated that the maximum fraction of hydrocarbons formed lies within the range of green diesel 72.0 % then jet fuel 30.4% by using Pd/C catalysts. The densities of product oil were 0.88 kg/m³, the viscosity of products calculated was 3.49 mm²/s. Calorific values for products obtained were 44.11 MJ/kg when Pd/C catalyst was used for hydrodeoxygenation. Based on products analysis it can conclude that Date pits oil could successfully utilize for synthesizing green diesel and jet fuel fraction.

Keywords: biomass, jet fuel, green diesel, catalyst

Procedia PDF Downloads 294

Authors: Shobrina Silmi Qori Tarlita, Fariz Kukuh Harwinda

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Indonesia has 81.000 kilometers coastal line and 70% water surface which is known as the country who has a huge potential in fisheries sector and also which is able to support more than 50 % of Gross Domestic Product. But according to Department of Marine and Fisheries data, fisheries sector supported only 20% of Total GDP in 1998. Not only that, the highest decline in fisheries sector income occured in 2009. Those conditions occur, because of some factors contributed to the lack of integrated working platform for the fisheries and marine management in some areas which have a high productivity to increase the economical profit every year for the country, especially Indonesia, besides the labor requirement for every company, whether a big company or smaller one, depends on the natural condition that makes a lot of people become unemployed if the weather condition or any other conditions dealing with the natural condition is bad for creating fisheries and marine management, especially in aquaculture and fish – captured operation. Not only those, a lot of fishermen, especially in Indonesia, mostly make their job profession as an additional job or side job to fulfill their own needs, although they are averagely poor. Another major problem are the lack of the sustainable developmental program to stabilize the productivity of fisheries and marine natural source, like protecting the environment for fish nursery ground and migration channel, that makes the low productivity of fisheries and marine natural resource, even though the growth of the society in Indonesia has increased for years and needs more food resource to comply the high demand nutrition for living. The development of Minapolitan Area is one of the alternative solution to build a better place for aqua-culturist as well as the fishermen which focusing on systemic and business effort for fisheries and marine management. Minapolitan is kind of integration area which gathers and integrates the ones who is focusing their effort and business in fisheries sector, so that Minapolitan is capable of triggering the fishery activity on the area which using Minapolitan management intensively. From those things, finally, Minapolitan is expected to reinforce the sustainable development through increasing the productivity of fish – capturing operation as well as aquaculture, and it is also expected that Minapolitan will be able to increase GDP, the earning for a lot of people and also will be able to bring prosperity around the world. From those backgrounds, this paper will explain more about the Minapolitan Area and the design of reinforcing the Minapolitan Area by zonation in the Fishery and Marine exploitation area with high productivity as well as low productivity. Hopefully, this solution will be able to answer the economical and social issue for declining food resource, especially fishery and marine resource.

Keywords: Minapolitan, fisheries, economy, Indonesia

Procedia PDF Downloads 463

Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

Procedia PDF Downloads 608

Authors: Alida Sandison, Louise A. Stroud

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Narcissism is a personality configuration which has both normal and pathological personality expressions. Narcissism is highly complex, and is linked to a broad field of research. There are both dimensional and categorical conceptualisations of narcissism, and a variety of theoretical formulations that have been put forward to understand the narcissistic personality configuration. Currently, Kernberg’s Object Relations theory is well supported for this purpose. The complexity and particular defense mechanisms at play in the narcissistic personality make it a difficult personality configuration worth further research. Psychobiography as a methodology allows for the exploration of the lived life, and is thus a useful methodology to surmount these inherent challenges. Narcissism has been a focus of academic interest for a long time, and although there is a lot of research done in this area, to the researchers' knowledge, narcissistic dynamics have never been explored within a psychobiographical format. Thus, the primary aim of the research was to explore and describe narcissism in the life of Howard Hughes, with the objective of gaining further insight into narcissism through the use of this unconventional research approach. Hughes was chosen as subject for the study as he is renowned as an eccentric billionaire who had his revolutionary effect on the world, but was concurrently disturbed within his personal pathologies. Hughes was dynamic in three different sectors, namely motion pictures, aviation and gambling. He became more and more reclusive as he entered into middle age. From his early fifties he was agoraphobic, and the social network of connectivity that could reasonably be expected from someone in the top of their field was notably distorted. Due to his strong narcissistic personality configuration, and the interpersonal difficulties he experienced, Hughes represents an ideal figure to explore narcissism. The study used a single case study design, and purposive sampling to select Hughes. Qualitative data was sampled, using secondary data sources. Given that Hughes was a famous figure, there is a plethora of information on his life, which is primarily autobiographical. This includes books written about his life, and archival material in the form of newspaper articles, interviews and movies. Gathered data were triangulated to avoid the effect of author bias, and increase the credibility of the data used. It was collected using Yin’s guidelines for data collection. Data was analysed using Miles and Huberman strategy of data analysis, which consists of three steps, namely, data reduction, data display, and conclusion drawing and verification. Patterns which emerged in the data highlighted the defense mechanisms used by Hughes, in particular that of splitting and projection, in defending his sense of self. These defense mechanisms help us to understand the high levels of entitlement and paranoia experienced by Hughes. Findings provide further insight into his sense of isolation and difference, and the consequent difficulty he experienced in maintaining connections with others. Findings furthermore confirm the effectiveness of Kernberg’s theory in understanding narcissism observing an individual life.

Keywords: Howard Hughes, narcissism, narcissistic defenses, object relations

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Breno M. Castilho

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The Iron Ore Quadrangle, located in the state of Minas Gerais, Brazil is responsible for most of the country’s iron ore production. As a result, some of the biggest tailings dams in the country are located in this area. In recent years, several major failure events have happened in Tailings Storage Facilities (TSF) located in the Iron Ore Quadrangle. Some of these failures were found to be caused by liquefaction flowslides. This paper presents Piezocone Penetration Test (CPTu) data that was used, by applying Olson and Peterson methods, for the liquefaction susceptibility assessment of the iron ore tailings that are typically found in most TSF in the area. Piezocone data was also used to determine the steady-state strength of the tailings so as to allow for comparison with its drained strength. Results have shown great susceptibility for liquefaction to occur in the studied tailings and, more importantly, a large reduction in its strength. These results are key to understanding the failures that took place over the last few years.

Keywords: Piezocone Penetration Test CPTu, iron ore tailings, mining, liquefaction susceptibility assessment

Procedia PDF Downloads 233

Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

Procedia PDF Downloads 217

Authors: Muhammad Ali

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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 125

Authors: Sheetla Prasad

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The objective of this study is ‘discovering the real psyche of human beings for prediction of mode, direction and strength of the potential of actions of the individual. The human face was taken as a source of central point to search for the route of real psyche. Analysis of the face architecture (shape and salient features of face) was done by three directional photographs ( 600 left and right and camera facing) of human beings. The shapes and features of the human face were scaled in 177 units on the basis of face–features locations (FFL). The mathematical analysis was done of FFLs by self developed and standardized formula. At this phase, 800 samples were taken from the population of students, teachers, advocates, administrative officers, and common persons. The finding shows that real psyche has two external rings (ER). These ER are itself generator of two independent psyches (manifested and manipulated). Prima-facie, it was proved that micro differences in FFLs have potential to predict the state of art of the human psyche. The potential of psyches was determined by the saving and distribution of mental energy. It was also mathematically proved.

Keywords: face architecture, psyche, potential, face functional ratio, external rings

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Authors: N. Gigauri, A. Surmava, L. Intskirveli, V. Kukhalashvili, S. Mdivani

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The subject of our study is atmospheric air pollution with numerical modeling. In the presented article, as the object of research, there is chosen city Tbilisi, the capital of Georgia, with a population of one and a half million and a difficult terrain. The main source of pollution in Tbilisi is currently vehicles and construction dust. The concentrations of dust and PM (Particulate Matter) were determined in the air of Tbilisi and in its vicinity. There are estimated their monthly maximum, minimum, and average concentrations. Processes of dust propagation in the atmosphere of the city and its surrounding territory are modelled using a 3D regional model of atmospheric processes and an admixture transfer-diffusion equation. There were taken figures of distribution of the polluted cloud and dust concentrations in different areas of the city at different heights and at different time intervals with the background stationary westward and eastward wind. It is accepted that the difficult terrain and mountain-bar circulation affect the deformation of the cloud and its spread, there are determined time periods when the dust concentration in the city is greater than MAC (Maximum Allowable Concentration, MAC=0.5 mg/m³).

Keywords: air pollution, dust, numerical modeling, PM-particles

Procedia PDF Downloads 140

Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah

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Finite element approach have been used via three-dimensional models by using Altair Hyper Work, a commercially available software, to describe heat gradients along the welding zones (axially and coronaly) in Friction Stir Welding (FSW). Transient thermal finite element analyses are performed in AA 6061-T6 Aluminum Alloy to obtain temperature distribution in the welded aluminum plates during welding operation. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and work piece is used in the analysis. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the work piece.

Keywords: Frictions Stir Welding (FSW), temperature distribution, Finite Element Method (FEM), altair hyperwork

Procedia PDF Downloads 537

Authors: Kugbeme Isumonah

Abstract:

The Nigerian State has continued to battle huge power supply challenges. Erratic supply, low voltage, and billing issues characterize its power sector. Solar power is increasingly being advocated for as a potential to Nigeria’s energy crisis. This study investigates how the Nigerian public perceives solar power. It employs the use of an open-ended online survey eliciting responses from participants resident in two of South-West Nigeria’s largest cities (Lagos and Ibadan). The study found that general attitudes towards solar power are positive, and the energy source is viewed with great optimism within the context of solutions to Nigeria’s energy issues. It also found no significant variation in public perceptions of solar power along demographic lines. Further, it found that finance represents the biggest barrier to broader solar power adoption. The results of this study provide evidence for policy formulation geared towards addressing finance difficulties that currently impede expansion of solar power use in Nigeria.

Keywords: public perceptions, solar energy, Nigeria, attitudes

Procedia PDF Downloads 107

Authors: M. Makary

Abstract:

Indigenous tourism is nowadays one of the fastest growing sections of the tourism industry. Nevertheless, it does not yet receive attention on the agenda of public tourism policies in Egypt; however, there are various tourism initiatives in indigenous areas throughout the country mainly in the Nubia region, which located in Upper Egypt, where most of Egypt's indigenous Nubians are concentrated. Considering indigenous tourism can lead to both positive and negative impacts on the indigenous communities the main aim of this study is to analyze the socio-cultural and economic impacts of the indigenous tourism on the indigenous communities in Egypt: the case study of Nubians. Qualitative and quantitative approaches of data collection were designed and applied in conducting this study. Semi-structured interviews, focus groups, and the observations are the main preliminary data collection techniques used in this study while, the secondary data were sourced from articles, statistics, dissertations, and websites. The research concludes that indigenous tourism offers a strong motivation to save the identity of the indigenous communities and to foster their economic development. However, it also has negative impacts on their society.

Keywords: indigenous tourism, sustainable tourism, Indigenous communities, Nubians

Procedia PDF Downloads 245

Authors: James Kinyua Gitonga, Toshio Fujimi

Abstract:

Vulnerability assessment and analysis is essential to solving the degree of damage and loss as a result of natural disasters. Urban flooding causes a major economic loss and casualties, at Mathare residential area in Nairobi, Kenya. High population caused by rural-urban migration, Unemployment, and unplanned urban development are among factors that increase flood vulnerability in Mathare area. This study aims to analyse flood risk physical vulnerabilities in Mathare based on scientific data, research data that includes the Rainfall data, River Mathare discharge rate data, Water runoff data, field survey data and questionnaire survey through sampling of the study area have been used to develop the risk curves. Three structural types of building were identified in the study area, vulnerability and risk curves were made for these three structural types by plotting the relationship between flood depth and damage for each structural type. The results indicate that the structural type with mud wall and mud floor is the most vulnerable building to flooding while the structural type with stone walls and concrete floor is least vulnerable. The vulnerability of building contents is mainly determined by the number of floors, where households with two floors are least vulnerable, and households with a one floor are most vulnerable. Therefore more than 80% of the residential buildings including the property in the building are highly vulnerable to floods consequently exposed to high risk. When estimating the potential casualties/injuries we discovered that the structural types of houses were major determinants where the mud/adobe structural type had casualties of 83.7% while the Masonry structural type had casualties of 10.71% of the people living in these houses. This research concludes that flood awareness, warnings and observing the building codes will enable reduce damage to the structural types of building, deaths and reduce damage to the building contents.

Keywords: flood loss, Mathare Nairobi, risk curve analysis, vulnerability

Procedia PDF Downloads 239

Authors: Ali Meawad Ahmad, Hosny A. Abdelrahman

Abstract:

Chicken meat is a good source of protein of high biological value which contains most of essential amino-acids with high proportion of unsaturated fatty acids and low cholesterol level. Besides, it contain many vitamins as well as minerals which are important for the human body. Therefore, a total of 150 frozen chicken meat product samples, 800g each within their shelf-life, were randomly collected from commercial markets from Egypt (75 samples) and Saudi Arabian (75 samples) for chemical evaluation. The mean values of fat% in the examined samples of Egyptian and Saudi markets were 16.0% and 4.6% for chicken burger; 15.0% and 11% for nuggets and 11% and 11% for strips respectively. The mean values of moisture % in the examined samples of Egyptian and Saudi markets were 67.0% and 81% for chicken burger; 66.0% and 78% for nuggets and 71.0% and 72% for strips respectively. The mean values of protein % in the examined samples of Egyptian and Saudi markets were 15% and 17% for chicken burger; 16% and 16% for nuggets and 16% and 17% for strips respectively. The obtained results were compared with the Egyptian slandered and suggestions for improving the chemical quality of chicken products were given.

Keywords: chicken meat, nutrition, Egypt, markets

Procedia PDF Downloads 568

Authors: Rosemary Hiscock, Clive Sabel, David Manley, Sam Wren-Lewis

Abstract:

As part of the Happy City Index Project, Happy City have developed a survey instrument to measure experienced wellbeing: how people are feeling and functioning in their everyday lives. The survey instrument, called the Happiness Pulse, was developed in partnership with the New Economics Foundation (NEF) with the dual aim of collecting citywide wellbeing data and engaging individuals and communities in the measurement and promotion of their own wellbeing. The survey domains and items were selected through a review of the academic literature and a stakeholder engagement process, including local policymakers, community organisations and individuals. The Happiness Pulse was included in the Bristol pilot of the Happy City Index (n=722). The experienced wellbeing items were subjected to factor analysis. A reduced number of items to be included in a revised scale for future data collection were again entered into a factor analysis. These revised factors were tested for reliability and validity. Among items to be included in a revised scale for future data collection three factors emerged: Be, Do and Connect. The Be factor had good reliability, convergent and criterion validity. The Do factor had good discriminant validity. The Connect factor had adequate reliability and good discriminant and criterion validity. Some age, gender and socioeconomic differentiation was found. The properties of a new scale to measure experienced wellbeing, intended for use by municipal authorities, are described. Happiness Pulse data can be combined with local data on wellbeing conditions to determine what matters for peoples wellbeing across a city and why.

Keywords: city wellbeing , community wellbeing, engaging individuals and communities, measuring wellbeing and happiness

Procedia PDF Downloads 261