Search results for: data communication

Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

Procedia PDF Downloads 315

Authors: Jochen Edmund Kerschenbauer, Roman Salinger, Daniel Strametz

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Insufficient informal communication systems can lead to the first crisis (‘Crisis of Leadership’) for start-ups. Management Control Systems (MCS) are one way for high-technology start-ups to successfully overcome these problems. So far the literature has investigated the incubation of a start-up, but focused less on the post-incubation stage. This paper focuses on the use of MCS in post-incubation and, if failed start-ups agree, on how MCS are used. We conducted 14 semi-structured interviews for this purpose, to obtain our results. The overall conclusion is that the majority of the companies were closed down due to a combination of strategic, operative and financial reasons.

Keywords: closed down, high-technology, incubation, levers of control, management control systems, post-incubation, start-ups

Procedia PDF Downloads 1086

Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

Procedia PDF Downloads 117

Authors: Peris Wanjiku

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The objective of this paper is to describe the development and implications of a national nursing workforce analytical system in Kenya. Findings: Creating a national electronic nursing workforce analytical system provides more reliable information on nurses ‘national demographics, migration patterns, and workforce capacity and efficiency. Data analysis is most useful for human resources for health (HRH) planning when workforce capacity data can be linked to worksite staffing requirements. As a result of establishing this database, the Kenya Ministry of Health has improved its capability to assess its nursing workforce and document important workforce trends, such as out-migration. Current data identify the United States as the leading recipient country of Kenyan nurses. The overwhelming majority of Kenyan nurses who decide to out-migrate are amongst Kenya’s most qualified. Conclusions: The Kenya nursing database is a first step toward facilitating evidence-based decision-making in HRH. This database is unique to developing countries in sub-Saharan Africa. Establishing an electronic workforce database requires long-term investment and sustained support by national and global stakeholders.

Keywords: analytical, information, health, migration

Procedia PDF Downloads 90

Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Lynndee Kemmet

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The U.S. military plays an increasing role in supporting political stability efforts, and this includes efforts to prevent the food insecurity that can trigger political and social instability. This paper presents a model that assists military commanders in identifying variables that impact food production and distribution in their areas of operation (AO), in identifying connections between variables and in assessing the impacts of those variables on food production and distribution. Through use of the model, military units can better target their data collection efforts and can categorize and analyze data within the data categorization framework most widely-used by military forces—PMESII-PT (Political, Military, Economic, Infrastructure, Information, Physical Environment and Time). The model provides flexibility of analysis in that commanders can target analysis to be highly focused on a specific PMESII-PT domain or variable or conduct analysis across multiple PMESII-PT domains. The model is also designed to assist commanders in mapping food systems in their AOs and then identifying components of those systems that must be strengthened or protected.

Keywords: food security, food system model, political stability, US Military

Procedia PDF Downloads 186

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

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Authors: K. A. Adepoju, O. I. Shittu, A. U. Chukwu

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In this paper, a new four-parameter generalized version of the Fisher Snedecor distribution called Beta- F distribution is introduced. The comprehensive account of the statistical properties of the new distributions was considered. Formal expressions for the cumulative density function, moments, moment generating function and maximum likelihood estimation, as well as its Fisher information, were obtained. The flexibility of this distribution as well as its robustness using cancer remission time data was demonstrated. The new distribution can be used in most applications where the assumption underlying the use of other lifetime distributions is violated.

Keywords: fisher-snedecor distribution, beta-f distribution, outlier, maximum likelihood method

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: Irfan U. Din

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The growing presence and operational capacity of Islamic State aka Daesh, which emerged in Pak-Afghan region in 2015, poses a serious threat to the already fragile state of the security situation in the region. This paper will shed light on the current state of IS-K network in the Pak-Afghan region and will explain how its presence and operational capacity in the northern and central Afghanistan has increased despite intensive military operations against the group in Nangarhar province – the stronghold of IS-K. It will also explore the role of Pakistani Taliban in the emergence and expansion of IS-K in the region and will unveil the security implication of growing nexus of IS-K and transnational organized groups for the region in Post NATO withdrawal scenario. The study will be qualitative and will rely on secondary and primary data to explore the topic. For secondary data existing literature on the topic will be extensively reviewed while for primary data in-depth interviews will be conducted with subject experts, Taliban commanders, and field researchers.

Keywords: Islamic State of Khorasan (IS-K), North Atlantic Treaty Organization (NATO), Pak-Afghan Region, Transnational Organized Crime (TNOC)

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Grace Iember Anweh, Er Shipp

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Child Sexual Abuse (CSA) has been a contending issue across the globe. The menace of child sexual violence cuts across all continents. From 0 - 13 years, children have been sexually abused – some to the extent that their reproductive organs have been permanently damaged. The research in view is timely, as it will contribute data on CSA and media role to the communication parlance. This study believes that the adverse effects of this menace can hinder children who are potential leaders of tomorrow from harnessing their potentials to contribute to the growth and development of societies due to the psychological, health, and social effects of sex abuse. Where government policies, the law, cultural beliefs, and bottle necks surrounding processes of fighting child sexual abuse have failed, this study assumes that adequate coverage by the mass media, especially the newspapers known for their in-depth coverage and reporting, can help to eradicate or reduce to its barest minimum, the menace of CSA. Therefore, this study aims at assessing the coverage of newspapers – their policies and content towards preventive strategies, and how the public access and receive the messages to the extent they take action to forestall the persistence of sexual violation of children in Nigeria. Methodologically, the study has adopted qualitative and quantitative methods to answer the problem. The study used in-depth interview method to find out from journalists and editors of newspapers the policies that define the production of news content on sexual gender-based violence. In addition, selected National Daily newspapers are content - analysed to determine the focus of media coverage and whether the contents are preventive-based or case-based. In addition, caregivers of the reproductive ages from 16 years and above, ranging from parents, guardians, and school management, will form the study population through a survey using the questionnaire. The aim is to determine their views regarding mass media coverage of sexual violence against children and the effectiveness of the content, to the extent of prompting them to keep the child safe from sexual molesters. Findings from the content analysis so far show that newspapers in Nigeria are not engaged in preventive content of CSA. Their contents are rather case-based.

Keywords: newspaper, coverage, prevention, child, sexual abuse

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Authors: Thiago M. R Dias, Gray F. Moita

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The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: extraction, data integration, information retrieval, scientific collaboration

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Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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Authors: Yang Yang, Lu Xin

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The study of extant musical sites can provide a side-by-side picture of historical ethnomusicological information. In their data collection on Chinese opera houses, researchers found that one Ming Dynasty opera house reached a width of nearly 18 meters, while all opera houses of the same period and after it was far from such a width, being significantly smaller than 18 meters. The historical transient fluctuations in the data dimension of width that caused Chinese theatres to fluctuate in the absence of construction scale constraints have piqued the interest of researchers as to why there is data variation in width. What factors have contributed to the lack of further expansion in the width of theatres? To address this question, this study used a comparative approach to conduct a venue experiment between this theater stage and another theater stage for non-heritage opera performances, collecting the subjective perceptions of performers and audiences at different theater stages, as well as combining BK Connect platform software to measure data such as echo and delay. From the subjective and objective results, it is inferred that the Chinese ancients discovered and understood the acoustical phenomenon of the Haas effect by exploring the effect of stage width on musical performance and appreciation of listening states during the Ming Dynasty and utilized this discovery to serve music in subsequent stage construction. This discovery marked a node of evolution in Chinese architectural acoustics technology driven by musical demands. It is also instructive to note that, in contrast to many of the world's "unsuccessful civilizations," China can use a combination of heritage and intangible cultural research to chart a clear, demand-driven course for the evolution of human music technology, and that the findings of such research will complete the course of human exploration of music acoustics. The findings of such research will complete the journey of human exploration of music acoustics, and this practical experience can be applied to the exploration and understanding of other musical heritage base data.

Keywords: Haas effect, musical acoustics, history of acoustical technology, Chinese opera stage, structure

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Authors: Annisa D. Febryandini

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Annexation is a typical construction that commonly used in Arabic language. The use of the construction appears in Arabic speech such as the speech of Thariq bin Ziyad. The speech as one of the most famous speeches in the history of Islam uses many annexations. This qualitative research paper uses the secondary data by library method. Based on the data, this paper concludes that the speech has two basic structures with some variations and has some grammatical relationship. Different from the other researches that identify the speech in sociology field, the speech in this paper will be analyzed in linguistic field to take a look at the structure of its annexation as well as the grammatical relationship.

Keywords: annexation, Thariq bin Ziyad, grammatical relationship, Arabic syntax

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Junwu Tian

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Chinese poetics originated in the pre-Qin period, while Western poetics came into being in the Hellenistic period. Although there was no mutual communication and influence between the two kinds of poetics due to both geographical distance and chronological displacement, the Sino-Western thinkers shared much in common, particularly in the social function of literature and art, the pursuit of unified and harmonious aesthetics, the advocacy of poets’ subjective initiative in the creative process of literature and art. In the sphere of rhetoric, the poetics of the pre-Qin scholars and their Greek counterparts also had heterogeneous similarities. By comparing the aesthetic ideas of Confucius, Mencius, Xun Zi, and Deng Xi with those of Plato, Aristotle, and Protagoras, this paper intends to reveal the common concerns of Chinese and Western poetics in the context of heterogeneous cultures and in their respective origin periods.

Keywords: Pre-Qin poetics, ancient Greek poetics, heterogeneous similarity, origin period

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Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

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Authors: Obadiah Nwabueze

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Bodija market is classified as Central Business District (CBD) of Ibadan North Local Government Area of Oyo State (Nigeria) because of socio economic activities, so Crime is a peculiar social issue that causes insecurity. The law enforcement agencies tasked with crime prevention and control such as the Nigerian Police have insufficient manpower, and a resultant effect is the emergence of Vigilante groups as citizen’s response to crime control and prevention (self-help). The research design adopted for this study is a case study design exploring Vigilante activities in Bodija Market. The study utilizes both quantitative and qualitative approach, sources of data includes primary and secondary sources. A sample of 127 respondents randomly picked from the 4 sections of Bodija Market through questionnaire, comprising of 50 male and 77 females which alienates issues of gender bias in addition to the 4 in-depth interview, making a total of 131 respondents. Statistical package for Social Sciences (SPSS) was used. The descriptive statistics of simple frequency, percentage, charts and graphs were computed for the analysis. Finding in the study shows that the market vigilante is able to deter and disrupt criminal activities through strategic spiritual intelligence (SSI), use of charm and juju, physical presence in strategic locations vulnerable to crime occurrence. Findings in the study also show that vigilantes collaborate with the police by assisting them in surveillance, tracking down criminals, identifying black spots, acting as informants to the police, arrest and handover criminal to police. Their challenges include poor equipment, motivation, unhealthy rivalry between the vigilante and the police. The study recommends that the government should support vigilantes with logistics and training, including patrol vehicle and radio communication. The study also recommends the integration of the informal mechanism (juju and charm) of crime detection and prevention into the formal policing strategy, an office should be created in the force commands for use of SSI.

Keywords: central business district, CBD, charm, Juju, strategic spiritual intelligence, SSI

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Ravi Gujjula, Chinna Eranna, Narasimha Mangadoddy

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Hydrodynamic study of gas and solid flow in an internally circulating fluidized bed with draft tube is made in this paper using high speed camera and pressure probes for the laboratory ICFB test rig 3.0 m X 2.7 m column having a draft tube located in the center of ICFB. Experiments were conducted using different sized sand particles with varying particle size distribution. At each experimental run the standard pressure-flow curves for both draft tube and annular region beds measured and the same time downward particles velocity in the annular bed region were also measured. The effect of superficial gas velocity, static bed height (40, 50 & 60 cm) and the draft tube gap height (10.5 & 14.5 cm) on pressure drop profiles, solid circulation pattern, and gas bypassing dynamics for the ICFB investigated extensively. The mechanism of governing solid recirculation and the pressure losses in an ICFB has been eluded based on gas and solid dynamics obtained from the experimental data. 3D ICFB CFD simulation runs conducted and extracted data validated with ICFB experimental data.

Keywords: icfb, cfd, pressure drop, solids recirculation, bed height, draft tube

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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Authors: Manoj Kumar

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

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Authors: Maha Mourad, Fady Todros

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The objective of this research is to find an explanatory model to define the most important variables and factors that affect the acceptance of Mobile Internet in the Egyptian market. A qualitative exploratory research was conducted to support the conceptual framework followed with a quantitative research in the form of a survey distributed among 411 respondents. It was clear that relative advantage, complexity, compatibility, perceived price level and perceived playfulness have a dominant role in influencing consumers to adopt mobile internet, while observability is correlated to the adoption but when measured with the other factors it lost its value. The perceived price level has a negative relationship with the adoption as well the compatibility.

Keywords: innovation, Egypt, communication technologies, diffusion, innovation adoption, emerging market

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Authors: Neetu Tyagi, Sumit Sharma

Abstract:

The study illustrates the results of an integrated study done on Tangni landslide located on NH-58 at Chamoli, Uttarakhand. Geological, geo-morphological and geotechnical investigations were carried out to understand the mechanism of landslide and to plan further investigation and monitoring. At any rate, the movements were favored by continuous rainfall water infiltration from the zones where the phyllites/slates and Dolomites outcrop. The site investigations were carried out including the monitoring of landslide movements and of the water level fluctuations due to rainfall give us a better understanding of landslide dynamics that have been causing in time soil instability at Tangni landslide site. The Early Warning System (EWS) installed different types of sensors and all sensors were directly connected to data logger and raw data transfer to the Defence Terrain Research Laboratory (DTRL) server room with the help of File Transfer Protocol (FTP). The slip surfaces were found at depths ranging from 8 to 10 m from Geophysical survey and hence sensors were installed to the depth of 15m at various locations of landslide. Rainfall is the main triggering factor of landslide. In this study, the developed model of unsaturated soil slope stability is carried out. The analysis of sensors data available for one year, indicated the sliding surface of landslide at depth between 6 to 12m with total displacement up to 6cm per year recorded at the body of landslide. The aim of this study is to set the threshold and generate early warning. Local peoples already alert towards landslide, if they have any types of warning system.

Keywords: early warning system, file transfer protocol, geo-morphological, geotechnical, landslide

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Authors: Zahid Ullah, Atlas Khan

Abstract:

This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 105