Search results for: malware information sharing platform

Authors: G. Natuhwera, M. Rabwoni, P. Ellis, A. Merriman

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Aims: Health workers are likely to document patients’ care inaccurately, especially when using new and revised case tools, and this could negatively impact patient care. This study set out to; (1) assess nurses’ and clinicians’ documentation practices when using a new patients’ continuation case sheet (PCCS) and (2) explore nurses’ and clinicians’ experiences regarding documentation of patients’ information in the new PCCS. The purpose of introducing the PCCS was to improve continuity of care for patients attending clinics at which they were unlikely to see the same clinician or nurse consistently. Methods: This was a mixed methods study. The cross-sectional inquiry retrospectively reviewed 100 case notes of active patients on hospice and palliative care program. Data was collected using a structured questionnaire with constructs formulated from the new PCCS under study. The qualitative element was face-to-face audio-recorded, open-ended interviews with a purposive sample of one palliative care clinician, and four palliative care nurse specialists. Thematic analysis was used. Results: Missing patients’ biogeographic information was prevalent at 5-10%. Spiritual and psychosocial issues were not documented in 42.6%, and vital signs in 49.2%. Poorest documentation practices were observed in past medical history part of the PCCS at 40-63%. Four themes emerged from interviews with clinicians and nurses-; (1) what remains unclear and challenges, (2) comparing the past with the present, (3) experiential thoughts, and (4) transition and adapting to change. Conclusions: The PCCS seems to be a comprehensive and simple tool to be used to document patients’ information at subsequent visits. The comprehensiveness and utility of the PCCS does paper to be limited by the failure to train staff in its use prior to introducing. The authors find the PCCS comprehensive and suitable to capture patients’ information and recommend it can be adopted and used in other palliative and hospice care settings, if suitable introductory training accompanies its introduction. Otherwise, the reliability and validity of patients’ information collected by this PCCS can be significantly reduced if some sections therein are unclear to the clinicians/nurses. The study identified clinicians- and nurses-related pitfalls in documentation of patients’ care. Clinicians and nurses need to prioritize accurate and complete documentation of patient care in the PCCS for quality care provision. This study should be extended to other sites using similar tools to ensure representative and generalizable findings.

Keywords: documentation, information case sheet, palliative care, quality improvement

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Benhenni Abdellaziz

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Irrigation is a limiting factor for agricultural production and socioeconomic development of many countries in the arid and semi-arid world. However, the sustainability of irrigation systems requires rational management of the water resource, which is becoming increasingly rare in these regions. The objective of this work is to apply a geographic information system (GIS) coupled with a model for calculating crop water requirements (CROPWATER) for the management of irrigation water in irrigated areas and offer managers an effective tool to better manage water resources in these areas. The application area of GIS is the irrigated perimeter of Western Middle Cheliff, which is located in a semi-arid region (Middle Cheliff). The scope in question is considerable agrarian dynamics and an increased need for irrigation of most crops.

Keywords: GIS, CROPWAT, irrigation, water management, middle cheliff

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Authors: Tim Nedyalkov

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A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. They are collecting, managing, and retaining large amounts of data in cloud environments makes information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: cloud compliance, cloud security, data governance, privacy protection

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Authors: Malini Ganapathy, Sarjit Kaur

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Maximising learning with higher-order thinking skills with Information and Communications Technology (ICT) has been deep-rooted and emphasised in various developed countries such as the United Kingdom, the United States of America and Singapore. The transformation of the education curriculum in the Malaysia Education Development Plan (PPPM) 2013-2025 focuses on the concept of Higher Order Thinking (HOT) skills which aim to produce knowledgeable students who are critical and creative in their thinking and can compete at the international level. HOT skills encourage students to apply, analyse, evaluate and think creatively in and outside the classroom. In this regard, the National Education Blueprint (2013-2025) is grounded based on high-performing systems which promote a transformation of the Malaysian education system in line with the vision of Malaysia’s National Philosophy in achieving educational outcomes which are of world class status. This study was designed to investigate ESL students’ learning practices on the emphasis of promoting HOTs while using ICT in their curricula. Data were collected using a stratified random sampling where 100 participants were selected to take part in the study. These respondents were a group of undergraduate students who undertook ESL courses in a public university in Malaysia. A three-part questionnaire consisting of demographic information, students’ learning experience and ICT utilization practices was administered in the data collection process. Findings from this study provide several important insights on students’ learning experiences and ICT utilization in developing HOT skills.

Keywords: English as a second language students, critical and creative thinking, learning, information and communication technology and higher order thinking skills

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Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

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In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished through the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: analog to digital conversion, digitization, sampling rate, ultrasonic

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Authors: G. A. Babalola, Yusuf Muhammad

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An analysis was carried out on 19,759 citations appended to the References Section of 881 research articles published in Bayero Journal of Pure and Applied Sciences. It was found that journals publications were the most cited source of information among pure and applied sciences scientists with 12,090 (61.2%). The study also revealed that researchers in the field of pure and applied sciences used very current and up to date information sources in writing theirs articles with 10,091 (51.1%) citations and an average mean 11.1 per article in the journal.

Keywords: citation analysis, BAJOPAS, journal article, Bayero University Kano, Nigeria

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Authors: Somayeh Nezami

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The management of financial and human resources of police in metropolitans requires many information and exact plans to reduce a rate of crime and increase the safety of the society. Geographical Information Systems have an important role in providing crime maps and their analysis. By using them and identification of crime hot spots along with spatial presentation of the results, it is possible to allocate optimum resources while presenting effective methods for decision making and preventive solutions. In this paper, we try to explain and compare between some of the methods of hot spots analysis such as Mode, Fuzzy Mode and Nearest Neighbour Hierarchical spatial clustering (NNH). Then the spots with the highest crime rates of drug smuggling for one province in Iran with borderline with Afghanistan are obtained. We will show that among these three methods NNH leads to the best result.

Keywords: GIS, Hot spots, nearest neighbor hierarchical spatial clustering, NNH, spatial analysis of crime

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Authors: Okike Benjamin, E. J. D. Garba

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The protection of sensitive information against unauthorized access or fraudulent changes has been of prime concern throughout the centuries. Modern communication techniques, using computers connected through networks, make all data even more vulnerable to these threats. The researchers in this work propose a new encryption technique to be known as Merged Irregular Transposition Cipher. In this proposed encryption technique, a message to be encrypted will first of all be split into multiple parts depending on the length of the message. After the split, different keywords are chosen to encrypt different parts of the message. After encrypting all parts of the message, the positions of the encrypted message could be swapped to other position thereby making it very difficult to decrypt by any unauthorized user.

Keywords: information security, message splitting, pattern, sequence

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Medhin Haftom Hailu

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The advancement of information technology has significantly impacted Ethiopia's economy, driving innovation, productivity, job creation, and global connectivity. This research examined the impact of contemporary information and communication technologies on Ethiopian economic progress. The study examined eight variables, including mobile, internet, and fixed-line penetration rates, and five macroeconomic control variables. The results showed a positive and strong effect of ICT on economic growth in Ethiopia, with 1% increase in mobile, internet, and fixed line services penetration indexes resulting in an 8.03, 10.05, and 30.06% increase in real GDP. The Granger causality test showed that all ICT variables Granger caused economic growth, but economic growth Granger caused mobile penetration rate only. The study suggests that coordinated ICT infrastructure development, increased telecom service accessibility, and increased competition in the telecom market are crucial for Ethiopia's economic growth. Ethiopia is attempting to establish a digital economy through massive investment in ensuring ICT quality and accessibility. Thus, the research could enhance in understanding of the economic impact of ICT expansion for successful ICT policy interventions for future research.

Keywords: economic growth, cointegration and error correction, ICT expansion, granger causality, penetration

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Authors: Shuai Yang, Bin Li, Sixing Chen

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Engaging and co-creating value with buyers (i.e., the buying organizations) have rapidly become a rising trend for sellers (i.e., the selling organizations) within Business-to-Business (B2B) environments, through which buyers can interact more with sellers and be better informed about products. One important way to achieve this is through engaging with buyers on social media, termed as brand engagement on social media, which provides a platform for sellers to interact with customers. This study addresses the research gap by answering the following questions: (1) Are B2B firms’ brand engagement on social media related to their firm value? (2) To what extent do analyst stock recommendations channel B2B firms’ brand engagement on social media’s possible impact on firm value? To answer the research questions, this study collected data merged from multiple sources. The results show that there is a positive association between seller-initiated engagement and B2B sellers’ firm value. Besides, analyst stock recommendations mediate the positive relationships between seller-initiated engagement and firm value. However, this study reveals buyer-initiated engagement has a counterintuitive and negative relationship with firm value, which shows a dark side of buyer-initiated engagement on social media for B2B sellers.

Keywords: brand engagement, B2B firms, firm value, social media, stock recommendations

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Authors: Andi Fallahi, Bona Ryan Situmeang

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The Construction Industry is notoriously risky. Much of the preparatory paperwork that precedes construction project can be viewed as the formulation of risk allocation between the owner and the Contractor. The Owner is taking the risk that his project will not get built on the schedule that it will not get built for what he has budgeted and that it will not be of the quality he expected. The Contractor Face a multitude of risk. One of them is an unforeseen condition at the construction site. The Owner usually has the upper hand here if the unforeseen condition occurred. Site data contained in Ground Investigation report is often of significant contractual importance in disputes related to the unforeseen ground condition. A ground investigation can never fully disclose all the details of the underground condition (Risk of an unknown ground condition can never be 100% eliminated). Adipala Coal Fired Steam Power Plant (CSFPP) 1 x 660 project is one of the large CSFPP project in Indonesia based on Engineering, Procurement, and Construction (EPC) Contract. Unforeseen Ground Condition it’s responsible by the Contractor has stipulated in the clausal of Contract. In the implementation, there’s indicated unforeseen ground condition at Circulating Water Pump House (CWPH) area which caused the Contractor should be changed the Method of Work that give big impact against Time of Completion and Cost Project. This paper tries to analyze the best way for allocating the risk between The Owner and The Contractor. All parties that allocating of sharing risk fairly can ultimately save time and money for all parties, and get the job done on schedule for the least overall cost.

Keywords: unforeseen ground condition, coal fired steam power plant, circulating water pump house, Indonesia

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Authors: Elsa Lamy, Marília Prada, Ada Rocha, Cláudia Viegas

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The traditional and widely used nutrition-focused approach to communicate with consumers is reductionist and makes it difficult for consumers to assess their food intake. Without sufficient nutrition knowledge and understanding, it would be difficult to choose a healthful diet based only on nutritional recommendations. This study aimed to evaluate the understanding of how food/nutritional information is presented in menus to Portuguese consumers, comparing the nutrient-focused approach (currently used Nutrition Declaration) and the new food-focused approach (the infographic). For data collection, a questionnaire was distributed online using social media channels. A main effect of format on ratings of meal balance and completeness (Fbalance(1,79) = 18.26, p < .001, ηp2 = .188; Fcompleteness(1,67) = 27.18, p < .001, ηp2 = .289). Overall, dishes paired with the nutritional information were rated as more balanced (Mbalance= 3.70, SE = .11; Mcompleteness = 4.00, SE = .14) than meals with the infographic representation (Mbalance = 3.14, SE = .11; Mcompleteness = 3.29, SE = .13). We also observed a main effect of the meal, F(3,237) = 48.90, p < .001, ηp2 = .382, such that M1 and M2 were perceived as less balanced than the M3 and M4, all p < .001. The use of a food-focused approach (infographic) helped participants identify the lack of balance in the less healthful meals (dishes M1 and M2), allowing for a better understanding of meals' compliance with recommendations contributing to better food choices and a healthier lifestyle.

Keywords: food labelling, food and nutritional recommendations, infographics, portions based information

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Authors: Khaled M. Alhawiti

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This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research.

Keywords: data retrieval, information retrieval, natural language processing, text structuring

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Authors: Charles Esambe Alobwede

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From the time of the biblical story of the Tower of Babel, languages as well as people have learnt to co-exist. It is obvious that when languages co-exist, there is the inevitable tendency of linguistic influence. This is because a language can either be a unifying factor or a factor of division within a given community, especially in a multicultural and multi-linguistic community where such a situation has led to socio-political and economic tension. Thus, leaders of such communities have a duty to plan and implement a language policy that will meet the needs of all members of the community in order to enhance its corporateness. The present article will focus on some of the major reasons that prompted the government of Cameroon to embark on an official bilingual policy after independence in 1961 and then evaluate the evolution of the linguistic situation. The article will equally look at the consequences, especially on a socio-political platform and what today has been termed 'the Anglophone problem' in Cameroon which has caused a fuse between the country’s minority Anglophone population and the majority Francophone administration. Data for the present article is collected from literature on the state of official bilingualism in Cameroon, newspapers articles on the prevailing situation in the country and interviews with actors on the field.

Keywords: language policy, linguistic influence, multicultural, official bilingualism, socio-political tension

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Authors: Thiraporn Chumphuming, Nuttida Boonmathi, Supattra Thanomsiang, Tawatchai Noree, Suthee Boonchaloem, Rinyaphat Kecharananta

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This research aims to study about the formats of low-cost airlines’ services in domestic route by surveying customers’ requirements and satisfactions in choosing low-cost airlines to travel domestically. Chiang Mai International Airport and other regions in Chiang Mai are the bases where the information is quantitatively collected. Passengers and questionnaires of 400 are the data base in which the researchers collected information from. Statistic units used are Percentage, Weighted Average, and Standard Deviation. The result of the study reveals that the group of 400 representative samples chooses Air Asia the most from overall six low-cost airlines that provide domestic services. Most of the representative samples book plane tickets for their traveling and they book tickets during the promotion time that provides cheap-priced tickets. Averagely, the price for a seat in one flight is around 501-1,000 Thai baht. The result of the satisfaction’s survey analyzed by the Marketing Mix Factors (7Ps) of low-cost airlines, which is divided into 4 parts including services before ticket reservations, services before boarding/purchasing tickets (ground), In-flight services, and Services after boarding they are satisfied with the baggage claim point informing, also gives the information that the passengers are highly satisfied with every process or the services.

Keywords: low-cost airline, service, satisfaction, customers' behavior

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Authors: Ezekiel Ejiofor Nnadi

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Nigeria construction industry is known for its active construction activities. This has earmarked the industry to be the key to economic growth of the nation. It has largest employer of labour and gives sustenance to other industries like manufacturing industry. While this is a sign of growth and prosperity; the waste generated by the industry has always been a problem and a serious concern. It results in wastage of economic gain and has resultant health effect on the populace apart from injury being sustained on sites. This work provides a platform to learn more about construction waste, its management strategy and how to reduce waste production in Nigeria construction industry. Construction sites, waste management authority and public health institutions in Lagos as the centre of most construction activities in Nigeria were selected, and a set of questionnaire was administered to using the systematic sampling technique. Descriptive statistics and relative importance index (RII) technique were employed for the analysis of the data gathered. The findings of the analysis show that excessive wastes reduce contractors’ profit margin and also that some construction wastes contain hazardous and toxic elements such as lead, asbestos or radioactive materials which required proper handling and effective disposal. The conclusion was drawn that the check on waste on construction sites starts with the designers to the contractors who execute on site.

Keywords: construction cost, construction industry, economic growth, materials wastes

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: information diffusion, personality and values, social network analysis, twitter mentions network

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Authors: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

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Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

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Authors: Agnes Utari Widyaningdyah

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This study investigates the relationship between strategy, intellectual capital (IC) disclosure, and the firm’s performance by considering business competition as a moderating variable. The secondary sectors manufacturing firms in the Jakarta Stock Industrial Classification as sample because this group represents a knowledge-intensive firm according to the OECD (Organization for Economic Cooperation and Development) criteria. Using path analysis, this study reveals that there is a significant influence of strategy toward IC disclosure. Firms with differentiation strategy tend to withhold its strategic information included IC because of afraid in losing their competitive advantage. The results also indicate that firms are more likely to withhold information about IC if they perceive that current or potential competition is strong. However, firms should consider that IC disclosure is a positive signal to the investor.

Keywords: strategy, IC disclosure, market performance, business competition

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: B. Gültekin, T. Gültekin

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Peace diplomacy is the most important international tool to maintain peace all over the World. This study consists of three parts. In the first part, the leadership of Devlet Bahçeli, leader of the Nationalist Movement Party, will be introduced as a tool of peace communication and peace management. Also, in this part, peace communication will be explained by the peace leadership traits of Devlet Bahçeli, who is one of the efficient political leaders representing the concepts of compromise and agreement on different sides of politics. In the second part of study, it is aimed to analyze Devlet Bahçeli’s leadership within the frame of peace communication and the final part of this study is about creating an original public communication model for public diplomacy based on Devlet Bahçeli as an example. As a result, the main purpose of this study is to develop an original peace communication model including peace modules, peace management projects, original dialogue procedures and protocols exhibited in the policies of Devlet Bahçeli. The political leadership represented by Devlet Bahçeli inspires political leaders to provide peace communication. In this study, principles and policies of peace leadership of Devlet Bahçeli will be explained as an original model on a peace communication platform.

Keywords: public diplomacy, dialogue management, peace leadership, peace diplomacy

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Authors: Sang Ho Lee, Tae Heon Moon, Youn Taik Leem, Kwang Woo Nam

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Knowledge and IT inputs to other industrial production have become more important as a key factor for the competitiveness of national and regional economies, such as knowledge economies in smart cities. Knowledge and IT industries lead the industrial innovation and technical (r)evolution through low cost, high efficiency in production, and by creating a new value chain and new production path chains, which is referred as knowledge and IT dynamics. This study aims to investigate the knowledge and IT dynamics in Korea, which are analyzed through the input-output model and structural path analysis. Twenty-eight industries were reclassified into seven categories; Agriculture and Mining, IT manufacture, Non-IT manufacture, Construction, IT-service, Knowledge service, Non-knowledge service to take close look at the knowledge and IT dynamics. Knowledge and IT dynamics were analyzed through the change of input output coefficient and multiplier indices in terms of technical innovation, as well as the changes of the structural paths of the knowledge and IT to other industries in terms of new production value creation from 1985 and 2010. The structural paths of knowledge and IT explain not only that IT foster the generation, circulation and use of knowledge through IT industries and IT-based service, but also that knowledge encourages IT use through creating, sharing and managing knowledge. As a result, this paper found the empirical investigation on the knowledge and IT dynamics of the Korean economy. Knowledge and IT has played an important role regarding the inter-industrial transactional input for production, as well as new industrial creation. The birth of the input-output production path has mostly originated from the knowledge and IT industries, while the death of the input-output production path took place in the traditional industries from 1985 and 2010. The Korean economy has been in transition to a knowledge economy in the Smart City.

Keywords: knowledge and IT industries, input-output model, structural path analysis, dynamics of knowledge and it, knowledge economy, knowledge city and smart city

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Authors: Hossein Keshavarz, Alejandro Ramirez-Serrano

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Energy efficiency and locomotion speed are two key parameters for legged robots; thus, finding ways to improve them are important. This paper proposes a locomotion framework to analyze the energy usage and speed of quadruped robots via a Genetic Algorithm (GA) optimization process. For this, a quadruped robot platform with joint redundancy in its hind legs that we believe will help multi-legged robots improve their speed and energy consumption is used. ContinuO, the quadruped robot of interest, has 14 active degrees of freedom (DoFs), including three DoFs for each front leg, and unlike previously developed quadruped robots, four DoFs for each hind leg. ContinuO aims to realize a cost-effective quadruped robot for real-world scenarios with high speeds and the ability to overcome large obstructions. The proposed framework is used to locomote the robot and analyze its energy consumed at diverse stride lengths and locomotion speeds. The analysis is performed by comparing the obtained results in two modes, with and without the joint redundancy on the robot’s hind legs.

Keywords: genetic algorithm optimization, locomotion path planning, quadruped robots, redundant legs

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

Abstract:

Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

Procedia PDF Downloads 66

Authors: Ahmed Fradi

Abstract:

In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

Procedia PDF Downloads 532

Authors: Yu Yaochuan

Abstract:

This paper explores the pivotal role of public opinion during the Xinhai Revolution. Examining the dynamics of public sentiment in Chinese society in 1911 shows how information dissemination, ideological propaganda, and public mobilization worked together to drive the revolution to success. The study highlights the indispensable role of revolutionary newspapers, assemblies, and speeches in spreading revolutionary ideas, mobilizing the public, and shaping policy perceptions. By analyzing these historical events, the paper provides a deeper insight into the Xinhai Revolution and offers theoretical and empirical support for understanding the application of public opinion in modern social and political transformations.

Keywords: Xinhai Revolution, public opinion, social mobilization, information dissemination, ideology, political transformation

Procedia PDF Downloads 19

Authors: Sofiane Bourchak, Sébastien Bridier

Abstract:

The objective of this study is to show how to calculate and map solar energy’s quantity (instantaneous and accumulated global solar radiation during the year) available on roofs in the city Aix-en-Provence which has a population of 140,000 inhabitants. The result is a geographic information system (GIS) layer, which represents hourly and monthly the production of solar energy on roofs throughout the year. Solar energy professionals can use it to optimize implementations and to size energy production systems. The results are presented as a set of maps, tables and histograms in order to determine the most effective costs in Aix-en-Provence in terms of photovoltaic power (electricity) and thermal power (hot water).

Keywords: geographic information system, photovoltaic, thermal, solar potential, solar radiation

Procedia PDF Downloads 413

Authors: Changhwan Choi, Yongwan Park

Abstract:

In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Keywords: traffic light, intelligent vehicle, night, detection, DGPS

Procedia PDF Downloads 311