Search results for: cognitive radio network (CRN)

Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Giulio Nisoli, Jonas Brüngger, Karin Hostettler, Nicole Stoller, Katrin Fischer

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Technical operators in the railway domain are experts responsible for the supervisory control of the railway power grid as well as of the railway tunnels. The technical systems used to master these demanding tasks are constantly increasing in their degree of automation. It becomes therefore difficult for technical operators to maintain the control over the technical systems and the processes of their job. In particular, the operators must have the necessary experience and knowledge in dealing with a malfunction situation or unexpected event. For this reason, it is of growing importance that the skills relevant for the execution of the job are maintained and further developed beyond the basic training they receive, where they are educated in respect of technical knowledge and the work with guidelines. Training methods aimed at improving the cognitive skills needed by technical operators are still missing and must be developed. Goals of the present study were to identify which are the relevant cognitive skills of technical operators in the railway domain and to define which topics should be addressed by the training of these skills. Observational interviews were conducted in order to identify the main tasks and the organization of the work of technical operators as well as the technical systems used for the execution of their job. Based on this analysis, the most demanding tasks of technical operators could be identified and described. The cognitive skills involved in the execution of these tasks are those, which need to be trained. In order to identify and analyze these cognitive skills a cognitive task analysis (CTA) was developed. CTA specifically aims at identifying the cognitive skills that employees implement when performing their own tasks. The identified cognitive skills of technical operators were summarized and grouped in training topics. For every training topic, specific goals were defined. The goals regard the three main categories; knowledge, skills and attitude to be trained in every training topic. Based on the results of this study, it is possible to develop specific training methods to train the relevant cognitive skills of the technical operators.

Keywords: cognitive skills, cognitive task analysis, technical operators in the railway domain, training topics

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Authors: Alireza Pirkhaefi

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Background: Multiple sclerosis (MS) is one of the most common diseases of the central nervous system (brain and spinal cord). Given the importance of cognitive disorders in patients with multiple sclerosis, the present study was in order to compare cognitive functions (Working memory, Attention and Centralization, and Visual-spatial perception) in patients with relapsing- remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). Method: Present study was performed as a retrospective study. This research was conducted with Ex-Post Facto method. The samples of research consisted of 60 patients with multiple sclerosis (30 patients relapsing-retrograde and 30 patients secondary progressive), who were selected from Tehran Community of MS Patients Supported as convenience sampling. 30 normal persons were also selected as a comparison group. Montreal Cognitive Assessment (MOCA) was used to assess cognitive functions. Data were analyzed using multivariate analysis of variance. Results: The results showed that there were significant differences among cognitive functioning in patients with RRMS, SPMS, and normal individuals. There were not significant differences in working memory between two groups of patients with RRMS and SPMS; while significant differences in these variables were seen between the two groups and normal individuals. Also, results showed significant differences in attention and centralization and visual-spatial perception among three groups. Conclusions: Results showed that there are differences between cognitive functions of RRMS and SPMS patients so that the functions of RRMS patients are better than SPMS patients. These results have a critical role in improvement of cognitive functions; reduce the factors causing disability due to cognitive impairment, and especially overall health of society.

Keywords: multiple sclerosis, cognitive function, secondary-progressive, normal subjects

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Authors: Clara Eichberger, Daantje Derks, Hannes Zacher

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Technology-assisted supplemental work (TASW) involves performing job-related tasks after regular working hours with the help of technological devices. Due to emerging information and communication technologies, such behavior becomes increasingly common. Since previous research on the relationship of TASW, psychological detachment and well-being are mixed, this study aimed to examine the moderating roles of appraisal and cognitive coping. A moderated mediation model was tested with daily diary data from 100 employees. As hypothesized, TASW was positively related to negative affect at bedtime. In addition, psychological detachment mediated this relationship. Results did not confirm appraisal and cognitive coping as moderators. However, additional analyses revealed cognitive coping as a mediator of the positive relationship of TASW and positive affect at bedtime. These results suggest that, on the one hand engaging in TASW can be harmful to employee well-being (i.e., more negative affect) and on the other hand, it can also be associated with higher well-being (i.e., more positive affect) in case it is accompanied by cognitive coping.

Keywords: cognitive coping, psychological detachment, technology-assisted supplemental work, well-being

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless nodes in a sensor network gather and process critical information designed to process and communicate, information flooding through such network is critical for decision making and data processing, the integrity of such data is one of the most critical factors in wireless security without compromising the processing and transmission capability of the network. This paper presents mechanism to securely transmit data over a chain of sensor nodes without compromising the throughput of the network utilizing available battery resources available at the sensor node.

Keywords: hybrid protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node data processing, Z-MAC

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Authors: Yusuf Seedat

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The necessity to understand global financial markets has increased following the unfortunate spread of the recent financial crisis around the world. Financial markets are considered to be complex systems consisting of highly volatile move-ments whose indexes fluctuate without any clear pattern. Analytic methods of stock prices have been proposed in which financial markets are modeled using common network analysis tools and methods. It has been found that two key components of social network analysis are relevant to modeling financial markets, allowing us to forecast accurate predictions of stock prices within the financial market. Financial markets have a number of interacting components, leading to complex behavioral patterns. This paper describes a social network approach to analyzing financial markets as a viable approach to studying the way complex stock markets function. We also look at how social network analysis techniques and metrics are used to gauge an understanding of the evolution of financial markets as well as how community detection can be used to qualify and quantify in-fluence within a network.

Keywords: network analysis, social networks, financial markets, stocks, nodes, edges, complex networks

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Authors: R. Geetha, J. Arunkumar, P. Gopal, D. Loganathan, K. Pavithra, C. Vikashini

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Mobile Number Portability is an attempt to switch over from one network to another network facility for mobile based on applications. This facility is currently not available for mobile handsets. This application is intended to assist the mobile network and its service customers in understanding the criteria; this will serve as a universal set of requirements which must be met by the customers. This application helps the user's network portability. Accessing permission from the network provider to enable services to the user and utilizing the available network signals. It is enabling the user to make a temporary switch over to other network. The main aim of this research work is to adapt multiple networks at the time of no network coverage. It can be accessed at rural and geographical areas. This can be achieved by this mobile application. The application is capable of temporary switch over between various networks. With this application both the service provider and the network user are benefited. The service provider is benefited by charging a minimum cost for utilizing other network. It provides security in terms of password that is unique to avoid unauthorized users and to prevent loss of balance. The goal intended to be attained is a complete utilization of available network at significant situations and to provide feature that satisfy the customer needs. The temporary switch over is done to manage emergency calls when user is in rural or geographical area, where there will be a very low network coverage. Since people find it trend in using Android mobile, this application is designed as an Android applications, which can be freely downloaded and installed from Play store. In the current scenario, the service provider enables the user to change their network without shifting their mobile network. This application affords a clarification for users while they are jammed in a critical situation. This application is designed by using Android 4.2 and SQLite Version3.

Keywords: mobile number, random number, alarm, imei number, call

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Authors: Sevilay Çankaya

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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

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Authors: Fahad R. Choudhry., Khadeeja Munawar

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This clinical case presents a 24 years old, Muslim Pakistani girl with a history of conversion disorder. Her symptoms comprised fits, restlessness, numbness in legs, poor coordination and balance, burning during urination and retention. A cognitive-behavioral model was used for conceptualizing her problem and devising a management plan based on cognitive behavioral therapy (CBT) and culturally adapted coping statements. She took 13 therapy sessions and was presented with idiosyncratic case conceptualization. Psychoeducation, coping statements, extinction, verbal challenging, and behavioral activation techniques were practiced in a collaborative way for cognitive restructuring of the client. Focus of terminal sessions was on anger management. The client needed a couple of more sessions in order to help her manage her anger. However, the therapy was terminated on the part of the client after attainment of short term goals. The client reported to have a 75 % improvement in her overall condition and remained compliant throughout the therapy.

Keywords: cognitive behavioral therapy, conversion disorder, female, Muslim, Pakistani

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Authors: Emil Ghiocel Ioanid, Viorica Frunză, Dorina Rusu, Ana Maria Vlad, Catalin Tanase, Simona Dunca

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The application of cold radio-frequency (RF) plasma in the conservation of cultural heritage became important in the last decades due to the positive results obtained in decontamination treatments. This paper presents an equipment especially designed for RF cold plasma application on paper documents, developed within a research project. The equipment allows the application of decontamination and cleaning treatments on any type of paper support, as well as the coating with a protective polymer. The equipment consists in a Pyrex vessel, inside which are placed two plane-parallel electrodes, capacitively coupled to a radio-frequency generator. The operating parameters of the equipment are: 1.2 MHz frequency, 50V/cm electric field intensity, current intensity in the discharge 100 mA, 40 W power in the discharge, the pressure varying from 5∙10-1 mbar to 5.5∙10-1 mbar, depending on the fragility of the material, operating in gaseous nitrogen. In order to optimize the equipment treatments in nitrogen plasma have been performed on samples infested with microorganisms, then the decontamination and the changes in surface properties (color, pH) were assessed. The analyses results presented in the table revealed only minor modifications of surface pH the colorimetric analysis showing a slight change to yellow. The equipment offers the possibility of performing decontamination, cleaning and protective coating of paper-based documents in successive stages, thus avoiding the recontamination with harmful biological agents.

Keywords: nitrogen plasma, cultural heritage, paper support, radio-frequency

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: biological molecular networks, essential genes, graph theory, network subgraphs

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Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: distributed generation photovoltaic (DG PV), optimal location, penetration level, sub–transmission network

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: Alvaro Marin

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This paper explores the challenges in Cognitive Translation Studies (CTS) conceptual development to accommodate professionals’ perceptions in the language industry into CTS established theoretical apparatus, empirical research projects, and university pedagogical proposals. A comparative conceptual assessment framework is developed from a pluralist epistemological stance that promotes interdisciplinary explorations of the translation process. The framework is used to review key notions such as expertise or feedback, as understood by language industry stakeholders. This review is followed by an analysis of how these notions can enrich research constructs to be applied in empirical investigations of translators’ cognitive processes from an embedded, situated cognition perspective. Thus, it will be proposed to apply the conceptual assessment framework as an effort towards strengthening the interpretative research tools and bridging the gap between industry and academia. The conclusions of this analysis will serve as a basis to further discuss how professional practices, combined with our current knowledge about expertise development in cognitive science and Expertise Studies, can enhance the learning experience of university translation students and help them better understand the processes and requirements of professional cross-linguistic mediation.

Keywords: language industry, cognitive translation studies, translation cognitive theory, translation teaching

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Authors: Jiahao Cui

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In the past centuries, due to climate change and intense whaling, the global whale population has dramatically declined. Among the various whale species, the fin whale experienced the most drastic drop in number due to its popularity in whaling. Under this background, identifying fin whale calls could be immensely beneficial to the preservation of the species. This paper uses feature extraction to process the input audio signal, then a network based on AlexNet and three networks based on the ResNet model was constructed to classify fin whale calls. A mixture of the DOSITS database and the Watkins database was used during training. The results demonstrate that a modified ResNet network has the best performance considering precision and network complexity.

Keywords: convolutional neural network, ResNet, AlexNet, fin whale preservation, feature extraction

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Authors: Kang Won Lee, Jung Won Lee

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Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: betweenness centrality, correlation coefficient, power-law distribution, Korea traffic DB

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Authors: Hui-Ling Yang, Kuei-Ru Chou

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Background: Studies show that cognitive training can effectively delay cognitive failure. However, there are several gaps in the previous studies of cognitive training in mild cognitive impairment: 1) previous studies enrolled mostly healthy older adults, with few recruiting older adults with cognitive impairment; 2) they also had limited generalizability and lacked long-term follow-up data and measurements of the activities of daily living functional impact. Moreover, only 37% were randomized controlled trials (RCT). 3) Limited cognitive training has been specifically developed for mild cognitive impairment. Objective: This study sought to investigate the changes in cognitive function, activities of daily living and degree of depressive symptoms in older adults with mild cognitive impairment after cognitive training. Methods: This double-blind randomized controlled study has a 2-arm parallel group design. Study subjects are older adults diagnosed with mild cognitive impairment in residential care facilities. 124 subjects will be randomized by the permuted block randomization, into intervention group (Cognitive training, CT), or active control group (Passive information activities, PIA). Therapeutic adherence, sample attrition rate, medication compliance and adverse events will be monitored during the study period, and missing data analyzed using intent-to-treat analysis (ITT). Results: Training sessions of the CT group are 45 minutes/day, 3 days/week, for 12 weeks (36 sessions each). The training of active control group is the same as CT group (45min/day, 3days/week, for 12 weeks, for a total of 36 sessions). The primary outcome is cognitive function, using the Mini-Mental Status Examination (MMSE); the secondary outcome indicators are: 1) activities of daily living, using the Lawton’s Instrumental Activities of Daily Living (IADLs) and 2) degree of depressive symptoms, using the Geriatric Depression Scale-Short form (GDS-SF). Latent growth curve modeling will be used in the repeated measures statistical analysis to estimate the trajectory of improvement by examining the rate and pattern of change in cognitive functions, activities of daily living and degree of depressive symptoms for intervention efficacy over time, and the effects will be evaluated immediate post-test, 3 months, 6 months and one year after the last session. Conclusions: We constructed a rigorous CT program adhering to the Consolidated Standards of Reporting Trials (CONSORT) reporting guidelines. We expect to determine the improvement in cognitive function, activities of daily living and degree of depressive symptoms of older adults with mild cognitive impairment after using the CT.

Keywords: mild cognitive impairment, cognitive training, randomized controlled study

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Authors: Ke Ma

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Through the long course of history, Buddhism has captivated generations of brilliant minds with its enlightening but elusive discernment. Far from religious dogmas, Buddhism not only represents spiritual revelation, but also logical reasoning.Among all of Buddhism’s concepts, emptiness is the most famous, and abstruse one. This word resulted from an inaccurate translation confuses both Buddhists and religious scholars who understand Heart Sutra based on its English version. In this essay, the idea of “emptiness” will be reinterpreted as “information,” leading not only to a clarification of the ideology of Buddhism, but also to greater correspondence between Buddhism concepts and cognitive science.

Keywords: religion, cognitive science, psychology, Buddhism

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Authors: Nisarg A. Patel, Hiren B. Patel

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Quantum cryptography is described as a point-to-point secure key generation technology that has emerged in recent times in providing absolute security. Researchers have started studying new innovative approaches to exploit the security of Quantum Key Distribution (QKD) for a large-scale communication system. A number of approaches and models for utilization of QKD for secure communication have been developed. The uncertainty principle in quantum mechanics created a new paradigm for QKD. One of the approaches for use of QKD involved network fashioned security. The main goal was point-to-point Quantum network that exploited QKD technology for end-to-end network security via high speed QKD. Other approaches and models equipped with QKD in network fashion are introduced in the literature as. A different approach that this paper deals with is using QKD in existing protocols, which are widely used on the Internet to enhance security with main objective of unconditional security. Our work is towards the analysis of the QKD in Mobile ad-hoc network (MANET).

Keywords: cryptography, networking, quantum, encryption and decryption

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Authors: Garima Joshi, Ashima N. Wadhawan

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Neuropsychology in India is a fairly new field, having started only four decades back. Neuropsychology has come a long way since the establishment of the first department, from using western batteries for assessing patients to the development of highly reliable indigenous tools for assessing neuropsychological functioning. Clinical neuropsychology has risen as a discipline in the field of assessing and rehabilitating patients with various neurological conditions such as Traumatic Brain Injury, Stroke, Mild Cognitive Impairment, Alzheimer’s, Schizophrenia and other disorders with cognitive decline. The current review attempts to assimilate the history of the discipline in India, along with the current developments and future direction of the field and highlights the pursuit and undertakings of the scientists to provide culturally appropriate services, in terms of assessment and rehabilitation, to the Indian population.

Keywords: clinical neuropsychology, cognitive assessment, cognitive rehabilitation, neuropsychological test batteries in India

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: Matthew O. Ikuabe, Ayodeji E. Oke, Clinton O. Aigbavboa, Douglas O. Aghimien

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The use of technological innovations have been touted to be beneficial in the delivery of construction projects. Particularly, Radio Frequency Identification (RFID) technology is widely regarded to be of immense advantage for the management of construction projects. This study focused on evaluating the barriers to the use of Radio Frequency Identification (RFID) technology for the delivery of construction projects. Using Gauteng Provincein South Africa as the study area, questionnaire was used in eliciting responses from construction professionals, which made up the population of the study. Retrieved data was analysed using Mean Item Score and One-Sample t-test. Findings from the study showed that the most significant barriers to the deployment of RFID for construction project delivery are high cost and lack of awareness. Conclusively, the study made recommendations that would aid in the abatement of the barriers to the use of RFID technology for construction project delivery.

Keywords: barriers, construction, project delivery, RFID

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Bohuslava Juhasova, Igor Halenar, Martin Juhas

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The wireless communication is one of the widely used methods of data transfer at the present days. The benefit of this communication method is the partial independence of the infrastructure and the possibility of mobility. In some special applications it is the only way how to connect. This paper presents some problems in the implementation of a sensor network connection for measuring environmental parameters in the area of manufacturing plants.

Keywords: network, communication, reliability, sensors

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Authors: Umut Tac, Leyla Tavacioglu, Pelin Bolat

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Human factor has been one of the elements that cause vulnerabilities which can be resulted with accidents in maritime transportation. When the roots of human factor based accidents are analyzed, gaps in performing cognitive abilities (reaction time, attention, memory…) are faced as the main reasons for the vulnerabilities in complex environment of maritime systems. Thus cognitive processes in maritime systems have arisen important subject that should be investigated comprehensively. At this point, neurocognitive tests such as reaction time analysis tests have been used as coherent tools that enable us to make valid assessments for cognitive status. In this respect, the aim of this study is to evaluate the reaction time (response time or latency) of seafarers due to their occupational experience and age. For this study, reaction time for different maneuverers has been taken while the participants were performing a sea voyage through a simulator which was run up with a certain scenario. After collecting the data for reaction time, a statistical analyze has been done to understand the relation between occupational experience and cognitive abilities.

Keywords: cognitive abilities, human factor, neurocognitive test battery, reaction time

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Authors: Ali Vaezi, Jyotirmoy Dalal, Manish Verma

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The railroad is one of the primary transportation modes for hazardous materials (hazmat) shipments in North America. Installing an emergency response network capable of providing a commensurate response is one of the primary levers to contain (or mitigate) the adverse consequences from rail hazmat incidents. To this end, we propose a two-stage stochastic program to determine the location of and equipment packages to be stockpiled at each response facility. The raw input data collected from publicly available reports were processed, fed into the proposed optimization program, and then tested on a realistic railroad network in Ontario (Canada). From the resulting analyses, we conclude that the decisions based only on empirical datasets would undermine the effectiveness of the resulting network; coverage can be improved by redistributing equipment in the network, purchasing equipment with higher containment capacity, and making use of a disutility multiplier factor.

Keywords: hazmat, rail network, stochastic programming, emergency response

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Authors: Ivan Belik, Kurt Jornsten

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We construct the coauthorship network based on the scientific collaboration between the faculty members at the Norwegian School of Economics (NHH) and based on their international academic publication experience. The network structure is based on the NHH faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The given network covers the publication activities of the NHH faculty members (over six departments) based on the information retrieved from the ISI Web of Science in Spring, 2014. In this paper we analyse the constructed coauthorship network in different aspects of the theory of social networks analysis.

Keywords: coauthorship networks, social networks analysis, Norwegian School of Economics, ISI

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Authors: Supriya H. S., Chandrakala B. M.

Abstract:

Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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