Search results for: bi-directional long and short-term memory networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9541

Search results for: bi-directional long and short-term memory networks

9331 Behavioral Assessment of the Role of Brain 5-HT4 Receptors on the Memory and Cognitive Performance in a Rat Model of Alzheimer Disease

Authors: Siamak Shahidi, Nasrin Hashemi-Firouzi, Sara Soleimani-Asl, Alireza Komaki

Abstract:

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory and cognitive performance. Recently, an involvement of the serotonergic system and their receptors are suspected in the AD progression. In the present behavioral study, the effects of BIMU (selective 5-HT4 receptor agonist) on cognition and memory in the rat model of AD was investigated. Material and Methods: The animal model of the AD was induced by intracerebroventricular (Icv) injection of amyloid beta (Aβ) in adult male Wistar rats. Animals were divided into experimental groups included control, sham, Aβ, Aβ +BIMU groups. The treatment substances were icv injected (1 μg/μL) for thirty consecutive days. Then, novel object recognition (NOR) and passive avoidance learning (PAL) tests were applied to investigate memory and cognitive performance. Results: Aβ decrease the discrimination index of NOR test. Also, it increases the time spent in the dark compartment during PAL test, as compared with sham and control groups. In addition, compared to Aβ groups, BIMU significantly increased the discrimination index of NOR test and decreased the time spent in the dark compartment of PAL test. Conclusion: These findings suggest that 5-HT4 receptor activation prevents progression of memory and cognitive impairment in a rat model of AD.

Keywords: Alzheimer disease, cognition, memory, serotonin receptors

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9330 Effect of Blood Sugar Levels on Short Term and Working Memory Status in Type 2 Diabetics

Authors: Mythri G., Manjunath ML, Girish Babu M., Shireen Swaliha Quadri

Abstract:

Background: The increase in diabetes among the elderly is of concern because in addition to the wide range of traditional diabetes complications, evidence has been growing that diabetes is associated with increased risk of cognitive decline. Aims and Objectives: To find out if there is any association between blood sugar levels and short-term and working memory status in patients of type 2 diabetes. Materials and Methods: The study was carried out in 200 individuals aged between 40-65 years consisting of 100 diagnosed cases of Type 2 Diabetes Mellitus and 100 non-diabetics from OPD of Mc Gann Hospital, Shivamogga. Rye’s Auditory Verbal Learning Test, Verbal Fluency Test and Visual Reproduction Test, Working Digit Span Test and Validation Span Test were used to assess short-term and working memory. Fasting and Post Prandial blood sugar levels were estimated. Statistical analysis was done using SPSS 21. Results: Memory test scores of type 2 diabetics were significantly reduced (p < 0.001) when compared to the memory scores of age and gender matched non-diabetics. Fasting blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.837), VFT (r=-0.888), VRT(r=-0.787), WDST (r=-0.795) and VST (r=-0.943). Post- Prandial blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.922), VFT (r=-0.848), VRT(r=-0.707),WDST (r=-0.729) and VST (r=-0.880) Memory scores in all 5 tests were found to be negatively correlated with the FBS and PPBS levels in diabetic patients (p < 0.001). Conclusion: The decreased memory status in diabetic patients may be due to many factors like hyperglycemia, vascular disease, insulin resistance, amyloid deposition and also some of the factor combine to produce additive effects like, type of diabetes, co-morbidities, age of onset, duration of the disease and type of therapy. These observed effects of blood sugar levels of diabetics on memory status are of potential clinical importance because even mild cognitive impairment could interfere with todays’ activities.

Keywords: diabetes, cognition, diabetes, HRV, respiratory medicine

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9329 Reliable Multicast Communication in Next Generation Networks

Authors: Muazzam Ali Khan Khattak

Abstract:

Next Generation Network is combination of different networks having different technologies. Due to mobile nature of nodes the movement of nodes occurs from one network to another network. Multicasting in such networks is still a hot issue of research because the user in today's world wants reliable communication wherever it lies. Due to heterogeneity of NGN it is very difficult to handle reliable multicast communication. In this paper we proposed an improved scheme for reliable multicast communication in next generation networks. Because multicast communication is very important to deliver same data packets to multiple receivers and minimize the network traffic. This new scheme will make the multicast communication in NGN more reliable and efficient.

Keywords: next generation networks, route request, IPT, NACK, ARQ, DTN

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9328 Analysis of Performance of 3T1D Dynamic Random-Access Memory Cell

Authors: Nawang Chhunid, Gagnesh Kumar

Abstract:

On-chip memories consume a significant portion of the overall die space and power in modern microprocessors. On-chip caches depend on Static Random-Access Memory (SRAM) cells and scaling of technology occurring as per Moore’s law. Unfortunately, the scaling is affecting stability, performance, and leakage power which will become major problems for future SRAMs in aggressive nanoscale technologies due to increasing device mismatch and variations. 3T1D Dynamic Random-Access Memory (DRAM) cell is a non-destructive read DRAM cell with three transistors and a gated diode. In 3T1D DRAM cell gated diode (D1) acts as a storage device and also as an amplifier, which leads to fast read access. Due to its high tolerance to process variation, high density, and low cost of memory as compared to 6T SRAM cell, it is universally used by the advanced microprocessor for on chip data and program memory. In the present paper, it has been shown that 3T1D DRAM cell can perform better in terms of fast read access as compared to 6T, 4T, 3T SRAM cells, respectively.

Keywords: DRAM Cell, Read Access Time, Retention Time, Average Power dissipation

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9327 Delay-Dependent Passivity Analysis for Neural Networks with Time-Varying Delays

Authors: H. Y. Jung, Jing Wang, J. H. Park, Hao Shen

Abstract:

This brief addresses the passivity problem for neural networks with time-varying delays. The aim is focus on establishing the passivity condition of the considered neural networks.

Keywords: neural networks, passivity analysis, time-varying delays, linear matrix inequality

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9326 Marketing in Post-Pandemic Environment

Authors: Mohammad Mehdizadeh

Abstract:

COVID-19 forced marketers to change their marketing strategies, focusing less on reactive approaches and more on proactive approaches, primarily social media. The next few years will be dominated by employee engagement and customer experience, leading to businesses focusing more on "long-term customer relationships." A large number of marketing strategies need to be employed in an ever-evolving online environment, which is both filled with opportunities and dangers, as well as being an intimidating platform to use, incorporating new and exciting opportunities for businesses and organizations as it constantly evolves. In this article, we examine the effect of social networks on marketing in post-pandemic environments. A descriptive survey is used as the research method. The results show that social networks have a positive and significant impact on marketing in a post-pandemic environment. Among the social networks studied, Instagram, Facebook, and Twitter have the most positive effect on marketing advancement.

Keywords: COVID-19, customers, marketing, post-pandemic

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9325 The Impact of CO2 on Learning and Memory Duration of Bombus terrestris

Authors: Gholizadeh F. F., Goldansaz S. H., Bandani A. R., A. Ashouri

Abstract:

This study aimed to investigate the direct effects of increasing carbon dioxide (CO₂) concentration on the behavior of Bombus terrestris bumblebees in laboratory conditions to understand the outcomes of the augmentation of this gas in the Earth's atmosphere on the decline of populations of these pollinators. Learning and memory duration of bumblebees were evaluated as two main behavioral factors in social insects at different concentrations of CO₂. In both series of experiments, the behavior of bees under the influence of CO₂ changes compared to the control. Insects kept at high CO₂ concentrations learn less than control bees and spend more time identifying and navigating to discover their food source and access time (nectar consumption). These results showed that bees maybe lose some of their food resources due to poorer identification and act weaker on searching due to less memory and avoiding the enemy in higher CO₂ concentration. Therefore, CO₂ increasing concentration can be one of the reasons for the decline of these pollinating insects' populations by negatively affecting their fitness.

Keywords: Bombus terrestris, CO₂, learning, memory duration

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9324 Investigating the Effect of Executive Functions on Young Children’s Drawing of Familiar and Unfamiliar

Authors: Reshaa Alruwaili

Abstract:

This study was inspired by previous studies with young children that found (a) that they need both inhibitory control and working memory when drawing an unfamiliar subject (e.g., animals) by adapting their schema of the human figure and (b) that when drawing something familiar (e.g., a person) they use inhibitory control mediated through fine motor control to execute their drawing. This study, therefore, systematically investigated whether direct effects for both working memory and inhibitory control and/or effects mediated through fine motor control existed when drawing both familiar and unfamiliar subjects. Participants were 95 children (41-66 months old) required to draw both a man and a dog, scored respectively for how representational they were and for differences from a human figure. Regression and mediation analyses showed that inhibitory control alone predicted drawing a recognizable man while working memory alone predicted drawing a dog that was not human-like when fine motor control, age, and gender were controlled. Contrasting with some previous studies, these results suggest that the roles of working memory and inhibitory control are sensitive to the familiarity of the drawing task and are not necessarily mediated through fine motor control. Implications for research on drawing development are discussed.

Keywords: child drawing, inhibitory control, working memory, fine motor control, mediation, familiar and unfamiliar subjects

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9323 IACOP - Route Optimization in Wireless Networks Using Improved Ant Colony Optimization Protocol

Authors: S. Vasundra, D. Venkatesh

Abstract:

Wireless networks have gone through an extraordinary growth in the past few years, and will keep on playing a crucial role in future data communication. The present wireless networks aim to make communication possible anywhere and anytime. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Since an ad hoc network may consist of a large number of mobile hosts, this imposes a significant challenge on the design of an effective and efficient routing protocol that can work well in an environment with frequent topological changes. This paper proposes improved ant colony optimization (IACO) technique. It also maintains load balancing in wireless networks. The simulation results show that the proposed IACO performs better than existing routing techniques.

Keywords: wireless networks, ant colony optimization, load balancing, architecture

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9322 Memory, Self, and Time: A Bachelardian Perspective

Authors: Michael Granado

Abstract:

The French philosopher Gaston Bachelard’s philosophy of time is articulated in his two works on the subject, the Intuition of the Instant (1932) and his The Dialectic of Duration (1936). Both works present a systematic methodology predicated upon the assumption that our understanding of time has radically changed as a result of Einstein and subsequently needs to be reimagined. Bachelard makes a major distinction in his discussion of time: 1. Time as it is (physical time), 2. Time as we experience it (phenomenological time). This paper will focus on the second distinction, phenomenological time, and explore the connections between Bachelard’s work and contemporary psychology. Several aspects of Bachelard’s philosophy of time nicely complement our current understanding of memory and self and clarify how the self relates to experienced time. Two points, in particular, stand out; the first is the relative nature of subjective time, and the second is the implications of subjective time in the formation of the narrative self. Bachelard introduces two philosophical concepts to explain these points: rhythmanalysis and reverie. By exploring these concepts, it will become apparent that there is an undeniable link between memory, self, and time. Through the use of narrative self, the individual connects and links memories and time together to form a sense of personal identity.

Keywords: Gaston Bachelard, memory, self, time

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9321 An Overview of Privacy and Security Issues in Social Networks

Authors: Mohamad Ibrahim Al Ladan

Abstract:

Social networks, such as Facebook, Myspace, LinkedIn, Google+, and Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They provide attractive means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The various personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. However, these practices have resulted in ample concerns with respect to privacy and security from different stakeholders. Addressing these privacy and security concerns in social networks is a must for these networks to be sustainable. Existing security and privacy tools may not be enough to address existing concerns. Some guidelines should be followed to protect users from the existing risks. In this paper, we have investigated and discussed the various privacy and security issues and concerns pertaining to social networks. Moreover, we have classified these privacy and security issues and presented a thorough discussion of the implications of these issues and concerns on the future of the social networks. In addition, we have presented a set of guidelines as precaution measures that users can consider to address these issues and concerns.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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9320 Cognitive Benefits of Being Bilingual: The Effect of Language Learning on the Working Memory in Emerging Miao-Mandarin Juveniles in Rural Regions of China

Authors: Peien Ma

Abstract:

Bilingual effect/advantage theorized the positive effect of being bilingual on general cognitive abilities, but it was unknown which factors tend to modulate these bilingualism effects on working memory capacity. This study imposed empirical field research on a group of low-SES emerging bilinguals, Miao people, in the hill tribes of rural China to investigate whether bilingualism affected their verbal working memory performance. 20 Miao-Chinese bilinguals (13 girls and 7 boys with a mean age of 11.45, SD=1.67) and 20 Chinese monolingual peers (13 girls and 7 boys with a mean age of 11.6, SD=0.68) were recruited. These bilingual and monolingual juveniles, matched on age, sex, socioeconomic status, and educational status, completed a language background questionnaire and a standard forward and backward digit span test adapted from Wechsler Adult Intelligence Scale-Revised (WAIS-R). The results showed that bilinguals earned a significantly higher overall mean score of the task, suggesting the superiority of working memory ability over the monolinguals. And bilingual cognitive benefits were independent of proficiency levels in learners’ two languages. The results suggested that bilingualism enhances working memory in sequential bilinguals from low SES backgrounds and shed light on our understanding of the bilingual advantage from a psychological and social perspective.

Keywords: bilingual effects, heritage language, Miao/Hmong language Mandarin, working memory

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9319 The Desire for Significance & Memorability in Popular Culture: A Cognitive Psychological Study of Contemporary Literature, Art, and Media

Authors: Israel B. Bitton

Abstract:

“Memory” is associated with various phenomena, from physical to mental, personal to collective and historical to cultural. As part of a broader exploration of memory studies in philosophy and science (slated for academic publication October 2021), this specific study employs analytical methods of cognitive psychology and philosophy of memory to theorize that A) the primary human will (drive) is to significance, in that every human action and expression can be rooted in a most primal desire to be cosmically significant (however that is individually perceived); and B) that the will to significance manifests as the will to memorability, an innate desire to be remembered by others after death. In support of these broad claims, a review of various popular culture “touchpoints”—historic and contemporary records spanning literature, film and television, traditional news media, and social media—is presented to demonstrate how this very theory is repeatedly and commonly expressed (and has been for a long time) by many popular public figures as well as “everyday people.” Though developed before COVID, the crisis only increased the theory’s relevance: so many people were forced to die alone, leaving them and their loved ones to face even greater existential angst than what ordinarily accompanies death since the usual expectations for one’s “final moments” were shattered. To underscore this issue of, and response to, what can be considered a sociocultural “memory gap,” this study concludes with a summary of several projects launched by journalists at the height of the pandemic to document the memorable human stories behind COVID’s tragic warped speed death toll that, when analyzed through the lens of Viktor E. Frankl’s psychoanalytical perspective on “existential meaning,” shows how countless individuals were robbed of the last wills and testaments to their self-significance and memorability typically afforded to the dying and the aggrieved. The resulting insight ought to inform how government and public health officials determine what is truly “non-essential” to human health, physical and mental, at times of crisis.

Keywords: cognitive psychology, covid, neuroscience, philosophy of memory

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9318 Clustering Based and Centralized Routing Table Topology of Control Protocol in Mobile Wireless Sensor Networks

Authors: Mbida Mohamed, Ezzati Abdellah

Abstract:

A strong challenge in the wireless sensor networks (WSN) is to save the energy and have a long life time in the network without having a high rate of loss information. However, topology control (TC) protocols are designed in a way that the network is divided and having a standard system of exchange packets between nodes. In this article, we will propose a clustering based and centralized routing table protocol of TC (CBCRT) which delegates a leader node that will encapsulate a single routing table in every cluster nodes. Hence, if a node wants to send packets to the sink, it requests the information's routing table of the current cluster from the node leader in order to root the packet.

Keywords: mobile wireless sensor networks, routing, topology of control, protocols

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9317 Volatility and Stylized Facts

Authors: Kalai Lamia, Jilani Faouzi

Abstract:

Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behaviour of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.

Keywords: asymmetry volatility, clustering, stylised facts, leverage effect

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9316 Modeling of Thermo Acoustic Emission Memory Effect in Rocks of Varying Textures

Authors: Vladimir Vinnikov

Abstract:

The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied with a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: crack growth, cyclic heating and cooling, rock texture, thermo acoustic emission memory effect

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9315 Performance Study of ZigBee-Based Wireless Sensor Networks

Authors: Afif Saleh Abugharsa

Abstract:

The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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9314 Effects of Listening to Pleasant Thai Classical Music on Increasing Working Memory in Elderly: An Electroencephalogram Study

Authors: Anchana Julsiri, Seree Chadcham

Abstract:

The present study determined the effects of listening to pleasant Thai classical music on increasing working memory in elderly. Thai classical music without lyrics that made participants feel fun and aroused was used in the experiment for 3.19-5.40 minutes. The accuracy scores of Counting Span Task (CST), upper alpha ERD%, and theta ERS% were used to assess working memory of participants both before and after listening to pleasant Thai classical music. The results showed that the accuracy scores of CST and upper alpha ERD% in the frontal area of participants after listening to Thai classical music were significantly higher than before listening to Thai classical music (p < .05). Theta ERS% in the fronto-parietal network of participants after listening to Thai classical music was significantly lower than before listening to Thai classical music (p < .05).

Keywords: brain wave, elderly, pleasant Thai classical music, working memory

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9313 6G: Emerging Architectures, Technologies and Challenges

Authors: Abdulrahman Yarali

Abstract:

The advancement of technology never stops because the demands for improved internet and communication connectivity are increasing. Just as 5G networks are rolling out, the world has begun to talk about the sixth-generation networks (6G). The semantics of 6G are more or less the same as 5G networks because they strive to boost speeds, machine-to-machine (M2M) communication, and latency reduction. However, some of the distinctive focuses of 6G include the optimization of networks of machines through super speeds and innovative features. This paper discusses many aspects of the technologies, architectures, challenges, and opportunities of 6G wireless communication systems.

Keywords: 6G, characteristics, infrastructures, technologies, AI, ML, IoT, applications

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9312 Improve of Power Quality in Electrical Network Using STATCOM

Authors: A. R. Alesaadi

Abstract:

Flexible AC transmission system (FACTS) devices have an important rule on expended electrical transmission networks. These devices can provide control of one or more AC transmission system parameters to enhance controllability and increase power transfer capability. In this paper the effect of these devices on reliability of electrical networks is studied and it is shown that using of FACTS devices can improve the reliability of power networks and power quality in electrical networks, significantly.

Keywords: FACTS devices, power networks, power quality, STATCOM

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9311 Governance Networks of China’s Neighborhood Micro-Redevelopment: The Case of Haikou

Authors: Lin Zhang

Abstract:

Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

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9310 Cluster-Based Multi-Path Routing Algorithm in Wireless Sensor Networks

Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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9309 Cognitive Functioning and Cortisol Suppression in Major Depression in a Long-Term Perspective

Authors: Pia Berner Hansson, Robert Murison Anders Lund, Hammar Åsa

Abstract:

Major Depressive Disorder (MDD) is often associated with high levels of stress and disturbances in the Hypothalamic Pituitary Adrenal (HPA) system, yielding high levels of cortisol, in addition to cognitive dysfunction. Previous studies in this patient group have shown a relationship between cortisol profile and cognitive functioning in the acute phase of MDD and that the patients had significantly less suppression after dexamethasone administration. However, few studies have investigated this relationship over time and in phases of symptom reduction. The aim of the present study was to examine the relationships between cortisol levels after the Dexamethasone Suppression Test (DST) and cognitive function in a long term perspective in MDD patients. Patients meeting the DSM-IV criteria for a MDD were included in the study and tested in symptom reduction. A control group was included. Cortisol was measured in saliva collected with Salivette sampling devices. Saliva samples were collected 4 times during a 24 hours period over two consecutive days: at awakening, after 45 minutes, after 7 hours and at 11 pm. Dexamethasone (1.0 mg) was given on Day 1 at 11 pm. The neuropsychological test battery consisted of standardized tests measuring memory and Executive Functioning (EF). Cortisol levels did not differ significantly between patients and controls on Day 1 or Day 2. Both groups showed significant suppression after Dexamethasone. There were no correlations between cortisol levels or suppression after Dexamethasone and cognitive measures. The results indicate that the HPA-axis functioning normalizes in phases of symptom reduction in MDD patients and that there no relation between cortisol profile and cognitive functioning in memory or EF.

Keywords: depression, MDD, cortisol, suppression, cognitive functioning

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9308 Trusting the Eyes: The Changing Landscape of Eyewitness Testimony

Authors: Manveen Singh

Abstract:

Since the very advent of law enforcement, eyewitness testimony has played a pivotal role in identifying, arresting and convicting suspects. Reliant heavily on the accuracy of human memory, nothing seems to carry more weight with the judiciary than the testimony of an actual witness. The acceptance of eyewitness testimony as a substantive piece of evidence lies embedded in the assumption that the human mind is adept at recording and storing events. Research though, has proven otherwise. Having carried out extensive study in the field of eyewitness testimony for the past 40 years, psychologists have concluded that human memory is fragile and needs to be treated carefully. The question that arises then, is how reliable is eyewitness testimony? The credibility of eyewitness testimony, simply put, depends on several factors leaving it reliable at times while not so much at others. This is further substantiated by the fact that as per scientific research, over 75 percent of all eyewitness testimonies may stand in error; quite a few of these cases resulting in life sentences. Although the advancement of scientific techniques, especially DNA testing, helped overturn many of these eyewitness testimony-based convictions, yet eyewitness identifications continue to form the backbone of most police investigations and courtroom decisions till date. What then is the solution to this long standing concern regarding the accuracy of eyewitness accounts? The present paper shall analyze the linkage between human memory and eyewitness identification as well as look at the various factors governing the credibility of eyewitness testimonies. Furthermore, it shall elaborate upon some best practices developed over the years to help reduce mistaken identifications. Thus, in the process, trace out the changing landscape of eyewitness testimony amidst the evolution of DNA and trace evidence.

Keywords: DNA, eyewitness, identification, testimony, evidence

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9307 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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9306 A Probabilistic View of the Spatial Pooler in Hierarchical Temporal Memory

Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

Abstract:

In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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9305 Deficits in Perceptual and Musical Memory in Individuals with Major Depressive Disorder

Authors: Toledo-Fernandez Aldebaran

Abstract:

Introduction: One of the least explored cognitive functions in relation with depression is the one related to musical stimuli. Music perception and memory can become impaired as well. The term amusia is used to define a type of agnosia caused by damage to basic processes that creates a general inability to perceive music. Therefore, the main objective is to explore performance-based and self-report deficits in music perception and memory on people with major depressive disorder (MDD). Method: Data was collected through April-October 2021 recruiting people who met the eligibility criteria and using the Montreal Battery of Evaluation of Amusia (MBEA) to evaluate performance-based music perception and memory, along with the module for depression of the Mini International Neuropsychiatric Interview, and the Amusic Dysfunction Inventory (ADI) which evaluates the participants’ self-report concerning their abilities in music perception. Results: 64 participants were evaluated. The main study, referring to analyzing the differences between people with MDD and the control group, only showed one statistical difference on the Interval subtest of the MBEA. No difference was found in the dimensions assessed by the ADI. Conclusion: Deficits in interval perception can be explained by mental fatigue, to which people with depression are more vulnerable, rather than by specific deficits in musical perception and memory associated with depressive disorder. Additionally, significant associations were found between musical deficits as observed by performance-based evidence and music dysfunction according to self-report, which could suggest that some people with depression are capable of detecting these deficits in themselves.

Keywords: depression, amusia, music, perception, memory

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9304 Recurrent Neural Networks for Complex Survival Models

Authors: Pius Marthin, Nihal Ata Tutkun

Abstract:

Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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9303 Thermomechanical Processing of a CuZnAl Shape-Memory Alloy

Authors: Pedro Henrique Alves Martins, Paulo Guilherme Ferreira De Siqueira, Franco De Castro Bubani, Maria Teresa Paulino Aguilar, Paulo Roberto Cetlin

Abstract:

Cu-base shape-memory alloys (CuZnAl, CuAlNi, CuAlBe, etc.) are promising engineering materials for several unconventional devices, such as sensors, actuators, and mechanical vibration dampers. Brittleness is one of the factors that limit the commercial use of these alloys, as it makes thermomechanical processing difficult. In this work, a method for the hot extrusion of a 75.50% Cu, 16,74% Zn, 7,76% Al (weight %) alloy is presented. The effects of the thermomechanical processing in the microstructure and the pseudoelastic behavior of the alloy are assessed by optical metallography, compression and hardness tests. Results show that hot extrusion is a suitable method to obtain severe cross-section reductions in the CuZnAl shape-memory alloy studied. The alloy maintained its pseudoelastic effect after the extrusion and the modifications in the mechanical behavior caused by precipitation during hot extrusion can be minimized by a suitable precipitate dissolution heat treatment.

Keywords: hot extrusion, pseudoelastic, shape-memory alloy, thermomechanical processing

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9302 Software-Defined Networks in Utility Power Networks

Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian

Abstract:

Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.

Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller

Procedia PDF Downloads 113