Search results for: memory isolation

Authors: Kenji Gwee

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In Singapore, the death penalty remains in active use for murder and drug trafficking of controlled drugs such as heroin. As such, the psychological assessment of defendants can often be of high stakes. The Test of Memory Malingering (TOMM) is employed by government psychologists to determine the degree of effort invested by defendants, which in turn inform on the veracity of overall psychological findings that can invariably determine the life and death of defendants. The purpose of this study was to find out if defendants facing the death penalty were more likely to invest less effort during psychological assessment (to fake bad in hopes of escaping the death sentence) compared to defendants facing lesser penalties. An archival search of all forensic cases assessed in 2012-2013 by Singapore’s designated forensic psychiatric facility yielded 186 defendants’ TOMM scores. Offence severity, coded into 6 rank-ordered categories, was analyzed in a one-way ANOVA with TOMM score as the dependent variable. There was a statistically significant difference (F(5,87) = 2.473, p = 0.038). A Tukey post-hoc test with Bonferroni correction revealed that defendants facing lower charges (Theft, shoplifting, criminal breach of trust) invested less test-taking effort (TOMM = 37.4±12.3, p = 0.033) compared to those facing the death penalty (TOMM = 46.2±8.1). The surprising finding that those facing death penalties actually invested more test taking effort than those facing relatively minor charges could be due to higher levels of cooperation when faced with death. Alternatively, other legal avenues to escape the death sentence may have been preferred over the mitigatory chance of a psychiatric defence.

Keywords: capital sentencing, offence severity, Singapore, Test of Memory Malingering

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory

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Authors: Anna Moskaleva

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A prolific body of research in theoretical and experimental linguistics claims that a preference for conceptual or grammatical information in the process of agreement greatly depends on the type of agreement dependency. According to the agreement hierarchy, an anaphoric agreement is more sensitive to semantic or conceptual rather than grammatical information of an antecedent. Furthermore, a higher linear distance between a pronoun and its antecedent is assumed to trigger semantic agreement, yet the hierarchical distance is hardly examined in the research field, and the contribution of each distance factor is unclear. Apart from that, working memory volume is deemed to play a role in maintaining grammatical information during language comprehension. The aim of this study is to observe distance and working memory effects in resolution of anaphora with collective nominals (e.g., team) and to have a closer look at the interaction of the factors. Collective nominals in many languages can have a holistic or distributive meaning and can be addressed by a singular or a plural pronoun, respectively. We investigated linguistic factors of linear and rhetorical (hierarchical) distance and a more general factor of working memory volume in their ability to facilitate the interpretation of the number feature of a collective noun in Russian. An eye-tracking reading experiment on comprehension has been conducted where university students were presented with composed texts, including collective nouns and personal pronouns alluding to them. Different eye-tracking measures were calculated using statistical methods. The results have shown that a significant increase in reading time in the case of a singular pronoun was demonstrated when both distances were high, and no such effect was observed when just one of the distances was high. A decrease in reading time has been obtained with distance in the case of a plural pronoun. The working memory effect was not revealed in the experiment. The resonance of distance factors indicates that not only the linear distance but also the hierarchical distance is of great importance in interpreting pronouns. The experimental findings also suggest that, apart from the agreement hierarchy, the preference for conceptual or grammatical information correlates with the distance between a pronoun and its antecedent.

Keywords: collective nouns, agreement hierarchy, anaphora resolution, eye-tracking, language comprehension

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Authors: Ghazala Yasmeen, Zahid Yousaf

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Frequent social media use has significantly changed people's life and communication styles during the last two decades. Social media use has multiple dimensions, and there are nuanced relationships between it and how it affects different societal subgroups. With the increased popularity and rapid growth of social networking sites, people are experiencing potential social media addiction, which causes severe mental health problems. How social media is dramatically influencing the lives and mental health of its users, and particularly of the students, creating psychological issues, e.g., isolation, depression, and anxiety, will be the primary objective of this study. This research will address the problems confronted by many students who are regular social media users and can undergo mental distress. This study aims to explore how social media use can lead to isolation, depression, and anxiety. This research will also investigate the effects of cyber-bullying on social, emotional, and psychological wellbeing. For this purpose, the researcher will use the survey technique as a method of inquiry. Ryff's theory of Psychological wellbeing will be used as a theoretical framework to explore the association between social media addiction and psychological effects among users. For data collection, the researcher will use the quantitative research method through a survey questionnaire from three universities in Pakistan from the public and private sectors. This study will imply a two-stage random sampling technique. At first, the researcher will select 20% of students from universities. In the second stage, 20% of students using different social networking sites will be chosen, and draw a representative sample from these will be. The intended study will use questionnaires comprising two portions. The first section will consist of social media engagement by the students, following impacts on their mental health and reported attitude towards psychological wellbeing. This study will spotlight the considerations of parents, educationists, and policymakers to take measures against the devastating effects of cyber-crimes on young adults.

Keywords: anxiety, depression, isolation, social media, wellbeing

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Authors: Jayson Wau, David Timi, Anthony Harakuwe, Bruce Bowden, Cherie Motti, Harry Sakulas, Rag Gubag-Sipou

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The latex of F. botryocarpa fruit is applied on sores, wounds and other skin infections in Papua New Guinea ethnotherapeutic practices. Systematic bioassay guided separation and isolation of subsequent fractions of latex extracts resulted in three bioactive fractions active against Staphylococcus aureus and Escherichia coli. This study reports structural elucidation of the three isolates. Structures were determined by physical (M.pt and Rf values) and spectroscopic (1D-1H NMR, 2D-HSQC NMR, 2D-HMBC NMR) and MS ESI-POS. The two methylene protons (2H-1) and (2H-3) resonate as triplets at δ 3.59 and δ 4.99 respectively. Electron dense δ 4.99 (2H-3) on (C-3) depicts the strong electron-withdrawing component, quaternary nitrogen (=N= +). Protons resonating at δ 3.88 and 3.89 are singlets depicting two methoxy groups. Both δ 3.88 and δ 3.89 are para-aryls substituents. The methines δ 9.13 and 8.60 are singlets depicting two lone protons on the indolizidinium aryl component. All isolates, (1), (2) and (3) were identified to be ficuseptine by comparing 1D-NMR assignments. 2D-NMR and MS of (2) found it to be ficuseptine chloride '2, 3-dihydro-6, 8-bis (4-methoxyphenyl)-, 1H-indolizinium chloride'. Their counter ions of the ficuseptines were not established and provide promising lead for the further investigation.

Keywords: Ficus botryocarpa, antimicrobial activity, ficuseptine, sores

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Authors: Baali Mohamed

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Campylobacter are among the most common human bacterial gastroenteritis cases in many countries, and poultry meat is considered as a major source of human campylobacteriosis. This study is conducted, on one hand, to determine the prevalence of infection with thermotolerant Campylobacter both in broiler flocks and men, and to study their sensitivity to antibiotics, and secondly for comparing the two methods of isolation of Campylobacter thermotolerant: technique of passive filtration and selective isolation technique using the Karmali medium. This study examined 310 samples, 260 of avian origin and 50 of human origin, during the period from June 2011 to March 2012. Detecting Campylobacter thermotolerant is conducted using the standard ISO 10272. The results show that 66% (95% CI : 60-72%) of avian samples are contaminated with C. TT (172/260). The study of antibiotic susceptibility revealed that all strains (100%) are resistant to ampicillin and amoxicillin/clavulanic acid, 90% to erythromycin, 66.3% to tetracycline, 53.3% to chloramphenicol and 46.7% to enrofloxacin. However, no resistance is noted to gentamycin. In human samples, three strains of C. thermotolerant are detected, with a contamination rate of 6%. The results of the statistical analysis using the chi-square test (χ2) showed that Campylobacter infection, on the one hand, had seasonal variation with a summer peak (p < 0.05) and, on the other hand, are not influenced by the size of the herd.

Keywords: thermotolerant campylobacter, broiler, man, Karmali

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Authors: Mohammadreza Azarnoush, Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considers the consumption of fossil fuels and also reduction of consumption civil energy in megacities as playing a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming, and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials, and the adoption to the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article, we investigate the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

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Authors: Eric Tardif, Nicolas Meylan

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Recent studies suggest that the consolidation of episodic memory is better achieved through repeated retrieval than with the use of concept mapping or repeated study. Although such laboratory results highly appeal to educationalists, it remains to be shown whether they can be directly used in a classroom setting. Forty-five college students (42 girls; mean age 16.1 y/o) were asked to remember pairs of biology-related words (e.g. mitochondria-energy) in two configurations. The first configuration consisted of a three-minute study of pairs of words followed by a final one-minute test in which the first word of a pair was shown and the subject asked to write down the second associated word. This procedure was repeated three times. The second configuration consisted of a one-minute study of a list of pairs of words, which was immediately followed by a one-minute test. This procedure was repeated 6 times. Subjects filled out a small questionnaire assessing their general mood, level of fatigue, stress and motivation to do the exercise. One week later, subjects were given a final test using the same words. A total of 8 lists of words were studied and tested during the semester. Results showed that subjects recalled more correct words when using the second configuration, both within the study period and one week later, confirming laboratory findings. However, the general performance (mean items recalled) as well as the motivation to do the exercise gradually decreased during the semester. Motivation was positively correlated with performance (r=0.77, p<0.05). The results suggest that laboratory findings may provide some applications in education but other variables inherent to the classroom setting must also be considered.

Keywords: long-term, episodic memory, consolidation, retrieval, school setting

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Authors: Kazushige Wada, Mayuko Ueda

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In the present study, we reanalyzed lapse errors in the last phase of a job, by re-counting near lapse errors and increasing the number of participants. We also examined the results of this study from the perspective of prospective memory (PM), which concerns future actions. This study was designed to investigate whether perceiving the importance of PM tasks caused lapse errors in the last phase of a job and to determine if such errors could be explained from the perspective of PM processing. Participants (N = 34) conducted a computerized clicking task, in which they clicked on 10 figures that they had learned in advance in 8 blocks of 10 trials. Participants were requested to click the check box in the start display of a block and to click the checking off box in the finishing display. This task was a PM task. As a measure of PM performance, we counted the number of omission errors caused by forgetting to check off in the finishing display, which was defined as a lapse error. The perceived importance was manipulated by different instructions. Half the participants in the highly important task condition were instructed that checking off was very important, because equipment would be overloaded if it were not done. The other half in the not important task condition was instructed only about the location and procedure for checking off. Furthermore, we controlled workload and the emotion of surprise to confirm the effect of demand capacity and attention. To manipulate emotions during the clicking task, we suddenly presented a photo of a traffic accident and the sound of a skidding car followed by an explosion. Workload was manipulated by requesting participants to press the 0 key in response to a beep. Results indicated too few forgetting induced lapse errors to be analyzed. However, there was a weak main effect of the perceived importance of the check task, in which the mouse moved to the “END” button before moving to the check box in the finishing display. Especially, the highly important task group showed more such near lapse errors, than the not important task group. Neither surprise, nor workload affected the occurrence of near lapse errors. These results imply that high perceived importance of PM tasks impair task performance. On the basis of the multiprocess framework of PM theory, we have suggested that PM task performance in this experiment relied not on monitoring PM tasks, but on spontaneous retrieving.

Keywords: prospective memory, perceived importance, lapse errors, multi process framework of prospective memory.

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Authors: Samil Ozcan

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Airlines companies target different customer segments in consideration of pricing, service quality, flight network, etc. and their brand positioning accords with the marketization strategies developed in the same direction. The object of this study, Turkish Airlines, has many peculiarities regarding its brand positioning as compared to its rivals in the sector. In the first place, it appeals to a global customer group because of its Star Alliance membership and its broad flight network with 315 destination points. The second group in its customer segmentation includes domestic customers. For this group, the company follows a marketing strategy that plays to local culture and accentuates the image of Turkishness as an emotional allurement. The advertisements and publicity projects designed in this regard put little emphasis on the service quality the company offers to its clients; it addresses the emotions of the consumers rather than individual benefits and relies on the historical memory of the nation and shared cultural values. This study examines the publicity work which aims at the second segment customer group focusing on Turkish Airlines’ 85th Anniversary Commercial through a symbolic meaning analysis approach. The commercial presents six stories with undertones of nationalism in its theme. Nationalism is not just the product of collective interests based on reason but a result of patriotism in the sense of loyalty to state and nation and love of ethnic belonging. While nationalism refers to concrete notions such as blood tie, common ancestor, shared history, it is not the actuality of these notions that it draws its real strength but the emotions invested in them. The myths of origin, the idea of common homeland, boundary definitions, and symbolic acculturation have instrumental importance in the development of these commonalities. The commercial offers concrete examples for an analysis of Connor’s definition of nationalism based on emotions. Turning points in the history of the Turkish Republic and the historical mission Turkish Airlines undertook in these moments are narrated in six stories in the commercial with a highly emotional theme. These emotions, in general, depend on collective memory generated by national consciousness. Collective memory is not simply remembering the past. It is constructed through the reconstruction and reinterpretation of the past in the present moment. This study inquires the motivations behind the nationalist emotions generated within the collective memory by engaging with the commercial released for the 85th anniversary of Turkish Airlines as the object of analysis. Symbols and myths can be read as key concepts that reveal the relation between 'identity and memory'. Because myths and symbols do not merely reflect on collective memory, they reconstruct it as well. In this sense, the theme of the commercial defines the image of Turkishness with virtues such as self-sacrifice, helpfulness, humanity, and courage through a process of meaning creation based on symbolic mythologizations like flag and homeland. These virtues go beyond describing the image of Turkishness and become an instrument that defines and gives meaning to Turkish identity.

Keywords: collective memory, emotions, identity, nationalism

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

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The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: S. Rostampour Yasouri, M. Ghane

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Leptospirosis is one the most important common diseases between human and live stock occurred by different species of Leptospira. This disease has been construed as the native in the northern provinces of Iran and risk of the infection with pathogenic is high. One hundred fifteen samples of water (67), soil (36) and feces of rodents (12) were collected from the rice fields of the suburbs of Tonekabon Township situated in northern part of Iran in 2012. The samples, after passage from membranous filters, were cultured in the liquid and solid EMJH medium and incubated at 30°C for 1 month. Leptospira spp. were isolated using culture technique, and the plates were studied from viewpoint of colony formation, microscopic observations and then identified by phenotyping tests. Finally, the identification of Leptospira genus was verified by PCR technique and 16S rRNA gene sequencing. Of 115 samples totally, 55 samples (47.82%) became positive by use of the culture technique which the positive cases included 47 water samples (70.14%) and 8 soil samples (22.22%), while the isolation was not accomplished from the sample of the rodents feces. Overall, according to these data, Leptospira spp. exists with high frequency in North Iran. Hence, based on foregoing evidence environments in the north of Iran are vehicles of Leptospira spp.

Keywords: EMJH Medium, Leptospira, Northern of Iran, rice fields

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Authors: Chan Kwong Tung

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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

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Authors: Asim Quddus

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A miniaturized three dimensional co-planar waveguide (CPW) two-port MIMO antenna, exhibiting high isolation and WLAN band-notched characteristics is presented in this paper for ultrawideband (UWB) communication applications. The microstrip patch antenna operates as a single UWB antenna element. The proposed design is a cuboid-shaped structure having compact size of 35 x 27 x 45 mm³. Radiating as well as decoupling structure is placed around cuboidal polystyrene sheet. The radiators are 27 mm apart, placed Face-to-Face in vertical direction. Decoupling structure is placed on the side walls of polystyrene. The proposed antenna consists of an oval shaped radiating patch. A rectangular structure with fillet edges is placed on ground plan to enhance the bandwidth. The proposed antenna exhibits a good impedance match (S11 ≤ -10 dB) over frequency band of 2 GHz – 10.6 GHz. A circular slotted structure is employed as a decoupling structure on substrate, and it is placed on the side walls of polystyrene to enhance the isolation between antenna elements. Moreover, to achieve immunity from WLAN band distortion, a modified, inverted crescent shaped slotted structure is etched on radiating patches to achieve band-rejection characteristics at WLAN frequency band 4.8 GHz – 5.2 GHz. The suggested decoupling structure provides isolation better than 15 dB over the desired UWB spectrum. The envelope correlation coefficient (ECC) and gain for the MIMO antenna are analyzed as well. Finite Element Method (FEM) simulations are carried out in Ansys High Frequency Structural Simulator (HFSS) for the proposed design. The antenna is realized on a Rogers RT/duroid 5880 with thickness 1 mm, relative permittivity ɛr = 2.2. The proposed antenna achieves a stable omni-directional radiation patterns as well, while providing rejection at desired WLAN band. The S-parameters as well as MIMO parameters like ECC are analyzed and the results show conclusively that the design is suitable for portable MIMO-UWB applications.

Keywords: 3-D antenna, band-notch, MIMO, UWB

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Authors: Camille Intson

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This paper endeavors to explore the opportunities, challenges, and ethics of reconstructing and re-enacting archives of memory through virtual reality (VR) performance, using Jordan Tannahill’s Draw Me Close as an exemplary case study. Draw Me Close is a 1:1 virtual reality (VR) performance in which the artist’s childhood memories, experiences, and interactions with his mother are reconstructed in the wake of her passing. Solo audience members are positioned as Jordan (the subject and character) and taken through a series of narratives, (virtual) spaces, and interactions with his “mother,” played by a live actor. Piece by piece, audiences are brought into the world of the “shifting” archive, inhabiting Jordan’s reconstructed virtual world from his early explorations of queer sexuality through to his mother’s cancer diagnosis and passing. This paper will explore how the world of Draw Me Close represents a “touching” and/or “queering” of time within its archive, blurring and transgressing the boundaries between the animate and the inanimate, life and death. On a philosophical level, considering foundational queer performance scholarship and archival theory, it will also examine how performance’s ephemerality rewards its artists with the dual advantages of visibility and protection, allowing for an ethical exploration of traumatic memory and loss within a disappearing medium. Finally, this provocation will use Draw Me Close as a point of departure from which to outline future possibilities for performance and emerging technologies’ engagements with archival theory and practice. By positioning virtual reality (VR) as an archive-constructing medium, it aims to move beyond the question of how we can take performances seriously as archives towards how personal archive construction is itself a performative act.

Keywords: intermedial theatre, new media arts, queer performance, virtual reality

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Authors: Andi Aliah Hidayani, Asmi Citra Malina A. R. Tassakka, Andi Parenrengi

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Vanname Shrimp is one of the high yielding varieties that are more resistant to virus attacks. However, now this shrimp more death due to virus attack such as white spot disease caused by white spot syndrome virus (WSSV). Various efforts have done to prevent the disease, like immunostimulatory, probiotics, and vaccine. White spot syndrome virus (WSSV) envelope protein VP19 gene is important because of its involvement in the system infection of shrimp. This study aimed to isolate and characterize an envelope protein VP19 – encoding gene of WSSV using WSSV infected Vanname Shrimp sample from some areas in South Sulawesi (Pangkep, Barru and Pinrang). The genomic of DNA were isolated from shrimp muscle using DTAB-CTAB method. Isolation of gene encoding envelope protein VP19 WSSV ws successfully performed with the results of the length of DNA fragment was 387 bp. The results of homology analysis using BLASTn homology suggested that these isolates genes from Barru, Pangkep and Pinrang have closest relationship with isolates from Mexican.

Keywords: vanname, shrimp, WSSV, viral protein 19

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Authors: W. J. Kim

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The behaviors of the recovery stress and strain of an ultrafine-grained Ni-50.2 at.% Ti alloy prepared by high-ratio differential speed rolling (HRDSR) were examined by a specially designed tensile-testing set up, and the factors that influence the recovery stress and strain were studied. After HRDSR, both the recovery stress and strain were enhanced compared to the initial condition. The constitutive equation showing that the maximum recovery stress is a sole function of the recovery strain was developed based on the experimental data. The recovery strain increased as the yield stress increased. The maximum recovery stress increased with an increase in yield stress. The residual recovery stress was affected by the yield stress as well as the austenite-to-martensite transformation temperature. As the yield stress increased and as the martensitic transformation temperature decreased, the residual recovery stress increased.

Keywords: high-ratio differential speed rolling, tensile testing, severe plastic deformation, shape memory alloys

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Authors: Swati Bajpai, S. P. K Jena

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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

Procedia PDF Downloads 164

Authors: Onmanee Prajuabjinda, Pakakrong Thondeeying, Jipisute Chunthorng-Orn, Bhanuz Dechayont, Arunporn Itharat

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A Thai medicinal preparation has been used for cancer treatment more than ten years ago in Khampramong Temple. Tectona grandis stem is one ingredient of this Thai medicinal remedy. The ethanolic extract of Tectona grandis stem showed the highest cytotoxic activities against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23) (IC50 = 3.92 and 7.78 µg/ml, respectively). It was isolated by bioassay-guided isolation method. Tectoquinone, a anthraquinone compound was isolated from this plant. This compound showed high specific cytotoxicity against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23)(IC50 =16.15 and 47.56 µg/ml or 72.67 and 214.00 µM, respectively). However, it showed less cytotoxic activity than the crude extract. In conclusion, tectoquinone as a main compound, is not the best cytotoxic compound from Tectona grandis, so there are more active cytotoxic compounds in this extract which should be isolated in the future. Moreover, tectoquinone displayed specific cytotoxicity against only human breast adenocarcinoma (MCF-7) which is a good criterion for cancer treatment.

Keywords: Tectona grandis, SRB assay, cytotoxicity, tectoquinone

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Authors: Mahmoud Lot

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In this article, we will discuss the solution of elliptic optimal control problem. First, by using the nite element method, we obtain the discrete form of the problem. The obtained discrete problem is actually a large scale constrained optimization problem. Solving this optimization problem with traditional methods is difficult and requires a lot of CPU time and memory. But split Bergman method converts the constrained problem to an unconstrained, and hence it saves time and memory requirement. Then we use the split Bregman method for solving this problem, and examples show the speed and accuracy of split Bregman methods for solving these types of problems. We also use the SQP method for solving the examples and compare with the split Bregman method.

Keywords: Split Bregman Method, optimal control with elliptic partial differential equation constraint, finite element method

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Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

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In the current paper, an indoor positioning system is proposed with consideration of measurement delay. Firstly, an estimation filter with a measurement delay is designed for the indoor positioning mechanism under a weighted least square criterion, which utilizes only finite measurements on the most recent window. The proposed estimation filtering based scheme gives the filtered estimates for position, velocity and acceleration of moving target in real-time, while removing undesired noisy effects and preserving desired moving positions. Secondly, the proposed scheme is shown to have good inherent properties such as unbiasedness, efficiency, time-invariance, deadbeat, and robustness due to the finite memory structure. Finally, computer simulations shows that the performance of the proposed estimation filtering based scheme can outperform to the existing infinite memory filtering based mechanism.

Keywords: indoor positioning system, wireless sensor networks, measurement delay

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Authors: Behrang Tavousi Tehrani, Mohammad-Zaman Kabir

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Shape memory alloys (SMA) are often implemented in smart structures as the active components. Their ability to recover large displacements has been used in many applications, including structural stability/response enhancement and active structural acoustic control. SMA wires or fibers can be embedded with composite cylinders to increase their critical buckling load, improve their load-deflection behavior, and reduce the radial deflections under various thermo-mechanical loadings. This paper presents a semi-analytical investigation on the non-linear load-deflection response of SMA-reinforced composite circular cylindrical shells. The cylinder shells are under uniform external pressure load. Based on first-order shear deformation shell theory (FSDT), the equilibrium equations of the structure are derived. One-dimensional simplified Brinson’s model is used for determining the SMA recovery force due to its simplicity and accuracy. Airy stress function and Galerkin technique are used to obtain non-linear load-deflection curves. The results are verified by comparing them with those in the literature. Several parametric studies are conducted in order to investigate the effect of SMA volume fraction, SMA pre-strain value, and SMA activation temperature on the response of the structure. It is shown that suitable usage of SMA wires results in a considerable enhancement in the load-deflection response of the shell due to the generation of the SMA tensile recovery force.

Keywords: airy stress function, cylindrical shell, Galerkin technique, load-deflection curve, recovery stress, shape memory alloy

Procedia PDF Downloads 188

Authors: Igor Jerkovic

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Biodiversity of flora provides many different nectar sources for the bees. Unifloral honeys possess distinctive flavours, mainly derived from their nectar sources (characteristic volatile organic components (VOCs)). Specific or nonspecific VOCs (chemical markers) could be used for unifloral honey characterisation as addition to the melissopalynologycal analysis. The main honey volatiles belong, in general, to three principal categories: terpenes, norisoprenoids, and benzene derivatives. Some of these substances have been described as characteristics of the floral source, and other compounds, like several alcohols, branched aldehydes, and furan derivatives, may be related to the microbial purity of honey processing and storage conditions. Selection of the extraction method for the honey volatiles profiling should consider that heating of the honey produce different artefacts and therefore conventional methods of VOCs isolation (such as hydrodistillation) cannot be applied for the honey. Two-way approach for the isolation of the honey VOCs was applied using headspace solid-phase microextraction (HS-SPME) and ultrasonic solvent extraction (USE). The extracts were analysed by gas chromatography and mass spectrometry (GC-MS). HS-SPME (with the fibers of different polarity such as polydimethylsiloxane/ divinylbenzene (PDMS/DVB) or divinylbenzene/carboxene/ polydimethylsiloxane (DVB/CAR/PDMS)) enabled isolation of high volatile headspace VOCs of the honey samples. Among them, some characteristic or specific compounds can be found such as 3,4-dihydro-3-oxoedulan (in Centaurea cyanus L. honey) or 1H-indole, methyl anthranilate, and cis-jasmone (in Citrus unshiu Marc. honey). USE with different solvents (mainly dichloromethane or the mixture pentane : diethyl ether 1 : 2 v/v) enabled isolation of less volatile and semi-volatile VOCs of the honey samples. Characteristic compounds from C. unshiu honey extracts were caffeine, 1H-indole, 1,3-dihydro-2H-indol-2-one, methyl anthranilate, and phenylacetonitrile. Sometimes, the selection of solvent sequence was useful for more complete profiling such as sequence I: pentane → diethyl ether or sequence II: pentane → pentane/diethyl ether (1:2, v/v) → dichloromethane). The extracts with diethyl ether contained hydroquinone and 4-hydroxybenzoic acid as the major compounds, while (E)-4-(r-1’,t-2’,c-4’-trihydroxy-2’,6’,6’-trimethylcyclo-hexyl)but-3-en-2-one predominated in dichloromethane extracts of Allium ursinum L. honey. With this two-way approach, it was possible to obtain a more detailed insight into the honey volatile and semi-volatile compounds and to minimize the risks of compound discrimination due to their partial extraction that is of significant importance for the complete honey profiling and identification of the chemical biomarkers that can complement the pollen analysis.

Keywords: honey chemical biomarkers, honey volatile compounds profiling, headspace solid-phase microextraction (HS-SPME), ultrasonic solvent extraction (USE)

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Mohamad Khairi Ishak

Abstract:

Conventional public key crypto systems such as RSA (Ron Rivest, Adi Shamir and Leonard Adleman), DSA (Digital Signature Algorithm), and Elgamal are no longer efficient to be implemented in the small, memory constrained devices. Elliptic Curve Cryptography (ECC), which allows smaller key length as compared to conventional public key crypto systems, has thus become a very attractive choice for many applications. This paper describes implementation of an elliptic curve cryptography (ECC) encryption engine on a FPGA. The system has been implemented in 2 different key sizes, which are 131 bits and 163 bits. Area and timing analysis are provided for both key sizes for comparison. The crypto system, which has been implemented on Altera’s EPF10K200SBC600-1, has a hardware size of 5945/9984 and 6913/9984 of logic cells for 131 bits implementation and 163 bits implementation respectively. The crypto system operates up to 43 MHz, and performs point multiplication operation in 11.3 ms for 131 bits implementation and 14.9 ms for 163 bits implementation. In terms of speed, our crypto system is about 8 times faster than the software implementation of the same system.

Keywords: elliptic curve cryptography, FPGA, key sizes, memory

Procedia PDF Downloads 322