Search results for: long-term memory recall

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Ashleigh Beales, Anne Whitworth, Jade Cartwright

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Background: While significant benefits of lexical retrieval intervention are evident within the Primary Progressive Aphasia (PPA) and Alzheimer’s disease (AD) literature, an understanding of the mechanisms that underlie change or improvement is limited. Change mechanisms have been explored in the non-progressive post-stroke literature that may offer insight into how interventions affect change with progressive language disorders. The potential influences of cognitive factors may also play a role here, interacting with the aims of intervention. Exploring how such processes have been applied is likely to grow our understanding of how interventions have, or have not, been effective, and how and why generalisation is likely, or not, to occur. Aims: This review of the literature aimed to (1) investigate the proposed mechanisms of change which underpin lexical interventions, mapping the PPA and AD lexical retrieval literature to theoretical accounts of mechanisms that underlie change within the broader intervention literature, (2) identify whether and which nonlinguistic cognitive functions have been engaged in intervention with these populations and any proposed influence, and (3) explore evidence of linguistic generalisation, with particular reference to change mechanisms employed in interventions. Main contribution: A search of Medline, PsycINFO, and CINAHL identified 36 articles that reported data for individuals with PPA or AD following lexical retrieval intervention. A review of the mechanisms of change identified 10 studies that used stimulation, 21 studies utilised relearning, three studies drew on reorganisation, and two studies used cognitive-relay. Significant treatment gains, predominantly based on linguistic performance measures, were reported for all client groups for each of the proposed mechanisms. Reorganisation and cognitive-relay change mechanisms were only targeted in PPA. Eighteen studies incorporated nonlinguistic cognitive functions in intervention; these were limited to autobiographical memory (16 studies), episodic memory (three studies), or both (one study). Linguistic generalisation outcomes were inconsistently reported in PPA and AD studies. Conclusion: This review highlights that individuals with PPA and AD may benefit from lexical retrieval intervention, irrespective of the mechanism of change. Thorough application of a theory of intervention is required to gain a greater understanding of the change mechanisms, as well as the interplay of nonlinguistic cognitive functions.

Keywords: Alzheimer's disease, lexical retrieval, mechanisms of change, primary progressive aphasia

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Authors: Kedibone Masenya, Memory Tekere, Jasper Rees

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Sorghum is an important cereal crop in the world. In particular, it has attracted breeders due to capacity to serve as food, feed, fiber and bioenergy crop. Like any other plant, sorghum hosts a variety of microbes, which can either, have a neutral, negative and positive influence on the plant. In the current study, regions (V3/V4) of 16 S rRNA were targeted to extensively assess bacterial multitrophic interactions in the phyllosphere of sorghum. The results demonstrated that the presence of a pathogen has a significant effect on the endophytic bacterial community. Understanding these interactions is key to develop new strategies for plant protection.

Keywords: bacteria, multitrophic, sorghum, target sequencing

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Vladimir Smirnov, Roman Tominov, Vadim Avilov, Oleg Ageev

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The creation of a new generation micro- and nanoelectronics elements opens up unlimited possibilities for electronic devices parameters improving, as well as developing neuromorphic computing systems. Interest in the latter is growing up every year, which is explained by the need to solve problems related to the unstructured classification of data, the construction of self-adaptive systems, and pattern recognition. However, for its technical implementation, it is necessary to fulfill a number of conditions for the basic parameters of electronic memory, such as the presence of non-volatility, the presence of multi-bitness, high integration density, and low power consumption. Several types of memory are presented in the electronics industry (MRAM, FeRAM, PRAM, ReRAM), among which non-volatile resistive memory (ReRAM) is especially distinguished due to the presence of multi-bit property, which is necessary for neuromorphic systems manufacturing. ReRAM is based on the effect of resistive switching – a change in the resistance of the oxide film between low-resistance state (LRS) and high-resistance state (HRS) under an applied electric field. One of the methods for the technical implementation of neuromorphic systems is cross-bar structures, which are ReRAM cells, interconnected by cross data buses. Such a structure imitates the architecture of the biological brain, which contains a low power computing elements - neurons, connected by special channels - synapses. The choice of the ReRAM oxide film material is an important task that determines the characteristics of the future neuromorphic system. An analysis of literature showed that many metal oxides (TiO2, ZnO, NiO, ZrO2, HfO2) have a resistive switching effect. It is worth noting that the manufacture of nanocomposites based on these materials allows highlighting the advantages and hiding the disadvantages of each material. Therefore, as a basis for the neuromorphic structures manufacturing, it was decided to use ZnₓTiᵧHfzOᵢ nanocomposite. It is also worth noting that the ZnₓTiᵧHfzOᵢ nanocomposite does not need an electroforming, which degrades the parameters of the formed ReRAM elements. Currently, this material is not well studied, therefore, the study of the effect of resistive switching in forming-free ZnₓTiᵧHfzOᵢ nanocomposite is an important task and the goal of this work. Forming-free nanocomposite ZnₓTiᵧHfzOᵢ thin film was grown by pulsed laser deposition (Pioneer 180, Neocera Co., USA) on the SiO2/TiN (40 nm) substrate. Electrical measurements were carried out using a semiconductor characterization system (Keithley 4200-SCS, USA) with W probes. During measurements, TiN film was grounded. The analysis of the obtained current-voltage characteristics showed a resistive switching from HRS to LRS resistance states at +1.87±0.12 V, and from LRS to HRS at -2.71±0.28 V. Endurance test shown that HRS was 283.21±32.12 kΩ, LRS was 1.32±0.21 kΩ during 100 measurements. It was shown that HRS/LRS ratio was about 214.55 at reading voltage of 0.6 V. The results can be useful for forming-free nanocomposite ZnₓTiᵧHfzOᵢ films in neuromorphic systems manufacturing. This work was supported by RFBR, according to the research project № 19-29-03041 mk. The results were obtained using the equipment of the Research and Education Center «Nanotechnologies» of Southern Federal University.

Keywords: nanotechnology, nanocomposites, neuromorphic systems, RRAM, pulsed laser deposition, resistive switching effect

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Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

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Authors: Akiyoshi Wakatani

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This paper describes the Message Passing Interface (MPI) implementation of ADETRAN language, and its evaluation on SX-ACE supercomputers. ADETRAN language includes pdo statement that specifies the data distribution and parallel computations and pass statement that specifies the redistribution of arrays. Two methods for implementation of pass statement are discussed and the performance evaluation using Splitting-Up CG method is presented. The effectiveness of the parallelization is evaluated and the advantage of one dimensional distribution is empirically confirmed by using the results of experiments.

Keywords: iterative methods, array redistribution, translator, distributed memory

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Authors: Jaechun No

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This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.

Keywords: SSD, data section, I/O optimizations, hybrid system

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Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

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Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

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Authors: H. Gorine, M. Ramadan Elmezughi

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In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: wireless sensor networks, network security, light weight encryption, threats

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Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Shahram Keshavarzi

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Today, getting good service, having a good time, and leaving the company with good feelings are importanttforbothcustomers and businesses. It has been observed that when customersareexposedtopleasantsmells, their visit times increase by 26%, and theyvisittheaislesfor 3 times longer. Byusingtheeffect of scents on people, it is toensurethatcustomersshopmore, benefit from the service and be satisfied. Intoday'sresearch, visual memory can be 40% effective after a period of 4 months, whileolfactorymemory is 60% moreeffectiveevenafter 1 year. The purpose of the research is thehiddenandeffectivepower of skepticism in the behavior of consumersandtheeffectivestrategy of modern marketing. Special scentsdirectlyaffecttheincrease in sales by influencing the customer's-decision mechanism in purchasing products.

Keywords: modern marketing strategy, scent, scent marketing, consumer behavior

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: Lev Bertovsky

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The purpose of this study was to determine the reasons for the formation of false testimony from witnesses and make recommendations on the recognition of such cases. During the studies, which were based on the achievements of professionals in the field of psychology, as well as personal investigative practice, the stages of perception of the information were studied, as well as the process of its reclaim from the memory and transmission to the communicator upon request. Based on the principles of the human brain, kinds of conscientious witness mistakes were systematized. Proposals were formulated for the optimization of investigative actions in cases where the witnesses make an honest mistake with respect to the effects previously observed by them.

Keywords: criminology, eyewitness testimony, honest mistake, information, investigator, investigation, questioning

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Authors: Inês Boticas, Diana P. Ferreira, Ana Eusébio, Carlos Silva, Pedro Magalhães, Ricardo Silva, Raul Fangueiro

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Since the beginning of the 20^th century, sportswear has a major contribution to the impact of fashion on our lives. Nowadays, the embracing of sportswear fashion/looks is undoubtedly noticeable, as the modern consumer searches for high comfort and linear aesthetics for its clothes. This compromise lead to the arise of the athleisure trend. Athleisure surges as a new style area that combines both wearability and fashion sense, differentiated from the archetypal sportswear, usually associated to “gym clothes”. Additionally, the possibility to functionalize and implement new technologies have shifted and progressively empowers the connection between the concepts of physical activities practice and well-being, allowing clothing to be more interactive and responsive with its surroundings. In this study, a design inspired in retro and urban lifestyle was envisioned, engineering textile structures that can respond to external stimuli. These structures are enhanced to be responsive to heat, water vapor and humidity, integrating shape memory polymers (SMP) to improve the breathability and heat-responsive behavior of the textiles and zinc oxide nanoparticles (ZnO NPs) to heighten the surface hydrophobic properties. The best results for hydrophobic exhibited superhydrophobic behavior with water contact angle (WAC) of more than 150 degrees. For the breathability and heat-response properties, SMP-coated samples showed an increase in water vapour permeability values of about 50% when compared with non SMP-coated samples. These innovative technological approaches were endorsed to design innovative clothing, in line with circular economy and eco-design principles, by assigning a substantial degree of mutability and versatility to the clothing. The development of a coat and shirt, in which different parts can be purchased separately to create multiple products, aims to combine the technicality of both the fabrics used and the making of the garments. This concept translates itself into a real constructive mechanism through the symbiosis of high-tech functionalities and the timeless design that follows the athleisure aesthetics.

Keywords: breathability, sportswear and casual clothing, sustainable design, superhydrophobicity

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Authors: Ghoul Rachid Brahim, Trad Khodja Rafik

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Vertebral localization of the hydatid cyst is a severe form of bone hydatidosis, is a parasitic infection caused by the larval forms of the tapeworms Echinococcus granulosus, The disease is slowly remaining silent (a long incubation period) which may explain why this pathology is often discovered at the stage of neurological complications. The objective of this study is to recall the clinical and radiological aspects of this condition and the importance of early diagnosis and appropriate management. We report a study of 5 patients with vertebral hydatidosis, four men and one woman, four (04) patients operated in the emergency setting for spinal cord compression (decompression by wide laminectomy with evacuation of intra and extra canal vesicles).Albendazole-based medical treatment is instituted in all patients. Results: The evolution was favorable for three patients, the other two patients reoperated for a local recurrence. Conclusion: Vertebral hydatidosis is a rare condition with a poor prognosis due to the risk of neurological damage, the infiltrating nature of bone lesions, the frequency of relapses and therapeutic difficulties. The only curative method remains surgery, which must aim for complete and large excision of the lesions as if it were a “malignant tumour”.

Keywords: hydatidosis, Echinococcosis granulosus, hydatid cyst, spinal cord compression, laminectomy

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Authors: Vano Tsertsvadze, Marina Chavchanidze, Lali Khurtsia

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Problem of drug use is often seen as a combination of psychological and social problems, but this problem can be considered as economically rational decision in the process of buying pleasure (looking after children, reading, harvesting fruits in the fall, sex, eating, etc.). Before the adoption of the decisions people face to a trade-off - when someone chooses a delicious meal, she takes a completely rational decision, that the pleasure of eating has a lot more value than the pleasure which she will experience after two months diet on the summer beach showing off her beautiful body. This argument is also true for alcohol, drugs and cigarettes. Smoking has a negative effect on health, but smokers are not afraid of the threat of a lung cancer after 40 years, more valuable moment is a pleasure from smoking. Our hypothesis - unsatisfied pleasure and frustration, probably determines the risk of dependence on drug abuse. The purpose of research: 1- to determine the relative measure unit of pleasure, which will be used to measure and assess the intensity of various human pleasures. 2- to compare the intensity of the pleasure from different kinds of activity, with pleasures received from drug use. 3- Based on the analysis of data, to identify factors affecting the rational decision making. Research method: Respondents will be asked to recall the greatest pleasure of their life, which will be used as a measure of the other pleasures. The study will use focus groups and structured interviews.

Keywords: drug, drug-user, measurement, satisfaction

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Peter Falanga

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During the process of de-Stalinization that began in 1956 with the Twentieth Congress of the Soviet Communist Party, many filmmakers in Hungary chose to explore their country’s political discomforts by using Socialist Realism as a negative model against which they could react to the dominating ideology. A renewed national film industry and a more permissive political regime would allow filmmakers to take to task the plight of the preceding generation who had experienced the fatal political turmoil of both World Wars and the purges of Stalin. What follows is no longer the multigenerational unity found in Socialist Realism wherein both the old and the young embrace Stalin’s revolutionary optimism; instead, the protagonists are parentless, and thus their connection to the previous generation is partially severed. In these films, violent historical forces leave one generation to search for both a connection with their family’s past, and for moral guidance to direct their future. István Szabó’s Father (1966), Márta Mészáros Diary for My Children (1984), and Pál Gábor’s Angi Vera (1978) each consider the fraught relationship between successive generations through the lens of postwar youth. A characteristic each of their protagonist’s share is that they are all missing one or both parents, and cope with familial loss either through recalling memories of their parents in dream-like sequences, or, in the case of Angi Vera, through embracing the surrogate paternalism that the Communist Party promises to provide. This paper considers the argument these films present about the progress of Hungarian history, and how this topic is explored in more recent films that similarly focus on the transmission of generational values. Scholars such as László Strausz and John Cunningham have written on the continuous concern with the transmission of generational values in more recent films such as István Szabó’s Sunshine (1999), Béla Tarr’s Werckmeister Harmonies (2000), György Pálfi’s Taxidermia (2006), Ágnes Kocsis’ Pál Adrienn (2010), and Kornél Mundruczó’s Evolution (2021). These films, they argue, make intimate portrayals of the various sweeping political changes in Hungary’s history and question how these epochs or events have impacted Hungarian identities. If these films attempt to personalize historical shifts of Hungary, then what is the significance of featuring characters who have lost one or both parents? An attempt to understand this coherent trend in Hungarian cinema will profit from examining the earlier, celebrated films of Szabó, Mészáros, and Gábor, who inaugurated this preoccupation with generational values. The pervasive interplay of dreams and memory in their films invites an additional element to their argument concerning historical progression. This paper incorporates Richard Teniman’s notion of the “dialectics of memory” in which memory is in a constant process of negation and reinvention to explain why these Directors prefer to explore Hungarian identity through the disarranged form of psychological realism over the linear causality structure of historical realism.

Keywords: film theory, Eastern European Studies, film history, Eastern European History

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Authors: Lorenzo Casagrande, Antonio Bonati, Ferdinando Auricchio, Antonio Occhiuzzi

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This paper summarizes the results of a survey on smart non-structural element dynamic dissipation when installed in modern high-rise mega-frame prototypes. An innovative glazed curtain wall was designed using Shape Memory Alloy (SMA) joints in order to increase the energy dissipation and enhance the seismic/wind response of the structures. The studied buildings consisted of thirty- and sixty-storey planar frames, extracted from reference three-dimensional steel Moment Resisting Frame (MRF) with outriggers and belt trusses. The internal core was composed of a CBF system, whilst outriggers were placed every fifteen stories to limit second order effects and inter-storey drifts. These structural systems were designed in accordance with European rules and numerical FE models were developed with an open-source code, able to account for geometric and material nonlinearities. With regard to the characterization of non-structural building components, full-scale crescendo tests were performed on aluminium/glass curtain wall units at the laboratory of the Construction Technologies Institute (ITC) of the Italian National Research Council (CNR), deriving force-displacement curves. Three-dimensional brick-based inelastic FE models were calibrated according to experimental results, simulating the fac¸ade response. Since recent seismic events and extreme dynamic wind loads have generated the large occurrence of non-structural components failure, which causes sensitive economic losses and represents a hazard for pedestrians safety, a more dissipative glazed curtain wall was studied. Taking advantage of the mechanical properties of SMA, advanced smart joints were designed with the aim to enhance both the dynamic performance of the single non-structural unit and the global behavior. Thus, three-dimensional brick-based plastic FE models were produced, based on the innovated non-structural system, simulating the evolution of mechanical degradation in aluminium-to-glass and SMA-to-glass connections when high deformations occurred. Consequently, equivalent nonlinear links were calibrated to reproduce the behavior of both tested and smart designed units, and implemented on the thirty- and sixty-storey structural planar frame FE models. Nonlinear time history analyses (NLTHAs) were performed to quantify the potential of the new system, when considered in the lateral resisting frame system (LRFS) of modern high-rise MRFs. Sensitivity to the structure height was explored comparing the responses of the two prototypes. Trends in global and local performance were discussed to show that, if accurately designed, advanced materials in non-structural elements provide new sources of energy dissipation.

Keywords: advanced technologies, glazed curtain walls, non-structural elements, seismic-action reduction, shape memory alloy

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Hala Obeid

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Among the cities that have been touched by hard events and have been experiencing this polemic of existence, one can quote Beirut. A city that defies and confronts itself for its own existence. Beirut materialized all the social complexity; it has also preserved the memory of a society that has been able to build and reflect a certain unique identity. In spite of its glory, Lebanon’s civil war has marked a turning point in Beirut’s history. It has caused many deaths and opposed religious communities. Once this civil war has ended, the reconstruction of the city center, however, saw the spatial exclusion of manual labor, small local commerce, and middle-class residences. The urban functions that characterized the pre-war center were removed, and the city’s spontaneous evolutions were replaced by a historical urban planning, which neglected the city’s memory and identity. The social and spatial fragmentation that has erupted since the war has led to a breakdown of spatial and social boundaries within the city. The aim of this study is to evaluate the impact of fragmentation and boundaries on the city of Beirut in spatial, social, religious and ethnic terms. The method used in this research is what we call the mixed method which is a combination between the quantitative method and the qualitative one. These two approaches, in this case, do not oppose but complement each other in order to study the city of Beirut physically and socially. The main purpose of the qualitative approach is to describe and analyze the social phenomenon of the fragmentation of the city; this method can be summarized by the field observation and study. While the quantitative approach is based on filling out questionnaires that leads to statistics analyzes. Together, these two approaches will mark the course of the research. As a result, Beirut is not only a divided city but is fragmented spatially into many fragments and socially into many groups. This fragmentation is creating immaterial boundaries between fragments and therefore between groups. These urban and social boundaries are specifically religious and ethnic limits. As a conclusion, one of the most important and discussed boundary in Beirut is a spatial and religious boundary called ‘the green line’ or the demarcation line, a true caesura within the city. It marks the opposition of two urban groups and the aggravated fragmentation between them. This line divided Beirut into two compartments: East Beirut (for Christians) and West Beirut (for Muslims). This green line has become an urban void that holds the past in suspension. Finally, to think of Beirut as an urban unit becomes an insoluble problem.

Keywords: Beirut, boundaries, fragmentation, identity

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Authors: Sepdiana W. Rahmawati, Santi A. P. Anggraini

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The world of education has made progress with the various new technologies with help of computer. No exception physics education, especially virtual physics practical work. By doing practical work, memory of physics concept will be more advantageous for student and they will understand the essence of actual physics, not only spiked formula. With help of computers, created a variety of applications that can be used by students to perform virtual practical work and students will start thinking systematically to be able find its own concepts and understand the application of physics.

Keywords: essence of physics, formation concept, physics concept, virtual practical work

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Authors: Shruti Jain

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During its independence struggle in the early 20th century, India witnessed trends of politicisation of various spiritual paths, one of them being that of Shaktism. Interestingly, Nietzsche’s teachings were being interpreted as being essentially the worship of Shakti. The present paper aims at investigating this claim and hence undertakes an intercultural archaeological excavation in the realm of the Goddess archetypes that Nietzsche’s work invokes. Ariadne is placed next to Radha, Baubo to Lajja Gauri, Medusa to Chhinnamasta, Hecate to Kali and Dhumavati and Athena to Sarawati. Indeed, the Eternal Feminine plays a vital role in Nietzsche’s writings. One might recall that Nietzsche even declared himself to be the first Psychologist of the Eternal Feminine. The present paper aims to illustrate how, the matter of the Eternal Feminine, like all other matters, is subjected to Nietzsche’s basic creative principle of transvaluation of values and new meaning making. In order to achieve this, Nietzsche applies what Heidegger calls a 'cross-wise striking-through' technique in his analysis of what can be termed as his engagement with Shaktism. Hence, not only is the mystical ascent and descent of the creative energy (Kundalini Shakti) dealt with under erasure in Thus Spake Zarathustra, but coincidentally also the Three Metamorphoses emerge as an instance of such an erasure, making the Devi invisible and yet not so invisible for an Indian reader.

Keywords: eternal feminine, Nietzsche and India, Shaktism, transvaluation of values

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Authors: Charisse H. Tay

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Background: Schizophrenia is a severe chronic mental disorder that can result in hallucinations, delusions, reduced social engagement, and lack of motivation. While antipsychotic medications often provide the basis for treatment, psychosocial strategies complement the benefit of medications and can result in meaningful improvements in symptoms and functioning. The aim of the study was to investigate psychosocial strategies used by internet self-help forum participants to effectively manage symptoms caused by schizophrenia. Internet self-help forums are a resource for medical and psychological problems and are commonly used to share information about experiences with symptom management. Method: Three international self-help internet forums on schizophrenia were identified using a search engine. 1,181 threads regarding non-pharmacological, psychosocial self-management of schizophrenia symptoms underwent screening, resulting in the final identification and coding of 91 threads and 191 posts from 134 unique forum users that contained details on psychosocial strategies endorsed personally by users that allowed them to effectively manage symptoms of schizophrenia, including positive symptoms (e.g., auditory/visual/tactile hallucinations, delusions, paranoia), negative symptoms (e.g.., avolition, apathy, anhedonia), symptoms of distress, and cognitive symptoms (e.g., memory loss). Results: Effective symptom management strategies personally endorsed by online forum users were psychological skills (e.g., re-focusing, mindfulness/meditation, reality checking; n = 94), engaging in activities (e.g., exercise, working/volunteering, hobbies; n = 84), social/familial support (n = 48), psychotherapy (n = 33), diet (n = 18), and religion/spirituality (n = 14). 44.4% of users reported using more than one strategy to manage their symptoms. The most common symptoms targeted and effectively managed, as specified by users, were positive symptoms (n = 113), negative symptoms (n = 17), distress (n = 8), and memory loss (n = 6). 10.5% of users reported more than one symptom effectively targeted. 70.2% of users with positive symptoms reported that psychological skills were effective for symptom relief. 88% of users with negative symptoms and 75% with distress symptoms reported that engaging in activities was effective. Discussion: Individuals with schizophrenia rely on a variety of different psychosocial methods to manage their symptoms. Different symptomology appears to be more effectively targeted by different types of psychosocial strategies. This may help to inform treatment strategy and tailored for individuals with schizophrenia.

Keywords: psychosocial treatment, qualitative methods, schizophrenia, symptom management

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Authors: Shu-Ching Chiu, Shu-Fang Chang

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The World Health Organization (WHO) has been actively developing intervention programs to deal with geriatric frailty. In its White Paper on Healthcare Policy 2020, the Department of Health, Bureau of Health Promotion proposed that active aging and the prevention of disability are essential for elderly people to maintain good health. The paper recommended five main policies relevant to this objective, one of which is the prevention of frailty and disability. Scholars have proposed a number of different criteria to diagnose and assess frailty; no consistent or normative standard of measurement is currently available. In addition, many methods of assessment are recursive, which can easily result in recall bias. Due to the relationship between frailty and physical fitness with regard to co-morbidity, it is important that academics optimize the criteria used to assess frailty by objectively evaluating the physical fitness of senior citizens. This study used a review of the literature to identify fitness indicators suitable for measuring frailty in the elderly. This study recommends that measurement criteria be integrated to produce an optimized predictive value for frailty score. Healthcare professionals could use this data to detect frailty at an early stage and provide appropriate care to prevent further debilitation and increase longevity.

Keywords: frailty, aging, physical fitness, optimized criteria, healthcare

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Authors: Piotr Jablonski, Krzysztof Mars, Wiktor Niemiec, Agnieszka Kyziol, Marek Hebda, Halina Krawiec, Karol Kyziol

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NiTi alloys, possessing unique mechanical properties such as pseudoelasticity and shape memory effect (SME), are suitable for many applications, including implanthology and biomedical devices. Additionally, these alloys have similar values of elastic modulus to those of human bones, what is very important in orthopedics. Unfortunately, the environment of physiological fluids in vivo causes unfavorable release of Ni ions, which in turn may lead to metalosis as well as allergic reactions and toxic effects in the body. For these reasons, the surface properties of NiTi alloys should be improved to increase corrosion resistance, taking into account biological properties, i.e. excellent biocompatibility. The prospective in this respect are layers based on DLC (Diamond-Like Carbon) structures, which are an attractive solution for many applications in implanthology. These coatings (DLC), usually obtained by PVD (Physical Vapour Deposition) and PA CVD (Plasma Activated Chemical Vapour Deposition) methods, can be also modified by doping with other elements like silicon, nitrogen, oxygen, fluorine, titanium and silver. These methods, in combination with a suitably designed structure of the layers, allow the possibility co-decide about physicochemical and biological properties of modified surfaces. Mentioned techniques provide specific physicochemical properties of substrates surface in a single technological process. In this work, the following types of layers based on DLC structures (incl. Si-DLC or Si/N-DLC) were proposed as prospective and attractive approach in surface functionalization of shape memory alloy. Nitinol substrates were modified in plasma conditions, using RF CVD (Radio Frequency Chemical Vapour Deposition). The influence of plasma treatment on the useful properties of modified substrates after deposition DLC layers doped with silica and/or nitrogen atoms, as well as only pre-treated in O2 NH3 plasma atmosphere in a RF reactor was determined. The microstructure and topography of the modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Furthermore, the atomic structure of coatings was characterized by IR and Raman spectroscopy. The research also included the evaluation of surface wettability, surface energy as well as the characteristics of selected mechanical and biological properties of the layers. In addition, the corrosion properties of alloys after and before modification in the physiological saline were also investigated. In order to determine the corrosion resistance of NiTi in the Ringer solution, the potentiodynamic polarization curves (LSV – Linear Sweep Voltamperometry) were plotted. Furthermore, the evolution of corrosion potential versus immersion time of TiNi alloy in Ringer solution was performed. Based on all carried out research, the usefullness of proposed modifications of nitinol for medical applications was assessed. It was shown, inter alia, that the obtained Si-DLC layers on the surface of NiTi alloy exhibit a characteristic complex microstructure, increased surface development, which is an important aspect in improving the osteointegration of an implant. Furthermore, the modified alloy exhibits biocompatibility, the transfer of the metal (Ni, Ti) to Ringer’s solution is clearly limited.

Keywords: bioactive coatings, corrosion resistance, doped DLC structure, NiTi alloy, RF CVD

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Authors: Maja Ruzic-Baf, Mirjana Radetic-Paic

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The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games. The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games.

Keywords: addiction to video games, behaviour, ICT, young people

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Authors: Mohammad Alshehri, Fahd Alfarsi

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Efficient supply chains play an essential role in delivering humanitarian supplies and directly impact the success of public aid initiatives globally. Predicting the delivery status of these essential supplies in a timely manner is crucial. Therefore, this study investigates the application of various machine learning (ML) approaches to predict whether humanitarian deliveries will be made on time, using a comprehensive case-study dataset provided by one of the largest international supplying organizations. We employed several ML methods, namely Logistics Regression, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Navie Bays, to assess the proposed predictive model. The outcome of the analysis showed promising results, with weighted Recall (WRec.) / Accuracy (Acc.) scores ranging from 0.77 to 0.86 using the 4 algorithms mentioned earlier. These high-performance levels indicate the robustness of Machine Learning (ML) techniques in forecasting delivery status, potentially enabling more proactive and efficient supply chain management in global aid initiatives. The implications of this study suggest that integrating advanced predictive analytics in supply chain management can significantly enhance the delivery performance of critical commodities to those in need.

Keywords: humanitarian aids, supply chains, artificial intelligence, delivery status

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