Search results for: long memory

Authors: Catherine Wright, Kate Luedke

Abstract:

This paper questions whether or not individuals who had been exposed to narratives describing secure and insecure-avoidant attachment styles experienced temporary changes in their attachment style when compared to individuals who had been exposed to neutral narratives. The Attachment Style Questionnaire (or ASQ) developed by Feeney, Noller, and Hanrahan in 1994 was utilized to assess attachment style. Participants filled out a truncated version of the ASQ prior to reading the respective narratives assigned to their groups, and filled out the entirety of the ASQ after reading the narratives. Utilizing a one-way independent groups ANOVA, researchers found that the group which read the insecure-avoidant narrative experienced a statistically significant decrease in secure attachment, as did the group which read the secure narrative. The control group, however, experienced a statistically significant increase in secure attachment. Based on these findings, researchers concluded that narratives may have the ability to call attention to parental shortcomings that individuals have experienced in the forms of reminding individuals of positive experiences that they were not able to experience while spending time with their parental figures and calling attention to the shortcomings of said parental figures by reminding them of the negative experiences which they did have with them.

Keywords: attachment, insecure-avoidant, memory, secure

Procedia PDF Downloads 400

Authors: Ghada Badr, Arwa Alturki

Abstract:

The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: alignment, RNA secondary structure, pairwise, component-based, data mining

Procedia PDF Downloads 456

Authors: Jackson Niyongabo

Abstract:

This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

Procedia PDF Downloads 57

Authors: Ozlem Temiz-Arpaci, Meryem Tasci, Fatma Sezer Senol, İlkay Erdogan Orhan

Abstract:

Alzheimer’s disease (AD), a neurodegenerative disorder characterized by a progressive deterioration of memory and cognition, occurs more frequently in elderly people. Current treatment approaches in this disease with the major therapeutic strategy are based on the AChE and BChE inhibition. On the other hand, tyrosinase inhibition has become a target for the treatment of Parkinson’s disease (PD) since this enzyme may play a role in neuromelanin formation in the human brain and could be critical in the formation of dopamine neurotoxicity associated with neurodegeneration linked to PD. Also benzoxazoles are structural isosteres of natural nucleotides that can interact with biopolymers so that benzoxazoles showed a lot of different biological activities. In this study, a series of 2,5-disubstituted-benzoxazole derivatives were synthesized and were evaluated as possible inhibitors of acetylcholinesterase (AChE) / butyrylcholinesterase (BChE) and tyrosinase. The results demonstrated that the compounds exhibited a weak spectrum of AChE / BChE inhibitory activity ranging between 3.92% - 54.32% except compound 8 which showed no activity against AChE and compound 4 which showed no activity against BChE at the specified molar concentrations. Also, the compounds indicated lower than tyrosinase inhibitory activity of ranging between 8.14% - 22.90% to that of reference (kojic acid).

Keywords: AChE and BChE inhibition, Alzheimer’s disease, benzoxazoles, tyrosinase inhibition

Procedia PDF Downloads 340

Authors: M. Ali Lotfollahi Yaghin, M. Reza Bagerzadeh Karimi, Ali Rahmani, V. Sadeghi Balkanlou

Abstract:

Structural engineers have long been trying to develop solutions using the full potential of its composing materials. Therefore, there is no doubt that the structural solution progress is directly related to an increase in materials science knowledge. These efforts in conjunction with up-to-date modern construction techniques have led to an extensive use of composite floors in large span structures. On the other hand, the competitive trends of the world market have long been forcing structural engineers to develop minimum weight and labour cost solutions. A direct consequence of this new design trend is a considerable increase in problems related to unwanted floor vibrations. For this reason, the structural floors systems become vulnerable to excessive vibrations produced by impacts such as human rhythmic activities. The main objective of this paper is to present an analysis methodology for the evaluation of the composite floors human comfort. This procedure takes into account a more realistic loading model developed to incorporate the dynamic effects induced by human walking. The investigated structural models were based on various composite floors, with main spans varying from 5 to 10 m. based on an extensive parametric study the composite floors dynamic response, in terms of peak accelerations, was obtained and compared to the limiting values proposed by several authors and design standards. This strategy was adopted to provide a more realistic evaluation for this type of structure when subjected to vibration due to human walking.

Keywords: vibration, resonance, composite floors, people’s rhythmic movement, dynamic analysis, Abaqus software

Procedia PDF Downloads 300

Authors: S. Nqayi

Abstract:

Understanding the structural, electronic, and magnetic properties of nanomaterials is essential for developing next-generation electronic and spintronic devices, contributing to the progress of nanoscience and nanotechnology applications. Multiferroic materials, with intimately coupled ferroic-order parameters, are widely considered to breed fascinating physical properties and provide unique opportunities for the development of next-generation devices, like multistate non-volatile memory. In this study, we are set to investigate the structural, electronic, and magnetic properties of the frustrated Feᴵᴵ/Smⱽᴵ sublattice in relation to the widely studied perovskites for spintronics applications. The atomic composition, microstructure, crystallography, magnetization, thermal, and dielectric properties of a pyrochlore Sm₂Fe₂O₇ system synthesized using sol-gel methods are currently being investigated. Precursor powders were dissolved in citric acid monohydrate to obtain a solution. The obtained solution was stirred and heated using a magnetic stirrer to obtain the gel phase. Then, the gel was dried at 200°C to remove water and organic compounds and form an orange powder. The X-ray diffraction analysis confirms that the structure crystallized as a pyrochlore structure with a tetragonal F4mm (107) symmetry. The presence of Fe³⁺/Fe⁴⁺ mixed states is also revealed by XPS analysis.

Keywords: nanostructures, multiferroic materials, pyrochlores, spintronics

Procedia PDF Downloads 54

Authors: Triza Edwar Fawzi Deif

Abstract:

In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

Procedia PDF Downloads 51

Authors: Cao Jiayu, Lan Ximing, Huang Jingjia, Burra Venkata Durga Kumar

Abstract:

The first virus to attack personal computers was born in early 1986, called C-Brain, written by a pair of Pakistani brothers. In those days, people still used dos systems, manipulating computers with the most basic command lines. In the 21st century today, computer performance has grown geometrically. But computer viruses are also evolving and escalating. We never stop fighting against security problems. Stack overflow is one of the most common security vulnerabilities in operating systems. It may result in serious security issues for an operating system if a program in it has a vulnerability with administrator privileges. Certain viruses change the value of specific memory through a stack overflow, allowing computers to run harmful programs. This study developed a mechanism to detect and respond to time whenever a stack overflow occurs. We demonstrate the effectiveness of standard machine learning algorithms and control flow enforcement techniques in predicting computer OS security using generating suspicious vulnerability functions (SVFS) and associated suspect areas (SAS). The method can minimize the possibility of stack overflow attacks occurring.

Keywords: operating system, security, stack overflow, buffer overflow, machine learning, control-flow enforcement technology

Procedia PDF Downloads 113

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

Abstract:

The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

Procedia PDF Downloads 125

Authors: Azizeh Chalak, Firouzeh Baktash

Abstract:

Reticence is a prominent and complex phenomenon which occurs in foreign language classrooms and influences students’ oral passivity. The present study investigated the extent in which students experience reticence in the EFL classrooms and explored the underlying factors triggering reticence. The participants were 104 Iranian freshmen undergraduate male and female EFL students, who enrolled in listening and speaking courses, all majoring in English studying at Islamic Azad University Isfahan (Khorasgan) Branch and University of Isfahan, Isfahan, Iran. To collect the data, the Reticence Scale-12 (RS-12) questionnaire which measures the level of reticence consisting of six dimensions (anxiety, knowledge, timing, organization, skills, and memory) was administered to the participants. The statistical analyses showed that the reticent level was high among the Iranian EFL undergraduate students, and their major problems were feelings of anxiety and delivery skills. Moreover, the results revealed that factors such as low English proficiency, the teaching method, and lack of confidence contributed to the students’ reticence in Iranian EFL classrooms. It can be implied that language teachers’ awareness of learners’ reticence can help them choose more appropriate activities and provide a friendly environment enhancing hopefully more effective participation of EFL learners. The findings can have implications for EFL teachers, learners and policy makers.

Keywords: anxiety, Iranian EFL learners, reticence, reticence scale-12

Procedia PDF Downloads 497

Authors: Jay L. Fu

Abstract:

Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 142

Authors: Sarah Crawford, Gerry Lesley

Abstract:

This research is a pre-clinical assessment of anti-cancer effects of novel non-steroidal diethyl stilbestrol-like estrogen analogs in estrogen-receptor positive/ progesterone-receptor positive human breast cancer microtumors of MCF 7 cell line. Tamoxifen analog formulation (Tam A1) was used as a single agent or in combination with therapeutic concentrations of 4-hydroxytamoxifen, currently used as a long-term treatment for the prevention of breast cancer recurrence in women with estrogen receptor positive/ progesterone receptor positive malignancies. At concentrations ranging from 30-50 microM, Tam A1 induced microtumor disaggregation and cell death. Incremental cytotoxic effects correlated with increasing concentrations of Tam A1. Live tumor microscopy showed that microtumos displayed diffuse borders and substrate-attached cells were rounded-up and poorly adherent. A complete cytotoxic effect was observed using 40-50 microM Tam A1 with time course kinetics similar to 4-hydroxytamoxifen. Combined treatment with TamA1 (30-50 microM) and 4-hydroxytamoxifen (10-15 microM) induced a highly cytotoxic, synergistic combined treatment response that was more rapid and complete than using 4-hydroxytamoxifen as a single agent therapeutic. Microtumors completely dispersed or formed necrotic foci indicating a highly cytotoxic combined treatment response. Moreover, breast cancer microtumors treated with both 4-hydroxytamoxifen and Tam A1 displayed lower levels of long-term post-treatment regrowth, a critical parameter of primary drug resistance, than observed for 4-hydroxytamoxifen when used as a single agent therapeutic. Tumor regrowth at 6 weeks post-treatment with either single agent 4-hydroxy tamoxifen, Tam A1 or a combined treatment was assessed for the development of drug resistance. Breast cancer cells treated with both 4-hydroxytamoxifen and Tam A1 displayed significantly lower levels of post-treatment regrowth, indicative of decreased drug resistance, than observed for either single treatment modality. The preclinical data suggest that combined treatment involving the use of tamoxifen analogs may be a novel clinical approach for long-term maintenance therapy in patients with estrogen-receptor positive/progesterone-receptor positive breast cancer receiving hormonal therapy to prevent disease recurrence. Detailed data on time-course, IC50 and tumor regrowth assays post- treatment as well as a proposed mechanism of action to account for observed synergistic drug effects will be presented.

Keywords: 4-hydroxytamoxifen, tamoxifen analog, drug-resistance, microtumors

Procedia PDF Downloads 67

Authors: Sh. Khoshemehry, M. E. Bahram, M. J. Pourvaghar

Abstract:

Sport has found a special place as an effective phenomenon in all societies of the contemporary world. The relationship between physical activity and exercise with different sciences has provided new fields for human study. The range of issues related to exercise and physical education is such that it requires specialized sciences and special studies. In this article, the psychological and social sections of exercise have been investigated for children and adults. It can be used for anyone in different age groups. Exercise and regular physical movements have a great impact on the mental and social health of the individual in addition to body health. It affects the individual's adaptability in society and his/her personality. Exercise affects the treatment of diseases such as depression, anxiety, stress, body image, and memory. Exercise is a safe haven for young people to achieve the optimum human development in its shelter. The effects of sensorimotor skills on mental actions and mental development are such a way that many psychologists and sports science experts believe these activities should be included in training programs in the first place. Familiarity of students and scholars with different programs and methods of sensorimotor activities not only causes their mental actions; but also increases mental health and vitality, enhances self-confidence and, therefore, mental health.

Keywords: anxiety, mental health, physical activity, serotonin

Procedia PDF Downloads 205

Authors: Nicolás Rudas

Abstract:

Sociologists have brought to light the fascination of contemporary societies with numbers but fall short of explaining it. In their accounts, people generally misunderstand the technical intricacies of statistical knowledge and therefore accept numbers as unassailable “facts”. It is due to such pervasive fascination, furthermore, that both old and new forms of social control find fertile ground. By focusing on the process whereby the fetishization of numbers reaches its zenith, i.e., when specific statistics become emblematic of an entire society, it is asserted that numbers primarily function as moral symbols with immense potential for galvanizing collective action. Their “facticity” is not solely a cognitive problem but one that is deeply rooted in myth and connected with social experiences of epiphany and ritual. Evidence from Colombia is used to illustrate how certain quantifications become canonical. In 2021, Colombia’s Peace Court revealed that the national army had executed 6,402 innocent civilians to later report them as members of illegal armed groups. Rapidly, “6,402” transformed into a prominent item in the country’s political landscape. This article reconstructs such a process by following the first six months of the figure’s circulation, both in traditional and social media. In doing so, it is developed a new cultural-sociological conceptualization of numbers as “fact-icons” that departs from traditional understandings of statistics as “technical” objects. Numbers are icons whose appropriation is less rational than aesthetic.

Keywords: culture, statistics, collective memory, social movements

Procedia PDF Downloads 69

Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

Abstract:

Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

Procedia PDF Downloads 123

Authors: Ephraim Ugwu, Christopher Ehinomen

Abstract:

Despite efforts by the Nigerian government to harmonize the macroeconomic policy implementations by establishing various committees to resolve disputes between the fiscal and monetary authorities, it is still evident that the federal government had continued its expansionary policy by increasing spending, thus creating huge budget deficit. This study evaluates the effect of macroeconomic policy coordination on economic growth uncertainty in Nigeria from 1980 to 2020. Employing the Auto regressive distributed lag (ARDL) bound testing procedures, the empirical results shows that the error correction term, ECM(-1), indicates a negative sign and is significant statistically with the t-statistic value of (-5.612882 ). Therefore, the gap between long run equilibrium value and the actual value of the dependent variable is corrected with speed of adjustment equal to 77% yearly. The long run coefficient results showed that the estimated coefficients of the intercept term indicates that other things remains the same (ceteris paribus), the economics growth uncertainty will continue reduce by 7.32%. The coefficient of the fiscal policy variable, PUBEXP, indicates a positive sign and significant statistically. This implies that as the government expenditure increases by 1%, economic growth uncertainty will increase by 1.67%. The coefficient of monetary policy variable MS also indicates a positive sign and insignificant statistically. The coefficients of merchandise trade variable, TRADE and exchange rate EXR show negative signs and significant statistically. This indicate that as the country’s merchandise trade and the rate of exchange increases by 1%, the economic growth uncertainty reduces by 0.38% and 0.06%, respectively. This study, therefore, advocate for proper coordination of monetary, fiscal and exchange rate policies in order to actualize the goal of achieving a stable economic growth.

Keywords: macroeconomic, policy coordination, growth uncertainty, ARDL, Nigeria

Procedia PDF Downloads 129

Authors: Asraful Islam

Abstract:

Extended dependency graph (EDG) is a state-of-the-art isomorphic graph to represent normal logic programs (NLPs) that can characterize the consistency of NLPs by graph analysis. To construct the vertices and arcs of an EDG, additional renaming atoms and rules besides those the given program provides are used, resulting in higher space complexity compared to the corresponding traditional dependency graph (TDG). In this article, we propose an extended labeled dependency graph (ELDG) to represent an NLP that shares an equal number of nodes and arcs with TDG and prove that it is isomorphic to the domain program. The number of nodes and arcs used in the underlying dependency graphs are formulated to compare the space complexity. Results show that ELDG uses less memory to store nodes, arcs, and cycles compared to EDG. To exhibit the desirability of ELDG, firstly, the stable models of the kernel form of NLP are characterized by the admissible coloring of ELDG; secondly, a relation of the stable models of a kernel program with the handles of the minimal, odd cycles appearing in the corresponding ELDG has been established; thirdly, to our best knowledge, for the first time an inverse transformation from a dependency graph to the representing NLP w.r.t. ELDG has been defined that enables transferring analytical results from the graph to the program straightforwardly.

Keywords: normal logic program, isomorphism of graph, extended labelled dependency graph, inverse graph transforma-tion, graph colouring

Procedia PDF Downloads 210

Authors: Khadija Kraiem, Salma Bessadok, Dorra Tabassi, Atef Jaouani

Abstract:

This study investigated the long-term impact of incorporating biowaste (i.e., cork and date stones) as a natural and cost-effective alternative to traditional substrates (e.g., gravel) in constructed wetlands (CWs). Results showed that pollutant removal efficiency was significantly improved after the addition of biowaste under different hydraulic retention time (HRT) conditions. The addition of cork in vertical flow constructed wetlands (VFCWs) improved chemical oxygen demand (COD) removal from 64% to 86%. Similarly, in horizontal flow constructed wetlands (HFCWs), COD removal increased from 67% to 81% with cork and 85% with date seeds. In terms of ammonium removal, cork in VFCWs increased efficiency from 34% to 56%, while in HFCWs, it improved from 24% to 47% with cork and reached 44% with date stones. Furthermore, our data showed that the addition of biowastes improved the removal of micropollutants, such as bisphenol A (BPA) and diclofenac (DFC), with the highest removal of BPA of 86% and DFC of 89% observed in the date seeds wetland. However, no significant changes were observed in pathogens removal. The evaluation of the impact of biowaste addition on the contribution of plant species and its interaction with hydraulic retention time (HRT) was also conducted for pollutant removal. The addition of biowaste resulted in a decrease in the required HRT for effective contaminant elimination, but it had no notable impact on the contribution of plant species. To summarize, our findings indicate that utilizing biowastes in artificial wetlands for the treatment of wastewater with various pollutants can result in synergistic effects, presenting potential benefits in terms of both efficiency and cost-effectiveness.

Keywords: constructed wetlands, cork, date stones, pollutant removal, wastewater

Procedia PDF Downloads 20

Authors: Pi-Lan Yang

Abstract:

It is controversial which type of gloss condition (i.e., gloss language or gloss position) is more effective in second or foreign language (L2) vocabulary learning. The present study compared the performance on learning ten English words in the conditions of L2 English reading with no glosses and with glosses of Chinese equivalents/translations and L2 English definitions at the side of a page and at an attached sheet for low-intermediate Chinese-speaking learners of English, who were technology university students in Taiwan. It is found first that the performances on the immediate posttest and the delayed posttest were overall better in the gloss condition than those in the no-gloss condition. Next, it is found that the glosses of Chinese translations were more effective and sustainable than those of L2 English definitions. Finally, the effects of L2 English glosses at the side of a page were observed to be less sustainable than those at an attached sheet. In addition, an opinion questionnaire used also showed a preference for the glosses of Chinese translations in L2 English reading. These results would be discussed in terms of automated lexical access, sentence processing mechanisms, and the trade-off nature of storage and processing functions in working memory system, proposed by the capacity theory of language comprehension.

Keywords: glosses of Chinese equivalents/translations, glosses of L2 English definitions, L2 vocabulary learning, L2 English reading

Procedia PDF Downloads 247

Authors: Rameesha Javaid

Abstract:

Balochistan, the largest landmass named after and dominated by the 55% Baloch population, which has had a difficult anti-center history like their brothers the Kurds of Middle East, reluctantly acceded to Pakistan in 1947. The region, which attained the status of a province after two decades of accession, has lagged behind in social development and economic growth as compared to the other three federating units. The province has seen the least financial autonomy and administrative decentralization both in autocratic and democratic dispensations under geostrategic and security considerations. Significant corrections have been recently made in the policy framework through changing the formula for intra-provincial National Finance Award, curtailing the number of subjects under federal control, and reactivating the Council of Common Interests. Yet policymaking remains overwhelmingly bureaucratic under a weak parliamentary oversight. The provincial coalition governments are unwieldy and directionless. The government machinery has much less than the optimal capability, character, integrity, will, and opportunity to perform. Decentralization further loses its semblance in the absence of local governments for long intervals and with the hold of hereditary tribal chiefs. Increased allocations failed to make an impact in the highest per capita cost environment due to long distances and scattered settlements. Decentralization, the basic ingredient of federalism has remained mortgaged to geo-strategic factors, internal security perceptions, autocratic and individualistic styles of governments, bureaucratic policymaking structures, bad governance, non-existent local governments, and feudalistic tribal lords. This suboptimal federalism speaks for the present underdevelopment in Balochistan and will earmark the milestones in the future.

Keywords: Balochistan, economic development, federalism, political economy

Procedia PDF Downloads 309

Authors: Prashansa Singh, Manjot Kaur, Rohit Bajaj

Abstract:

The proliferation of wireless sensor networks and Internet of Things (IoT) devices in the quickly changing digital landscape has highlighted the urgent need for strong security solutions that can handle these systems’ limited resources. A key solution to this problem is the emergence of ultralightweight security protocols, which provide strong security features while respecting the strict computational, energy, and memory constraints imposed on these kinds of devices. This in-depth analysis explores the field of ultralightweight security protocols, offering a thorough examination of their evolution, salient features, and the particular security issues they resolve. We carefully examine and contrast different protocols, pointing out their advantages and disadvantages as well as the compromises between resource limitations and security resilience. We also study these protocols’ application domains, including the Internet of Things, RFID systems, and wireless sensor networks, to name a few. In addition, the review highlights recent developments and advancements in the field, pointing out new trends and possible avenues for future research. This paper aims to be a useful resource for researchers, practitioners, and developers, guiding the design and implementation of safe, effective, and scalable systems in the Internet of Things era by providing a comprehensive overview of ultralightweight security protocols.

Keywords: wireless sensor network, machine-to-machine, MQTT broker, server, ultralightweight, TCP/IP

Procedia PDF Downloads 78

Authors: Seyong Oh, Jin-Hong Park

Abstract:

Recently, neuromorphic computing based on brain-inspired artificial neural networks (ANNs) has attracted huge amount of research interests due to the technological abilities to facilitate massively parallel, low-energy consuming, and event-driven computing. In particular, research on artificial synapse that imitate biological synapses responsible for human information processing and memory is in the spotlight. Here, we demonstrate a photosynaptic device, wherein a synaptic weight is governed by a mixed spike consisting of voltage and light spikes. Compared to the device operated only by the voltage spike, ∆G in the proposed photosynaptic device significantly increased from -2.32nS to 5.95nS with no degradation of nonlinearity (NL) (potentiation/depression values were changed from 4.24/8 to 5/8). Furthermore, the Modified National Institute of Standards and Technology (MNIST) digit pattern recognition rates improved from 36% and 49% to 50% and 62% in ANNs consisting of the synaptic devices with 20 and 100 weight states, respectively. We expect that the photosynaptic device technology processed by optoelectronic spike will play an important role in implementing the neuromorphic computing systems in the future.

Keywords: optoelectronic synapse, IGZO (Indium-Gallium-Zinc Oxide) photosynaptic device, optoelectronic spiking process, neuromorphic computing

Procedia PDF Downloads 173

Authors: Kiomars Sefidi

Abstract:

Dead and habitat tree such as fallen logs, snags, stumps and cracks and loos bark etc. is regarded as an important ecological component of forests on which many forest dwelling species depend, yet its relation to management history in Caspian forest has gone unreported. The aim of research was to compare the amounts of dead tree and habitat in the forests with historically different intensities of management, including: forests with the long term implication of management (PS), the short-term implication of management (NS) which were compared with semi virgin forest (GS). The number of 405 individual dead and habitat trees were recorded and measured at 109 sampling locations. ANOVA revealed volume of the dead tree in the form and decay classes significantly differ within sites and dead volume in the semi virgin forest significantly higher than managed sites. Comparing the amount of dead and habitat tree in three sites showed that dead tree volume related with management history and significantly differ in three study sites. Also, the numbers of habitat trees including cavities, Cracks and loose bark and Fork split trees significantly vary among sites. Reaching their highest in virgin site and their lowest in the site with the long term implication of management, it was concluded that forest management cause reduction of the amount of dead and habitat tree. Forest management history affect the forest's ability to generate dead tree especially in a large size, thus managing this forest according to ecological sustainable principles require a commitment to maintaining stand structure that allow, continued generation of dead tree in a full range of size.

Keywords: forest biodiversity, cracks trees, fork split trees, sustainable management, Fagus orientalis, Iran

Procedia PDF Downloads 552

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

Abstract:

Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 176

Authors: Vitus Onyebuchim Onyemailu, Olive Obianuju Okalibe

Abstract:

The study tried to examine relationship between exchange rate variations on the balance of payments in Nigeria from 1970 to 2012. Using time series on econometric measures such as Granger causality and ordinary least square (OLS), the study found that exchange rate movements especially the depreciation of naira has not contributed significantly on the balance of payments under the year of the study. The granger result conform the Marshall-Lerner short and long run prepositions that exchange rate devaluation enhances balance of payments. On disaggregation exchange rate granger causes current and capital account balances give the Nigeria data from 1970 to 2012. Overall in the long run OLS regression analysis, exchange rate on semi log functional form, exchange rate variation did not record significant effect on balance of payment equation. This height was also maintained in the current or trade balance which does not match the Marshall-Lerner. The capital account balance in reverse reported a significant impact of exchange rate variability on the capital account balance. Finally, on exchange rate determination equation, where many fundamentals were considered including lagged of exchange rate. Thus, the lagged of exchange rate recorded a positive and significant influence on the present exchange rate. This means that players in the financial markets usually out plays authority’s policy’s stances through their speculative tendencies. The work therefore, recommend that effort should be made by the authorities to providing enabling environment for production of goods and services to triumph in order to take advantages of steady devaluation of its currency. This is done by providing infrastructure, provision of science and technology. Thus, when this is done Nigeria would be able to have competitive power against the rest of the world.

Keywords: exchange rate variation, balance of payments, current account, capital account, Marshall-Lerner hypothesis

Procedia PDF Downloads 395

Authors: Jonathan Matyenyika

Abstract:

In recent years, automobile manufacturers have increasingly produced vehicles equipped with cutting-edge automotive electronic technology to match the fast-paced digital world of today; this has brought about various benefits in different business sectors that make use of these vehicles as a means of turning over a profit. In the logistics industry, vehicles equipped with this technology have proved to be very utilitarian; this paper focuses on the benefits automobile electronic equipped vehicles have in the logistics industry. Automotive vehicle manufacturers have introduced new technological electronic features to their vehicles to enhance and improve the overall performance, efficiency, safety and driver comfort. Some of these features have proved to be beneficial to logistics operators. To start with the introduction of adaptive cruise control in long-distance haulage vehicles, to see how this system benefits the drivers, we carried out research in the form of interviews with long-distance truck drivers with the main question being, what major difference have they experienced since they started to operate vehicles equipped with this technology to which most stated they had noticed that they are less tired and are able to drive longer distances as compared to when they used vehicles not equipped with this system. As a result, they can deliver faster and take on the next assignment, thus improving efficiency and bringing in more monetary return for the logistics company. Secondly, the introduction of electric hybrid technology, this system allows the vehicle to be propelled by electric power stored in batteries located in the vehicle instead of fossil fuel. Consequently, this benefits the logistic company as vehicles become cheaper to run as electricity is more affordable as compared to fossil fuel. The merging of electronic systems in vehicles has proved to be of great benefit, as my research proves that this can benefit the logistics industry in plenty of ways.

Keywords: logistics, manufacturing, hybrid technology, haulage vehicles

Procedia PDF Downloads 56

Authors: Anjalika Fernando, Banuka Athuraliya

Abstract:

This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

Procedia PDF Downloads 103

Authors: Lim Poh Im

Abstract:

This paper examines the current strategic and planning issues in the provision of affordable housing in urban centres in Malaysia from the perspective of sustainability. Sustainability here refers to social sustainability such as the need to address urban poverty and ensure better quality of life; economic sustainability in ensuring that the financial mechanisms are healthy and stable in the long-run, and to a lesser extent, environmental sustainability in reducing pollution related problems and building footprint. The Malaysian affordable housing sector has undergone tremendous transformations since the sixties, transcending from the earlier social housing catering to the poorer strata of the society, to the current state of housing woes plaguing the young urban middle class. The increase in urban land prices and construction costs, coupled with rampant property speculative and manipulative activities have resulted in situations of housing that are largely unaffordable even to the middle income sector of the urban populations. To overcome such scenario, the public as well as private sectors in the recent years, have came up with various intermediate, as well as medium-term policies aimed to curb the burning housing needs of the urban populations. Key strategies include financial intervention in regulating the interests rates, imposing property gain taxes; loosening the requirement for density and other planning requirements, faster approval of projects, compulsory contribution from developers, etc. Some of the policies are commendable, while others are ad-hoc by nature, and are not able to resolve the long-term socio-economic challenges. This paper discusses and examines the issues from the ‘sustainability’ perspective, focusing on key fiscal, land use and planning policies, as well as the more subtle (but important) political and institutional factors shaping the provision of mass housing for the urban populations in Malaysia.

Keywords: affordable housing, urban housing, sustainable housing, planning for urban housing

Procedia PDF Downloads 442

Authors: Lia Matchavariani

Abstract:

Water reservoir construction on the rivers flowing into the sea complicates the coast protection, seashore starts to degrade causing coast erosion and disaster on the backdrop of current climate change. The instruments of the impact of a water reservoir on the climate and coastal areas are its contact surface with the atmosphere and the area irrigated with its water or humidified with infiltrated waters. The Black Sea coastline is characterized by the highest ecological vulnerability. The type and intensity of the water reservoir impact are determined by its morphometry, type of regulation, level regime, and geomorphological and geological characteristics of the adjoining area. Studies showed the impact of the water reservoir on the climate, on its comfort parameters is positive if it is located in the zone of insufficient humidity and vice versa, is negative if the water reservoir is found in the zone with abundant humidity. There are many natural and anthropogenic factors determining the peculiarities of the impact of the water reservoir on the climate, which can be assessed with maximum accuracy by the so-called “long series” method, which operates on the meteorological elements (temperature, wind, precipitations, etc.) with the long series formed with the stationary observation data. This is the time series, which consists of two periods with statistically sufficient duration. The first period covers the observations up to the formation of the water reservoir and another period covers the observations accomplished during its operation. If no such data are available, or their series is statistically short, “an analog” method is used. Such an analog water reservoir is selected based on the similarity of the environmental conditions. It must be located within the zone of the designed water reservoir, under similar environmental conditions, and besides, a sufficient number of observations accomplished in its coastal zone.

Keywords: coast-constituent sediment, eustasy, meteorological parameters, seashore degradation, water reservoirs impact

Procedia PDF Downloads 43

Authors: S. A. Tabatabaei, S. Aarabi

Abstract:

Predicting the hot mix asphalt (HMA) response and performance is a challenging task because of the subjectivity of HMA under the complex loading and environmental condition. The behavior of HMA is a function of temperature of loading and also shows the time and rate-dependent behavior directly affecting design criteria of mixture. Velocity of load passing make the time and rate. The viscoelasticity illustrates the reaction of HMA under loading and environmental conditions such as temperature and moisture effect. The behavior has direct effect on design criteria such as tensional strain and vertical deflection. In this paper, the computational framework for viscoelasticity and implementation in 3D dimensional HMA model is introduced to use in finite element method. The model was lied under various repeated loading conditions at constant temperature. The response of HMA viscoelastic behavior is investigated in loading condition under speed vehicle and sensitivity of behavior to the range of speed and compared to HMA which is supposed to have elastic behavior as in conventional design methods. The results show the importance of loading time pulse, unloading time and various speeds on design criteria. Also the importance of memory fading of material to storing the strain and stress due to repeated loading was shown. The model was simulated by ABAQUS finite element package

Keywords: viscoelasticity, finite element method, repeated loading, HMA

Procedia PDF Downloads 396