Search results for: deep and shallow strategies

Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: Hurgesa Hundera, Samuel Shibeshibikeko, Tarike Daba, Tesfaye Ganamo

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The study aimed at examining the ongoing adaptation strategies used by smallholder farmers in response to climate variability in Boset district. It also assessed the socioeconomic factors that influence the choice of adaptation strategies of smallholder farmers to climate variability risk. For attaining the objectives of the study, both primary and secondary sources of data were employed. The primary data were obtained through a household questionnaire, key informant interviews, focus group discussions, and observations, while secondary data were acquired through desk review. Questionnaires were distributed and filled by 328 respondents, and they were identified through systematic random sampling technique. Descriptive statistics and binary logistic regression model were applied in this study as the main analytical methods. The findings of the study reveal that the sample households have utilized multiple adaptation strategies in response to climate variability, such as cropping early mature crops, planting drought resistant crops, growing mixed crops on the same farm lands, and others. The results of the binary logistic model revealed that education, sex, age, family size, off farm income, farm experience, access to climate information, access to farm input, and farm size were significant and key factors determining farmers’ choice of adaptation strategies to climate variability in the study area. To enable effective adaptation measures, Ministry of Agriculture and Natural Resource, with its regional bureaus and offices and concerned non–governmental organizations, should consider climate variability in their planning and budgeting in all levels of decision making.

Keywords: adaptation strategies, boset district, climate variability, smallholder farmers

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Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

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Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

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Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

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Authors: Mohamed Ahmed Khalil

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The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Mukesh A. Modi

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High-nitrate concentration in groundwater of unconfined aquifers has been a serious issue for public health risk at a global scale. Various anthropogenic activities in agricultural land and urban land of alluvial soil have been observed to be responsible for the increment of nitrate in groundwater. The present study was designed to identify suitable denitrification strategies to minimize the effects of high nitrate in groundwater near the Mahi River of Vadodara block, Gujarat. There were 11 wells of Jal Jeevan Mission, Ministry of Jal Shakti, along with 3 observation wells of Gujarat Water Resources Development Corporation have been used for the duration of 21 years. MODFLOW and MT3DMS codes have been used to simulate solute transport phenomena along with attempted effectively for optimization. Current research is one step ahead by optimizing various denitrification strategies with the simulation of the model. The in-situ and ex-situ denitrification strategies viz. NAS (No Action Scenario), CAS (Crop Alternation Scenario), PS (Phytoremediation Scenario), and CAS + PS (Crop Alternation Scenario + Phytoremediation Scenario) have been selected for the optimization. The groundwater model simulates the most suitable denitrification strategy considering the hydrogeological characteristics at the targeted well.

Keywords: groundwater, high nitrate, MODFLOW, MT3DMS, optimization, denitrification strategy

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Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: C. Y. Ng, A. M. Johan, A. E. Kajuputra

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Wave-in-deck phenomenon for fixed jacket platforms at shallow water condition has been reported as a notable risk to the workability and reliability of the platform. Reduction in reservoir pressure, due to the extraction of hydrocarbon for an extended period of time, has caused the occurrence of seabed subsidence. Platform experiencing subsidence promotes reduction of air gaps, which eventually allows the waves to attack the bottom decks. The impact of the wave-in-deck generates additional loads to the structure and therefore increases the values of the moment arms. Higher moment arms trigger instability in terms of overturning, eventually decreases the reserve strength ratio (RSR) values of the structure. The mechanics of wave-in-decks, however, is still not well understood and have not been fully incorporated into the design codes and standards. Hence, it is necessary to revisit the current design codes and standards for platform design optimization. The aim of this study is to evaluate the effects of RSR due to wave-in-deck on four-legged jacket platforms in Malaysia. Base shear values with regards to calibration and modifications of wave characteristics were obtained using SESAM GeniE. Correspondingly, pushover analysis is conducted using USFOS to retrieve the RSR. The effects of the contributing factors i.e. the wave height, wave period and water depth with regards to the RSR and base shear values were analyzed and discussed. This research proposal is important in optimizing the design life of the existing and aging offshore structures. Outcomes of this research are expected to provide a proper evaluation of the wave-in-deck mechanics and in return contribute to the current mitigation strategies in managing the issue.

Keywords: wave-in-deck loads, wave effects, water depth, fixed jacket platforms

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Authors: Yasser Shabana, Khaled Ghoneem, Nehal Arafat, Younes Rashad, Dalia Aseel, Bruce Fitt, Aiming Qi, Benjamine Richard

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Providing food for more than 100 million people is one of Egypt's main challenges facing development. The overall goal is to formulate strategies to enhance food security in light of population growth. Two hundred samples of maize grains from 25 governates were collected. For the detection of seed-borne fungi, the deep-freezing blotter method (DFB) and washing method (ISTA 1999) were used. A total of 41 fungal species was recovered from maize seed samples. Weather data from 30 stations scattered all over Egypt and covering the major maize growing areas were obtained. Canonical correspondence analysis of data for the obtained fungal genera with temperature, relative humidity, precipitation, wind speed, or solar radiation revealed that relative humidity, temperature and wind speed were the most influential weather variables.

Keywords: biodiversity, climate change, maize, seed-borne fungi

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Authors: Sanjay Patil, Shakil A. Kagzi, Harit K. Raval

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Tailor Welded Blanks (TWB) are utilized in automotive industries widely because of their advantage of weight and cost reduction and maintaining required strength and structural integrity. TWB consist of two or more sheet having dissimilar or similar material and thickness; welded together to form a single sheet before forming it to desired shape. Forming of the tailor welded blank is affected by ratio of thickness of blanks, ratio of their strength, etc. mainly due to in-homogeneity of material. In the present work the relative effect of these parameters on weld line movement is studied during deep drawing of TWB using FE simulation using HYPERWORKS. The simulation is validated with results from the literature. Simulations were than performed based on Taguchi orthogonal array followed by the ANOVA analysis to determine the significance of these parameters on forming of TWB.

Keywords: ANOVA, deep drawing, Tailor Welded Blank (TWB), weld line movement

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Authors: Olga Guseynova

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Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Understanding the behaviour of the piles under the action of the independent lateral loads and the precise prediction of the capacity of piles subjected to different lateral loads are vital topics in foundation design and analysis. Moreover, the laterally loaded behaviour of deep foundations penetrated in cohesive and non-cohesive soils is basically analysed by the Winkler Model (beam on elastic foundation), in which the interaction between the pile embedded depth and contacted soil is simulated by nonlinear p–y curves. The presence of many approaches to interpret the behaviour of soil-pile interaction has resulted in numerous outputs and indicates that no general approach has yet been adopted. The current study presents the result of numerical modelling of the behaviour of steel tubular piles (25.4mm) outside diameter with various embedment depth-to-diameter ratios (L/d) embedded in a sand calibrated chamber of known relative density. The study revealed that the shear strength parameters of the sand specimens and the (L/d) ratios are the most significant factor influencing the response of the pile and its capacity while taking into consideration the complex interaction between the pile and soil. Good agreement has been achieved when comparing the application of this modelling approach with experimental physical modelling carried out by another researcher.

Keywords: deep foundations, slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), non-cohesive soil

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Authors: Sharifullah Ahmed

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Shallow foundation on soft soils without ground improvement can represent a high level of settlement. In such a case, an alternative to pile foundations may be shallow strip footings placed on a soil system in which the upper layer is untreated or cement-treated compacted sand to limit the settlement within a permissible level. This research work deals with a rigid plane-strain strip footing of 2.5m width placed on a soil consisting of untreated or cement treated sand layer underlain by homogeneous soft clay. Both the thin and thick compared the footing width was considered. The soft inorganic cohesive NC clay layer is considered undrained for plastic loading stages and drained in consolidation stages, and the sand layer is drained in all loading stages. FEM analysis was done using PLAXIS 2D Version 8.0 with a model consisting of clay deposits of 15m thickness and 18m width. The soft clay layer was modeled using the Hardening Soil Model, Soft Soil Model, Soft Soil Creep model, and the upper improvement layer was modeled using only the Hardening Soil Model. The system is considered fully saturated. The value of natural void ratio 1.2 is used. Total displacement fields of strip footing and subsoil layers in the case of Untreated and Cement treated Sand as Upper layer are presented. For Hi/B =0.6 or above, the distribution of major deformation within an upper layer and the influence zone of footing is limited in an upper layer which indicates the complete effectiveness of the upper layer in bearing the foundation effectively in case of the untreated upper layer. For Hi/B =0.3 or above, the distribution of major deformation occurred within an upper layer, and the function of footing is limited in the upper layer. This indicates the complete effectiveness of the cement-treated upper layer. Brittle behavior of cemented sand and fracture or cracks is not considered in this analysis.

Keywords: displacement, ground improvement, influence depth, PLAXIS 2D, primary and secondary settlement, sand mat, soft clay

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Authors: Israa A. Qari

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Learning to request in a foreign language is a key ability within pragmatics language teaching. This paper examines how requests are taught in English Unlimited Book 3 (Cambridge University Press), an EFL textbook series employed by King Abdulaziz University in Jeddah, Saudi Arabia to teach advanced foundation year students English. The focus of analysis is the evaluation of the request linguistic strategies present in the textbook, frequency of the use of these strategies, and the contextual information provided on the use of these linguistic forms. The researcher collected all the linguistic forms which consisted of the request speech act and divided them into levels employing the CCSARP request coding manual. Findings demonstrated that simple and commonly employed request strategies are introduced. Looking closely at the exercises throughout the chapters, it was noticeable that the book exclusively employed the most direct form of requesting (the imperative) when giving learners instructions: e.g. listen, write, ask, answer, read, look, complete, choose, talk, think, etc. The book also made use of some other request strategies such as ‘hedged performatives’ and ‘query preparatory’. However, it was also found that many strategies were not dealt with in the book, specifically strategies with combined functions (e.g. possibility, ability). On a sociopragmatic level, a strong focus was found to exist on standard situations in which relations between the requester and requestee are clear. In general, contextual information was communicated implicitly only. The textbook did not seem to differentiate between formal and informal request contexts (register) which might consequently impel students to overgeneralize. The paper closes with some recommendations for textbook and curriculum designers. Findings are also contrasted with previous results from similar body of research on EFL requests.

Keywords: EFL, requests, saudi, speech acts, textbook evaluation

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Authors: Mahdieh Omranian, Mehran Ghanbari Motlagh

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As we know, today urban growth, development, and intelligent social evolutions have been proposed in metropolises and this matter extends urban life which can have negative items besides positive and strong items. Along with research on urban life desirable development, conditions should be provided to provide the possibility of human stable development and improvement social welfare. These conditions can reinforce social, economic, and political structures related to non-expensive housing. Demand for non-expensive housing is increasing regarding to population increase and incremental urbanizing process. Therefore, the present study by precise exploration on conceptions, challenges, and strategies, should achieve an endogenous pattern and improve housing condition by looking to instant development. Therefore, the general objective of this article recognizes the existed strategies in housing and achieving desirable conditions for all social classes by sustainable development.

Keywords: housing strategies, infrastructure, metropolis, sustainable development

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Authors: Sidra Rizwan

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The article focuses on the training needs of secondary school teachers related to the knowledge component of instructional planning and strategies as stated in the National professional standards for teachers in Pakistan. The study aimed to determine the training needs of secondary school teachers on different aspects of knowledge & understanding component of instructional planning and strategies. The target population of the study was the secondary school teachers across Pakistan. For this purpose, a sample of 400 secondary school teachers was selected through multistage sampling from all the four provinces and Federal capital area. Survey method was adopted to assess the training needs by using a self reporting tool. The tool helped to gauge the training needs through indirect inventory questions as well as a ranking list in which the respondents themselves prioritized their training areas. The results showed variation between the direct and indirect reporting of the teachers on the basis of which it was concluded that the secondary school teachers needed awareness about the knowledge component of instructional planning and strategies in order to redefine their actual training needs. The researcher further identified the training needs of secondary school teachers within each province and Islamabad capital territory; including an analysis of variations between strata. As teachers are considered agents of change, their training according to the professional standards should provide a solid base for “rethinking education”.

Keywords: training needs, secondary school teachers, instructional planning & strategies, knowledge & understanding

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: N. G. Teik Hiang, Fathyah Hashim

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This is a case of how strategic management techniques can be used to help resolving problems faced by an ageing Small and Medium Enterprise (SME). Strategic way of resolving problems had been proven to be possible in this case despite general thought that strategic management is useful mostly for large corporations. Small and Medium Enterprises (SMEs) can also use strategic management in managing their business and determining their future cause of action and strategies in order to survive in this ever competent world. Strategic orientation is the key to survival and development of small and medium enterprises. In order to adapt to the fierce market competition, ageing SMEs should improve competitiveness and operational efficiency. They must therefore establish a sense of strategic management to improve the strategic management skills, combined with its own unique characteristics, and work out practical strategies to develop core competitiveness of enterprises in the fierce market competition in order to be sustainable. In this case, internal strengths and weaknesses of an SME had been identified. Strategic internal factors and external factors had been classified and further utilized to formulate potential strategies to encounter various problems faced by the SME. These strategies had been further match to take advantages of the opportunities and to overcome the weaknesses and minimize the threats it is facing. Tan, a consultant who was given the opportunity to formulate a plan for the business started with the environmental scanning (internal and external environmental analysis), assessing strengths and weaknesses for the company, strategies generation, analysis and evaluation. He had numerous discussions with the owner of the business and the senior management in order to match the key internal and external factors to formulate alternative strategies for solving the problems that the company facing. Some of the recommendations or solutions are generated from the inspiration of the owner of the business who is a very enterprising and experience businessman.

Keywords: strategic orientation, strategic management, SME, core competitiveness, sustainable

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Authors: Muhammad Awais Kiani, Maryam Kiani

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This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Akshat Mathur, Sunil Kumar Khatri

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This paper presents brief about how the use of Artificial intelligence in respect to GUI testing can reduce workload by using DL-fueled method. This paper also discusses about how graphical user interface and event driven software testing can derive benefits from the use of AI techniques. The use of AI techniques not only reduces the task and work load but also helps in getting better output than manual testing. Although results are same, but the use of Artifical intelligence techniques for GUI testing has proven to provide ideal results. DL-fueled framework helped us to find imperfections of the entire webpage and provides test failure result in a score format between 0 and 1which signifies that are test meets it quality criteria or not. This paper proposes DL-fueled method which helps us to find the genuine GUI bugs and defects and also helped us to scale the existing labour-intensive and skill-intensive methodologies.

Keywords: graphical user interface, GUI, artificial intelligence, deep learning, ML technology

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Authors: Alex Arghya Adhikari

Abstract:

Gaming and esports industry is one of the biggest and fastest growing industries in the world. Globally people have started investing more in this industry since now people believe just like traditional sports, esports can also sustain their future. Last year in the month of December, the Indian government also recognised esports as an official sport but there has not been any positive initiative by the government in encouraging people to enter esports. This is a problem which cannot be overlooked since we are already in the digital age and gaming and esports is the future industry. There is a need for multiple effective marketing strategies by the game publishers to stabilize the esports in the country. Purpose: To observe the marketing-communication strategies that are implemented by Riot Games’ Valorant and how those strategies influence the consumer behavior and the esports of the game. Methodology: Activities over the internet related to the game like livestreams, discord chats, Instagram posts and YouTube videos over a period of two months have been collected through the Digital Ethnography. To support and validate the observations of the data collected, in-depth online interviews have been conducted which includes streamers, journalists, LAN experienced players and casual players. Findings: The game publisher through its Dynamic Competitive Gaming Experience and Community-Engaged Ecosystem succeeded in making the game a Recreational activity and a Community which goes beyond the In-game experiences which helped in understanding the impact of audience engagement on esports and the loopholes and setbacks of Indian esports. Conclusion: The study provides a comprehensive analysis of how Valorant's successful marketing and community engagement strategies have contributed to its global popularity and competitive esports environment. It highlights the various strategies employed by Riot Games to keep players engaged and connected, and also the challenges in the Indian esports landscape which differentiates it from the global competition.

Keywords: esports, valorant, marketing, consumer behaviour

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Authors: Pradeep G. Siddheshwar, K. M. Lakshmi

Abstract:

The present study deals with weakly non-linear stability analysis of Rayleigh-Benard-Brinkman convection in nanoliquid-saturated porous enclosures. The modified-Buongiorno-Brinkman model (MBBM) is used for the conservation of linear momentum in a nanoliquid-saturated-porous medium under the assumption of Boussinesq approximation. Thermal equilibrium is imposed between the base liquid and the nanoparticles. The thermophysical properties of nanoliquid are modeled using phenomenological laws and mixture theory. The fifth-order Lorenz model is derived for the problem and is then reduced to the first-order Ginzburg-Landau equation (GLE) using the multi-scale method. The analytical solution of the GLE for the amplitude is then used to quantify the heat transport in closed form, in terms of the Nusselt number. It is found that addition of dilute concentration of nanoparticles significantly enhances the heat transport and the dominant reason for the same is the high thermal conductivity of the nanoliquid in comparison to that of the base liquid. This aspect of nanoliquids helps in speedy removal of heat. The porous medium serves the purpose of retainment of energy in the system due to its low thermal conductivity. The present model helps in making a unified study for obtaining the results for base liquid, nanoliquid, base liquid-saturated porous medium and nanoliquid-saturated porous medium. Three different types of enclosures are considered for the study by taking different values of aspect ratio, and it is observed that heat transport in tall porous enclosure is maximum while that of shallow is the least. Detailed discussion is also made on estimating heat transport for different volume fractions of nanoparticles. Results of single-phase model are shown to be a limiting case of the present study. The study is made for three boundary combinations, viz., free-free, rigid-rigid and rigid-free.

Keywords: Boungiorno model, Ginzburg-Landau equation, Lorenz equations, porous medium

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Authors: Ching-Hsu Huang, Shang-Huan Wu

Abstract:

In recent years, environmental awareness has increased, environmental issues caused by meat-eating have been extended to promote reducing food surplus and waste advocates. We lose more than 3 million tons of food on average on a daily basis. Private households represent the largest food-waste faction. The main purpose of this study is to design and develop household dishes by using edible food surplus. The questionnaires were conducted to find the majority of food surplus from households, including carrot peel, pumpkin, fish skin, and soy dregs—this study designed and developed the household dishes by using the leftovers. We briefly discuss the contributions of the dishes. Mapping the household dishes deepens the promotion of household food waste prevention strategies. This study also linked the results with a set of policy, education, and restaurant business options

Keywords: food waste, food surplus, household dishes design, food waste prevention strategies

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Authors: Yingying Ding

Abstract:

This study presents a methodology of specialized translation with the objective of helping teachers to improve the strategies in teaching translation. In order to allow students to acquire skills to translate specialized texts, they need to become familiar with the semantic and syntactic features of source texts and target texts. The aim of our study is to use a corpus-based approach in the teaching of specialized translation between Chinese and Italian. This study proposes to construct a specialized Chinese - Italian comparable corpus that consists of 50 economic contracts from the domain of food. With the help of AntConc, we propose to compile a comparable corpus in for translation teaching purposes. This paper attempts to provide insight into how teachers could benefit from comparable corpus in the teaching of specialized translation from Italian into Chinese and through some examples of passive sentences how students could learn to apply different strategies for translating appropriately the voice.

Keywords: contrastive studies, specialised translation, corpus-based approach, teaching

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Authors: Rahime Filiz Kiremit

Abstract:

This study identifies six different articles to explain which strategies are most effective for kindergarten English Language Learners. The literature review project has information about six different research articles, purpose of the studies, and results of the studies. There are several strategies can be used for ELL students to help them to develop their English language skills. Some articles mention technology as a multimedia integrated into the curriculum, some of them mention writing as a method of learning English as a second language. However, they all have a common strategy that is shared reading. According to these six articles, shared reading has a big role of ELL students’ language developmental process. All in all, read-aloud with multimedia enhancement strategy is the best strategy to use in the classroom, because this strategy is based on shared reading and also integrated with technology.

Keywords: bilingual education, effective strategies, english language learners, kindergarten

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Authors: S. Aberkane, N. Djabali, S. Fafi, A. Baghezza

Abstract:

Chronic illnesses affect many Algerians. It is possible to investigate the impact of illness representations and coping on quality of life and whether illness representations are indirectly associated with quality of life through their influence on coping. This study aims at investigating the relationship between illness perception, coping strategies and quality of life with chronic illness. Illness perceptions are indirectly associated with the quality of life through their influence on coping mediation. A sample of 316 participants with chronic illness living in the region of Batna, Algeria, has been adopted in this study. A correlation statistical analysis is used to determine the relationship between illness perception, coping strategies, and quality of life. Multiple regression analysis was employed to highlight the predictive ability of the dimensions of illness perception and coping strategies on the dependent variables of quality of life, where mediation analysis is considered in the exploration of the indirect effect significance of the mediator. This study provides insights about the relationship between illness perception, coping strategies and quality of life in the considered sample (r = 0.39, p < 0.01). Therefore, it proves that there is an effect of illness identity perception, external and medical attributions related to emotional role, physical functioning, and mental health perceived, and these were fully mediated by the asking for assistance (c’= 0.04, p < 0.05), the guarding (c’= 0.00, p < 0.05), and the task persistence strategy (c’= 0.05, p < 0.05). The findings imply partial support for the common-sense model of illness representations in a chronic illness population. Directions for future research are highlighted, as well as implications for psychotherapeutic interventions which target unhelpful beliefs and maladaptive coping strategies (e.g., cognitive behavioral therapy).

Keywords: chronic illness, coping, illness perception, quality of life, self- regulation model

Procedia PDF Downloads 222