Search results for: modified simplex algorithm

Authors: Mohsen Maadani, Seyed Ahmad Motamedi

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The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

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Authors: Hsin-Yun Lee

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In this study, the pedestrian simulation VISWALK integration and application platform ant algorithms written program made to construct a renovation engineering schedule planning mode. The use of simulation analysis platform construction site when the user running the simulation, after calculating the user walks in the case of construction delays, the ant algorithm to find out the minimum delay time schedule plan, and add volume and unit area deactivated loss of business computing, and finally to the owners and users of two different positions cut considerations pick out the best schedule planning. To assess and validate its effectiveness, this study constructed the model imported floor of a shopping mall floor renovation engineering cases. Verify that the case can be found from the mode of the proposed project schedule planning program can effectively reduce the delay time and the user's walking mall loss of business, the impact of the operation on the renovation engineering facilities in the building to a minimum.

Keywords: pedestrian, renovation, schedule, simulation

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Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

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Authors: Merad Boudia Omar Rafik, Feham Mohammed

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Data aggregation in wireless sensor networks (WSNs) provides a great reduction of energy consumption. The limited resources of sensor nodes make the choice of an encryption algorithm very important for providing security for data aggregation. Asymmetric cryptography involves large ciphertexts and heavy computations but solves, on the other hand, the problem of key distribution of symmetric one. The latter provides smaller ciphertexts and speed computations. Also, the recent researches have shown that achieving the end-to-end confidentiality and the end-to-end integrity at the same is a challenging task. In this paper, we propose (SA-SPKC), a novel security protocol which addresses both security services for WSNs, and where only the base station can verify the individual data and identify the malicious node. Our scheme is based on stateful public key encryption (StPKE). The latter combines the best features of both kinds of encryption along with state in order to reduce the computation overhead. Our analysis

Keywords: secure data aggregation, wireless sensor networks, elliptic curve cryptography, homomorphic encryption

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Authors: Yan Lyu

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Japanese degree adverbs can be explained in different ways, which is hard for Japanese learners to comprehend. For instance, when ‘tyotto’ is used as a degree word, it can be interpreted literally or not. In the sentence ‘Ano mise, tyotto oishi yo. zehi iku to ii yo.’, ‘tyotto’ can be interpreted as a high degree contextually. Despite pragmatic factors, phonetics factors can also affect the interpretation of such ‘tyotto’. Concentrating on the pattern of ‘tyotto +adjective’, the paper aims to investigate the correlation between the interpretation of ‘tyotto’ and the phonetic factors in some specific contexts based on a listening experiment via PRAAT. It is also investigated that how the phonetic factors affect the interpretation of high degree adverbs, including ‘soutou’ , ‘totemo’ , ‘kanari’ and ‘sugoku’. In the experiment, Japanese speakers listened to sentences which were composed of degree adverbs and adjectives in different intonations and judged which degree the sentences expressed. Two conclusions can be drawn from the experiment results. Firstly, for adverbs expressing a high degree, in the pattern of ‘degree adverb + adjective’, either degree adverb or adjective is pronounced in a higher pitch, or both are highly pronounced, a higher degree can be expressed. Besides, with the insertion of geminate consonant and the extension of the vowel, the longer the duration of the degree adverb becomes, the higher degree can be expressed. Secondly, for ‘tyotto’, which expresses a low degree, the interpretation will be influenced by both phonetic and contextual factors. Phonetically, there are three factors causing ‘tyotto’ to be interpreted as a common degree or a high degree. The three factors are the high pitch of the modified adjective, the extended silence period of the geminate consonant and the change in the intonations of ‘tyotto’. In some contexts just like the comparison sentences, no matter how ‘tyotto + adjective’ is pronounced, ‘tyotto’ tends to be interpreted as a low degree literally.

Keywords: contextual interpretation, Japanese degree adverbs, phonetic interpretation, PRAAT

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Authors: P.Kiruthika, K. Ramani

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This paper presented the design and advancement of a single-phase 27-level Hybrid Multilevel DC-AC Converter interfacing with Photo Voltaic. In this context, the Multicarrier Pulse Width Modulation method can be implemented in 27-level Hybrid Multilevel Inverter for generating a switching pulse. Perturb & Observer algorithm can be used in the Maximum Power Point Tracking method for the Photo Voltaic system. By implementing Maximum Power Point Tracking with three separate solar panels as an input source to the 27-level Hybrid Multilevel Inverter. This proposed method can be simulated by using MATLAB/simulink. The result shown that the proposed method can achieve silky output wave forms, more flexibility in voltage range, and to reduce Total Harmonic Distortion in medium-voltage drives.

Keywords: Multi Carrier Pulse Width Modulation Technique (MCPWM), Multi Level Inverter (MLI), Maximum Power Point Tracking (MPPT), Perturb and Observer (P&O)

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

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Authors: Lakshmidevi Rajendran, Bharathidasan Kanniappan, Gopi Raja, Muthukumar Karuppan

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This study investigates the feasibility of fed-batch mixotrophic cultivation of microalgae Scenedesmus sp. in a 3-litre airlift photobioreactor under standard operating conditions. The results of this study suggest the algae species may serve as an excellent feed for aquatic species using organic byproducts. Microalgae Scenedesmus sp., was cultured using a synthetic wastewater by stepwise addition of crude glycerol concentration ranging from 2-10g/l under fed-batch mixotrophic mode for a period of 15 days. The attempts were made with the stepwise addition of crude glycerol as a carbon source in the initial growth phase to evade the inhibitory nature of high glycerol concentration on the growth of Scenedesmus sp. Crude glycerol was chosen since it is readily accessible as byproduct from biodiesel production sectors. Highest biomass concentration was achieved to be 2.43 g/l at the crude glycerol concentration of 6g/l after 10 days which is 3 fold times the increase in the biomass concentration compared with the control medium without the addition of glycerol. Biomass growth data obtained for the microalgae Scenedesmus sp. was fitted well with the modified Logistic equation. Substrate utilization kinetics was also employed to model the biomass productivity with respect to the various crude glycerol concentration. The results indicated that the supplement of crude glycerol to the mixotrophic culture of Scenedesmus sp., enhances the biomass concentration, chlorophyll and lutein productivity. Thus the application of fed-batch mixotrophic cultivation with stepwise addition of crude glycerol to Scenedesmus sp., provides a subtle way to reduce the production cost and improvisation in the large-scale cultivation along with biochemical compound synthesis.

Keywords: airlift photobioreactor, crude glycerol, microalgae Scenedesmus sp., mixotrophic cultivation, lutein production

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: Ahmed Abdelsalam, Daniel Roozbahani, Marjan Alizadeh, Heikki Handroos

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The aim of this study was to redesign a pressing air nozzle with lower weight and improved efficiency utilizing Selective Laser Melting (SLM) technology based on Design for Additive Manufacturing (DfAM) methods. The original pressing air nozzle was modified in SolidWorks 3D CAD, and two design concepts were introduced considering the DfAM approach. In the proposed designs, the air channels were amended. 3D models for the original pressing air nozzle and introduced designs were created to obtain the flow characteristic data using Ansys software. Results of CFD modeling for the original and two proposed designs were extracted, compared, and analyzed to demonstrate the impact of design on the development of a more efficient pressing air nozzle by AM process. Improved airflow was achieved by optimizing the pressing air nozzle's internal channel for both design concepts by providing 30% and 50.6% fewer pressure drops than the original design. Moreover, utilizing the presented designs, a significant reduction in product weight was attained. In addition, by applying the proposed designs, 48.3% and 70.3% reduction in product weight was attained compared to the original design. Therefore, pressing air nozzle with enhanced productivity and lowered weight was generated utilizing the DfAM-driven designs developed in this study. The main contribution of this study is to investigate the additional possibilities that can be achieved in designing modern parts using the advantage of SLM technology in producing that part. The approach presented in this study can be applied to almost any similar industrial application.

Keywords: additive manufacturing, design for additive manufacturing, design methods, product design, pressing air nozzle

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Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: Anujendra, Parag Kumar Guha Thakurta

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The data transmission between mobile hosts and base stations (BSs) in Mobile networks are often vulnerable to failure. Thus, efficient link connectivity, in terms of the services of both base stations and communication channels of the network, is required in wireless mobile networks to achieve highly reliable data transmission. In addition, it is observed that the number of blocked hosts is increased due to insufficient number of channels during heavy load in the network. Under such scenario, the channels are allocated accordingly to offer a reliable communication at any given time. Therefore, a reliability-based channel allocation model with acceptable system performance is proposed as a MOO problem in this paper. Two conflicting parameters known as Resource Reuse factor (RRF) and the number of blocked calls are optimized under reliability constraint in this problem. The solution to such MOO problem is obtained through NSGA-II (Non-dominated Sorting Genetic Algorithm). The effectiveness of the proposed model in this work is shown with a set of experimental results.

Keywords: base station, channel, GA, pareto-optimal, reliability

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Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: R. Santos Alimi

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Using time-series techniques, this study empirically tested the validity of existing theory which stipulates there is a nonlinear relationship between government size and economic growth; such that government spending is growth-enhancing at low levels but growth-retarding at high levels, with the optimal size occurring somewhere in between. This study employed three estimation equations. First, for the size of government, two measures are considered as follows: (i) share of total expenditures to gross domestic product, (ii) share of recurrent expenditures to gross domestic product. Second, the study adopted real GDP (without government expenditure component), as a variant measure of economic growth other than the real total GDP, in estimating the optimal level of government expenditure. The study is based on annual Nigeria country-level data for the period 1970 to 2012. Estimation results show that the inverted U-shaped curve exists for the two measures of government size and the estimated optimum shares are 19.81% and 10.98%, respectively. Finally, with the adoption of real GDP (without government expenditure component), the optimum government size was found to be 12.58% of GDP. Our analysis shows that the actual share of government spending on average (2000 - 2012) is about 13.4%.This study adds to the literature confirming that the optimal government size exists not only for developed economies but also for developing economy like Nigeria. Thus, a public intervention threshold level that fosters economic growth is a reality; beyond this point economic growth should be left in the hands of the private sector. This finding has a significant implication for the appraisal of government spending and budgetary policy design.

Keywords: public expenditure, economic growth, optimum level, fully modified OLS

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Authors: Remon Karam Zakry Kelada

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This survey research ambitions to examine the usual of carrier quality of meals and beverage provider staffs in lodge business by way of studying the carrier fashionable of 3 pattern inns, Siam Kempinski lodge Bangkok, four Seasons lodge Chiang Mai, and Banyan Tree Phuket. as a way to locate the international provider general of food and beverage provider, triangular research, i.e. quantitative, qualitative, and survey were hired. on this research, questionnaires and in-depth interview have been used for getting the statistics on the sequences and method of services. There had been three components of modified questionnaires to degree carrier pleasant and visitor’s satisfaction inclusive of carrier facilities, attentiveness, obligation, reliability, and circumspection. This observe used pattern random sampling to derive topics with the go back fee of the questionnaires changed into 70% or 280. information have been analyzed via SPSS to find mathematics mean, SD, percent, and comparison by using t-take a look at and One-manner ANOVA. The outcomes revealed that the service first-rate of the three lodges have been in the worldwide stage that could create excessive pride to the international clients. hints for studies implementations have been to hold the area of precise carrier satisfactory, and to enhance some dimensions of service fine together with reliability. training in service fashionable, product expertise, and new generation for employees must be provided. furthermore, for you to develop the provider pleasant of the enterprise, training collaboration among inn corporation and academic institutions in food and beverage carrier should be considered.

Keywords: food and beverage staff, food poisoning, food production, hygiene knowledge BPA, health, regulations, toxicity service standard, food and beverage department, sequence of service, service method

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: Asmaa Fathy Mohamed Desoky

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The subject of this research is the inference of intentionality and context from the verses of the Meccan surahs, which include the paradox of reward and punishment, applied to the duality of disbelief and faith; The Holy Quran is the most important sacred linguistic reference in the Arabic language because it is rich in all the rules of the language in addition to the linguistic miracle. the Quranic text is a first-class intentional text, sent down to convey something to the recipient (Muhammad first and then communicates it to Muslims) and influence and convince him, which opens the door to many Ijtihad; a desire to reach the will of Allah and his intention from his words Almighty. Intentionality as a term is one of the most important deliberative terms, but it will be modified to suit the Quranic discourse, especially since intentionality is related to intention-as it turned out earlier - that is, it turns the reader or recipient into a predictor of the unseen, and this does not correspond to the Quranic discourse. Hence, in this research, a set of dualities will be identified that will be studied in order to clarify the meaning of them according to the opinions of previous interpreters in accordance with the sanctity of the Quranic discourse, which is intentionally related to the dualities of reward and punishment, such as: the duality of disbelief and faith, noting that it is a duality that combines opposites and Paradox on one level, because it may be an external paradox between action and reaction, and may be an internal paradox in matters related to faith, and may be a situational paradox in a specific event or a certain fact. It should be noted that the intention of the Qur'anic text is fully realized in form and content, in whole and in part, and this research includes a presentation of some applied models of the issues of intention and context that appear in the verses of the paradox of reward and punishment in the Meccan surahs in Quraan.

Keywords: intentionality, context, the paradox, reward, punishment, Meccan surahs

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Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

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Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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Authors: Tamer M. Shehata, Heba S. Elsewedy, Mashel Al Dosary, Alaa Elshehry, Mohamed A. Khedr, Maged E. Mohamed

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Objective: 2,4-Dichlorophenoxy acetic acid (2,4-D) is a well-known herbicide widely used as a weed killer. Recently, 2,4-D was rediscovered as a new anti-inflammatory agent through in silico as well as in-vivo experiments. However, poor solubility of 2,4-D could represent a problems during pharmaceutical development in addition to lower bioavailability. Solid dispersion (SD) refers to a group of solid products consisting of at least two different components, usually a hydrophobic drug and hydrophilic matrix. It is well known technique for enhancing drug solubility. Therefore, selecting SD as a tool for enhancing 2,4-D could be of great interest to the formulator. Method: In our project, several polymers were investigated (such as PEG, HPMC, citric acid and others) in addition to drug polymer ratios and its effect on solubility. Evaluation of drug polymer interaction was investigated through both Fourier Transform Infrared (FTIR) and Differential Scanning Calorimetry (DSC). Finally, in-vivo evaluation was performed for the best selected preparation through inflammatory response of rat induce hind paw. Results: Results indicated that, citric acid 2,4-D and in ratio of 0.75 : 1 showed modified the dissolution profile of the drug. The FTIR resltes indicated no significant chemical interaction, however DSC showed shifting of the drug melting point. Finally, Carragenan induced rat hind paw edema showed significant reduction of the drug solid dispersion in comparison to the pure drug, indicating rapid and complete absorption of the drug in solid dispersion form. Conclusion: Solid dispersion technology can be utilized efficiently to enhance the solubility of 2,4-D.

Keywords: solid dispersion, 2, 4-D solubility, carragenan induced edema

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Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Sidharta Sahirman, Ardiansyah, Muhammad Rifan, Edy-Melmambessy

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Merauke district in Papua, Indonesia has a strategic position and natural potential for the development of agricultural industry. The development of agriculture in this region is being accelerated as part of Indonesian Government’s declaration announcing Merauke as one of future national food barns. Therefore, land-use suitability analysis for Merauke need to be performed. As a result, the mapping for future agriculture-based industries can be done optimally. In this research, a case study is carried out in Semangga sub district. The objective of this study is to determine the suitability of Merauke land for some food crops. A modified agro-ecological zoning is applied to reach the objective. In this research, land cover based on satellite imagery is combined with soil, water and climate survey results to come up with preliminary zoning. Considering the special characteristics of Merauke community, the agricultural zoning maps resulted based on those inputs will be combined with socio-economic information and culture to determine the final zoning map for agricultural industry in Merauke. Examples of culture are customary rights of local residents and the rights of local people and their own local food patterns. This paper presents the results of first year of the two-year research project funded by The Indonesian Government through MP3EI schema. It shares the findings of land cover studies, the distribution of soil physical and chemical parameters, as well as suitability analysis of Semangga sub-district for five different food plants.

Keywords: agriculture, agro-ecological, Merauke, zoning

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

Abstract:

Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

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Authors: V. Makis, L. Jafari

Abstract:

In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

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Authors: Yihao Kuang, Bowen Ding

Abstract:

With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference

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Authors: Abdulrahman Sumayli, Saad M. AlShahrani

Abstract:

For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

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Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

Abstract:

We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

Procedia PDF Downloads 437