Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling a wet station for wafer cleaning with multiple job flows and multiple wafer-handling robots

A wet station performs a cleaning process in semiconductor manufacturing. It consists of several processing baths and multiple wafer-handling robots. It simultaneously processes multiple wafer types with different processing sequences. Robot collisions and deadlocks should be prevented. There are also strict no-wait time constraints where, after a wafer is cleaned in a chemical bath, it should immediately be removed from the bath and rinsed at a water bath. We examine the scheduling problem when different jobs are repetitively processed in cyclic order. We propose a way of modelling a Petri net for the wet station operation. By examining the Petri net model, we develop conditions for preventing deadlocks and collisions. We show that the Petri net model, which is apparently an asymmetric Petri net, is behaviourally equivalent to an event graph, for which cycle time computation and many analysis methods are available. Based on these findings, we develop a mixed integer programming model for determining the robot task sequences, the jobs in progress at the baths, and a timing schedule, which are free from deadlocks and collisions, satisfy the no-wait time constraints, and minimize the cycle time. We discuss the computational results.
“Am I doing this all wrong?” Challenges and Opportunities in Family Information Management

Running a household requires a large amount of labor, from ensuring multiple bills are paid to organizing important documents. Failure to manage such information can have critical consequences for the fnancial and psychological well-being of the family; however, little is known about how families manage the full scale of information encountered in the home. In this paper, we introduce family information management (FIM) as a set of overarching practices involved in managing and coordinating household-related information. To understand how families engage in FIM, we conducted in-depth interviews with members of ten families, which included guided tours of their information archives. We found that families struggle to organize, store, retrieve, and share information, and that there are signifcant socioemotional costs to this work. We propose opportunities for designing technologies to support FIM and argue that, given the numerous challenges and unmet needs, the understudied area of FIM deserves further investment of research and design eforts.
INFLUENCE OF SHOE MIDSOLE MATERIAL HARDNESS ON PERCEIVED COMFORT, REARFOOT MOTION, AND PLANTAR PRESSURE

The purpose of this study was to determine the influence of different midsole hardness on perceived comfort, rearfoot motion, and plantar pressure. Fifteen injury-free male amateur runners participated in this study. Rearfoot motion, plantar pressure, and perceived comfort were recorded while running. Smaller rearfoot maximal pronation, lower comfort scale, and greater maximum force and peak pressure of the lateral side were found in the harder shoe. In the harder midsole shoe, greater force and pressure were found in the lateral side of the midfoot and the forefoot, which may be attributed to a smaller pronation.
Bioinformatics Research Through Image Processing of Histopathological Response to Stonefish Venom

The present study utilizes coastal and environmental engineering to investigate the histopathological effects of Synanceia verrucosa venom on Albino BALB/c mice. S. verrucosa is the most hazardous venomous marine fish that belong to the family Synanceiidae, generally known as the "Reef Stonefish". Crude venom was collected from venom glands of the dorsal spines of stonefish samples taken from the Jordanian coastline of the Gulf of Aqaba, Red Sea. The mice were given intramuscular injections of the venom. Consequently, the research evaluated the acute toxicity and influence on selected serum biomarker enzymes, as well as possible histological alterations of the soleus skeletal muscles. The mice 24 h LD50 was 0.107 μg toxin/kg mouse body weight. After the treatment using venom sublethal dose, the serum biomarkers, including Lactate dehydrogenase (LDH) and Alanine aminotransferase (ALT), were significantly improved (P≤0.05). In addition, Lipid Peroxidation (LPO) contents were significantly increased (P≤0.05) after venom treatment. Moreover, we combined routine medical procedures and artificial intelligence-assisted image analysis for a rapid qualitative and quantitative diagnosis of stonefish injury, based on the histophotography of mice tissue samples during the observation period (1, 2, and 3 hours respectively). The novelty of our method is that we could detect severe and mild damage with an accuracy of 93% and 91%, respectively. The most histological abnormalities in muscles were the great variety in diameters, content, and widespread among randomly distributed muscle fibres. In addition, loss of the tissue's striated appearance was noticed in toxin-treated groups compared with the control group. Consequently, our findings indicate the Stonefish's harmful influences that may endanger human life and highlight the need for appropriate measures to be considered. This, in turn, can ensure beach safety in the Gulf of Aqaba. Keywords—Synanceia verrucosa; Gulf of Aqaba; artificial intelligence; marine biotoxins
Assessment of urban tree condition using VTA at Urban Green Space of Mataram University Rectorate

Urban green spaces, including those in the University of Mataram, is all urban land covered by vegetation of any kind, which has aesthetic and recreation values and are important components in improving the ecosystem function. Many trees at the University of Mataram Rectorate Area have aesthetical and ecological values. These trees have not been subjected to health assessment, while various stressors may have impacted the trees in the past. There is no available previous assessment information regarding the tree’s health condition. The purpose of this study is to conduct a Visual Tree Assessment (VTA) to evaluate the 62 trees’ health condition at the Mataram University Rectorate Area. The target trees were ≥20 cm diameter at breast height (dbh) and poles (10-19 cm dbh). The assessment was carried out using the VTA method to the condition of the common defects of the tree. The results show that based on the condition of the common defects of the tree, it was found that 22% of the trees had dead trees, top, and branches; 21% had parasite or mistletoe; 19% had stem or branch decay; 13% had weak branch union; 10% had poor tree architecture; 6% had cracks; 4% had termite attack; 3% had cankers, and 2% trees had root problems. Based on the hazard category of targeted trees, 79,03% of the trees are in Low hazard conditions (sound), 19,35% were in Moderately hazardous conditions, and only 1,61% were in Highly hazardous conditions. This assessment should be continued with an in-depth investigation. Monitoring and evaluation of tree health assessment should be done at least once a year. It is very important to gather up-to-date information on health conditions in the trees. The evaluation results integrated into GIS will be used as a tree health database that can be updated continuously. This data is expected to reduce the risk of damage that can be caused by the trees.
Internet-based temperature monitoring system for hydroponic

This study presents a monitoring system to provide real-time measurement data of hydroponic that is accessible from anywhere through internet. Temperatures of nutrient solution and ambient air are of concern in the monitoring system. The system is developed through the following steps: design, implementation, and experimental test. The system is built by applying a NodeMCU ESP-12 as the microcontroller and two temperature sensors DS18B20 The NodeMCU ESP-12 is to collect measurement data of both temperature sensors and send the data to a cloud server through a WiFi internet communication. The Google Sheets is applied as the cloud server to store the measurement data and provide the data to users. Using the Google Sheets, the data is presented in a table as in the Microsoft Excel which is very convenience for processing and analyzing the data. Experimental test results show that the system is able to provide real-time and reliable data of the hydroponics temperatures that can be accessed from anywhere through the internet. The monitoring system has a delay about 3 to 6 seconds in presenting the measurement data. This delay is quite small compare to the temperature change period and therefore is negligible. Moreover, the monitoring system is built at cost USD 6.0 which is quite cheap.
Irregular working hours in the airline industry : Work schedule related health outcomes and possibilities for prevention

Objective This systematic review aims to summarise the available evidence and thereby elucidate the effects of shift work which includes night work, on body weight change. Methods A systematic search strategy on longitudinal studies was performed. Articles were included following strict inclusion criteria, methodological quality was assessed by a standardised quality checklist. The results were summarised using a levels of evidence synthesis. Results The search strategy resulted in eight articles that met the inclusion criteria. Five of them were considered as high quality and three as low quality studies. Seven studies presented crude results for an association between shift work exposure and change in body weight; five high quality and two low quality studies. There was strong evidence for a crude relationship between shift work and body weight increase. Five studies presented weight related outcomes adjusted for potentially relevant confounders (age, gender, bodyweight at baseline and physical activity). Two studies found a significant difference between groups in the same direction. Consequently, the evidence for a for these confounders adjusted relationship between shift work exposure and body weight was considered to be insufficient. Conclusion Strong evidence for a crude association between shift work exposure and body weight increase was found. In order to further clarify the underlying mechanisms, more and better high quality studies about this subject are necessary.
OILU Tag: A Projective Invariant Fiducial System

 Abstract — This paper presents the development of a 2D visual marker, derived from a recent patented work in the field of numbering systems. The proposed fiducial uses a group of projective invariant straight-line patterns, easily detectable and remotely recognizable. Based on an efficient data coding scheme, the developed marker enables producing a large panel of unique real time identifiers with highly distinguishable patterns. The proposed marker Incorporates simultaneously decimal and binary information, making it readable by both humans and machines. This important feature opens up new opportunities for the development of efficient visual human-machine communication and monitoring protocols. Extensive experiment tests validate the robustness of the marker against acquisition and geometric distortions.
Cropping pattern and schedule using K-Factor for optimizing irrigation networks operation in Krueng Jreu Irrigation Area, Aceh, Indonesia

Determining the cropping pattern and schedule according to the availability and requirement of irrigation water is important in an irrigation command area. Supplying irrigation water in the Krueng Jreu Irrigation Area is still less effective in the dry season, so it is necessary to review the existing cropping pattern and schedule in the irrigation area by considering the K factor. To achieve optimal irrigation networks operation, simulation of cropping patterns and schedules based on the K factor was conducted. Optimal cropping patterns and schedules were determined by the highest frequency of the half-month K factor greater than 0.75. The best cropping pattern and schedule for Krueng Jreu Irrigation Area was rice-rice-soybean cropping pattern with first planting season started in mid-July, second planting season in mid-November and third planting season in mid-March. The results achieved the best frequency of K factor > 0.75 as many as 15 times, K factor in the range of 0.50 - 0.75 as many as 3 times, and K factor < 0.25 as many as 4 times. The application of the selected cropping pattern and schedule was done by allocating water into three groups in case of the K factor < 0.75, namely Group I (Menara and Krueng Aceh Extension secondary canal), Group II (Krueng Jreu Kiri secondary canal) and Group III (Kayee, Lamkrah, and Inong secondary canal).
Biological treatment of palm oil mill effluent by using a downflow hanging sponge reactor

The performance of biological treatment using a downflow hanging sponge reactor as post-treatment of agro-industrial wastewater has been recognized worldwide. However, the effectiveness of the system in treating POME is remain unknown. Therefore, with this background in mind, an anaerobic treatment operated at COD loading rate of 0.4-0.6 kg/m3/day, HRT of 2 hours and input pH of 7.6 was run using a DHS reactor packed with sponge media for the treatment of POME. During the study, the output concentration performances of COD (32-58%), Colour (41-76%), ammoniacal nitrogen (66-92%) and phosphate (54-87%) were recorded. These results indicate comparable performances with the existing biological treatment system. However, it also offered additional credits in-term of fouling and clogging issues, practically as well as lower cost and energy consumption. Thus, it will be great to have a system that is capable to provide a simple technology which is affordable to various industrial scales.
Study of power flow in electricity system using extreme learning machine

Load Flow or Power Flow Analysis in the power system in used to determine the power system parameters such as voltage, current, active power, and reactive power contained in the power grid. The method that has long been used in the calculation of load flow or power flow is the Newton-Raphson iteration method. As for its development, to complete the power flow study, it is carried out by implementing the Artificial Intelligence method, one of which is the Extreme Learning Machine method. This method is used in the simulation of the simple 39 Bus system calculation from IEEE. In this Extreme Learning Machine, the testing analysis is carried out with 2 inputs, 1 hidden layer, 5 neurons, and 2 outputs and the number of datasets is 39 to produce MAE and MAPE respectively 2.02 and 0.76% and with a very fast processing time of 0.010s
SUPER-EFFICIENT OR SUPER-INEFFICIENT? INSIGHTS FROM A JOINT COMPUTATION MODEL FOR SLACKS-BASED MEASURE IN DEA: A NOTE

Chen (2013) extended the exiting SBM approaches and developed a joint model (J-SBM) that can (1) simultaneously compute SBM scores for inefficient DMUs and super-efficiency for efficient DMUs, (2) guarantee the reference points generated by the J-SBM are Pareto-efficient, and (3) the J-SBM scores of a DMU are continuous in the input and output space. In this note, we provide a counter example which shows that the reference point generated by the J-SBM might not be Paretoefficient, and the current study has also revised the model (8) proposed by Chen (2013).
A General Framework for the Disintegration of PAC-Bayesian Bounds

PAC-Bayesian bounds are known to be tight and in-formative when studying the generalization ability of randomized classiﬁers. However, when applied to some family of deterministic models such as neural networks, they require a loose and costly derandomization step. As an alternative to this step, we introduce new PAC-Bayesian generalization bounds that have the originality to provide disintegrated bounds, i.e. , they give guarantees over one single hypothesis instead of the usual averaged analysis. Our bounds are easily optimizable and can be used to design learning algorithms. We illustrate the interest of our result on neural networks and show a signiﬁcant practical improvement over the state-of-the-art framework.
An Approach to Reducing Bus Bunching

The tendency of buses to bunch is a problem that was defined almost 50 years ago. Since then, there has been a significant amount of work done on the problem; however, the tendency of the current literature is either to only focus on the surface causes or to rely on simulation to create results instead of model formulation. With GPS installed on many buses throughout the world, the data is only being used for monitoring and informing the user. This research proposes a new approach to solving the problem that uses the GPS data to directly counteract the cause of the bunching by allowing the buses to cooperate with each other and determine their speed based on relative position. A continuum approximation model is presented as a tool to systematically analyze the behavior of the system and test the proposed control. In order to validate the model and the control, a simulation tool is used to model the system in a more realistic, discrete way. The control is shown to produce bounded deviations in spacing consistent with those predicted by the model. The resulting bus system will not bunch with only a small reduction in commercial speed.
Implementation of an analogue model of a memristor based on a light-dependent resistor

In this paper, an analogue model of a memristor using a light-dependent resistor (LDR) is presented. This model can be simplified into two parts: a control circuit and a variable resistor. It can be used to easily verify theoretical presumptions about the switching properties of memristors. This LDR-based memristor model can also be used in both simulations and experiments for future research into memristor applications. The paper includes mathematical models, simulations, and experimental results.
Calibration for Gingivitis Binary Classifier via Epoch-wise Decaying Label-Smoothing

Future healthcare systems will heavily rely on ill-labeled data due to scarcity of the experts who are trained enough to label the data. Considering the contamination of the dataset, it is not desirable to make the neural network being overconfident to the dataset, but rather giving them some margins for the prediction is preferable. In this paper, we propose a novel epoch-wise decaying label-smoothing function to alleviate the model over-confidency
Approximate Index Routing: A Case for Content-based Peer-to-Peer Routing

– Object location in a distributed peer-to-peer system has been a challenging problem. Our goal is to achieve efficient and effective query routing while imposing little restriction upon the system structure. We propose the approach of content-based peer-to-peer routing, in comparison to the highly structured address-based routing schemes such as the distributed hash table (DHT) approaches. By decoupling object content and their locations, content-based routing retains the simplicity and flexibility of an unstructured peer-to-peer system. We present one implementation of content-based peer-to-peer routing, namely Approximate Index Routing (AIR). Each AIR node maintains an independent summarization of the global index. The space consumption at each node is saved, while high routing accuracy is achieved by cooperation between nodes with different summarizations. Because of its simple structure, AIR is able to exploit application inherent optimization opportunities, such as resource heterogeneity and content locality. We show that AIR is able to scale to peer-to-peer systems with hundreds of millions of objects.
COMPARATIVE STUDY OF DIFFERENT CLASSIFIERS: AN APPLE FRUIT AS CASE STUDY

: This paper is aim to classify Apple fruit image on different classifiers: SVM, KNN, Naïve Bayes, Random Forest and Neural Network. There are several methods for fruit classification which are based on color and shape based but fruit has same color and shape which will not enough to identify fruits, proposed method is based on Color, Zone, Area, Centroid, Size, Equvidiameter, Perimeter and Roundness. This features are extracted from the images and provided to classifier models as training and classifying, to train classifiers supervised training approach is used. To compare classifiers Orange canvas and Weka datamining tools are used and found that SVM has highest 95.8% and 87.5% accuracy.
A Comparative Study on Different Training Model in Machine Learning

: Image reconstruction is the process of regeneration of an image from its distorted version. The image reconstruction problem is part of a larger field of image processing that is used in a variety of applications, including Forensic Analysis, Medical Science, Astronomy, Entertainment industry, Legal Services, etc. Designing a neural network that memorizes a given pattern or image and reconstructing the image requires resources, which is a tedious task and time-consuming. Many studies have been conducted in order to reconstruct images that have been distorted. This paper conducts a review of the current research to reconstruct the image from the distorted image using different Machine Learning methods. The domain of machine learning has led to the tremendous development of deep neural network techniques. Neural Networks are used to model complex patterns and predictive problems. This survey has compared different approaches for solving the problem and has proposed the neuromodulation technique as an efficient technique.
Do we need more immigration ? Socio-cultural diversity and export sophistication in EU 28 countries

One of the main concerns for policymakers is the ability of their nations to grow and to provide their citizens with a better standard of living. In a globalized world, this ability is increasingly being linked with the ability to export and structure of exported products. It is widely held that sophisticated knowledge and technologyintensive products offer higher prospects for growth than standardized price competitive goods. Ever since the work of Schumpeter migrations have been considered as an important driver of entrepreneurship, innovation, and technological progress. The social and professional networks of foreign-born individuals mobilize information, know-how, skills and capital to start new firms. They also provide valuable contacts and resources for both resident and newly arrived immigrants. Yet, the existing literature notes that the impact of immigration on innovations in the EU is smaller than that in the USA due to the greater cultural and institutional barriers in the former entity. The understanding of the immigrant role in the economic performance of the EU is particularly important since the growth of the foreign-born population in the EU has been faster than anywhere else in the world. Recent waves of EU enlargement and immigration pressures from other parts of the world have further facilitated this trend. Bearing above said in mind this paper explores the relationship between export sophistication and immigration in EU28 countries over the 2006-2015 period. A dynamic panel estimator is used to discern between short and long-run effects of immigration on the international competitiveness of EU economies. Our results suggest that greater socio-economic diversity increases the sophistication of exports in both the short and long run. The long-run effects are about twice as large than short-run ones.