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Specific intrusion detection systems (IDSs) are needed to secure modern supervisory control and data acquisition (SCADA) systems due to their architecture, stringent real-time requirements, network traffic features and specific application layer protocols. This article aims to contribute to assess the state-of-the-art, identify the open issues and provide an insight for future study areas. To achieve these objectives, we start from the factors that impact the design of dedicated intrusion detection systems in SCADA networks and focus on network-based IDS solutions. We propose a structured evaluation methodology that encompasses detection techniques, protected protocols, implementation tools, test environments and IDS performance. Special attention is focused on assessing implementation maturity as well as the applicability of each surveyed solution in the Future Internet environment. Based on that, we provide a brief description and evaluation of 26 selected research papers, published in the period 2015-2019. Results of our analysis indicate considerable progress regarding the development of machine learning-based detection methods, implementation platforms, and to some extent, sophisticated testbeds. We also identify research gaps and conclude the analysis with a list of the most important directions for further research.

This paper aims to systematically review and suggest new ideas for an E-commerce business that operates specifically to pre-purchase and post-purchase behavior. The authors screened the Web of Science database's initial data to identify and discuss several factors affecting consumer's purchase behavior, besides suggesting some ideas to cluster different socio-economic contexts. This work presents the theoretical system, the influencing factors, pre-purchase and post-purchase behavior attributes to cluster in different groups setting within e-commerce business. Besides, four major recommendations have provided to help other researchers in future study agendas.

This article carries out a systematic review of the literature on the topic of service quality, satisfaction, and loyalty in e-business. A total of 27 Scopus based articles, published between 2016 and 2020, have been analyzed. The results are presented with regard to the research contribution to the current study of the correlation between service quality, satisfaction, and loyalty. The objective of this research is to offer an overview of the establishment of service quality research in the last 5 years and fill the gap in broader knowledge about the correlation between service quality, satisfaction, and loyalty so that it can become a basis for researchers to perform future study on the topic.

Adversarial examples about deep learning models have been paid much attention in recent years, including single-label adversarial examples and multi-label adversarial examples. In this paper, for the first time, an empirical study of generating a multi-label adversarial example to hide all labels in a multi-label example is presented. The objective of hiding all labels in a multi-label example is to make deep learning models know nothing about the environments. That is very worthy of studying because deep learning models will say there is nothing, although the real input has more than one label. In the empirical study, we use five state-of-the-art multi-label attack algorithms, i.e., ML-CW, ML-DP, FGSM, MI-FGSM, MLA-LP, four popular datasets, i.e., VOC2007, VOC2012, NUS-WIDE and COCO, and two typical models ML-GCN and ASL for evaluation. We conduct extensive experiments and report the attack success rates, the amount of perturbations of the adversarial examples generated by state-of-the-art multi-label attack algorithms. We also report the attack performance when a typical defending algorithm based on JPEG compression is used. The work in this paper is beneficial to the future study of generating multi-label adversarial examples as well as defending them.

The implementation of gamification is driven by a range of factors, including the environment of the application, the elements involved and the types of users. The best practical method for effective gamification application still remains unclear, making it difficult to determine the most effective elements for an e-commerce website. This paper aims to present the literature review conducted to classify the gamification elements in e-commerce that have been investigated in previous studies which were published within the last four years (20182021). This is done to identify the most appropriate and relevant gamification elements to use in our future study. The findings from previous studies showed that gamification improved positive consumer behaviour in e-commerce, particularly in terms of engagement, and at the same time helped to boost business profitability. Furthermore, previous studies in this field have also found that rewards, badges and leaderboards were the most widely used gamification elements. This study may be used as a foundation for the researchers to build and develop a gamification framework for e-commerce in the future.

Ransomware is a new business model for cybercrime which mainly targets individual users and machines. Many events have shown how profitable the technique can be. Industrial control systems (ICS) are becoming the next domain. More and more researchers and attackers have become the focus on this field and presented some ICS ransomware. But existing ICS ransomware is theoretically feasible and has a limited effect on real ICS. In this work, we present ICS-BROCK, a full-fledged ICS ransomware that can compromise a real-world. To demonstrate the capability of ICS-BROCK, we use SIEMENS S7-300 PLC, one of the most widely used devices in ICSs, to build a real water treatment environment. The results empirically demonstrate the feasibility of launching ICS ransomware attacks in a practical setting. In the end, we give some suggestions on ICS ransomware to aid in future study and defenses.

Promoting the development of the economy and society, the Internet of Things (IoTs) is receiving wide attention. However, the devices of the IoTs are largely restricted by their power supply methods. As such, ambient backscatter communications (ABCs) are extensively discussed by industry and academia. In order to further improve the ability of coverage, data transmission, and other aspects of ABCs, this paper sheds lights on the cooperative ambient backscatter communications (CABCs), which integrate cooperative communications and ambient backscatter communications, and reviews many relative literatures, where showing that CABCs can provide performance gains compared to ABCs. Furthermore, some future research directions are also given. The future study may include constructing reasonable communication models of the CABC systems for the IoTs, collaboratively optimizing the use of the involved radio resources, overcoming the uncertainty of the environment to ensure robust and secure communications, and so on. This paper will provide reference to the use of the CABC techniques in the future IoTs.

In this study, the authors explored extensively about using digital folklore in early childhood disaster education. The researchers used a Comprehensive Literature Review (CLR) as a data collection tool and method of inquiry. The research followed the Seven-Step Model for CLR by Onwuegbuzie and Frels [1], which consisted of: exploring beliefs and subjects, initiating the search, storing and organizing information, selecting/deselecting information, extending search, evaluating and synthesizing information, and finally reporting the CLR. The authors explored conceptualizations and analyzed models used in early childhood disaster education that use digital folklore, as well as related studies. The comprehensive literature review shows that when folklore and digital technology are combined, they appear to create interesting and engaging early childhood disaster education. However, further scientific research is required, as there is a lack of empirical data on how it works exactly and also how effective it is. This study is aimed at improving our understanding of the use of digital folklore in early childhood disaster education by presenting a detailed overview of the existing debate and offering valuable guidance for future study.

Supply chain plays a significant job in an organization making systems between an organization and its supplier to deliver and disperse items and administrations to the last purchasers. Digitization alludes to the way toward moving physical reports into physical documents. Digitization will make incredible open doors for associations and supply chain rehearses. Numerous associations need to turn out to be progressively “advanced” since they have watched the criticality and value of computerized advances for their development and their own organizations. This research study topic presents a review of the supply chain management digitization practices and dreams with a merged image of digitization and stream of data between the Supplier and Manufacturer chain. Value management, in value analysis, assumes a huge job in a viable Digital Supply Chain Management, it is progressively centered around mechanization, digitizing the procedure, and the coordination and reconciliation of the considerable number of components associated with the supply chain. In view of how value-chain management has developed, it assumes an urgent job in managing the ever-expanding unpredictability in supply chains all inclusive. This study presents an overview of the supply chain management digitization practices and visions with a consolidated picture of digitization and flow of information between the Supplier and Manufacturer chain. This study can be further improved by integrating the latest technology and tools AI and IoT-as a future study.

Lung cancer is a condition which causes uncontrollable division of cells in the lungs. This causes tumor growth, which decreases a person's breathing ability. There are two types of Lung cancer - small and non-small. Both these forms of lung cancer behave differently, and have different treatments. Nevertheless, it can be difficult to identify lung cancer in its earliest stages, because the symptoms may be close to those of a respiratory infection or there may be no symptoms at all. The main aim of this paper is to find different ways to identify lung tumors using methods of photonics. We here discuss a few methods with its pros and cons. Among these we find few methods which are effective when compared to the others on basis of less time consumption, specificity, sensitivity and precision. These are discussed in detail in our discussion section. We can thereby infer that the future study of these approaches would help to diagnose and cure lung cancer in earlier stages.

This paper provides a brief overview of cooling strategies for decreasing the operating temperature of photovoltaic (PV) panels. Temperatures of PV panels during operation can reach up to 60 °C, thus decreasing the operating efficiency at rates up to 0.5 %/°C. The paper describes different cooling strategies with an emphasis on active cooling of PV panels via water spraying since this method is beneficial due to (i) cleaning effect of the surface of the PV panel, (ii) decreasing the operating temperature significantly and (iii) lowering the refraction index, thus minimizing the amount of infrared radiation absorbed by the PV cell. Computational fluid dynamics (CFD) model is developed to study the heat and mass transfer during regular operation of the PV cell without cooling and during operation with water spray cooling, and the results are compared with experimentally obtained data with good agreement. The guidelines for future studies are outlined.

Safety cases have been produced, reviewed, and written about for decades. Experts point to growing popularity and opine that their use helps to reduce major accident risk, but their history includes noteworthy accidents. Given the potential consequences of regulatory failure, it is crucial that regulatory practice be evidence-based. However, testable hypotheses about the efficacy of safety cases are rarely given, let alone supported by compelling empirical evidence. Moreover, different authors have used the term 'safety case' to mean different things. To help put safety argument practice on a sounder evidential footing, we conducted an analysis to identify potential efficacy hypotheses for future study. Our analysis considers the kinds of value arguments might bring, forms of safety case and safety argument, stakeholders, and plausible alternatives serving the same purposes. In this paper, we present our analysis and findings and discuss potential research directions.

With the development of artificial intelligence technology, artificial interactions come up for providing powerful assistance to our lives. Among them, voice user interface (VUI) plays important roles in assisting the disabled and complex interaction scenarios. This paper mainly introduces the key elements and core technics in VUI. Also, future challenges will be discussed from the perspective of empathy, ethics, and accessibility. This paper serves as a summary for future study in VUI.

Air traffic at many airports around the world is expected to grow, more often than not and at near capacity. Investing in new infrastructure is an option albeit relatively long-term but making a better use of existing facilities is an even better short and mid-term solution. Although Aircraft ground movement represents only a fraction of overall operations, optimal airport taxiing in terms of fuel burn and CO emission can contribute significantly to running costs and environment impact. Hence, with the view of optimising ground movement at busy airports, this research paper investigates a new framework for utilising model predictions to optimise the planning of taxiing operations of a BOEING-747 Aircraft. Research studies relating to how fuel consumption and emissions models (such as Carbon monoxide oxides of Nitrogen) are carried out. Specifically, the use of fuzzy-logic based models via quantitative data for the successful prediction of fuel consumption and CO emissions is explored in the paper. The fuzzy models are accurate, transparent but most importantly are capable of dealing with uncertainties, normally present in the system, intrinsically. These models and analyses will be integrated into a future study involving the development of optimal taxiing and navigation algorithms and to which the development of accurate models of aircraft fuel consumptions and emissions is crucial.

The study aimed to determine the influence of leadership behaviour on the health and safety performance in the United Arab Emirates Construction Industry was studied by this research. Construction is by far the largest industry in the UAE and the maintenance of health and safety standards that are in line with the current mandates of UAE health and safety standards are required. This ensures the safety of workers and all other project stakeholders. In addition, accident-free sites result in saving for the projects as savings will increase with no cost of accidents. Questionnaires were prepared targeting construction project leaders, in addition to construction workers at various sites in the Emirates of Abu Dhabi, Dubai, and Sharjah, also projects of different sizes were visited. Construction project leaders revealed that they do maintain current health and safety plans and policies that are in line with UAE laws and that training as well as incentives are provided for their workers. Workers, admitted to the fact that they receive the adequate training and that they are in full compliance with the set health and safety rules and regulations. Primary data, represented by the collected responses from the managers and workers interviewed, was compiled with the secondary data obtained through a thorough literature review prior to conducting the qualitative data analysis. The analysis of the data revealed a number of positive conclusions that are signs of proper implementation of health and safety rules by both managers and workers at construction sites. On the other hand, the analysis identified a number of issues, particularly with respect to the construction workers, that need to be further considered in a future study.

Medicine intake, as prescribed by physicians and health care providers, is important not only for minimizing the risk of relapse but also to treating conditions and improving one’s overall well-being. However, adherence to a medication routine seems to be a problem for some people which is usually affected by a variety of factors such as hectic day-to-day activity schedules, poor prescription instruction, concurrent intake of multiple medications, and forgetfulness. Medication adherence has been then considered as one of the major medical problems globally. In such cases, a medical device that could alert and remind patients in taking their medicines on time will come in handy. Consequently, this study aimed to design and develop a pocket-sized electronic pillbox device using TFT LCD display, Arduino microcontroller, Piezo Buzzer (for sound notification), Eccentric Rotating Mass (for vibration notification), Lithium Ion battery as power source, and plastic organizer as the main body. The said pillbox device will act as a countermeasure for medication non-adherence particularly by patients under the case of polypharmacy. Thus, this study focused on the design and development of the prototype, hardware testing and system qualification only. Furthermore, this paper is part of a future study where the assessment and measure of device behavior and adherence will be conducted to compare whether the utilization of pillbox device has an impact to the people who are using it.

The management and execution of good cybersecurity audits help organizations to strengthen their cybersecurity operations by detecting and mitigating cyberattacks and threats from attacking and destroying organizational assets based on the result of audit findings. However, the objectives of this audit cannot be fully achieved because of the various problems prevalent in audit management and execution. This paper aims to review issues that motivate the research of cybersecurity audit and the approaches to manage and execute it. Previous works in this area of interest are discussed by classifying and analyzing the current approaches. Models, scopes, strengths and limitations are studied and the most effective and accurate synthesis that can improve the quality of cybersecurity audits is highlighted. Various approaches to manage and execute cybersecurity audit with their objectives and advantages are classified. From this literature review, it is clear that cybersecurity audits can be improved by addressing the highlighted issues and create a well-rounded approach to improve the management and execution of auditing. Timeliness, accuracy and measurement in regards of cybersecurity auditing are not included in this review and shall be discussed in future study as they have significant impact on the audits.

Highly elliptical orbit (HEO) Synthetic Aperture Radar (SAR) satellites are endowed with long-term consecutive observation nearby apogee and high-resolution imaging nearby perigee. In this paper, we conduct the demand analysis and provide multiple application modes for highly elliptical orbit SAR satellite, which will provide a comprehensive reference work for future study and deployment.

While traffic modeling and prediction are at the heart of providing high-quality telecommunication services in cellular networks and have attracted much attention, they have been proved as extremely challenging tasks. Due to the diverse network demand of Internet-based apps, the cellular traffic from an individual user can have a wide dynamic range. Given the observation, we propose to leverage deep learning techniques to explore latent features in individual user’s cellular traffic. However, it is unclear what kind of features are explorable. To answer this question, we conducted a one-month data collection campaign and carried out a thorough analysis over the generated dataset. We find that user traffic demonstrates clear spatial-temporal patterns which are essential to our future study that leverages these characteristics for traffic forecasting.

In this paper, by studying the domestic and international numerous documents on vehicle suspension system failure detection methodology, different kinds of method were introduced in detail, according to the characteristics of the Urban Rain Transit Vehicle Suspension System during working state, the feasibility and the advantages and disadvantages of vehicle suspension system failure detection methodologies were discussed. To realize in-situ measurement, a novel method of fault detection and self -balance based on four-port theory was proposed, which will also be the theoretical base for the future study on failure detection and control.

Denial-of-service (DoS) attacks targeting the controller in software-defined networks (SDN) are dangerous due to the importance of the controller. In this paper, we characterize the effects of flooding attacks in SDN and discuss potential countermeasures. We concentrate on the controller-side effects of flooding attacks and present our experimental results on how packet-in message counts change in a simulation scenario. Our results imply that differentiating hosts based on only packet-in counts may be misleading for detecting attackers. Instead, packet-in to transmitted packet count ratio is better for distinguishing attackers from normal users. In addition, we measure fairness values with different attacker counts. Our results show that Jain's index is better than entropy in terms of detecting anomaly in our simulation environment. We leave utilizing fairness values to better handle packet-in requests as a future study.

Currently, k-mer counting is an important algorithm for bioinformatics research. This review lists the major application fields of k-mer counting in Bioinformatics at the beginning. Next, we introduce the commonly used memory-efficient strategy for k-mer counting tools, because the large amount of memory request is a bottleneck of k-mer counting tools. Next we illustrate the current parallel computing technologies for k-mer counting tool. Finally, we discuss the future study for k-mer counting.

The bad sitting posture leads to many back problems for young people. Nowadays the adults and young people seat for long hours hunching over their laptops and tablets. Recent researches are focus on the study and develop systems to prevent the seated persons from spinal pain with monitoring and improve the sitting posture in real-time. In this study we analyze the specification of sitting posture monitoring systems, the information required to define the human posture, the technologies used and the systems limits. The person posture can be identified by different information provided by the sensing technologies. This research can be a reference for future study for posture monitoring systems.

As the complexity of a software system grows, it becomes increasingly difficult for developers to be aware of all the dependencies that exist between artifacts (e.g., files or methods) of the system. Change impact analysis helps to overcome this problem, as it recommends to a developer relevant source-code artifacts related to her current changes. Association rule mining has shown promise in determining change impact by uncovering relevant patterns in the system's change history. State-of-the-art change impact mining algorithms typically make use of a change history of tens of thousands of transactions. For efficiency, targeted association rule mining focuses on only those transactions potentially relevant to answering a particular query. However, even targeted algorithms must consider the complete set of relevant transactions in the history. This paper presents ATARI, a new adaptive approach to association rule mining that considers a dynamic selection of the relevant transactions. It can be viewed as a further constrained version of targeted association rule mining, in which as few as a single transaction might be considered when determining change impact. Our investigation of adaptive change impact mining empirically studies seven algorithm variants. We show that adaptive algorithms are viable, can be just as applicable as the start-of-the-art complete-history algorithms, and even outperform them for certain queries. However, more important than the direct comparison, our investigation lays necessary groundwork for the future study of adaptive techniques and their application to challenges such as the on-the-fly style of impact analysis that is needed at the GitHub-scale.

The common problem in the university is the high dropout rate. The high dropout rate will have a bad impact on the university. Various studies have tried to determine the factors that influence the dropout. Almost all research focuses on academic factors of students as a determinant of potential dropouts. However, there are sometimes cases of dropout students who cannot be determined using academic factors. This raises the hypothesis that the potential dropout students can be determined from non-academic factors. There are 5 non-academic factors criteria that can be used as determinants of dropout, demography, social interaction, finance, motivation, and personal. These criteria give rise to 37 factors that are considered influential in determining the potential dropout. The factors processed into three phases are collecting data, preprocessing data, and modelling. The factor that are independent to other factors are the number of family, the interest in the future study, and the relationship with the lecturer. Based on the result of correlation test there are two factors had correlation, so the modelling done with two combination factors. The best model is using combination of factor the number of family and the relationship with the lecturer using Decision Tree with split criterion is Maximum Deviance Reduction and maximum split is 2 with time for training is 1.7386 seconds.

Pre-Silicon hardware Trojan detection has been studied for years. The most popular benchmark circuits are from the Trust-Hub. Their common feature is that the probability of activating hardware Trojans is very low. This leads to a series of machine learning based hardware Trojan detection methods which try to find the nets with low signal probability of 0 or 1. On the other hand, it is considered that, if the probability of activating hardware Trojans is high, these hardware Trojans can be easily found through behaviour simulations or during functional test. This paper explores the "grey zone" between these two opposite scenarios: if the activation probability of a hardware Trojan is not low enough for machine learning to detect it and is not high enough for behaviour simulation or functional test to find it, it can escape from detection. Experiments show the existence of such hardware Trojans, and this paper suggests a new set of hardware Trojan benchmark circuits for future study.

Collaborative annotation tools have been adopted to facilitate reading comprehension. The more the students make annotations, the better they can achieve in learning. However, students might decrease their willingness of providing annotations when they can easily read peers' annotations. To encourage students to contribute annotations in collaborative digital reading, this study employed gamification design in the developed Collaborative Reading Annotation System (CRAS) and investigated its effects on promoting students' annotation behaviors, reading comprehension, and immersion experience. Participants were 55 students from two classes of an elementary school in Northeastern Taiwan. A quasi-experimental research design was adopted. One class was assigned as the experimental group that utilized gamified CRAS and another class was assigned as the control group that used CRAS without gamification mechanisms. The results showed that students in the experimental group made significant more annotations across almost all types of annotations and had significant higher degree of engagement of using CRAS than the students in the control group. In this study, the differences of the reading performance between the two groups were not found. Future study is needed to modify the gamification mechanisms to promote both reading engagement and reading achievement.

This paper presents an analysis of transients in a system with a parallel connection of one synchronous generator and one self-excited induction generator, each coupled to a dc machine as well as a capacitor bank. A resistive load is connected to the system. Changes in the load were provoked. Then, each generators was removed, one at a time, and reconnected. The results are shown here and the respective curves are analyzed. The conclusion indicates, for this new arrangement of generators, good regulation regarding transients from load and generation. Improvement points are given for future study.

Recently, games have grown in popularity as tools to support student learning and motivation. Accordingly, games represent one possible contributor to student motivation, an outcome of engineering education particularly important to learning and to student persistence. However, research into game-based learning — a broad term referring to the use of games in education — has been rather narrow to date, focusing on proving or disproving the effectiveness of games as learning tools. As evidence supporting games' effectiveness continues to mount, it is important that the field broaden its inquiry to provide practice-based insights that enable instructors to implement game-based learning in an effective manner. Our research seeks to address this gap by studying how engineering instructors use games in the classroom, and how these teaching practices related to student motivation to learn. The overall study will use a multiple-case study approach, including observations and interviews with instructors and their students. Preliminary results from this work-in-progress study revealed substantial variability in the teaching practices of two engineering instructors using non-digital games, and provided several methodological implications for future study of game-based teaching.

This paper presents a new data decimation method called phase-preserving quantization (PPQ) that allows wireless data transmission of thousands of simultaneously recorded μECoG channels. PPQ consists of a 1-bit compression scheme and a simple decision condition that permits efficient in-situ hardware implementation. The effectiveness of PPQ was validated by demonstrating accurate calculation of phase synchrony across many channels of real ECoG recording datasets. Results show that PPQ preserves the instantaneous phase information needed to produce synchrony patterns with a minimum accuracy of 90%. The presented method enables high-channel-count μECoG recordings suitable for the future study of functional interactions across diverse areas of the brain.

EEG-based BCI (brain-computer-interface) speller, especially gaze-independent BCI speller, has become a hot topic in recent years. It provides direct spelling device by non-muscular method for people with severe motor impairments and with limited gaze movement. Brain needs to conduct both stimuli-driven and stimuli-related attention in fast presented BCI paradigms for such BCI speller applications. Few researchers studied the mechanism of brain response to such fast presented BCI applications. In this study, we compared the distribution of brain activation in visual, auditory, and audio-visual combined stimuli paradigms using sLORETA (standardized low-resolution brain electromagnetic tomography). Between groups comparisons showed the importance of visual and auditory stimuli in audio-visual combined paradigm. They both contribute to the activation of brain regions, with visual stimuli being the predominate stimuli. Visual stimuli related brain region was mainly located at parietal and occipital lobe, whereas response in frontal-temporal lobes might be caused by auditory stimuli. These regions played an important role in audio-visual bimodal paradigms. These new findings are important for future study of ERP speller as well as the mechanism of fast presented stimuli.

Gray mold causes a sharp drop in blueberries production, the modeling and analysis of blueberry gray mold are important for the future study of blueberry related diseases and insect pests. In the introduction, the related diseases and insect pests of blueberry were summarized. The modeling method of blueberry pests and diseases was introduced. On this basis, the blueberry gray mold was modeled. And the results of the model test are in good agreement with the target.

Breaking contracts have a major impact on API clients. Despite this fact, recent studies show that libraries are often backward incompatible and that the rate of breaking changes increase over time. However, the specific reasons that motivate library developers to break contracts with their clients are still unclear. In this paper, we describe a qualitative study with library developers and real instance of API breaking changes. Our goal is to (i) elicit the reasons why developers introduce breaking changes; and (ii) check if they are aware about the risks of such changes. Our survey with the top contributors of popular Java libraries contributes to reveal a list of five reasons why developers break API contracts. Moreover, it also shows that most of developers are aware of these risks and, in some cases, adopt strategies to mitigate them. We conclude by prospecting a future study to strengthen our current findings. With this study, we expect to contribute on delineating tools to better assess the risks and impacts of API breaking changes.

Continuous Positive Airway Pressure (CPAP) is used to maintain the most effective way to live with obstructive sleep apnea. The working principle of the machine is to blow air through the nose or mouth to keep open the upper airway all the time. The price of CPAP in the market is very expensive which affects many people who need to use CPAP for treatment but cannot afford it. The design and development of a prototype CPAP which functions in the way it is supposed to will be the main objectives of this study. The results of a performance test show that accuracy of the measurement of moisture is 94.09% and the accuracy of temperature measurement is 99.20%. The pressure sensor has an accuracy of over 97%. The CPAP machine provided similar pressure to the ideal pressure values for CPAP settings. The results are quite satisfactory which can be a platform for future study of clinical trials.

Currently, colorectal cancer (CRC) already becomes one of the most common cancers worldwide. Though the prognosis of CRC patients is dramatically improved due to the new advanced treatments and medical improvements, the 5-year survival rate for the CRC patient is still low. Thus, we hypothesize that CRC may result from the complicated reasons related to both genetic and environmental factors. For this reason, this study collects such big CRC data with information of genetic variations and environmental exposure for the CRC patients and cancer-free controls that are employed to train and test the predictive CRC model. Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to cause the CRC by the manually reviewed experimental evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, (3) our innovated generalized kernel recursive maximum correntropy(GKRMC) algorithm has high predictive power. Finally, we discuss why the GKRMC can outperform the classical regression algorithms and the related future study.

By using monthly precipitation data and standardized precipitation index (SPI), combining the normalized difference vegetation index (NDVI) data and historical statistical data of drought area, the drought trend of Gannan region from 1965 to 2013 was analyzed. The results showed that: (1) from 1965 to 2013, the drought index in study area rose firstly (1965–1976) and leveled off (1977–1989), then decreased (1990–2001) and finally rose again (2000–2012). (2) SPI was closely related to NDVI, y=0.0298x2+0.062+0.7678, (R2=0.9034), y is the NDVI value of the pixel, x is the SPI value of the meteorological stations. (3) Compared with historical data, SPI6 could reveal the drought conditions in alpine meadows commendably. These results would provide effective theory and method which can support related research in the future study.

This paper expands upon a proposed freeway-style method of traffic management for commercial sUAS, with the goal of increasing traffic safety and efficiency. Various potential hazards that sUAS may encounter mid-flight will be examined and categorized by severity; their resulting effects on traffic flow will be analyzed when applicable. Potential design improvements will be suggested, and areas for future study will be pinpointed in the process. The purpose of this paper is to help bring large-scale sUAS travel networks closer to reality.

We motivate further study of vibrotactile rendering schemes for the sensation of arbitrary points in irregular grids or meshes, outline a conceptual approach, and propose a study for assessing and comparing approaches. A conceptual model presents the combination of vibrations from multiple elements (tactors) as a two-stage pairing of tactors into virtual tactors, considering the 2D dimensionality. To support irregular triangle meshes, we suggest parameters to characterize triangle shape and a future study to measure sensations for varying shape. Gathered data will be used to assess and compare perceptual combination models and to develop precise rendering functions for irregular triangle meshes.

This paper presents the Certificate of Science and Technology (CertScT) a pre-degree programme at Auckland University of Technology in New Zealand, developed with the aim of preparing students to undertake degree level study in Science, Technology, Engineering and Mathematics (STEM) subjects. The history, context and rationale for the programme is outlined together with its structure and content, and pedagogical and programme level strategies that have been adopted to encourage student success. The authors reflect on the success of the programme to date in achieving its aims, based upon observation, reflections and data from internal evaluations of the programme. The paper notes the challenges for the programme posed by external metrics which the New Zealand Government has adopted. The paper concludes with a commentary on the success of the programme in achieving its goals, and the risks to its continuation.

Broadband network performance is multi-faceted: it varies by ISP, by content source, by household connection, and by time-of-day. Daily or monthly averages, as published by content providers such as Netflix and Google, do not convey the full picture. In this paper we leverage M-Lab, the world's largest open measurement platform, to characterize broadband performance across Australian households. Our study delves into millions of data samples collected from 96,882 households over four months, and looks beyond averages to make several interesting observations: 1) There is considerable variation amongst households, in terms of their broadband speeds and variability of network performance within a day and across days, and this information is lost when data is averaged across houses; 2) The fluctuations (even for a specific house) are significant, and can exhibit unexpected patterns, such as wide variations from one day to the next, and some clusters of outliers at certain times of the day. 3) By our experimental results, we conclude that neither aggregating by household nor aggregating by day or by hour is a sound measurement strategy. Moreover, our study sheds new perspectives on broadband evaluation by using M-Lab data, and can inspire future study into the underlying reasons of performance variation.

Unvalidated Sources of Health Information (USHI) have been very successful in spite of the risk they pose to the health and well-being of their users. Our goal is to present a framework for the future study of USHI that studies the basic factors responsible for its success so as to enable the creation of better strategies to curb their use. Such studies leading to the identification of the components of USHI's success can be useful in improving the design of other less adopted consumer healthcare systems. To achieve this goal, we suggest the "reverse-engineering" of various information technology (IT) adoption and success theories to identify the actionable components of their antecedents with respect to USHI that can be directly useful to designers of IT artifacts. We also speculate on several potential benefits of such research beyond addressing the threat USHI represents.

The problem of estimating causal relationships from purely observational data is studied in this paper. We observe samples from a pair of random variables (X,Y) and wish to estimate whether X causes Y or Y causes X. Any joint distribution can be factored as pX,Y = pX pY|X = pY pX|Y and therefore the “causal” direction cannot be inferred from the joint distribution without further assumptions. In this paper, we propose and study the utility of Shannon capacity as a metric for causal directionality estimation. This opens up several open questions and directions for future study.

OsteoArthritis is a debilitating disease throughout the developed world, causing significant loss of quality of life to individuals and damaging economies, the imaging system described in this paper has the potential to provide an objective means of measuring and reporting lesion dimensions and providing a machine readable data archive for future study. Existing imaging methodologies have been reviewed and contrasted and despite certain limitations the optical method proposed has the potential to address the issues highlighted to date. The preliminary depth measurement results with an accuracy of 200 µm±6% suggests a potential system for the objective reporting of tissue degradation. It is also envisaged that the bio tribological performance may be inferred from the tissue surface condition as image by the proposed system.

Many people have lower limb paralysis from different reasons and many Thai patients were prescribed by passive orthoses although some active orthoses have been invented [1–5] for more natural and smooth gait because of augmentation and control of weak motions for the paralyze people, but the price is expensive and difficult for Thai disables to access. The objective of this study is to develop the active orthosis that help empower knee motions for weak knee extensor patients. One normal subject participated and walked with the developed device for three rounds in order to see if the desired knee angle and power is achieved. The knee angles were measured and compared with normal data of knee angle during a gait cycle. The design criteria were achieved but further improvement should be done for the future study.

This article presents experimental tests made on a DC to DC Boost Converter of 24 V-48 V. The boost converter was first realized on a laboratory version, regarding it's utility as a voltage source for the E.I.A (Equipments and Installations for Aviation) laboratory of the University of Craiova, and also to be used in teaching activities and for research. During tests it was point out the performances obtained, but also the inconvenient and the limitations of the purposed scheme. The improvements of this schema will be presented in a future study.

Social networking has changed human life style in the recent era. The impact of use of social networking has not only resulted in globalization but has influenced many other vital factors of human performance This study aimed at exploring impact of Facebook usage intensity on academic grades of the private university students. It was hypothesized that there will be a significant impact of Facebook usage on university student grades and that there will be a significant gender difference on the variable of Facebook intensity scores. Quantitative method was chosen for the study with a survey strategy. The data was collected from a total number of 275 participants from 13 different private universities of Pakistan. Hypotheses were tested using linear regression analysis and independent sample t-test. The data analysis revealed that Facebook usage doesn't predict university student grades and likewise there is no gender difference found on the variable of Facebook intensity. The study was concluded elaborating the discussion and providing recommendations for the future study.

It has been established that tumor cells can be distinguished from surrounding healthy tissue by electrical impedance. However, existing impedance measuring apparatus require direct contact or excision. In this work, we suggest the application of Biomimetic Electrostatic Imaging (BEI) to the task of impedance-based cellular-scale cancer screening and conduct a phantom study with a hyperconductive target to explore efficacy. It was shown that current BEI hardware could detect the phantom target at ranges exceeding seven-times the excitation length. Future study is needed to prove the result holds with miniaturization.

Electromyogram (EMG) activity from the extensor and flexor muscles of the forearm was sensed with high-density surface electrode arrays and related to the force produced at the four fingertips during constant-posture, slowly force-varying contractions from three healthy subjects. Various electrode montages (spatial filters) and number of electrodes used in the system identification were studied. Average errors were small, ranging from 4.21 to 8.10 %MVCF (flexion maximum voluntary contraction), with errors trending lower when more EMG channels were used and when a monopolar electrode montage was selected. Results are supportive that multiple degrees of freedom of proportional control information are available from the surface EMG of the forearm, at least in intact subjects. Applications for future study include the control of prosthetic upper limb devices in amputees.

In this paper we present a vision of how a sequence of three embedded systems design courses currently being taught for computer engineering technology students will be adapted from a quarter based delivery to a semester based delivery. The conversion brings the opportunity to revise the course contents, platforms used and make changes that will prepare students with a more up-to-date skill set and a robust industrial training. In this work in progress we will present some of the new ideas that will be implemented in our semester courses. After offering these courses multiple times, feedback will be gathered from students and industry, and a future study will be presented outlining the achieved outcomes as compared to our intended outcomes for curriculum continuous improvement.

This paper introduces the concept of using tactical shortcuts to improve arrival precision and thereby increase throughput. This concept schedules flights to a longer path for which a shortcut path option is available for time recovery when speed is restricted. Shortcut design parameter sensitivity for schedule-based and spacing-based use policies is explored for single vs. multiple shortcut designs and shortcut availability. Simulation results show schedule-based shortcuts can reduce scheduling buffer size by 35-55% (increasing maximum throughput) or reduce separation violation probability 15-20% (reducing controller workload). Spacing-based shortcuts can reduce scheduling buffer size or separation violation probability by an additional 20% or 5% respectively. Additional studies were conducted to evaluate throughput and delay performance of each shortcut use policy for a wide range of demand rates. Spacing-based shortcuts performed the best. A use policy that combined the schedule-based shortcut method and scheduling without shortcuts outperformed using either of these methods individually. The potential benefits of using tactical shortcuts warrants future study in its application to multi-point scheduling, performance-based operations, geometric design, and decision support tools.decision support tools.