Search results for: subjective bias detection

Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Rachelle Angeli Maranon

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This research explored the relationships of a child’s family condition, sex and subjective well-being (SWB) to gain some understanding of the experiences of both transnational and non-transnational families. A descriptive-correlational design was used to study the variables. Participants included 52 male and female children from Iloilo and Kabankalan cities, representing the family conditions in this study. Data were gathered using a semi-structured interview guide. Responses were analyzed using Mann-Whitney U Test. The results showed that the SWB of non-transnational children was significantly higher compared to their transnational counterparts (U = 134, p = .00). Also, analysis between females and males indicated a significant difference only on some aspects (U = 318, p = .71). Some recommendations were suggested to better understand the plight of the left-behind children.

Keywords: left-behind children, mothers, subjective well-being, transnational families

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

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Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder bias voltage, switching voltage, radio-over-fiber, RF gain

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Authors: H. Benmoussa, A. A. El Kalam, A. Ait Ouahman

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The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility.

Keywords: Intrusion Detection System (IDS), preventive detection, mobile agents, distributed architecture

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Authors: Nguyen Thi Huong Nhai

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This paper examines how different motivations to engage in organic farming may impact the farmers’ subjective well-being using a survey database from the French Agence Bio. Three measures representing the subjective well-being of farmers brought by their involvement in organic farming are used in this study: feelings of pride, satisfaction, and feeling of happiness. We focus on the effects of two different types of motivations: intrinsic motivations, such as preservation of human health and public health, concern about the environment, and autonomy in farming decisions; extrinsic motivations, such as fair price, income, and demand incentives. Results show that not all intrinsic motivations can increase farmers’s well-being. The intrinsic motivation relating to environment concern and aspiration seems to have the highest positive impact on the three proxies of SWB in our study. It is interesting to find out that the two extrinsic motivations (profitable price, satisfying the incentive of consumer and cooperative) are proven to have a negative influence. Some comparisons, explanations, and practical implications are also indicated in this research.

Keywords: intrinsic otivation, extrinsic motivation, subjective wellbeing, organic farmers

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Maria Luskova, Maria Hudakova, Katarina Buganova

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Established objective and subjective preconditions for entrepreneurship, forming the business organically related whole, are the necessary condition of successful entrepreneurial activities. Objective preconditions for entrepreneurship are developed by the market economy that should stimulate entrepreneurship by allowing the use of economic opportunities for all those who want to do business in respective field while providing guarantees to all owners and creating a stable business environment for entrepreneurs. Subjective preconditions of entrepreneurship are formed primarily by personal characteristics of the entrepreneur. These are his properties, abilities, skills, physiological, and psychological preconditions which may be inherited, inborn or sequentially developed and obtained during his life on the basis of education and influences of surrounding environment. The paper is dealing with issues of objective and subjective preconditions for entrepreneurship and provides their analysis in view of the current situation in Slovakia. It presents risks of the business environment in Slovakia that the Slovak managers considered the most significant in 2014 and defines the dominant attributes of the entrepreneur in the current business environment in Slovakia.

Keywords: entrepreneurship, innovations, opportunity, risk, uncertainty

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Authors: Yeşim Özer Özkan, Fatma Büşra Fincan

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Biased sample is a regression of an observation, design process and all of the specifications lead to tendency of a side or the situation of leaving from the objectivity. It is expected that, test items are answered by the students who come from different social groups and the same ability not to be different from each other. The importance of the expectation increases especially during student selection and placement examinations. For example, all of the test items should not be beneficial for just a male or female group. The aim of the research is an investigation of item bias whether or not the exam included in 2014 free boarding and scholarship examination in terms of gender variable. Data which belong to 5th, 6th, and 7th grade the secondary education students were obtained by the General Directorate of Measurement, Evaluation and Examination Services in Turkey. 20% students were selected randomly within 192090 students. Based on 38418 students’ exam paper were examined for determination item bias. Winsteps 3.8.1 package program was used to determine bias in analysis of data, according to Rasch Model in respect to gender variable. Mathematics items tests were examined in terms of gender bias. Firstly, confirmatory factor analysis was applied twenty-five math questions. After that, NFI, TLI, CFI, IFI, RFI, GFI, RMSEA, and SRMR were examined in order to be validity and values of goodness of fit. Modification index values of confirmatory factor analysis were examined and then some of the items were omitted because these items gave an error in terms of model conformity and conceptual. The analysis shows that in 2014 free boarding and scholarship examination exam does not include bias. This is an indication of the gender of the examination to be made in favor of or against different groups of students.

Keywords: gender, item bias, placement test, Rasch model

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Authors: Hyungil Chae

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This work presents a method to reduce spinning current of a Hall-effect sensor for low-power magnetic sensor applications. Spinning current of a Hall-effect sensor changes the direction of bias current periodically and can separate signals from DC-offset. The bias current is proportional to the sensor sensitivity but also increases the power consumption. To achieve both high sensitivity and low power consumption, the bias current can be pulse-width modulated. When the bias current duration Tb is reduced by a factor of N compared to the spinning current period of Tₛ/2, the total power consumption can be saved by N times. N can be large as long as the Hall-effect sensor settles down within Tb. The proposed scheme is implemented and simulated in a 0.18um CMOS process, and the power saving factor is 9.6 when N is 10. Acknowledgements: This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (20160001360022003, Development of Hall Semi-conductor for Smart Car and Device).

Keywords: chopper stabilization, Hall-effect sensor, pulse width modulation, spinning current

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

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Authors: Grace Baptie, Jackie Andrade, Alison Bacon, Alyson Norman

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Background: Many women experience their childbirth as traumatic, and 4-6% of mothers present with postnatal posttraumatic stress disorder (PTSD) as a result of their birth. Aims: To measure the relationship between obstetric and subjective experience of childbirth on mothers’ experience of postnatal trauma and identify salient aspects of the birth experience considered traumatic. Methods: Women who had given birth within the last year completed an online mixed-methods survey reporting on their subjective and obstetric birth experience as well as symptoms of postnatal trauma, depression and anxiety. Findings: 29% of mothers experienced their labour as traumatic and 15% met full or partial criteria for PTSD. Feeling supported and in control mediated the relationship between obstetric intervention and postnatal trauma symptoms. Five key themes were identified from the qualitative data regarding aspects of the birth considered traumatic including: obstetric complications; lack of control; concern for baby; psychological trauma and lack of support. Conclusion: Subjective birth experience is a significantly stronger predictor of postnatal trauma than level of medical intervention, the psychological consequences of which can be buffered by an increased level of support and control.

Keywords: birth trauma, perinatal mental health, postnatal PTSD, subjective experience

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Authors: Adilla Anggraeni

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The purpose of the paper is to investigate the effects of religiosity and subjective knowledge towards initial trust that a consumer has towards a product manufacturer. Since globalization enters the point of no return, it should be acknowledged that further exploration of country of origin image, its influences and possible limiting factors is imperative. This model aims to broaden COO-related research, especially related to different product categories based on the perception of consumers in emerging markets. The study employs quantitative method, aiming to involve 200 Indonesian respondents to evaluate different product categories (food/apparel). Relationships between variables are evaluated using structural equation modeling. It is expected that subjective knowledge will have significant influence towards initial trust that an individual possesses towards food products. A major contribution of this study will be the inclusion of religiosity and subjective knowledge in the country of origin study’s body of knowledge. Companies are also expected to benefit from the study as the acceleration of globalization may again repose the question of whether companies should market their product using similar strategies across different countries or different ones. Religiosity dimension is expected to add values to international marketing literature concerning emerging economies in particular, as many companies view the emerging economies as promising markets.

Keywords: country of origin, subjective knowledge, initial trust, emerging economy, Indonesia

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Authors: Mamoona Mushtaq, Komal Meher

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The COVID-19 pandemic, a global public health crisis, has triggered anxiety and fear of death in the public, particularly among health professionals. This study aimed to assess the direct and mediated associations between death anxiety, sleep quality, and subjective well-being in doctors working during the pandemic. Another aim was tested to analyze the interactive role of workplace locality in these associations. An indirect-effect model was tested on a sample of 244 doctors working during the pandemic. Findings revealed that the association between death anxiety and subjective well-being was mediated through depression. The theoretical and practical implications of the findings are discussed.

Keywords: death anxiety, depression, subjective well-being, working locality

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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Authors: Cory A. Logston

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It is imperative researchers continue to explore every transformative strategy to increase empathy and awareness of racial bias. Racism is a social and political concept that uses stereotypical ideology to highlight racial inequities. Everyone has biases they may not be aware of toward disparate out-groups. There is some form of racism in every profession; doctors, lawyers, and teachers are not immune. There have been numerous successful and unsuccessful strategies to motivate and transform an individual’s unconscious biased attitudes. One method designed to induce a transformative experience and identify implicit bias is virtual reality (VR). VR is a technology designed to transport the user to a three-dimensional environment. In a virtual reality simulation, the viewer is immersed in a realistic interactive video taking on the perspective of a Black man. The viewer as the character experiences discrimination in various life circumstances growing up as a child into adulthood. For instance, the prejudice felt in school, as an adolescent encountering the police and false accusations in the workplace. Current research suggests that an immersive VR simulation can enhance self-awareness and become a transformative learning experience. This study uses virtual reality immersion and transformative learning theory to create empathy and identify any unintentional racial bias. Participants, White teachers, will experience a VR immersion to create awareness and identify implicit biases regarding Black students. The desired outcome provides a springboard to reconceptualize their own implicit bias. Virtual reality is gaining traction in the research world and promises to be an effective tool in the transformative learning process.

Keywords: empathy, implicit bias, transformative learning, virtual reality

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Authors: M. H. Aldahrob, A. Kokce, S. Altindal, H. E. Lapa

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In order to obtain the detailed information about the effect of (Zn-doped PVA) interfacial layer, surface states (Nss) and series resistance (Rs) on electrical characteristics, both Au/n- type 4H-SiC (MS) with and without (Zn doped PVA) interfacial layer were fabricated to compare. The main electrical parameters of them were investigated using forward and reverse bias current-voltage (I-V), capacitance-voltage (C-V) and conductance –voltage (G/W –V) measurements were performed at room temperature. Experimental results show that the value of ideality factor (n), zero –bias barrier height (ΦBo), Rs, rectifier rate (RR=IF/IR) and the density of Nss are strong functions interfacial layer and applied bias voltage. The energy distribution profile of Nss was obtained from forward bias I-V data by taking into account voltage dependent effective BH (ΦBo) and ideality factor (n(V)). Voltage dependent profile of Rs was also obtained both by using Ohm’s law and Nicollian and Brew methods. The other main diode parameters such as the concentration of doping donor atom (ND), Fermi energy level (EF).BH (ΦBo), depletion layer with (WD) were obtained by using the intercept and slope of the reverse bias C-2 vs V plots. It was found that (Zn-doped PVA) interfacial layer lead to a quite decrease in the values Nss, Rs and leakage current and increase in shunt resistance (Rsh) and RR. Therefore, we can say that the use of thin (Zn-doped PVA) interfacial layer can quite improved the performance of MS structure.

Keywords: interfacial polymer layer, thickness dependence, electric and dielectric properties, series resistance, interface state

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno

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The most common source of bias detected are those of gender and socioeconomic status. The present study investigated the Differential Item Functioning (DIF) or item bias between public and private school students in a vocabulary test. Studies on DIF were expanded by using the type of school as a source of bias. There were 200 participants in this study. 100 came from a public secondary school and 100 came from a private secondary school. The vocabulary skills of students were measured using a standardized vocabulary test for grade 7 students. Using DIF, specifically the Rasch-Welch approach, it was found that out of 24 items, 12 were biased for a specific group. The vocabulary skills on the use of slang, idiomatic expression, personification, collocations, and partitive relations were biased for private schools while the use of slang and homonymous words were biased for public school students. The analysis debunked the trend that private school students are outperforming public school students in terms of academic achievement. It was revealed that there are some competencies that private school students are having difficulty and vice versa.

Keywords: differential item functioning, item bias, public school students, private school students, vocabulary

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Authors: Eszter Siposne Nandori

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The paper describes how the subjective interpretation of poverty changed during the COVID-19 pandemic. The results of data collection at the end of 2020 are compared to the results of a similar survey from 2019. The methods of systematic data collection are used to collect data about the beliefs of the population about poverty. The analysis is carried out in Borsod-Abaúj-Zemplén County, one of the most backward areas in Hungary. The paper concludes that poverty is mainly linked to material values, and it did not change from 2019 to 2020. Some slight changes, however, highlight the effect of the pandemic: poverty is increasingly seen as a generational problem in 2020, and another important change is that isolation became more closely related to poverty.

Keywords: Hungary, interpretation of poverty, pandemic, systematic data collection, subjective poverty

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

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Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

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Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

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Authors: Atefeh Bagherianziarat, Dana Hamplova

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The inverse social gradient in life satisfaction (LS) is a well-established research finding. To estimate the influence of inequality on LS, most of the studies have explored the effect of the objective aspects of inequality or individuals’ socioeconomic status (SES). However, relatively fewer studies have confirmed recently the significant effect of the subjective aspect of inequality or subjective socioeconomic status (SSS) on life satisfaction over and above SES. In other words, it is confirmed by some studies that individuals’ perception of their unequal status in society or SSS can moderate the impact of their absolute unequal status on their life satisfaction. Nevertheless, this newly confirmed moderating link has not been affirmed to work likewise in societies with different levels of social inequality and also for people who believe in the value of equality, at different levels. In this study, we compared the moderative influence of subjective inequality on the link between objective inequality and life satisfaction. In particular, we focus on differences across welfare state regimes based on Esping-Andersen's theory. Also, we explored the moderative role of believing in the value of equality on the link between objective and subjective inequality on LS in the given societies. Since our studied variables were measured at both individual and country levels, we applied a multilevel analysis to the European Social Survey data (round 9). The results showed that people in deferent regimes reported statistically meaningful different levels of life satisfaction that is explained to different extends by their household income and their perception of their income inequality. The findings of the study supported the previous findings of the moderator influence of perceived inequality on the link between objective inequality and LS. However, this link is different in various welfare state regimes. The results of the multilevel modeling showed that country-level subjective equality is a positive predictor for individuals’ life satisfaction, while the GINI coefficient that was considered as the indicator of absolute inequality has a smaller effect on life satisfaction. Also, country-level subjective equality moderates the confirmed link between individuals’ income and their life satisfaction. It can be concluded that both individual and country-level subjective inequality slightly moderate the effect of individuals’ income on their life satisfaction.

Keywords: individual values, life satisfaction, multilevel analysis, objective inequality, subjective inequality, welfare regimes status

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Authors: Zeinu Ahmed Rabba, Derek D Stretch

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Remote sensing contributes valuable information to streamflow estimates. Usually, stream flow is directly measured through ground-based hydrological monitoring station. However, in many developing countries like Ethiopia, ground-based hydrological monitoring networks are either sparse or nonexistent, which limits the manage water resources and hampers early flood-warning systems. In such cases, satellite remote sensing is an alternative means to acquire such information. This paper discusses the application of remotely sensed rainfall data for streamflow modeling in Gilgel Ghibe basin in Ethiopia. Ten years (2001-2010) of two satellite-based precipitation products (SBPP), TRMM and WaterBase, were used. These products were combined with the PyTOPKAPI hydrological model to generate daily stream flows. The results were compared with streamflow observations at Gilgel Ghibe Nr, Assendabo gauging station using four statistical tools (Bias, R², NS and RMSE). The statistical analysis indicates that the bias-adjusted SBPPs agree well with gauged rainfall compared to bias-unadjusted ones. The SBPPs with no bias-adjustment tend to overestimate (high Bias and high RMSE) the extreme precipitation events and the corresponding simulated streamflow outputs, particularly during wet months (June-September) and underestimate the streamflow prediction over few dry months (January and February). This shows that bias-adjustment can be important for improving the performance of the SBPPs in streamflow forecasting. We further conclude that the general streamflow patterns were well captured at daily time scales when using SBPPs after bias adjustment. However, the overall results demonstrate that the simulated streamflow using the gauged rainfall is superior to those obtained from remotely sensed rainfall products including bias-adjusted ones.

Keywords: Ethiopia, PyTOPKAPI model, remote sensing, streamflow, Tropical Rainfall Measuring Mission (TRMM), waterBase

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Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

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In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

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Authors: Linnan Zhang

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Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

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Authors: Norzalina Othman, Nurul Na’imy Wan, Azliza Mohd Rusli, Wan Noor Syahirah Meor Idris

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Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors.

Keywords: iris detection, midpoint coordinates, RGB images, side mirror

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Authors: Maha Hammami, Olfa Benouda Sioud

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This study investigates the reliability of management earnings forecasts with reference to these two ingredients: verifiability and neutrality. Specifically, we examine the biasedness (or accuracy) of management earnings forecasts and company specific characteristics that can be associated with accuracy. Based on sample of 102 IPO prospectuses published for admission on NYSE Euronext Paris from 2002 to 2010, we found that these forecasts are on average optimistic and two of the five test variables, earnings variability and financial leverage are significant in explaining ex post bias. Acknowledging the possibility that the bias is the result of the managers’ forecasting behavior, we then examine whether managers decide to under-predict, over-predict or forecast accurately for self-serving purposes. Explicitly, we examine the role of financial distress, operating performance, ownership by insiders and the economy state in influencing managers’ forecasting preferences. We find that managers of distressed firms seem to over-predict future earnings. We also find that when managers are given more stock options, they tend to under-predict future earnings. Finally, we conclude that the management earnings forecasts are affected by an intentional bias due to managers’ forecasting preferences.

Keywords: intentional bias, management earnings forecasts, neutrality, verifiability

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Authors: Jiaqi Zhang, Zhi Dong, Pan Xing

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With the continuous development of urban agglomerations, higher demands are placed on intercity public transport travel services. To improve these services, it is necessary to comprehensively understand the views and evaluations of travelers. Taking the Guanzhong Plain urban agglomeration in China as the object, this study explores subjective attitude indicators from self-administrated survey data and examines the relationship among perceived accessibility, preference, and satisfaction for intercity public transport using a structural equation model. The results show that perceived service quality has a direct positive impact on perceived accessibility and satisfaction. Perceived accessibility and preference significantly affect satisfaction. In addition, perceived accessibility mediates the effect of service quality on satisfaction. This study provides valuable insights from a policy perspective to improve the subjective evaluation of intercity public transport travelers while emphasizing the importance of subjective variables in transport system evaluation and advocates for their subdivision to more comprehensively improve the travel experience.

Keywords: intercity public transport, perceived accessibility, satisfaction, structural equation model

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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