How International College Students Understand Entrepreneurial Readiness and Business-Related Skills: A Qualitative Study

The free-market economy provides many opportunities for entrepreneurship or starting one’s own business, attracting many students to study business at for-profit colleges in the United States. This is also true for international students, many of whom are filled with the hope of making a better life for themselves and their families through entrepreneurial endeavors. This qualitative research showed that not all graduates business students start their own business. In investigating this phenomenon, the effectiveness of entrepreneurship curricula at international colleges needs to be examined in order to adjust, improve and reform entrepreneurship curricula. This qualitative study will explore how business skills learned in college for-profit play a role in the entrepreneurial readiness of undergraduate business students in the south Florida. Business curricula helps international students achieve goals and transform their actions to understand challenges in a corporate society. Students will be interviewed to gain information about the students’ experience with entrepreneurship curricula in a for-profit college in south Florida.

Development of a Basic Robot System for Medical and Nursing Care for Patients with Glaucoma

Medical methods to completely treat glaucoma are yet to be developed. Therefore, ophthalmologists manage patients mainly to delay disease progression. Patients with glaucoma are mainly elderly individuals. In elderly people's houses, having an equipment that can provide medical treatment and care can release their family from their care. For elderly people with the glaucoma to live by themselves as much as possible, we developed a support robot having five functions: elderly people care, ophthalmological examination, trip assistance to the neighborhood, medical treatment, and data referral to a hospital. The medical and nursing care robot should approach the visual field that the patients can see at a speed suitable for their eyesight. This is because the robot will be dangerous if it approaches the patients from the visual field that they cannot see. We experimentally developed a robot that brings a white cane to elderly people with glaucoma. The base part of the robot is a carriage, which is a Megarover 1.1, and it has two infrared sensors. The robot moves along a white line on the floor using the infrared sensors and has a special arm, which does not use electricity. The arm can scoop the block attached to the white cane. Next, we also developed a direction detector comprised of a charge-coupled device camera (SVR41ResucueHD; Sun Mechatronics), goggles (MG-277MLF; Midori Anzen Co. Ltd.), and biconvex lenses with a focal length of 25 mm (Edmund Co.). Some young people were photographed using the direction detector, which was put on their faces. Image processing was performed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2. To measure the people's line of vision, we calculated the iris's center of gravity using five processes: reduction, trimming, binarization or gray scale, edge extraction, and Hough transform. We compared the binarization and gray scale processes in image processing. The binarization process was better than the gray scale process. For edge extraction, we compared five methods: Sobel, Prewitt, Laplacian of Gaussian, fast Fourier transform, and Canny. The Canny method was the optimal extraction method. We performed the Hough transform to search for the main coordinates from the iris's edge, and we found that the Hough transform could calculate the center point of the iris.

Sex Education: A Need for Students with Disabilities in India

Sexuality remains a personal or a private matter of discussion in the Indian society and generally discussed among the same age group or gender. Complete absence of the sex education has caused serious implications for the students with disabilities in Indian society. There are widespread perceptions that student with disabilities are ‘asexual’, ‘unattractive’ and therefore cannot be considered sexually desirable. Such perceptions continue to reinforce the other perceptions that student with disabilities are somehow incapable of being in an intimate relationship in the life and therefore they do not need any learning related to the sex education. We need to understand that if a student has a disability, it does not mean that student have no emotional feelings, hormones and sexual desires like any other student without disability. Sexuality is an integral part of every human life and should not be seen as matter of shame and guilt. Unfortunately, the concept of the sex education is misunderstood in itself. Instead of realizing the crucial importance of sex education for the students with disabilities or non-disabilities, it is often considered mainly as an education about ‘how to have sexual intercourse’. One needs to understand that it is not just about sexual conduct but also about the gender and sexual identity, self-esteem, self protection and acceptance of self. This research paper examined issues and debates around the sex education, particularly in context of the students with disabilities in India and focuses on how students with disabilities themselves see the need of sex (health) education. To understand their perceptions, descriptive survey method was used. It was found that most of the students among respondent were comfortable and felt it as a strong need for such orientation during their schooling. The paper emphasizes that sex education is a need of the time and further a necessity. Hence it is important for our education system to implement it for the complete well being of the students with disabilities.

Implementing a Mobility Platform to Connect Hubs in Rural Areas

Mobility, for many people, is an important factor in the satisfaction of daily needs and many people are dependent on public transport. In rural areas with a low population density, it is difficult to provide public transportation with sufficient coverage and frequency. Therefore, the available public transport is unattractive. As a result, people use their own car, which is not desirable from a sustainable point of view and not possible for children and elderly people. Sometimes people organize themselves and volunteer transport services are created. These services are similar to demand-oriented taxis. However, these transport services are usually independent from each other and from the available line-based public transport, limiting both their usability and sustainability. We have developed a platform to improve usability and sustainability by connecting the different demand-oriented transport offerings with the line-based public transport. The system was implemented and tested in a rural area in Germany, but the SARS-CoV-2 pandemic limited real live operation.

A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Recycling Behavior in a Multicultural Urban Area in Sweden

Alabastern, a multicultural rental housing area in the Växjö city of Sweden, was identified as poor at recycling household waste compared to other housing areas in the town. In this paper, a qualitative and quantitative analysis is conducted to understand the underlying causes of waste recycling behavior of the tenants. Results showed that majority of the studied participants perceived themselves to be environmentally friendly. They reported that they recycled household waste quite often, but it was the other tenants who did not sort their waste properly. The respondents identified the causes of the improper waste recycling as lack of attitude and awareness, limitation of communication, sense of insecurity, lack of means to transport bulky waste, limitation of the recycling room, and inadequate action by the housing company Växjöbostäder.

Platform-as-a-Service Sticky Policies for Privacy Classification in the Cloud

In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Social Influences on Americans' Mask-Wearing Behavior during COVID-19

Based on a convenience sample of 2,092 participants from across all 50 states of the United States, a survey was conducted to explore Americans’ mask-wearing behaviors during COVID-19 according to their political convictions, religious beliefs, and ethnic cultures from late July to early September, 2020. The purpose of the study is to provide evidential support for government policymaking so as to drive up more effective public policies by taking into consideration the variance in these social factors. It was found that the respondents’ party affiliation or preference, religious belief, and ethnicity, in addition to their health condition, gender, level of concern of contracting COVID-19, all affected their mask-wearing habits both in March, the initial coronavirus outbreak stage, and in August, when mask-wearing had been made mandatory by state governments. The study concludes that pandemic awareness campaigns must be run among all citizens, especially among African Americans, Muslims, and Republicans, who have the lowest rates of wearing masks, in order to protect themselves and others. It is recommended that complementary cognitive bias awareness programs should be implemented in non-Black and non-Muslim communities to eliminate social concerns that deter them from wearing masks.

Reimagining the Learning Management System as a “Third” Space

This paper focuses on a sense of belonging, isolation, and the use of a learning management system as a “third space” for connection and community. Given student use of learning management systems (LMS) for courses on campuses, moderate to high use of social media and hand-held devices, the author explores the possibilities of LMS as a third space. The COVID-19 pandemic has exacerbated student experiences of isolation, and research indicates that students who experience a sense of belonging have a greater likelihood for academic retention and success. The impacts on students of an LMS designed for student employee orientation and training were examined through a mixed methods approach, including a survey, individual interviews, and focus groups. The sample involved 250-450 undergraduate student employees at a US northwestern university. The goal of the study was to find out the efficiency and effectiveness of the orientation information for a wide range of student employees from multiple student affairs departments. And unexpected finding emerged within the study in 2015 and was noted again as a finding in the 2017 study. Students reported feeling like they individually connected to the department, and further to the university because of the LMS orientation. They stated they could see themselves as part of the university community and like they belonged. The orientation, through the LMS, was designed for and occurred online (asynchronous), prior to students traveling and beginning university life for the academic year. The students indicated connection and belonging resulting from some of the design features. With the onset of COVID-19 and prolonged sheltering in place in North America, as well as other parts of the world, students have been precluded from physically gathering to educate and learn. COVID-19 essentially paused face-to-face education in 2020. Media, governments, and higher education outlets have been reporting on widespread college student stress, isolation, loneliness, and sadness. In this context, the author conducted a current mixed methods study (online survey, online interviews) of students in advanced degree programs, like Ph.D. and Ed.D. specifically investigating isolation and sense of belonging. As a part of the study a prototype of a Canvas site was experienced by student interviewees for their reaction of this Canvas site prototype as a “third” space. Some preliminary findings of this study are presented. Doctoral students in the study affirmed the potential of LMS as a third space for community and social academic connection.

Income Inequality and the Poverty of Youth in the Douala Metropolis of Cameroon

More and more youth are doubtful of making a satisfactory labour market transition because of the present global economic instability and this is more so in Africa of the Sahara and metropolis like Douala. We use the explanatory sequential mixed method: in the first phase we randomly administered 610 questionnaires in the Douala metropolis respecting the population size of each division and its gender composition. We constructed the questionnaire using the desired values for living a comfortable life in Douala. In the second phase, we purposefully selected and interviewed 50 poor youth in order to explain in detail the initial quantitative results. We obtain the following result: The modal income class is 24,000-74,000 frs Central Africa Franc (CFA) and about 67% of the youth of the Douala metropolis earn below 75,000 frs CFA. They earn only 31.02% of the total income. About 85.7% earn below 126,000 frs CFA and about 92.14% earn below 177,000 frs CFA. The poverty-line is estimated at 177,000 frs CFA per month based on the desired predominant values in Douala and only about 9% of youth earn this sum, therefore, 91% of the youth are poor. We discovered that the salary a youth earns influences his level of poverty. Low income earners eat once or twice per day, rent low-standard houses of below 20,000 frs, are dependent and possess very limited durable goods, consult traditional doctors when they are sick, sleep and gamble during their leisure time. Intermediate income earners feed themselves either twice or thrice per day, eat healthy meals weekly, possess more durable goods, are independent, gamble and drink during their leisure time. High income earners feed themselves at least thrice per day, eat healthy food daily, inhabit high quality and expensive houses, are more stable by living longer in their neighbourhoods, like travelling and drinking during their leisure time. Unsalaried youth, are students, housewives or unemployed youth, they eat four times per day, take healthy meals daily, weekly, fortnightly or occasionally, are dependent or homeless depending on whether they are students or unemployed youth. The situation of the youth can be ameliorated through investing in the productive sector and promoting entrepreneurship as well as formalizing the informal sector.

A Case Study on Vocational Teachers’ Perceptions on Their Linguistically and Culturally Responsive Teaching

In Finland the transformation from homogenous culture into multicultural one as a result of heavy immigration has been rapid in the recent decades. As multilingualism and multiculturalism are growing features in our society, teachers in all educational levels need to be competent for encounters with students from diverse cultural backgrounds. Consequently, also the number of multicultural and multilingual vocational school students has increased which has not been taken into consideration in teacher education enough. To bridge this gap between teachers’ competences and the requirements of the contemporary school world, Finnish Ministry of Culture and Education established the DivEd-project. The aim of the project is to prepare all teachers to work in the linguistically and culturally diverse world they live in, to develop and increase culturally sustaining and linguistically responsive pedagogy in Finland, increase awareness among Teacher Educators working with preservice teachers and to increase awareness and provide specific strategies to in-service teachers. The partners in the nationwide project are 6 universities and 2 universities of applied sciences. In this research, the linguistically and culturally sustainable teaching practices developed within the DivEd-project are tested in practice. This research aims to explore vocational teachers’ perceptions of these multilingualism and multilingual educational practices. The participants of this study are vocational teachers in of different fields. The data were collected by individual, face-to-face interviews. The data analysis was conducted through content analysis. The findings indicate that the vocational teachers experience that they lack knowledge on linguistically and culturally responsive pedagogy. Moreover, they regard themselves in some extent incompetent in incorporating multilingually and multiculturally sustainable pedagogy in everyday teaching work. Therefore, they feel they need more training pertaining multicultural and multilingual knowledge, competences and suitable pedagogical methods for teaching students from diverse linguistic and cultural backgrounds.

Enhancing Temporal Extrapolation of Wind Speed Using a Hybrid Technique: A Case Study in West Coast of Denmark

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Association Rules Mining and NOSQL Oriented Document in Big Data

Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Einstein’s General Equation of the Gravitational Field

The generalization of relativistic theory of gravity based essentially on the principle of equivalence stipulates that for all bodies, the grave mass is equal to the inert mass which leads us to believe that gravitation is not a property of the bodies themselves, but of space, and the conclusion that the gravitational field must curved space-time what allows the abandonment of Minkowski space (because Minkowski space-time being nonetheless null curvature) to adopt Riemannian geometry as a mathematical framework in order to determine the curvature. Therefore the work presented in this paper begins with the evolution of the concept of gravity then tensor field which manifests by Riemannian geometry to formulate the general equation of the gravitational field.

Analysis of Cross-Sectional and Retrograde Data on the Prevalence of Marginal Gingivitis

Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values ​​according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.

Optical Signal-To-Noise Ratio Monitoring Based on Delay Tap Sampling Using Artificial Neural Network

With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

The Concept of Birthday: A Theoretical, Historical, and Social Overview, in Judaism and Other Cultures

In the age of social distance, which has been added to an individual and competitive worldview, it has become important to find a way to promote closeness and personal touch. The sense of social belonging and the existence of positive interaction with others have recently become a considerable necessity. Therefore, this theoretical paper will review one of the familiar and common concepts among different cultures around the world – birthday. This paper has a theoretical contribution that deepens the understanding of the birthday concept. Birthday rituals are historical and universal events, which noted since the prehistoric eras. In ancient history, birthday rituals were solely reserved for kings and nobility members, but over the years, birthday celebrations have evolved into a worldwide tradition. Some of the familiar birthday customs and symbols are currently common among most cultures, while some cultures have adopted for themselves unique birthday customs, which characterized their values and traditions. The birthday concept has a unique significance in Judaism as well, historically, religiously, and socially: It is considered as a lucky day and a private holiday for the celebrant. Therefore, the present paper reviews diverse birthday customs around the world in different cultures, including Judaism, and marks important birthdays throughout history. The paper also describes how the concept of birthday appears over the years in songs, novels, and art, and presents quotes from distinguished sages. The theoretical review suggests that birthday has a special meaning as a time-mark in the cycle of life, and as a socialization means in human development. Moreover, the birthday serves as a symbol of belonging and group cohesiveness, a day in which the celebrant's sense of belonging and sense of importance are strengthened and nurtured. Thus, the reappearance of these elements in a family or group interaction during the birthday ceremony allows the celebrant to absorb positive impressions about himself. In view of the extensive theoretical review, it seems that the unique importance of birthdays can serve as the foundation for intervention programs that may affect the participants’ sense of belonging and empowerment. In the group aspect, perhaps it can also yield therapeutic factors within a group. Concrete recommendations are presented at the end of the paper.

Systematic Mapping Study of Digitization and Analysis of Manufacturing Data

The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Drawings as a Methodical Access to Reconstruct Children's Perspective on a Horse-Assisted Intervention

In this article, the collection and analysis of drawings are implemented and discussed as a methodological approach to reconstruct children's perspective on horse-assisted interventions. For this purpose, drawings of three children (8-10 years old) were included in the research process in order to clarify the question of what insights can be derived from the drawings about the child's perspective on the intervention. The children were asked to draw a picture of themselves at the horse stable. Practical implementation considerations are disclosed. The developed analysis steps consider the work of two art historians (Erwin Panofsky and Max Imdahl) to capture the visual sense and to interpret the children's drawings. Relevant topics about the children's perspective can be inferred from the drawings. In the drawings, the following topics are important for the children: Overcoming challenges and fears in handling the horse, support from an adult in handling the horse and feeling self-confident and competent to act after completing tasks with the horse. The drawings show the main topics which are relevant for the children and can be used as a basis for conversation. All in all, the child's drawing offers a useful addition to other survey methods in order to gain further insights into the experiences of children in a horse-assisted setting.

Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.