International Journal of Social and Humanistic Computing (9 papers in press)
Exploring Taiwanese smartphone user intention: An integrated model of Technology Acceptance Model and Information System Successful Model
by Ching-Hsue Cheng, Chung-Hsi Chen, You-Shyang Chen, Ho-Long Guo
Abstract: The study is focused on behavioral intentions of smartphone users, and theses are based on information system success model (ISSM) and technology acceptance model. In this study, we use SEM to examine the model that includes dimensions and relevant variables. The dimensions of model include information quality, system quality, service quality, perceived ease of use, perceived usefulness, attitude and behavioral intentions. The results indicate that there are no differences between perceived usefulness and information quality, system quality, and there is also no difference between perceived ease of use and behavioral intentions. In addition to above hypotheses the other are all supported among these hypotheses. We found the most indirect variable affect the behavioral intentions is system quality. This means that system quality is the most important factor to affect smartphone system. We also found that perceived ease of use is very important for smartphone users, and if the smartphone systems are not easy to use, they would not be accepted by people.
Keywords: Smartphone; Information system success model (ISSM); Technology acceptance model (TAM); Behavioral intention (BI).
Causal relation extraction and network construction of web events
by Qichen Ma
Abstract: The explosive increase of news data on the web has created a mass of causal knowledge, which explains the causal relation between two events that effect event will occur following the occurrence of cause event. Analysis of causal knowledge has gain lots of attentions due to its widespread applications, such as question answering, event prediction, generating future scenarios, and commonsense causal reasoning. However, few work analyzes the causal knowledge in a particular domain. Therefore, we extract causal relation and build network of causal events in food domain. First, we propose a method to obtain complete cue phrases and present four common causal patterns to extract causal relations. And then we merge the same events by similarity calculation of causal events. At last, a network of causal events is constructed. Experiments on the datasets show the effectiveness of the proposed approach.
Keywords: causality knowledge; causal relation extraction; causality network.
Context-Sensitive Smart Devices Definition and a Functional Taxonomy
by Ramnath Krishnan Pallasena, Mayank Sharma, Venkataraghavan Krishnaswamy
Abstract: Smart devices are no longer fashionable artifacts but have found mainstream adoption. Smart devices help humans by being context-sensitive, run errands or execute tasks and support their daily operations. This paper defines these context-sensitive smart devices (CSSD). We review the context and context sensitivity exhibited by mobile phones and smart devices. We further discuss the functionality of these smart devices and provide a functional taxonomy classification. This functional taxonomy could act as a framework in the design and development of CSSD. We illustrate the application of the functional taxonomy in different contexts, bringing out the characteristics, challenges, and applications in each context.
Keywords: Smart devices; Context-aware systems; Context-sensitivity; Taxonomy classification.
Image-based Human Sperm Counting Method
by Hyun-Mo Yang, Dong-Woo Lim, Yong-Sik Choi, Jin-Gu Kang, In-Hwan Kim, Ailing Lin, Jin-Woo Jung
Abstract: Modern people have a great interest in health, but most people are less interested in their sperm health than other body conditions. In this paper, we propose a method to measure the average number of sperms through a sperm image sequence captured by a smartphone with a small microscope lens so that the image acquisition could be easily performed. In order to distinguish between noise and sperm in the photographed sperm image, sperms are searched by using difference image based on the assumption that sperms are always moving. In addition, the number of detected sperms is measured and tested based on the WHO criteria. Experimental results show the effective of the proposed method.
Keywords: Sperm Count; Microscopic Image; Image Processing.
Analysis of pulse diagnosis data for the elderly by using two analytical methods
by Siyu Zhou, Zhiwei Leng, Atsushi Ogihara, Qun Jin, Shoji Nishimura
Abstract: The use of information and communication technology (ICT) to analyse pulse diagnosis data has become one of the pathways of modernising traditional Chinese medicine (TCM). In this study, we used two methods of medical statistics and machine learning to analyse diagnosis data. We used the Youden index to evaluate the authenticity of the diagnosis and the Kappa statistic to evaluate the consistency of the diagnosis made by the pulse diagnosis instrument and the TCM doctor. The accuracy of a single pulse was almost 80%. The authenticity and consistency were acceptable. The k-NN method was used to match the diagnosis results of the pulse diagnosis instrument and the TCM doctor. The overall accuracy rate was 62%, similar to that in previous studies. In practice, medical statistical methods (Youden index and Kappa statistic) are used to determine the accuracy of a single pulse, and machine learning methods (k-NN method) are used to classify pulse matching.
Keywords: pulse diagnosis; data analysis; traditional Chinese medicine; TCM; k-NN; Youden index.
The Research on the Professional Development of Information Technology Teachers Based on the Implementation of Flipped Classroom Teaching Model
by Dongmei Zhao, Xiaofan Liang
Abstract: With the rapid development of science and technology, human society has entered a new era of knowledge innovation and the cultivation of students information literacy has received increasing attention of researchers.
Keywords: basic computer courses in academy;SPOC;flipped classroom;information technology teacher;professional development studies.
Image Processing based Intelligent Robotic System for Assistance of Agricultural Crops
by Nikhil Paliwal, Pankhuri Vanjani, Jing-Wei Liu, Abhishek Sharma, Sandeep Saini
Abstract: Agriculture has been practiced in conventional ways for centuries and supported with mechanical systems in the last few decades. With the evolution of robotic equipment and sensors, the researchers are focusing on introducing smart farming. In this paper, we propose improved algorithms for infection detection in leaves and field classification targeting a heterogeneous robotic system. Image processing methods have been used on the leaves of the plants to calculate the infection percentage in crops and elementary machine learning algorithm k-means clustering for classifying the field. Classification of the agricultural field has been done for growing different types of crops in a mixed cropping technique which has an advantage over other farming procedures. Early detection of diseases can help in better preventive measures in the early stages. We have used 3150 images of crop diseases for three different types of crops and by smartly incorporating some previously established techniques. The primary objective of this paper includes the qualitative analysis of infection detection algorithms and further elaboration for the possible application of the suggested work in smart farming.
Keywords: Disease detection; Mixed Cropping; Unmanned autonomous vehicles; Computer vision; Medical robotics; Image processing; Machine Learning.
Simulation Analysis of the Wild Animal Observation System
by Lin Hui, Kuei Min Wang
Abstract: There are many animal species have extinct from the earth because of the behavior of human being, such as killing and the change of habitat environment due to climate change, contamination and pollution, etc. The close-in observation is a way for counting and identifying the animal, which is on the verge of distinction. The conven-tional way in animal observation is by vehicle/foot on land and by vessel at sea that is not only man-power consuming, but costly, ineffective and weather limited. This paper aims at using a new information technology for dolphin observation instead of man-power on board vessel. A concept of responsive action in observation operation is applied carrying out by an information-based observation system which consists of hy-drophone laid on the sea floor, camera/IR camera carried by Quadrocopter, and land control center. For verifying the effectiveness of this information-based observation system, the Monte Carlo simulation model is developed. The results showed this in-formation-based observation system is more effective than the man-power, and the concept of the search in area of uncertainty (AOU) can make a significant improvement in detecting dolphin.
Keywords: Dolphin; Hydrophone; Information-based observation system; Simulation; UAV.
A Survey on the Influence of Developer Emotions on Software Coding Productivity
by Mohammed R. Anany, Heba M.W. Hussein, Sherif G. Aly
Abstract: Software coding productivity indicators and associated influencing factors have always been topics of increased attention. Little focus was given to the understanding of the influence of contextual information, and in specific, user emotions during the software coding process. Such understanding can eventually pave the way to emotion-based mechanisms to enhance software coding productivity in stressful work environments. In this paper, we survey the major research efforts found in literature to develop an understanding of human emotions in relation to its effect on software coding productivity. To achieve this, we first highlight the main contributions for eliciting user emotions, including their properties, representation, limitations, and available APIs. We then report on our survey of the important factors that influence software coding productivity and various metrics to measure it. Our intent is to focus on productivity aspects measured over short durations of time, and not only measuring effort consumed in software coding alone. We then report on the studies that were conducted to investigate the impact of emotions on the productivity of developers. Some studies performed sentiment analysis on text, while others relied on biometric sensors to perform measurements. Most studies, however, relied on selfassessment to obtain data. Overall, the limited number of studies and the inconsistencies in the findings suggest the need for more effective ways to detect users emotions and related productivity during software development activities.
Keywords: Emotions; affects; software productivity; developer productivity; measurement; influence; survey; coding.