Miracle-dz/UniFAR-FTUs huggingface dataset:
File Fragmentation in Mobile Devices: Measurement, Evaluation, and Treatment

Mobile devices, such as smartphones, have become a necessity in our daily life. However, users may notice that after being used for a long time, mobile devices begin to exhibit a sluggish response. Based on an empirical study on a collection of aged smartphones, this work identified that file fragmentation is among the key factors that contribute to the progressive degradation of response time. This study takes a three-step approach: First, this study designed a set of reproducible file-system aging processes based on User-Interface (UI) script replay. Through the aging processes, it confirmed that file fragmentation quickly emerged, and SQLite files were among the most severely fragmented files. Second, based on the workloads of a selection of popular mobile applications, this study observed that file fragmentation did have an impact on user-perceived latencies. Specifically, the launching time of Chrome on an aged file system was 79 percent slower than it was on a pristine file system. Third, this study evaluated existing treatments of file fragmentation, including space preallocation, persistent journal, and file defragmentation to understand their efficacies and limitations. This study also evaluated a state-of-the-art copyless defragmenter, $\mathsf{janusd}$janusd, to show its advantage over the existing methods.
Multiview-based group behavior analysis in optical image sequence

Group behavior analysis is a hot topic in intelligent video surveillance, and has attracted a surge of interest in the field of artificial intelligence. Groups are the basic components of a crowd system, and provide a high-level representation of the crowd phenomenon. By investigating the motion dynamics within each image patch, this paper proposes a multiview-based group behavior analysis method that is able to divide the paths into different groups. The main contributions are threefold: (1) the correlation between image paths is captured from four views (interaction, distance, motion direction, and motion transition), (2) a multiview clustering method with diversity regularization is proposed to perceive the complementary information within the multiview data and alleviate the influence of redundant features, and (3) a cluster merging strategy is designed to combine the highly correlated clusters and determine the final groups automatically. Experimental results on several benchmark datasets validate the good performance of the proposed method.
Folklore-Based Asynchronous Cybercounseling through Classical Guidance Format Module as The Practical Solution to Increase Children's Respect

Character building is a term to describe the children’ behavior education. It will assist them developing various good and acceptable behavior such as politeness, obedience, and respects as a holistic of a cultural life context. As the time flies, many things shift into a negative line and do not correspond to the nature of the aim of the education. Carelessness of the prevailing regulation; intolerance; bad language use; and disrespect are the form of moral shifting. Attempts to build character and minds of adolescents particularly in educational settings can be made through folklore developed in many regions in Indonesia by possessing ethics values which is beneficial for Indonesia golden generation. The use of folklore is effective to teach good ethics and moral. Cybercounseling can be defined as counselor’ creative attempts in giving professional counseling service by utilizing electronic media to communicate through the internet. Classical Guidance is called as basic service since it is the part that possesses the biggest portion of school guidance and counseling services. The classical guidance focuses on the prevention and students’ mastery of their developmental tasks so it can be in line with the guidance’ goal of ethics understanding such as respect. In this case, the use of folklore wrapped in asynchronous cybercounseling through classical guidance format module can be a practical solution in increasing students’ respect.
Heuristics for batching jobs under weighted average completion time

Heuristics for Batching Jobs Under Weighted Average Completion Time by Lewis A. Raymond Dr. Wolfgang Bein, Examination Committee Chair Associate Professor of Computer Science University of Nevada, Las Vegas Batching problems are machine scheduling problems, where a set of jobs with given processing requirements has to be scheduled on a single machine. The set of Jobs has to be partitioned into subsets to form a sequence of batches. A batch combines Jobs to run Jointly, and each Job's completion time is defined to be the completion time of the entire batch. For a batching problem, it is also assumed that when each batch is scheduled, it requires a setup time. One seeks to find a schedule that minimizes the total weighted completion time. This problem is NP-complete, but the problem can be solved efficiently in 0 {n log (n)) time if the order of the Jobs is given. This is accomplished through a non-trivial reduction to on-line matrix searching in a totally monotone array. An implementation of this algorithm is part of the thesis work. To remove the requirement of a fixed order and thus to solve the original NPcomplete batching problem, the space of permutations is searched using a genetic algorithm technique. The implementation uses a library of object-oriented functions, GAlib, to implement genetic algorithms. This highly versatile library
MB-CNN: Memristive Binary Convolutional Neural Networks for Embedded Mobile Devices

Applications of neural networks have gained significant importance in embedded mobile devices and Internet of Things (IoT) nodes. In particular, convolutional neural networks have emerged as one of the most powerful techniques in computer vision, speech recognition, and AI applications that can improve the mobile user experience. However, satisfying all power and performance requirements of such low power devices is a significant challenge. Recent work has shown that binarizing a neural network can significantly improve the memory requirements of mobile devices at the cost of minor loss in accuracy. This paper proposes MB-CNN, a memristive accelerator for binary convolutional neural networks that perform XNOR convolution in-situ novel 2R memristive data blocks to improve power, performance, and memory requirements of embedded mobile devices. The proposed accelerator achieves at least 13.26 × , 5.91 × , and 3.18 × improvements in the system energy efficiency (computed by energy × delay) over the state-of-the-art software, GPU, and PIM architectures, respectively. The solution architecture which integrates CPU, GPU and MB-CNN outperforms every other configuration in terms of system energy and execution time.
The readability of reading texts on the English textbook

Many English teacher in Indonesia use textbooks as the primary reading in their classroom. Generally, the textbooks written at a higher readability level than the grade level for which text is intended even published by the government, in this case Pusat Kurikulum dan Perbukuan, Balai Penelitian dan Pengembangan, Kementerian Pendidikam dan Kebudayaan. This research sought to explore the readability of textbook for use by Senior High School Grade XI Semester 1 student in the year 2014. The research question in this study was: What is the readability level of reading texts on the English textbook? This book used as the newest and first English textbook under Kurikulum 2013 at that time. In the study, Flesch Reading Ease Formula was chosen to analyze the reading texts. The formula were used to determine the readability level. The results show that the book were in Standard level with score 69.392. In other words, the reading texts was relatively suitable for eleventh grade students.
OPAQUE - a tool for the elicitation and grading of audioquality attributes

The evaluation of different aspects of audio quality can be realised by means of attribute scales. Studies have shown that the attributes selected are of great importance for the evaluation result. Consequently, the process whereby these attributes are generated has to be given careful consideration. It was previously shown that elements from the repertory grid technique facilitated the elicitation and grading of quality attributes, which resulted in a new audio quality evaluation method. The result from this work has now been implemented as a software prototype aimed to support listening tests. This paper reports on the results from a pilot experiment involving the OPAQUE software
Development and validation of an instrument to measure students’ perceptions of technology-enabled active learning

This article reports on the design, development, and validation of a new instrument, the Technology-Enabled Active Learning Inventory (TEAL), to measure students’ perceptions of active learning in a technology-enabled learning context. By laying the theoretical foundation, a conceptual framework for technology-enabled active learning was developed. The conceptual framework formed the basis of the instrument development process including the design, development and validation of TEAL to measure students’ perceptions of active learning in a technology-enabled learning context. The self-reporting questionnaire consisted of four scales: interactive engagement, problem-solving skills, interest and feedback. All scales were assessed on a 7-point Likert scale. The survey items were designed to measure the four aspects of technology-enabled active learning and were verified by two panels using a formalised card sorting procedure as well as confirmatory factor analysis of a small-scale (n = 61) pilot survey. The TEAL questionnaire demonstrated internal consistency. Reliability as measured by Cronbach’s coefficient alpha ranged from 0.83 to 0.88 indicating good reliability and internal consistency of the items. The resultant instrument is a valid and reliable instrument that can be used in future research to gather and represent data on students’ perceptions of active learning in a technology-enabled learning context.
Design and implementation of web-based expert tool for selection of climate resilient rapeseed-mustard varieties

Rapeseed-mustard grown area in India has been classified into five major agro-ecological zones. The basic climatic conditions targeted for developing the resource efficient varieties are rainfed and irrigated. Approximately 30% of total rapeseed-mustard cultivated area in the country is rainfed. In situations of erratic climatic conditions, it is imperative for the farmers to be well informed about the available technologies suitable for their regions. In India, rapeseed-mustard researchers have developed many improved varieties performing well in both rainfed & irrigated conditions. However, information about these varieties is scattered and in several forms. The challenge was to organize the information electronically so that the farmers of the country could be benefited from this information. For this purpose, a web based expert system for rapeseed-mustard crop variety selection was developed by applying knowledge engineering approaches with scientific knowledge base in backend. The system suggests the varieties of farmer’s/advisors’s choice based on agro-climatic conditions. The system carries detailed information about 160 notified varieties that have been stored in its knowledge base. The important feature implemented in this expert system is that it is bilingual and available in English and Hindi languages making it easily understandable by farmers of the major rapeseed-mustrad grown states.
Efficacy and safety of policosanol and pravastatin in treatment of hyperlipidemia in Chinese patients

AIM To evaluate the efficacy and safety of policosanol manufactured by Laboratorios Dalmer S.A of Cuba in the treatment of hyperlipidemia,especially hypercholesterolemia.METHODS This study was conducted as a randomized,double-blinded,double-dummy and parallel controlled trial.Patients with hyperlipi- demia were randomized into the trial group and the control group.Policosanol 10 mg.d~(-1) was administered to 1 19 patients in trial group and pravastatin 10 mg·d~(-1) was given to 119 patients in control group.The efficacy and adverse reactions were observed.RESULTS TC,LDL-C,TC-HDL-C/HDL-C,Apo B_(100,Lpa in trial group were (6.0±s 1.3),(3.5±0.8),(0.09±0.04),(2.7±0.8) mmol·L~(-1),(130±130) mg·L~(-1) after the treatment and(6.6±0.7),(4.0±0.6),(0.10±0.03),(3.3±0.5) mmol·L~(-1),(260±184)mg·L~(-1) before the treatment.Those in control group were(6.0±1.3),(3.5±0.9),(0.09±0.03),(2.8±0.8) mmol·L~(-1),(182±213)mg·L~(-1) after the treatment and(6.7±0.8),(4.1±0.7),(0.10±0.03),(3.4±0.5)mmol·L~(-1),(279±240)mg·L~(-1) before the treatment.The improvement in two groups was significant(P0.01). The policosanol was similar to pravastatin in decreasing lipidemia.There was no significant difference between two groups(P0.05). Adverse reactions(ADR)in trial group(9.2 %)were significantly lower than that in control group (18.5 %). Most of the ADR were mild and can be remitted.CONCLUSION Policosanol 10 mg·d~(-1) can significantly decrease TC,LDL-C,TC-HDL-C/HDL-C,Apo B_(100) and Lpa.The policosanol is superior to pravastatin in ADR.The ADR caused by policosanol are mild and can be well tolerated.
Spectral printing with a CMYKRGB printer: a closer look

With the advent of multi-channel technologies, printers offer more and more possibilities for spectral reproduction. In order to print a specific color sensation, there are now more degrees of freedom when it comes to combining inks (i.e. more metamerism). In this paper, we take the example of a CMYKRGB printer and propose to visualize the extent of its spectral variability (or degree of metamerism) through the analysis of so-called paramermismatch gamuts. We then evaluate the suitability of the recently proposed LabAB interim connection space in the design of look-up tables for spectral color management. We demonstrate in particular that the spectral variability of this printer is small enough to drastically reduce the number of necessary grid points needed to sample the connection space without loss of perceived quality.
Proposal of a Purchase Behavior Analysis Model on an Electronic Commerce Site Using Questionnaire Data

Due to the recent development of electronic commerce (EC) technology, sale amounts on EC sites have increased rapidly. Large amounts of consumer purchase history data can now easily be obtained, and many data-based approaches to identifying consumer purchase trends have been studied. On the other hand, since diversification of consumer consciousness such as their values and lifestyles are important for marketing research, many approaches to identifying the relationship between “consumers’ values and consciousness” and “consumers’ preferences underlying their purchase behavior” have been discussed in the existing literature. To investigate consumers’ values and consciousness, a questionnaire survey is an efficient tool. It is, however, difficult to collect questionnaire responses from all consumers due to cost issues. Therefore, it is difficult to know the values and consciousness of consumers who have not responded to the questionnaire. In this study, we propose a new model to identify both consumer purchase behavior and their consciousness based on a latent class model estimated by questionnaire responses and the purchase history data for all users. In addition, we apply the proposed model to actual data to analyze its effectiveness.
Psychological and pharmacological approaches to smoking relapse prevention

This paper reports data from two studies which examined the effects of smoking treatments combining psychological and pharmacologic treatment methods. Nicotine chewing gum (Nicorette) was used as a pharmacologic aid to help achieve nonsmoking and maintain abstinence. Aversive smoking procedures were used to produce rapid cessation. Cognitive behavioral skills training was included to help subjects develop strategies for identifying and coping with high risk episodes.
The effects of Xinnao Shutong capsule on the expressions of Angiopoietin1/Tie2 and angiogenesis after cerebral ischemia- reperfusion injury in rats

Objective To study the effects of Xinnao Shutong capsule(XNST)on the expressions of Angiopoietin(Ang)1 /Tyrosine kinase receptor( Tie)2 and angiogenesis after cerebral ischemia-reperfusion injury in rats. Methods 50 male Wistar rats were randomly divided into sham operation,model and XNST-treatment(56,28,14 mg / kg) groups. The cerebral ischemic injury was induced by middle cerebral artery occlusion( MCAO). The microvascular morphology and the volume of blood perfusion in the brain tissue were observed under lasers canning confocal microscope( LSCM),and the expression of IBZ was observed. The expressions of Ang1,Tie2 and Ang2 in the ischaemic border were detected using Western blot after 7 days of medication. Results The blood perfusion volumes in the ischemic brain cortex were promoted in middle and large dose XNST groups( P 0. 01,P 0. 05). XNST-treatment significantly increased Ang1 and Tie2 expressions in the ischaemic border compared to that of MCAO group( P 0. 01,P 0. 05). XNST also significantly increased to further investigate the signalling pathway of XNST-induced vascular stabilization and angiogenesis. Conclusions XNST up-regulates the Ang1 / Tie2 expressions,mediates vascular angiogenesis and stabilization the course of cerebral ischemia-reperfusion injury.
Inverse kinematics of asymmetric octahedral variable geometry truss manipulator with obstacle avoidance through inexact interior point optimization

This article studies the inverse kinematics for asymmetric octahedral variable geometry truss manipulator with obstacle avoidance. The inverse kinematics problem is cast as a nonconvex optimization that having quadratic objective function subject to quadratic constraints. This article uses an inexact interior point optimization to solve it, which is developed on the basis of the imprecise algorithm Ipopt. According to the particularity of our actual optimization problem, each iteration undergoes specific modifications so as to minimize the memory consumption as well as computation time. Utilizing the sparse and binary characteristics of the coefficient matrix, respectively, the algorithm allocates the computation to the finite sparse matrix vector multiplication and changes the storage form, which greatly reduces the memory space. Based on the unique rules of inverse kinematics, the iteration direction of the algorithm becomes more clear. With the aid of mechanical constraints inherent in the manipulator, the algorithm omits the feasibility recovery part that embedded in the solver Ipopt. All these make us save the operation time greatly while utilizing Ipopt algorithm. To demonstrate the effectiveness of the proposed approach, the scheme was applied to obstacle avoidance inverse kinematics of variable geometry truss manipulator with three modules.
A roadmap for (un)successful BPM: positivist case studies

Purpose While much research exists on methods and tools to support business processes, little research exists on the interrelationship with cultural and structural aspects. The purpose of this paper is to explore the chronological sequence in which culture and structure are important, as evidenced in 13 non-profit organisations that are changing towards a process-oriented way of working. Design/methodology/approach The authors use a positivist case study methodology with pattern-matching to falsify or confirm three theoretical perspectives that claim to explain the phenomena of organisational structure and culture, and their impact on business processes. The competing perspectives are: process lifecycle theories, organisational design theories and cultural and motivational theories. Findings The case studies cover six scenarios based on a recurrent sequence of changes and perceived outcome. The (theoretical and empirical) relationships between business processes, a process-oriented culture and a process-oriented structure are then combined in a process capability success model. Research limitations/implications Although limited to the non-profit sector, the findings agree that the process lifecycle is insufficient. Cultural and motivational theories prevail over organisational design theories to explain and predict process success. Practical implications From the process capability success model, a roadmap for (un)successful business process management (BPM) is derived with best practices and advice on the sequence of process improvements. Originality/value While the relevance of culture and structure has been touched in research before, the aspect of chronological sequence and pattern-matching sheds new light on the topic. The case studies performed also help to evidence how important it is to believe in process-oriented developments for organisations that want to apply BPM.
Normalized Dependency Distance: Proposing a New Measure

ABSTRACT Previous studies of dependency distance as a measure of, or a proxy for, syntactic complexity do not consider factors such as sentence length and root distance. In the present study, we propose a new algorithm, i.e. Normalized Dependency Distance (NDD), that takes sentence length and root distance into consideration. Our analysis showed that exponential distribution fit well the distribution model of NDD as it did with Mean Dependency Distance (MDD), the algorithm used in previous studies. Findings indicated that NDD is significantly less dependent on sentence length than MDD is, which suggests that the new algorithm may have, to some extent, addressed the issue of MDD’s dependency on sentence length. It is argued that NDD may serve as a measure of syntactic complexity, which is a kind of universality limited by the capacity of human working memory.
Improving the efficiency of thePre-Optimization Plan Techniques

Automated planning is an important research area of Artificial Intelligence (AI). In classical planning, which is a sub-area of automated planning, attention is given to ‘agile’ planning, i.e., solving planning problems as quickly as possible regardless of the quality of solution plans. Obtaining solutions quickly is important for real-time applications as well as in situations of imminent danger. Post-planning optimisation techniques for improving the quality of solution plans are a good option for improving poor quality plans. Since such techniques are run as post-processing, this avoids situations where there is a risk of not having solution plans in time. This thesis focuses on an important sub-area of post-planning optimisation; that is, on identifying and removing redundant actions from solution plans. In particular, this study extends the existing Action Elimination and Greedy Action Elimination algorithms by introduce two approaches to improve their efficiency. The AE and GAE algorithms are thereby developed into the UAIAE and UGAIAE systems respectively. The key to our approaches is based on optimise the process while keeping the same elimination power’ (identifying and removing the same number of redundant actions). First approach improves the algorithms by considering situations where inverse actions are redundant, while the other identifies a subset of actions that cannot be present in any redundant actions set. This subset is named justified unique actions. The study’s approach to identifying this subset has been motivated by a promising heuristic approach called ‘landmarks’, which are facts or actions that cannot be eliminated to achieve the goal. The approaches in this study have been empirically evaluated using several benchmark domains, as well as several planning engines that participated in the Agile track of the International Planning Competition 2014. In addition, they have been evaluated against state-of-the-art optimal and satisficing planners, as well as they are evaluated against a plan repair technique. The methods of AE family can be understood as polynomial methods that improve the quality of a plan by removing redundant actions, or as tools to complement more sophisticated plan optimisation techniques.